Mordechai Kornbluth

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Jonathan Pradana MailoaTencent Quantum Lab; Past Work @ Bosch & MITVerified email at alum.mit.edu
Boris KozinskyHarvard University, Bosch ResearchVerified email at seas.harvard.edu
Georgy SamsonidzeLead Engineer, Bosch Research and Technology Center North AmericaVerified email at civet.berkeley.edu
Soo KimSr. Manager, Battery Advanced Materials - Rivian AutomotiveVerified email at rivian.com
Simon BatznerGoogle DeepMindVerified email at google.com
Lixin Sun 孙励新Microsoft Research, Cambridge, UKVerified email at microsoft.com
Nicola MolinariRobert Bosch. Formerly @ Harvard, Imperial College LondonVerified email at us.bosch.com
Andrew S WestoverOak Ridge National LaboratoryVerified email at ornl.gov
Fredy ZypmanYeshiva UniversityVerified email at case.edu
Saravanan KuppanLead Engineer, Robert Bosch LLC, Lawrence Berkeley National LabVerified email at us.bosch.com
Sergiy KalnausORNLVerified email at asme.org
Jake ChristensenRobert Bosch LLCVerified email at us.bosch.com
K.R.GadelrabLab for Theoretical Soft Materials, MIT - Robert Bosch LLCVerified email at mit.edu
Chris WolvertonProfessor of Materials Science and Eng., Northwestern UniversityVerified email at northwestern.edu
Erik G. HerbertGroup Leader, Mechanical Properties & Mechanics, Oak Ridge National LaboratoryVerified email at mtu.edu
Chris AblittDepartment of Chemistry, University of WarwickVerified email at warwick.ac.uk
Michael MetzgerDalhousie UniversityVerified email at dal.ca
Lyuwen FuZhejiang Lab, Columbia UniversityVerified email at zhejianglab.edu.cn
Zhengqian ChengPostdoc researcher, Columbia UniversityVerified email at columbia.edu
David HumphreysPrincipal Scientist, General AtomicsVerified email at gat.com

Mordechai Kornbluth

Robert Bosch LLC

Verified email at us.bosch.com

Computational materials science atomistic simulations quantum chemistry molecular dynamics density functional theory


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E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials S Batzner, A Musaelian, L Sun, M Geiger, JP Mailoa, M Kornbluth, ... Nature Communications 13, 2453, 2022	1164	2022
Learning local equivariant representations for large-scale atomistic dynamics A Musaelian, S Batzner, A Johansson, L Sun, CJ Owen, M Kornbluth, ... Nature Communications 14 (1), 579, 2023	387	2023
Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture CW Park, M Kornbluth, J Vandermause, C Wolverton, B Kozinsky, ... npj Computational Materials 7 (1), 73, 2021	119*	2021
A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems JP Mailoa, M Kornbluth, S Batzner, G Samsonidze, ST Lam, ... Nature machine intelligence 1 (10), 471-479, 2019	56	2019
Light-induced electronic non-equilibrium in plasmonic particles M Kornbluth, A Nitzan, T Seideman The Journal of chemical physics 138 (17), 2013	56	2013
Resistance to fracture in the glassy solid electrolyte Lipon S Kalnaus, AS Westover, M Kornbluth, E Herbert, NJ Dudney Journal of Materials Research 36, 787-796, 2021	34	2021
Analysis of shot-to-shot variability in post-disruption runaway electron currents for diverted DIII-D discharges VA Izzo, DA Humphreys, M Kornbluth Plasma Physics and Controlled Fusion 54, 095002, 2012	34	2012
Negentropy generation and fractality in the dry friction of polished surfaces P Fleurquin, H Fort, M Kornbluth, R Sandler, M Segall, F Zypman Entropy 12 (3), 480-489, 2010	24	2010
Uncertainties of coherent states for a generalized supersymmetric annihilation operator M Kornbluth, F Zypman Journal of Mathematical Physics 54 (1), 2013	21	2013
Group theoretical approach to computing phonons and their interactions L Fu, M Kornbluth, Z Cheng, CA Marianetti Physical Review B 100 (1), 014303, 2019	20	2019
Plasma synthesis of spherical crystalline and amorphous electrolyte nanopowders for solid-state batteries AS Westover, AK Kercher, M Kornbluth, M Naguib, MJ Palmer, DA Cullen, ... ACS applied materials & interfaces 12 (10), 11570-11578, 2020	19	2020
A community-powered search of machine learning strategy space to find NMR property prediction models LA Bratholm, W Gerrard, B Anderson, S Bai, S Choi, L Dang, P Hanchar, ... Plos one 16 (7), e0253612, 2021	15	2021
Desalination electrode KIM Soo, J Mailoa, M Kornbluth, G Samsonidze, M Metzger, S Kuppan, ... US Patent 10,988,391, 2021	9	2021
Spectral Denoising for Accelerated Analysis of Correlated Ionic Transport N Molinari, Y Xie, I Leifer, M Kornbluth, B Kozinsky Physical Review Letters 127, 025901, 2021	8	2021
Medium-Range Ordering in the Ionic Glass Electrolytes LiPON and LiSiPON AS Westover, M Kornbluth, T Egami, J Liu, S Kalnaus, D Ma, AK Kercher, ... Chemistry of Materials 35 (7), 2730-2739, 2023	5	2023
Origin of Spinel Nanocheckerboards via First Principles M Kornbluth, CA Marianetti Physical Review Letters 114 (22), 226102, 2015	4	2015
Fuel cell electrode catalyst layer coating KIM Soo, J Mailoa, M Kornbluth, Y Gorlin, G Samsonidze, B Kozinsky, ... US Patent 11,145,875, 2021	3	2021
Desalination device KIM Soo, M Metzger, J Mailoa, M Kornbluth, G Samsonidze, S Kuppan, ... US Patent App. 16/448,440, 2020	3	2020
Amorphous LiF as an Artificial SEI Layer for Lithium Batteries M Kornbluth, J Mailoa, B Kozinsky, G Samsonidze, JF Christensen US Patent App. 16/046,867, 2019	3	2019
E (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials, Nat. Commun. 13 (2022) 2453 S Batzner, A Musaelian, L Sun, M Geiger, JP Mailoa, M Kornbluth, ...	3

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