ArticleNature communications2024
Machine learning-based design of electrocatalytic materials towards high-energy lithium||sulfur batteries development.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Machine Learning-Assisted Screening of Non-Adjacent Dual-Atom Catalysts on N-Doped Graphene: Insights Into the Electron "Storage-Feedback" Mechanism for NSmall (Weinheim an der Bergstrasse, Germany) · 2026Article
- Tuning the Conversion Mechanisms of Metal-Sulfur Batteries: From Nanostructures to Single Atoms.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Machine Learning-Driven Nanoscale Synthesis for Electrocatalytic Performance: From Data-Driven Methodologies to Closed-Loop Optimization.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Multidimensional Nanostructure Engineering in Practical Lithium-sulfur Batteries.Small methods · 2026Review
- From Mononuclear to Trinuclear: Tailoring Coordination Metal Cluster Node for High-Energy Li-S Batteries.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Orientation-Entropy-Mediated Derivative Cu Sites for Selective COAngewandte Chemie (International ed. in English) · 2026Article
- Beyond d-Band Catalysis: A Critical Review and Descriptor Framework for Rare-Earth Engineering in Lithium-Sulfur Batteries.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Practical Lithium-Sulfur Batteries: An Integrated Design Roadmap from High-Loading Cathodes to High-Energy Pouch Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Breaking the Limitations of Sulfur Redox Kinetics by Accelerated LiNano-micro letters · 2026Article
- Accelerated discovery of highly stable ruthenium-based high-entropy oxides for acidic oxygen evolution.Science advances · 2026Article
- Active site design enables industrial scale HNature communications · 2026Article
- W/V Dual-Atom Doping MoSNano-micro letters · 2026Article
- Applications and Advances of Machine Learning in the Development of Solid-State Electrolytes for Lithium-Ion Batteries.ACS omega · 2025Review
- Spin chemistry: the key to revolutionizing energy storage and conversion efficiency.Chemical science · 2025Review
- Uncovering battery electrochemical mechanisms by artificial intelligence.National science review · 2025Review
- Decoding single-crystal lithium growth through solid electrolyte interphase omics.Nature communications · 2025Article
- Machine learning-based design of electrocatalytic materials towards high-energy lithium||sulfur batteries development.Nature communications · 2024Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
The practical development of Li | |S batteries is hindered by the slow kinetics of polysulfides conversion reactions during cycling. To circumvent this limitation, researchers suggested the use of transition metal-based electrocatalytic materials in the sulfur-based positive electrode. However, the atomic-level interactions among multiple electrocatalytic sites are not fully understood. Here, to improve the understanding of electrocatalytic sites, we propose a multi-view machine-learned framework to evaluate electrocatalyst features using limited datasets and intrinsic factors, such as corrected d orbital properties. Via physicochemical characterizations and theoretical calculations, we demonstrate that orbital coupling among sites induces shifts in band centers and alterations in the spin state, thus influencing interactions with polysulfides and resulting in diverse Li-S bond breaking and lithium migration barriers. Using a carbon-coated Fe/Co electrocatalyst (synthesized using recycled Li-ion battery electrodes as raw materials) at the positive electrode of a Li | |S pouch cell with high sulfur loading and lean electrolyte conditions, we report an initial specific energy of 436 Wh kg
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.