A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges
Mathematical models play a crucial role in data acquisition by boosting the capacity to interpret and group the gathered information. However, the challenge lies in choosing the most accurate model to represent data sets with very slight nuances, as it occurs in the validation of adsorption processe...
- Autores:
-
Ferreira Piazzi Fuhr, Ana Carolina
Vieira, Yasmin
Silva Oliveira, Marcos Leandro
Silva Oliveira, Luis Felipe
Manoharadas, Salim
Nawaz, Asad
Dotto, Guilherme Luiz
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2023
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/13984
- Acceso en línea:
- https://hdl.handle.net/11323/13984
https://repositorio.cuc.edu.co/
- Palabra clave:
- Parameter estimation
Pesticide adsorption
Physical meaning
Statistical physical modeling
- Rights
- openAccess
- License
- Atribución 4.0 Internacional (CC BY 4.0)
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A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges |
| title |
A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges |
| spellingShingle |
A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges Parameter estimation Pesticide adsorption Physical meaning Statistical physical modeling |
| title_short |
A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges |
| title_full |
A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges |
| title_fullStr |
A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges |
| title_full_unstemmed |
A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges |
| title_sort |
A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges |
| dc.creator.fl_str_mv |
Ferreira Piazzi Fuhr, Ana Carolina Vieira, Yasmin Silva Oliveira, Marcos Leandro Silva Oliveira, Luis Felipe Manoharadas, Salim Nawaz, Asad Dotto, Guilherme Luiz |
| dc.contributor.author.none.fl_str_mv |
Ferreira Piazzi Fuhr, Ana Carolina Vieira, Yasmin Silva Oliveira, Marcos Leandro Silva Oliveira, Luis Felipe Manoharadas, Salim Nawaz, Asad Dotto, Guilherme Luiz |
| dc.subject.proposal.eng.fl_str_mv |
Parameter estimation Pesticide adsorption Physical meaning Statistical physical modeling |
| topic |
Parameter estimation Pesticide adsorption Physical meaning Statistical physical modeling |
| description |
Mathematical models play a crucial role in data acquisition by boosting the capacity to interpret and group the gathered information. However, the challenge lies in choosing the most accurate model to represent data sets with very slight nuances, as it occurs in the validation of adsorption processes considering molecules with different properties but similar structural attributes. Due to these very small variations, there is a high chance of excessive adaption to specific patterns created by the distributions, statistically blindsiding the decision-making. In this work, we used statistical physics (sta-phy) modeling and thermodynamic calculations of the three different pesticides 2,4-dichlorophenoxyacetic acid (2,4-D), dicamba (DCB), and mecoprop (MCPP) on a woody based activated carbon (WBAC) to demonstrate these patterns while also unveiling the mechanisms involved. We demonstrate that the statistical criteria alone do not provide enough clarity in these cases, and we propose using the physical meaning of each estimated parameter as a way out. Thus, in this work, we prove in detail that using sta-phy models requires absolute mastering of the subjects to ensure reliable results by understanding the relationships between the adsorption parameters and the system properties instead of a simple read of the determination coefficients. |
| publishDate |
2023 |
| dc.date.issued.none.fl_str_mv |
2023-11-30 |
| dc.date.accessioned.none.fl_str_mv |
2025-02-25T22:29:20Z |
