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Slow settling behaviour of soil nano-particles in water and synthetic sugarcane juice solutions
Journal of Food Engineering 279 (2020) 109978
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Journal of Food Engineering journal homepage: http://www.elsevier.com/locate/jfoodeng
Slow settling behaviour of soil nano-particles in water and synthetic sugarcane juice solutions Hakan Bakir a, John A. Denman b, William O.S. Doherty a, * a b
Centre for Tropical Crops and Biocommodities, Queensland University of Technology, GPO Box 2434, Brisbane, QLD, 4001, Australia Future Industries Institute, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
A R T I C L E I N F O
A B S T R A C T
Keywords: Settling rate Flocculation Soil Sugarcane juice Clarification
Surface chemistry, morphological and physical properties of nano-particles in soils affect the settling behaviour of suspended particles in sedimentation clarifiers used in the raw sugar manufacturing process. This paper re veals subtle differences in the chemical specie compositions between soils that have good settling behaviour and those that do not using x-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spec trometry (TOF-SIMS). TOF-SIMS was further used to provide an understanding of differences between wet and dry soils that influence their settling behaviour. Differences in packing arrangements of the nano-particles in the soils and the presence of inter voids between individual particles and between microflocs, as revealed by high resolution microscopic techniques, provided evidence that the use of high density particles such as sugarcane bagasse fly ash was effective in increasing the settling rate of slow settling soils.
1. Introduction Solid-liquid separation processes are used in many industrial and chemical processes such as sugarcane, water and wastewater treatments, mining, drilling and extraction processes such as coal mining and oil sands (Doherty and Edye, 1999; Gregory, 2006; Oliveira and Rubio, 2012; Meadus et al., 1982). The raw products present in these processes all contain soil, organics and water, forming a solid-liquid suspension having particles with various sizes (Singer and Munns, 2006). Current solid-liquid separation technologies rely heavily on an initial pre-treatment process to coagulate and flocculate the suspended parti cles to form larger “floc” clusters, which are more efficiently separated (Somasundaran and Runkana, 2005). Therefore, the destabilisation of colloids (1 nm–1000 nm particle sizes) to achieve aggregation of parti cles (coagulation and flocculation) is a key governing factor in solid-liquid separation processes (Pefferkorn, 1995; Sabah and Cengiz, 2004). In the sugarcane manufacturing process, after the juice is extracted from the cane, the suspended and other impurities present in the juice are removed through a solid-liquid separation process (i.e., clarifica tion). During clarification the juice is heated and limed to form microflocs. The juice is then flashed to remove dissolved air from the juice as well as dispersed air bubbles. The juice is then flocculated by adding
anionic polyacrylamide polymer to form large macro-flocs (mud flocs) and clarified in a continuous gravity sedimentation clarifier. The mud flocs settle to the floor of the clarifier forming a mud layer, which is removed as mud underflow whilst the clarified juice flows upwards to the upper sections of the clarifier and is collected via overflow channels (Rein, 2007). The rate at which the mud flocs settle (settling velocity) is of great practical importance in solid-liquid separation processes involving the design and sizing of gravity settling clarifiers (Rein, 2007). The settling rates of mud flocs produced in Australian sugar factories typically varies between ~20 and 50 cm/min with an industry average of ~30 cm/min (Doherty et al., 2002; Steindl, 1998). If the settling rate of the mud flocs is not sufficiently faster than the bulk upward velocity of the juice then there is a risk that the mud flocs will be retained in the clarified juice stream and cause high turbidity of the juice (Rein, 2007). Under such circumstances, it is necessary to reduce the crushing rate and juice processing rate of the factory until improved clarification condi tions are restored. The slow settling mud problem is dependent on the type (e.g., clay mineral composition, clay content and morphology, organic content) and quantity of soil in the cane supply which in turn depends on a number of factors including harvesting method, growing and climatic conditions (dry or wet weather), quality of the cane crop, burnt or green cane and condition of the farm ground (Bakir et al., 2016). The quantity of soil entering the cane supply has tended to
* Corresponding author. E-mail address: [email protected] (W.O.S. Doherty). https://doi.org/10.1016/j.jfoodeng.2020.109978 Received 3 October 2019; Received in revised form 31 January 2020; Accepted 11 February 2020 Available online 14 February 2020 0260-8774/© 2020 Elsevier Ltd. All rights reserved.
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Currently, there is insufficient knowledge on how clay minerals in fluence the coagulation and flocculation mechanisms that take place during sugar cane juice clarification. Recent work by the authors was on the characterisation of soils that have different flocculation character istics, and the identification of nano-clays which impacted on the clar ification process (Bakir, 2016). The study showed that soils that impact on poor coagulation/flocculation processes (and hence settling behav iour) compared to other soils (Fig. 1) have the following features: (a) contain a lower portion of particles that have higher densities, (b) contain a higher portion of organic material and amorphous content, (c) higher specific surface area, (e) contain Si:Al ratio of 2:1 typical of montmorillonite type composition, (f) higher cation exchange capacity, and (g) higher zeta potential. Although, the study clearly demonstrated how the floc structure influenced the settling rate of the flocs, the un derlying surface chemistry of the individual particles, micro-flocs and flocs that influence and control the floc properties were not investigated, neither were strategies that should improve floc settling rate proposed. The present study uses X-ray photoelectron spectroscopy (XPS) to pro vide information on the elemental composition of the soil surface, time-of-flight secondary ion mass spectrometry (TOF-SIMS) to evaluate the functional groups of the soil surface, and scanning electron micro scopy (SEM) and transmission electron microscopy (TEM) to examine the packing arrangement of the soils, size, shape and type of mineral phases. The differences between the surface chemistry of dry and wet soils were also studied using TOF-SIMS because slow settling muds were more prevalent in sugarcane factories during the periods of wet weather. An option examined on the settling rate of the soil particles was to add sugarcane bagasse ash (fly ash) to occupy the voids in the floc network of the soil particles in order to increase the floc density and hence increase the settling rate. Because of differences in the surface chemistry of these
Fig. 1. Settling profiles of soil (1 wt%) samples. Table 1 True particle density, clay and organic content of soil samples. Standard devi ation included for true particle density and clay content. Soil
True particle density (kg/ m3)
Clay content (wt %)
Organic content (wt %)
Mt Mackay Invicta Gluepot
2508 � 2
6.83 � 2.84
8.02 � 0.80
2539 � 1 2324 � 2
9.91 � 3.05 10.80 � 1.88
4.39 � 0.40 12.93 � 0.75
increase significantly with the introduction of mechanical harvesting (Steindl, 1998; Kroes and Forsell, 1999) through the 1960’s and more recently, as a result of green cane harvesting (Moller et al., 2010; Thai and Doherty, 2011). In Australia, cane is harvested mechanically and the quantity of soil is typically ~2% by weight of the cane supply to the factory (Olson et al., 1999). This amount is steadily increasing due to a change in the cultivated area from rich alluvial flood planes to marginal soil types as a result of urban encroachment and competition from other crops. In Australian sugar factories mud filtration is almost universally undertaken using rotary vacuum filters (RVF). During the period when slow settling mud prevails there is the undesirable effect of producing light fluffy mud that is difficult to separate and wash, causing bot tlenecking at the filter station. In extreme cases a build-up of this light fluffy mud will require cane crushing to be stopped to allow processing of the high levels of mud in the factory. In Australia, the total industry cost associated with slow settling muds is estimated at ~$1 M per annum due to reduction in throughput, and the yield and quality of the product sugar. However, most of this cost is due to lost production time as a consequence of reduced throughput and/or short term production stoppages.
Fig. 2. XPS survey scan for colloidal soil particles for the Mt Mackay soil.
Table 2 Specific surface area and particle sizes of soils. Soil
Specific surface area m2/kg
D [4,3] μm
Mt Mackay Invicta Gluepot
2221 2293 2645
20.6 106.0 54.7
Volume, %
2
Dx (10) μm
Dx (50) μm
Dx (90) μm
0.875 0.840 0.819
6.30 8.04 4.19
65.2 321.0 54.3
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sugarcane is grown. The samples were labelled Mt Mackay, Invicta and Gluepot. The sample collection procedure is described in Bakir et al. (2016). The historical factory clarification performance of sugarcane juices containing these soils based on settling rate are 30–60 cm/min (good), 1–20 cm/min (poor) and 1–20 cm/min (poor) for Mt Mackay, Invicta and Gluepot respectively. The 2016 study by the authors confirmed the clarification performance of the soils. The compositions of the soils determined by X-ray powder diffraction (XRD) are Gluepot: 71.2 wt% amorphous, 11.8 wt% quartz, 4 wt% Albite, 7.9 wt% kaolinite, 1.3 wt% smectite; Invicta: 38.9 wt% amorphous, 45.1 wt% quartz, 4.9 wt% Albite, 6.4 wt% Microcline, 1.1 wt% kaolinite, 3.6 wt% muscosite; Mt Mackay: 5.3 wt% amorphous, 51.5 wt% quartz, 9.3 wt% microcline, 1.1 wt% anorthite, 26.0 wt% kaolinite, 5.0 wt% muscostite, 1.7 wt% gibbsite (Bakir et al., 2016). Fly ash samples were obtained from Isis Central Mill, Bundaberg, Queensland, Australia. Fly ash is the remaining product after bagasse is combusted (maximum temperatures of ~1000–1300 � C) in the boiler to provide energy for the running of the factory. On a dry basis, the fly ash consists of 74.2 wt% SiO2, 16.5 wt% Al2O3, 1.4 wt% P2O5, 5.5 wt% Fe2O3, 0.5 wt% K2O/Na2O 1.6 wt% CaO, 0.06 wt% MgO, 0.25 wt% others. The anionic polyacrylamide flocculants tested were the Superflocs A2115, A2120, A2125 and A2130 (Kermira, Albury, New South Wales, Australia), Sucrafloc 2310 and 2320 (TD Chemicals, Pty Ltd, Gold Coast, Queensland, Australia), and Magnafloc LT27 (Ciba, Sydney, Australia). The molecular weights of the Superflocs and LT27 are 23 � 106 and 18 � 106 respectively and for the Sucrafloc 2320 and 2310 they are 16 � 106 and 7–10 � 106 respectively.
Fig. 3. XPS survey scan for colloidal soil particles for the Invicta soil.
