Self-driving laboratories for chemistry and materials science
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …
Through the automation of experimental workflows, along with autonomous experimental …
Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science
Machine learning has been pervasively touching many fields of science. Chemistry and
materials science are no exception. While machine learning has been making a great …
materials science are no exception. While machine learning has been making a great …
Adaptive Photochemical Amination via Co (II) Catalysis
G Song, J Song, Q Li, T Kang, J Dong, G Li… - Journal of the …, 2024 - ACS Publications
Transition-metal-catalyzed amination of aryl halides is one of the most employed methods
for constructing N-arylation adducts. However, the broad success of these reactions largely …
for constructing N-arylation adducts. However, the broad success of these reactions largely …
Reinforcement Learning for Improving Chemical Reaction Performance
Deep learning (DL) methods have gained notable prominence in predictive and generative
tasks in molecular space. However, their application in chemical reactions remains grossly …
tasks in molecular space. However, their application in chemical reactions remains grossly …
Machine learning-guided strategies for reaction conditions design and optimization
This review surveys the recent advances and challenges in predicting and optimizing
reaction conditions using machine learning techniques. The paper emphasizes the …
reaction conditions using machine learning techniques. The paper emphasizes the …
Learning Mixture-of-Experts for General-Purpose Black-Box Discrete Optimization
Real-world applications involve various discrete optimization problems. Designing a
specialized optimizer for each of these problems is challenging, typically requiring …
specialized optimizer for each of these problems is challenging, typically requiring …
How to do impactful research in artificial intelligence for chemistry and materials science
Machine learning has been pervasively touching many fields of science. Chemistry and
materials science are no exception. While machine learning has been making a great …
materials science are no exception. While machine learning has been making a great …
Text-Augmented Multimodal LLMs for Chemical Reaction Condition Recommendation
Y Zhang, R Yu, K Zeng, D Li, F Zhu, X Yang… - arXiv preprint arXiv …, 2024 - arxiv.org
High-throughput reaction condition (RC) screening is fundamental to chemical synthesis.
However, current RC screening suffers from laborious and costly trial-and-error workflows …
However, current RC screening suffers from laborious and costly trial-and-error workflows …
Surrogate-guided optimization in quantum networks
We propose an optimization algorithm to improve the design and performance of quantum
communication networks. When physical architectures become too complex for analytical …
communication networks. When physical architectures become too complex for analytical …
Application of the Digital Annealer Unit in Optimizing Chemical Reaction Conditions for Enhanced Production Yields
SC Li, PH Wang, JW Su, WY Chiang, SH Huang… - arXiv preprint arXiv …, 2024 - arxiv.org
Finding appropriate reaction conditions that yield high product rates in chemical synthesis is
crucial for the chemical and pharmaceutical industries. However, due to the vast chemical …
crucial for the chemical and pharmaceutical industries. However, due to the vast chemical …