Finite Dilution Inverse Gas Chromatography as a Versatile Tool To

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Finite dilution-inverse gas chromatography (FD-IGC) as a versatile tool to determine the surface properties of bio-fillers for plastic composite applications Zhitong Yao, Liuqin Ge, Wenye Yang, Meisheng Xia, Xiaosheng Ji, Meiqing Jin, Junhong Tang, and Jurgen Dienstmaier Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.5b01004 • Publication Date (Web): 28 May 2015 Downloaded from http://pubs.acs.org on June 4, 2015

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Analytical Chemistry

Finite dilution-inverse gas chromatography (FD-IGC) as a versatile tool to determine the surface properties of bio-fillers for plastic composite applications Zhitong Yao a, Liuqin Ge b, Wenye Yang b, Meisheng Xia b, Xiaosheng Ji b,*, Meiqing Jin a, Junhong Tang a,*, and Jürgen Dienstmaier c a

College of Materials Science and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China

b

Ocean College, Zhejiang University, Hangzhou 310058, China

c Surface Measurement Systems Ltd., 5 Wharfside, Rosemont Road, London, HA0 4PE, United Kingdom

*Corresponding authors. Tel./fax: +86 571 86919158 E-mail address: [email protected], [email protected] (X.S. Ji); [email protected] (J.H. Tang)

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ACS Paragon Plus Environment


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ABSTRACT: An improved understanding of a filler’s surface properties is important for determining the most effective polymer reinforcement fillers. In this work, the surface characteristics of two bio-fillers—namely clam shell modified by hydrochloric acid (AMF) and furfural (FMF)—were investigated using inverse gas chromatography (IGC). The IGC results showed that the dispersive surface energy ( γ SD ) contributed the major part to the total surface energy for the bio-fillers. The values changed as a function of surface coverages, meaning that both samples were energetically fairly heterogeneous. The γ SD calculated with the Dorris-Gray method was larger than that

γ SD , Dorris −Gray calculated with the Schultz method, with a ratio of 1.10. Compared to γ SD , Schultz AMF, FMF possessed higher γ SD value; however, this difference was compensated AB by γ S . Both samples predominantly interacted with ethanol and acetonitrile,

implying an amphoteric nature of the material surfaces. Gutmann acid and base number profiles indicated that the surfaces of both samples were more basic in nature. The FMF showed a lower WCohtotal value compared to the AMF, which could lead to an increase in composite performance. Keywords: Bio-filler; polymer matrix; plastic composite; dispersibility; surface energy; mechanical property

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1. Introduction Calcium carbonate (CaCO3) is one of the most widely used inorganic polymer fillers. However, adding excessive amounts of it frequently can decrease the impact properties of polymer.1-3 There is an ongoing need to develop new approaches to improving the mechanical properties of polymer with little or no increase in production cost. Bivalve shell waste, with its predominantly CaCO3 content and abundant availability, can be used as a potential substitute for commercial CaCO3, yielding a polymer with unique mechanical properties. Li et al. reported higher yield strength, tensile strength and elongation at break, of polypropylene (PP) composites filled with bio-aragonite derived from shell waste.4 Mustata et al. investigated the thermal properties of epoxy resin/conch shell composite. When bio-based CaCO3 was introduced, the glass transition temperature presented an increase at 10wt.% filler loading.5 De Melo et al. found that the incorporation of mollusk shell could increase the extent of crystallinity and stiffness of high-density polyethylene.6 Fombuena et al. also prepared epoxy resin composites filled with seashells of different bivalve mollusks.7 It has been widely recognized that the extent of reinforcement depends mainly on the nature of the fillers and polymers, filler loading and filler/matrix interfacial adhesion.8-12 Among them, the filler nature affects the reinforcement ability through the properties of surface activity, particle size, surface area, aggregate structure, surface functional groups, etc.13 The surface activity, for example, influences the reinforcement ability via its physicochemical properties, because the chemical nature of a particle’s surface determines the interactions both among fillers and between the fillers and the polymer matrix. These interactions in turn influence the filler’s dispersion in the matrix and thus affect the composites’ performance.14 Therefore, a

