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Do MH, Dubreuil B, Peydecastaing J, Vaca-Medina G, Nhu-Trang TT, Jaffrezic-Renault N, Behra P. Chitosan-Based Nanocomposites for Glyphosate Detection Using Surface Plasmon Resonance Sensor. SENSORS 2020; 20:s20205942. [PMID: 33096666 PMCID: PMC7589946 DOI: 10.3390/s20205942] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 10/12/2020] [Accepted: 10/14/2020] [Indexed: 01/28/2023]
Abstract
This article describes an optical method based on the association of surface plasmon resonance (SPR) with chitosan (CS) film and its nanocomposites, including zinc oxide (ZnO) or graphene oxide (GO) for glyphosate detection. CS and CS/ZnO or CS/GO thin films were deposited on an Au chip using the spin coating technique. The characterization, morphology, and composition of these films were performed by Fourier-transform infrared spectroscopy (FTIR), atomic force microscopy (AFM), and contact angle technique. Sensor preparation conditions including the cross-linking and mobile phase (pH and salinity) were investigated and thoroughly optimized. Results showed that the CS/ZnO thin-film composite provides the highest sensitivity for glyphosate sensing with a low detection limit of 8 nM and with high reproducibility. From the Langmuir-type adsorption model and the effect of ionic strength, the adsorption mechanisms of glyphosate could be controlled by electrostatic and steric interaction with possible formation of 1:1 outer-sphere surface complexes. The selectivity of the optical method was investigated with respect to the sorption of glyphosate metabolite (aminomethylphosphonic acid) (AMPA), glufosinate, and one of the glufonisate metabolites (3-methyl-phosphinico-propionic acid) (MPPA). Results showed that the SPR sensor offers a very good selectivity for glyphosate, but the competition of other molecules could still occur in aqueous systems.
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Affiliation(s)
- Minh Huy Do
- Laboratoire de Chimie Agro-industrielle, LCA, Université de Toulouse, INRAE, 31030 Toulouse CEDEX 4, France; (M.H.D.); (B.D.); (J.P.); (G.V.-M.)
- “Water–Environment–Oceanography” Department, University of Science and Technology of Hanoi (USTH), Vietnam Academy of Science and Technology (VAST), 100000 Hanoi, Vietnam
| | - Brigitte Dubreuil
- Laboratoire de Chimie Agro-industrielle, LCA, Université de Toulouse, INRAE, 31030 Toulouse CEDEX 4, France; (M.H.D.); (B.D.); (J.P.); (G.V.-M.)
| | - Jérôme Peydecastaing
- Laboratoire de Chimie Agro-industrielle, LCA, Université de Toulouse, INRAE, 31030 Toulouse CEDEX 4, France; (M.H.D.); (B.D.); (J.P.); (G.V.-M.)
| | - Guadalupe Vaca-Medina
- Laboratoire de Chimie Agro-industrielle, LCA, Université de Toulouse, INRAE, 31030 Toulouse CEDEX 4, France; (M.H.D.); (B.D.); (J.P.); (G.V.-M.)
- Centre d’Application et de Traitement des Agroressources (CATAR), Université de Toulouse, 31030 Toulouse CEDEX 4, France
| | - Tran-Thi Nhu-Trang
- Faculty of Environmental and Food Engineering, Nguyen Tat Thanh University (NTTU), 700000 Ho Chi Minh, Vietnam;
| | - Nicole Jaffrezic-Renault
- Institute of Analytical Sciences, UMR 5280 CNRS-Université Claude Bernard, 69100 Villeurbanne, France;
| | - Philippe Behra
- Laboratoire de Chimie Agro-industrielle, LCA, Université de Toulouse, INRAE, 31030 Toulouse CEDEX 4, France; (M.H.D.); (B.D.); (J.P.); (G.V.-M.)