2.2. Methods 2.2.1. Moisture content, particle density, particle size distribution, clay fraction content, total organic carbon content of the soils The moisture content of the soils was determined by drying the samples in an oven at 65 � C for 72 h to constant weight. The values were 10.4 wt%, 2.7 wt% and 7.9 wt% for Mt Mackay, Invicta and Gluepot respectively. The true particle density of the soils was determined by the Helium Pycnometer test using an AccuPyc 1340. A 15 cm3 sample holding chamber was used and filled to ~75% full. Particle size distri butions of the soils were determined using a Malvern Mastersizer 3000 E (Malvern Instruments Ltd., United Kingdom). The clay fraction was determined by allowing a soil suspension with a known soil content to stand for a pre-calculated period using Stokes law to allow particles to settle to the extent that only the clay fraction (2 μm size) remained in suspension in the top section of the supernatant. A known volume of the clay-suspension was taken and dried. The clay fraction of the soil in the original suspension was back calculated by mass balance. The total organic matter, organic carbon and carbonate by loss on ignition were determined based on a method (6G1) in Rayment and Lyons (2011). 2.2.2. X-ray photoelectron spectroscopy X-ray photoelectron spectroscopy (XPS) is a valuable technique, which provides both qualitative and quantitative information on the surface chemistry and elemental composition of substances. Survey (i.e., wide) scans were taken with pass energy of 160 eV and multiplex (i.e., narrow) high-resolution scans were taken at 40 eV. Survey scans were carried out over a binding energy range of 1200 eV–0 eV with 1.0 eV steps and a dwell time of 100 ms. Narrow high-resolution scans were run with 0.05 eV steps and 250 ms dwell time. Base pressure was 1.0 � 10 9 Torr and 1.0 � 10 8 Torr in the analysis chamber and during the sample analysis, respectively. Peak fitting of the high-resolution data were also carried out using the CasaXPS software (Casa Software Ltd, United Kingdom).
Fig. 4. XPS survey scan for colloidal soil particles for the Gluepot soil.
soils, anionic polyacrylamide flocculants with different degrees of hy drolysis were added to see what effect they had on the settling rate of the soil particles. Therefore, the present study complements the authors’ previous work and provides additional information on issues sur rounding poor juice clarification encountered from time to time in sugarcane factories. 2. Materials and methods 2.1. Materials
2.2.3. Time of flight secondary ion mass spectrometry (TOF-SIMS) ToF-SIMS experiments were performed using a Physical Electronics
Three (3) soil samples were collected from three districts where 3
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Table 3 Binding energy values for the soils. Bond Fe 2p Fe 2p O 1s, some O*-amide N*-H2/N*-C-O K 2p3/2 K 2p1/2 C*-C C*-OH C*-O C*-OC Si 2p Al 2p
Mt Mackay
Invicta
Gluepot
Binding energy (eV)
Atomic (%)
Binding energy (eV)
Atomic (%)
Binding energy (eV)
Atomic (%)
711.935 714.560 531.941 400.080 293.307 296.184 284.800 286.409 287.694 288.877 102.798 74.467
0.143 0.034 57.790 0.778 0.343 0.180 8.225 6.061 1.707 1.478 11.130 12.130
712.342 714.677 531.941 400.234 293.498 296.282 284.800 286.731 285.847 288.902 712.342 714.677
0.678 0.174 62.430 0.462 0.936 0.419 5.375 2.293 0.876 0.768 0.678 0.174
712.427 714.983 531.931 400.164 293.548 296.309 284.800 286.172 286.958 288.928 102.831 74.5213
0.544 0.190 60.450 0.407 0.675 0.353 6.839 2.212 2.226 1.232 14.33 10.53
Fig. 5. High resolution XPS spectra for Mt Mackay soil.
Inc. PHI TRIFT V nanoTOF instrument (Physical Electronics Inc., Chanhassen, MN, USA) equipped with a pulsed liquid metal 79 þ Au primary ion gun (LMIG), operating at 30 kV energy. Dual charge
neutralisation was provided by an electron flood gun and 10eV Ar þ ions. The experiments were performed under a vacuum of 5 � 10 6Pa. “Bunched” Au1 instrumental settings were used to optimise mass 4
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Fig. 6. High resolution XPS spectra for Invicta soil.
resolution for the collection of spectra. þSIMS and -SIMS data were collected typically using a raster of ~50 � 50 μm and an acquisition time of 2 min. Sample spectra and images were processed and integrated using WincadenceN software (Physical Electronics Inc., Chanhassen, MN, USA). Surface analysis was carried out on dry loose soil samples and wet samples obtained from a suspension in Milli-Q water (18.2 MΩ cm @25 � C). The wet samples were prepared by adding soil material to Milli-Q water, sonicating for 5 min and allowing it to settle for 30 min. Ali quots were extracted from the suspension near the top of the solution. A droplet of this sample was then placed on a clean silicon wafer and the sample placed in a desiccator and pumped down to remove the liquid phase. The soil residue on the wafer was then loaded for surface analysis.
a known weight (0.5 g) was dispersed in 4 mL of Milli-Q water, sonicated for 1 min, and then allowed to settle for 5 min. A droplet was taken with a glass Pasteur pipette from the colloidal solution and placed onto an SEM stub and allowed to dry at ambient temperature. For the TEM study, the droplet was placed onto a carbon film prior to drying at 45 � C in an oven overnight. 2.2.5. Preparation of flocculant solution A 100 mL stock flocculant solution at 0.2 wt% was prepared by dispersing and dissolving flocculant powder (0.2 g) in Milli-Q water using a stirrer with a 45� pitch four blade turbine impeller of 50 mm diameter running at 50 r/min for ~4 h. The powder was added slowly and carefully during mixing to ensure that each flocculant granule is wetted to prevent agglomeration and the formation of ‘oysters’. The stock solution was stored in the fridge at ~4 � C. The effective life of a 0.2 wt% stock solution stored at ~4 � C is approximately two weeks. On the day of the tests the stock flocculant solution was used to prepare a 100 mL flocculant solution at either 0.01 wt% or 0.04 wt%.
2.2.4. Packing arrangements of the soils Investigations were conducted using JEOL-2100 Transmission Elec tron Microscope (TEM) (JEOL Ltd., Japan) with 200 kV accelerating potential and JEOL-6040 Scanning Electron Microscope (SEM) (JEOL Ltd., Japan) in accelerating voltage 15–20 kV. For SEM investigation samples were coated with platinum film few nm thick. For this analysis, 5
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Fig. 7. High resolution XPS spectra for Gluepot soil.
2.2.6. Stock synthetic juice solution (Electrolyte) Chemicals, CaCl2⋅2H2O (Chem Supply, Gillman, Australia), MgCl2⋅6H2O (Merck, Kilsyth, Australia), NaCl and KCl (Sigma- Aldrich, Sydney, Australia) were analytical grade. The stock synthetic juice solution was prepared by dissolving 1.91 g of NaCl, 47.67 g of KCl, 18.34 g of CaCl2⋅2H2O and 31.37 g of MgCl2⋅6H2O in 1000 mL of Milli-Q water. For each test, a 4 mL aliquot of the stock solution was added to the soil/Milli-Q water suspensions to produce a synthetic juice with an electrolyte composition of 30 ppm Naþ (as NaCl), 1000 ppm Kþ (as KCl), 200 ppm Ca2þ (as CaCl2⋅H2O), 150 ppm Mg2þ (MgCl2⋅6H2O). The pH of the solutions ranged between 4.67 and 5.93 and the value depended on the soil type.
was added to the mixture to give a volume of 100 mL and the whole stirred for 1 min. A flocculant dose to give 1 ppm in the 100 mL solution was added to the mixture in a single dose and stirred for a further 1 min. The flocculated suspension was then transferred into a 100 mL glass cylinder, inverted 10 times and left standing for sedimentation to occur. The mud interface heights were recorded over a 30 min period. The height of glass cylinder at the 100 mL graduation (~195 mm) was used to determine the settling rates over the first 5 min of sedimentation. The average error in the measurements is �0.25%. The turbidity of the su pernatant was determined by measuring its light absorbance at a wavelength of 900 nm and multiplying by 100. 2.2.8. Addition of ash aggregates The bagasse fly ash were flocculated to form ash aggregates. A known amount of bagasse fly (10 g) was added to 1 L of MilliQ water and stirred for 1 min. A 1 ppm flocculant LT 27 was added to floc the ash particles, and the glass cylinder was then inverted 10 times and left standing for 3 min. The flocculated particles were collected on a Whatman No 52 filter paper. Particle size distribution of the flocculated particles were determined using a Malvern Mastersizer 3000 E (Malvern
2.2.7. Batch settling tests using electrolyte with flocculants One (1) g of soil was weighed into 20 mL jar, which were then filled with Milli-Q water and sonicated in a water bath for 5 min to completely break down aggregates. After sonication, the mixture transferred into a glass beaker pre-filled with 76 mL of Milli-Q water. The mixture was stirred using a magnetic stirrer (~300 r/min) and a 5 cm stirrer bar for 1 min. Approximately 4 mL aliquot of the stock synthetic juice solution 6
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Fig. 8. PCA score plot of Mt Mackay samples obtained by TOF-SIMS.
Fig. 9. PCA loading of chemical species present in Mt Mackay samples obtained by TOF-SIMS.
Instruments Ltd., United Kingdom). For the clarification test, a known amount of the aggregated ash particles was then added to the soil so lution, as described in the batch settling tests. The total mass of soil/ash mixture was maintained at 1.000 g. The experiments were done in duplicate.
2.2.9. Statistical analysis of data Moisture, particle density, particle size, clay, and total organic car bon contents of the soils were analysed in duplicate and the mean value recorded. The error in the surface properties of the soils analysed by XPS was <5% and the standard deviation for elemental analysis of surface of the soils by XPS was <10%. 7
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Fig. 10. PCA score plot of Gluepot samples obtained by TOF-SIMS.
Fig. 11. PCA loading of chemicals species present in Gluepot samples obtained by TOF-SIMS.
