Applications of machine learning in perovskite materials
Z Wang, M Yang, X Xie, C Yu, Q Jiang… - … Composites and Hybrid …, 2022 - Springer
Abstract Machine learning (ML) offers the opportunities to discover certain unique properties
for typical material. Taking perovskite materials as an example, this review summarizes the …
for typical material. Taking perovskite materials as an example, this review summarizes the …
Applied machine learning for predicting the lanthanide-ligand binding affinities
Binding affinities of metal–ligand complexes are central to a multitude of applications like
drug design, chelation therapy, designing reagents for solvent extraction etc. While state-of …
drug design, chelation therapy, designing reagents for solvent extraction etc. While state-of …
Absorber layer thickness as a new feature in statistical learning tools of Perovskite solar cells
Recently, the development of Perovskite-based solar cells has emerged as a technological
alternative to photovoltaic generation with a higher efficiency/cost ratio. Many contributions …
alternative to photovoltaic generation with a higher efficiency/cost ratio. Many contributions …
Machine learning accelerated insights of perovskite materials
In recent years, lead-halide perovskite (LHP) have made tremendous progress in
photovoltaic and optoelectronic fields. However, stability and toxicity still are obstacles for …
photovoltaic and optoelectronic fields. However, stability and toxicity still are obstacles for …
Deep elastic strain engineering of materials electronic properties by machine learning
Z Shi - 2021 - dspace.mit.edu
The introduction of elastic strains has become an appealing strategy for providing unique
and exciting electronic properties in nanostructured materials. Recent successes in diamond …
and exciting electronic properties in nanostructured materials. Recent successes in diamond …