Chemometrics investigation of the light-free degradation of methyl green and malachite green by starch-coated CdSe quantum dots

Accepted Manuscript Title: Chemometrics investigation of the light-free degradation of methyl green and malachite green by starch-coated CdSe quantum dots Author: Bahram Hemmateenejad Parisa Shadabipour Tahereh Khosousi Mojtaba Shamsipur PII: DOI: Reference:

S1226-086X(15)00028-3 http://dx.doi.org/doi:10.1016/j.jiec.2015.01.018 JIEC 2398

To appear in: Received date: Revised date: Accepted date:

21-7-2014 15-12-2014 8-1-2015

Please cite this article as: Chemometrics investigation of the light-free degradation of methyl green and malachite green by starch-coated CdSe quantum dots, Journal of Industrial and Engineering Chemistry (2015), http://dx.doi.org/10.1016/j.jiec.2015.01.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Chemometrics investigation of the light-free degradation of methyl green and malachite green by starch-coated CdSe quantum dots

Department of Chemistry, Razi University, Kermanshah, Iran

us

b

Department of Chemistry, Shiraz University, Shiraz, Iran

cr

a

ip t

Bahram Hemmateenejad,a* ParisaShadabipour,aTaherehKhosousi,aMojtabaShamsipurb

Abstract

an

Starch-coated CdSe quantum dots weresynthesized and utilized as aphotocatalystfor degradation of Methyl Green (MG)in ambient condition.Very low quantities of photocatalystfound to be capable ofsignificantly decolorize large amount of MG (ratio of MG to photocatalyst 1000:1)

M

within a few minutesin pH neutral.Simple UV/Vis spectroscopy measurements was coupledwith multivariate curve resolution-alternative least-squares (MCR-ALS) to present a new paradigm in

d

employing MCR-ALS technique for studying reaction kinetic. Five chemical components were detected for decomposition of MG using factor analysis (FA) and concentration profiles and pure

te

spectra of detected components were resolved using MCR-ALS.

Ac ce p

Keywords: Photocatalytic degradation; CdSe Quantum dots; Methyl Green; Chemometrics; MCR-ALS

* Corresponding author, Phone: +98 711 6460724, Fax: +98 711 6460788, E-mail address: [email protected] (B. Hemmateenejad)

1 Page 1 of 27

ip t

1. Introduction

cr

Technology advancement in textile, plastic, photography and several other industries over the past century has resulted overgrowing demand for utilizing synthetic dyes that subsequently

us

caused relentless release of organic pollutant into environment[1-3].This is becoming a topic of

an

concern by virtue of severe negative impact of organic dyes on surrounding environment, in particular on aquatic life[4,5]. The above mentioned concern in addition to population growth

M

and shortage of water resourceshighlights the essential importance of wastewater remediation and proper removal of synthetic dyes.Hence, recent years have seen a significant growing

d

interest toward wastewater treatment to avoid a global catastrophe in near future.Hitherto,

heterogeneousphotocatalytic

processes[11-15].Among

them,

the

Ac ce p

anaerobic[8-10],and

te

several approaches have introduced includingadsorption and coagulation, biological[6,7],

decomposition of organic dyes induced by photogenerated carries in semiconductors is a highly evolved environmental enterprise[16, 17]and appears to be the most promising approach for wastewater treatment that has enormous potential to make positive impacts on our life. In this context, titanium dioxide (TiO2) is the most commonly used photocatalystfor heterogeneous photocatalytic oxidation process, e.g degradation of organic dyes, due to its attracting properties such as strong oxidation power (very positive valance band), availability, long-term stability, and having non-toxic nature [16, 18-21]. However, photocatalytic efficiency suffers from poor absorption properties as TiO2has large band gap and mainly absorbs in ultraviolet region (λ<380

2 Page 2 of 27

nm). In addition, it has short minority carrier diffusion length, thus high ratio of photogenerated carriers are recombined before reaching to the surface of semiconductor[11, 22]. Development ofquantum dots during past a few decades has opened a new venue for solar

ip t

based photocatalytic processes with broad range applications from environmental prospective to

cr

solar-to fuel energy conversion[23-28]. This is fuelled by size dependent opto-electrical propertiesof quantum dotsin addition to short distance available for charge carriers to reach the

us

surface as size of quantum dots is generally less than minority carrier diffusion length[29, 30].Cadmium selenide (CdSe) quantum dots is well-known example for its size tunable band gap

an

that lays in visible region of solar spectrum from 1.74 eV to 3 eV by moving from bulk CdSe to