The data from the TOF-SIMS of the soils was analysed by Principal component analysis (PCA). It was used to help highlight and identify variation in the data set, and hence differences between samples. PCA is primarily concerned with reducing the multiple dimensionality of a data set in which there are many related variables, while still retaining as much of the variation as possible in the data set. It does this by trans forming the data to a set of values of linearly uncorrelated variables
called principal components, which are ordered in terms of their vari ance, i.e., the first few contain most of the variation in the data that is present in all of the original variables. The lack of correlation is important as it indicates that the components are measuring or repre senting different aspects in the data. The inorganic data was statistically treated using the Student’s T-test. The error bars indicate the 95% confidence interval based on the mean value. 8
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basis, expected to have the fastest settling rate. These physical properties of the soil support the evidence provided by Bakir et al. (2016) that Mt Mackay is a ‘good’ soil exhibiting good settling properties while Gluepot is a ‘bad’ soil exhibiting poor settling properties. The results are not clear cut with the Invicta sample, though the clay content, which is higher than that obtained with the Mt Mackay sample, points to it being a ‘bad soil’. 3.2. Surface chemistry by x-ray photoelectron spectroscopy (XPS) The surface chemistry of the particles affects the way they coagulate and flocculate. Figs. 2–4 show the XPS survey scans for the colloidal portion of the Mt Mackay, Invicta and Gluepot soil samples, respec tively. The scans show that there are relatively higher quantities of O, C, Si and Al compared to Fe, N, Ca and K in these samples. The Si:Al ratio indicates the type of mineral present in the soils (Shainberg and Levy, 2005). The Si:Al ratio is 1:1 for the Mt Mackay sample indicating a clay mineral of kaolinite type, while the Si:Al ratio for the other two soils indicate a mixture of the 1:1 and 2:1 mineral types. The 2:1 mineral is of the montmorillonite type, known expandable clay (Barton and Kar athanasis, 2002). Expandable clays have the ability to absorb water (Karpinski and Szkodo, 2015), which would reduce their bulk density and hence their settling rates. As the ratio of Si:Al for both the Invicta and Gluepot samples, the 2:1 mineral is expected to be present in these samples, thereby supporting the poor settling behaviour of these samples. The amount of Ca is lowest in the Mt Mackay sample. This supports the loss on ignition data at 950 � C (which is related to Ca organics) where values of 0.43 wt%, 0.56 wt% and 0.83 wt% for Mt Mackay, Invicta and Gluepot, respectively. Iron is also shown to be the lowest with Mt Mackay, and so these elements may be present, at least in part, in their non-ionisable forms, as their ions enhance coagulation, though the overriding behaviour of the soils are likely to be dependent on other factors previously mentioned. Hydrolysable cations such as Al3þ can be highly effective in dispersion destabilisation, and in addition to cause double-layer compression and can reverse the zeta potential (Tripathy and De, 2006). These species can also promote aggregation by modi fying dispersed particles properties through surface precipitation of colloidal hydroxides. The XPS data show that the Mt Mackay sample has significantly the highest Al content than the two other samples, which is mainly because of the 1:1 mineral present, and so it is speculated that aluminium hydroxide species are formed. To determine the chemical states associated with the C, O, N, Si and Al peaks, a high resolution scan was obtained for the samples (Table 3 and Figs. 5–7). The high resolution XPS spectra of the C 1s electrons clearly indicate four chemically shifted C 1s peaks, of different chemical environments. The XPS analysis of the soil samples reveal the presence of hydrocarbons (C*-C), alcohol (C*-OH), carbonyl (C*-O) and organic ethers (C*-OC). These carbon functional groups suggest the presence of polysaccharides and organic acid compounds. The amide functional group indicates the presence of proteins, and that the surfaces are negatively charged due to the ionisation of the carboxyl and amino groups to give COO and NHþ 4 ions (Miflin, 2014). It should be noted, however, that no carboxylate ion was detected from the binding energy results, perhaps indicating that at the pH the samples were analysed was not sufficient for this to occur. As shown in Table 3, the proportions of the organic and also inor ganic compounds are different among the three samples. The pro portions of hydrocarbon and alcohol species are highest in the Mt Mackay samples, while the proportion of the carbonyl group is highest in the Gluepot sample. It is probable that alcohol species may well participate in hydrogen bonding enhancing polymer-particle interaction.
Fig. 12. Distribution of inorganic ions and total organics on the surfaces of Mt Mackay particles obtained by TOF-SIMS.
Fig. 13. Distribution of inorganic ions and total organics on the surfaces of Gluepot particles obtained by TOF-SIMS.
3. Results and discussion 3.1. Physical properties of the soils The true particle density is most relevant in relation to settling rates of flocs formed from soil suspensions. Because soils are typically made up of varying quantities of silicates, organics and metal oxides, the true particle density that is measured represent the average true particle density of all the components that make up the soil. The true particle densities of the soil samples are shown in Table 1 and indicate that the particle densities vary between 2320 and ~2540 kg/m3. Gluepot has the lowest particle density at 2320 kg/m3 and Invicta has the highest par ticle density at 2540 kg/m3. These values are less than most soils which typically have values of 2650 kg/m3 because of relatively higher pro portion of quartz present (Schjonning et al., 2017). On the basis of the true particle density, the Invicta sample should have the fastest settling rate, or at least comparable with the soil sample for Mt Mackay. However, Mt Mackay soil sample has the lowest clay content, than either the soil from Invicta or Gluepot. In the previous work by the authors (Bakir et al., 2016), Mt Mackay soil has the fastest settling rate, so from the result of Table 1, the clay content influences the settling rate of the particles the most. Further evidence of the clay par ticles playing a significant role is illustrated in the particle size volume fractions of Table 2, which shows Mt Mackay particles having the lowest proportion of particles less than 1 μm. The specific surface area data of Table 2 indicates that Mt Mackay has the lowest value, hence on that 9
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Fig. 14. Intra- and inter-aggregate voids: (A) soil, and (B) schematic floc structure.
3.3. Surface chemistry by time of flight secondary ion mass spectrometry (TOF-SIMS)
score plots. 3.3.1. Organic species Figs. 8 and 10 show the PCA score plots for the wet and dry Mt Mackay and Gluepot samples, respectively. Figs. 9 and 11 show the PCA loadings plots for the Mt Mackay and Gluepot samples, respectively. The first principal component in the score plot for Mt Mackay (Fig. 8), which represents ~93% of the variation in the original data set, shows that the wet and dry samples are separated on the PC1 axis. There is a larger spread in the ‘dry’ data points suggesting more surface heterogeneity. The loadings plot (Fig. 10) shows a negative correlation with some hy drocarbon chain fragments as well as a strong correlation to NHþ 4 . The þ dry samples show strongest correlation to C2Hþ 4 and C3H5 species. The PC1 in the score plot for Gluepot (Fig. 10), which represents ~66% of the variation in the original data set, shows that the wet and dry samples are roughly separated on the PC1 axis. There is however a larger spread in the ‘dry’ data points also suggesting more surface het erogeneity, in the Mt Mackay sample. The loadings plot (Fig. 11) shows an intense negative correlation to the first PC for NHþ 4 , as well as some
Time of flight secondary ion mass spectrometry (TOF-SIMS) is one of the most sensitive and reliable analytical techniques that assist with the identification of chemical species present on the outer most layer (~1–2 nm) of solid materials. TOF-SIMS has been used by many researchers to identify organic and inorganic species on the surfaces of particles (Cliff et al., 2002; Grams and Bawolak, 2007; Chehreh Chelgani and Hart, 2014). The TOF-SIMS analysis was undertaken on the Mt Mackay and Gluepot soil samples. Principal component analysis (PCA) was used to distinguish any differences in the surface functional groups between the Mackay and Gluepot soils as well as between wet and dry samples of the soils. Clustering of measurements in the PCA score plots suggests similar surface chemistry and conversely measurements separated suggest sig nificant variation (Holzweber et al., 2014). Reference to the species in the loadings plots can help explain why measurements are either posi tively or negatively correlated to the principal component axes of the 10
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Fig. 15. Electron micrographs of (A) SEM-Mt Mackay, (B) TEM-Mt Mackay, (C) SEM-Invicta, (D) TEM-Invicta, (E) SEM-Gluepot, (F) TEM-Gluepot.
strong correlations for some hydrocarbon fragments. The most posi tively correlated, and hence associated with the dry samples, are signals for CH3N and C3H4O species. Overall, there are a few trends apparent in the data. The spread in dry data points compared to wet data points suggest that the surfaces of the dry soils are more heterogeneous. The reason the surfaces of the wet samples appear more homogeneous after wetting may perhaps be due to the sample preparation method. When the soils are wet, any soluble material may have been released, and then on drying redeposited on the surface of the soil particles in a more even manner. One of these species seems to contain NHþ 4 functionality, which exhibits a very strong cor relation in all wet samples.
elemental species (i.e., Na, Al, Si, K, Ca and Fe). A significant difference between the wet and dry samples is the higher proportion of Na ions in the wet samples. Sodium ions are known to be highly hydrated and are known to be good dispersants and hence poor coagulants (Sakuma et al., 2011; Scholz, 2016), and so the wet sample is expected to be flocculated less compared to the dry sample. There is also a higher proportion of total organics in the wet samples, which will affect the rate of settling of the particles. So in summary, looser flocs are expected to be formed with the wet samples compared to the dry samples, and the higher organic content in the wet samples, will to a certain extent, influence the floc density. The soil from Mt Mackay has good settling and flocculating charac teristics based on previous work and anecdotal evidence. As illustrated in Figs. 12 and 13 the proportion of Na ions on the surface of the wet particles of the Mt Mackay’s soil is significantly less than the Gluepot 3552 A sample, so also the ratio Si:Al counts is lower a further confir mation of the differences in the coagulation/flocculation characteristics
3.3.2. Inorganic species Figs. 12 and 13 show the distributions of inorganic ions and total organics in the dry and wet samples. In all cases the mass spectra collected from the analyses show high responses from the inorganic 11
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Fig. 16. Particle size distribution of the flocculated ash.
Fig. 17. Variation in final settling time for various soil:ash ratios (flocculant LT27, dose rate of 0.125 ppm).
of these soils based on surface chemistry.
arrangement of micro-flocs of the soils were examined using SEM and TEM. SEM micrograph of the Mt Mackay shows various sizes and mostly shapeless platy clay minerals which in some cases are of reassembly pseudo hexagonal symmetry, characteristic of kaolinites. TEM micro graph show mostly kaolinite platelets which vary in size from one μm to about 50 nm. Most platelets have irregular shape and some of them, in fragments display pseudo-hexagonal grain edges. Kaolinite are probably are poorly crystalline. In the micrograph stacks of kaolinite and tubular halloysite can be observed, and not many voids are present. In SEM micrograph (Fig. 15) of the Invicta sample, clay minerals are present and they reassembly thin platelets of irregular shape and broad variation in diameter. Most of these platelets are below one μm in diameter and they are well dispersed, not aggregated. The TEM micro graphs show irregular in shape and extremely dispersed platy minerals,
3.4. Flocculation with bagasse fly ash The results of the surface chemistry study (as well as particle size and particle density) in the previous sections have shown these influence the behaviour of the soil particles. The challenge is therefore to develop strategies based on these information to control floc settling rate. However, in the free settling zone of floc aggregates, intra-aggregate and inter-aggregate solution fluid influence the floc density as they occupy voids between particles and between micro-flocs (Fig. 14). Reduction of voids and/or increasing the floc density will therefore increase the settling rate and minimise the effect of the surface chemistry. As the way particles are arranged in the micro-floc network has a bearing on the void fraction and hence on the particle settling rate, the packing 12
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incorporating high density particles into gravity settling clarification systems to improve the bulk density and hence the settling rate of flocs (Young and Edwards, 2003; Lombard et al., 2013; Kumar et al., 2016), the authors investigated the use of bagasse fly ash, which has a particle density of ~1390 kg/m3 (Lima et al., 2012) to assess whether it would improve the settling behaviour of Gluepot and Invicta soils. Preliminary tests using bagasse fly ash (i.e., without pre-flocculating) showed that a reasonable amount of fine ash particles was present in the supernatant with little or no improvement on settling speed. In the sugar factory process, the bagasse fly ash is typically removed from the boiler in a slurry form using water. The slurry undergoes a clarification process using a flocculant to aggregate the ash particles and to aid in the sepa ration process and produce low turbidity water so that it can be recycled back to the boiler ash system. Hence it was decided to pre-flocculate the ash particles prior to use in the clarification tests with the soils. Fig. 16 shows the particle size distribution of the flocculated ash with a mean size of 100 μm. Fig. 17 shows the final settling times for the different soil to ash ratios for each of the three soils. The final settling times (30 min) rather than the standard interface height measurements at certain intervals were measured due to difficulties in reading the interface during the initial settling period. The results show that there are benefits in adding floc culated ash to the soil solution prior to clarification. The addition of flocculated ash has a more significant impact on the soils that have poor settling rates (i.e., Gluepot and Invicta). For soil to ash ratio of 3:1 the
Fig. 18. Effect of degree of hydrolysis of flocculant on initial settling rate for Gluepot and Mt Mackay.