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better understanding of a filler’s surface properties is important to determining the most effective polymer reinforcement filler. For over 50 years, inverse gas chromatography (IGC) has been shown to be a powerful tool for evaluating the surface energy of solids. This technique typically takes the form of infinite dilution inverse gas chromatography (ID-IGC), or more recently, finite dilution inverse gas chromatography (FD-IGC).15 FD-IGC provides data over a wide range of probe surface coverages, yielding information about the relative heterogeneity of the surface energy distribution of a material. It has proved to be a reliable technique for determining the surface properties of different solid materials.16-20 The surface properties of commercial CaCO3 have been previously studied by IGC. Fekete et al. reported that CaCO3 coated with stearic acid showed relatively strong acidity.21 Jeong et al. examined the surface properties of CaCO3 with and without stearic acid treatment.22 Shi et al. determined the surface energy of precipitated CaCO3 and the results were consistent with those derived from other methods.23 In our previous work, the surface properties of nano-CaCO3 were also studied.24 However, to the best of our knowledge, reports on the surface properties of bio-fillers derived from bivalve shell waste are sparse. Thus, in this work we attempted to investigate the surface characteristics of clam shell waste modified by hydrochloric acid and furfural, with the aim of providing solid and valid bases for abundant shell waste recycling, especially for use in the plastics industry. 2. Basic IGC theory The basic theory of IGC is presented here and more details can be found elsewhere.24,25 In IGC, the term ‘‘inverse’’ indicates that the solids to be characterized are packed into the chromatographic column and this material is probed by gas mixtures injected into the column.26 The injection of known molecule probes,

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including both non-polar and polar probes, enables us to characterize the surface properties of the packed materials. Stationary-phase characterization can be achieved by partitioning the sample between the mobile phase and the stationary phase, indicated by the time taken to elute the samples. In IGC analysis, the surface energy has traditionally been determined at infinite dilution (or zero coverage), where probe concentrations were kept low to rule out lateral probe-probe interactions and favor probe-stationary phase interactions only.27 In this case, the injected gas probes interacted with only the highest-energy sites. However, in reality many real solid surfaces are heterogeneous and more likely to have a distribution of differing surface energy sites. The probe molecules should interact with both low- and high-energy sites, although the interactions should be dominated by the high-energy sites.28 Therefore, the development of methodologies to determine the surface energy distributions over the whole surface is essential in order to complete the surface energy characterization. To address this shortcoming, IGC analysis has been extended to finite concentrations,29-31 allowing the construction of adsorption isotherms for full surface characterization. These isotherms, covering a wider or even an entire adsorption range, can provide more in-depth information on adsorbate-adsorbent interactions, complement the analysis at infinite concentrations, and determine the surface energy distributions. 2.1 Surface energy The surface energy is defined as the average free energy per unit area surface of T a material. The total surface energy ( γ S ) is often the combination of dispersive

D

AB

surface energy ( γ S ) and specific (acid-base) surface energy ( γ S ). Dispersive (apolar) interactions, also known as Lifshitz-van der Waals interactions, consist of London, Keesom and Debye interactions. Specific (polar) interactions explain all other types of 5



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interactions, such as the acid-base interactions, hydrogen bonding or π bonding. A D standard method of surface characterization is that the γ S is first determined using a

series of linear alkane liquids (n-alkanes) as molecular probes; then the acid-base parameters can be calculated using acid-base liquid probes. 2.2 Dispersive interactions D The γ S analysis was performed by measuring the net retention volume (VN,

measured retention volume minus dead volume) for a series of n-alkanes (in this case, heptane, octane, nonane and decane). The dead volume was determined using methane, which does not interact significantly with samples under the chosen conditions. At each surface coverage (n/nm, where n is the amount adsorbed and nm is the monolayer adsorbed gas amount), the VN was calculated for each probe, and then the γ SD was calculated.28 For the calculation of γ SD , two methods—Dorris-Gray and Schultz methods—are usually used.32,33 More details of the two approaches can be found elsewhere.24,25 The dispersive results calculated from two methods were generally different at the same measuring conditions. Some data determined using Dorris–Gray method were larger than that calculated by Schultz method, while some results were opposite. In this study, the two approaches were both applied and the