M

1.7nm quantum dots[31,32]. As a result, CdSe has potential to become an efficient photocatalyst for oxidation process because of its ability to absorb decent portion of ultraviolet-visible region

te

35].

d

of solar spectrum along with positive valance band that is suitable to drive oxidation reaction[33-

However, due to the release of Cd2+ ion, the bare Cd-based nanoparticles have represented

Ac ce p

toxicity and cytotoxicity effects [36, 37]. To reduce these undesirable effects, the nanoparticles are coated with some chemicals, e.g., ZnS. Here, we coated the CdSe QDs with starch as a biocompatible polysaccharide. In addition, the chemical nature of the coating effects on the photo-electronic property of the QDs. Study of mechanism of chemical reactions isalways subjected to great interestsfor understanding both fundamental phenomena and steering reaction pathway toward desire product(s). This usually entails combination of ultrafast spectroscopy, chromatographic and mass spectrometry and other sophisticated techniques to provide robust and complete picture of reactionpathway[38-41].UV/Vis absorption spectroscopy, in the other words, can be considered

3 Page 3 of 27

as an alternative owing to its low cost, speed and simplicity of measurements. However, obtained results are not usually informative enough to draw conclusion about reaction kinetic and thus its applications in multi-component system is limited. Thanks to recent advancement in

ip t

chemometrics, now it is possible to employ multivariate curve resolution–alternating least square (MCR–ALS) techniqueto analyze spectroscopic data of evolutionary processesin order to extract

cr

information regarding number of chemical species involved in the reaction, along with their

us

concentration profiles and pure spectra of species[42-47]. This has potential to open up a new door for studying photocatalysis process, e.g. photocatalytic degradation.

an

In the present study, we aimed to employ well-established MCR-ALS technique coupled with simple UV/Vis spectroscopy to process photodegradation of synthetic dyes in presence of starch-

M

stabilized CdSe quantum dots. MG was chosen as model example as it is among the most widely

d

used synthetic organic dyes[48].MCR-ALS was employedin order to resolve concentration and

te

pure spectral profiles of involved species, and thus gain a new insight into photocatalytic

Ac ce p

degradation of organic pollutants.

2. Materials and methods

2.1. Apparatus and software

A Perkin–Elmer (Lambda 2) UV/Vis spectrophotometer equipped with a 10 mm quartz cell was used for spectral measurements. The software of the instrument was used to collect the absorbance data in a spreadsheet. The temperature was maintained at 30 °C using a Shimadzu TB-85 thermostat via water circulation around the cell holder. Measurements of pH were done by using a Metrohm 780 pH-meter equipped with a combined glass electrode.

4 Page 4 of 27

2.2. Reagents and solutions

ip t

Methyl green, malachite green and phosphoric acid were purchased from Fluka. Acetic acid and boric acid were obtained from BDH. Sodium hydroxide and potassium chloride were from

cr

Merck. All reagents were in ACS grade and used without further purification. Millipore water with resistivity of 18.2 MΩ was used for solution preparation. All glass-ware were cleaned by

an

us

aqua regiasolution and were rinsed with Millipore water prior to experiments.

M

2.2. Methods

2.2.1 Synthesis of starch-capped CdSe quantum dots

d

Starch-coated CdSe quantum dots were prepared according to the existing procedure with minor

te

modifications[49]. A stock aqueous solution of 0.5 M sodium selenosulfate (Na2SeSO3) was

Ac ce p

prepared through reaction between Na2SO3 and selenium powder. In a separate round-bottom flask, 1.0 mL of 0.1M cadmium chloride was mixed with 100 mL aqueous solution of 0.05 wt% starch with gentle stirring in room temperature and pH was adjusted to be a basic value. This followed by slow addition of as-prepared Na2SeSO3 until the molar ratio of Cd:Na2SeSO3 reached 1:5 in final solution. The mixture was then stirred to obtain a red transparent solution indicating formation of CdSe quantum dots.