- “Water–Environment–Oceanography” Department, University of Science and Technology of Hanoi (USTH), Vietnam Academy of Science and Technology (VAST), 100000 Hanoi, Vietnam
- Correspondence:
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Cano T, Offringa N, Willson RC. The effectiveness of three multi-component binding models in describing the binary competitive equilibrium adsorption of two cytochrome b(5) mutants. J Chromatogr A 2007; 1144:197-202. [PMID: 17303149 DOI: 10.1016/j.chroma.2007.01.059] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2006] [Revised: 01/09/2007] [Accepted: 01/11/2007] [Indexed: 11/26/2022]
Abstract
Competitive adsorption isotherms for two conservative surface charge-neutralizing mutants of cytochrome b(5), E11Q and E44Q, previously measured with competitor concentration held constant over the range of the isotherm, were used to test three widely-used multi-component isotherm models. The extended Langmuir-Freundlich, Langmuir and Jovanovic-Freundlich models each adequately described the weaker infinite dilution adsorption of the E44Q protein in the presence of the strong binding E11Q. The extended Langmuir-Freundlich model generally gave the lowest errors at higher concentrations, and the Jovanovic-Freundlich model gave the best fits when using empirically optimized maximal loading values based on multi-component as well as pure-component isotherm data.
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Affiliation(s)
- Tony Cano
- Department of Chemical Engineering, University of Houston, 4800 Calhoun Ave., Houston, TX 77204-4004, USA
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Abstract
A fractal analysis of a confirmative nature only is presented for the binding of estrogen receptor (ER) in solution to its corresponding DNA (estrogen response element, ERE) immobilized on a sensor chip surface [J. Biol. Chem. 272 (1997) 11384], and for the cooperative binding of human 1,25-dihydroxyvitamin D(3) receptor (VDR) to DNA with the 9-cis-retinoic acid receptor (RXR) [Biochemistry 35 (1996) 3309]. Ligands were also used to modulate the first reaction. Data taken from the literature may be modeled by using a single- or a dual-fractal analysis. Relationships are presented for the binding rate coefficient as a function of either the analyte concentration in solution or the fractal dimension that exists on the biosensor surface. The binding rate expressions developed exhibit a wide range of dependence on the degree of heterogeneity that exists on the surface, ranging from sensitive (order of dependence equal to 1.202) to very sensitive (order of dependence equal to 12.239). In general, the binding rate coefficient increases as the degree of heterogeneity or the fractal dimension of the surface increases. The predictive relationships presented provide further physical insights into the reactions occurring on the biosensor surface. Even though these reactions are occurring on the biosensor surface, the relationships presented should assist in understanding and in possibly manipulating the reactions occurring on cellular surfaces.
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Affiliation(s)
- Ajit Sadana
- Chemical Engineering Department, University of Mississippi, Post Office Box 1848, University, MS 38677-1848, USA.
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Butala HD, Sadana A. A fractal analysis of analyte-estrogen receptor binding and dissociation kinetics using biosensors: environmental effects. J Colloid Interface Sci 2003; 263:420-31. [PMID: 12909031 DOI: 10.1016/s0021-9797(03)00338-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
A fractal analysis is used to model the binding and dissociation kinetics between analytes in solution and estrogen receptors (ER) immobilized on a sensor chip of a surface plasmon resonance (SPR) biosensor. Both cases are analyzed: unliganded as well as liganded. The influence of different ligands is also analyzed. A better understanding of the kinetics provides physical insights into the interactions and suggests means by which appropriate interactions (to promote correct signaling) and inappropriate interactions such as with xenoestrogens (to minimize inappropriate signaling and signaling deleterious to health) may be better controlled. The fractal approach is applied to analyte-ER interaction data available in the literature. Numerical values obtained for the binding and the dissociation rate coefficients are linked to the degree of roughness or heterogeneity (fractal dimension, D(f)) present on the biosensor chip surface. In general, the binding and the dissociation rate coefficients are very sensitive to the degree of heterogeneity on the surface. For example, the binding rate coefficient, k, exhibits a 4.60 order of dependence on the fractal dimension, D(f), for the binding of unliganded and liganded VDR mixed with GST-RXR in solution to Spp-1 VDRE (1,25-dihydroxyvitamin D(3) receptor element) DNA immobilized on a sensor chip surface (Cheskis and Freedman, Biochemistry 35 (1996) 3300-3318). A single-fractal analysis is adequate in some cases. In others (that exhibit complexities in the binding or the dissociation curves) a dual-fractal analysis is required to obtain a better fit. A predictive relationship is also presented for the ratio K(A)(=k/k(d)) as a function of the ratio of the fractal dimensions (D(f)/D(fd)). This has biomedical and environmental implications in that the dissociation and binding rate coefficients may be used to alleviate deleterious effects or enhance beneficial effects by selective modulation of the surface. The K(A) exhibits a 112-order dependence on the ratio of the fractal dimensions for the ligand effects on VDR-RXR interaction with specific DNA.
