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Machine learning methods for small data challenges in molecular science
B Dou, Z Zhu, E Merkurjev, L Ke, L Chen… - Chemical …, 2023 - ACS Publications
Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
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 …
Applications of machine learning in alloy catalysts: rational selection and future development of descriptors
Z Yang, W Gao - Advanced Science, 2022 - Wiley Online Library
At present, alloys have broad application prospects in heterogeneous catalysis, due to their
various catalytic active sites produced by their vast element combinations and complex …
various catalytic active sites produced by their vast element combinations and complex …
Atomic-level structure determination of amorphous molecular solids by NMR
Abstract Structure determination of amorphous materials remains challenging, owing to the
disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder …
disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder …
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 …
Organic crystal structure prediction via coupled generative adversarial networks and graph convolutional networks
Organic crystal structures exert a profound impact on the physicochemical properties and
biological effects of organic compounds. Quantum mechanics (QM)–based crystal structure …
biological effects of organic compounds. Quantum mechanics (QM)–based crystal structure …
[HTML][HTML] Top 20 influential AI-based technologies in chemistry
VP Ananikov - Artificial Intelligence Chemistry, 2024 - Elsevier
The beginning and ripening of digital chemistry is analyzed focusing on the role of artificial
intelligence (AI) in an expected leap in chemical sciences to bring this area to the next …
intelligence (AI) in an expected leap in chemical sciences to bring this area to the next …
Knowledge-reused transfer learning for molecular and materials science
Leveraging big data analytics and advanced algorithms to accelerate and optimize the
process of molecular and materials design, synthesis, and application has revolutionized the …
process of molecular and materials design, synthesis, and application has revolutionized the …
Synthesis, biological application, and computational study of a thymol-based molecule
S Akkoc, MT Muhammed - Journal of Biologically Active Products …, 2024 - Taylor & Francis
A thymol-based molecule was synthesized and characterized. The anti-proliferative activity
of molecule 4 was tested in vitro in three cancer cell lines and a healthy human cell line. The …
of molecule 4 was tested in vitro in three cancer cell lines and a healthy human cell line. The …
Graph comparison of molecular crystals in band gap prediction using neural networks
T Taniguchi, M Hosokawa, T Asahi - ACS omega, 2023 - ACS Publications
In material informatics, the representation of the material structure is fundamentally essential
to obtaining better prediction results, and graph representation has attracted much attention …
to obtaining better prediction results, and graph representation has attracted much attention …