- Email: [email protected]
New nano-biomaterials for the removal of malachite green from aqueous solution via a response surface methodology
Accepted Manuscript New nano-biomaterials for the removal of malachite green from aqueous solution via a response surface methodology Beibei Li, Li Gan, Gary Owens, Zuliang Chen PII:
S0043-1354(18)30710-3
DOI:
10.1016/j.watres.2018.09.006
Reference:
WR 14056
To appear in:
Water Research
Received Date: 14 May 2018 Revised Date:
13 August 2018
Accepted Date: 3 September 2018
Please cite this article as: Beibei Li, Li Gan, Gary Owens, Zuliang Chen, New nano-biomaterials for the removal of malachite green from aqueous solution via a response surface methodology, Water Research (2018), doi: 10.1016/j.watres.2018.09.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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New nano-biomaterials for the removal of malachite green from
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aqueous solution via a response surface methodology.
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Beibei Li1, Li Gan1, Gary Owens2, Zuliang Chen1*
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1. School of Environmental Science and Engineering, Fujian Normal University,
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Fuzhou 350007, Fujian Province, China.
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2. Environmental Contaminants Group, Future Industries Institute, University of
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South Australia, Mawson Lakes, SA 5095, Australia.
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*Corresponding author：School of Environmental Science and Engineering, Fujian Normal University, Fuzhou 350007, Fujian Province, China; Email: [email protected]
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ACCEPTED MANUSCRIPT Abstract
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The development of new biomaterials for the remove of organic contaminants from
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wastewater has attracted much attention over the few past years. One of the most
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cost-effective approaches is to produce new high value biomaterials from low value
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solid agricultural biowastes. In this work, sugarcane bagasse and agricultural waste
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rich in reducing sugars, acted as both a green bioreductant for graphene oxide (GO)
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and a sustainable supporter for the immobilization of Burkholderia cepacia. Therefore,
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this new biomaterial which contained both reduced graphene oxide (RGO) and
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Burkholderia cepacia, was cable of initial adsorption of malachite green (MG) and its
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subsequent biodegradation. After 60 h, immobilized Burkholderia cepacia degraded
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more MG (98.5%) than a cell cultured Burkholderia cepacia (87.7%) alone. Raman
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spectroscopy confirmed that GO was successfully reduced by bagasse and that
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consequently a composite (B-RGO) was prepared. SEM indicated that Burkholderia
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cepacia was well immobilized and kinetics studies showed that the adsorption of MG
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onto the developed composite fitted a pseudo-second order kinetics model (R2 > 0.99).
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Biodegradation of MG, was confirmed by the detection of appropriate degradation
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products such as N, N-dimethylaniline and 4-(Dimethylamino) benzophenone using
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GC-MS, UV and FT-IR, and via best fit first-order biodegration kinetics. Furthermore,
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a response surface methodology (RSM) was applied to the removal process by
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varying four independent parameters using a Box-Behnken design (BBD). Optimum
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MG removal (99.3%) was achieved at 31.5 °C, with an initial MG concentration of
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114.5 mg L-1, initial pH of 5.85, and an adsorbent dosage of 0.11 g L -1. The excellent
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removal efficiency indicated that agricultural waste derived reduced graphene oxide
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bio-adsorbents have significant potential for the removal of dyes such as MG from
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industrial wastewaters.
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ACCEPTED MANUSCRIPT Keywords: Nano-biomaterials, Sugarcane bagasse, Reduced graphene oxide,
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Malachite green
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1. Introduction
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Since its discovery, due to its unique physiochemical proprieties (e.g. high
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conductivity, high intrinsic mobility, high chemical thermal stability (Allen et al.,
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2010; Li et al., 2014), and high specific surface area (Mhamane et al., 2011) graphene
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has been widely studied in many industrial applications including as biomedical,
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sensors, reinforced composites, catalysts and super-capacitors (Allen et al., 2010;
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Thakur and Karak, 2015; Xie et al., 2014). In addition, while graphene can also be
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used in the environmental remediation sectors for contaminant removal it does have
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some limitations; including acting as a secondary source of pollution; requiring some
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reprocessing after adsorption, and is also generally not effective at removing low
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concentrations of Persistent Organic Pollutants (POPs) (Badmus et al., 2018;
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Chaukura et al., 2016; Li et al., 2017b). In addition, most current methods for
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synthesizing graphene tend to be expensive and use a variety of toxic chemicals.
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Therefore, our goal was to develop a low-cost, pollution-free and environmentally
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friendly sustainable method for the preparation of nanoscale RGO sheets using a
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waste biomass to improve these current deficiencies. While biodegradation is one of
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the traditional techniques to remove organic contaminants it also has certain flaws.
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For example, planktonic microorganisms commonly used for contaminant
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biodegradation are often limited by cell growth, cell separation, and sensitivity to
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environmental factors, such as fluctuations in the influent quality and component
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concentrations of the waste streams to be treated (Gao et al., 2011). However some of
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these problems may be overcome by combining graphene adsorption and
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biodegradation technology in one novel material.
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Bagasse is a major abundant and renewable agricultural waste that has not; as yet,
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been effectively reused. Sugarcane bagasse (B), is one of the main agricultural
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bagasse, and is mainly composed of hemicellulose (25-35%), lignin (15-35%) and
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cellulose (40-45%) (Gnansounou, 2010). Some researchers have already successfully
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used bagasse (Lin et al., 2015) as an immobilization material for microorganisms.
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Extending this preliminary work, the hypothesis of this paper is that bagasse can also
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be used as both a fibrous carbon adsorbent for pollutants, as a natural reducing agent
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to produce reduced graphene oxide (RGO) and as a microbial nutrient source.
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Fabrication of such composite materials has the advantage that both adsorption and
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degradation of contaminants can be carried out simultaneously; thus overcoming
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some of the limitations experienced when applying individual adsorption and
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biodegradation in isolation. This combined approach also the significant advantage of
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also providing a feasible reuse option for a variety of solid waste resources.
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Malachite green (MG) is a triphenylmethane dye that is used extensively in the textile
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and fish farming industries as a biocide. MG is toxic to humans, affecting both the
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immune and reproductive systems (Lv et al., 2013). MG is also toxic to freshwater
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fish following either acute or chronic exposure (Lee and Kim, 2012; Saha et al., 2012).
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Therefore, to protect environmental and human health, it is critical to establish
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efficient methods to remove MG from waste streams. Bioremediation is currently the
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most commonly adopted method for dye
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microorganisms which have been reported to successfully degrade triphenylmethane
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dyes include white rot fungi, actinomycetes and algae. In contrast, there are relatively
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few reports of bacterial degradation. However, Burkholderia cepacia are a
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remediation, where the main
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nutritionally diverse bacterial organism that can grow successfully in diverse
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environments and therefore, in this paper, Burkholderia cepacia was evaluated for the
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first time for its potential to degrade MG.
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Thus, the overall goal of this study was to develop a new functional material which
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contained nanoscale RGO sheets which was produced via a simple, low-cost, and
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environmentally-friendly synthetic route and which allowed for incorporation of a
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microbiological MG dye degradation agent. Such a functionalized material would
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have several advantages. Firstly, RGO has good toughness and biocompatibility, and
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can both strengthen bagasse and provide a surface for loading of microorganisms.
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Secondly, in the long-term, even when bagasse is decomposed, dispersed RGO can
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still provide a stable platform for supporting microorganisms. Thirdly, sugarcane
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bagasse is also a natural biomass, with excellent biocompatibility and is harmless to
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the bacteria. Sugarcane bagasse is also rich in nutrients and can act as both a carbon
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and nitrogen source to support microorganisms. To our knowledge, there are no
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reports of immobilization of Burkholderia cepacia on bagasse reduced graphene
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oxide (B-RGO) for the removal of MG and this is the first report of applying this
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novel technique to the degradation of MG. Therefore, the objectives of this study
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were progressed in a series of structured steps. Firstly, the appearance and
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morphology of the sample were studied using a scanning electron microscope (SEM).
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Secondly, the degradation of malachite green products by nano-biomaterils (NBMs)
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was analyzed by ultraviolet-visible (UV), Fourier transform infrared (FT-IR) and gas
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chromatography-mass spectrometry (GC-MS). Finally, the obtained kinetic data for
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NBMs removal of MG were fit to appropriate kinetic models and response surface
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methodology was used to optimize the removal of MG by NBMs, and a mechanism
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for removal of MG by NBMs was proposed.
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2. Experimental
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2.1 Chemicals and cultures
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A graphene oxide (GO) aqueous suspension was prepared using the modified
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Hummer's method (Li et al., 2017a). Graphite powder (8000 mesh, purity 99.95%)
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and malachite green (MG, molecular weight: 364.92, purity 99.95%) were purchased
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from Aladdin Reagent Co. Ltd., Shanghai, China. Sugarcane bagasse was purchased
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locally from a market in Fuzhou, China. All other inorganic and organic chemicals
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were of analytical grade. Cell suspensions were cultured in a liquid medium (LB)
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containing (g L-1): peptone 10; yeast extract 5; NaCl 10 and the pH was adjusted to
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7.0-7.2 using mineral salts medium (MSM) solution (g L-1) prepared as follows:
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KH2PO4 1.8, Na2HPO4·12H2O 3.5, FeCl3·6H2O 0.01, MgSO4 0.1, C6H12O6 6.0,
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KNO3 3.0. Burkholderia cepacia was cultivated for 24 h at 30 °C and 150 rpm using
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LB liquid medium containing 100 mg L-1 of MG, after which time the biomass was
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collected. The resulting cell sample was then centrifuged at 4000 rpm for 10 min, the
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supernatant removed and diluted with sterile phosphate buffered solution until the
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concentration of the cell suspension reached 0.7 (AU, UV–visible at 600 nm).
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2.2 Preparation of nano-biomaterials (NBMs)
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2.2.1 Preparation of Sugarcane bagasse
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Sugarcane bagasse was initially washed with deionized water three times before
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drying at 60 °C in oven for 24 hours and grinding into a fine homogeneous powder. 6
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An aqueous solution (400 mL) containing sugarcane bagasse powder (4 g) and
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sulfuric acid (300 µL) was heated at 60 °C for 5 hours before cooling to room
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temperature and stored at 4 °C.