γ SD, Dorris −Gray results were also compared using the ratio as a major index. γ SD, Schultz 2.3 Lewis acid/base interactions A comprehensive insight into the Lewis acid-base surface interactions can provide a better understanding of the influence of surface chemical-physical characteristics of the filler on the reinforcement properties of the polymer.34 To determine the contribution of acid-base properties of solids, polar probes must be injected into the packed column, in addition to non-polar probes. The acid-base 6


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properties are obtained by first measuring the specific free energies of adsorption (∆GSP) for the several polar probe molecules (in this case, ethanol, ethyl acetate, acetone, acetonitrile and dichloromethane). From the ∆GSP values, one can calculate acid-base numbers related to the specific surface energies. Two well-known concepts—the van Oss-Good-Chaudhury (vOGC) approach and Gutmann approach—can be used to determine the acid-base parameters.35,36 Based on the vOGC approach and applying the Della Volpe scale,37 γ SAB is subdivided into Lewis acid (electron acceptor, γ s+ ) and Lewis base (electron donor,

γ s− ) parameters of the surface tension. A parameter is calculated as the geometric mean of γ S+ and γ S− , which is determined from the injection of a pair of mono-functional acidic and basic probe molecules, such as dichloromethane ( γ l+ =124.58 mJ/m2, γ l− =0 mJ/m2) and ethyl acetate ( γ l− =475.67 mJ/m2, γ l+ =0 mJ/m2).38,39

The

Gutmann

approach,

on

the

other

hand,

represents

the

electron-accepting and electron-donating characteristics of the surface by the acid (Ka) and base (Kb) numbers and is routinely used to characterize the surface chemistry of samples. Ka and Kb reflect the ability of the examined surface to act as electron acceptor and electron donor, respectively. In this work, the Gutmann acid and base numbers for AMF and FMF were also determined. 3. Experimental 3.1 Raw materials Raw clam shell was collected from a seafood processing factory in Zhoushan city, China. It was first washed with tap water, removing the residual meat and attachments, and then coarsely ground. The ground sample was immersed in dilute NaOH solution, then washed until neutralization, and dried.

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3.2 Bio-fillers preparation Acid-modified filler (AMF): The pretreated clam shell powder was subjected to fine grinding using a stirring ball mill after adding 20 wt.% hydrochloric acid with a weight ratio of 1: 4. The ground powder was then dried and the acid-modified filler was prepared. Furfural-modified filler (FMF): The pretreated clam shell powder was also subjected to fine grinding using a ball mill after adding furfural with a weight ratio of 1: 5. The treated powder was then dried and the furfural-modified filler obtained. Particle size distribution analysis showed that the mean and median particle sizes of the AMF were 2.50 and 2.14 µm, respectively. Approximately 82% of the particles were less than 4 µm in diameter. For FMF, the mean and median particle sizes were 2.03 and 1.76 µm, respectively, and 93% of the particles were less than 4 µm. The BET specific surface areas of AMF and FMF were also determined as 3.51 and 3.86 m2/g, respectively. 3.3 PP composites preparation Before mixing, the PP matrix, AMF and FMF were dried in an oven. The PP and two fillers with various weight ratios (PP/filler ratios=100: 0, 95: 5, 93: 7, 90: 10, 85: 15, 80: 20 and 70: 30) were mixed with 0.2 wt.% antioxidant 168 using a Berstorff ZE-25 twin-screw extruder. The extrudates were then pelletized. Then, a vertical injection-molding machine was used to prepare the test specimens. Prior to the test, impact and tensile dumb-bell bars were conditioned at a temperature of 23 ± 2 ◦C and relative humidity of 50 ± 5% for 40 h. 3.4 Characterization and tests All surface energy analyses and specific surface area determinations were carried out using an iGC Surface Energy Analyzer (iGC-SEA, Surface Measurement Systems,

