Ghanshyam Pilania

Citirano

	Sve	Od 2020.
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Suautori

Rampi RamprasadGeorgia Institute of TechnologyPotvrđena adresa e-pošte na gatech.edu
Blas Pedro UberuagaLos Alamos National LaboratoryPotvrđena adresa e-pošte na buber.net
Arun Mannodi-KanakkithodiPurdue UniversityPotvrđena adresa e-pošte na purdue.edu
Chiho KimGeorgia Institute of TechnologyPotvrđena adresa e-pošte na gatech.edu
Chenchen WangUniversity of ConnecticutPotvrđena adresa e-pošte na uconn.edu
Vinit SharmaOak Ridge National Laboratory and University of Tennessee, Oak Ridge, TN, USAPotvrđena adresa e-pošte na ornl.gov
Babetta L. MarroneLos Alamos National LaboratoryPotvrđena adresa e-pošte na lanl.gov
Huan TranGeorgia Institute of Technology & Matmerize, Inc.Potvrđena adresa e-pošte na mse.gatech.edu
Rohit BatraAssistant Professor IIT MadrasPotvrđena adresa e-pošte na iitm.ac.in
Prasanna V BalachandranUniversity of VirginiaPotvrđena adresa e-pošte na virginia.edu
C.R. StanekLos Alamos National LaboratoryPotvrđena adresa e-pošte na lanl.gov
Anjana TalapatraLos Alamos National Laboratory, Los Alamos, New MexicoPotvrđena adresa e-pošte na lanl.gov
Xiang-Yang (Ben) LiuLos Alamos National LaboratoryPotvrđena adresa e-pošte na lanl.gov
Karteek BejagamSenior Research ScientistPotvrđena adresa e-pošte na lightwavelogic.com
Steven T. HartmanUnaffiliatedPotvrđena adresa e-pošte na wustl.edu
Vancho KocevskiUniversity of MichiganPotvrđena adresa e-pošte na umich.edu
Qiang ZhuUniversity of North Carolina at CharlottePotvrđena adresa e-pošte na uncc.edu
Artem R. OganovDistinguished Professor, Skolkovo Institute of Science and Technology, Russia; APS Fellow, FRSC, MAEPotvrđena adresa e-pošte na skoltech.ru
Christopher KuennethAssistant Professor, University of BayreuthPotvrđena adresa e-pošte na uni-bayreuth.de
Sanguthevar RajasekaranProfessor of Computer Science and Engineering, University of ConnecticutPotvrđena adresa e-pošte na engr.uconn.edu

Prati

Ghanshyam Pilania

Senior Engineer, GE Aerospace Research

Potvrđena adresa e-pošte na ge.com

Materials informatics Quantum mechanical computations Atomistic simulations Materials by design


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Machine learning in materials informatics: recent applications and prospects R Ramprasad, R Batra, G Pilania, A Mannodi-Kanakkithodi, C Kim npj Computational Materials 3 (1), 54, 2017	1426	2017
Accelerating materials property predictions using machine learning G Pilania, C Wang, X Jiang, S Rajasekaran, R Ramprasad Scientific reports 3 (1), 2810, 2013	858	2013
Machine learning bandgaps of double perovskites G Pilania, A Mannodi-Kanakkithodi, BP Uberuaga, R Ramprasad, ... Scientific reports 6 (1), 19375, 2016	493	2016
Machine Learning Strategy for Accelerated Design of Polymer Dielectrics A Mannodi-Kanakkithodi, G Pilania, TD Huan, T Lookman, R Ramprasad Scientific Reports 6, 20952, 2016	374	2016
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design K Choudhary, KF Garrity, ACE Reid, B DeCost, AJ Biacchi, ... npj computational materials 6 (1), 173, 2020	366	2020
Rational design of all organic polymer dielectrics V Sharma, C Wang, RG Lorenzini, R Ma, Q Zhu, DW Sinkovits, G Pilania, ... Nature communications 5 (1), 4845, 2014	336	2014
Multi-fidelity machine learning models for accurate bandgap predictions of solids G Pilania, JE Gubernatis, T Lookman Computational Materials Science 129, 156-163, 2017	329	2017
From Organized High-Throughput Data to Phenomenological Theory using Machine Learning: The Example of Dielectric Breakdown CK Kim, G Pilania, R Ramprasad Chemistry of Materials, 2016	238	2016
Polymer informatics: Current status and critical next steps L Chen, G Pilania, R Batra, TD Huan, C Kim, C Kuenneth, R Ramprasad Materials Science and Engineering: R: Reports 144, 100595, 2021	217	2021
Machine Learning in Materials Science: From Explainable Predictions to Autonomous Design G Pilania Computational Materials Science 193, 110360, 2021	213	2021
Machine Learning Assisted Predictions of Intrinsic Dielectric Breakdown Strength of ABX₃ Perovskites C Kim, G Pilania, R Ramprasad The Journal of Physical Chemistry C 120 (27), 14575-14580, 2016	205	2016
Scoping the polymer genome: A roadmap for rational polymer dielectrics design and beyond A Mannodi-Kanakkithodi, A Chandrasekaran, C Kim, TD Huan, G Pilania, ... Materials Today, 2018	201	2018
A polymer dataset for accelerated property prediction and design TD Huan, A Mannodi-Kanakkithodi, C Kim, V Sharma, G Pilania, ... Scientific Data 3, 160012, 2016	200	2016
Finding new perovskite halides via machine learning G Pilania, PV Balachandran, C Kim, T Lookman Frontiers in Materials 3, 19, 2016	194	2016
Computational strategies for polymer dielectrics design CC Wang, G Pilania, SA Boggs, S Kumar, C Breneman, R Ramprasad Polymer 55 (4), 979-988, 2014	153	2014
Machine-learning-based predictive modeling of glass transition temperatures: a case of polyhydroxyalkanoate homopolymers and copolymers G Pilania, CN Iverson, T Lookman, BL Marrone Journal of Chemical Information and Modeling 59 (12), 5013-5025, 2019	132	2019
Revisiting the Al/Al₂O₃ Interface: Coherent Interfaces and Misfit Accommodation G Pilania, BJ Thijsse, RG Hoagland, I Lazić, SM Valone, XY Liu Scientific reports 4 (1), 4485, 2014	108	2014
A machine learning approach for the prediction of formability and thermodynamic stability of single and double perovskite oxides A Talapatra, BP Uberuaga, CR Stanek, G Pilania Chemistry of materials 33 (3), 845-858, 2021	100	2021
Structure classification and melting temperature prediction in octet AB solids via machine learning G Pilania, JE Gubernatis, T Lookman Physical Review B 91 (21), 214302, 2015	88	2015
Developing an interatomic potential for martensitic phase transformations in zirconium by machine learning H Zong, G Pilania, X Ding, GJ Ackland, T Lookman npj Computational Materials 4 (1), 48, 2018	86	2018

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