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2.2.2 Preparation of the sugarcane bagasse reduced graphene oxide
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(B-RGO)
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A standard procedure was used to convert GO to B-RGO (Li et al., 2018). Briefly,
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dried GO (300 mg) was dispersed in DI water (600 mL) and the solution was
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exfoliated by an ultrasonicator for 30 mins. In general the presence of hydrophilic
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functional groups at the edges and basal planes of GO makes dispersion in water
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relatively easy (Li et al., 2018). Thus, sonication led to a very fine dispersion of GO
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nanosheets. Subsequently, an aqueous solution of the sugarcane bagasse (4 g per 400
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mL) as prepared in section 2.2.1 was added to the suspension, and ammonia (600 µL)
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was added to the mixture, and then stirred for 12 h at 95 °C. In the sugarcane bagasse
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extract, fructose can be readily transformed into reducing sugars because ketoenol
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tautomerism occurs in the presence of base (i.e. the ammonia solution) (Zhu et al.,
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2010). The resultant mixture was centrifuged at 4000 rpm for 30 min and the
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precipitate collected and vacuum lyophilized for 48 hours to produce a solid material
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(B-RGO).
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2.2.3 Preparation of nano-biomaterials (NBMs)
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In brief, the B-RGO prepared in Section 2.2.2. was washed with distilled water three
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times, and dried in an oven at 105°C for 6 h, and then autoclaved at 121°C for 15 min. 7
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and the modified B-RGO particles (1.0 g) were placed into a 150 mL Erlenmeyer
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flask containing MSM (25 mL) and the mixture incubated for 24 h in a reciprocating
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shaker at 150 rpm and 30°C until all cells were adsorbed onto the B-RGO’s surface.
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2.3 Characterization and analytical methods
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Surface morphology of all NBMs was studied using a JEOL JSM-S4800 field
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emission scanning electron microscope (SEM). Raman spectra were determined on a
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Micro Raman spectrometer (LabRAM ARAMIS, Horiba Jobin-Yvon, France) using a
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laser excitation wavelength of 532 nm. During degradation experiments cultures were
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periodically sampled (withdrawn) for subsequent degradation products analysis.
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UV-Vis spectra were recorded on an UV1902 spectrometer (Phoenix, Shanghai, China)
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in the wavelength range from 190 to 800 nm at atmospheric pressure and room
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temperature. Samples suitable for Fourier transform infrared (FT-IR) spectroscopic
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analysis were pretreated by drying at 70 °C for 5 hours. FT-IR spectra were
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determined in the frequency range 4000 - 400 cm-1 using KBr pressed plates on a
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Nicolet 6700 spectrometer (Thermo Fisher Scientific, USA). Potassium bromide was
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dried at 240 °C for 12 hours, prior to combining with samples and the background
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peaks associated with any residual water and carbon dioxide were subtracted during
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the test using KBr blanks.
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To determine any potential intermediate products resulting from MG degradation,
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samples (25 mL) were centrifuged at 10,000 rpm for 15 min to remove the adsorbent 8
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triplicate. The extracts were then dried over anhydrous sodium sulfate and
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concentrated to a 1 mL for GC-MS analysis. Intermediate and degradation products of
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MG were analyzed by gas chromatography-mass spectrometry (GC-MS; Focus GC
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and DSQ II MS) using a DB-5 fused silica capillary column (30 m × 0.25 m id, 0.25
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µm). The column temperature was programmed to ramp from 100 to 280 °C at 8°C
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min-1 and to hold for 15 min at 290 °C. Carrier gas (helium) flow rate was 1 mL min-1,
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where injector and detector temperatures were 250 and 280 °C, respectively. Analysis
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of the intermediate products was carried out in electron-impact (EI) mode, 70 eV, and
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at full scan.
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2.4 Removal experiments
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NBMs degradation of MG was conducted as follows. Firstly, a 1.5% (v/v) suspension
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of cells (OD600 = 0.7) and B-RGO (0.5 g) were aseptically inoculated into a 100 mL
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Erlenmeyer flask containing MSM (50 mL) and an aqueous MG solution (100 mg L-1).
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Triplicate samples were then agitated at 150 rpm on a reciprocating shaker at 30 °C
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for 96h. In the removal experiment, the NBMs were initially washed with sterile
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water three times and subsequently again with MSM three times to remove free cells.
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Control samples consisted of MSM (50 mL) containing B (0.5 g), B-RGO (0.5 g), and
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free cells (1.5% (v/v)) in a 250 mL Erlenmeyer flask. A separate biodegradation
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experiment was conducted to assess NBMs reusability as follows: NBMs were
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washed sequentially with distilled water and MSM.
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The MG removal quantity (Q) and efficiency (E) were calculated using the following
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two equations:
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Q = (C − C ) × V/m
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W = (C − C )/C × 100%
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where Q is the adsorption capacity (mg g-1), W is the removal efficiency (%), C0 and
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Ct are respectively, the solution concentrations of MG at time zero (initial) and at time
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t (mg L-1), V is the volume of solution (L), and m is the quality of NBMs added (g).
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2.5 Removal Kinetics
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The aqueous adsorption of MG by NBMs was fit to either pseudo-first order (equation
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3) or pseudo-second order (equation 4) kinetics (Balarak et al., 2015):
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ln(Q − Q ) = lnQ − k t
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t/Q = 1/(k Q ) + t/Q
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where Qe is the amount of MG adsorbed at equilibrium (mg g-1), Qt is the amount of
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MG adsorbed at time t (mg g-1), k1 is the rate constant of the pseudo-first order
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reaction (min-1), k2 is the rate constant of the pseudo-second order reaction (g mg-1
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min-1), and t is the reaction time (min).
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The first-order kinetic model (equation 5) is often used to describe the biodegradation
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of dyes. 10
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−ln
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where c is the concentration of MG dye (mg L-1) at time t (h); k is the biodegradation
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rate constant (h-1);
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The half-life for biodegradation of MG can then be expressed as: t ⁄ =
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2.6 MG removal using response surface methodology
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Response surface methodology (RSM) experiments were designed and analyzed using
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the Design Expert software (version, 8.0.6), and Box-Behnken design (BBD). The
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experiment set comprised four factors, concentration (A), temperature (B), pH (C) and
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dosage (D), each at three levels (-1, 0, 1) (Table 1).
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Experimental data were fitted to a quadratic polynomial model to obtain optimal
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regression coefficients. The non-linear generated quadratic model used in the
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response surface was as described by equation 7(Dastkhoon et al., 2017; Kumar
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Gupta et al., 2017):
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Y = b + ∑ $& b$ x$ + ∑ $& b$$ x$ + ∑ $( b$' x$ x' + ε
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where Y is MG adsorption efficiency, b0 is the model coefficient, bi is the linear
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coefficient, bii is the quadratic coefficient, bij is the interaction coefficient, xj are the
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independent variables in coded levels, n is the number of independent variables, and ε 11
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is the model error. Analysis of variance (ANOVA) was used to assess the significance
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and adequacy of the regression model. The model’s fitness, was evaluated via
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examination of the correlation coefficient (R2) and statistical significance was
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confirmed using the F test.
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3. Results and discussion
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3.1 Characterization
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3. 1.1 SEM images
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SEM analysis revealed that the sugarcane bagasse contained porous structures which
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could provide spaces for storing substrates to metabolize microorganisms (Fig. 1a).
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Based on previous studies (Li et al., 2018), we have proven that the yellow box in Fig.
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1b marks the reduced graphene oxide (RGO). During GO reduction, since the
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reducing sugar in the sugarcane bagasse acts as both a reducing agent and a stabilizer,
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the oxygen-containing functional groups (hydroxyl, epoxy and carboxyl groups) of
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GO are effectively removed via Scheme 1. This reaction has previously been
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confirmed using various characterization techniques (Li et al., 2018). The indigo blue
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boxes in Fig. 1a and b were the aqueous solution states of bagasse and B-RGO,
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respectively. In combination with Fig. 1d, it can be proved that RGO was dispersed on
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bagasse. B-RGO clearly contained numerous porous and fold structures (Fig. 1b),
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which could both physically stengthen sugarcane bagasse and simultaneously provide
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living spaces to protect microorganisms and prevent their external environmental
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poisoning. The surface morphology of Burkholderia cepacia on the B-RGO (Fig. 1c
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and d), indicates short rod-shaped cells approximately 1 µm × 2 µm, and confirms
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that Burkholderia cepacia was successfully immobilized onto the internal and
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external walls of the large pores and folded structures of B-RGO. Compared with
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Fig.1c, after MG degradation Burkholderia cepacia (shown in Fig.1d) on the surface
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of B-RGO were poisoned by external adverse conditions, causing a morphology
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deformations.
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The efficiency of removal of MG by NBMs was faster than that of planktonic cells
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alone due to the larger specific surface area, higher adsorption capacity and
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hydrophobicity of B-RGO. Microbial immobilization has also been reported to protect
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cells from the environmental changes and toxicity of contaminants (Hsieh et al., 2008).
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Thus the stable microenvironment of the pores can protect the immobilized cells from
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adverse environmental factors (Hou et al., 2013). Bacteria attached to B-RGO
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particles were unevenly distributed, with some cells clustering and others spreading.
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We speculated that the attachment of microbial cells includes interaction between
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cells and B-RGO, and adhesion between B-RGO and the extracellular secretion of
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cells (Lin et al., 2010).
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3.1.2. Raman spectroscopy
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In Raman spectroscopy, two main characteristic peaks have been used to identify the
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structure of graphene (Akhavan et al., 2012); the D peak (close to 1350 cm-1 ) and the
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G peak (close to 1580 cm-1), As shown in Fig. 2, the Raman spectrum of GO resulted
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in a broad G peak at 1612 cm-1 corresponding to the in-phase vibration of the graphite
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oxide lattice and the D band at 1356 cm-1 .While the Raman spectrum of B-RGO is
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similar to GO, there are subtle but significant changes. The intensity ratio (ID/IG) has
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previously been used as an indicator for identifying the size of the sp2 domain carbon
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structures containing sp3 and sp2 bonds (Akhavan et al., 2012) and was applied here.
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Fig. 2 shows that the ID/IG ratio for B-RGO (1.32) which is significantly higher than
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the ID/IG ratio observed for GO (0.86), indicating that in B-RGO the graphene sheets
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are disordered and the size of the in-plane sp2 domain decreases following reduction.
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At the same time, this result confirmed that the reduction of GO led to fragmentation
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and produced many different sizes of RGO domains (Shen et al., 2012).
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3. 1.3 UV spectra
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The UV–visible spectra of MG before and after treatment with NBMs is shown in Fig.
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3. The characteristic MG peak (peak 4) at 617 nm (λmax for MG) disappeared
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gradually when incubated with Burkholderia cepacia as did the two peaks at 318 and
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425 nm. At the same time, small peaks appeared at 230 nm (peak 1) and 257 nm (peak
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2) which increased in height as incubation time increased. Simultaneously, a
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significant spectral band that likely represented a new metabolite with an absorption
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maximum at 375 nm (peak 3) emerged. Therefore, the decolorization of MG in the
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present study is attributed to degradation. Conjugated polycyclic aromatic compounds
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are known to have strong auxochromic moieties that appear at longer wavelengths
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than the band position of single-benzene derivatives. Therefore, it was speculated that
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peak 1 and peak 2 were generated by the vibrations of single-benzene ring, and that
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peak 3 was attributed to the vibrations from a conjugated polycyclic aromatic
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structure. In support of this assignment Ju et al. (Ju et al., 2009) had previously
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reported that 4-dimethylaminobenzophenone (DLBP) was one of the major products
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produced by the attack on the MG central carbon, which has a significant absorbance
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at 360 nm and is therefore likely to support the assignment of peak 3 as being due to
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DLBP.