2.2.2 Degradation Procedure The aqueous universal buffer solutions over a pH range of 2.0–9.0 were prepared by successive addition of different aliquots of 0.2 M NaOH to a 1:1:1 aqueous mixture of boric acid (H3BO3): 5 Page 5 of 27

phosphoric acid (H3PO4): acetic acid (CH3COOH) (all 4.0×10-2 M). Proper amount of potassium chloride was also added to the stock buffer solution to adjust ionic strength at 0.1 M. Then, 3.0 mL of the prepared buffer with desire pH were transferred to a 5.0 mL volumetric flask, and

ip t

appropriate amount of prepared stock dye solution was added to buffer solution followed by dilution to 5.0mL. The concentration of dye in final solutions was kept at 4.8×10-5M (31.0 mg/L)

cr

in all cases. A 3.0 mL portion of dye solution was transferred to quartz cuvettes and certain

us

quantity of QD was injected into the solution in ambient light. UV/Vis absorbance spectra of the

an

resulting solutions were recorded for about 12 min with 30 s intervals.

M

2.2.3 MCR-ALS analysis

The recorded absorbance spectra of MG with time in each pH is considered as a data matrix

d

D(r×c), where r is equal to 25 and corresponded to number of recorder spectra (12min absorption

te

measurement with 30s time intervals) and c is equal to 501 and referred to the number of

Ac ce p

monitored wavelengths (200nm-700nm with 1.0 nm intervals). The total absorption profiles obtained in eight different pH from 2.0-9.0 were arranged in column-wise manner to form an augmented data matrix Daugment with dimension of (200 × 501). The soft-modeling methods of MCR-ALS employ iterative algorithm of ALS to decompose the data matrix into bilinear model consisting a sub-matrices C(r×n) and S(n×c) that represent the concentration and pure spectra profiles of the resolved components (n), respectively. E is the residuals matrix that ideally is close to the experimental error. D = CST + E

(1)

6 Page 6 of 27

As an essential step prior to MCR-ALS analysis, factor analysis (FA) based on singular value decomposition (SVD) algorithm performed in order to determine the number of chemical components (n)[50]. Using number of chemical components determined by FA, Evolving factor

ip t

analysis (EFA) can provide an initial estimation of the concentration profiles necessary for MCR-ALS outset. MCR-ALS was performed using the MCR-ALS subroutine written by Tauler

cr

et al[46]. Natural constraints, such as unimodality and nonnegativity are applied to MCR-ALS

us

analysis so that the resolved C and S matrices are being associated with more chemical insights [51]. Change in the lack of fit (LOF) of MCR–ALS model were monitored along with varying

an

number of components to generate a model with an optimal fit, i.e., with the minimum sum of squares of all the elements in the error matrix E [51, 52].Chemometrics analyses were performed

te

3. Results and discussion

d

M

in MATLAB (Mathwork, Inc., version 7- Natick, MA, USA) environment.

Ac ce p

Figure 1a shows the absorption and fluorescence spectra of as-prepared CdSe quantum dots. The absorption and fluorescence maxima are located at about 554nm and 570nm, respectively. The concentration of quantum dots solution was calculated using Eqs. (1) and (2) [53]. D= (1.6122×10-9) λ4-(2.6575×10-6) λ3+ (1.6242×10-3) λ2-(0.4277) λ+ (41.57)

(2)

ɛ= 5857 (D) 2.65

(3)

Where λ, D and ɛ are maximum absorption at highest wavelength, average diameter of quantum dots, and molar absorptivity, respectively. Using Lambert–Beer’s law and λ of about 554 nm from absorption spectra, the average diameter and concentration of quantum dots were calculated to be 3.1 nm and 5.7×10-6 M, respectively. The calculated diameter is in agreement with that

7 Page 7 of 27

observed from TEM image (Fig. 1b). The solutions of the starch capped CdSe QDs were highly stable and showed no signs of aggregation even after a year of storage. In fact,the stability of solution lies in starch matrix, which is enriched with hydroxyl groups and thus prevent the

ip t

particles from aggregation through hydrogen bonding with water. The X-ray diffraction peaks (Fig. 1c) indicate the nanocrystalline nature of the QDs. The peaks observed at 2θ = 25.6, 42.7

cr

and 49.7 are corresponding to the (111), (220), and (311) planes, respectively. The XRD patterns

us

are identical to the cubic phase with zinc blend structure. In these samples, (111) plane is very clear and abundant, which indicates the preferential growth of crystallites in this particular

an

direction [33].

