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      2D MOFs and their derivatives for electrocatalytic applications: Recent advances and new challenges

      , ,
      Coordination Chemistry Reviews
      Elsevier BV

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          Computational high-throughput screening of electrocatalytic materials for hydrogen evolution.

          The pace of materials discovery for heterogeneous catalysts and electrocatalysts could, in principle, be accelerated by the development of efficient computational screening methods. This would require an integrated approach, where the catalytic activity and stability of new materials are evaluated and where predictions are benchmarked by careful synthesis and experimental tests. In this contribution, we present a density functional theory-based, high-throughput screening scheme that successfully uses these strategies to identify a new electrocatalyst for the hydrogen evolution reaction (HER). The activity of over 700 binary surface alloys is evaluated theoretically; the stability of each alloy in electrochemical environments is also estimated. BiPt is found to have a predicted activity comparable to, or even better than, pure Pt, the archetypical HER catalyst. This alloy is synthesized and tested experimentally and shows improved HER performance compared with pure Pt, in agreement with the computational screening results.
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            Isolated Single Iron Atoms Anchored on N-Doped Porous Carbon as an Efficient Electrocatalyst for the Oxygen Reduction Reaction

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              Metal-organic frameworks and self-assembled supramolecular coordination complexes: comparing and contrasting the design, synthesis, and functionality of metal-organic materials.

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                Author and article information

                Journal
                Coordination Chemistry Reviews
                Coordination Chemistry Reviews
                Elsevier BV
                00108545
                December 2022
                December 2022
                : 472
                : 214777
                Article
                10.1016/j.ccr.2022.214777
                c9c8c89b-33d5-4ffc-b2f5-61fee4c1d698
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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