Integrating Data Mining and Natural Language Processing to Construct a Melting Point Database for Organometallic Compounds
As semiconductor devices are miniaturized, the importance of atomic layer deposition (ALD)
technology is growing. When designing ALD precursors, it is important to consider the …
technology is growing. When designing ALD precursors, it is important to consider the …
[HTML][HTML] Predictive modeling of critical temperatures in magnesium compounds using transfer learning
This study presents a transfer learning approach for discovering potential Mg-based
superconductors utilizing a comprehensive target dataset. Initially, a large source dataset …
superconductors utilizing a comprehensive target dataset. Initially, a large source dataset …
Enhancing Predictions of Experimental Band Gap Using Machine Learning and Knowledge Transfer
Density functional theory (DFT) calculations using the generalized gradient approximation
(GGA) functional are known to underestimate the bandgap (E g) compared with …
(GGA) functional are known to underestimate the bandgap (E g) compared with …
Harnessing graph convolutional neural networks for identification of glassy states in metallic glasses
EJ Gurniak, S Yuan, X Ren, PS Branicio - Computational Materials Science, 2024 - Elsevier
Abstract Graph Convolutional Neural Networks (GCNNs) have emerged as powerful tools
for analyzing materials. In this study, we employ GCNNs to examine structural characteristics …
for analyzing materials. In this study, we employ GCNNs to examine structural characteristics …