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3. 1.4 FT-IR spectra 14
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of MG and its treatment products before and after treatment with NBMs is depicted in
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Fig. 4. The FT-IR spectra shows that following treatment with NBMs new peaks
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appeared at 3734 cm-1 associated with -OH stretching vibrations indicating the
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formation of hydroxylated metabolites, together with peaks at 3417 cm-1
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corresponding to stretching vibrations of -NH2 groups. Peaks at 1628 cm-1 and 1385
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cm-1 were attributed to -NH or -CN stretching vibrations in amine groups. In addition,
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the small peak at 1718 cm-1 was attributed to -C=O stretching of ketones. Moreover,
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new peaks at 1076 cm-1 (C-C) and 542 cm-1 (P-O-C or P-O-P) were used to infer
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bacterial secretions. Therefore, overall the results of FT-IR analysis indicated that the
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main functional groups of MG metabolites included -OH, -C=O and -NH2. However,
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while suggestive of dye gradation FT-IR is not sensitive enough to identify specific
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metabolites and thus GC analysis was undertaken.
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3. 1.5 GC-MS
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Applying an identification program from the NIST library to the GC-MS analysis of
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MG and its products after complete degradation identified three possible metabolites
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(Fig. 5). The parent peak associated with MG, eluted at 25.6 min, and gradually
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degraded into infinitesimal quantities the incubation experiment progressed. The first
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new metabolite peak eluting at 6.5 min was identified as N, N-dimethylaniline, while
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a second metabolite peak eluting at 20.9 min was identified as 4-(Dimethylamino)
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benzophenone (abbreviation: 4-DLBP). These two metabolites, detected by GC-MS,
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most likely result from the cleavage of the entire conjugated chromophore, leading to
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2003) described the detection of 4-aminobenzoic acid and N-methylaniline following
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the photocatalytic degradation of crystal violet via GC-MS analysis, signifying that
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different chemical bond-breaking dispositions due to different strategies can lead to
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the differential accumulation of compounds.
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3.2 Degradation of MG by B, B-RGO, free cells and NBMs
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The removal efficiency of MG by B-RGO was 76.1% (Fig. 6.) which was
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significantly higher than the removal efficiency of sugarcane bagasse alone (54.2%).
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This result indicated that B-RGO was more suitable for MG removal than sugarcane
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bagasse in isolation. After reacting for 60 h, the highest MG removal efficiency
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(99.3%) was achieved by NBMs, compared to only 87.7% MG degradation by free
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cells alone (Fig. 6). This indicated that the free cells were capable of effectively
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degrading MG, with more than 93.6% of MG being degraded by free cells alone
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within 96 h at pH 5.5 and 30 °C after a short adaptation period (Fig. 6). In comparison
374
to NBMs, only 82.3% of MG was removed by B-RGO and the adsorption of MG onto
375
the B-RGO reached equilibrium within 12 h (Fig. 6). This indicated that while
376
B-RGO was an effective adsorbent for removing MG from aqueous medium it was
377
not as good as NBMs alone. This was attributed to MG adsorbing onto B-RGO using
378
electrostatic interactions between MG and the surfaces of B-RGO which had a
379
constant negative charge.
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The degradation efficiency of MG using NBMs was higher than that of free cells in
382
the first 48 h, indicating that in agreement with other studies of immobilized cells for
383
the dye degradation (Cheng et al., 2012) that immobilizing cells on B-RGO
384
significantly improves MG degradation. However, in this study, B-RGO had a porous
385
folded structure, allowing both substrate and oxygen to diffuse into the internal pores
386
while retaining high mechanical strength. This consequently allowed for the B-RGO 16
ACCEPTED MANUSCRIPT component of the NBMs to increase the stability of the microbial system and maintain
388
a higher level of MG degradation compared to free cells alone. It was also evident that
389
B-RGO could alter cell physiology and increase cell membrane permeability where
390
the B-RGO and the external cells of microcolonies on the surface of B-RGO act as a
391
barrier to protect internal cells (Ha et al., 2009).
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In summary, NBMs exhibited superior MG degradation than both B-RGO and free
394
cells. During the first 12 h, the relative degradation efficiency for MG was 76 and 85%
395
for B-RGO and NBMs, respectively. It was concluded that adsorption of MG onto the
396
NBMs plays an important role during the first 12 h and that B-RGO can be practically
397
used for the adsorption of MG. The increased removal efficiency of MG using NBMs
398
compared to free cells, was attributable to the MG initially being adsorbed onto
399
B-RGO; and subsequently being degraded by Burkholderia cepacia supported by the
400
NBMs (Cheng et al., 2012).
401
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3.3 Kinetics Studies
403
3.3.1 Adsorption kinetics
404
The kinetics data for three initial MG concentrations were fit to both the first and
405
second order kinetics models and the resulting best fit parameters are summarized in
406
Table 2. Overall removal kinetics by NBMs best fit the pseudo second order model
407
(R > 0.980), which was consistently higher than the R observed for fits to the
408
pseudo first order model which were < 0.648. Additionally, the calculated Qe values
409
(21.9, 22.5, and 24.6) for the pseudo second order model were much closer to the
410
experimental data (21.7, 23.3, and 25.6) than the Qe’s obtained from fits to the pseudo
411
first order model. Consistent with a previous analysis using immobilized cells for the
412
biodegradation of highly concentrated phenolic water (Ma et al., 2013), this suggested
413
that the adsorption efficiency was more dependent on the availability of adsorption
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17
ACCEPTED MANUSCRIPT sites than on solution concentration of MG (Da Silva Lacerda et al., 2015). In this
415
study, absorption capacity increased significantly with increasing initial MG
416
concentration, while the rate constant decreased from 6.9×10-3 to 1.2×10-3 g mg-1
417
min-1. This result suggested that as the concentration of MG increased, the
418
competition for active adsorption sites also increased and the adsorption process
419
became slower (Cheng et al., 2012). Consistent with previous adsorption studies
420
(Ahmad & Kumar, 2010), as the initial MG concentration increased the value of Qe
421
rose from 21.9 to 24.6 mg·g-1 due to the increased driving force of the concentration
422
gradient.
423
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3.3.2 Biodegradation kinetics
425
Investigation of the variation in biodegradation of MG by free cells and NBMs with
426
temperature showed that the time taken to degrade MG using NBMs was quicker
427
compared to free cells (Table 3). From analysis of the kinetics data for MG
428
biodegradation it was concluded that MG degradation kinetics, by both NBMs and
429
free cells, was first-order as evidenced by the high-degree of linearity (R2>0.99)
430
obtained from a plot of -ln (C/C0) versus time. As the temperature increased from 25
431
to 35 °C, the degradation efficiency of free cells and NBMs also increased from 0.86
432
to 1.35 mg L-1 h-1 and from 1.18 to 1.31 mg L-1 h-1, respectively. However, the values
433
of the biodegradation efficiency constant k for NBMs significantly decreased
434
compared to that of free cells indicating that immobilization of Burkholderia cepacia
435
within NBMs potentially provided a better thermally stable environment during
436
storage and operation than for free cells (Wu et al., 2009).
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18
ACCEPTED MANUSCRIPT 437
A smaller half-life (t1/2) was obtained using NBMs compared to free cells at all tested
439
temperatures (Table 3), indicating that NBMs was less sensitive to changes in
440
environmental conditions such as temperature. In summary, consistent with previous
441
research (Cheng et al., 2012), comparison of the biodegradation efficiency constants
442
(k) and half-lives (t1/2) of NBMs and free cells suggested that the biodegradation of
443
MG by NBMs was much faster with a shorter half-life.
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3.4 Reusability and stability of the NBMs
446
The reusability of NBMs was investigated to confirm its practical potential through 7
447
cycles of MG removal (Fig. 7). During the first cycle the removal efficiency of MG
448
by NBMs was high at 97.7% and decreased only marginally with each cycle, so that
449
even after reusing NBMs for 7 cycles of repeated batch experiments the removal
450
efficiency was still relative high (93.6%). Thus it appears that physiological activity
451
of the immobilized cells remained almost constant and close to the original activity
452
even after the seventh cycle. This material could thus maintain a high removal
453
efficiency of more than 90% over an extended period. This suggested that B-RGO
454
was an excellent cell carrier with multiple porosity providing enough space to support
455
bacterial growth. This result conclusively demonstrated that NBMs have the potential
456
to sustainably biologically remove MG.
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3.5 Response surface methodology analysis 19
ACCEPTED MANUSCRIPT
3.5.1 Statistical analysis and analysis of variance
460
The experimental design was previously detailed in Table 1 and the of response
461
surface method analysis are shown in Table 4. Across all experimental results the MG
462
removal efficiency ranged from 0 to 99.7%. The best fit of the data to a quadratic
463
polynomial via regression analysis for the MG removal efficiency gave
464
Y = −53.79 − 0.580A + 7.540B + 2.775C + 473.550D − 0.022AB + 0.077AC +
465
2.022AD + 0.506BC + 11.964BD − 12.630CD + 3.063E − 003A − 0.136B −
466
2.255C − 3615.875D ………………………………………………………………………………………. (8)
467
Where the Y is the concentration of MG removed, A is the initial concentration, B is
468
temperature, C is the pH and D is dosage.
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469
The analysis of variance for the regression of predicted values is shown in Table 4.
471
The model F (6.45) and P (<0.0001) values indicated that the model was a sufficiently
472
good fit to explain MG removal efficiency as a function of just four system
473
parameters. In addition, the lack of fit value was 2.45E+06 (P<0.0001), which also
474
implied that the regression equation described the relationship between response
475
variables and the removal efficiency well. The F values of B (P=0.0050), D
476
(P=0.0045), BC (P=0.0056), B2 (P=0.0018), C2 (P<0.0001) and D2 (P=0.0236) were
477
statistically significant. The good fit of the regression equation (R2 = 0.986) indicated
478
that the four selected factors (concentration, temperature, pH and dosage) explained
479
98.6 % of the experimental results and hence the regression model provided a good
480
prediction of MG removal efficiency in water by NBMs. According to the model, the
481
effect of each factor on the removal of MG by NBMs decreased in the order: pH >
482
temperature > dosage > concentration. The optimum adsorption conditions were pH
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ACCEPTED MANUSCRIPT 5.85, dosage 0.11 g L-1, temperature 31.5 °C and an initial concentration 114.50 mg
484
L-1, yielding an optimal removal rate for MG of 99.3%. The results also showed that
485
the interaction between pH and temperature had the most significant effect on the
486
removal of MG by NBMs. This proves consistent with the results of ANOVA (Table
487
5).
