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Machine-learning-assisted design of a binary descriptor to decipher electronic and structural effects on sulfur reduction kinetics | Nature Catalysis
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商品詳細情報
| 管理番号 |
新品 ：782336682
中古 ：782336682-1 |
メーカー | c70ce44b | 発売日 | 2025-05-16 06:10 | 定価 | 7000円 | ||
|---|---|---|---|---|---|---|---|---|---|
| カテゴリ | |||||||||
Machine-learning-assisted design of a binary descriptor to decipher electronic and structural effects on sulfur reduction kinetics | Nature Catalysis
Machine-learning-assisted design of a binary descriptor to decipher electronic and structural effects on sulfur reduction kinetics | Nature Catalysis,The effect of NiO-Ni3N interfaces in in-situ formed heterostructure ultrafine nanoparticles on enhanced polysulfide regulation in lithium-sulfur batteries - ScienceDirect,Appreciating the role of polysulfides in lithium-sulfur batteries and regulation strategies by electrolytes engineering - ScienceDirect,Kesterite Films Processed with Organic Solvents: Unveiling the Impact of Carbon‐Rich Fine‐Grain‐Layer Formation on Solar‐Cell Performance - Javed - 2024 - Energy Technology - Wiley Online Library,A Single Model for the Thermodynamics and Kinetics of Metal Exsolution from Perovskite Oxides | Journal of the American Chemical Society
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