Sergei Manzhos

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Prashant SonarProfessor & ARC Future Fellow, Organic and Printed Electronic Research Group @QUTDirección de correo verificada de qut.edu.au
T CarringtonQueen's UniversityDirección de correo verificada de queensu.ca
Krishna Feron[email protected]Dirección de correo verificada de newcastle.edu.au
Daniel KochResearch Associate, German Aerospace Center (DLR)Dirección de correo verificada de dlr.de
Yingqian ChenResearch Fellow, National University of SingaporeDirección de correo verificada de u.nus.edu
Hong Duc PhamPhD, Postdoctoral Research Fellow (Novel Energy Technologies), Centre for Future Materials @UniSQDirección de correo verificada de unisq.edu.au
Oleksandr I. MalyiInverse Materials Design groupDirección de correo verificada de e.ntu.edu.sg
John BellUniversity of Southern QueenslandDirección de correo verificada de unisq.edu.au
Qian LIU (刘谦)ARC DECRA Fellow at Queensland University of Technology (QUT)Dirección de correo verificada de qut.edu.au
Il JeonVice Provost & Centre Director & Professor & CEO, Sungkyunkwan University (SKKU)Dirección de correo verificada de spc.oxon.org
Johann LüderNational Sun Yat-sen UniversityDirección de correo verificada de mail.nsysu.edu.tw
Steven BottleChemistry QUT Queensland University of TechnologyDirección de correo verificada de qut.edu.au
Hiroshi SegawaDirección de correo verificada de mail.ecc.u-tokyo.ac.jp
Teck Leong TanInstitute of High Performance Computing SingaporeDirección de correo verificada de ihpc.a-star.edu.sg
Vadym KulishNational University of SingaporeDirección de correo verificada de nus.edu.sg
Hans-Peter LoockUniversity of Victoria (Queen's University 1999-2019)Dirección de correo verificada de uvic.ca
Yutaka MatsuoNagoya UniversityDirección de correo verificada de chem.material.nagoya-u.ac.jp
Shigeo MaruyamaProfessor of Mechanical Engineering, The University of TokyoDirección de correo verificada de photon.t.u-tokyo.ac.jp
Hao-Sheng LinAssistant Professor, Nagoya UniversityDirección de correo verificada de material.nagoya-u.ac.jp
Amrita PalNUS - National University of SingaporeDirección de correo verificada de nus.edu.sg

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Sergei Manzhos

Associate Professor, Ihara-Manzhos laboratory, Tokyo Institute of Technology

Dirección de correo verificada de m.titech.ac.jp - Página principal

machine learning solar cells fuel cells computational spectroscopy large-scale ab initio


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
A random-sampling high dimensional model representation neural network for building potential energy surfaces S Manzhos, T Carrington The Journal of chemical physics 125 (8), 2006	288	2006
Neural network potential energy surfaces for small molecules and reactions S Manzhos, T Carrington Jr Chemical Reviews 121 (16), 10187-10217, 2020	276	2020
Neural networks vs Gaussian process regression for representing potential energy surfaces: A comparative study of fit quality and vibrational spectrum accuracy A Kamath, RA Vargas-Hernández, RV Krems, T Carrington, S Manzhos The Journal of chemical physics 148 (24), 2018	239	2018
Neural network‐based approaches for building high dimensional and quantum dynamics‐friendly potential energy surfaces S Manzhos, R Dawes, T Carrington International Journal of Quantum Chemistry 115 (16), 1012-1020, 2015	221	2015
A nested molecule-independent neural network approach for high-quality potential fits S Manzhos, X Wang, R Dawes, T Carrington The Journal of Physical Chemistry A 110 (16), 5295-5304, 2006	216	2006
Organic interfacial materials for perovskite-based optoelectronic devices HD Pham, L Xianqiang, W Li, S Manzhos, AKK Kyaw, P Sonar Energy & Environmental Science 12 (4), 1177-1209, 2019	206	2019
Using neural networks to represent potential surfaces as sums of products S Manzhos, T Carrington The Journal of chemical physics 125 (19), 2006	203	2006
Molecular engineering using an anthanthrone dye for low‐cost hole transport materials: a strategy for dopant‐free, high‐efficiency, and stable perovskite solar cells HD Pham, TT Do, J Kim, C Charbonneau, S Manzhos, K Feron, WC Tsoi, ... Advanced Energy Materials 8 (16), 1703007, 2018	172	2018
Roadmap on machine learning in electronic structure HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ... Electronic Structure 4 (2), 023004, 2022	150	2022
Phenothiazine and carbazole substituted pyrene based electroluminescent organic semiconductors for OLED devices JK Salunke, FL Wong, K Feron, S Manzhos, MF Lo, D Shinde, A Patil, ... Journal of Materials Chemistry C 4 (5), 1009-1018, 2016	137	2016
In search of high performance anode materials for Mg batteries: Computational studies of Mg in Ge, Si, and Sn OI Malyi, TL Tan, S Manzhos Journal of Power Sources 233, 341-345, 2013	124	2013
Using neural networks, optimized coordinates, and high-dimensional model representations to obtain a vinyl bromide potential surface S Manzhos, T Carrington The Journal of chemical physics 129 (22), 2008	123	2008
Using redundant coordinates to represent potential energy surfaces with lower-dimensional functions S Manzhos, T Carrington The Journal of chemical physics 127 (1), 2007	120	2007
On the charge state of titanium in titanium dioxide D Koch, S Manzhos The journal of physical chemistry letters 8 (7), 1593-1598, 2017	115	2017
A computational study of Na behavior on graphene OI Malyi, K Sopiha, VV Kulish, TL Tan, S Manzhos, C Persson Applied Surface Science 333, 235-243, 2015	113	2015
Insertion energetics of lithium, sodium, and magnesium in crystalline and amorphous titanium dioxide: A comparative first-principles study F Legrain, O Malyi, S Manzhos Journal of Power Sources 278, 197-202, 2015	106	2015
Photofragment image analysis using the Onion-Peeling Algorithm S Manzhos, HP Loock Computer physics communications 154 (1), 76-87, 2003	102	2003
Machine learning for the solution of the Schrödinger equation S Manzhos Machine Learning: Science and Technology 1 (1), 013002, 2020	100	2020
A comparative computational study of structures, diffusion, and dopant interactions between Li and Na insertion into Si OI Malyi, TL Tan, S Manzhos Applied Physics Express 6 (2), 027301, 2013	99	2013
A computational study of the insertion of Li, Na, and Mg atoms into Si (111) nanosheets O Malyi, VV Kulish, TL Tan, S Manzhos Nano Energy 2 (6), 1149-1157, 2013	92	2013

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