488
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3.5.2 Effects of variable interaction on MG removal
490
The response surface and contour plots examining the relationship between variables
491
on MG removal efficiency are shown in Fig. 8. Low temperature and ionic strength
492
were not favorable for MG adsorption by NBMs (Fig. 8a). Greater amounts of MG
493
were removed when the temperature increased and the initial concentrations ranged
494
between 80 and 110 mg L-1. As shown in Fig. 8 (b), the removal of MG increased
495
considerably when the pH was < 6 and decreased considerably when the pH was > 6,
496
regardless of the concentration. Removal of MG increased with increasing NBMs
497
dosage and concentration (Fig 8c). The removal rate of MG increased considerably
498
when the pH was < 6 and decreased considerably when the pH > 6 regardless of
499
dosage (Fig. 8d). More MG was removed at pH < 6 when temperature ranged
500
between 20-35 °C (Fig. 8e), but declined with increasing pH above 6 when
501
temperature ranged from 35-40 °C. The rate of MG removal also increased as dosage
502
and temperature increased (Fig. 8f).
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4. Conclusions
505
In this study a new nano-biomaterial was successfully tested as a novel remediation
506
agent for malachite green dye. Raman spectroscopy confirmed that GO was
507
successfully reduced by bagasse and that a new product B-RGO was prepared. The 21
ACCEPTED MANUSCRIPT new material exhibited better MG degradability than that of free Burkholderia
509
cepacia cells, which was attributable to MG being initially adsorbed onto B-RGO and
510
subsequently degraded by Burkholderia cepacia immobilized in the NBMs. The
511
adsorption of MG onto the NBMs followed a pseudo-second order kinetics model (R2 >
512
0.99) which suggested that adsorption was more dependent on the availability of
513
adsorption sites on the NBMs than on the initial concentration of MG in solution.
514
Biodegradation of MG using Burkholderia cepacia immobilized on NBMs also fitted
515
well first-order reaction kinetics. SEM analysis confirmed that Burkholderia cepacia
516
was
517
N-dimethylaniline and 4-(Dimethylamino) benzophenone. The best removal
518
conditions for MG were 31.5 °C, at an initial MG concentration of 114.50 mg L-1, a
519
pH of 5.85, and a NBMs dosage of 0.11 g L-1, which removed 99.3% of MG. Thus
520
this simple, environmentally-friendly, low-cost material is promising for the
521
remediation of dyes from wastewaters.
on
NBMs.
The
main
degradation
products
were
N,
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Acknowledgements
524
This research was supported by the Major Project of Fujian Province, China [Grant
525
No: 2015YZ0001-1]; the Natural Science Foundation of Fujian Province, China
526
[Grant No: 2016J01048]; and “Shuang Chuang” Fellowship, Fujian, China.
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References
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24
ACCEPTED MANUSCRIPT Figure Captions:
623
Fig 1. SEM images of Sugarcane bagasse (a), B-RGO (b) and NBMs before and after
624
degradation of MG (c and d).
625
Fig 2. Raman spectra of graphene oxide (GO) and sugarcane bagasse reduced
626
graphene oxide (B-RGO).
627
Fig 3. UV–visible spectra of an MG-containing solution before and after treatment
628
with NBMs.
629
Fig 4. FT-IR spectra of a MG-containing solution before and after treatment by
630
NBMs.
631
Fig 5. GC-MS of MG-containing solution before and after treatment with NBMs.
632
Fig 6. Removal efficiency of MG by free cells, NBMs, B-RGO and Sugarcane
633
bagasse (B). Conditions: Concentration (MG) =100 mg L-1; pH = 5.5; temperature =
634
30 °C; rotative speed: 150 rpm.
635
Fig 7. Repeated MG removal by reusing NBMs through seven consecutive cycles.
636
Initial MG concentration: 100 mg L-1; agitation speed: 150 rpm; pH 5.5; temperature
637
30 C; reaction time 96 h.
638
Fig 8. Response surfaces for the Box-Behnken: (a) Concentration-temperature; (b)
639
pH-concentration; (c) Concentration-dosing; (d) pH-dosing; (e) pH-temperature and (f)
640
temperature-dosing.
641
Table Captions:
642
Table1. Experimental factors and their investigated levels.
643
Table 2. Kinetics parameters of pseudo first order and pseudo second order models for
AC C
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622
25
ACCEPTED MANUSCRIPT simultaneous adsorption and biodegradation of MG by NBMs.
645
Table 3. Kinetic equations of MG degradation by free cells and NBMs (Co: 100 mg
646
L-1; agitation speed: 150 rpm; pH: 5.5).
647
Table 4. Response center combination test design and results
648
Table 5. Analysis of variance (ANOVA) for the response surface quadratic model for
649
the biodegradation of MG.
650
Scheme Captions:
651
Scheme 1. Illustration of the preparation of RGO based on glucose in sugarcane
652
bagasse reduction.
SC
Figures, Tables and Schemes:
658 659 660 661 662
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657
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656
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655
M AN U
653 654
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644
663 664 665 26
ACCEPTED MANUSCRIPT 666
668
671 672 673 674
EP
670
Fig. 1
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669
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667
675 676 677 678 27
ACCEPTED MANUSCRIPT 679
681
684 685 686
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683
Fig. 2
AC C
682
TE D
M AN U
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680
687 688 689 690 28
ACCEPTED MANUSCRIPT 691
693
696 697 698 699
EP
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Fig. 3
AC C
694
TE D
M AN U
SC
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692
700 701 702 29
ACCEPTED MANUSCRIPT 703
705
708 709 710 711
EP
707
Fig. 4
AC C
706
TE D
M AN U
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704
712 713 714 715 30
ACCEPTED MANUSCRIPT 716
718
720 721
Fig. 5
AC C
719
EP
TE D
M AN U
SC
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717
722 723 724 725 31
ACCEPTED MANUSCRIPT 726
728
731 732 733 734
EP
730
Fig. 6
AC C
729
TE D
M AN U
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727
735 736 737 32
ACCEPTED MANUSCRIPT 738 739
741
743 744 745
Fig. 7
AC C
742
EP
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M AN U
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740
746 747 748 749 33
ACCEPTED MANUSCRIPT 750
752
754 755
Fig. 8
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753
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751
756 757 758 759 34
ACCEPTED MANUSCRIPT 760 761 762
Table1
Low (-1)
110
140
B: Temperature (°C)
20
30
40
C: pH
4.5
6.0
7.5
D: Dosage (g L-1)
0.05
0.10
771 772 773
EP AC C
770
TE D
766
769
0.15
M AN U
765
774 775 776
35
-α
+α
50
170
10
50
3.0
9.0
0.00
0.20
SC
80
764
768
High (+1)
A:Concentration (mg L-1)
763
767
Central (0)
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Levels Factors
ACCEPTED MANUSCRIPT 777 778
Table1 Pseudo first order Qe (mg g-1)
K1 /min-1
R
Qe (mg g-1)
K2／(g mg-1 min-1)
R
80
20.627
-4×10-5
0.648
21.978
6.878×10-3
0.980
120
16.405
-9×10-5
0. 538
22.523
2.026×10-3
0.995
140
9.876
-2×10-4
0.347
24.631
1.158×10-3
0.996
M AN U
780 781 782
787 788 789
EP
786
AC C
785
TE D
783 784
Pseudo second order
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C0 (mg L-1)
SC
779
790 791 792 793 36
ACCEPTED MANUSCRIPT 794 795
Table 3 k (h-1)
t1/2 (h)
25
0.86
0.81
0.992
30
1.13
0.61
0.994
35
1.35
0.51
0.995
25
1.18
30
1.24
NBMs
35 797 798
802 803 804 805
EP
801
AC C
800
1.31
TE D
799
SC
Free cells
806 807 808 809 37
R2
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Temperature (°C)
0.59
0.991
0.57
0.995
0.53
0.996
M AN U
796
ACCEPTED MANUSCRIPT 810 811
Table 4 C
D
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
140 80 80 80 80 110 110 140 140 110 110 110 110 170 110 80 80 140 80 110 140 140 50 140 80 110 110 140 110 110
20 40 40 20 20 30 30 40 40 30 50 30 10 30 30 40 20 20 40 30 20 20 30 40 20 30 30 40 30 30
7.5 4.5 7.5 7.5 7.5 6.0 9.0 4.5 7.5 6.0 6.0 6.0 6.0 6.0 6.0 4.5 4.5 4.5 7.5 6.0 7.5 4.5 6.0 4.5 4.5 6.0 6.0 7.5 3.0 6.0
0.05 0.15 0.15 0.15 0.05 0.00 0.10 0.15 0.05 0.10 0.10 0.10 0.10 0.10 0.10 0.05 0.05 0.15 0.05 0.10 0.15 0.05 0.10 0.05 0.15 0.20 0.10 0.15 0.10 0.10
TE D
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B
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A
MG removal efficiency (%) Observed Predicted 58.38 36.09 78.85 87.87 93.48 89.10 0.10 8.50 3.75 4.73 0.00 37.27 4.42 6.29 92.47 77.69 73.82 66.69 98.65 98.02 56.55 70.09 99.01 99.02 6.12 19.64 97.40 120.64 96.48 99.02 63.92 52.59 76.73 56.67 86.49 83.91 72.08 61.39 99.05 99.02 54.47 52.00 69.84 60.42 95.63 99.46 51.95 30.28 74.69 68.02 98.66 88.46 99.01 99.02 99.73 106.52 4.20 29.40 97.15 99.02
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Table 5
819 820 821
2.45E+06
< 0.0001
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6.45 1.91 10.81 2.27 11.13 1.92 2.16 0.42 10.45 1.62 0.16 0.59 14.24 31.99 6.35
P-value Prob > F <0.0001 0.1877 0.0050 0.1527 0.0045 0.1857 0.1625 0.5283 0.0056 0.2223 0.6925 0.4543 0.0018 < 0.0001 0.0236
F-Value
significant
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Mean Square 2277.49 672.99 3818.06 801.45 3930.37 679.51 762.17 147.20 3689.65 572.53 57.42 208.42 5027.36 11297.12 2241.35 353.15 529.73 2.17E-04 0.9864
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Model A B C D AB AC AD BC BD CD A2 B2 C2 D2 Residual Lack of Fit Pure Error Cor Total R2
Sum of Squares 31884.85 672.99 3818.06 801.45 3930.37 679.51 762.17 147.20 3689.65 572.53 57.42 208.42 5027.36 11297.12 2241.35 5297.29 5297.29 1.08E-03 37182.14
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significant
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Scheme 1
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Highlights A new nano-biomaterials (NBMs) was successfully prepared.