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2025-02-25T22:29:20Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Ana Carolina Ferreira Piazzi Fuhr, Yasmin Vieira, Marcos Leandro Silva Oliveira, Luis Felipe Oliveira Silva, Salim Manoharadas, Asad Nawaz, Guilherme Luiz Dotto, A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges, Journal of Molecular Liquids, Volume 390, Part B, 2023, 123107, ISSN 0167-7322, https://doi.org/10.1016/j.molliq.2023.123107. |
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0167-7322 |
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https://hdl.handle.net/11323/13984 |
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10.1016/j.molliq.2023.123107 |
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1873-3166 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
| identifier_str_mv |
Ana Carolina Ferreira Piazzi Fuhr, Yasmin Vieira, Marcos Leandro Silva Oliveira, Luis Felipe Oliveira Silva, Salim Manoharadas, Asad Nawaz, Guilherme Luiz Dotto, A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges, Journal of Molecular Liquids, Volume 390, Part B, 2023, 123107, ISSN 0167-7322, https://doi.org/10.1016/j.molliq.2023.123107. 0167-7322 10.1016/j.molliq.2023.123107 1873-3166 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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https://hdl.handle.net/11323/13984 https://repositorio.cuc.edu.co/ |
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eng |
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eng |
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Journal of Molecular Liquids |
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E.C. Lima, A.A. Gomes, H.N. Tran, Comparison of the non-linear and linear forms of the van’t Hoff equation for calculation of adsorption thermodynamic parameters (ΔS◦ and ΔH◦), J. Mol. Liq. 311 (2020), 113315, https://doi.org/10.1016/J. MOLLIQ.2020.113315 M. Khalfaoui, S. Knani, M.A. Hachicha, A. Ben Lamine, New theoretical expressions for the five adsorption type isotherms classified by BET based on statistical physics treatment, Journal of Colloid and Interface Science 263 (2003) 350–356, https:// doi.org/10.1016/S0021-9797(03)00139-5. F.K. Rodrigues, N.P.G. Salau, G.L. Dotto, New insights about reactive red 141 adsorption onto multi–walled carbon nanotubes using statistical physics coupled with Van der Waals equation, Sep. Purif. Technol. 224 (2019) 290–294, https:// doi.org/10.1016/J.SEPPUR.2019.05.042. Y. Vieira, C. Schnorr, A.C. Piazzi, M.S. Netto, W.M. Piccini, D.S.P. Franco, E. S. Mallmann, J. Georgin, L.F.O. Silva, G.L. Dotto, An advanced combination of density functional theory simulations and statistical physics modeling in the unveiling and prediction of adsorption mechanisms of 2,4-D pesticide to activated carbon, J. Mol. Liq. 361 (2022), 119639, https://doi.org/10.1016/J. MOLLIQ.2022.119639. Y. Vieira, J.P. Silveira, G.L. Dotto, S. Knani, J. Vieillard, J. Georgin, D.S.P. Franco, E.C. Lima, Mechanistic insights and steric interpretations through statistical physics modelling and density functional theory calculations for the adsorption of the pesticides atrazine and diuron by Hovenia dulcis biochar, J. Mol. Liq. 367 (2022), 120418, https://doi.org/10.1016/J.MOLLIQ.2022.120418. J. Qu, R. Liu, X. Bi, Z. Li, K. Li, Q. Hu, X. Zhang, G. Zhang, S. Ma, Y. Zhang, Remediation of atrazine contaminated soil by microwave activated persulfate system: Performance, mechanism and DFT calculation, J. Clean. Prod. 399 (2023), 136546, https://doi.org/10.1016/J.JCLEPRO.2023.136546. A. Samanth, R. Vinayagam, G. Murugesan, T. Varadavenkatesan, R. Selvaraj, A. Pugazhendhi, Enhanced adsorption of 2,4-dichlorophenoxyacetic acid using low-temperature carbonized Peltophorum pterocarpum pods and its statistical physics modeling, Chemosphere 336 (2023), 139143, https://doi.org/10.1016/J. CHEMOSPHERE.2023.139143 A. de Jesús Gonzalez, ´ N.A. Rangel Vazquez, ´ PM3 semi-empirical method and Monte Carlo simulation application on pesticides adsorption on SWCNT, Colloid Interface, Sci. Commun. 