Figure 2 demonstrates changes in absorption spectra of MG solution upon injection of little

M

quantity ofphotocatalyst under room light at neutral pH 7, whilst the mole ratio of photocatalyst

d

to dye was kept at about 1:1000 (3.0 ml of 4.8×10-5M dye vs 10.0 µL of 5.7×10-6 M of QD).

te

Interestingly, the declining of absorption started to occurright after addition of QD and decolorization occurred to a significant extent after 3.5 min. This isremarkable compare to

Ac ce p

literature reports, where considerable quantities of photo-catalysts have been used for degradation of MG usually under UV illumination, and reaction kinetics were slow[1, 55-56]. For example, Nickel-Dimethylglyoxime/ZSM-5 Zeolite was recently used as a heterogeneous catalyst for photodegradation of MG under UV illumination in pH=9, and 80% decolorization reported for 20ppm dye after 2hr illumination of 0.6gL-1 of photocatalys[55].In contrast, developed photocatalyst in the present study showed excellent performance under ambient light and at very low ratio of photocatalyst to dye (1:1000). Several factors may contribute to photocatalytic activity and thus degradation kinetic. To investigate the effect of pH on degradation of MG, a series of experiments were conducted at pH 8 Page 8 of 27

range of 3.0 to 9.0. Initial pH of dye solution was found to havesignificant contribution tophotodegradation as reaction kinetic was boosted along with increasing pH. According to Fig.3a, at pH=7-9, decolorization efficiency reached more than 80% within 2.0 min corresponds

ip t

to absorption decay at λmax= 632 nmfrom 1.2 to about 0.2. Enhancing photocatalytic activity at higher pH concurred with literatures[54, 57]and canbe explained based on higher concentration

cr

of hydroxyl radical at higher pH (OH- + h+ → OH●) that are scavenged more rapidly at a higher

us

pH[58-60]. Similar trend were observed for photodegradation of Malachite green (MaG) in ambient condition (see Figure S1, Supporting Information). Also, we performed control

an

experiments for degradation of MG in absence of QDs and observed close to 30% decline of absorption intensity at 632nm after 12min in pH=9 (see Figure S2, Supporting

M

Information).Therefore, it is important to optimize pH in order to isolate degradation due

d

tophotocatalyst. pH of 5.0 was found to be the optimum one for further study as control

te

experiment revealedtrivialcontribution of pH for photodegradationand at the same time degradation rate in presence of QDs was decent.It is also should be mentioned that capping agent

Ac ce p

(starch) does not contribute in degradation process as no absorption decay observed for MG solution contained 1.0 mM starch at pH=7 (see Figure S3, Supporting Information).Figure 3b representsthe effect of QD quantity on degradation kinetic. As expected, increasing QDs content in dye solution significantly accelerates degradation process as solution absorbance dramatically decreases.

The kinetics curves (absorbance decayvs time) at pH above 4 resemble an exponential decay indicating a pseudo-first order kinetic for degradation of both MeGand MaG(equation 4) that also supported by earlier reports [55, 61]. ln (C0/C) = kt

(4) 9 Page 9 of 27

where C0, C, t and k are the initial dye concentration, dye concentration at time t, degradation time (min) and rate constant (min−1), respectively.Absorbance measurements were used to calculate rate constants for both MeG and MaGin different pH and results were tabulated in

cr

transition pH of about 6 (see Figure S4, Supporting Information).

ip t

Table1. The changes in rate constants as function of pH resembles a sigmoid relationship with a

For chemometrics study, we only focused on photodegradation of MG as an example model.

us

As explained before, the augmented matrix Daug(200 × 501) consists eight sub-matrixes of

an

declining absorption profile with time in different pH that were arranged in column-wise manner. This approach prevents rotational ambiguity associated with analysis of single data matrices. The

M

way of data matrix augmentation and bilinear decomposition by MCR-ALS is shown in Figure 4.Daug was subjected to factor analysis (FA) in order to determine number of independent

d

chemical absorbing species involving in degradation process [62]. The score plot of singular

te

values shown in Fig.S5a(supplementary materials) represent a distinct separation between the

