Toward autonomous materials research: Recent progress and future challenges
The modus operandi in materials research and development is combining existing data with
an understanding of the underlying physics to create and test new hypotheses via …
an understanding of the underlying physics to create and test new hypotheses via …
Application of machine learning classifiers to X‐ray diffraction imaging with medically relevant phantoms
Purpose Recent studies have demonstrated the ability to rapidly produce large field of view
X‐ray diffraction (XRD) images, which provide rich new data relevant to the understanding …
X‐ray diffraction (XRD) images, which provide rich new data relevant to the understanding …
Deep-freeze graph training for latent learning
VN Romanov - Computational Materials Science, 2021 - Elsevier
Scientific and engineering advances are primarily driven by multi-tier conceptual constructs
and conditional theoretical frameworks. The theories allow predictions of hypothetical …
and conditional theoretical frameworks. The theories allow predictions of hypothetical …
Crystals with Transformers on Graphs, for Prediction of Unconventional Crystal Material Properties and the Benchmark
The ionic bonding across the lattice and ordered microscopic structures endow crystals with
unique symmetry and determine their macroscopic properties. Unconventional crystals, in …
unique symmetry and determine their macroscopic properties. Unconventional crystals, in …