probably disorderly kaolinite, illites and vermiculites of diameters from 20 to 200 nm. As the particles are well dispersed many more voids are present compared to Mt Mackay. With the Gluepot sample the clay platelets are well dispersed compared to Mt Mackay and Invicta implying of more voids in the micro-flocs. On the basis of these differences in porosity and the practice of
Fig. 19. Schematic representation of interactions between the soil surface containing (A) high and (B) low Na contents and polymer flocculant. 13
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final settling times are at least 63% and 47% lower when compared no ash addition for the Gluepot and Invicta 255 B soils respectively. The results for Mt Mackay indicate there is only a slight benefit when the total ash content is at least 50% (i.e., 1:1 ratio). Although the results show higher reductions of the final settling times when higher quantities of flocculated ash is added, it may not provide overall benefits in factory juice clarification processes. This is due to the fact that any ash added to the juice in a raw sugar factory ends up in the filter feed which increases the production of mud cake. Unless the addition of ash also improves filtration efficiency it is likely that higher sugar losses to the mud cake will result. In practice, therefore the amount of pre-flocculated ash added to the juice will also need to be assessed in terms of its effect on mud filtration efficiency and pol losses in the mud cake.
approached zero with increasing ionic strength compared to Gluepot. The overall outcome of the present and previous results explains the slower settling behaviour of soil particles from Gluepot. The improve ment in settling rate with increasing degree of hydrolysis of the floc culant (Fig. 18) is because of tighter binding of the floc aggregates by increasing carboxylate ion content. The turbidities of the supernatants for the best performing flocculant A2130 was 2.4 units and 3.0 for Gluepot and Mt Mackay respectively, while the mud height was 8% for Gluepot and 4% for Mt Mackay. The slightly lower turbidity obtained with Gluepot is because of the slower settling rate. 4. Conclusion The XPS analysis of the soil samples identified polysaccharides, organic acid compounds, and proteins, on the surfaces of the soil par ticles. The proportion of alcohol groups is highest in the Mt Mackay sample, and since these are likely to form hydrogen bonds will impact on the particle-flocculant interactions, and hence on the settling behaviour. TOF-SIMS results of the soils showed higher proportions of sodium and clay species in the slow settling Gluepot samples. Difference between wet and dry samples was clearly revealed with the TOF-SIMS results confirming that the chemistry of the surface of particles play significant roles in the settling rate of the flocs, and provides an explanation, to a certain extent, why slow settling soils tend to be observed more during wet weather. The packing arrangement of the particles was found to be another feature that distinguishes the soils, and that the addition of flocculated bagasse fly ash significantly improved the settling behav iour, presumably by blocking the voids in the floc structures.
3.5. Effect of the degree of hydrolysis of flocculant on settling rate The process of flocculation is a complicated one, involving the following steps: (a) particle-polymer mixing, (b) attachment of the polymer molecules onto the particle surface including charge neutrali sation, (c) re-conformation of the polymer molecules on the particle surface, (d) particle flocculation, and (e) floc breakage. So, particle flocculation is influenced by the surface species, functionality and charge of the particles and degree of hydrolysis of the flocculant. As has been demonstrated in previous sections, the surface chemistry of the ‘good’ and ‘bad’ soils are different. So, the effect of flocculant of floc culants with different degrees of hydrolysis was evaluated on the settling rate of Gluepot and Mt Mackay soils. The flocculant dosage used for the clarification of sugarcane juice in raw sugar manufacturing typically vary between ~3 and 5 ppm (Rein, 2007), though in this study 1 ppm was the concentration used. The selected flocculant dosage of 1 ppm (after initial screening with 0.25–1.0 ppm) in this work was because the main aim was to achieve settling rates that are easily distinguishable between the two soil types and to identify the flocculant type that pro duces the best clarification performance. Fig. 18 shows the effect of the degree of hydrolysis of flocculant on the initial settling rate. The settling rates for Mt Mackay are in the range 78.6–123.6 cm/min, while those of Gluepot are in the range 34.3–50.9 cm/min. The general trend is that the higher the degree of hydrolysis the faster the rate of settling of the flocculated soil particles. The higher settling data for Mt Mackay is in agreement with the properties of the soil as previously stated. The TOF-SIMS results of Figs. 12 and 13 indicate that the particle surfaces of both Mt Mackay and Gluepot soils are dominated by silicaaluminium species and organic matter. Sodium ions are the dominant inorganic ions on the surface of these particles. Fig. 19 shows a sche matic representation of the distribution of clay particles and sodium ions on particle surfaces. The particles contain –OH groups and the distance between individual clay particles will depend whether they swell (as in Gluepot containing Si:Al ratio of 2, smectites) or not (as in Si:Al ratio of 1 as in Mt Mackay). Therefore, the spacing between individual clay par ticles will be wider for Gluepot than for Mt Mackay. In the aqueous electrolyte medium, the polymer flocculant will be dissociated with carboxylate ions distributed along its chain length. The –OH groups on the particle surfaces will couple to the Ca2þ (from the electrolyte) and form bridges with the carboxylate ions of the flocculant. This will bring the particles together to form aggregates and enhance flocculation. Tighter network floc structures will form, as a result of this, but more so with Mt Mackay particles because of the short distances between the particles. As Gluepot has a higher proportion of Naþ, the clay particles will be more stable than those of Mt Mackay as its large water of hy dration will increase particle-particle separation. As reported in previous publication (Bakir et al., 2016), Gluepot has a higher cation exchange capacity than Mt Mackay and will absorb more exchangeable inorganic ions which will be retained on the clay surface. This is confirmed by the TOF-SIMS results of Figs. 12 and 13. The pre vious study also showed that the zeta potential for Mt Mackay
Declaration of competing interest There are no conflict of interests with the publication of this paper. CRediT authorship contribution statement Hakan Bakir: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administra tion, Writing - review & editing. John A. Denman: Investigation, Data curation, Formal analysis, Writing - review & editing. William O.S. Doherty: Supervision, Conceptualization, Data curation, Formal anal ysis, Funding acquisition, Investigation, Methodology, Project admin istration, Visualization, Writing - original draft. Acknowledgments The authors would like to thank Sugar Research Limited, Brisbane, Australia and Queensland University of Technology, Queensland, Australia for providing financial support. The authors acknowledge the facilities and the scientific and tech nical assistance of Microscopy Australia at the South Australian Regional Facility, University of South Australia. References Bakir, H., Zhangying, Z., Zbik, M., Harrison, M., Doherty, W.O.S., 2016. Understanding flocculation properties of soil impurities present in the factory sugarcane supply, 2016 J. Food Eng. 189, 55–63. Barton, C.D., Karathanasis, A.D., 2002. Clay Minerals. Encyclopedia of Soil Science. Retrieved from. https://www.srs.fs.usda.gov/pubs/ja/ja_barton002.pdf on 29/04/2 018. Chehreh Chelgani, S., Hart, B., 2014. TOF-SIMS studies of surface chemistry of minerals subjected to flotation separation – a review. Miner. Eng. 57, 1–11. Cliff, J.B., Gaspar, D.J., Bottomley, P.J., Myrold, D.D., 2002. Exploration of inorganic C and N assimilation by soil microbes with time-of-flight secondary ion mass spectrometry. Appl. Environ. Microbiol. 68 (8), 4067–4073. Doherty, W.O.S., Edye, L.A., 1999. An overview on the chemistry of clarification of cane sugar juice. Proc. Aust. Soc. Sugar Cane Technol. 21, 381–388.
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Journal of Food Engineering 279 (2020) 109978 Oliveira, C., Rubio, J., 2012. A short overview of the formation of aerated flocs and their applications in solid/liquid separation by flotation. Miner. Eng. 39, 124–132. Olson, B.C., Coleman, M.P., Fuelling, T.G., 1999. A commercial monitor for soil in sugar cane. Proc. Aust. Soc. Sugar Cane Technol. 21, 443–448. Pefferkorn, E., 1995. The role of polyelectrolytes in the stabilisation and destabilisation of colloids. Adv. Colloid Interface Sci. 56, 33–104. Rayment, G.E., Lyons, D.J., 2011. Soil Chemicals Methods – Australasia. Csiro Publishing. Rein, P., 2007. Cane Sugar Engineering. Verlag Dr. Albert Bartens KG, Berlin. Sabah, E., Cengiz, I., 2004. An evaluation procedure for flocculation of coal preparation plant tailings. Water Res. 38 (6), 1542–1549. Sakuma, H., Kondo, T., Nakoa, H., Shikari, K., Kawamura, K., 2011. Structure of hydrated sodium ions and water molecules adsorbed on the mica/water interface. J. Phys. Chem. C 115 (32), 15959–15964. Schjonning, P., McBride, R.A., Keller, T., Obour, P.B., 2017. Predicting soil particle density from clay and soil organic matter contents. Geoderma 286, 83–87. Scholz, M., 2016. Chapter 7 – coagulation and flocculation. In: Wetlands for Water Pollution Control, second ed. Elselvier, pp. 37–46. 978044436072. Shainberg, I., Levy, G.J., 2005. Salination processes. Encyclopedia of Soils in the Environment, pp. 429–435. Singer, M.J., Munns, D.N., 2006. Soils: an Introduction. Pearson Prentice Hall, New Jersey. Somasundaran, P., Runkana, V., 2005. Investigation of the flocculation of colloidal suspensions by controlling adsorbed layer microstructure and population balance modelling. Glasgow Proc. 7th World Congress of Chemical Engineering 83 (A7), 905–914. July. Steindl, R.J., 1998. Dirt – its implications for the clarifier and filter stations. Proc. Aust. Soc. Sugar Cane Technol. 20, 484–490. Thai, C.C.D., Doherty, W.O.S., 2011. The composition of sugarcane juices derived from burnt cane and whole green cane crop. Proc. Aust. Soc. Sugar Cane Technol. 33 (electronic format). Tripathy, T., De, B.R., 2006. Flocculation: a new way to treat the waste water. J. Phys. Sci. 10, 93–127. Young, J.C., Edwards, F.G., 2003. Factors affecting ballasted flocculation reactions. Water Environ. Res. 75 (3), 263–272.
