Felix Uhl

Materials Chemistry · 2018

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 9 citations into it

Whom Felix Uhl trusts overall

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

1. J. Behler

Papers from Felix Uhl's perspective

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

1. Generalized neural-network representation of high-dimensional potential-energy surfaces.
2. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density.
3. GROMACS: Fast, flexible, and free
4. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu.
5. Water: From Clusters to the Bulk. (Angewandte Chemie)
6. Accuracy and transferability of Gaussian approximation potential models for tungsten
7. Accurate Force Field for Molybdenum by Machine Learning Large Materials Data
8. Machine learning based interatomic potential for amorphous carbon
9. Comparing molecules and solids across structural and alchemical space.
10. Understanding molecular simulation : from algorithms to applications. 2nd ed.

Their papers

• High-dimensional neural network potentials for solvation: The case of protonated water clusters in helium. (2018) — 40 citations