Polarons in materials

C Franchini, M Reticcioli, M Setvin… - Nature Reviews Materials, 2021 - nature.com
Polarons are quasiparticles that easily form in polarizable materials due to the coupling of
excess electrons or holes with ionic vibrations. These quasiparticles manifest themselves in …

Deep learning analysis on microscopic imaging in materials science

M Ge, F Su, Z Zhao, D Su - Materials Today Nano, 2020 - Elsevier
Microscopic imaging providing the real-space information of matter, plays an important role
for understanding the correlations between structure and properties in the field of materials …

Materials informatics: From the atomic-level to the continuum

JM Rickman, T Lookman, SV Kalinin - Acta Materialia, 2019 - Elsevier
In recent years materials informatics, which is the application of data science to problems in
materials science and engineering, has emerged as a powerful tool for materials discovery …

Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS2

A Maksov, O Dyck, K Wang, K Xiao… - npj Computational …, 2019 - nature.com
Recent advances in scanning transmission electron microscopy (STEM) allow the real-time
visualization of solid-state transformations in materials, including those induced by an …

Mapping mesoscopic phase evolution during E-beam induced transformations via deep learning of atomically resolved images

RK Vasudevan, N Laanait, EM Ferragut… - npj Computational …, 2018 - nature.com
Understanding transformations under electron beam irradiation requires mapping the
structural phases and their evolution in real time. To date, this has mostly been a manual …

Toward electrochemical studies on the nanometer and atomic scales: Progress, challenges, and opportunities

SV Kalinin, O Dyck, N Balke, S Neumayer, WY Tsai… - ACS …, 2019 - ACS Publications
Electrochemical reactions and ionic transport underpin the operation of a broad range of
devices and applications, from energy storage and conversion to information technologies …

A self-driving microscope and the Atomic Forge

O Dyck, S Jesse, SV Kalinin - MRS Bulletin, 2019 - cambridge.org
MATERIAL MATTERS OPINION atomic motion demonstrated in a scanning tunneling
microscope by Eigler, 16–19 which ignited the field of nanotechnology. However, the range …

Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation

Y Liu, U Pratiush, J Bemis, R Proksch, R Emery… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid development of computation power and machine learning algorithms has paved
the way for automating scientific discovery with a scanning probe microscope (SPM). The …

A lightweight particle detection algorithm based on an improved YOLOv8

B Wang, P Liu, H Tian, H Ren, Y Cao, S Li… - Journal of Physics …, 2024 - iopscience.iop.org
A method for lightweight grain detection under transmission electron microscopy is
proposed to address the issues of inadequate detection accuracy, slow speed, and high …

Artificial Intelligence in Materials Science: Applications of Machine Learning to Extraction of Physically Meaningful Information from Atomic Resolution Microscopy …

AB Maksov - 2018 - trace.tennessee.edu
Materials science is the cornerstone for technological development of the modern world that
has been largely shaped by the advances in fabrication of semiconductor materials and …