Compositionally restricted attention-based network for materials property predictions

AYT Wang, SK Kauwe, RJ Murdock… - Npj Computational …, 2021 - nature.com
In this paper, we demonstrate an application of the Transformer self-attention mechanism in
the context of materials science. Our network, the Compositionally Restricted Attention …

Machine learning for structural materials

TD Sparks, SK Kauwe, ME Parry… - Annual Review of …, 2020 - annualreviews.org
The development of structural materials with outstanding mechanical response has long
been sought for innumerable industrial, technological, and even biomedical applications …

Core electron count as a versatile and accurate new descriptor for sorting mechanical properties of diverse transition metal compounds

R Zhang, X Gu, K Zhang, X Gao, C Liu… - Advanced …, 2023 - Wiley Online Library
Transition‐metal light‐element compounds show superb mechanical, chemical, and thermal
properties, and accurate descriptors are important to sorting targeted properties among this …

High-pressure studies of size dependent yield strength in rhenium diboride nanocrystals

S Hu, SG Hamilton, CL Turner, DD Robertson… - Nanoscale …, 2024 - pubs.rsc.org
The superhard ReB2 system is the hardest pure phase diboride synthesized to date.
Previously, we have demonstrated the synthesis of nano-ReB2 and the use of this …

CrabNet for explainable deep learning in materials science: bridging the gap between academia and industry

AYT Wang, MS Mahmoud, M Czasny… - Integrating Materials and …, 2022 - Springer
Despite recent breakthroughs in deep learning for materials informatics, there exists a
disparity between their popularity in academic research and their limited adoption in the …

Virtual issue on machine-learning discoveries in materials science

AO Oliynyk, JM Buriak - Chemistry of Materials, 2019 - ACS Publications
Applications of machine learning, and machine learning-based models in materials
chemistry, are a rapidly growing area of research. Traditional methods of exploration are …

Twenty years of exceptional success: The molecular education and research consortium in undergraduate computational chemistry (MERCURY)

GC Shields - International Journal of Quantum Chemistry, 2020 - Wiley Online Library
The molecular education and research consortium in undergraduate computational
chemistry (MERCURY) consortium, established in 2000, has contributed greatly to the …

[HTML][HTML] Predicting active, selective and stable Mo2C–based bimetallic carbides for direct deoxygenation and hydrogenation reactions: A computational screening

S Bathla, RWJ Tan, SH Mushrif - Catalysis Today, 2025 - Elsevier
Transition metal carbides (TMCs), especially molybdenum carbide (Mo 2 C), represent an
economical and attractive alternative to precious noble metal catalysts for processes …

[HTML][HTML] Exploring the hardness and high-pressure behavior of osmium and ruthenium-doped rhenium diboride solid solutions

S Hu, LE Pangilinan, CL Turner, R Mohammadi… - APL Materials, 2023 - pubs.aip.org
Rhenium diboride (ReB 2) exhibits high differential strain due to its puckered boron sheets
that impede shear deformation. Here, we demonstrate the use of solid solution formation to …

Synthesis and characterization of polycrystalline Mo2BC ceramic

S Wang, X Pang, Z Zhang, B Chang, J Yang… - Journal of the European …, 2021 - Elsevier
Single-phase polycrystalline Mo 2 BC ceramic bulks were synthesized successfully from
molybdenum, boron, and graphite powders using the spark plasma sintering method …