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Virtual screening of organic quinones as cathode materials for sodium-ion batteries

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    Abstract

    High-throughput virtual screening (HTVS) has been increasingly applied as an effective approach to find candidate materials for energy applications. We performed a HTVS study, which is powered by: (i) automated virtual screening library generation, (ii) automated search on a readily purchasable chemical space of quinone-based compounds, and (iii) computed physicochemical descriptors for the prediction of key battery-related features of compounds, including the reduction potential, gravimetric energy density, gravimetric charge capacity, and molecular stability. From the initial virtual library of approximately 450k molecules, a total of 326 compounds have been identified as commercially available. Among them, 289 of the molecules are predicted to be stable for the sodiation reactions that take place at the sodium-ion battery cathodes. To study the behaviour of molecules over time at room temperature, we performed molecular dynamics simulations on a group of sodiated product molecules, which was narrowed down to 21 quinones after scrutinizing the key battery performance indicators. As a result, 17 compounds are suggested for validation as candidate cathode materials in sodium-ion batteries.

    Original languageEnglish
    Pages (from-to)820-828
    Number of pages9
    JournalEnergy Advances
    Volume2
    Issue number6
    DOIs
    Publication statusPublished - 1 Jun 2023

    Bibliographical note

    Funding Information:
    We acknowledge funding from the initiative “Computational Sciences for Energy Research” of Shell and NWO grant no. 15CSTT05. X. Z. acknowledges financial support from the China Scholarship Council grant no. CSC201806240322. This work was sponsored by NWO Exact and Natural Sciences for the use of the supercomputer facilities.

    Publisher Copyright:
    © 2023 RSC.

    Funding

    We acknowledge funding from the initiative “Computational Sciences for Energy Research” of Shell and NWO grant no. 15CSTT05. X. Z. acknowledges financial support from the China Scholarship Council grant no. CSC201806240322. This work was sponsored by NWO Exact and Natural Sciences for the use of the supercomputer facilities.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

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