香港城市大学王昕最新JACS丨配位环境调控双原子催化协同机制！
Merged summary
TL;DR - A JACS study uses large-scale DFT and machine-learning analysis to explain how coordination environments govern synergy in M₁M₂N₆ dual-atom catalysts. The findings offer a molecular-orbital framework for designing stable catalysts with tunable hydrogen adsorption.
- Screening over 400 models linked catalyst stability and adsorption behavior to metal d-orbital coupling.
- Direct dx²⁻ʸ² overlap in M₁−N₃−M₂−N₃−C weakens some M−N bonds but strongly tunes hydrogen adsorption through bridge-site binding.
- In M₁−N₄−M₂−N₄−C, bridging nitrogen 2p orbitals mediate coupling, preserving stability and producing milder terminal-site hydrogen adsorption.
- Machine-learning feature importance corroborated the stronger influence of the second metal in the directly coupled N₃ configuration.
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香港城市大学王昕最新JACS丨配位环境调控双原子催化协同机制！
TL;DR - A JACS study uses large-scale DFT and machine-learning analysis to explain how coordination environments govern synergy in M₁M₂N₆ dual-atom catalysts. The findings offer a molecular-orbital framework for designing stable catalysts with tunable hydrogen adsorption.
- Screening over 400 models linked catalyst stability and adsorption behavior to metal d-orbital coupling.
- Direct dx²⁻ʸ² overlap in M₁−N₃−M₂−N₃−C weakens some M−N bonds but strongly tunes hydrogen adsorption through bridge-site binding.
- In M₁−N₄−M₂−N₄−C, bridging nitrogen 2p orbitals mediate coupling, preserving stability and producing milder terminal-site hydrogen adsorption.
- Machine-learning feature importance corroborated the stronger influence of the second metal in the directly coupled N₃ configuration.