53 (2023), 100699, https://doi.org/10.1016/J. COLCOM.2023.100699 S.H. Alrefaee, M. Aljohani, K. Alkhamis, F. Shaaban, M.G. El-Desouky, A.A. ElBindary, M.A. El-Bindary, Adsorption and effective removal of organophosphorus pesticides from aqueous solution via novel metal-organic framework: Adsorption isotherms, kinetics, and optimization via Box-Behnken design, J. Mol. Liq. 384 (2023), 122206, https://doi.org/10.1016/J.MOLLIQ.2023.122206. H.A. Pereira, K. da Boit Martinello, Y. Vieira, J.C. Diel, M.S. Netto, G.D. Reske, E. Lorenzett, L.F.O. Silva, T.A.L. Burgo, G.L. Dotto, Adsorptive behavior of multiwalled carbon nanotubes immobilized magnetic nanoparticles for removing selected pesticides from aqueous matrices, Chemosphere 325 (2023), 138384, https://doi.org/10.1016/J.CHEMOSPHERE.2023.138384. U.S. McKnight, J.J. Rasmussen, B. Kronvang, P.J. Binning, P.L. Bjerg, Sources, occurrence and predicted aquatic impact of legacy and contemporary pesticides in streams, Environ. Pollut. 200 (2015) 64–76, https://doi.org/10.1016/J. ENVPOL.2015.02.015. J. McGinley, M.G. Healy, P.C. Ryan, P.E. Mellander, L. Morrison, J.H. O’Driscoll, A. Siggins, Batch adsorption of herbicides from aqueous solution onto diverse reusable materials and granulated activated carbon, J. Environ. Manage. 323 (2022), 116102, https://doi.org/10.1016/J.JENVMAN.2022.116102. R. Vinayagam, S. Ganga, G. Murugesan, G. Rangasamy, R. Bhole, L.C. Goveas, T. Varadavenkatesan, N. Dave, A. Samanth, V. Radhika Devi, R. Selvaraj, 2,4- Dichlorophenoxyacetic acid (2,4-D) adsorptive removal by algal magnetic activated carbon nanocomposite, Chemosphere 310 (2023), 136883, https://doi. org/10.1016/J.CHEMOSPHERE.2022.136883 Z. Aksu, E. Kabasakal, Batch adsorption of 2,4-dichlorophenoxy-acetic acid (2,4-D) from aqueous solution by granular activated carbon, Sep. Purif. Technol. 35 (2004) 223–240, https://doi.org/10.1016/S1383-5866(03)00144-8. J.P. Kearns, L.S. Wellborn, R.S. Summers, D.R.U. Knappe, 2,4-D adsorption to biochars: Effect of preparation conditions on equilibrium adsorption capacity and comparison with commercial activated carbon literature data, Water Res. 62 (2014) 20–28, https://doi.org/10.1016/J.WATRES.2014.05.023. J.O. Ighalo, A.G. Adeniyi, A.A. Adelodun, Recent advances on the adsorption of herbicides and pesticides from polluted waters: Performance evaluation via physical attributes, J. Ind. Eng. Chem. 93 (2021) 117–137, https://doi.org/ 10.1016/J.JIEC.2020.10.011. N.R. Zuanazzi, N. de C. Ghisi, E.C. Oliveira, Analysis of global trends and gaps for studies about 2,4-D herbicide toxicity: A scientometric review, Chemosphere. 241 (2020) 125016. https://doi.org/10.1016/J.CHEMOSPHERE.2019.125016. S. Spahr, M. Teixido, ´ S.S. Gall, J.C. Pritchard, N. Hagemann, B. Helmreich, R. G. Luthy, Performance of biochars for the elimination of trace organic contaminants and metals from urban stormwater, Environ. Sci. Water Res. Technol. 8 (2022) 1287–1299, https://doi.org/10.1039/D1EW00857A. L. Sellaoui, H. Guedidi, S. Knani, L. Reinert, L. Duclaux, A. Ben Lamine, Application of statistical physics formalism to the modeling of adsorption isotherms of ibuprofen on activated carbon, Fluid Phase Equilib. 387 (2015) 103–110, https:// doi.org/10.1016/J.FLUID.2014.12.018. A.F.M. Streit, G.C. Collazzo, S.P. Druzian, R.S. Verdi, E.L. Foletto, L.F.S. Oliveira, G. L. Dotto, Adsorption of ibuprofen, ketoprofen, and paracetamol onto activated carbon prepared from effluent treatment plant sludge of the beverage industry, Chemosphere 262 (2021), 128322, https://doi.org/10.1016/J. CHEMOSPHERE.2020.128322. |
