Journal Articles
2025
47.
Beyond the four core effects: revisiting thermoelectrics with a high-entropy design Materials Horizons (2025) DOI:10.1039/D5MH00356C (PDF)
46.
High entropy powering green energy: hydrogen, batteries, electronics, and catalysis npj Computational Materials 11 (2025) DOI:10.1038/s41524-025-01594-6 (PDF)
2024
45.
Atomic Ordering-Induced Ensemble Variation in Alloys Governs Electrocatalyst On/Off States Journal of the American Chemical Society 147 (2024) DOI:10.1021/jacs.4c11753 (PDF)
44.
Fermi energy engineering of enhanced plasticity in high-entropy carbides Acta Materialia 276 (2024) DOI:10.1016/j.actamat.2024.120117 (PDF)
43.
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange Digital Discovery 3 (2024) DOI:10.1039/D4DD00039K (PDF)
42.
Disordered enthalpy-entropy descriptor for high-entropy ceramics discovery Nature 625 (2024) DOI:10.1038/s41586-023-06786-y (PDF)
41.
Materials Design for Hypersonics Nature Communications 15 (2024) DOI:10.1038/s41467-024-46753-3 (PDF)
2023
40.
Influence of Processing on the Microstructural Evolution and Multiscale Hardness in Titanium Carbonitrides (TiCN) Produced via Field Assisted Sintering Technology Materialia 27 (2023) DOI:10.1016/j.mtla.2023.101682 (PDF)
39.
aflow++: a C++ framework for autonomous materials design Computational Materials Science 217 (2023) DOI:10.1016/j.commatsci.2022.111889 (PDF)
38.
aflow.org: a web ecosystem of databases, software and tools Computational Materials Science 216 (2023) DOI:10.1016/j.commatsci.2022.111808 (PDF)
37.
QH-POCC: taming tiling entropy in thermal expansion calculations of disordered materials Acta Materialia 245 (2023) DOI:10.1016/j.actamat.2022.118594 (PDF)
2022
36.
Plasmonic high-entropy carbides Nature Communications 13 (2022) DOI:10.1038/s41467-022-33497-1 (PDF)
35.
The Microscopic Diamond Anvil Cell: Stabilization of Superhard, Superconducting Carbon Allotropes at Ambient Pressure Angewandte Chemie 61 (2022) DOI:10.1002/anie.202205129 (PDF)
34.
Roadmap on Machine Learning in Electronic Structure Electronic Structure 4 (2022) DOI:10.1088/2516-1075/ac572f (PDF)
33.
Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping Frontiers in Physics 10 (2022) DOI:10.3389/fphy.2022.815863 (PDF)
32.
High-entropy ceramics: Propelling applications through disorder MRS Bulletin 47 (2022) DOI:10.1557/s43577-022-00281-x (PDF)
2021
31.
Settling the matter of the role of vibrations in the stability of high-entropy carbides Nature Communications 12 (2021) DOI:10.1038/s41467-021-25979-5 (PDF)
30.
Entropy Landscaping of High-Entropy Carbides Advanced Materials 33 (2021) DOI:10.1002/adma.202102904 (PDF)
29.
OPTIMADE: an API for exchanging materials data Scientific Data 8 (2021) DOI:10.1038/s41597-021-00974-z (PDF)
28.
Automated coordination corrected enthalpies with AFLOW-CCE Physical Review Materials 5 (2021) DOI:10.1103/PhysRevMaterials.5.043803 (PDF)
27.
The AFLOW Library of Crystallographic Prototypes: Part 3 Computational Materials Science 199 (2021) DOI:10.1016/j.commatsci.2021.110450 (PDF)
26.
Tin-pest problem as a test of density functionals using high-throughput calculations Physical Review Materials 5 (2021) DOI:10.1103/PhysRevMaterials.5.083608 (PDF)
25.
Carbon Stoichiometry and Mechanical Properties of High Entropy Carbides Acta Materialia 215 (2021) DOI:10.1016/j.actamat.2021.117051 (PDF)
2020
24.
On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning Nature Communications 11 (2020) DOI:10.1038/s41467-020-19597-w (PDF)
23.
Discovery of novel high-entropy ceramics via machine learning npj Computational Materials 6 (2020) DOI:10.1038/s41524-020-0317-6 (PDF)
2019
21.
Metallic glasses for biodegradable implants Acta Materialia 176 (2019) DOI:10.1016/j.actamat.2019.07.008 (PDF)
20.