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Alperton, UK) and the data were analyzed using both standard and advanced SEA analysis software. The detailed procedure is described in the Supporting Information. The data were fitted using an exponential association function in the Origin 8.0 software. The particle size distribution was determined using a Beckman LS13320 laser particle size analyzer. The mechanical tests of bio-filler/PP composites were conducted according to the ASTM D638 standard. 4. Results and discussion 4.1 Surface energies and distributions D AB T The combined plot of γ S , γ S and γ S profiles of AMF and FMF powders

obtained directly from the iGC-SEA are displayed in Figure 1. The profiles showed D that the γ S of the two fillers contributed the major part of the total surface energy. In

addition, these values changed as a function of surface coverages, meaning that the D samples were energetically fairly heterogeneous. For both fillers, the γ S displayed a

decreasing trend with an increase in the surface coverages, and the highest energetic sites occupied approximately 0.5% of the fillers. However, the decreasing trend was not significant when the surface coverage was larger than 0.06. The difference in D measured absolute γ S values at low and high coverages indicated significant

heterogeneity among the surface energy sites—those at highest-energetic sites showing approximately 32% higher absolute values of surface energy compared to the lowest-energetic sites. Bivalve shell wastes are heterogeneous and rough, consisting mainly of an outer periostracum, a middle prismatic layer and an inner nacreous layer. As a relatively heterogeneous material, the VN of AMF and FMF decreased with increasing surface coverage, because the high-energy sites were first taken up by probe molecules at low surface coverages; increasing the surface coverage led to the

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adsorption on lower-energy sites by the probe. The interaction between the alkane probes and the less energetic sites at high surface coverage was weaker.18,25,40,41 As D compared to AMF, FMF was more active, possessing slightly higher γ S across most

surface coverages measured. D However, this difference in the γ S was compensated for by AMF, which had

AB D AB T higher γ S than FMF, and in the end γ S and γ S added up to very similar γ S AB values for both samples. Nonetheless, AMF had narrower range of γ S values as D AB compared to FMF. Compared with the γ S component, the γ S components of AMF

and FMF contributed about 19% and 17% of the total surface energy, respectively, implying a lower wettability of both samples. This was consistent with the results from contact angle measurement in our previous study,42 where both AMF and FMF were determined to be amphiphilic. The AMF and FMF showed water contact angles of 45.5 and 36.3, respectively. By contrast, alcohol spread out over the surface of both AB samples. The γ S at each surface coverage was calculated from the basic γ s− and

acid γ s+ components of surface energy using the vOGC concept. As compared to the

γ s− component, the γ s+ component of surface energy of both samples decreased remarkably at lower surface coverages when it was conducted at finite dilution. T The γ S was also found to significantly decrease at lower surface coverages, and T D a similar trend was displayed for both samples. As the γ S is a combination of γ S

AB D and γ S , the greater increase in γ S at larger surface coverages for FMF resulted in T an increase in γ S . Thus, the two fillers had similar surface energies, indicating that

the differing treatment process had not significantly affected their surface energies. 10


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Surface energy values are inherently independent of surface area and particle size. For some materials (such as silica and fiber), high surface area is associated with high surface energy.11,34 However, this is not always true because a larger surface area implies a larger number of units, whereas higher surface energy means a higher concentration of active sites or even a change in composition per unit surface. From a theoretical standpoint, changes in surface roughness alone will not affect surface energy. However, the orientation and interaction of IGC probe molecules can vary slightly if surface roughness is of the same magnitude as the molecular probe diameters (i.e., ~5-10 Å). Therefore, surface roughness effects on measured surface energy values measured by IGC cannot be completely dismissed.40 Overall, the measured increased surface energy is due not merely to structural variations, but also to changes in the density or type of functional groups orientated on the surface. Bivalve shells consist typically of three separate layers: an outer periostracum, a middle prismatic layer and an inner nacreous layer. A small amount of biomacromolecules, including polysaccharides, proteins and glycoproteins are also present in both inter- and intra-crystalline locations within the nacre structure. Furthermore, it is believed that structural defects could be formed during shell waste modification. The energetic surface sites that interacted with the probes were heterogeneous, enhancing the adsorption of probes with greater surface coverage. The FMF had a relatively smaller particle size and larger BET specific surface area, which might contributed to its higher surface energy. From the above results, it can be inferred that the FMF will reduce the particle-particle interactions, allowing its better dispersion in a polymer matrix.

