Jin-Xun Liu

Materials Chemistry · 2015–2018

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 47 citations into it
• Renewable Energy, Sustainability and the Environment — 26 citations into it
• Computational Theory and Mathematics — 8 citations into it

Whom Jin-Xun Liu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Jeff Greeley
2. Matthias Rupp 

Papers from Jin-Xun Liu's perspective

Ordered by how strongly the researchers Jin-Xun Liu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials
2. Machine learning of accurate energy-conserving molecular force fields
3. Understanding Machine-learned Density Functionals
4. On representing chemical environments
5. Quantum-chemical insights from deep tensor neural networks
6. An overview on subgroup discovery: foundations and applications
7. Machine learning for quantum mechanics in a nutshell
8. Bypassing the Kohn-Sham equations with machine learning
9. Big data of materials science: critical role of the descriptor.
10. Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning

Their papers

• Machine learning for heterogeneous catalyst design and discovery (2018) — 369 citations
• Optimum Cu nanoparticle catalysts for CO2 hydrogenation towards methanol (2018) — 168 citations
• High Alcohols Synthesis via Fischer–Tropsch Reaction at Cobalt Metal/Carbide Interface (2015) — 233 citations