journal article·2025-08-30Open access

Quantitative analysis of reactive dye–cellulose affinity via molecular dynamics simulations verified by diffusion experiments

Hongxia Long, Wei Wu, Hong Xu, Yi Zhong, Linping Zhang, Qingyong Zhao, Zhiping Mao

Abstract

Quantifying affinity differences between various dyes and cellulose fibers is essential for optimizing low-water and low-salt pad dyeing processes for cotton fabrics. Molecular dynamics (MD) simulations were used to model interactions within the water–dye–cellulose system. The absolute binding free energy between the dye and cellulose was calculated to understand how their affinity influences dye diffusion and adsorption. The simulations examined the effects of system size, pore size, salt concentration, and dye structure on dye solvation free energy (ΔG A ) and dye-cellulose binding free energy (ΔG binding ). Results showed that ΔG A was independent of system size and solely dependent on dye structure. Dyes containing more sulfonic acid groups exhibited higher ΔG A values. NaCl reduced electrostatic repulsion between the dye and cellulose through a dispersion–aggregation–redispersion mechanism, which enhanced dye–cellulose binding. Increasing NaCl concentrations further enhanced ΔG binding . Larger pore sizes also resulted in higher ΔG binding . This affected dye diffusion paths by modulating hydrogen bonding strength between the dye–cellulose and dye–water, thereby affecting dye–cellulose interactions. Reactive dyes containing more aromatic rings, hydroxyl groups, and amino groups exhibited stronger interactions with cellulose, leading to higher ΔG binding values. Furthermore, experimental dye diffusion coefficients in cotton fibers were measured using confocal Raman spectroscopy. Among the dyes studied, B194 had the highest ΔG binding and the lowest experimental diffusion coefficient, while B19 exhibited the lowest ΔG binding and the highest diffusion coefficient. Higher ΔG binding was associated with stronger dye–cellulose affinity and lower diffusion coefficients, validating the reliability of the MD system for quantitative analysis of dye–cellulose interactions.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Dyeing and Modifying Textile Fibers · Enzyme-mediated dye degradation · Lignin and Wood Chemistry

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Science and Technology of Eco-Textile, College of Chemistry and Chemical Engineering, Donghua University, Shanghai 201620, China

National Innovation Center of Advanced Dyeing & Finishing Technology, Shandong Zhongkang Guochuang Research Institute of Advanced Dyeing & Finishing Technology Co., Ltd., Taian 271000, China

Shanghai Frontier Science Research Center for Modern Textiles, Donghua University, China

Funding

the International Cooperation Fund of Science and Technology Commission of Shanghai Municipality · the National Natural Science Foundation of China · the Key Technology Research and Development Program of Shandong Province

References (48)

Show source-provided references
1. 10.1007/s10570-022-04576-910.1007/s10570-022-04576-9 ↗
2. 10.1016/j.indcrop.2024.11936810.1016/j.indcrop.2024.119368 ↗
3. Lewis DM. Dyestuff–fibre interactions. Color Technol 2008; 28: 12–17.
4. 10.1080/08927022.2020.175503710.1080/08927022.2020.1755037 ↗
5. 10.1016/j.indcrop.2024.11995510.1016/j.indcrop.2024.119955 ↗
6. 10.3390/coatings1304067710.3390/coatings13040677 ↗
7. 10.1016/j.geoderma.2007.11.02010.1016/j.geoderma.2007.11.020 ↗
8. 10.1177/00405175580280120710.1177/004051755802801207 ↗
9. 10.1016/S0927-7757(97)00196-910.1016/S0927-7757(97)00196-9 ↗
10. Mutlu AD, Giilçena BG. Investigation of the usablity of eastern groundsel (Senecio vernalis) plant in nature dyeing. Tekstil ve Muhendis 2020; 27: 236–242.
11. 10.1007/s10692-005-0060-210.1007/s10692-005-0060-2 ↗
12. 10.1016/j.dyepig.2014.01.02710.1016/j.dyepig.2014.01.027 ↗
13. 10.1016/j.saa.2020.11805110.1016/j.saa.2020.118051 ↗
14. 10.1111/cote.1254910.1111/cote.12549 ↗
15. 10.1016/j.polymer.2004.03.10310.1016/j.polymer.2004.03.103 ↗
16. 10.1021/acs.iecr.9b0711010.1021/acs.iecr.9b07110 ↗
17. 10.1007/s10570-005-7132-610.1007/s10570-005-7132-6 ↗
18. 10.1016/j.dyepig.2021.10916010.1016/j.dyepig.2021.109160 ↗
19. 10.3390/pr912216210.3390/pr9122162 ↗
20. 10.1007/s12221-023-00202-y10.1007/s12221-023-00202-y ↗
21. 10.1016/j.dyepig.2012.01.01510.1016/j.dyepig.2012.01.015 ↗
22. 10.1016/j.dyepig.2018.01.05310.1016/j.dyepig.2018.01.053 ↗
23. Adam S, Kass I. Effect of protein-polarized ligand charges on relative protein ligand binding affinities. J Chem Theory Comput 2024; 20: 8270–8278.
24. 10.1021/acs.jctc.3c0036510.1021/acs.jctc.3c00365 ↗
25. 10.1111/cote.1250310.1111/cote.12503 ↗
26. 10.1002/jcc.2029110.1002/jcc.20291 ↗
27. 10.1021/j100011a06110.1021/j100011a061 ↗
28. 10.1002/jcc.2003510.1002/jcc.20035 ↗
29. 10.1021/acs.jctc.5b0025510.1021/acs.jctc.5b00255 ↗
30. 10.1063/1.44586910.1063/1.445869 ↗
31. Zhivotovskii. Computer models of quantitative characteristics in genetics. Communication II. Dynamics of the frequency of alleles with different types of selection. Sov Genetics 1974; 8: 937–941.
32. 10.1021/acs.biomac.6b0084610.1021/acs.biomac.6b00846 ↗
33. 10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H ↗
34. 10.1063/1.46439710.1063/1.464397 ↗
35. 10.1002/jcc.2295910.1002/jcc.22959 ↗
36. 10.1002/jcc.2122410.1002/jcc.21224 ↗
37. 10.1007/s10822-015-9840-910.1007/s10822-015-9840-9 ↗
38. 10.1016/j.jmb.2009.09.04910.1016/j.jmb.2009.09.049 ↗
39. 10.1021/jp021783910.1021/jp0217839 ↗
40. 10.1007/978-1-4939-7756-7_1110.1007/978-1-4939-7756-7_11 ↗
41. 10.1063/1.482626110.1063/1.4826261 ↗
42. 10.1063/1.174965710.1063/1.1749657 ↗
43. 10.1002/cphc.20180116010.1002/cphc.201801160 ↗
44. 10.1016/j.dyepig.2017.11.03910.1016/j.dyepig.2017.11.039 ↗
45. 10.1063/1.274238510.1063/1.2742385 ↗
46. 10.1021/acs.est.0c0106510.1021/acs.est.0c01065 ↗
47. 10.1063/1.499179810.1063/1.4991798 ↗
48. 10.1080/0026897041000167556310.1080/00268970410001675563 ↗