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Figure 1. Surface energy profiles of AMF and FMF as a function of surface coverages 4.2 Dispersive surface energy profiles The dispersive surface energy profiles of AMF and FMF determined using both Dorris-Gray and Schultz methods are illuminated in Figure 2. For AMF, the calculated

γ SD fell into the ranges of 43.41-64.20 mJ/m2 and 39.38-58.23 mJ/m2, for

the Dorris-Gray and Schultz methods, respectively. For FMF, the values were in the ranges of 44.48-66.29 mJ/m2 and 40.35-59.98 mJ/m2, respectively. This result was consistent with the report of 44.6 mJ/m2 at 30 °C for CaCO3.43 However, it is worth noting that the

γ SD mainly depends on the nature, origin, and surface composition of

D the CaCO3 powders and test temperature. Schmitt et al. reported that the γ S of

CaCO3 was 44.4 mJ/m2 at 70 °C, and 45.1 mJ/m2 at 99 °C, not showing significant 12


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changes related to the test temperatures; while for the stearic acid-treated CaCO3, the

γ SD values decreased with increasing temperature and were 29 mJ/m2 at 70°C and 18 mJ/m2 at 99°C.2 In addition, the modification of precipitated CaCO3 with chemicals D such as hydroxyacids or silanes could decrease the γ S in most cases.44 The work of

Papirer et al. revealed a drastic decrease in surface energy as the CaCO3 surface was progressively coated with stearic acid, and concluded that the modified surface became more uniform and less polar.45 Jeong et al. also examined the surface D properties of stearic acid-treated CaCO3 and found that the γ S of treated powder

was considerably lower than that of untreated powder.22

Figure 2. Dispersive surface energy profiles of AMF and FMF as a function of surface coverages In order to compare the results calculated by the Dorris-Gray and Schultz 13



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γ SD, Dorris −Gray methods, the ratio was calculated in this work. It was determined as 1.10 γ SD,Schultz for both fillers over the surface coverage of 0.005-0.15. In other words, the γ SD value calculated by the Dorris-Gray method was larger than that calculated by the Schultz method. According to the literatures,46-48 the results calculated from the two methods are generally different under the same measuring conditions. The difference between the two results depends on n-alkane series and becomes significant with an increase in the measuring temperature.49 The values from the Dorris-Gray method were mostly larger than those from the Schultz method. Mohammad reported a ratio of 1.05 for mannitol.49 Gamelas et al. calculated the γ SD of kaolinitic materials and found that the ratio was approximately 1.2.46 Shi et al. calculated the

γ SD, Dorris −Gray ratio at three γ SD, Schultz

temperatures and found that the ratio increased from 1.02 to 1.06 as temperatures

γ SD, Dorris −Gray increased from 30 to 50°C. Topaloğlu Yazıcı et al. calculated the ratio at γ SD, Schultz 47

five temperatures (30, 35, 40, 45 and 50°C) and found that the ratio increased from 1.06 to 1.10 as temperatures increased.50 As a compasion, Voelkel and Strzemiecka reported that the γ SD values from the Dorris-Gray method were generally lower than those from the Schultz method. 51 4.3 Specific free energy profiles The surface properties of fillers also depend on the ability to participate in specific interactions resulting from the presence of polar functional groups on the surface of the material. The Gutmann theory accommodates the amphoteric nature of bipolar compounds and is routinely used to characterize the surface chemistry of samples and applied to determine the electron donor–acceptor properties of the

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material surfaces via IGC. The Gutmann acid (Ka) and base (Kb) numbers were used for characterization of the acidity or basicity of the surface layer of fillers. The dimensionless Ka and Kb values of the samples were calculated by first measuring the ∆GSP values of polar probes (ethanol, acetonitrile, acetone, ethyl acetate, and

dichloromethane) at surface coverages (0.005-0.15). The ∆GSP profiles resulting from the interactions with five polar probe molecules for AMF and FMF are displayed in Figure 3. The

∆GSP

changed with surface coverages, confirming the

heterogeneous nature of the samples, especially for FMF. Higher ∆GSP values can be attributed to a higher concentration of polar surface groups or different surface groups with higher specific surface energy. This was consistent with the results from FT-IR analysis in our previous study,42 where C-O stretching vibrations located at 1153 and 1147 cm-1 increased significantly for FMF as compared with AMF. This indicated that furfural modification increased the number of functional groups in the filler and thus could improve its dispersability in the PP matrix. In Figure 3, similar curves were generated for the AMF and the FMF. Both samples also showed strong degrees of interaction with all the polar probes, but predominantly interacted with ethanol and acetonitrile, and to a lesser extent with dicholoromethane. Acetonitrile and ethanol are bifunctional probes, with the former being slightly basic and the latter being slightly acidic.40 Stronger interaction with these probes confirmed that the material surfaces were amphoteric in nature. Thus the amphoteric nature of the samples’ surfaces was established. The ranking for decreasing