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Affiliation(s)
- Harshala D Butala
- Chemical Engineering Department, University of Mississippi, MS 38677-1848, USA.
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Ramakrishnan A, Sadana A. A mathematical analysis using fractals for binding interactions of nuclear estrogen receptors occurring on biosensor surfaces. Anal Biochem 2002; 303:78-92. [PMID: 11906154 DOI: 10.1006/abio.2002.5581] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
A mathematical approach using fractal concepts is presented for modeling the binding and dissociation interactions between analytes and nuclear estrogen receptors (ER) occurring on surface plasmon resonance biosensor chip surfaces. A kinetic knowledge of the binding interactions mediated by ER would help in better understanding the carcinogenicity of these steroidogenic compounds and assist in modulating these reactions. The fractal approach is applied to analyte-ER interaction data obtained from literature. Numerical values obtained for the binding and dissociation rate coefficients are linked to the degree of roughness or heterogeneity (fractal dimension, D(f)) present on the biosensor surface. For example, a single-fractal analysis is used to describe the binding and dissociation phases for the binding of estradiol and ERalpha in solution to clone 31 protein immobilized on a biosensor chip (C-S. Suen et al., 1998, J. Biol. Chem. 273(42), 27645-27653). The binding and the dissociation rate coefficients are 27.57 and 8.813, respectively, and the corresponding fractal dimensions are 1.986 and 2.268, respectively. In some examples dual-fractal models were employed to obtain a better fit of either the association or the dissociation phases or for both. Predictive relationships are developed for (a) the binding and the dissociation rate coefficients as a function of their respective fractal dimensions and (b) the ratio K(A) (= k/k(d)) as a function of the ratio of the fractal dimensions (D(f)/D(fd)). The analysis should provide further physical insights into the ER-mediated interactions occurring on biosensor and other surfaces.
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Affiliation(s)
- Anand Ramakrishnan
- Chemical Engineering Department, University of Mississippi, University, MS 38677-1848, USA
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Podkościelny P, Dąbrowski A, Leboda R. Fractal approach of adsorption from liquid mixtures on silica gel. Colloids Surf A Physicochem Eng Asp 2001. [DOI: 10.1016/s0927-7757(00)00844-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Ramakrishnan A, Sadana A. Analyte-receptor binding and dissociation kinetics for biosensor applications: a fractal analysis. Biosens Bioelectron 2001; 15:651-62. [PMID: 11213226 DOI: 10.1016/s0956-5663(00)00124-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
A fractal analysis of confirmative nature only is presented for analyte-receptor binding and dissociation kinetics for biosensor applications. Data taken from the literature may be modeled, in the case of binding using a single-fractal analysis or a dual-fractal analysis. The dual-fractal analysis represents a change in the binding mechanism as the reaction progresses on the surface. Relationships are presented for the binding and dissociation rate coefficients as a function of their corresponding fractal dimension, Df or the degree of heterogeneity that exists on the surface. When analyte-receptor binding or dissociation is involved, an increase in the heterogeneity on the surface (increase in Df) leads to an increase in the binding and in the dissociation rate coefficient. It is suggested that an increase in the degree of heterogeneity on the surface leads to an increase in the turbulence on the surface owing to the irregularities on the surface. This turbulence promotes mixing, minimizes diffusional limitations, and leads subsequently to an increase in the binding and in the dissociation rate