Jonathan Schmidt

Materials Chemistry · 2017–2020

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

Subfields

• Materials Chemistry — 43 citations into it
• Atomic and Molecular Physics, and Optics — 28 citations into it

Whom Jonathan Schmidt trusts overall

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

1. J. Perdew
2. Axel D. Becke
3. Fabien Tran
4. Rickard Armiento
5. Peter Blaha

Papers from Jonathan Schmidt's perspective

Ordered by how strongly the researchers Jonathan Schmidt trusts endorse each paper. Same corpus, a different order for every researcher.

1. Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties.
2. Functional designed to include surface effects in self-consistent density functional theory
3. Challenges for density functional theory. (Chemical Reviews)
4. A simple effective potential for exchange. (Journal of Chemical Physics)
5. Accurate band gaps of semiconductors and insulators with a semilocal exchange-correlation potential. (Physical Review Letters)
6. First-principles calculations for point defects in solids
7. Density-functional exchange-energy approximation with correct asymptotic behavior.
8. Machine-Learning-Assisted Accurate Band Gap Predictions of Functionalized MXene (Chemistry of Materials)
9. Resolution of the Band Gap Prediction Problem for Materials Design.
10. Density-functional thermochemistry. III. The role of exact exchange

Their papers

• Predicting the Thermodynamic Stability of Solids Combining Density Functional Theory and Machine Learning (2017) — 306 citations
• Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning (2020) — 300 citations