P. Schultz

Modelling and Simulation in Materials Science and Engineering · with Mattsson · 2004–2020

A researcher in the Science corpus: 4 papers; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom P. Schultz trusts overall

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

1. Roberto Car
2. S. Plimpton
3. Michele Parrinello
4. J. Perdew
5. C. Stampfl

Papers from P. Schultz's perspective

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

1. Generalized neural-network representation of high-dimensional potential-energy surfaces.
2. Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
3. Unified approach for molecular dynamics and density-functional theory.
4. Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons.
5. Machine learning based interatomic potential for amorphous carbon
6. Fast parallel algorithms for short-range molecular dynamics
7. A Chemist's Guide to Density Functional Theory
8. Materials Genome Initiative for Global Competitiveness
9. Identifying structural flow defects in disordered solids using machine-learning methods.
10. Transient computational homogenization for heterogeneous materials under dynamic excitation

Their papers

• Designing meaningful density functional theory calculations in materials science—a primer (2004) — 354 citations
• Roadmap on multiscale materials modeling (2020) — 162 citations
• Electronic structure of intrinsic defects in crystalline germanium telluride (2006) — 184 citations
• Nonequivalence of the generalized gradient approximations PBE and PW91 (2006) — 152 citations