Corey Oses
Materials Chemistry · 2015–2020
A researcher in the Science corpus: 5 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Materials Chemistry — 97 citations into it
- Statistics and Probability — 5 citations into it
Whom Corey Oses trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Stefano Curtarolo
- Radford M. Neal
- Abhishek Sarkar
- W. Setyawan
- Jien‐Wei Yeh
- Daniel B. Miracle
- Axel van de Walle
- Cormac Toher
- Trevor J. Hastie
- D. Bérardan
Who trusts Corey Oses overall
Papers from Corey Oses's perspective
Ordered by how strongly the researchers Corey Oses trusts endorse each paper. Same corpus, a different order for every researcher.
- Generalized Gradient Approximation Made Simple.
- AFLOW: An automatic framework for high-throughput materials discovery
- The inorganic crystal structure data base
- NEW METHOD FOR CALCULATING THE ONE-PARTICLE GREEN'S FUNCTION WITH APPLICATION TO THE ELECTRON-GAS PROBLEM
- Accuracy of ab initio methods in predicting the crystal structures of metals: A review of 80 binary alloys
- AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations
- High-throughput computational screening of thermal conductivity, Debye temperature, and Grüneisen parameter using a quasiharmonic Debye model
- Book-Review - Numerical Recipes in Pascal - the Art of Scientific Computing
- Reformulation of DFT + U as a pseudohybrid hubbard density functional for accelerated materials discovery
- Atoms, molecules, solids, and surfaces: Applications of the generalized gradient approximation for exchange and correlation.
Their papers
- Universal fragment descriptors for predicting properties of inorganic crystals (2016) — 599 citations
- The AFLOW standard for high-throughput materials science calculations (2015) — 356 citations
- High-entropy ceramics (2020) — 1,557 citations
- High-entropy high-hardness metal carbides discovered by entropy descriptors (2018) — 905 citations
- Machine learning modeling of superconducting critical temperature (2017) — 446 citations