Sergei Manzhos

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

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Sergei Manzhos

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

Email verificata su m.titech.ac.jp - Home page

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


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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	284	2006
Neural network potential energy surfaces for small molecules and reactions S Manzhos, T Carrington Jr Chemical Reviews 121 (16), 10187-10217, 2020	263	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	230	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	216	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	214	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	202	2019
Using neural networks to represent potential surfaces as sums of products S Manzhos, T Carrington The Journal of chemical physics 125 (19), 2006	201	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	168	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	135	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	131	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	122	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	119	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	111	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	109	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	105	2015
Photofragment image analysis using the Onion-Peeling Algorithm S Manzhos, HP Loock Computer physics communications 154 (1), 76-87, 2003	102	2003
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	98	2013
Machine learning for the solution of the Schrödinger equation S Manzhos Machine Learning: Science and Technology 1 (1), 013002, 2020	97	2020
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	90	2013

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