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For: Patra TK. Data-Driven Methods for Accelerating Polymer Design. ACS Polym Au 2022;2:8-26. [DOI: 10.1021/acspolymersau.1c00035] [Cited by in Crossref: 9] [Cited by in F6Publishing: 12] [Article Influence: 4.5] [Reference Citation Analysis]
Number Citing Articles
1 Wu J, Gong X, Wang Q, Yan F, Li J. A QSPR study for predicting θ(LCST) and θ(UCST) in binary polymer solutions. Chemical Engineering Science 2023;267:118326. [DOI: 10.1016/j.ces.2022.118326] [Reference Citation Analysis]
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10 Wang M, Jiang J. Accelerating Discovery of High Fractional Free Volume Polymers from a Data-Driven Approach. ACS Appl Mater Interfaces 2022. [PMID: 35767720 DOI: 10.1021/acsami.2c03917] [Reference Citation Analysis]
11 Kumar R. Materiomically Designed Polymeric Vehicles for Nucleic Acids: Quo Vadis? ACS Appl Bio Mater 2022. [PMID: 35642794 DOI: 10.1021/acsabm.2c00346] [Reference Citation Analysis]
12 Amamoto Y. Data-driven approaches for structure-property relationships in polymer science for prediction and understanding. Polym J. [DOI: 10.1038/s41428-022-00648-6] [Reference Citation Analysis]
13 Morgan AB, Mukhopadhyay P. A targeted review of bio-derived plasticizers with flame retardant functionality used in PVC. J Mater Sci. [DOI: 10.1007/s10853-022-07096-w] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
14 Simmons DS. Macromolecular Modeling. Macromolecular Engineering 2022. [DOI: 10.1002/9783527815562.mme0049] [Reference Citation Analysis]
15 Schneider L, Schwarting M, Mysona J, Liang H, Han M, Rauscher PM, Ting JM, Venkatram S, Ross RB, Schmidt KJ, Blaiszik B, Foster I, de Pablo JJ. In silico active learning for small molecule properties. Mol Syst Des Eng . [DOI: 10.1039/d2me00137c] [Reference Citation Analysis]
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