Maxim Ziatdinov
Hivatkozott rá
Hivatkozott rá
Deep learning of atomically resolved scanning transmission electron microscopy images: chemical identification and tracking local transformations
M Ziatdinov, O Dyck, A Maksov, X Li, X Sang, K Xiao, RR Unocic, ...
ACS nano 11 (12), 12742-12752, 2017
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics
RK Vasudevan, K Choudhary, A Mehta, R Smith, G Kusne, F Tavazza, ...
MRS communications 9 (3), 821-838, 2019
Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS2
A Maksov, O Dyck, K Wang, K Xiao, DB Geohegan, BG Sumpter, ...
npj Computational Materials 5 (1), 12, 2019
Learning surface molecular structures via machine vision
M Ziatdinov, A Maksov, SV Kalinin
npj Computational Materials 3 (1), 31, 2017
Atom-by-atom fabrication with electron beams
O Dyck, M Ziatdinov, DB Lingerfelt, RR Unocic, BM Hudak, AR Lupini, ...
Nature Reviews Materials 4 (7), 497-507, 2019
Chemical robotics enabled exploration of stability in multicomponent lead halide perovskites via machine learning
K Higgins, SM Valleti, M Ziatdinov, SV Kalinin, M Ahmadi
ACS Energy Letters 5 (11), 3426-3436, 2020
Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study
M Ziatdinov, O Dyck, X Li, BG Sumpter, S Jesse, RK Vasudevan, ...
Science advances 5 (9), eaaw8989, 2019
Atomic-scale observation of structural and electronic orders in the layered compound α-RuCl3
M Ziatdinov, A Banerjee, A Maksov, T Berlijn, W Zhou, HB Cao, JQ Yan, ...
Nature communications 7 (1), 13774, 2016
Machine learning in scanning transmission electron microscopy
SV Kalinin, C Ophus, PM Voyles, R Erni, D Kepaptsoglou, V Grillo, ...
Nature Reviews Methods Primers 2 (1), 11, 2022
Role of edge geometry and chemistry in the electronic properties of graphene nanostructures
S Fujii, M Ziatdinov, M Ohtsuka, K Kusakabe, M Kiguchi, T Enoki
Faraday discussions 173, 173-199, 2014
Automated and autonomous experiments in electron and scanning probe microscopy
SV Kalinin, M Ziatdinov, J Hinkle, S Jesse, A Ghosh, KP Kelley, AR Lupini, ...
ACS nano 15 (8), 12604-12627, 2021
Experimental discovery of structure–property relationships in ferroelectric materials via active learning
Y Liu, KP Kelley, RK Vasudevan, H Funakubo, MA Ziatdinov, SV Kalinin
Nature Machine Intelligence 4 (4), 341-350, 2022
Direct imaging of monovacancy-hydrogen complexes in a single graphitic layer
M Ziatdinov, S Fujii, K Kusakabe, M Kiguchi, T Mori, T Enoki
Physical Review B 89 (15), 155405, 2014
Visualization of electronic states on atomically smooth graphitic edges with different types of hydrogen termination
M Ziatdinov, S Fujii, K Kusakabe, M Kiguchi, T Mori, T Enoki
Physical Review B—Condensed Matter and Materials Physics 87 (11), 115427, 2013
Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform
R Kannan, AV Ievlev, N Laanait, MA Ziatdinov, RK Vasudevan, S Jesse, ...
Advanced Structural and Chemical Imaging 4, 1-20, 2018
Machine learning for high-throughput experimental exploration of metal halide perovskites
M Ahmadi, M Ziatdinov, Y Zhou, EA Lass, SV Kalinin
Joule 5 (11), 2797-2822, 2021
Bowl inversion and electronic switching of buckybowls on gold
S Fujii, M Ziatdinov, S Higashibayashi, H Sakurai, M Kiguchi
Journal of the American Chemical Society 138 (37), 12142-12149, 2016
Exploring order parameters and dynamic processes in disordered systems via variational autoencoders
SV Kalinin, O Dyck, S Jesse, M Ziatdinov
Science Advances 7 (17), eabd5084, 2021
Phases and interfaces from real space atomically resolved data: physics-based deep data image analysis
RK Vasudevan, M Ziatdinov, S Jesse, SV Kalinin
Nano letters 16 (9), 5574-5581, 2016
Hypothesis learning in automated experiment: application to combinatorial materials libraries
MA Ziatdinov, Y Liu, AN Morozovska, EA Eliseev, X Zhang, I Takeuchi, ...
Advanced Materials 34 (20), 2201345, 2022
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Cikkek 1–20