Predicting Superhard Materials via a Machine Learning Informed Evolutionary Structure Search npj Computational Materials 5 (2019) DOI:10.1038/s41524-019-0226-8 (PDF)
19.
Unavoidable disorder and entropy in multi-component systems npj Computational Materials 5 (2019) DOI:10.1038/s41524-019-0206-z (PDF)
18.
Coordination corrected ab initio formation enthalpies npj Computational Materials 5 (2019) DOI:10.1038/s41524-019-0192-1 (PDF)
17.
AFLOW-QHA3P: Robust and automated method to compute thermodynamic properties of solids Physical Review Materials 3 (2019) DOI:10.1103/PhysRevMaterials.3.073801 (PDF)
2018
16.
AFLOW-CHULL: Cloud-oriented platform for autonomous phase stability analysis Journal of Chemical Information and Modeling 58 (2018) DOI:10.1021/acs.jcim.8b00393 (PDF)
15.
Data-driven design of inorganic materials with the Automatic Flow Framework for Materials Discovery MRS Bulletin 43 (2018) DOI:10.1557/mrs.2018.207 (PDF)
14.
High-entropy high-hardness metal carbides discovered by entropy descriptors Nature Communications 9 (2018) DOI:10.1038/s41467-018-07160-7 (PDF)
13.
Machine learning modeling of superconducting critical temperature npj Computational Materials 4 (2018) DOI:10.1038/s41524-018-0085-8 (PDF)
12.
AFLOW-ML: A RESTful API for machine-learning prediction of materials properties Computational Materials Science 152 (2018) DOI:10.1016/j.commatsci.2018.03.075 (PDF)
11.
AFLOW-SYM: platform for the complete, automatic and self-consistent symmetry analysis of crystals Acta Crystallographica Section A 74 (2018) DOI:10.1107/S2053273318003066 (PDF)
2017
10.
The structure and composition statistics of 6A binary and ternary structures Inorganic Chemistry 57 (2017) DOI:10.1021/acs.inorgchem.7b02462 (PDF)
9.
AFLUX: The LUX materials search API for the AFLOW data repositories Computational Materials Science 137 (2017) DOI:10.1016/j.commatsci.2017.04.036 (PDF)
8.
Universal Fragment Descriptors for Predicting Properties of Inorganic Crystals Nature Communications 8 (2017) DOI:10.1038/ncomms15679 (PDF)
7.
Combining the AFLOW GIBBS and elastic libraries to efficiently and robustly screening thermomechanical properties of solids Physical Review Materials 1 (2017) DOI:10.1103/PhysRevMaterials.1.015401 (PDF)
6.
A Computational High-Throughput Search for New Ternary Superalloys Acta Materialia 122 (2017) DOI:10.1016/j.actamat.2016.09.017 (PDF)
5.
Accelerated Discovery of New Magnets in the Heusler Alloy Family Science Advances 3 (2017) DOI:10.1126/sciadv.1602241 (PDF)
2016
4.
High-Throughput Computation of Thermal Conductivity of High-Temperature Solid Phases: The Case of Oxide and Fluoride Perovskites Physical Review X 6 (2016) DOI:10.1103/PhysRevX.6.041061 (PDF)
3.
Modeling Off-Stoichiometry Materials with a High-Throughput Ab-Initio Approach Chemistry of Materials 28 (2016) DOI:10.1021/acs.chemmater.6b01449 (PDF)
2015
2.
The AFLOW Standard for High-Throughput Materials Science Calculations Computational Materials Science 108A (2015) DOI:10.1016/j.commatsci.2015.07.019 (PDF)
1.
Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints Chemistry of Materials 27 (2015) DOI:10.1021/cm503507h (PDF)
Book Chapters
2019
3.
Automated computation of materials properties in Materials Informatics: Methods, Tools and Applications (2019) DOI:10.1002/9783527802265.ch7 (PDF)
2018
2.
Machine learning and high-throughput approaches to magnetism in Handbook of Materials Modeling. Volume 2 Applications: Current and Emerging Materials (2018) DOI:10.1007/978-3-319-50257-1_108-1 (PDF)
1.
The AFLOW Fleet for Materials Discovery in Handbook of Materials Modeling. Volume 1 Methods: Theory and Modeling (2018) DOI:10.1007/978-3-319-42913-7_63-2 (PDF)