Doherty, W.O.S., Greenwood, J., Pilaski, D., Wright, P.G., 2002. The effect of liming conditions in juice clarification. Proc. Aust. Soc. Sugar Cane Technol. 24, 443–451. Grams, J., Bawolak, K., 2007. Surface characterization of different particles arising as a result of coal combustion process in selected power plants from Central Poland using ToF-SIMS. Pol. J. Chem. Technol. 9 (4), 77–80. Gregory, J., 2006. Particles in Water: Properties and Processes. Verlag Dr. Albert Bartens KG, Berlin. Holzweber, M., Heinrich, T., Kunz, V., Richter, S., Traulsen, C.H.-H., Schalley, C.A., Unger, W.E.S., 2014. Principal component analysis (PCA)-Assisted time-of-flight secondary-ion mass spectrometry (ToF-SIMS): a versatile method for the investigation of self-assembled monolayers and multilayers as precursors for the bottom-up approach of nanoscaled devices. Anal. Chem. 86 (12), 5740–5748. https://doi.org/10.1021/ac500059a. Karpinski, B., Szkodo, M., 2015. Clay minerals – mineralogy and phenomenon of clay swelling in oil and gas industry. Adv. Mater. Sci. 15 (1), 43. Kroes, S., Forsell, L., 1999. Dirt in cane supply – where is it? Proc. Aust. Soc. Sugar Cane Technol. 21, 449–453. Kumar, S., Ghosh, N.C., Kazmi, A.A., 2016. Ballasted sand flocculation for water, wastewater and CSO treatment. Environmental Technology Reviews 5 (1), 57–67. https://doi.org/10.1080/21622515.2016.1207715. Lima, S.A., Varum, H., Sales, A., Neto, V.F., 2012. Analysis of the mechanical properties of compressed earth block masonry using the sugarcane bagasse ash. Construct. Build. Mater. 35, 829–837. Lombard, F., Guidi, L., Kiorboe, T., 2013. Effect of type and concentration of ballasting particles on sinking rate of marine snow produced by the appendicularian oikopleura dioica. PloS One 8 (9). https://doi.org/10.1371/journal.pone.0075676 e75676. Meadus, F.W., Bassaw, B.P., Sparks, B.D., 1982. Solvent extraction of Athabasca oil-sand in a rotating mill: Part 2. Solid-liquid separation and bitumen quality. Fuel Process. Technol. 6, 289–300. Miflin, B.J., 2014. Amino Acids and Derivatives: the Biochemistry of Plants. Elsevier Science & Technology, Saint Louis (ProQuest Ebook Central). (Accessed 29 April 2018). Moller, D., Broadfoot, R., Bell, S., Bakir, H., 2010. Whole crop processing at Broadwater Mill: impacts on process operations. Proc. Aust. Soc. Sugar Cane Technol. 32, 573–587.
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Contents lists available at ScienceDirect
Journal of Food Engineering journal homepage: http://www.elsevier.com/locate/jfoodeng
Slow settling behaviour of soil nano-particles in water and synthetic sugarcane juice solutions Hakan Bakir a, John A. Denman b, William O.S. Doherty a, * a b
Centre for Tropical Crops and Biocommodities, Queensland University of Technology, GPO Box 2434, Brisbane, QLD, 4001, Australia Future Industries Institute, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
A R T I C L E I N F O
A B S T R A C T
Keywords: Settling rate Flocculation Soil Sugarcane juice Clarification
Surface chemistry, morphological and physical properties of nano-particles in soils affect the settling behaviour of suspended particles in sedimentation clarifiers used in the raw sugar manufacturing process. This paper re veals subtle differences in the chemical specie compositions between soils that have good settling behaviour and those that do not using x-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spec trometry (TOF-SIMS). TOF-SIMS was further used to provide an understanding of differences between wet and dry soils that influence their settling behaviour. Differences in packing arrangements of the nano-particles in the soils and the presence of inter voids between individual particles and between microflocs, as revealed by high resolution microscopic techniques, provided evidence that the use of high density particles such as sugarcane bagasse fly ash was effective in increasing the settling rate of slow settling soils.
1. Introduction Solid-liquid separation processes are used in many industrial and chemical processes such as sugarcane, water and wastewater treatments, mining, drilling and extraction processes such as coal mining and oil sands (Doherty and Edye, 1999; Gregory, 2006; Oliveira and Rubio, 2012; Meadus et al., 1982). The raw products present in these processes all contain soil, organics and water, forming a solid-liquid suspension having particles with various sizes (Singer and Munns, 2006). Current solid-liquid separation technologies rely heavily on an initial pre-treatment process to coagulate and flocculate the suspended parti cles to form larger “floc” clusters, which are more efficiently separated (Somasundaran and Runkana, 2005). Therefore, the destabilisation of colloids (1 nm–1000 nm particle sizes) to achieve aggregation of parti cles (coagulation and flocculation) is a key governing factor in solid-liquid separation processes (Pefferkorn, 1995; Sabah and Cengiz, 2004). In the sugarcane manufacturing process, after the juice is extracted from the cane, the suspended and other impurities present in the juice are removed through a solid-liquid separation process (i.e., clarifica tion). During clarification the juice is heated and limed to form microflocs. The juice is then flashed to remove dissolved air from the juice as well as dispersed air bubbles. The juice is then flocculated by adding
anionic polyacrylamide polymer to form large macro-flocs (mud flocs) and clarified in a continuous gravity sedimentation clarifier. The mud flocs settle to the floor of the clarifier forming a mud layer, which is removed as mud underflow whilst the clarified juice flows upwards to the upper sections of the clarifier and is collected via overflow channels (Rein, 2007). The rate at which the mud flocs settle (settling velocity) is of great practical importance in solid-liquid separation processes involving the design and sizing of gravity settling clarifiers (Rein, 2007). The settling rates of mud flocs produced in Australian sugar factories typically varies between ~20 and 50 cm/min with an industry average of ~30 cm/min (Doherty et al., 2002; Steindl, 1998). If the settling rate of the mud flocs is not sufficiently faster than the bulk upward velocity of the juice then there is a risk that the mud flocs will be retained in the clarified juice stream and cause high turbidity of the juice (Rein, 2007). Under such circumstances, it is necessary to reduce the crushing rate and juice processing rate of the factory until improved clarification condi tions are restored. The slow settling mud problem is dependent on the type (e.g., clay mineral composition, clay content and morphology, organic content) and quantity of soil in the cane supply which in turn depends on a number of factors including harvesting method, growing and climatic conditions (dry or wet weather), quality of the cane crop, burnt or green cane and condition of the farm ground (Bakir et al., 2016). The quantity of soil entering the cane supply has tended to
* Corresponding author. E-mail address: [email protected] (W.O.S. Doherty). https://doi.org/10.1016/j.jfoodeng.2020.109978 Received 3 October 2019; Received in revised form 31 January 2020; Accepted 11 February 2020 Available online 14 February 2020 0260-8774/© 2020 Elsevier Ltd. All rights reserved.
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Currently, there is insufficient knowledge on how clay minerals in fluence the coagulation and flocculation mechanisms that take place during sugar cane juice clarification. Recent work by the authors was on the characterisation of soils that have different flocculation character istics, and the identification of nano-clays which impacted on the clar ification process (Bakir, 2016). The study showed that soils that impact on poor coagulation/flocculation processes (and hence settling behav iour) compared to other soils (Fig. 1) have the following features: (a) contain a lower portion of particles that have higher densities, (b) contain a higher portion of organic material and amorphous content, (c) higher specific surface area, (e) contain Si:Al ratio of 2:1 typical of montmorillonite type composition, (f) higher cation exchange capacity, and (g) higher zeta potential. Although, the study clearly demonstrated how the floc structure influenced the settling rate of the flocs, the un derlying surface chemistry of the individual particles, micro-flocs and flocs that influence and control the floc properties were not investigated, neither were strategies that should improve floc settling rate proposed. The present study uses X-ray photoelectron spectroscopy (XPS) to pro vide information on the elemental composition of the soil surface, time-of-flight secondary ion mass spectrometry (TOF-SIMS) to evaluate the functional groups of the soil surface, and scanning electron micro scopy (SEM) and transmission electron microscopy (TEM) to examine the packing arrangement of the soils, size, shape and type of mineral phases. The differences between the surface chemistry of dry and wet soils were also studied using TOF-SIMS because slow settling muds were more prevalent in sugarcane factories during the periods of wet weather. An option examined on the settling rate of the soil particles was to add sugarcane bagasse ash (fly ash) to occupy the voids in the floc network of the soil particles in order to increase the floc density and hence increase the settling rate. Because of differences in the surface chemistry of these
Fig. 1. Settling profiles of soil (1 wt%) samples. Table 1 True particle density, clay and organic content of soil samples. Standard devi ation included for true particle density and clay content. Soil
True particle density (kg/ m3)
Clay content (wt %)
Organic content (wt %)
Mt Mackay Invicta Gluepot
2508 � 2
6.83 � 2.84
8.02 � 0.80
2539 � 1 2324 � 2
9.91 � 3.05 10.80 � 1.88
4.39 � 0.40 12.93 � 0.75
increase significantly with the introduction of mechanical harvesting (Steindl, 1998; Kroes and Forsell, 1999) through the 1960’s and more recently, as a result of green cane harvesting (Moller et al., 2010; Thai and Doherty, 2011). In Australia, cane is harvested mechanically and the quantity of soil is typically ~2% by weight of the cane supply to the factory (Olson et al., 1999). This amount is steadily increasing due to a change in the cultivated area from rich alluvial flood planes to marginal soil types as a result of urban encroachment and competition from other crops. In Australian sugar factories mud filtration is almost universally undertaken using rotary vacuum filters (RVF). During the period when slow settling mud prevails there is the undesirable effect of producing light fluffy mud that is difficult to separate and wash, causing bot tlenecking at the filter station. In extreme cases a build-up of this light fluffy mud will require cane crushing to be stopped to allow processing of the high levels of mud in the factory. In Australia, the total industry cost associated with slow settling muds is estimated at ~$1 M per annum due to reduction in throughput, and the yield and quality of the product sugar. However, most of this cost is due to lost production time as a consequence of reduced throughput and/or short term production stoppages.
Fig. 2. XPS survey scan for colloidal soil particles for the Mt Mackay soil.