coefficient (Martin S.J., Granstaff, V.E., Frye, G.C., Anal. Chem., 65, (1991) 2910). The binding and the dissociation rate coefficient are rather sensitive to the degree of heterogeneity, Df,bind and Df,diss respectively, that exists on the biosensor surface. For example, the order of dependence on Df,bind is 19.2 for the binding rate coefficient, kbind for the binding of 0.03-1.0 microM SH-2Ld in solution to 2C TCR immobilized on a surface plasmon resonance (SPR) biosensor (Corr, M., Salnetz, A.E., Boyd, L.F., Jelonek, M.T., Khilko, S., Al-Ramadi, B.K., Kim, Y.S., Maher, S.E., Bothwell, A.L.M., Margulies, D.H., Science, 265, (1994) 946). The order of dependence on Df,diss is -6.22 for the dissociation rate coefficient, kdiss for the dissociation of 250-1000 nM Sophora japonica agglutinin (SJA)-lactose complex from the SPR surface. In general, the technique is applicable to other reactions occurring on different types of surfaces, such as cell-surface reactions.
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Affiliation(s)
- A Ramakrishnan
- Chemical Engineering Department, University of Mississippi, MS 38677-1848, USA
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Sadana A. A kinetic study of analyte-receptor binding and dissociation, and dissociation alone, for biosensor applications: a fractal analysis. Anal Biochem 2001; 291:34-47. [PMID: 11262154 DOI: 10.1006/abio.2000.4981] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
A fractal analysis is presented for (a) analyte-receptor binding and dissociation kinetics and (b) dissociation kinetics alone for biosensor applications. Emphasis is placed on dissociation kinetics. Data taken from the literature may be modeled, in the case of binding, using a single-fractal analysis or a dual-fractal analysis. The dual-fractal analysis represents a change in the binding mechanism as the reaction progresses on the surface. A single-fractal analysis is adequate to model the dissociation kinetics in the examples presented. Predictive relationships developed for the dissociation rate coefficient(s) as a function of the analyte concentration are of particular value since they provide a means by which the dissociation rate coefficients may be manipulated. Relationships are also presented for the binding and dissociation rate coefficients as a function of their corresponding fractal dimension, D(f), or the degree of heterogeneity that exists on the surface. When analyte-receptor binding or dissociation is involved, an increase in the heterogeneity on the surface (increase in D(f)) leads to an increase in the binding and in the dissociation rate coefficient.
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Affiliation(s)
- A Sadana
- Chemical Engineering Department, University of Mississippi, University, MS 38677-1848, USA
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Sadana A, Ramakrishnan A. A Fractal Analysis Approach for the Evaluation of Hybridization Kinetics in Biosensors. J Colloid Interface Sci 2001; 234:9-18. [PMID: 11161484 DOI: 10.1006/jcis.2000.7274] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The diffusion-limited hybridization kinetics of analyte in solution to a receptor immobilized on a biosensor or immunosensor surface is analyzed within a fractal framework. The data may be analyzed by a single- or a dual-fractal analysis. This was indicated by the regression analysis provided by Sigmaplot (Sigmaplot, Scientific Graphing Software, User's Manual, Jandel Scientific, CA, 1993). It is of interest to note that the binding rate coefficient and the fractal dimension both exhibit changes, in general, in the same direction for both the single-fractal and the dual-fractal analysis examples presented. The binding rate coefficient expression developed as a function of the analyte concentration in solution and the fractal dimension is of particular value since it provides a means to better control biosensor or immunosensor performance. Copyright 2001 Academic Press.