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NBMs were used to degrade malachite green (MG). The mechanism of NBMs removing MG was proposed.
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The best removal efficiency for MG was 99.3%.
S0043-1354(18)30710-3
DOI:
10.1016/j.watres.2018.09.006
Reference:
WR 14056
To appear in:
Water Research
Received Date: 14 May 2018 Revised Date:
13 August 2018
Accepted Date: 3 September 2018
Please cite this article as: Beibei Li, Li Gan, Gary Owens, Zuliang Chen, New nano-biomaterials for the removal of malachite green from aqueous solution via a response surface methodology, Water Research (2018), doi: 10.1016/j.watres.2018.09.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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New nano-biomaterials for the removal of malachite green from
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aqueous solution via a response surface methodology.
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Beibei Li1, Li Gan1, Gary Owens2, Zuliang Chen1*
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1. School of Environmental Science and Engineering, Fujian Normal University,
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Fuzhou 350007, Fujian Province, China.
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2. Environmental Contaminants Group, Future Industries Institute, University of
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South Australia, Mawson Lakes, SA 5095, Australia.
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*Corresponding author：School of Environmental Science and Engineering, Fujian Normal University, Fuzhou 350007, Fujian Province, China; Email: [email protected]
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ACCEPTED MANUSCRIPT Abstract
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The development of new biomaterials for the remove of organic contaminants from
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wastewater has attracted much attention over the few past years. One of the most
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cost-effective approaches is to produce new high value biomaterials from low value
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solid agricultural biowastes. In this work, sugarcane bagasse and agricultural waste
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rich in reducing sugars, acted as both a green bioreductant for graphene oxide (GO)
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and a sustainable supporter for the immobilization of Burkholderia cepacia. Therefore,
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this new biomaterial which contained both reduced graphene oxide (RGO) and
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Burkholderia cepacia, was cable of initial adsorption of malachite green (MG) and its
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subsequent biodegradation. After 60 h, immobilized Burkholderia cepacia degraded
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more MG (98.5%) than a cell cultured Burkholderia cepacia (87.7%) alone. Raman
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spectroscopy confirmed that GO was successfully reduced by bagasse and that
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consequently a composite (B-RGO) was prepared. SEM indicated that Burkholderia
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cepacia was well immobilized and kinetics studies showed that the adsorption of MG
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onto the developed composite fitted a pseudo-second order kinetics model (R2 > 0.99).
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Biodegradation of MG, was confirmed by the detection of appropriate degradation
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products such as N, N-dimethylaniline and 4-(Dimethylamino) benzophenone using
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GC-MS, UV and FT-IR, and via best fit first-order biodegration kinetics. Furthermore,
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a response surface methodology (RSM) was applied to the removal process by
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varying four independent parameters using a Box-Behnken design (BBD). Optimum
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MG removal (99.3%) was achieved at 31.5 °C, with an initial MG concentration of
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114.5 mg L-1, initial pH of 5.85, and an adsorbent dosage of 0.11 g L -1. The excellent
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removal efficiency indicated that agricultural waste derived reduced graphene oxide
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bio-adsorbents have significant potential for the removal of dyes such as MG from
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industrial wastewaters.
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ACCEPTED MANUSCRIPT Keywords: Nano-biomaterials, Sugarcane bagasse, Reduced graphene oxide,
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Malachite green
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1. Introduction
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Since its discovery, due to its unique physiochemical proprieties (e.g. high
54
conductivity, high intrinsic mobility, high chemical thermal stability (Allen et al.,
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2010; Li et al., 2014), and high specific surface area (Mhamane et al., 2011) graphene
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has been widely studied in many industrial applications including as biomedical,
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sensors, reinforced composites, catalysts and super-capacitors (Allen et al., 2010;
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Thakur and Karak, 2015; Xie et al., 2014). In addition, while graphene can also be
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used in the environmental remediation sectors for contaminant removal it does have
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some limitations; including acting as a secondary source of pollution; requiring some
61
reprocessing after adsorption, and is also generally not effective at removing low
62
concentrations of Persistent Organic Pollutants (POPs) (Badmus et al., 2018;
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Chaukura et al., 2016; Li et al., 2017b). In addition, most current methods for
64
synthesizing graphene tend to be expensive and use a variety of toxic chemicals.
65
Therefore, our goal was to develop a low-cost, pollution-free and environmentally
66
friendly sustainable method for the preparation of nanoscale RGO sheets using a
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waste biomass to improve these current deficiencies. While biodegradation is one of
68
the traditional techniques to remove organic contaminants it also has certain flaws.
69
For example, planktonic microorganisms commonly used for contaminant
70
biodegradation are often limited by cell growth, cell separation, and sensitivity to
71
environmental factors, such as fluctuations in the influent quality and component
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concentrations of the waste streams to be treated (Gao et al., 2011). However some of
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these problems may be overcome by combining graphene adsorption and
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biodegradation technology in one novel material.
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Bagasse is a major abundant and renewable agricultural waste that has not; as yet,
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been effectively reused. Sugarcane bagasse (B), is one of the main agricultural
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bagasse, and is mainly composed of hemicellulose (25-35%), lignin (15-35%) and
79
cellulose (40-45%) (Gnansounou, 2010). Some researchers have already successfully
80
used bagasse (Lin et al., 2015) as an immobilization material for microorganisms.
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Extending this preliminary work, the hypothesis of this paper is that bagasse can also
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be used as both a fibrous carbon adsorbent for pollutants, as a natural reducing agent
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to produce reduced graphene oxide (RGO) and as a microbial nutrient source.
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Fabrication of such composite materials has the advantage that both adsorption and
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degradation of contaminants can be carried out simultaneously; thus overcoming
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some of the limitations experienced when applying individual adsorption and
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biodegradation in isolation. This combined approach also the significant advantage of
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also providing a feasible reuse option for a variety of solid waste resources.
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Malachite green (MG) is a triphenylmethane dye that is used extensively in the textile
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and fish farming industries as a biocide. MG is toxic to humans, affecting both the
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immune and reproductive systems (Lv et al., 2013). MG is also toxic to freshwater
93
fish following either acute or chronic exposure (Lee and Kim, 2012; Saha et al., 2012).
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Therefore, to protect environmental and human health, it is critical to establish
95
efficient methods to remove MG from waste streams. Bioremediation is currently the
96
most commonly adopted method for dye
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microorganisms which have been reported to successfully degrade triphenylmethane
98
dyes include white rot fungi, actinomycetes and algae. In contrast, there are relatively
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few reports of bacterial degradation. However, Burkholderia cepacia are a
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remediation, where the main
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nutritionally diverse bacterial organism that can grow successfully in diverse
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environments and therefore, in this paper, Burkholderia cepacia was evaluated for the
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first time for its potential to degrade MG.
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Thus, the overall goal of this study was to develop a new functional material which
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contained nanoscale RGO sheets which was produced via a simple, low-cost, and
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environmentally-friendly synthetic route and which allowed for incorporation of a
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microbiological MG dye degradation agent. Such a functionalized material would
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have several advantages. Firstly, RGO has good toughness and biocompatibility, and
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can both strengthen bagasse and provide a surface for loading of microorganisms.
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Secondly, in the long-term, even when bagasse is decomposed, dispersed RGO can
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still provide a stable platform for supporting microorganisms. Thirdly, sugarcane
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bagasse is also a natural biomass, with excellent biocompatibility and is harmless to
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the bacteria. Sugarcane bagasse is also rich in nutrients and can act as both a carbon
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and nitrogen source to support microorganisms. To our knowledge, there are no
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reports of immobilization of Burkholderia cepacia on bagasse reduced graphene
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oxide (B-RGO) for the removal of MG and this is the first report of applying this
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novel technique to the degradation of MG. Therefore, the objectives of this study
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were progressed in a series of structured steps. Firstly, the appearance and
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morphology of the sample were studied using a scanning electron microscope (SEM).
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Secondly, the degradation of malachite green products by nano-biomaterils (NBMs)
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was analyzed by ultraviolet-visible (UV), Fourier transform infrared (FT-IR) and gas
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chromatography-mass spectrometry (GC-MS). Finally, the obtained kinetic data for
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NBMs removal of MG were fit to appropriate kinetic models and response surface
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methodology was used to optimize the removal of MG by NBMs, and a mechanism
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for removal of MG by NBMs was proposed.
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2. Experimental
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2.1 Chemicals and cultures
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A graphene oxide (GO) aqueous suspension was prepared using the modified
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Hummer's method (Li et al., 2017a). Graphite powder (8000 mesh, purity 99.95%)
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and malachite green (MG, molecular weight: 364.92, purity 99.95%) were purchased
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from Aladdin Reagent Co. Ltd., Shanghai, China. Sugarcane bagasse was purchased
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locally from a market in Fuzhou, China. All other inorganic and organic chemicals
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were of analytical grade. Cell suspensions were cultured in a liquid medium (LB)
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containing (g L-1): peptone 10; yeast extract 5; NaCl 10 and the pH was adjusted to
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7.0-7.2 using mineral salts medium (MSM) solution (g L-1) prepared as follows:
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KH2PO4 1.8, Na2HPO4·12H2O 3.5, FeCl3·6H2O 0.01, MgSO4 0.1, C6H12O6 6.0,
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KNO3 3.0. Burkholderia cepacia was cultivated for 24 h at 30 °C and 150 rpm using
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LB liquid medium containing 100 mg L-1 of MG, after which time the biomass was
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collected. The resulting cell sample was then centrifuged at 4000 rpm for 10 min, the
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supernatant removed and diluted with sterile phosphate buffered solution until the
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concentration of the cell suspension reached 0.7 (AU, UV–visible at 600 nm).
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2.2 Preparation of nano-biomaterials (NBMs)
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2.2.1 Preparation of Sugarcane bagasse
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Sugarcane bagasse was initially washed with deionized water three times before
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drying at 60 °C in oven for 24 hours and grinding into a fine homogeneous powder. 6
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An aqueous solution (400 mL) containing sugarcane bagasse powder (4 g) and
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sulfuric acid (300 µL) was heated at 60 °C for 5 hours before cooling to room
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temperature and stored at 4 °C.
