Maxim Ziatdinov
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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
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), 1-8, 2019
Learning surface molecular structures via machine vision
M Ziatdinov, A Maksov, SV Kalinin
npj Computational Materials 3 (1), 1-9, 2017
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
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), 1-8, 2016
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
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 87 (11), 115427, 2013
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
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
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
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
Mapping mesoscopic phase evolution during E-beam induced transformations via deep learning of atomically resolved images
RK Vasudevan, N Laanait, EM Ferragut, K Wang, DB Geohegan, K Xiao, ...
npj Computational Materials 4 (1), 1-9, 2018
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
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), 1-20, 2018
Deep data mining in a real space: separation of intertwined electronic responses in a lightly doped BaFe2As2
M Ziatdinov, A Maksov, L Li, AS Sefat, P Maksymovych, SV Kalinin
Nanotechnology 27 (47), 475706, 2016
167-pflops deep learning for electron microscopy: from learning physics to atomic manipulation
RM Patton, JT Johnston, SR Young, CD Schuman, DD March, TE Potok, ...
SC18: International Conference for High Performance Computing, Networking …, 2018
Data mining for better material synthesis: The case of pulsed laser deposition of complex oxides
SR Young, A Maksov, M Ziatdinov, Y Cao, M Burch, J Balachandran, L Li, ...
Journal of Applied Physics 123 (11), 115303, 2018
Atomic mechanisms for the Si atom dynamics in graphene: chemical transformations at the edge and in the bulk
M Ziatdinov, O Dyck, S Jesse, SV Kalinin
Advanced Functional Materials 29 (52), 1904480, 2019
Learning from imperfections: predicting structure and thermodynamics from atomic imaging of fluctuations
L Vlcek, M Ziatdinov, A Maksov, A Tselev, AP Baddorf, SV Kalinin, ...
ACS nano 13 (1), 718-727, 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
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