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Affiliation(s)
- Ajit Sadana
- Chemical Engineering Department, University of Mississippi, University, Mississippi, 38677-9740
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Ramakrishnan A, Sadana A. A single-fractal analysis of cellular analyte-receptor binding kinetics utilizing biosensors. Biosystems 2001; 59:35-51. [PMID: 11226625 DOI: 10.1016/s0303-2647(00)00142-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
A fractal analysis of a confirmative nature only is presented for cellular analyte-receptor binding kinetics utilizing biosensors. Data taken from the literature can be modeled by using a single-fractal analysis. Relationships are presented for the binding rate coefficient as a function of the fractal dimension and for the analyte concentration in solution. In general, the binding rate coefficient is rather sensitive to the degree of heterogeneity that exists on the biosensor surface. It is of interest to note that examples are presented where the binding coefficient, k exhibits an increase as the fractal dimension (D(f)) or the degree of heterogeneity increases on the surface. The predictive relationships presented provide further physical insights into the binding reactions occurring on the surface. These should assist in understanding the cellular binding reaction occurring on surfaces, even though the analysis presented is for the cases where the cellular "receptor" is actually immobilized on a biosensor or other surface. The analysis suggests possible modulations of cell surfaces in desired directions to help manipulate the binding rate coefficient (or affinity). In general, the technique presented is applicable for the most part to other reactions occurring on different types of biosensor or other surfaces.
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Affiliation(s)
- A Ramakrishnan
- Chemical Engineering Department, University of Mississippi, 134 Anderson Hall, Mississippi 38677-9740, USA
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Ramakrishnan A, Sadana A. An Evaluation of Cellular Analyte-Receptor Binding Kinetics Utilizing Biosensors: A Fractal Analysis. J Colloid Interface Sci 2000; 224:219-230. [PMID: 10727332 DOI: 10.1006/jcis.2000.6736] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
A fractal analysis is presented for cellular analyte-receptor binding kinetics utilizing biosensors. Data taken from the literature can be modeled by using (a) a single-fractal analysis and (b) a single- and a dual-fractal analysis. Case (b) represents a change in the binding mechanism as the reaction progresses on the biosensor surface. Relationships are presented for the binding rate coefficient(s) as a function of the fractal dimension for the single-fractal analysis examples. In general, the binding rate coefficient is rather sensitive to the degree of heterogeneity that exists on the biosensor surface. For example, for the binding of mutagenized and back-mutagenized forms of peptide E1037 in solution to salivary agglutinin immobilized on a sensor chip, the order of dependence of the binding rate coefficient, k, on the fractal dimension, D(f), is 13.2. It is of interest to note that examples are presented where the binding coefficient (k) exhibits an increase as the fractal dimension (D(f)) or the degree of heterogeneity increases on the surface. The predictive relationships presented provide further physical insights into the binding reactions occurring on the surface. These should assist us in understanding the cellular binding reaction occurring on surfaces, even though the analysis presented is for the cases where the cellular "receptor" is actually immobilized on a biosensor or other surface. The analysis suggests possible modulations of cell surfaces in desired directions to help manipulate the binding rate coefficients (or affinities). In general, the technique presented is applicable for the most part to other reactions occurring on different types of biosensors or other surfaces. Copyright 2000 Academic Press.