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Atribución 4.0 Internacional (CC BY 4.0)© 2023 Elsevier B.V.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ferreira Piazzi Fuhr, Ana CarolinaVieira, YasminSilva Oliveira, Marcos LeandroSilva Oliveira, Luis FelipeManoharadas, SalimNawaz, AsadDotto, Guilherme Luiz2025-02-25T22:29:20Z2025-02-25T22:29:20Z2023-11-30Ana Carolina Ferreira Piazzi Fuhr, Yasmin Vieira, Marcos Leandro Silva Oliveira, Luis Felipe Oliveira Silva, Salim Manoharadas, Asad Nawaz, Guilherme Luiz Dotto, A detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges, Journal of Molecular Liquids, Volume 390, Part B, 2023, 123107, ISSN 0167-7322, https://doi.org/10.1016/j.molliq.2023.123107.0167-7322https://hdl.handle.net/11323/1398410.1016/j.molliq.2023.1231071873-3166Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Mathematical models play a crucial role in data acquisition by boosting the capacity to interpret and group the gathered information. However, the challenge lies in choosing the most accurate model to represent data sets with very slight nuances, as it occurs in the validation of adsorption processes considering molecules with different properties but similar structural attributes. Due to these very small variations, there is a high chance of excessive adaption to specific patterns created by the distributions, statistically blindsiding the decision-making. In this work, we used statistical physics (sta-phy) modeling and thermodynamic calculations of the three different pesticides 2,4-dichlorophenoxyacetic acid (2,4-D), dicamba (DCB), and mecoprop (MCPP) on a woody based activated carbon (WBAC) to demonstrate these patterns while also unveiling the mechanisms involved. We demonstrate that the statistical criteria alone do not provide enough clarity in these cases, and we propose using the physical meaning of each estimated parameter as a way out. Thus, in this work, we prove in detail that using sta-phy models requires absolute mastering of the subjects to ensure reliable results by understanding the relationships between the adsorption parameters and the system properties instead of a simple read of the determination coefficients.Elsevier B.V.15 páginasapplication/pdfengElsevier B.V.Netherlandshttps://www.sciencedirect.com/science/article/pii/S016773222301913X?via%3DihubA detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature rangesArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Journal of Molecular LiquidsE.C. Lima, A.A. Gomes, H.N. Tran, Comparison of the non-linear and linear forms of the van’t Hoff equation for calculation of adsorption thermodynamic parameters (ΔS◦ and ΔH◦), J. Mol. Liq. 311 (2020), 113315, https://doi.org/10.1016/J. MOLLIQ.2020.113315M. Khalfaoui, S. Knani, M.A. Hachicha, A. Ben Lamine, New theoretical expressions for the five adsorption type isotherms classified by BET based on statistical physics treatment, Journal of Colloid and Interface Science 263 (2003) 350–356, https:// doi.org/10.1016/S0021-9797(03)00139-5.F.K. Rodrigues, N.P.G. Salau, G.L. Dotto, New insights about reactive red 141 adsorption onto multi–walled carbon nanotubes using statistical physics coupled with Van der Waals equation, Sep. Purif. Technol. 224 (2019) 290–294, https:// doi.org/10.1016/J.SEPPUR.2019.05.042.Y. Vieira, C. Schnorr, A.C. Piazzi, M.S. Netto, W.M. Piccini, D.S.P. Franco, E. S. Mallmann, J. Georgin, L.F.O. Silva, G.L. Dotto, An advanced combination of density functional theory simulations and statistical physics modeling in the unveiling and prediction of adsorption mechanisms of 2,4-D pesticide to activated carbon, J. Mol. Liq. 361 (2022), 119639, https://doi.org/10.1016/J. MOLLIQ.2022.119639.Y. Vieira, J.P. Silveira, G.L. Dotto, S. Knani, J. Vieillard, J. Georgin, D.S.P. Franco, E.C. Lima, Mechanistic insights and steric interpretations through statistical physics modelling and density functional theory calculations for the adsorption of the pesticides atrazine and diuron by Hovenia dulcis biochar, J. Mol. Liq. 367 (2022), 120418, https://doi.org/10.1016/J.MOLLIQ.2022.120418.J. Qu, R. Liu, X. Bi, Z. Li, K. Li, Q. Hu, X. Zhang, G. Zhang, S. Ma, Y. Zhang, Remediation