∆GSP

interactions was: ethanol (amphoteric probe) > acetonitrile

(amphoteric probe) > acetone (amphoteric probe) > ethyl acetate (amphoteric probe) > dichloromethane (acidic probe). 15



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In this work, Ka and Kb were determined as 0.18~0.29 and 0.47~0.54, respectively, for AMF over the surface coverages (see Figure 4). For FMF, the values were calculated as 0.14~0.24 and 0.47~0.62, across the entire surface coverage range measured. The Ka/Kb ratios were determined as 0.38~0.53 and 0.28~0.38 for AMF and FMF, respectively. The Kb for the samples was consistently higher than Ka, indicating that the surfaces of both samples were more basic in nature. This meant that both samples, especially FMF, possess marginally higher concentrations of electron-donating surface functional groups.

Figure 3. Specific free energy profiles of different solvents for AMF and FMF as a function of surface coverages

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Figure 4. Gutmann acid and base number profiles of AMF and FMF as a function of surface coverages 4.4 Total work of cohesion profiles Surface energy is defined as the energy required to form (or increase) a unit area of surface under reversible conditions.52 Knowledge of the surface energies between filler particles would allow an objective decision to be made about the extent of filler-polymer interaction. If the redistributed filler particles on the surface of polymer allowed the filler particles to be more easily detached from the polymer surface than from an agglomerate of filler, then the presence of polymer particles could facilitate dispersion. The extent of the interaction between filler particles could be quantified by the total work of cohesion (WCohtotal), which in turn can be determined by IGC.53 The plot of WCohtotal for AMF and FMF is shown in Figure 5. The WCohtotal between filler particles was determined as 107.13-159.45 mJ/m2 for AMF and 17



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111.78-168.35 mJ/m2 for FMF. The AMF showed a higher WCohtotal value compared to the FMF at surface coverages of 0.02, 0.03, 0.04, 0.08 and 0.10, indicating stronger filler-filler interactions, which could lead to a decrease in composite performance. It is worth noting that, the work of adhesion of fillers to polymers, the spreading coefficient of the filler over the polymer and the interfacial tensions between the fillers and the polymer also affect composites performance. These factors will be considered in future work.

Figure 5. Total work of cohesion profiles of AMF and FMF as a function of surface coverage 5. Conclusion Bivalve shell waste, with its predominantly CaCO3 content plus a small amount of biomacromolecules, can be used as a substitute for commercial polymer filler. An improved understanding of the filler’s surface properties is important for determining 18


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the most effective polymer reinforcement fillers. In this work, the surface properties of clam shell waste modified by hydrochloric acid (AMF) and furfural (FMF), including surface energy, acid-base character, and total work of cohesion were investigated. The results showed that the γ SD contributed the major part of the total surface energy for both samples. The γ SD calculated with the Dorris-Gray method

was larger than that calculated with the Schultz method, with a

γ sd , Dorris −Gray γ sd , Schultz

1.10. As compared to AMF, FMF was more active, possessing higher

ratio of

γ SD across

most surface coverages. The ∆GSP changed with surface coverages, confirming the heterogeneous nature of the samples, especially for FMF. Both samples predominantly interacted with ethanol and acetonitrile, implying an amphoteric nature of the material surfaces. The Kb for the samples was consistently higher than Ka, indicating that the surfaces of both samples are more basic in nature. The FMF showed a lower WCohtotal value compared to the AMF, which could lead to an increase in composite performance. The work of adhesion of fillers to polymers, the spreading coefficient of the filler over the polymer and the interfacial tensions between the fillers and the polymer also affect composites performance. These factors will be considered in future work. Acknowledgements The authors gratefully acknowledge financial support from the Zhejiang Provincial Natural Science Foundation of China (Grant no. LQ13B070005) and National Natural Science Foundation of China (Grant no. 41373121 and 21407038). We would like to thank Dr. Jürgen Dienstmaier (Surface Measurement Systems Ltd.) for his help in the iGC-SEA measurement. We would also like to thank the

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anonymous referees for their helpful comments on our manuscript.

