Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
traditional research paradigms in the era of artificial intelligence and automation. An …
Black-box optimization for automated discovery
Conspectus In chemistry and materials science, researchers and engineers discover,
design, and optimize chemical compounds or materials with their professional knowledge …
design, and optimize chemical compounds or materials with their professional knowledge …
Adaptive neural decision tree for EEG based emotion recognition
Y Zheng, J Ding, F Liu, D Wang - Information Sciences, 2023 - Elsevier
An adaptive neural decision tree is investigated to recognize electroencephalogram (EEG)
emotion signal with ability of intelligently selecting network structure. Firstly, to overcome …
emotion signal with ability of intelligently selecting network structure. Firstly, to overcome …
Multiagent reinforcement learning-based adaptive sampling for conformational dynamics of proteins
DE Kleiman, D Shukla - Journal of Chemical Theory and …, 2022 - ACS Publications
Machine learning is increasingly applied to improve the efficiency and accuracy of molecular
dynamics (MD) simulations. Although the growth of distributed computer clusters has …
dynamics (MD) simulations. Although the growth of distributed computer clusters has …
Accelerating copolymer inverse design using monte carlo tree search
TK Patra, TD Loeffler, SKRS Sankaranarayanan - Nanoscale, 2020 - pubs.rsc.org
There exists a broad class of sequencing problems in soft materials such as proteins and
polymers that can be formulated as a heuristic search that involves decision making akin to …
polymers that can be formulated as a heuristic search that involves decision making akin to …
[HTML][HTML] Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins
JG Greener, DT Jones - PloS one, 2021 - journals.plos.org
Finding optimal parameters for force fields used in molecular simulation is a challenging and
time-consuming task, partly due to the difficulty of tuning multiple parameters at once …
time-consuming task, partly due to the difficulty of tuning multiple parameters at once …
Molecular simulations of amyloid beta assemblies
G Grasso, A Danani - Advances in Physics: X, 2020 - Taylor & Francis
Several neurodegenerative disorders arise from the abnormal protein aggregation in the
nervous tissue leading tointracellular inclusions or extracellular aggregates in specific brain …
nervous tissue leading tointracellular inclusions or extracellular aggregates in specific brain …
Learning with delayed rewards—a case study on inverse defect design in 2D materials
Defect dynamics in materials are of central importance to a broad range of technologies from
catalysis to energy storage systems to microelectronics. Material functionality depends …
catalysis to energy storage systems to microelectronics. Material functionality depends …
PaCS-Toolkit: Optimized Software Utilities for Parallel Cascade Selection Molecular Dynamics (PaCS-MD) Simulations and Subsequent Analyses
S Ikizawa, T Hori, TN Wijaya, H Kono… - The Journal of …, 2024 - ACS Publications
Parallel cascade selection molecular dynamics (PaCS-MD) is an enhanced conformational
sampling method conducted as a “repetition of time leaps in parallel worlds”, comprising …
sampling method conducted as a “repetition of time leaps in parallel worlds”, comprising …
Thirty years of molecular dynamics simulations on posttranslational modifications of proteins
Posttranslational modifications (PTMs) are an integral component to how cells respond to
perturbation. While experimental advances have enabled improved PTM identification …
perturbation. While experimental advances have enabled improved PTM identification …