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2.2.2 Preparation of the sugarcane bagasse reduced graphene oxide
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(B-RGO)
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A standard procedure was used to convert GO to B-RGO (Li et al., 2018). Briefly,
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dried GO (300 mg) was dispersed in DI water (600 mL) and the solution was
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exfoliated by an ultrasonicator for 30 mins. In general the presence of hydrophilic
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functional groups at the edges and basal planes of GO makes dispersion in water
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relatively easy (Li et al., 2018). Thus, sonication led to a very fine dispersion of GO
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nanosheets. Subsequently, an aqueous solution of the sugarcane bagasse (4 g per 400
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mL) as prepared in section 2.2.1 was added to the suspension, and ammonia (600 µL)
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was added to the mixture, and then stirred for 12 h at 95 °C. In the sugarcane bagasse
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extract, fructose can be readily transformed into reducing sugars because ketoenol
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tautomerism occurs in the presence of base (i.e. the ammonia solution) (Zhu et al.,
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2010). The resultant mixture was centrifuged at 4000 rpm for 30 min and the
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precipitate collected and vacuum lyophilized for 48 hours to produce a solid material
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(B-RGO).
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2.2.3 Preparation of nano-biomaterials (NBMs)
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In brief, the B-RGO prepared in Section 2.2.2. was washed with distilled water three
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times, and dried in an oven at 105°C for 6 h, and then autoclaved at 121°C for 15 min. 7
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and the modified B-RGO particles (1.0 g) were placed into a 150 mL Erlenmeyer
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flask containing MSM (25 mL) and the mixture incubated for 24 h in a reciprocating
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shaker at 150 rpm and 30°C until all cells were adsorbed onto the B-RGO’s surface.
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2.3 Characterization and analytical methods
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Surface morphology of all NBMs was studied using a JEOL JSM-S4800 field
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emission scanning electron microscope (SEM). Raman spectra were determined on a
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Micro Raman spectrometer (LabRAM ARAMIS, Horiba Jobin-Yvon, France) using a
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laser excitation wavelength of 532 nm. During degradation experiments cultures were
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periodically sampled (withdrawn) for subsequent degradation products analysis.
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UV-Vis spectra were recorded on an UV1902 spectrometer (Phoenix, Shanghai, China)
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in the wavelength range from 190 to 800 nm at atmospheric pressure and room
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temperature. Samples suitable for Fourier transform infrared (FT-IR) spectroscopic
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analysis were pretreated by drying at 70 °C for 5 hours. FT-IR spectra were
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determined in the frequency range 4000 - 400 cm-1 using KBr pressed plates on a
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Nicolet 6700 spectrometer (Thermo Fisher Scientific, USA). Potassium bromide was
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dried at 240 °C for 12 hours, prior to combining with samples and the background
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peaks associated with any residual water and carbon dioxide were subtracted during
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the test using KBr blanks.
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To determine any potential intermediate products resulting from MG degradation,
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samples (25 mL) were centrifuged at 10,000 rpm for 15 min to remove the adsorbent 8
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triplicate. The extracts were then dried over anhydrous sodium sulfate and
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concentrated to a 1 mL for GC-MS analysis. Intermediate and degradation products of
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MG were analyzed by gas chromatography-mass spectrometry (GC-MS; Focus GC
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and DSQ II MS) using a DB-5 fused silica capillary column (30 m × 0.25 m id, 0.25
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µm). The column temperature was programmed to ramp from 100 to 280 °C at 8°C
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min-1 and to hold for 15 min at 290 °C. Carrier gas (helium) flow rate was 1 mL min-1,
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where injector and detector temperatures were 250 and 280 °C, respectively. Analysis
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of the intermediate products was carried out in electron-impact (EI) mode, 70 eV, and
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at full scan.
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2.4 Removal experiments
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NBMs degradation of MG was conducted as follows. Firstly, a 1.5% (v/v) suspension
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of cells (OD600 = 0.7) and B-RGO (0.5 g) were aseptically inoculated into a 100 mL
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Erlenmeyer flask containing MSM (50 mL) and an aqueous MG solution (100 mg L-1).
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Triplicate samples were then agitated at 150 rpm on a reciprocating shaker at 30 °C
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for 96h. In the removal experiment, the NBMs were initially washed with sterile
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water three times and subsequently again with MSM three times to remove free cells.
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Control samples consisted of MSM (50 mL) containing B (0.5 g), B-RGO (0.5 g), and
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free cells (1.5% (v/v)) in a 250 mL Erlenmeyer flask. A separate biodegradation
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experiment was conducted to assess NBMs reusability as follows: NBMs were
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washed sequentially with distilled water and MSM.
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The MG removal quantity (Q) and efficiency (E) were calculated using the following
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two equations:
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Q = (C − C ) × V/m
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W = (C − C )/C × 100%
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where Q is the adsorption capacity (mg g-1), W is the removal efficiency (%), C0 and
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Ct are respectively, the solution concentrations of MG at time zero (initial) and at time
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t (mg L-1), V is the volume of solution (L), and m is the quality of NBMs added (g).
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2.5 Removal Kinetics
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The aqueous adsorption of MG by NBMs was fit to either pseudo-first order (equation
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3) or pseudo-second order (equation 4) kinetics (Balarak et al., 2015):
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t/Q = 1/(k Q ) + t/Q
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where Qe is the amount of MG adsorbed at equilibrium (mg g-1), Qt is the amount of
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MG adsorbed at time t (mg g-1), k1 is the rate constant of the pseudo-first order
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reaction (min-1), k2 is the rate constant of the pseudo-second order reaction (g mg-1
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min-1), and t is the reaction time (min).
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The first-order kinetic model (equation 5) is often used to describe the biodegradation
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of dyes. 10
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−ln
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where c is the concentration of MG dye (mg L-1) at time t (h); k is the biodegradation
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rate constant (h-1);
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The half-life for biodegradation of MG can then be expressed as: t ⁄ =
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2.6 MG removal using response surface methodology
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Response surface methodology (RSM) experiments were designed and analyzed using
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the Design Expert software (version, 8.0.6), and Box-Behnken design (BBD). The
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experiment set comprised four factors, concentration (A), temperature (B), pH (C) and
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dosage (D), each at three levels (-1, 0, 1) (Table 1).
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Experimental data were fitted to a quadratic polynomial model to obtain optimal
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regression coefficients. The non-linear generated quadratic model used in the
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response surface was as described by equation 7(Dastkhoon et al., 2017; Kumar
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Gupta et al., 2017):
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Y = b + ∑ $& b$ x$ + ∑ $& b$$ x$ + ∑ $( b$' x$ x' + ε
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where Y is MG adsorption efficiency, b0 is the model coefficient, bi is the linear
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coefficient, bii is the quadratic coefficient, bij is the interaction coefficient, xj are the
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independent variables in coded levels, n is the number of independent variables, and ε 11
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is the model error. Analysis of variance (ANOVA) was used to assess the significance
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and adequacy of the regression model. The model’s fitness, was evaluated via
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examination of the correlation coefficient (R2) and statistical significance was
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confirmed using the F test.
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3. Results and discussion
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3.1 Characterization
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3. 1.1 SEM images
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SEM analysis revealed that the sugarcane bagasse contained porous structures which
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could provide spaces for storing substrates to metabolize microorganisms (Fig. 1a).
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Based on previous studies (Li et al., 2018), we have proven that the yellow box in Fig.
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1b marks the reduced graphene oxide (RGO). During GO reduction, since the
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reducing sugar in the sugarcane bagasse acts as both a reducing agent and a stabilizer,
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the oxygen-containing functional groups (hydroxyl, epoxy and carboxyl groups) of
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GO are effectively removed via Scheme 1. This reaction has previously been
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confirmed using various characterization techniques (Li et al., 2018). The indigo blue
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boxes in Fig. 1a and b were the aqueous solution states of bagasse and B-RGO,
278
respectively. In combination with Fig. 1d, it can be proved that RGO was dispersed on
279
bagasse. B-RGO clearly contained numerous porous and fold structures (Fig. 1b),
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which could both physically stengthen sugarcane bagasse and simultaneously provide
281
living spaces to protect microorganisms and prevent their external environmental
282
poisoning. The surface morphology of Burkholderia cepacia on the B-RGO (Fig. 1c
283
and d), indicates short rod-shaped cells approximately 1 µm × 2 µm, and confirms
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that Burkholderia cepacia was successfully immobilized onto the internal and
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external walls of the large pores and folded structures of B-RGO. Compared with
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Fig.1c, after MG degradation Burkholderia cepacia (shown in Fig.1d) on the surface
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of B-RGO were poisoned by external adverse conditions, causing a morphology
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deformations.
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The efficiency of removal of MG by NBMs was faster than that of planktonic cells
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alone due to the larger specific surface area, higher adsorption capacity and
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hydrophobicity of B-RGO. Microbial immobilization has also been reported to protect
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cells from the environmental changes and toxicity of contaminants (Hsieh et al., 2008).
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Thus the stable microenvironment of the pores can protect the immobilized cells from
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adverse environmental factors (Hou et al., 2013). Bacteria attached to B-RGO
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particles were unevenly distributed, with some cells clustering and others spreading.
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We speculated that the attachment of microbial cells includes interaction between
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cells and B-RGO, and adhesion between B-RGO and the extracellular secretion of
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cells (Lin et al., 2010).
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3.1.2. Raman spectroscopy
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In Raman spectroscopy, two main characteristic peaks have been used to identify the
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structure of graphene (Akhavan et al., 2012); the D peak (close to 1350 cm-1 ) and the
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G peak (close to 1580 cm-1), As shown in Fig. 2, the Raman spectrum of GO resulted
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in a broad G peak at 1612 cm-1 corresponding to the in-phase vibration of the graphite
306
oxide lattice and the D band at 1356 cm-1 .While the Raman spectrum of B-RGO is
307
similar to GO, there are subtle but significant changes. The intensity ratio (ID/IG) has
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previously been used as an indicator for identifying the size of the sp2 domain carbon
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structures containing sp3 and sp2 bonds (Akhavan et al., 2012) and was applied here.
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Fig. 2 shows that the ID/IG ratio for B-RGO (1.32) which is significantly higher than
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the ID/IG ratio observed for GO (0.86), indicating that in B-RGO the graphene sheets
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are disordered and the size of the in-plane sp2 domain decreases following reduction.
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At the same time, this result confirmed that the reduction of GO led to fragmentation
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and produced many different sizes of RGO domains (Shen et al., 2012).
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3. 1.3 UV spectra
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The UV–visible spectra of MG before and after treatment with NBMs is shown in Fig.
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3. The characteristic MG peak (peak 4) at 617 nm (λmax for MG) disappeared
319
gradually when incubated with Burkholderia cepacia as did the two peaks at 318 and
320
425 nm. At the same time, small peaks appeared at 230 nm (peak 1) and 257 nm (peak
321
2) which increased in height as incubation time increased. Simultaneously, a
322
significant spectral band that likely represented a new metabolite with an absorption
323
maximum at 375 nm (peak 3) emerged. Therefore, the decolorization of MG in the
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present study is attributed to degradation. Conjugated polycyclic aromatic compounds
325
are known to have strong auxochromic moieties that appear at longer wavelengths
326
than the band position of single-benzene derivatives. Therefore, it was speculated that
327
peak 1 and peak 2 were generated by the vibrations of single-benzene ring, and that
328
peak 3 was attributed to the vibrations from a conjugated polycyclic aromatic
329
structure. In support of this assignment Ju et al. (Ju et al., 2009) had previously
330
reported that 4-dimethylaminobenzophenone (DLBP) was one of the major products
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produced by the attack on the MG central carbon, which has a significant absorbance
332
at 360 nm and is therefore likely to support the assignment of peak 3 as being due to
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DLBP.