Table 2 Specific surface area and particle sizes of soils. Soil
Specific surface area m2/kg
D [4,3] μm
Mt Mackay Invicta Gluepot
2221 2293 2645
20.6 106.0 54.7
Volume, %
2
Dx (10) μm
Dx (50) μm
Dx (90) μm
0.875 0.840 0.819
6.30 8.04 4.19
65.2 321.0 54.3
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sugarcane is grown. The samples were labelled Mt Mackay, Invicta and Gluepot. The sample collection procedure is described in Bakir et al. (2016). The historical factory clarification performance of sugarcane juices containing these soils based on settling rate are 30–60 cm/min (good), 1–20 cm/min (poor) and 1–20 cm/min (poor) for Mt Mackay, Invicta and Gluepot respectively. The 2016 study by the authors confirmed the clarification performance of the soils. The compositions of the soils determined by X-ray powder diffraction (XRD) are Gluepot: 71.2 wt% amorphous, 11.8 wt% quartz, 4 wt% Albite, 7.9 wt% kaolinite, 1.3 wt% smectite; Invicta: 38.9 wt% amorphous, 45.1 wt% quartz, 4.9 wt% Albite, 6.4 wt% Microcline, 1.1 wt% kaolinite, 3.6 wt% muscosite; Mt Mackay: 5.3 wt% amorphous, 51.5 wt% quartz, 9.3 wt% microcline, 1.1 wt% anorthite, 26.0 wt% kaolinite, 5.0 wt% muscostite, 1.7 wt% gibbsite (Bakir et al., 2016). Fly ash samples were obtained from Isis Central Mill, Bundaberg, Queensland, Australia. Fly ash is the remaining product after bagasse is combusted (maximum temperatures of ~1000–1300 � C) in the boiler to provide energy for the running of the factory. On a dry basis, the fly ash consists of 74.2 wt% SiO2, 16.5 wt% Al2O3, 1.4 wt% P2O5, 5.5 wt% Fe2O3, 0.5 wt% K2O/Na2O 1.6 wt% CaO, 0.06 wt% MgO, 0.25 wt% others. The anionic polyacrylamide flocculants tested were the Superflocs A2115, A2120, A2125 and A2130 (Kermira, Albury, New South Wales, Australia), Sucrafloc 2310 and 2320 (TD Chemicals, Pty Ltd, Gold Coast, Queensland, Australia), and Magnafloc LT27 (Ciba, Sydney, Australia). The molecular weights of the Superflocs and LT27 are 23 � 106 and 18 � 106 respectively and for the Sucrafloc 2320 and 2310 they are 16 � 106 and 7–10 � 106 respectively.
Fig. 3. XPS survey scan for colloidal soil particles for the Invicta soil.
2.2. Methods 2.2.1. Moisture content, particle density, particle size distribution, clay fraction content, total organic carbon content of the soils The moisture content of the soils was determined by drying the samples in an oven at 65 � C for 72 h to constant weight. The values were 10.4 wt%, 2.7 wt% and 7.9 wt% for Mt Mackay, Invicta and Gluepot respectively. The true particle density of the soils was determined by the Helium Pycnometer test using an AccuPyc 1340. A 15 cm3 sample holding chamber was used and filled to ~75% full. Particle size distri butions of the soils were determined using a Malvern Mastersizer 3000 E (Malvern Instruments Ltd., United Kingdom). The clay fraction was determined by allowing a soil suspension with a known soil content to stand for a pre-calculated period using Stokes law to allow particles to settle to the extent that only the clay fraction (2 μm size) remained in suspension in the top section of the supernatant. A known volume of the clay-suspension was taken and dried. The clay fraction of the soil in the original suspension was back calculated by mass balance. The total organic matter, organic carbon and carbonate by loss on ignition were determined based on a method (6G1) in Rayment and Lyons (2011). 2.2.2. X-ray photoelectron spectroscopy X-ray photoelectron spectroscopy (XPS) is a valuable technique, which provides both qualitative and quantitative information on the surface chemistry and elemental composition of substances. Survey (i.e., wide) scans were taken with pass energy of 160 eV and multiplex (i.e., narrow) high-resolution scans were taken at 40 eV. Survey scans were carried out over a binding energy range of 1200 eV–0 eV with 1.0 eV steps and a dwell time of 100 ms. Narrow high-resolution scans were run with 0.05 eV steps and 250 ms dwell time. Base pressure was 1.0 � 10 9 Torr and 1.0 � 10 8 Torr in the analysis chamber and during the sample analysis, respectively. Peak fitting of the high-resolution data were also carried out using the CasaXPS software (Casa Software Ltd, United Kingdom).
Fig. 4. XPS survey scan for colloidal soil particles for the Gluepot soil.
soils, anionic polyacrylamide flocculants with different degrees of hy drolysis were added to see what effect they had on the settling rate of the soil particles. Therefore, the present study complements the authors’ previous work and provides additional information on issues sur rounding poor juice clarification encountered from time to time in sugarcane factories. 2. Materials and methods 2.1. Materials
2.2.3. Time of flight secondary ion mass spectrometry (TOF-SIMS) ToF-SIMS experiments were performed using a Physical Electronics
Three (3) soil samples were collected from three districts where 3
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Table 3 Binding energy values for the soils. Bond Fe 2p Fe 2p O 1s, some O*-amide N*-H2/N*-C-O K 2p3/2 K 2p1/2 C*-C C*-OH C*-O C*-OC Si 2p Al 2p
Mt Mackay
Invicta
Gluepot
Binding energy (eV)
Atomic (%)
Binding energy (eV)
Atomic (%)
Binding energy (eV)
Atomic (%)
711.935 714.560 531.941 400.080 293.307 296.184 284.800 286.409 287.694 288.877 102.798 74.467
0.143 0.034 57.790 0.778 0.343 0.180 8.225 6.061 1.707 1.478 11.130 12.130
712.342 714.677 531.941 400.234 293.498 296.282 284.800 286.731 285.847 288.902 712.342 714.677
0.678 0.174 62.430 0.462 0.936 0.419 5.375 2.293 0.876 0.768 0.678 0.174
712.427 714.983 531.931 400.164 293.548 296.309 284.800 286.172 286.958 288.928 102.831 74.5213
0.544 0.190 60.450 0.407 0.675 0.353 6.839 2.212 2.226 1.232 14.33 10.53
Fig. 5. High resolution XPS spectra for Mt Mackay soil.
Inc. PHI TRIFT V nanoTOF instrument (Physical Electronics Inc., Chanhassen, MN, USA) equipped with a pulsed liquid metal 79 þ Au primary ion gun (LMIG), operating at 30 kV energy. Dual charge
neutralisation was provided by an electron flood gun and 10eV Ar þ ions. The experiments were performed under a vacuum of 5 � 10 6Pa. “Bunched” Au1 instrumental settings were used to optimise mass 4
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Fig. 6. High resolution XPS spectra for Invicta soil.
resolution for the collection of spectra. þSIMS and -SIMS data were collected typically using a raster of ~50 � 50 μm and an acquisition time of 2 min. Sample spectra and images were processed and integrated using WincadenceN software (Physical Electronics Inc., Chanhassen, MN, USA). Surface analysis was carried out on dry loose soil samples and wet samples obtained from a suspension in Milli-Q water (18.2 MΩ cm @25 � C). The wet samples were prepared by adding soil material to Milli-Q water, sonicating for 5 min and allowing it to settle for 30 min. Ali quots were extracted from the suspension near the top of the solution. A droplet of this sample was then placed on a clean silicon wafer and the sample placed in a desiccator and pumped down to remove the liquid phase. The soil residue on the wafer was then loaded for surface analysis.
a known weight (0.5 g) was dispersed in 4 mL of Milli-Q water, sonicated for 1 min, and then allowed to settle for 5 min. A droplet was taken with a glass Pasteur pipette from the colloidal solution and placed onto an SEM stub and allowed to dry at ambient temperature. For the TEM study, the droplet was placed onto a carbon film prior to drying at 45 � C in an oven overnight. 2.2.5. Preparation of flocculant solution A 100 mL stock flocculant solution at 0.2 wt% was prepared by dispersing and dissolving flocculant powder (0.2 g) in Milli-Q water using a stirrer with a 45� pitch four blade turbine impeller of 50 mm diameter running at 50 r/min for ~4 h. The powder was added slowly and carefully during mixing to ensure that each flocculant granule is wetted to prevent agglomeration and the formation of ‘oysters’. The stock solution was stored in the fridge at ~4 � C. The effective life of a 0.2 wt% stock solution stored at ~4 � C is approximately two weeks. On the day of the tests the stock flocculant solution was used to prepare a 100 mL flocculant solution at either 0.01 wt% or 0.04 wt%.
2.2.4. Packing arrangements of the soils Investigations were conducted using JEOL-2100 Transmission Elec tron Microscope (TEM) (JEOL Ltd., Japan) with 200 kV accelerating potential and JEOL-6040 Scanning Electron Microscope (SEM) (JEOL Ltd., Japan) in accelerating voltage 15–20 kV. For SEM investigation samples were coated with platinum film few nm thick. For this analysis, 5
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Fig. 7. High resolution XPS spectra for Gluepot soil.
2.2.6. Stock synthetic juice solution (Electrolyte) Chemicals, CaCl2⋅2H2O (Chem Supply, Gillman, Australia), MgCl2⋅6H2O (Merck, Kilsyth, Australia), NaCl and KCl (Sigma- Aldrich, Sydney, Australia) were analytical grade. The stock synthetic juice solution was prepared by dissolving 1.91 g of NaCl, 47.67 g of KCl, 18.34 g of CaCl2⋅2H2O and 31.37 g of MgCl2⋅6H2O in 1000 mL of Milli-Q water. For each test, a 4 mL aliquot of the stock solution was added to the soil/Milli-Q water suspensions to produce a synthetic juice with an electrolyte composition of 30 ppm Naþ (as NaCl), 1000 ppm Kþ (as KCl), 200 ppm Ca2þ (as CaCl2⋅H2O), 150 ppm Mg2þ (MgCl2⋅6H2O). The pH of the solutions ranged between 4.67 and 5.93 and the value depended on the soil type.
was added to the mixture to give a volume of 100 mL and the whole stirred for 1 min. A flocculant dose to give 1 ppm in the 100 mL solution was added to the mixture in a single dose and stirred for a further 1 min. The flocculated suspension was then transferred into a 100 mL glass cylinder, inverted 10 times and left standing for sedimentation to occur. The mud interface heights were recorded over a 30 min period. The height of glass cylinder at the 100 mL graduation (~195 mm) was used to determine the settling rates over the first 5 min of sedimentation. The average error in the measurements is �0.25%. The turbidity of the su pernatant was determined by measuring its light absorbance at a wavelength of 900 nm and multiplying by 100. 2.2.8. Addition of ash aggregates The bagasse fly ash were flocculated to form ash aggregates. A known amount of bagasse fly (10 g) was added to 1 L of MilliQ water and stirred for 1 min. A 1 ppm flocculant LT 27 was added to floc the ash particles, and the glass cylinder was then inverted 10 times and left standing for 3 min. The flocculated particles were collected on a Whatman No 52 filter paper. Particle size distribution of the flocculated particles were determined using a Malvern Mastersizer 3000 E (Malvern
2.2.7. Batch settling tests using electrolyte with flocculants One (1) g of soil was weighed into 20 mL jar, which were then filled with Milli-Q water and sonicated in a water bath for 5 min to completely break down aggregates. After sonication, the mixture transferred into a glass beaker pre-filled with 76 mL of Milli-Q water. The mixture was stirred using a magnetic stirrer (~300 r/min) and a 5 cm stirrer bar for 1 min. Approximately 4 mL aliquot of the stock synthetic juice solution 6
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Fig. 8. PCA score plot of Mt Mackay samples obtained by TOF-SIMS.