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Affiliation(s)
- A Ramakrishnan
- Chemical Engineering Department, University of Mississippi, University, Mississippi, 38677-9740
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Podkościelny P, Dąbrowski A. A new approach to determination of the parameters describing liquid adsorption on the solid surfaces. Colloids Surf A Physicochem Eng Asp 2000. [DOI: 10.1016/s0927-7757(99)00242-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Sadana A. Adsorption Influence on Bioseparation and Inactivation. SEP SCI TECHNOL 1998. [DOI: 10.1016/s0149-6395(98)80035-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Kumar A, Fish W. Ligands, metals, and metal-ligand complexes as differential probes of soil adsorptive heterogeneity. Colloids Surf A Physicochem Eng Asp 1996. [DOI: 10.1016/0927-7757(95)03348-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Excess adsorption isotherms for solid-liquid systems and their analysis to determine the surface phase capacity. Adv Colloid Interface Sci 1990. [DOI: 10.1016/0001-8686(90)80006-l] [Citation(s) in RCA: 29] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Rudziński W, Michałek J, Brun B, Partyka S. Further comments on the preparation of mixed organic layers chemically bonded on silicon dioxide. J Chromatogr A 1987. [DOI: 10.1016/s0021-9673(00)94037-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Dabrowski A, Jaroniec M. Theoretical foundations of physical adsorption from binary non-electrolytic liquid mixtures on solid surfaces: present and future. Adv Colloid Interface Sci 1987. [DOI: 10.1016/0001-8686(87)85004-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Dabrowski A, Jaroniec M, Markowski W, Czapińska K, Soczewiński E. Characterization of Liquid-Solid Adsorption Systems by Using TLC Data. ACTA ACUST UNITED AC 1986. [DOI: 10.1080/01483918608078747] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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An isotherm equation for adsorption from binary liquid mixtures on solids involving surface heterogeneity and differences in molecular sizes of components and its numerical verification. MONATSHEFTE FUR CHEMIE 1986. [DOI: 10.1007/bf00809434] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Jaroniec M, Marczewski AW. Physical adsorption of gases on energetically heterogeneous solids I. GeneralizedLangmuir equation and its energy distribution. MONATSHEFTE FUR CHEMIE 1984. [DOI: 10.1007/bf00798768] [Citation(s) in RCA: 30] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Adsorption from solutions of nonelectrolytes on heterogeneous solid surfaces: A four-parameter equation for the excess adsorption isotherm. MONATSHEFTE FUR CHEMIE 1984. [DOI: 10.1007/bf00799161] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Jaroniec M, Dabrowski A, Toth J. Multilayer single-solute adsorption from dilute solutions on energetically heterogeneous solids. Chem Eng Sci 1984. [DOI: 10.1016/0009-2509(84)80130-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Ideal adsorption from binary liquid mixtures on heterogeneous solid surfaces: Equations for excess isotherms and heats of immersion. J Colloid Interface Sci 1983. [DOI: 10.1016/0021-9797(83)90038-3] [Citation(s) in RCA: 44] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Dabrowski A, Jaroniec M, Tóth J. Application of tóth's equation to describe the single-solute adsorption from dilute solutions on solids. J Colloid Interface Sci 1983. [DOI: 10.1016/0021-9797(83)90298-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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28
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Theoretical studies on the adsorption from non-ideal binary liquid mixtures on heterogeneous surfaces involving difference in molecular sizes of components. MONATSHEFTE FUR CHEMIE 1983. [DOI: 10.1007/bf00799949] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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29
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Current state in adsorption from multicomponent solutions of nonelectrolytes on solids. Adv Colloid Interface Sci 1983. [DOI: 10.1016/0001-8686(83)80006-2] [Citation(s) in RCA: 48] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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30
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TheLangmuir-Freundlich equation in adsorption from dilute solutions on solids. MONATSHEFTE FUR CHEMIE 1983. [DOI: 10.1007/bf00798437] [Citation(s) in RCA: 27] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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31
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Jaroniec M, Marczewski AW, Einicke WD, Herden H, Sch�llner R. Adsorption of 1-tetradecene/dodecane mixtures on different types of zeolites. MONATSHEFTE FUR CHEMIE 1983. [DOI: 10.1007/bf00799948] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Bor�wko M, Goworek J, Jaroniec M. A model of adsorption at liquid-solid interface involving association in the bulk phase. MONATSHEFTE FUR CHEMIE 1982. [DOI: 10.1007/bf00809005] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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34
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Dabrowski A, Jaroniec M. Effects of surface heterogeneity in adsorption from binary liquid mixtures. IV. Adsorption model with nonideal bulk phase and regular surface phase. J Colloid Interface Sci 1980. [DOI: 10.1016/0021-9797(80)90332-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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