Ac ce p

fifth Eigen-value and the later ones. This also can be confirmed by the loading plot (see Fig.S5b) as the first 5 Eigen-vectors contain systematic information and the later Eigen-values are associated with noise. Thus, we considered 5 principal components for further MCR-ALS analysis. Evolving factor analysis (EFA) was then employed to obtain an initial estimate of concentration profile where clear separation between the fifth Eigen-values and the rest confirms five significant principal components and thus the results of FA (see Fig.S6, Supporting Information). For MCR-ALS, non-negativity constraint was applied to both concentration and spectral profiles. Also, unimodality and closure constraints were applied on concentration profiles. MCR-ALS convergence was achieved after a few iterations with lack of fit errors of

10 Page 10 of 27

0.49% and 0.60% for PCA and model, respectively. The resultant concentration profiles of the species at different pHs and corresponding pure spectra of the species are given in Fig.5. The obtained results of concentration profiles show three different groups of components. The

ip t

first group consists components of 2 and 3 for them concentration is decreasing over the course of reaction thus they can be considered as different form of reactants. The initial fraction ratio of

cr

component 2 to 3 increases by increasing pH from 2 to 3 and is almost constant by further

us

increase ofpH.This is in accordance with color change of aqueous solution from green at pH 2 to blue at pH 3 or higher. Therefore, we considered components 3 and 2 as protonated and neutered

an

forms of MeG, respectively.The next group containsevolved species includingcomponents of 4, and 5. The fraction of component 4 to 5 is decreasing by increasing pH from 2 to 4 and

M

component 5 is becoming dominant at higher pH with nominal fraction for component 4.

d

Component 1is the only member of the third group which resembles the behavior of an

te

intermediate species as it evolved at initial time and disappeared at longer times. The norms of the vectors of concentration profiles of the species at each pH were calculated

Ac ce p

and plotted against pH in Fig.6. At acidic pH, component 3 is the main reactant; however, component 3 is exchanged by component 2 by slight increase in pH so that it is becoming dominant reactant at pH values higher than 4. The rising part of component 2 can be attributed to conversion of component 3 to 2; whereas the falling part can be related to conversion of component 2 to products as reaction kinetic is faster at higher pHs.The evolution of the norm of component 4 and 5 as function of pH revealed interesting information about the protonation/deporotonation states of the degradation products as concentration of component 4 is decreasing along with increasing pH, while component 5 is dominant at higher pHs. Thus, components 4 and 5 can be attributed to the basic and acidic forms of products, respectively.This

11 Page 11 of 27

is supported by earlier report on mechanistic study of photodegradation of methyl green on TiO2 using HPLC-PDA-ESI-MS technique[54], whereproducts of methyl green degradation categorized into two groups illustrated in Fig.7. We assumed that compound ofFig.7a and b are

ip t

corresponded to components of 5 and 4, respectively. Hence, p-amino phenol derivatives (Fig.7a) are most likely dominant products at higher pH values. Finally, component 1, which

cr

probably contains several intermediates that could not be detected by UV/Vis spectroscopy,

an

resulted fast conversion of intermediate to products.

us

mostly exists at very lowpH.It could be due to very fast reaction kinetic at higher pHs that

M

4. Conclusion

In conclusion, starch-capped CdSe quantum dots presented excellent performance for rapid

d

photodegradation of methylene green and Malachite green under ambient condition. At neutral

te

pH and within 3.0 min,%80 decalorization was observed at very low ratio of photocatalyst to dye

Ac ce p

(1:1000). This offersCdSe quantum dots potential for efficient removing of organic pollutant from effluent. The calculated rate constant as function of pH for different quantities of photocatalyst demonstrated pseudo-first order kinetic for degradation of both MeG and MaG.MCR-ALS was undertaken to study photodegradation mechanism of methyl green and to resolve absorption and concentration profiles of the involved species through analysis of recorded absorption spectra over the course of reaction in several pH.The obtained results suggested three groups of species including two reactants, one intermediate and two products. Acknowledgements

12 Page 12 of 27

The authors wish to express their gratitude for the support of this work by Iran National Science

Ac ce p

References

te

d

M

an

us

cr

ip t

Foundation (INSF) through grant number 90005891.

[1] A. Houas, H. Lachheb, M. Ksibi, E. Elaloui, C. Guillard, J.-M. Herrmann, Appl Catal B 31 (2001) 145-157.

