Gaussian process regression for materials and molecules

VL Deringer, AP Bartók, N Bernstein… - Chemical …, 2021 - ACS Publications
We provide an introduction to Gaussian process regression (GPR) machine-learning
methods in computational materials science and chemistry. The focus of the present review …

Machine learning in energy storage materials

ZH Shen, HX Liu, Y Shen, JM Hu… - Interdisciplinary …, 2022 - Wiley Online Library
With its extremely strong capability of data analysis, machine learning has shown versatile
potential in the revolution of the materials research paradigm. Here, taking dielectric …

Multi-scale computer-aided design and photo-controlled macromolecular synthesis boosting uranium harvesting from seawater

Z Liu, Y Lan, J Jia, Y Geng, X Dai, L Yan, T Hu… - Nature …, 2022 - nature.com
By integrating multi-scale computational simulation with photo-regulated macromolecular
synthesis, this study presents a new paradigm for smart design while customizing polymeric …

Advancing Predictive Risk Assessment of Chemicals via Integrating Machine Learning, Computational Modeling, and Chemical/Nano‐Quantitative Structure‐Activity …

AV Singh, M Varma, M Rai… - Advanced Intelligent …, 2024 - Wiley Online Library
The escalating use of novel chemicals and nanomaterials (NMs) across diverse sectors
underscores the need for advanced risk assessment methods to safeguard human health …

Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: A review

LE Vivanco-Benavides, CL Martínez-González… - Computational Materials …, 2022 - Elsevier
Abstract Machine learning has proven to be technically flexible in recent years, which allows
it to be successfully implemented in problems in various areas of knowledge. Carbon …

[HTML][HTML] Understanding contact electrification at water/polymer interface

Y Nan, J Shao, M Willatzen, ZL Wang - Research, 2022 - spj.science.org
Contact electrification (CE) involves a complex interplay of physical interactions in realistic
material systems. For this reason, scientific consensus on the qualitative and quantitative …

Reversible assembly of nanoparticles: theory, strategies and computational simulations

D Gentili, G Ori - Nanoscale, 2022 - pubs.rsc.org
The significant advances in synthesis and functionalization have enabled the preparation of
high-quality nanoparticles that have found a plethora of successful applications. The unique …

AI for dielectric capacitors

RL Liu, J Wang, ZH Shen, Y Shen - Energy Storage Materials, 2024 - Elsevier
Dielectric capacitors, characterized by ultra-high power densities, have been widely used in
Internet of Everything terminals and vigorously developed to improve their energy storage …

Upgrading carbonaceous materials: Coal, tar, pitch, and beyond

X Zang, Y Dong, C Jian, N Ferralis, JC Grossman - Matter, 2022 - cell.com
Heavy carbonaceous materials (HCMs) such as coal are mostly used for nonrenewable
power generation, while derivatives such as tar and pitch are often discarded by-products …