Supporting information：： This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Adeosun, S. O.; Usman, M. A.; Ayoola, W. A.; Bodud, M. A. J. Min. Mater. Charact. Eng. 2013, 1, 145-152.

(2) Schmitt, P.; Koerper, E.; Schultz, J.; Papirer, E. Chromatographia 1988, 25: 786-790. (3) Eiras, D.; Pessan, L. A. Mater. Res. 2009, 12, 517-522. (4) Li, H. Y.; Tan, Y. Q.; Zhang, L.; Zhang, Y. X.; Song, Y. H.; Ye, Y.; Xia, M. S. J. Hazard. Mater. 2012, 217-218, 256-262.

(5) Mustata, F.; Tudorachi, N.; Rosu, D. Compos Part B: Eng. 2012, 43, 702-710. (6) de Melo, P. M. A.; Silva, L. B.; Santos, A. S. F.; Passos, T. A.; Lima, S. J. G.; Ueki, M. M. In Evaluation of thermal and mechanical behavior of HDPE/mollusk shell composites prepared in single screw extruder; Proceedings of 22nd

International Congress of Mechanical Engineering (COBEM 2013), November 3-7, 2013, SP, Brazil, pp 3757-3762. (7) Fombuena, V.; Bernardi, L.; Fenollar, O.; Boronat, T.; Balart, R. Mater. Des. 2014, 57, 168-174. (8) Mohamed, M. A.; Shaltout, N. A.; El Miligy, A. A. Arab. J. Chem. 2011, 4, 71-77. (9) Gupta, A.; Kumar, A.; Patnaik, A.; Biswas, S. J. Surf. Eng. Mater. Adv. Technol. 2012, 2, 149-157. (10) Dominic, C. D. M.; Begum, P. M. S.; Joseph, R.; Jose, A. R. Int. J. Adv. Sci. Technol. Res. 2014, 4, 561-569.

(11) Zhang, W. J.; Leonov, A. I. J. Appl. Polym. Sci. 2001, 81, 2517-2530. 20


Page 21 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(12) Fu, S. Y.; Feng, X. Q.; Laukec, B.; Maid, Y. W. Compos. Part B: Eng. 2008, 39, 933-961. (13) Aderikha, V. N.; Shapovalov, V. A. Wear 2010, 268, 1455-1464. (14) Ray, S.; Bhowmick, A. K. Polym. Eng. Sci. 2004, 44, 163-178. (15) Voelkel, A.; Strzemiecka, B.; Adamska, K.; Milczewska, K. J. Chromatogr. A 2009, 1216, 1551-1566. (16) Smith, R. R.; Williams, D. R.; Burnett, D. J.; Heng, J. Y. Y. Langmuir 2014, 30, 8029-8035. (17) Shah, U. V.; Olusanmi, D.; Narang, A. S.; Hussain, M. A.; Gamble, J. F.; Tobyn, M. J.; Heng, J. Y. Y. Int. J. Pharm. 2014, 472, 140-147. (18) Ho, R.; Hinder, S. J.; Watts, J. F.; Dilworth, S. E.; Williams, D. R.; Heng, J. Y. Y. Int. J. Pharm. 2010, 387, 79-86.

(19) Donnet, J. B.; Custodéro, E.; Wang, T. K.; Hennebert, G. Carbon 2002, 40, 163-167. (20) Thielmann, F.; Butler, D. A.; Williams, D. R. Colloid. Surfaces A 2001, 187-188, 267-272. (21) Fekete, E.; Móczó, J.; Pukánszky, B. J. Colloid. Interf. Sci. 2004, 269, 143-152. (22) Jeong, S. B.; Yang, Y. C.; Chae, Y. B.; Kim, B. G. Mater. Trans. 2009, 50, 409-414. (23) Shi, X. T.; Bertóti, I.; Pukánszky, B.; Rosa, R.; Lazzeri, A. J. Colloid. Interf. Sci. 2011, 362, 67-73. (24) Yao, Z. T.; Ge, L. Q.; Ji, X. S.; Tang, J. H.; Xia, M. S.; Xi, Y. Q. J. Alloy Compd. 2015, 621, 389-395. (25) Mohammadi-Jam, S.; Waters, K. E. Adv. Colloid Interface 2014, 212, 21-44. (26) Perruchot, C.; Chehimi, M. M.; Vaulay, M. J.; Benzarti, K. Cem. Concr. Res. 2006,

21



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 24

36, 305-319.