[2] C. Ràfols, D. Barceló, J. Chromatogr. A 77 (1997) 177-192. [3] E. J. Weber, V.C. Stickney, Water Res. 27 (1993) 63-67. [4] S. Srivastava, R. Sinha, D. Roy, Aquat. Toxicol. 66 (2004) 319-329. [5] E. A. Clarke, R. Anliker, Anthropogenic Compounds: in Handbook of Environmental Chemistry, Springer, Berlin/Heidelberg, 1980, pp. 181-215. [6] I. Arslan, I.A. Balcioğlu, Dyes Pigm. 43 (1999) 95-108. [7] S. Papić, N. Koprivanac, A. L. Božić, A. Meteš, Dyes Pigm. 62 (2004) 291-298. [8] G. Mezohegyi, A. Kolodkin, U.I. Castro, C. Bengoa, F. Stuber, J. Font, A. Fabregat, A. Fortuny, Ind. Eng. Chem. Res. 46 (2007) 6788-6792. [9] G.L. Baughman, E.J. Weber, Environ. Sci. Technol. 28 (1994) 267-276. [10] E.J. Weber, R. L. Adams, Environ. Sci. Technol. 29 (1995) 1163-1170. 13 Page 13 of 27

[11] I.K. Konstantinou, T.A. Albanis, Appl. Catal. B 49 (2004) 1-14. [12] K. Soutsas, V. Karayannis, I. Poulios, A. Riga, K. Ntampegliotis, X. Spiliotis, G. Papapolymerou, Desalination 250 (2010) 345-350. [13] N. Daneshvar,D. Salari, A. R. Khataee, J. Photochem. Photobiol. A 162 (2004) 317-322.

ip t

[14] H. Yu, S. Chen, X. Quan, H. Zhao, Y. Zhang, Environ. Sci. Technol. 42 (2008) 3791-3796. [15] L. Karimi, S. Zohoori, M.E. Yazdanshenas, J. Saudi Chem. Soc. 18 (2014)581-588. [16] M. Yin, Z. Li, J. Kou, Z. Zou, Environ. Sci. Technol. 43 (2009) 8361-8366.

cr

[17] H.C. Yatmaz, A. Akyol, M. Bayramoglu, Ind. Eng. Chem. Res. 43 (2004) 6035-6039. [18] Y. Zhang, Z.-R. Tang, X. Fu, Y.-J. Xu, ACS Nano 4 (2010) 7303-7314.

us

[19] U.G. Akpan, B.H. Hameed, J. Hazard. Mater. 170 (2009) 520-529.

[20] W. Zhao, W. Ma, C. Chen, J. Zhao, Z. Shuai, J. Am. Chem. Soc. 126 (2004) 4782-4783. [21] A.R. Khataee, M.B. Kasiri, J. Mol. Catal. A: Chem. 328 (2010) 8-26.

an

[22] S. Gupta, M.A. Tripathi, Chin. Sci. Bull. 56 (2011) 1639-1657. [23] P.V. Kamat, J. Phys. Chem. C 112 (2008) 18737-18753.

M

[24] S. Zhuo, M. Shao, S.-T. Lee, ACS Nano 6 (2012) 1059-1064.

[25] H. Li, X. He, Z. Kang, H. Huang, Y. Liu, J. Liu, S. Lian, C.H.A. Tsang,X. Yang, S.-T. Lee, Angew. Chem., Int. Ed. 49 (2010) 4430-4434.

d

[26] K.S. Leschkies, R. Divakar, J. Basu, E. Enache-Pommer, J. E. Boercker, C.B. Carter, U.R.

te

Kortshagen, D.J. Norris, E.S. Aydil, Nano Lett. 7 (2007) 1793-1798. [27] J. Yu, J. Zhang, M. Jaroniec, Green Chem. 12 (2010) 1611-1614.

