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March 31, 2026Nature CommunicationsOpen Access

Multi-field coupling enhanced plasmonic Moδ+ active site to efficiently hydrolyze ammonia borane

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Authors

PLPengcheng LiNTNengrong TuYYYang Yang

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Overview

This work demonstrates machine learning enhances ammonia borane hydrolysis in a novel catalyst, suggesting new paths for efficient energy conversion.

Key Points

  • The study aims to address the limitations of solar-driven ammonia borane hydrolysis by enhancing catalytic activity.
  • Utilized machine learning to develop multi-field coupling techniques.
  • Reconstructed unsaturated Mo<sup>δ+</sup> active sites for improved stability and activity.
  • Measured turnover frequency during hydrolysis over a 100-hour period.
  • Achieved a turnover frequency of up to 5806 min<sup>-1</sup> in ammonia borane hydrolysis.
  • Demonstrated that polarized electric fields improved carrier separation and electron accumulation.
  • Showed enhanced local electric fields facilitated better hot electron delocalization, lowering reaction barriers.

Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69cb645fe6a8c024954b8997https://doi.org/10.1038/s41467-026-71055-1
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