MatGPT: A vane of materials informatics from past, present, to future
Combining materials science, artificial intelligence (AI), physical chemistry, and other
disciplines, materials informatics is continuously accelerating the vigorous development of …
disciplines, materials informatics is continuously accelerating the vigorous development of …
Materials data toward machine learning: advances and challenges
Machine learning (ML) is believed to have enabled a paradigm shift in materials research,
and in practice, ML has demonstrated its power in speeding up the cost-efficient discovery of …
and in practice, ML has demonstrated its power in speeding up the cost-efficient discovery of …
Charge injection engineering at organic/inorganic heterointerfaces for high-efficiency and fast-response perovskite light-emitting diodes
The development of advanced perovskite emitters has considerably improved the
performance of perovskite light-emitting diodes (LEDs). However, the further development of …
performance of perovskite light-emitting diodes (LEDs). However, the further development of …
Data-driven design of high-performance MASnxPb1-xI3 perovskite materials by machine learning and experimental realization
X Cai, F Liu, A Yu, J Qin, M Hatamvand… - Light: Science & …, 2022 - nature.com
The photovoltaic performance of perovskite solar cell is determined by multiple interrelated
factors, such as perovskite compositions, electronic properties of each transport layer and …
factors, such as perovskite compositions, electronic properties of each transport layer and …
Design of organic–inorganic hybrid heterostructured semiconductors via high-throughput materials screening for optoelectronic applications
Organic–inorganic hybrid semiconductors, of which organometal halide perovskites are
representative examples, have drawn significant research interest as promising candidates …
representative examples, have drawn significant research interest as promising candidates …
MaterialsAtlas. org: a materials informatics web app platform for materials discovery and survey of state-of-the-art
The availability and easy access of large-scale experimental and computational materials
data have enabled the emergence of accelerated development of algorithms and models for …
data have enabled the emergence of accelerated development of algorithms and models for …
Global instability index as a crystallographic stability descriptor of halide and chalcogenide perovskites
Crystallographic stability is an important factor that affects the stability of perovskites. The
stability dictates the commercial applications of lead-based organometal halide perovskites …
stability dictates the commercial applications of lead-based organometal halide perovskites …
AlphaMat: a material informatics hub connecting data, features, models and applications
The development of modern civil industry, energy and information technology is inseparable
from the rapid explorations of new materials. However, only a small fraction of materials …
from the rapid explorations of new materials. However, only a small fraction of materials …
Molecular engineering towards efficientwhite-light-emitting perovskite
Low-dimensional hybrid perovskites have demonstrated excellent performance as white-
light emitters. The broadband white emission originates from self-trapped excitons (STEs) …
light emitters. The broadband white emission originates from self-trapped excitons (STEs) …
Application of machine learning in material synthesis and property prediction
G Huang, Y Guo, Y Chen, Z Nie - Materials, 2023 - mdpi.com
Material innovation plays a very important role in technological progress and industrial
development. Traditional experimental exploration and numerical simulation often require …
development. Traditional experimental exploration and numerical simulation often require …