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3. 1.4 FT-IR spectra 14
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of MG and its treatment products before and after treatment with NBMs is depicted in
338
Fig. 4. The FT-IR spectra shows that following treatment with NBMs new peaks
339
appeared at 3734 cm-1 associated with -OH stretching vibrations indicating the
340
formation of hydroxylated metabolites, together with peaks at 3417 cm-1
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corresponding to stretching vibrations of -NH2 groups. Peaks at 1628 cm-1 and 1385
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cm-1 were attributed to -NH or -CN stretching vibrations in amine groups. In addition,
343
the small peak at 1718 cm-1 was attributed to -C=O stretching of ketones. Moreover,
344
new peaks at 1076 cm-1 (C-C) and 542 cm-1 (P-O-C or P-O-P) were used to infer
345
bacterial secretions. Therefore, overall the results of FT-IR analysis indicated that the
346
main functional groups of MG metabolites included -OH, -C=O and -NH2. However,
347
while suggestive of dye gradation FT-IR is not sensitive enough to identify specific
348
metabolites and thus GC analysis was undertaken.
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3. 1.5 GC-MS
351
Applying an identification program from the NIST library to the GC-MS analysis of
352
MG and its products after complete degradation identified three possible metabolites
353
(Fig. 5). The parent peak associated with MG, eluted at 25.6 min, and gradually
354
degraded into infinitesimal quantities the incubation experiment progressed. The first
355
new metabolite peak eluting at 6.5 min was identified as N, N-dimethylaniline, while
356
a second metabolite peak eluting at 20.9 min was identified as 4-(Dimethylamino)
357
benzophenone (abbreviation: 4-DLBP). These two metabolites, detected by GC-MS,
358
most likely result from the cleavage of the entire conjugated chromophore, leading to
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ACCEPTED MANUSCRIPT aminobenzene derivatives. In comparison Saquib and Muneer (Saquib and Muneer,
360
2003) described the detection of 4-aminobenzoic acid and N-methylaniline following
361
the photocatalytic degradation of crystal violet via GC-MS analysis, signifying that
362
different chemical bond-breaking dispositions due to different strategies can lead to
363
the differential accumulation of compounds.
364
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3.2 Degradation of MG by B, B-RGO, free cells and NBMs
366
The removal efficiency of MG by B-RGO was 76.1% (Fig. 6.) which was
367
significantly higher than the removal efficiency of sugarcane bagasse alone (54.2%).
368
This result indicated that B-RGO was more suitable for MG removal than sugarcane
369
bagasse in isolation. After reacting for 60 h, the highest MG removal efficiency
370
(99.3%) was achieved by NBMs, compared to only 87.7% MG degradation by free
371
cells alone (Fig. 6). This indicated that the free cells were capable of effectively
372
degrading MG, with more than 93.6% of MG being degraded by free cells alone
373
within 96 h at pH 5.5 and 30 °C after a short adaptation period (Fig. 6). In comparison
374
to NBMs, only 82.3% of MG was removed by B-RGO and the adsorption of MG onto
375
the B-RGO reached equilibrium within 12 h (Fig. 6). This indicated that while
376
B-RGO was an effective adsorbent for removing MG from aqueous medium it was
377
not as good as NBMs alone. This was attributed to MG adsorbing onto B-RGO using
378
electrostatic interactions between MG and the surfaces of B-RGO which had a
379
constant negative charge.
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The degradation efficiency of MG using NBMs was higher than that of free cells in
382
the first 48 h, indicating that in agreement with other studies of immobilized cells for
383
the dye degradation (Cheng et al., 2012) that immobilizing cells on B-RGO
384
significantly improves MG degradation. However, in this study, B-RGO had a porous
385
folded structure, allowing both substrate and oxygen to diffuse into the internal pores
386
while retaining high mechanical strength. This consequently allowed for the B-RGO 16
ACCEPTED MANUSCRIPT component of the NBMs to increase the stability of the microbial system and maintain
388
a higher level of MG degradation compared to free cells alone. It was also evident that
389
B-RGO could alter cell physiology and increase cell membrane permeability where
390
the B-RGO and the external cells of microcolonies on the surface of B-RGO act as a
391
barrier to protect internal cells (Ha et al., 2009).
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In summary, NBMs exhibited superior MG degradation than both B-RGO and free
394
cells. During the first 12 h, the relative degradation efficiency for MG was 76 and 85%
395
for B-RGO and NBMs, respectively. It was concluded that adsorption of MG onto the
396
NBMs plays an important role during the first 12 h and that B-RGO can be practically
397
used for the adsorption of MG. The increased removal efficiency of MG using NBMs
398
compared to free cells, was attributable to the MG initially being adsorbed onto
399
B-RGO; and subsequently being degraded by Burkholderia cepacia supported by the
400
NBMs (Cheng et al., 2012).
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3.3 Kinetics Studies
403
3.3.1 Adsorption kinetics
404
The kinetics data for three initial MG concentrations were fit to both the first and
405
second order kinetics models and the resulting best fit parameters are summarized in
406
Table 2. Overall removal kinetics by NBMs best fit the pseudo second order model
407
(R > 0.980), which was consistently higher than the R observed for fits to the
408
pseudo first order model which were < 0.648. Additionally, the calculated Qe values
409
(21.9, 22.5, and 24.6) for the pseudo second order model were much closer to the
410
experimental data (21.7, 23.3, and 25.6) than the Qe’s obtained from fits to the pseudo
411
first order model. Consistent with a previous analysis using immobilized cells for the
412
biodegradation of highly concentrated phenolic water (Ma et al., 2013), this suggested
413
that the adsorption efficiency was more dependent on the availability of adsorption
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17
ACCEPTED MANUSCRIPT sites than on solution concentration of MG (Da Silva Lacerda et al., 2015). In this
415
study, absorption capacity increased significantly with increasing initial MG
416
concentration, while the rate constant decreased from 6.9×10-3 to 1.2×10-3 g mg-1
417
min-1. This result suggested that as the concentration of MG increased, the
418
competition for active adsorption sites also increased and the adsorption process
419
became slower (Cheng et al., 2012). Consistent with previous adsorption studies
420
(Ahmad & Kumar, 2010), as the initial MG concentration increased the value of Qe
421
rose from 21.9 to 24.6 mg·g-1 due to the increased driving force of the concentration
422
gradient.
423
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3.3.2 Biodegradation kinetics
425
Investigation of the variation in biodegradation of MG by free cells and NBMs with
426
temperature showed that the time taken to degrade MG using NBMs was quicker
427
compared to free cells (Table 3). From analysis of the kinetics data for MG
428
biodegradation it was concluded that MG degradation kinetics, by both NBMs and
429
free cells, was first-order as evidenced by the high-degree of linearity (R2>0.99)
430
obtained from a plot of -ln (C/C0) versus time. As the temperature increased from 25
431
to 35 °C, the degradation efficiency of free cells and NBMs also increased from 0.86
432
to 1.35 mg L-1 h-1 and from 1.18 to 1.31 mg L-1 h-1, respectively. However, the values
433
of the biodegradation efficiency constant k for NBMs significantly decreased
434
compared to that of free cells indicating that immobilization of Burkholderia cepacia
435
within NBMs potentially provided a better thermally stable environment during
436
storage and operation than for free cells (Wu et al., 2009).
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ACCEPTED MANUSCRIPT 437
A smaller half-life (t1/2) was obtained using NBMs compared to free cells at all tested
439
temperatures (Table 3), indicating that NBMs was less sensitive to changes in
440
environmental conditions such as temperature. In summary, consistent with previous
441
research (Cheng et al., 2012), comparison of the biodegradation efficiency constants
442
(k) and half-lives (t1/2) of NBMs and free cells suggested that the biodegradation of
443
MG by NBMs was much faster with a shorter half-life.
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3.4 Reusability and stability of the NBMs
446
The reusability of NBMs was investigated to confirm its practical potential through 7
447
cycles of MG removal (Fig. 7). During the first cycle the removal efficiency of MG
448
by NBMs was high at 97.7% and decreased only marginally with each cycle, so that
449
even after reusing NBMs for 7 cycles of repeated batch experiments the removal
450
efficiency was still relative high (93.6%). Thus it appears that physiological activity
451
of the immobilized cells remained almost constant and close to the original activity
452
even after the seventh cycle. This material could thus maintain a high removal
453
efficiency of more than 90% over an extended period. This suggested that B-RGO
454
was an excellent cell carrier with multiple porosity providing enough space to support
455
bacterial growth. This result conclusively demonstrated that NBMs have the potential
456
to sustainably biologically remove MG.
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3.5 Response surface methodology analysis 19
ACCEPTED MANUSCRIPT
3.5.1 Statistical analysis and analysis of variance
460
The experimental design was previously detailed in Table 1 and the of response
461
surface method analysis are shown in Table 4. Across all experimental results the MG
462
removal efficiency ranged from 0 to 99.7%. The best fit of the data to a quadratic
463
polynomial via regression analysis for the MG removal efficiency gave
464
Y = −53.79 − 0.580A + 7.540B + 2.775C + 473.550D − 0.022AB + 0.077AC +
465
2.022AD + 0.506BC + 11.964BD − 12.630CD + 3.063E − 003A − 0.136B −
466
2.255C − 3615.875D ………………………………………………………………………………………. (8)
467
Where the Y is the concentration of MG removed, A is the initial concentration, B is
468
temperature, C is the pH and D is dosage.
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469
The analysis of variance for the regression of predicted values is shown in Table 4.
471
The model F (6.45) and P (<0.0001) values indicated that the model was a sufficiently
472
good fit to explain MG removal efficiency as a function of just four system
473
parameters. In addition, the lack of fit value was 2.45E+06 (P<0.0001), which also
474
implied that the regression equation described the relationship between response
475
variables and the removal efficiency well. The F values of B (P=0.0050), D
476
(P=0.0045), BC (P=0.0056), B2 (P=0.0018), C2 (P<0.0001) and D2 (P=0.0236) were
477
statistically significant. The good fit of the regression equation (R2 = 0.986) indicated
478
that the four selected factors (concentration, temperature, pH and dosage) explained
479
98.6 % of the experimental results and hence the regression model provided a good
480
prediction of MG removal efficiency in water by NBMs. According to the model, the
481
effect of each factor on the removal of MG by NBMs decreased in the order: pH >
482
temperature > dosage > concentration. The optimum adsorption conditions were pH
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ACCEPTED MANUSCRIPT 5.85, dosage 0.11 g L-1, temperature 31.5 °C and an initial concentration 114.50 mg
484
L-1, yielding an optimal removal rate for MG of 99.3%. The results also showed that
485
the interaction between pH and temperature had the most significant effect on the
486
removal of MG by NBMs. This proves consistent with the results of ANOVA (Table
487
5).
