ArticleNature communications2023
Electron transfer rules of minerals under pressure informed by machine learning.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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.
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Who cites it
5 citing papers in PubMed.
- Discovering physical laws with parallel symbolic enumeration.Nature computational science · 2026Article
- Machine-learning-assisted photonic device development: a multiscale approach from theory to characterization.Nanophotonics (Berlin, Germany) · 2025Review
- A MID-1DC+LRT Multi-Task Model for SOH Assessment and RUL Prediction of Mechanical Systems.Sensors (Basel, Switzerland) · 2025Article
- Inefficient nitrogen transport to the lower mantle by sediment subduction.Nature communications · 2024Article
- Electron transfer rules of minerals under pressure informed by machine learning.Nature communications · 2023Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Electron transfer is the most elementary process in nature, but the existing electron transfer rules are seldom applied to high-pressure situations, such as in the deep Earth. Here we show a deep learning model to obtain the electronegativity of 96 elements under arbitrary pressure, and a regressed unified formula to quantify its relationship with pressure and electronic configuration. The relative work function of minerals is further predicted by electronegativity, presenting a decreasing trend with pressure because of pressure-induced electron delocalization. Using the work function as the case study of electronegativity, it reveals that the driving force behind directional electron transfer results from the enlarged work function difference between compounds with pressure. This well explains the deep high-conductivity anomalies, and helps discover the redox reactivity between widespread Fe(II)-bearing minerals and water during ongoing subduction. Our results give an insight into the fundamental physicochemical properties of elements and their compounds under pressure.
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Registered trials
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