(27) Voelkel, A. Chemometr. Intell. Lab. 2004, 72, 205-207. (28) Das, S. C.; Stewart, P. J. J. Pharm. Pharmacol. 2012, 64, 1337-1348. (29) Thielmann, F.; Burnett, D. J.; Heng, J. Y. Y. Drug Dev. Ind. Pharm. 2007, 33, 1240-1253. (30) Ylä-Mäihäniemi, P. P.; Heng, J. Y. Y.; Thielmann, F.; Williams, D. R. Langmuir 2008, 24, 9551-9557. (31) Tong, H. H. Y.; Shekunov, B. Y.; York, P.; Chow, A. H. L. J. Pharm. Sci. 2005, 94, 695-700. (32) Dorris, G. M.; Gray, D. G. J. Colloid Interface Sci. 1980, 77, 353-362. (33) Schultz, L.; Lavielle, C.; Martin, J. J. Adhes. 1987, 23, 45-60. (34) Cordeiro, N.; Gouveia, C.; Moraes, A. G. O.; Amico, S. C. Carbohyd. Polym. 2011, 84, 110-117. (35) Van Oss, C. J.; Good, R. J.; Chaudhury, M. K. Langmuir 1988, 4, 884-891. (36) Gutmann, V. The Donor–Acceptor Approach to Molecular Interactions; Plenum Press: New York, 1978. (37) Della Volpe, C.; Siboni, S. J. Colloid Interf. Sci 1997, 195, 121-136. (38) Tewes, F.; Gobbo, O. L.; Amaro, M. I.; Tajber, L.; Corrigan, O. I.; Ehrhardt, C.; Healy, A. M. Mol. Pharm. 2011, 8, 1887-1898. (39) Ali, S. S. M.; Heng, J. Y. Y.; Nikolaev, A. A.; Waters, K. E. Powder Technol. 2013, 249, 373-377.

(40) Burnett, D. J.; Khoo, J.; Naderi, M.; Heng, J. Y. Y.; Wang, G. D.; Thielmann, F. AAPS PharmSciTech. 2015, 13, 1511-1517.

(41) Lapčík, L.; Otyepková, E.; Lapčíková, B.; Otyepka, M. Colloid Surface A 2013, 436, 1170-1174.

22


Page 23 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(42) Yao, Z. T.; Xia, M. S.; Ge, L. Q.; Chen, T.; Li, H. Y.; Ye, Y.; Zheng, H. Fiber. Polym. 2014, 15, 1278-1287.

(43) Schreiber, H. P.; Saint Germain, F. J. Adhes. Sci. Technol. 1990, 4, 319-331. (44) Ahsan, T.; Colenutt, B. A.; Sing, K. S. W. J. Chromatogr. A 1991, 464, 416-421. (45) Papirer, E.; Schultz, J.; Turchi, C. Eur. Polm. J. 1984, 20, 1155-1158. (46) Gamelas, J. A. F.; Ferraz, E.; Rocha, F. Colloid. Surface A 2014, 455, 49-57. (47) Shi, B. L.; Wang, Y.; Jia, L. N. J. Chromatogr. A 2011, 1218, 860-862. (48) Bilgiç, C.; Tümsek, F. J. Chromatogr. A 2007, 1162, 83-89. (49) Mohammad, M. A. J. Chromatogr. A 2013, 1318, 270-275. (50) Topaloğlu Yazıcı, D.; Aşkın, A.; Bütün, V. Surf. Interface Anal. 2006, 38, 561-564. (51) Voelkel, A.; Strzemiecka, B. Int. J. Adhes. Adhes. 2007, 27, 188-194. (52) Arsalan, N.; Buiting, J. J.; Nguyen, Q. P. Colloid. Surface A 2015, 467, 107-112. (53) Swaminathan, V.; Cobb, J.; Saracovan, I. Int. J. Pharm. 2006, 312, 158-165.

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For TOC only

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Finite Dilution Inverse Gas Chromatography as a Versatile Tool To

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