Ac ce p

[28] H.M. Chen, C.K. Chen, Y.-C. Chang, C.-W. Tsai, R.-S. Liu, S.-F. Hu, W.-S. Chang, K.-H. Chen, Angew. Chem. 122 (2010) 6102-6105. [29] I. Robel, M. Kuno, P.V. Kamat, J. Am. Chem. Soc. 129 (2007) 4136-4137. [30] I. Moreels, K. Lambert, D. Smeets, D. De Muynck, T. Nollet, J.C. Martins, F. Vanhaecke, A. Vantomme, C. Delerue, G. Allan, Z. Hens, ACS Nano 3 (2009) 3023-303 [31] C.B. Murray, D.J. Norris, M.G. Bawendi, J. Am. Chem. Soc. 115 (1993) 8706-8715. [32] H. Sheng, L. Yu, Y. Jian-Hua, Y. Ying, ACS Symposium Series 1140 (2013)219-241. [33] X. Liu, C. Ma, Y. Yan, G. Yao, Y. Tang, P. Huo, W. Shi, Y. Yan, Ind. Eng. Chem. Res. 52 (2013) 15015-15023 [34] C. Harris, P.V. Kamat, ACS Nano 4 (2010)7321-7330. [35] R.C. Chikate, B.S. Kadu, M.A. Damle, RSC Adv. 4 (2014) 35997-36005. [36] R.Xing,X.Wang,L.Yan,C.Zhang, Z.Yang,X.Wanga, Z.Guo, Dalton Trans. 10 (2009) 1710-1713. [37] C. Kirchner, T.Liedl,S.Kudera, T. Pellegrino, A.M. Javier, H.E. Gaub, S. Stölzle, N. Fertig, W.J. Parak, J. Am. Soc. Mass Spectrom. 18 (2007) 679-687. 14 Page 14 of 27

[38] M.-I. Baraton, Spectroscopic Study of the Gas Detection Mechanism by Semiconductor Chemical Sensors. In Sensors for Environment, Health and Security, Baraton, M.-I., Ed. Springer Netherlands: 2009, 31-45. [39] A. Haynes, B.E. Mann, G.E. Morris, P.M. Maitlis, J. Am. Chem. Soc. 115 (1993) 4093-4100.

ip t

[40] H. Yang, M.C. Asplund, K.T. Kotz, M.J. Wilkens,H. Frei, C.B. Harris, J. Am. Chem. Soc. 120 (1998)10154-10165.

[41] B. Hemmateenejad, P. Shadabipour, M. Mohamadizadeh, J. Iran. Chem. Soc. 11 (2014) 147-154.

cr

[42] X. Zhang, R. Tauler, Anal. Chim. Acta 762 (2013) 25-38. [43] B. Hemmateenejad, J. Chemom. 19 (2005) 657-667.

us

[44] M.R. Hormozi-Nezhad, M.Jalali-Heravi, F. Kafrashi, J. Chemom. 27 (2013) 353-358. [45] J. Jaumot, R. Gargallo, A. de Juan, R. Tauler, Chemom. Intell. Lab. Syst. 76 (2005) 101-110. [47] D.F. Duxbury, Chem. Rev. 93 (1993) 381-433.

an

[46] T. Azzouz, R. Tauler, Talanta 74 (2008) 1201-1210. [48] O.S. Oluwafemi, Colloids Surf. B 73 (2009) 382-386.

M

[49] M. Wall, A. Rechtsteiner, L. Rocha, Practical Approach to Microarray Data Analysis, D. Berrar, W. Dubitzky, M. Granzow, Eds. Springer US 2003 91-109. [50] R. Tauler, Chemom. Intell. Lab. Syst. 30 (1995) 133-146.

d

[51] A. de Juan, M. Maeder, M. Martı́nez, R.Tauler, Chemom. Intell. Lab. Syst. 54 (2000) 123-141.

te

[52] W.W. Yu, L. Qu, W. Guo, X. Peng, Chem. Mater. 15 (2003) 2854-2860. [53] C.-C. Chen, C.-S. Lu, Environ. Sci. Technol. 41 (2007) 4389-4396.

Ac ce p

[54] A. Nezamzadeh-Ejhieh, Z. Shams-Ghahfarokhi, J. Chem. 2013 Article ID 104093. [55] F. Han, V.S.R. Kambala, M. Srinivasan, D. Rajarathnam, R. Naidu, Appl. Catal. A 359 (2009) 2540.

[56] B. Neppolian, H.C. Choi, S. Sakthivel, B. Arabindoo, V. Murugesan, J. Hazard. Mater. 89 (2002) 303-317.

[57] F.D. Mai, C.C. Chen, J.L. Chen, S.C. Liu, J. Chromatogr. A 1189 (2008) 355-365. [58] A. Piscopo, D. Robert, J.V. Weber, Appl. Catal. B 35 (2001) 117-124. [59] E.-J. Kwak, Y.S. Lee, M. Murata, S. Homma, LWT--Food Sci. Technol. 37 (2004) 255-262. [60] T. Ahmed, F. Uddin, R. Azmat, Chin. J. Chem. 28 (2010) 748-754. [61] E. R. Malinowski, Factor analysis in chemistry, Wiley, New York, 2002.

