Deep dive into machine learning density functional theory for materials science and chemistry

L Fiedler, K Shah, M Bussmann, A Cangi - Physical Review Materials, 2022 - APS
With the growth of computational resources, the scope of electronic structure simulations has
increased greatly. Artificial intelligence and robust data analysis hold the promise to …

[HTML][HTML] Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations

DEP Klenam, TK Asumadu, M Vandadi, N Rahbar… - Results in …, 2023 - Elsevier
Data science and material informatics are gaining traction in alloy design. This is due to
increasing infrastructure, computational capabilities and established open-source …

A deep learning framework to emulate density functional theory

BG del Rio, B Phan, R Ramprasad - npj Computational Materials, 2023 - nature.com
Density functional theory (DFT) has been a critical component of computational materials
research and discovery for decades. However, the computational cost of solving the central …

[HTML][HTML] GlacierNet2: A hybrid Multi-Model learning architecture for alpine glacier mapping

Z Xie, UK Haritashya, VK Asari, MP Bishop… - International Journal of …, 2022 - Elsevier
In recent decades, climate change has significantly affected glacier dynamics, resulting in
mass loss and an increased risk of glacier-related hazards including supraglacial and …

[HTML][HTML] Precursory motion and deformation mechanism of the 2018 Xe Pian-Xe Namnoy dam Collapse, Laos: Insights from satellite radar interferometry

L Xie, W Xu, X Ding - International Journal of Applied Earth Observation and …, 2022 - Elsevier
The sudden failure of hydraulic dams poses catastrophic hydrological risks to local
communities and environments. The 2018 Xe Pian-Xe Namnoy Dam collapse in Southern …

Machine learning approach to transform scattering parameters to complex permittivities

R Tempke, L Thomas, C Wildfire… - Journal of Microwave …, 2021 - Taylor & Francis
This study investigates the application of artificial neural networks to determine the complex
dielectric material properties derived from experimental VNA scattering parameter …

[PDF][PDF] Results in Materials

DEP Klenam, TK Asumadu, M Vandadi, N Rahbar… - researchgate.net
Data science and material informatics are gaining traction in alloy design. This is due to
increasing infrastructure, computational capabilities and established open-source …