Fig. 9. PCA loading of chemical species present in Mt Mackay samples obtained by TOF-SIMS.
Instruments Ltd., United Kingdom). For the clarification test, a known amount of the aggregated ash particles was then added to the soil so lution, as described in the batch settling tests. The total mass of soil/ash mixture was maintained at 1.000 g. The experiments were done in duplicate.
2.2.9. Statistical analysis of data Moisture, particle density, particle size, clay, and total organic car bon contents of the soils were analysed in duplicate and the mean value recorded. The error in the surface properties of the soils analysed by XPS was <5% and the standard deviation for elemental analysis of surface of the soils by XPS was <10%. 7
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Fig. 10. PCA score plot of Gluepot samples obtained by TOF-SIMS.
Fig. 11. PCA loading of chemicals species present in Gluepot samples obtained by TOF-SIMS.
The data from the TOF-SIMS of the soils was analysed by Principal component analysis (PCA). It was used to help highlight and identify variation in the data set, and hence differences between samples. PCA is primarily concerned with reducing the multiple dimensionality of a data set in which there are many related variables, while still retaining as much of the variation as possible in the data set. It does this by trans forming the data to a set of values of linearly uncorrelated variables
called principal components, which are ordered in terms of their vari ance, i.e., the first few contain most of the variation in the data that is present in all of the original variables. The lack of correlation is important as it indicates that the components are measuring or repre senting different aspects in the data. The inorganic data was statistically treated using the Student’s T-test. The error bars indicate the 95% confidence interval based on the mean value. 8
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basis, expected to have the fastest settling rate. These physical properties of the soil support the evidence provided by Bakir et al. (2016) that Mt Mackay is a ‘good’ soil exhibiting good settling properties while Gluepot is a ‘bad’ soil exhibiting poor settling properties. The results are not clear cut with the Invicta sample, though the clay content, which is higher than that obtained with the Mt Mackay sample, points to it being a ‘bad soil’. 3.2. Surface chemistry by x-ray photoelectron spectroscopy (XPS) The surface chemistry of the particles affects the way they coagulate and flocculate. Figs. 2–4 show the XPS survey scans for the colloidal portion of the Mt Mackay, Invicta and Gluepot soil samples, respec tively. The scans show that there are relatively higher quantities of O, C, Si and Al compared to Fe, N, Ca and K in these samples. The Si:Al ratio indicates the type of mineral present in the soils (Shainberg and Levy, 2005). The Si:Al ratio is 1:1 for the Mt Mackay sample indicating a clay mineral of kaolinite type, while the Si:Al ratio for the other two soils indicate a mixture of the 1:1 and 2:1 mineral types. The 2:1 mineral is of the montmorillonite type, known expandable clay (Barton and Kar athanasis, 2002). Expandable clays have the ability to absorb water (Karpinski and Szkodo, 2015), which would reduce their bulk density and hence their settling rates. As the ratio of Si:Al for both the Invicta and Gluepot samples, the 2:1 mineral is expected to be present in these samples, thereby supporting the poor settling behaviour of these samples. The amount of Ca is lowest in the Mt Mackay sample. This supports the loss on ignition data at 950 � C (which is related to Ca organics) where values of 0.43 wt%, 0.56 wt% and 0.83 wt% for Mt Mackay, Invicta and Gluepot, respectively. Iron is also shown to be the lowest with Mt Mackay, and so these elements may be present, at least in part, in their non-ionisable forms, as their ions enhance coagulation, though the overriding behaviour of the soils are likely to be dependent on other factors previously mentioned. Hydrolysable cations such as Al3þ can be highly effective in dispersion destabilisation, and in addition to cause double-layer compression and can reverse the zeta potential (Tripathy and De, 2006). These species can also promote aggregation by modi fying dispersed particles properties through surface precipitation of colloidal hydroxides. The XPS data show that the Mt Mackay sample has significantly the highest Al content than the two other samples, which is mainly because of the 1:1 mineral present, and so it is speculated that aluminium hydroxide species are formed. To determine the chemical states associated with the C, O, N, Si and Al peaks, a high resolution scan was obtained for the samples (Table 3 and Figs. 5–7). The high resolution XPS spectra of the C 1s electrons clearly indicate four chemically shifted C 1s peaks, of different chemical environments. The XPS analysis of the soil samples reveal the presence of hydrocarbons (C*-C), alcohol (C*-OH), carbonyl (C*-O) and organic ethers (C*-OC). These carbon functional groups suggest the presence of polysaccharides and organic acid compounds. The amide functional group indicates the presence of proteins, and that the surfaces are negatively charged due to the ionisation of the carboxyl and amino groups to give COO and NHþ 4 ions (Miflin, 2014). It should be noted, however, that no carboxylate ion was detected from the binding energy results, perhaps indicating that at the pH the samples were analysed was not sufficient for this to occur. As shown in Table 3, the proportions of the organic and also inor ganic compounds are different among the three samples. The pro portions of hydrocarbon and alcohol species are highest in the Mt Mackay samples, while the proportion of the carbonyl group is highest in the Gluepot sample. It is probable that alcohol species may well participate in hydrogen bonding enhancing polymer-particle interaction.
Fig. 12. Distribution of inorganic ions and total organics on the surfaces of Mt Mackay particles obtained by TOF-SIMS.
Fig. 13. Distribution of inorganic ions and total organics on the surfaces of Gluepot particles obtained by TOF-SIMS.
3. Results and discussion 3.1. Physical properties of the soils The true particle density is most relevant in relation to settling rates of flocs formed from soil suspensions. Because soils are typically made up of varying quantities of silicates, organics and metal oxides, the true particle density that is measured represent the average true particle density of all the components that make up the soil. The true particle densities of the soil samples are shown in Table 1 and indicate that the particle densities vary between 2320 and ~2540 kg/m3. Gluepot has the lowest particle density at 2320 kg/m3 and Invicta has the highest par ticle density at 2540 kg/m3. These values are less than most soils which typically have values of 2650 kg/m3 because of relatively higher pro portion of quartz present (Schjonning et al., 2017). On the basis of the true particle density, the Invicta sample should have the fastest settling rate, or at least comparable with the soil sample for Mt Mackay. However, Mt Mackay soil sample has the lowest clay content, than either the soil from Invicta or Gluepot. In the previous work by the authors (Bakir et al., 2016), Mt Mackay soil has the fastest settling rate, so from the result of Table 1, the clay content influences the settling rate of the particles the most. Further evidence of the clay par ticles playing a significant role is illustrated in the particle size volume fractions of Table 2, which shows Mt Mackay particles having the lowest proportion of particles less than 1 μm. The specific surface area data of Table 2 indicates that Mt Mackay has the lowest value, hence on that 9
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Fig. 14. Intra- and inter-aggregate voids: (A) soil, and (B) schematic floc structure.
3.3. Surface chemistry by time of flight secondary ion mass spectrometry (TOF-SIMS)
score plots. 3.3.1. Organic species Figs. 8 and 10 show the PCA score plots for the wet and dry Mt Mackay and Gluepot samples, respectively. Figs. 9 and 11 show the PCA loadings plots for the Mt Mackay and Gluepot samples, respectively. The first principal component in the score plot for Mt Mackay (Fig. 8), which represents ~93% of the variation in the original data set, shows that the wet and dry samples are separated on the PC1 axis. There is a larger spread in the ‘dry’ data points suggesting more surface heterogeneity. The loadings plot (Fig. 10) shows a negative correlation with some hy drocarbon chain fragments as well as a strong correlation to NHþ 4 . The þ dry samples show strongest correlation to C2Hþ 4 and C3H5 species. The PC1 in the score plot for Gluepot (Fig. 10), which represents ~66% of the variation in the original data set, shows that the wet and dry samples are roughly separated on the PC1 axis. There is however a larger spread in the ‘dry’ data points also suggesting more surface het erogeneity, in the Mt Mackay sample. The loadings plot (Fig. 11) shows an intense negative correlation to the first PC for NHþ 4 , as well as some
Time of flight secondary ion mass spectrometry (TOF-SIMS) is one of the most sensitive and reliable analytical techniques that assist with the identification of chemical species present on the outer most layer (~1–2 nm) of solid materials. TOF-SIMS has been used by many researchers to identify organic and inorganic species on the surfaces of particles (Cliff et al., 2002; Grams and Bawolak, 2007; Chehreh Chelgani and Hart, 2014). The TOF-SIMS analysis was undertaken on the Mt Mackay and Gluepot soil samples. Principal component analysis (PCA) was used to distinguish any differences in the surface functional groups between the Mackay and Gluepot soils as well as between wet and dry samples of the soils. Clustering of measurements in the PCA score plots suggests similar surface chemistry and conversely measurements separated suggest sig nificant variation (Holzweber et al., 2014). Reference to the species in the loadings plots can help explain why measurements are either posi tively or negatively correlated to the principal component axes of the 10
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Fig. 15. Electron micrographs of (A) SEM-Mt Mackay, (B) TEM-Mt Mackay, (C) SEM-Invicta, (D) TEM-Invicta, (E) SEM-Gluepot, (F) TEM-Gluepot.
strong correlations for some hydrocarbon fragments. The most posi tively correlated, and hence associated with the dry samples, are signals for CH3N and C3H4O species. Overall, there are a few trends apparent in the data. The spread in dry data points compared to wet data points suggest that the surfaces of the dry soils are more heterogeneous. The reason the surfaces of the wet samples appear more homogeneous after wetting may perhaps be due to the sample preparation method. When the soils are wet, any soluble material may have been released, and then on drying redeposited on the surface of the soil particles in a more even manner. One of these species seems to contain NHþ 4 functionality, which exhibits a very strong cor relation in all wet samples.
elemental species (i.e., Na, Al, Si, K, Ca and Fe). A significant difference between the wet and dry samples is the higher proportion of Na ions in the wet samples. Sodium ions are known to be highly hydrated and are known to be good dispersants and hence poor coagulants (Sakuma et al., 2011; Scholz, 2016), and so the wet sample is expected to be flocculated less compared to the dry sample. There is also a higher proportion of total organics in the wet samples, which will affect the rate of settling of the particles. So in summary, looser flocs are expected to be formed with the wet samples compared to the dry samples, and the higher organic content in the wet samples, will to a certain extent, influence the floc density. The soil from Mt Mackay has good settling and flocculating charac teristics based on previous work and anecdotal evidence. As illustrated in Figs. 12 and 13 the proportion of Na ions on the surface of the wet particles of the Mt Mackay’s soil is significantly less than the Gluepot 3552 A sample, so also the ratio Si:Al counts is lower a further confir mation of the differences in the coagulation/flocculation characteristics
3.3.2. Inorganic species Figs. 12 and 13 show the distributions of inorganic ions and total organics in the dry and wet samples. In all cases the mass spectra collected from the analyses show high responses from the inorganic 11
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Fig. 16. Particle size distribution of the flocculated ash.