15 Page 15 of 27

ip t cr us an M d te Ac ce p

Legend for the figures:

Fig.1. Characterization of the synthesized nanoparticles(a)Absorption and fluorescence spectra of as-prepared starch-capped CdSe quantum dots (inset: digital image of QD), (b) TEM photograph and (c) XRD spectra. Fig. 2. Declining absorption spectra and corresponding digital image of 3.0 mL of 4.8×10-5 M methyl green upon injection of 10.0 µL of 5.7×10-6 M QD in ambient condition and pH=7.

16 Page 16 of 27

Fig. 3.(a) Effect of pH on degradation of 3.0 mL methyl green (4.8×10-5 M) upon injection of 10.0 µl QDs (5.7×10-6 M) in ambient condition. Absorbance values reflect absorption intensity at 632nm maxima. (b) Effect of quantity of QDs (5.7×10-6 M) on degradation kinetic of 3.0 mL

ip t

methyl green (4.8×10-5 M) at pH 5 and ambient condition. Fig. 4.Schematic representation of data matrix augmentation and bilinear decomposition using

cr

MCR-ALS.

Fig.5.(a)Concentration profiles resolved by MCR-ALS at different pH b) The resolved pure

us

spectra of methyl green and its degradation products.

Fig.6.Changes in the norm of the vectors of the concentration profiles of the identified species by

an

MCR-ALS as function of pH.

Ac ce p

te

d

M

Fig. 7. Structures of probable products of MG decomposition proposed by ref [54].

17 Page 17 of 27

Table 1. Calculated rate constants as function of pH for photodegradation of 3ml of 4.8×10-5 M Methyl green (MG) and 3ml of 4.8×10-5 M Malachite green (MaG) in presence of different

25 μL QD

10 μL QD

3

0.0098

0.0189

0.0075

4

0.0154

0.0464

0.0124

5

0.0764

0.2155

0.0575

6

0.2473

0.8091

0.1646

7

0.4836

1.1026

0.5015

0.5475

1.1494

0.6240

0.6221

1.1495

0.6811

8

Ac ce p

9

M

10 μL QD

an

us

MaG

d

MeG

te

pH

cr

ip t

quantities of CdSeQD (5.7×10-6 M).

18 Page 18 of 27

ip t us

b)

0.4 0.2

580

10 nm

te

Wavelength (nm ) Wavelength (nm)

630

d

530

Ac ce p

0 480

M

0.6

an

Fluorescence (a.u.)

0.8

Abs

Absorbance

1

cr

a) 1.2

c)

Figure 1 19 Page 19 of 27

ip t cr us an

90s 120s 150s 180s 210s

d

M

60s

te

30s

Ac ce p

Absorbance

0

Wavelength (nm)

Figure 2

20 Page 20 of 27

ip t cr us

a)

an

b

10µL QD 25µL QD

A b so r

te

d

M

A b so r

Ac ce p

Time (min)

Time (min)

Figure 3

21 Page 21 of 27

ip t cr us an M

pH=2

Ac ce p

pH=5

te

pH=4

d

pH=3

pH=6

pH=7

pH=8

pH=9

DAugment 22

CAugment

EAugment Page 22 of 27

C

pH =3

C

pH =4

C

pH =7

C

M

an

pH =2

us

cr

ip t

Figure 4

pH =8

C

pH =6

C

pH =9

C

te

C

Ac ce p

pH =5

d

Figure 6.

S

T

23 Page 23 of 27

M

an

us

cr

ip t

Figure 5

Ac ce p

te

d

Figure 6

24 Page 24 of 27

ip t cr us an M Ac ce p

te

d

Figure 7

25 Page 25 of 27

Ac ce p

te

d

M

an

us

cr

ip t

Graphical abstract

27 Page 26 of 27

Highlights  Starch-coated CdSe quantum dots were synthesized.

 The reactions could be conducted in dark.

cr

 In basic media more efficient catalytic activities was observed.

ip t

 They used as catalyst for degradation of two triphenylmethane dyes.

Ac ce p

te

d

M

an

us

 Chemometrics analysis revealed the contributions of different forms of reactants.

28 Page 27 of 27