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Rational Design of Highly Stable and Active Single-Atom Modified S-MXene as Cathode Catalysts for Li-S Batteries

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10258137" target="_blank" >RIV/61989100:27740/25:10258137 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11320/25:10501816

  • Result on the web

    <a href="https://advanced.onlinelibrary.wiley.com/doi/full/10.1002/adma.202501523" target="_blank" >https://advanced.onlinelibrary.wiley.com/doi/full/10.1002/adma.202501523</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/adma.202501523" target="_blank" >10.1002/adma.202501523</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Rational Design of Highly Stable and Active Single-Atom Modified S-MXene as Cathode Catalysts for Li-S Batteries

  • Original language description

    The practical application of Li-S batteries is hindered by the shuttle effect and sluggish sulfur conversion kinetics. To address these challenges, this work proposes an efficient strategy by introducing single atoms (SAs) into sulfur-functionalized MXenes (S-MXenes) catalysts and evaluate their potential in Li-S batteries through first-principles calculations. Using high-throughput screening of various SA-modified S-MXenes, this work identifies 73 promising candidates that exhibit exceptional thermodynamic and kinetic stability, along with the effective immobilization of polysulfides. Notably, the incorporation of Ni, Cu, or Zn as SAs into S-MXenes results in a significant Gibbs free energy barrier reduction by 51%–75%, outperforming graphene-based catalysts. This reduction arises from SA-induced surface electron density that influences the adsorption energies of intermediates and thereby disrupts the scaling relations between Li₂S₂ and other key intermediates. Further enhancement in catalytic performance is achieved through strain engineering by shifting the d-band center of metal atoms to higher energy levels, increasing the chemical affinity for intermediates. To elucidate the intrinsic adsorption properties of intermediates, this work develops a machine learning model with high accuracy (R2 = 0.88), which underscores the pivotal roles of SA electronegativity and local coordination environment in determining adsorption strength, offering valuable insights for the rational design of catalysts. © 2025 Wiley-VCH GmbH.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10302 - Condensed matter physics (including formerly solid state physics, supercond.)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Advanced Materials

  • ISSN

    0935-9648

  • e-ISSN

  • Volume of the periodical

    37

  • Issue of the periodical within the volume

    28

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    16

  • Pages from-to

    2501523

  • UT code for WoS article

    001481720200001

  • EID of the result in the Scopus database

    2-s2.0-105004342431