of atrazine contaminated soil by microwave activated persulfate system: Performance, mechanism and DFT calculation, J. Clean. Prod. 399 (2023), 136546, https://doi.org/10.1016/J.JCLEPRO.2023.136546.A. Samanth, R. Vinayagam, G. Murugesan, T. Varadavenkatesan, R. Selvaraj, A. Pugazhendhi, Enhanced adsorption of 2,4-dichlorophenoxyacetic acid using low-temperature carbonized Peltophorum pterocarpum pods and its statistical physics modeling, Chemosphere 336 (2023), 139143, https://doi.org/10.1016/J. CHEMOSPHERE.2023.139143A. de Jesús Gonzalez, ´ N.A. Rangel Vazquez, ´ PM3 semi-empirical method and Monte Carlo simulation application on pesticides adsorption on SWCNT, Colloid Interface, Sci. Commun. 53 (2023), 100699, https://doi.org/10.1016/J. COLCOM.2023.100699S.H. Alrefaee, M. Aljohani, K. Alkhamis, F. Shaaban, M.G. El-Desouky, A.A. ElBindary, M.A. El-Bindary, Adsorption and effective removal of organophosphorus pesticides from aqueous solution via novel metal-organic framework: Adsorption isotherms, kinetics, and optimization via Box-Behnken design, J. Mol. Liq. 384 (2023), 122206, https://doi.org/10.1016/J.MOLLIQ.2023.122206.H.A. Pereira, K. da Boit Martinello, Y. Vieira, J.C. Diel, M.S. Netto, G.D. Reske, E. Lorenzett, L.F.O. Silva, T.A.L. Burgo, G.L. Dotto, Adsorptive behavior of multiwalled carbon nanotubes immobilized magnetic nanoparticles for removing selected pesticides from aqueous matrices, Chemosphere 325 (2023), 138384, https://doi.org/10.1016/J.CHEMOSPHERE.2023.138384.U.S. McKnight, J.J. Rasmussen, B. Kronvang, P.J. Binning, P.L. Bjerg, Sources, occurrence and predicted aquatic impact of legacy and contemporary pesticides in streams, Environ. Pollut. 200 (2015) 64–76, https://doi.org/10.1016/J. ENVPOL.2015.02.015.J. McGinley, M.G. Healy, P.C. Ryan, P.E. Mellander, L. Morrison, J.H. O’Driscoll, A. Siggins, Batch adsorption of herbicides from aqueous solution onto diverse reusable materials and granulated activated carbon, J. Environ. Manage. 323 (2022), 116102, https://doi.org/10.1016/J.JENVMAN.2022.116102.R. Vinayagam, S. Ganga, G. Murugesan, G. Rangasamy, R. Bhole, L.C. Goveas, T. Varadavenkatesan, N. Dave, A. Samanth, V. Radhika Devi, R. Selvaraj, 2,4- Dichlorophenoxyacetic acid (2,4-D) adsorptive removal by algal magnetic activated carbon nanocomposite, Chemosphere 310 (2023), 136883, https://doi. org/10.1016/J.CHEMOSPHERE.2022.136883Z. Aksu, E. Kabasakal, Batch adsorption of 2,4-dichlorophenoxy-acetic acid (2,4-D) from aqueous solution by granular activated carbon, Sep. Purif. Technol. 35 (2004) 223–240, https://doi.org/10.1016/S1383-5866(03)00144-8.J.P. Kearns, L.S. Wellborn, R.S. Summers, D.R.U. Knappe, 2,4-D adsorption to biochars: Effect of preparation conditions on equilibrium adsorption capacity and comparison with commercial activated carbon literature data, Water Res. 62 (2014) 20–28, https://doi.org/10.1016/J.WATRES.2014.05.023.J.O. Ighalo, A.G. Adeniyi, A.A. Adelodun, Recent advances on the adsorption of herbicides and pesticides from polluted waters: Performance evaluation via physical attributes, J. Ind. Eng. Chem. 93 (2021) 117–137, https://doi.org/ 10.1016/J.JIEC.2020.10.011.N.R. Zuanazzi, N. de C. Ghisi, E.C. Oliveira, Analysis of global trends and gaps for studies about 2,4-D herbicide toxicity: A scientometric review, Chemosphere. 241 (2020) 125016. https://doi.org/10.1016/J.CHEMOSPHERE.2019.125016.S. Spahr, M. Teixido, ´ S.S. Gall, J.C. Pritchard, N. Hagemann, B. Helmreich, R. G. Luthy, Performance of biochars for the elimination of trace organic contaminants and metals from urban stormwater, Environ. Sci. Water Res. Technol. 8 (2022) 1287–1299, https://doi.org/10.1039/D1EW00857A.L. Sellaoui, H. Guedidi, S. Knani, L. Reinert, L. Duclaux, A. Ben Lamine, Application of statistical physics formalism to the modeling of adsorption isotherms of ibuprofen on activated carbon, Fluid Phase Equilib. 