In silico Design, Virtual Screening and Synthesis of Novel Electrolytic Solvents.
Mol Inform
; 38(10): e1900014, 2019 10.
Article
em En
| MEDLINE
| ID: mdl-31166649
ABSTRACT
We report the building, validation and release of QSPR (Quantitative Structure Property Relationship) models aiming to guide the design of new solvents for the next generation of Li-ion batteries. The dataset compiled from the literature included oxidation potentials (Eox ), specific ionic conductivities (κ), melting points (Tm ) and boiling points (Tb ) for 103 electrolytes. Each of the resulting consensus models assembled 9-19 individual Support Vector Machine models built on different sets of ISIDA fragment descriptors.(1) They were implemented in the ISIDA/Predictor software. Developed models were used to screen a virtual library of 9965 esters and sulfones. The most promising compounds prioritized according to theoretically estimated properties were synthesized and experimentally tested.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Solventes
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Simulação por Computador
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Avaliação Pré-Clínica de Medicamentos
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Eletrólitos
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Screening_studies
Idioma:
En
Revista:
Mol Inform
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
França