Machine learning in materials science: From explainable predictions to autonomous design
G Pilania - Computational Materials Science, 2021 - Elsevier
The advent of big data and algorithmic developments in the field of machine learning (and
artificial intelligence, in general) have greatly impacted the entire spectrum of physical …
artificial intelligence, in general) have greatly impacted the entire spectrum of physical …
Chalcogenide perovskites: tantalizing prospects, challenging materials
Chalcogenide perovskites have recently emerged into the spotlight as highly robust, earth
abundant, and nontoxic candidates for various energy conversion applications, not least …
abundant, and nontoxic candidates for various energy conversion applications, not least …
[HTML][HTML] Scope of machine learning in materials research—A review
This comprehensive review investigates the multifaceted applications of machine learning in
materials research across six key dimensions, redefining the field's boundaries. It explains …
materials research across six key dimensions, redefining the field's boundaries. It explains …
Crystal graph attention networks for the prediction of stable materials
Graph neural networks for crystal structures typically use the atomic positions and the atomic
species as input. Unfortunately, this information is not available when predicting new …
species as input. Unfortunately, this information is not available when predicting new …
Thermodynamic stability and anion ordering of perovskite oxynitrides
Perovskite oxynitrides (PONs) are a promising class of materials for applications ranging
from catalysis to photovoltaics. However, the vast space of single PON materials (ABO3–x N …
from catalysis to photovoltaics. However, the vast space of single PON materials (ABO3–x N …
Unfolding the role of B site-selective doping of aliovalent cations on enhancing sacrificial visible light-induced photocatalytic H2 and O2 evolution over BaTaO2N
The doping of foreign cations and anions is one of the effective strategies for engineering
defects and modulating the optical, electronic, and surface properties that directly govern the …
defects and modulating the optical, electronic, and surface properties that directly govern the …
Oxynitride, Oxyfluoride, and Nitrofluoride Perovskites: Theoretical Evaluation of Photon Absorption Properties for Solar Water Splitting
Photocatalytic water splitting represents a very promising but at the same time challenging
contribution to a clean and renewable route to produce hydrogen fuel. Developing efficient …
contribution to a clean and renewable route to produce hydrogen fuel. Developing efficient …
Designing workflows for materials characterization
Experimental science is enabled by the combination of synthesis, imaging, and functional
characterization organized into evolving discovery loop. Synthesis of new material is …
characterization organized into evolving discovery loop. Synthesis of new material is …
Anion-polarisation-directed short-range-order in antiperovskite Li 2 FeSO
Short-range ordering in cation-disordered cathodes can have a significant effect on their
electrochemical properties. Here, we characterise the cation short-range order in the …
electrochemical properties. Here, we characterise the cation short-range order in the …
A high-throughput study of oxynitride, oxyfluoride and nitrofluoride perovskites
Perovskite solar devices are nowadays the fastest advancing photovoltaic technology. Their
large-scale application is however restrained by instability and toxicity issues. Alloying is a …
large-scale application is however restrained by instability and toxicity issues. Alloying is a …