First-principles phonon calculations with phonopy and phono3py
A Togo - Journal of the Physical Society of Japan, 2023 - journals.jps.jp
Harmonic, quasi-harmonic, and anharmonic phonon properties of crystals are getting to be
better predicted using first-principles phonon calculations by virtue of the progress of the …
better predicted using first-principles phonon calculations by virtue of the progress of the …
Recent advances and applications of deep learning methods in materials science
Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …
Machine learning for high-entropy alloys: Progress, challenges and opportunities
High-entropy alloys (HEAs) have attracted extensive interest due to their exceptional
mechanical properties and the vast compositional space for new HEAs. However …
mechanical properties and the vast compositional space for new HEAs. However …
FAIR data enabling new horizons for materials research
The prosperity and lifestyle of our society are very much governed by achievements in
condensed matter physics, chemistry and materials science, because new products for …
condensed matter physics, chemistry and materials science, because new products for …
Mattergen: a generative model for inorganic materials design
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design
Abstract The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an
integrated infrastructure to accelerate materials discovery and design using density …
integrated infrastructure to accelerate materials discovery and design using density …
Human-and machine-centred designs of molecules and materials for sustainability and decarbonization
Breakthroughs in molecular and materials discovery require meaningful outliers to be
identified in existing trends. As knowledge accumulates, the inherent bias of human intuition …
identified in existing trends. As knowledge accumulates, the inherent bias of human intuition …
Machine learning for materials scientists: an introductory guide toward best practices
This Methods/Protocols article is intended for materials scientists interested in performing
machine learning-centered research. We cover broad guidelines and best practices …
machine learning-centered research. We cover broad guidelines and best practices …
Electronic-structure methods for materials design
The accuracy and efficiency of electronic-structure methods to understand, predict and
design the properties of materials has driven a new paradigm in research. Simulations can …
design the properties of materials has driven a new paradigm in research. Simulations can …