Using the vector of the ideality of correlation to simulate the zeta potential of nanoparticles under different experimental conditions, represented by quasi-SMILES
Author:
Funder
sOFT-ERA
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11224-024-02357-7.pdf
Reference22 articles.
1. Toropov AA, Sizochenko N, Toropova AP, Leszczynski J (2018) Towards the development of global nano-quantitative structure–property relationship models: zeta potentials of metal oxide nanoparticles. Nanomaterials 8(4):243. https://doi.org/10.3390/nano8040243
2. Sengottiyan S, Mikolajczyk A, Jagiełło K, Swirog M, Puzyn T (2023) Core, coating, or corona? The importance of considering protein coronas in nano-QSPR modeling of zeta potential. ACS Nano 17(3):1989–1997. https://doi.org/10.1021/acsnano.2c06977
3. Jafari K, Fatemi MH, Toropova AP, Toropov AA (2022) The development of nano-QSPR models for viscosity of nanofluids using the index of ideality of correlation and the correlation intensity index. Chemom Intell Lab Syst 222:104500. https://doi.org/10.1016/j.chemolab.2022.104500
4. Wyrzykowska E, Mikolajczyk A, Sikorska C, Puzyn T (2016) Development of a novel in silico model of zeta potential for metal oxide nanoparticles: a nano-QSPR approach. Nanotechnology 27(44):445702. https://doi.org/10.1088/0957-4484/27/44/445702
5. Swirog M, Mikolajczyk A, Jagiello K, Jänes J, Tämm K, Puzyn T (2022) Predicting electrophoretic mobility of TiO2, ZnO, and CeO2 nanoparticles in natural waters: the importance of environment descriptors in nanoinformatics models. Sci Total Environ 840:156572. https://doi.org/10.1016/j.scitotenv.2022.156572
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