488
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483
3.5.2 Effects of variable interaction on MG removal
490
The response surface and contour plots examining the relationship between variables
491
on MG removal efficiency are shown in Fig. 8. Low temperature and ionic strength
492
were not favorable for MG adsorption by NBMs (Fig. 8a). Greater amounts of MG
493
were removed when the temperature increased and the initial concentrations ranged
494
between 80 and 110 mg L-1. As shown in Fig. 8 (b), the removal of MG increased
495
considerably when the pH was < 6 and decreased considerably when the pH was > 6,
496
regardless of the concentration. Removal of MG increased with increasing NBMs
497
dosage and concentration (Fig 8c). The removal rate of MG increased considerably
498
when the pH was < 6 and decreased considerably when the pH > 6 regardless of
499
dosage (Fig. 8d). More MG was removed at pH < 6 when temperature ranged
500
between 20-35 °C (Fig. 8e), but declined with increasing pH above 6 when
501
temperature ranged from 35-40 °C. The rate of MG removal also increased as dosage
502
and temperature increased (Fig. 8f).
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4. Conclusions
505
In this study a new nano-biomaterial was successfully tested as a novel remediation
506
agent for malachite green dye. Raman spectroscopy confirmed that GO was
507
successfully reduced by bagasse and that a new product B-RGO was prepared. The 21
ACCEPTED MANUSCRIPT new material exhibited better MG degradability than that of free Burkholderia
509
cepacia cells, which was attributable to MG being initially adsorbed onto B-RGO and
510
subsequently degraded by Burkholderia cepacia immobilized in the NBMs. The
511
adsorption of MG onto the NBMs followed a pseudo-second order kinetics model (R2 >
512
0.99) which suggested that adsorption was more dependent on the availability of
513
adsorption sites on the NBMs than on the initial concentration of MG in solution.
514
Biodegradation of MG using Burkholderia cepacia immobilized on NBMs also fitted
515
well first-order reaction kinetics. SEM analysis confirmed that Burkholderia cepacia
516
was
517
N-dimethylaniline and 4-(Dimethylamino) benzophenone. The best removal
518
conditions for MG were 31.5 °C, at an initial MG concentration of 114.50 mg L-1, a
519
pH of 5.85, and a NBMs dosage of 0.11 g L-1, which removed 99.3% of MG. Thus
520
this simple, environmentally-friendly, low-cost material is promising for the
521
remediation of dyes from wastewaters.
on
NBMs.
The
main
degradation
products
were
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Acknowledgements
524
This research was supported by the Major Project of Fujian Province, China [Grant
525
No: 2015YZ0001-1]; the Natural Science Foundation of Fujian Province, China
526
[Grant No: 2016J01048]; and “Shuang Chuang” Fellowship, Fujian, China.
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References
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24
ACCEPTED MANUSCRIPT Figure Captions:
623
Fig 1. SEM images of Sugarcane bagasse (a), B-RGO (b) and NBMs before and after
624
degradation of MG (c and d).
625
Fig 2. Raman spectra of graphene oxide (GO) and sugarcane bagasse reduced
626
graphene oxide (B-RGO).
627
Fig 3. UV–visible spectra of an MG-containing solution before and after treatment
628
with NBMs.
629
Fig 4. FT-IR spectra of a MG-containing solution before and after treatment by
630
NBMs.
631
Fig 5. GC-MS of MG-containing solution before and after treatment with NBMs.
632
Fig 6. Removal efficiency of MG by free cells, NBMs, B-RGO and Sugarcane
633
bagasse (B). Conditions: Concentration (MG) =100 mg L-1; pH = 5.5; temperature =
634
30 °C; rotative speed: 150 rpm.
635
Fig 7. Repeated MG removal by reusing NBMs through seven consecutive cycles.
636
Initial MG concentration: 100 mg L-1; agitation speed: 150 rpm; pH 5.5; temperature
637
30 C; reaction time 96 h.
638
Fig 8. Response surfaces for the Box-Behnken: (a) Concentration-temperature; (b)
639
pH-concentration; (c) Concentration-dosing; (d) pH-dosing; (e) pH-temperature and (f)
640
temperature-dosing.
641
Table Captions:
642
Table1. Experimental factors and their investigated levels.
643
Table 2. Kinetics parameters of pseudo first order and pseudo second order models for
AC C
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25
ACCEPTED MANUSCRIPT simultaneous adsorption and biodegradation of MG by NBMs.
645
Table 3. Kinetic equations of MG degradation by free cells and NBMs (Co: 100 mg
646
L-1; agitation speed: 150 rpm; pH: 5.5).
647
Table 4. Response center combination test design and results
648
Table 5. Analysis of variance (ANOVA) for the response surface quadratic model for
649
the biodegradation of MG.
650
Scheme Captions:
651
Scheme 1. Illustration of the preparation of RGO based on glucose in sugarcane
652
bagasse reduction.
SC
Figures, Tables and Schemes:
658 659 660 661 662
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ACCEPTED MANUSCRIPT 666
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Fig. 1
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Fig. 2
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Fig. 3
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700 701 702 29
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Fig. 4
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720 721
Fig. 5
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722 723 724 725 31
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728
731 732 733 734
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Fig. 6
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ACCEPTED MANUSCRIPT 738 739
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Fig. 7
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746 747 748 749 33
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Fig. 8
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Table1
Low (-1)
110
140
B: Temperature (°C)
20
30
40
C: pH
4.5
6.0
7.5
D: Dosage (g L-1)
0.05
0.10
771 772 773
EP AC C
770
TE D
766
769
0.15
M AN U
765
774 775 776
35
-α
+α
50
170
10
50
3.0
9.0
0.00
0.20
SC
80
764
768
High (+1)
A:Concentration (mg L-1)
763
767
Central (0)
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Levels Factors
ACCEPTED MANUSCRIPT 777 778
Table1 Pseudo first order Qe (mg g-1)
K1 /min-1
R
Qe (mg g-1)
K2／(g mg-1 min-1)
R
80
20.627
-4×10-5
0.648
21.978
6.878×10-3
0.980
120
16.405
-9×10-5
0. 538
22.523
2.026×10-3
0.995
140
9.876
-2×10-4
0.347
24.631
1.158×10-3
0.996
M AN U
780 781 782
787 788 789
EP
786
AC C
785
TE D
783 784
Pseudo second order
RI PT
C0 (mg L-1)
SC
779
790 791 792 793 36
ACCEPTED MANUSCRIPT 794 795
Table 3 k (h-1)
t1/2 (h)
25
0.86
0.81
0.992
30
1.13
0.61
0.994
35
1.35
0.51
0.995
25
1.18
30
1.24
NBMs
35 797 798
802 803 804 805
EP
801
AC C
800
1.31
TE D
799
SC
Free cells
806 807 808 809 37
R2
RI PT
Temperature (°C)
0.59
0.991
0.57
0.995
0.53
0.996
M AN U
796
ACCEPTED MANUSCRIPT 810 811
Table 4 C
D
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
140 80 80 80 80 110 110 140 140 110 110 110 110 170 110 80 80 140 80 110 140 140 50 140 80 110 110 140 110 110
20 40 40 20 20 30 30 40 40 30 50 30 10 30 30 40 20 20 40 30 20 20 30 40 20 30 30 40 30 30
7.5 4.5 7.5 7.5 7.5 6.0 9.0 4.5 7.5 6.0 6.0 6.0 6.0 6.0 6.0 4.5 4.5 4.5 7.5 6.0 7.5 4.5 6.0 4.5 4.5 6.0 6.0 7.5 3.0 6.0
0.05 0.15 0.15 0.15 0.05 0.00 0.10 0.15 0.05 0.10 0.10 0.10 0.10 0.10 0.10 0.05 0.05 0.15 0.05 0.10 0.15 0.05 0.10 0.05 0.15 0.20 0.10 0.15 0.10 0.10
TE D
EP
RI PT
B
SC
A
MG removal efficiency (%) Observed Predicted 58.38 36.09 78.85 87.87 93.48 89.10 0.10 8.50 3.75 4.73 0.00 37.27 4.42 6.29 92.47 77.69 73.82 66.69 98.65 98.02 56.55 70.09 99.01 99.02 6.12 19.64 97.40 120.64 96.48 99.02 63.92 52.59 76.73 56.67 86.49 83.91 72.08 61.39 99.05 99.02 54.47 52.00 69.84 60.42 95.63 99.46 51.95 30.28 74.69 68.02 98.66 88.46 99.01 99.02 99.73 106.52 4.20 29.40 97.15 99.02
M AN U
Run
AC C
812
813 814
38
ACCEPTED MANUSCRIPT 815 816
Table 5
819 820 821
2.45E+06
< 0.0001
RI PT
6.45 1.91 10.81 2.27 11.13 1.92 2.16 0.42 10.45 1.62 0.16 0.59 14.24 31.99 6.35
P-value Prob > F <0.0001 0.1877 0.0050 0.1527 0.0045 0.1857 0.1625 0.5283 0.0056 0.2223 0.6925 0.4543 0.0018 < 0.0001 0.0236
F-Value
significant
SC
14 1 1 1 1 1 1 1 1 1 1 1 1 1 1 15 10 5 29
Mean Square 2277.49 672.99 3818.06 801.45 3930.37 679.51 762.17 147.20 3689.65 572.53 57.42 208.42 5027.36 11297.12 2241.35 353.15 529.73 2.17E-04 0.9864
AC C
818
DF
EP
Model A B C D AB AC AD BC BD CD A2 B2 C2 D2 Residual Lack of Fit Pure Error Cor Total R2
Sum of Squares 31884.85 672.99 3818.06 801.45 3930.37 679.51 762.17 147.20 3689.65 572.53 57.42 208.42 5027.36 11297.12 2241.35 5297.29 5297.29 1.08E-03 37182.14
M AN U
Source
TE D
817
822 823 824 825 39
significant
ACCEPTED MANUSCRIPT 826
Scheme 1
RI PT
827
AC C
EP
TE D
M AN U
SC
828
40
ACCEPTED MANUSCRIPT
Highlights A new nano-biomaterials (NBMs) was successfully prepared.
RI PT
NBMs were used to degrade malachite green (MG). The mechanism of NBMs removing MG was proposed.
AC C
EP
TE D
M AN U
SC
The best removal efficiency for MG was 99.3%.