Fig. 17. Variation in final settling time for various soil:ash ratios (flocculant LT27, dose rate of 0.125 ppm).
of these soils based on surface chemistry.
arrangement of micro-flocs of the soils were examined using SEM and TEM. SEM micrograph of the Mt Mackay shows various sizes and mostly shapeless platy clay minerals which in some cases are of reassembly pseudo hexagonal symmetry, characteristic of kaolinites. TEM micro graph show mostly kaolinite platelets which vary in size from one μm to about 50 nm. Most platelets have irregular shape and some of them, in fragments display pseudo-hexagonal grain edges. Kaolinite are probably are poorly crystalline. In the micrograph stacks of kaolinite and tubular halloysite can be observed, and not many voids are present. In SEM micrograph (Fig. 15) of the Invicta sample, clay minerals are present and they reassembly thin platelets of irregular shape and broad variation in diameter. Most of these platelets are below one μm in diameter and they are well dispersed, not aggregated. The TEM micro graphs show irregular in shape and extremely dispersed platy minerals,
3.4. Flocculation with bagasse fly ash The results of the surface chemistry study (as well as particle size and particle density) in the previous sections have shown these influence the behaviour of the soil particles. The challenge is therefore to develop strategies based on these information to control floc settling rate. However, in the free settling zone of floc aggregates, intra-aggregate and inter-aggregate solution fluid influence the floc density as they occupy voids between particles and between micro-flocs (Fig. 14). Reduction of voids and/or increasing the floc density will therefore increase the settling rate and minimise the effect of the surface chemistry. As the way particles are arranged in the micro-floc network has a bearing on the void fraction and hence on the particle settling rate, the packing 12
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incorporating high density particles into gravity settling clarification systems to improve the bulk density and hence the settling rate of flocs (Young and Edwards, 2003; Lombard et al., 2013; Kumar et al., 2016), the authors investigated the use of bagasse fly ash, which has a particle density of ~1390 kg/m3 (Lima et al., 2012) to assess whether it would improve the settling behaviour of Gluepot and Invicta soils. Preliminary tests using bagasse fly ash (i.e., without pre-flocculating) showed that a reasonable amount of fine ash particles was present in the supernatant with little or no improvement on settling speed. In the sugar factory process, the bagasse fly ash is typically removed from the boiler in a slurry form using water. The slurry undergoes a clarification process using a flocculant to aggregate the ash particles and to aid in the sepa ration process and produce low turbidity water so that it can be recycled back to the boiler ash system. Hence it was decided to pre-flocculate the ash particles prior to use in the clarification tests with the soils. Fig. 16 shows the particle size distribution of the flocculated ash with a mean size of 100 μm. Fig. 17 shows the final settling times for the different soil to ash ratios for each of the three soils. The final settling times (30 min) rather than the standard interface height measurements at certain intervals were measured due to difficulties in reading the interface during the initial settling period. The results show that there are benefits in adding floc culated ash to the soil solution prior to clarification. The addition of flocculated ash has a more significant impact on the soils that have poor settling rates (i.e., Gluepot and Invicta). For soil to ash ratio of 3:1 the
Fig. 18. Effect of degree of hydrolysis of flocculant on initial settling rate for Gluepot and Mt Mackay.
probably disorderly kaolinite, illites and vermiculites of diameters from 20 to 200 nm. As the particles are well dispersed many more voids are present compared to Mt Mackay. With the Gluepot sample the clay platelets are well dispersed compared to Mt Mackay and Invicta implying of more voids in the micro-flocs. On the basis of these differences in porosity and the practice of
Fig. 19. Schematic representation of interactions between the soil surface containing (A) high and (B) low Na contents and polymer flocculant. 13
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final settling times are at least 63% and 47% lower when compared no ash addition for the Gluepot and Invicta 255 B soils respectively. The results for Mt Mackay indicate there is only a slight benefit when the total ash content is at least 50% (i.e., 1:1 ratio). Although the results show higher reductions of the final settling times when higher quantities of flocculated ash is added, it may not provide overall benefits in factory juice clarification processes. This is due to the fact that any ash added to the juice in a raw sugar factory ends up in the filter feed which increases the production of mud cake. Unless the addition of ash also improves filtration efficiency it is likely that higher sugar losses to the mud cake will result. In practice, therefore the amount of pre-flocculated ash added to the juice will also need to be assessed in terms of its effect on mud filtration efficiency and pol losses in the mud cake.
approached zero with increasing ionic strength compared to Gluepot. The overall outcome of the present and previous results explains the slower settling behaviour of soil particles from Gluepot. The improve ment in settling rate with increasing degree of hydrolysis of the floc culant (Fig. 18) is because of tighter binding of the floc aggregates by increasing carboxylate ion content. The turbidities of the supernatants for the best performing flocculant A2130 was 2.4 units and 3.0 for Gluepot and Mt Mackay respectively, while the mud height was 8% for Gluepot and 4% for Mt Mackay. The slightly lower turbidity obtained with Gluepot is because of the slower settling rate. 4. Conclusion The XPS analysis of the soil samples identified polysaccharides, organic acid compounds, and proteins, on the surfaces of the soil par ticles. The proportion of alcohol groups is highest in the Mt Mackay sample, and since these are likely to form hydrogen bonds will impact on the particle-flocculant interactions, and hence on the settling behaviour. TOF-SIMS results of the soils showed higher proportions of sodium and clay species in the slow settling Gluepot samples. Difference between wet and dry samples was clearly revealed with the TOF-SIMS results confirming that the chemistry of the surface of particles play significant roles in the settling rate of the flocs, and provides an explanation, to a certain extent, why slow settling soils tend to be observed more during wet weather. The packing arrangement of the particles was found to be another feature that distinguishes the soils, and that the addition of flocculated bagasse fly ash significantly improved the settling behav iour, presumably by blocking the voids in the floc structures.
3.5. Effect of the degree of hydrolysis of flocculant on settling rate The process of flocculation is a complicated one, involving the following steps: (a) particle-polymer mixing, (b) attachment of the polymer molecules onto the particle surface including charge neutrali sation, (c) re-conformation of the polymer molecules on the particle surface, (d) particle flocculation, and (e) floc breakage. So, particle flocculation is influenced by the surface species, functionality and charge of the particles and degree of hydrolysis of the flocculant. As has been demonstrated in previous sections, the surface chemistry of the ‘good’ and ‘bad’ soils are different. So, the effect of flocculant of floc culants with different degrees of hydrolysis was evaluated on the settling rate of Gluepot and Mt Mackay soils. The flocculant dosage used for the clarification of sugarcane juice in raw sugar manufacturing typically vary between ~3 and 5 ppm (Rein, 2007), though in this study 1 ppm was the concentration used. The selected flocculant dosage of 1 ppm (after initial screening with 0.25–1.0 ppm) in this work was because the main aim was to achieve settling rates that are easily distinguishable between the two soil types and to identify the flocculant type that pro duces the best clarification performance. Fig. 18 shows the effect of the degree of hydrolysis of flocculant on the initial settling rate. The settling rates for Mt Mackay are in the range 78.6–123.6 cm/min, while those of Gluepot are in the range 34.3–50.9 cm/min. The general trend is that the higher the degree of hydrolysis the faster the rate of settling of the flocculated soil particles. The higher settling data for Mt Mackay is in agreement with the properties of the soil as previously stated. The TOF-SIMS results of Figs. 12 and 13 indicate that the particle surfaces of both Mt Mackay and Gluepot soils are dominated by silicaaluminium species and organic matter. Sodium ions are the dominant inorganic ions on the surface of these particles. Fig. 19 shows a sche matic representation of the distribution of clay particles and sodium ions on particle surfaces. The particles contain –OH groups and the distance between individual clay particles will depend whether they swell (as in Gluepot containing Si:Al ratio of 2, smectites) or not (as in Si:Al ratio of 1 as in Mt Mackay). Therefore, the spacing between individual clay par ticles will be wider for Gluepot than for Mt Mackay. In the aqueous electrolyte medium, the polymer flocculant will be dissociated with carboxylate ions distributed along its chain length. The –OH groups on the particle surfaces will couple to the Ca2þ (from the electrolyte) and form bridges with the carboxylate ions of the flocculant. This will bring the particles together to form aggregates and enhance flocculation. Tighter network floc structures will form, as a result of this, but more so with Mt Mackay particles because of the short distances between the particles. As Gluepot has a higher proportion of Naþ, the clay particles will be more stable than those of Mt Mackay as its large water of hy dration will increase particle-particle separation. As reported in previous publication (Bakir et al., 2016), Gluepot has a higher cation exchange capacity than Mt Mackay and will absorb more exchangeable inorganic ions which will be retained on the clay surface. This is confirmed by the TOF-SIMS results of Figs. 12 and 13. The pre vious study also showed that the zeta potential for Mt Mackay
Declaration of competing interest There are no conflict of interests with the publication of this paper. CRediT authorship contribution statement Hakan Bakir: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administra tion, Writing - review & editing. John A. Denman: Investigation, Data curation, Formal analysis, Writing - review & editing. William O.S. Doherty: Supervision, Conceptualization, Data curation, Formal anal ysis, Funding acquisition, Investigation, Methodology, Project admin istration, Visualization, Writing - original draft. Acknowledgments The authors would like to thank Sugar Research Limited, Brisbane, Australia and Queensland University of Technology, Queensland, Australia for providing financial support. The authors acknowledge the facilities and the scientific and tech nical assistance of Microscopy Australia at the South Australian Regional Facility, University of South Australia. References Bakir, H., Zhangying, Z., Zbik, M., Harrison, M., Doherty, W.O.S., 2016. Understanding flocculation properties of soil impurities present in the factory sugarcane supply, 2016 J. Food Eng. 189, 55–63. Barton, C.D., Karathanasis, A.D., 2002. Clay Minerals. Encyclopedia of Soil Science. Retrieved from. https://www.srs.fs.usda.gov/pubs/ja/ja_barton002.pdf on 29/04/2 018. Chehreh Chelgani, S., Hart, B., 2014. TOF-SIMS studies of surface chemistry of minerals subjected to flotation separation – a review. Miner. Eng. 57, 1–11. Cliff, J.B., Gaspar, D.J., Bottomley, P.J., Myrold, D.D., 2002. Exploration of inorganic C and N assimilation by soil microbes with time-of-flight secondary ion mass spectrometry. Appl. Environ. Microbiol. 68 (8), 4067–4073. Doherty, W.O.S., Edye, L.A., 1999. An overview on the chemistry of clarification of cane sugar juice. Proc. Aust. Soc. Sugar Cane Technol. 21, 381–388.
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