387 (2015) 103–110, https:// doi.org/10.1016/J.FLUID.2014.12.018.A.F.M. Streit, G.C. Collazzo, S.P. Druzian, R.S. Verdi, E.L. Foletto, L.F.S. Oliveira, G. L. Dotto, Adsorption of ibuprofen, ketoprofen, and paracetamol onto activated carbon prepared from effluent treatment plant sludge of the beverage industry, Chemosphere 262 (2021), 128322, https://doi.org/10.1016/J. CHEMOSPHERE.2020.128322.151123107390Parameter estimationPesticide adsorptionPhysical meaningStatistical physical modelingPublicationORIGINALA detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges.pdfA detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges.pdfapplication/pdf2615455https://repositorio.cuc.edu.co/bitstreams/026f148e-fef5-4b3f-94d2-e84cf927c522/download57b6bcdd9f26406f68ea59e3e5d015f9MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-815543https://repositorio.cuc.edu.co/bitstreams/7a9dc404-e55a-4d97-a242-507cd93af0c1/download73a5432e0b76442b22b026844140d683MD52TEXTA detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges.pdf.txtA detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges.pdf.txtExtracted texttext/plain80133https://repositorio.cuc.edu.co/bitstreams/9d421ce2-a6c4-4a72-9c38-e0cb25e696a1/download6e429da5ae722ccadf936eff59dfa270MD53THUMBNAILA detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges.pdf.jpgA detailed study on the selection of borderline features for accurate mechanism description of the adsorption of different pesticide molecules under different temperature ranges.pdf.jpgGenerated Thumbnailimage/jpeg14702https://repositorio.cuc.edu.co/bitstreams/4f20d2b0-cb06-4b9a-871a-9955b7b8f519/download7c2a7fe79dd03ea0acd5c459f7106cd1MD5411323/13984oai:repositorio.cuc.edu.co:11323/139842025-02-26 13:53:36.647https://creativecommons.org/licenses/by/4.0/© 2023 Elsevier B.V.open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa 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ara ejercer estos derechos sobre la Obra tal y como se indica a continuación:</p>
    <ol type="a">
      <li>Reproducir la Obra, incorporar la Obra en una o más Obras Colectivas, y reproducir la Obra incorporada en las Obras Colectivas.</li>
      <li>Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.</li>
      <li>Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.</li>
    </ol>
    <p>Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).</p>
  </li>
  <br/>
  <li>
    Restricciones.
    <p>La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:</p>
    <ol type="a">
      <li>Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).</li>
      <li>Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.</li>
      <li>Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.</li>
      <li>
        Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:
        <ol type="i">
          <li>Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.</li>
          <li>Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
        </ol>
      </li>
      <li>Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
    </ol>
  </li>
  <br/>
  <li>
    Representaciones, Garantías y Limitaciones de Responsabilidad.
    <p>A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Limitación de responsabilidad.
    <p>A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Término.
    <ol type="a">
      <li>Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.</li>
      <li>Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.</li>
    </ol>
  </li>
  <br/>
  <li>
    Varios.
    <ol type="a">
      <li>Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.</li>
      <li>Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.</li>
      <li>Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.</li>
      <li>Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.</li>
    </ol>
  </li>
  <br/>
</ol>
 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