High Throughput Selection of Organic Cathode Materials.
Journal of computational chemistry(2023)
摘要
Efficient and affordable batteries require the design of novel organic electrode materials to overcome the drawbacks of the traditionally used inorganic materials, and the computational screening of potential candidates is a very efficient way to identify prospective solutions and minimize experimental testing. Here we present a DFT high-throughput computational screening where 86 million molecules contained in the PUBCHEM database have been analyzed and classified according to their estimated electrochemical features. The 5445 top-performing candidates were identified, and among them, 2306 are expected to have a one-electron reduction potential higher than 4 V versus (Li/Li+). Analogously, one-electron energy densities higher than 800 Whkg-1 have been predicted for 626 molecules. Explicit calculations performed for certain materials show that at least 69 candidates with a two-electron energy density higher than 1300 Whkg-1. Successful molecules were sorted into several families, some of them already commonly used electrode materials, and others still experimentally untested. Most of them are small systems containing conjugated C(sic)O, N(sic)N, or N(sic)C functional groups. Our selected molecules form a valuable starting point for experimentalists exploring new materials for organic electrodes. To discover new organic cathode materials, 86 million organic structures were screened. Two thousand three hundred six materials are predicted to have a monoelectronic reduction potential higher than 4 V (vs. Li/Li+), while 626 materials reached an energy density higher than 800 Whkg-1. Successful materials were sorted in families, some of them never proposed before.image
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关键词
cathode materials,computational screening,DFT,linear correlation
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