| Polymer genome: a data-powered polymer informatics platform for property predictions C Kim, A Chandrasekaran, TD Huan, D Das, R Ramprasad The Journal of Physical Chemistry C 122 (31), 17575-17585, 2018 | 380 | 2018 |
| Solving the electronic structure problem with machine learning A Chandrasekaran, D Kamal, R Batra, C Kim, L Chen, R Ramprasad npj Computational Materials 5 (1), 22, 2019 | 275 | 2019 |
| Ferroelectricity, antiferroelectricity, and ultrathin 2D electron/hole gas in multifunctional monolayer MXene A Chandrasekaran, A Mishra, AK Singh Nano letters 17 (5), 3290-3296, 2017 | 231 | 2017 |
| 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 21 (7), 785-796, 2018 | 196 | 2018 |
| Critical assessment of the Hildebrand and Hansen solubility parameters for polymers S Venkatram, C Kim, A Chandrasekaran, R Ramprasad Journal of chemical information and modeling 59 (10), 4188-4194, 2019 | 189 | 2019 |
| Machine-learning predictions of polymer properties with Polymer Genome H Doan Tran, C Kim, L Chen, A Chandrasekaran, R Batra, S Venkatram, ... Journal of Applied Physics 128 (17), 2020 | 180 | 2020 |
| Defect ordering and defect–domain-wall interactions in PbTiO: A first-principles study A Chandrasekaran, D Damjanovic, N Setter, N Marzari Physical Review B 88 (21), 214116, 2013 | 138 | 2013 |
| Electrochemical stability window of polymeric electrolytes L Chen, S Venkatram, C Kim, R Batra, A Chandrasekaran, R Ramprasad Chemistry of Materials 31 (12), 4598-4604, 2019 | 124 | 2019 |
| Active-learning and materials design: the example of high glass transition temperature polymers C Kim, A Chandrasekaran, A Jha, R Ramprasad Mrs Communications 9 (3), 860-866, 2019 | 111 | 2019 |
| Impact of dataset uncertainties on machine learning model predictions: the example of polymer glass transition temperatures A Jha, A Chandrasekaran, C Kim, R Ramprasad Modelling and Simulation in Materials Science and Engineering 27 (2), 024002, 2019 | 97 | 2019 |
| A multi-fidelity information-fusion approach to machine learn and predict polymer bandgap A Patra, R Batra, A Chandrasekaran, C Kim, TD Huan, R Ramprasad Computational Materials Science 172, 109286, 2020 | 78 | 2020 |
| A deep learning solvent-selection paradigm powered by a massive solvent/nonsolvent database for polymers A Chandrasekaran, C Kim, S Venkatram, R Ramprasad Macromolecules 53 (12), 4764-4769, 2020 | 60 | 2020 |
| General atomic neighborhood fingerprint for machine learning-based methods R Batra, HD Tran, C Kim, J Chapman, L Chen, A Chandrasekaran, ... The Journal of Physical Chemistry C 123 (25), 15859-15866, 2019 | 51 | 2019 |
| Polymer genome–based prediction of gas permeabilities in polymers G Zhu, C Kim, A Chandrasekarn, JD Everett, R Ramprasad, RP Lively Journal of Polymer Engineering 40 (6), 451-457, 2020 | 50 | 2020 |
| Effect of crystallinity on Li adsorption in polyethylene oxide D Das, A Chandrasekaran, S Venkatram, R Ramprasad Chemistry of Materials 30 (24), 8804-8810, 2018 | 31 | 2018 |
| Asymmetric structure of domain walls and interactions with defects in A Chandrasekaran, XK Wei, L Feigl, D Damjanovic, N Setter, N Marzari Physical Review B 93 (14), 144102, 2016 | 31 | 2016 |
| A charge density prediction model for hydrocarbons using deep neural networks D Kamal, A Chandrasekaran, R Batra, R Ramprasad Machine Learning: Science and Technology 1 (2), 025003, 2020 | 27 | 2020 |
| Iterative-learning strategy for the development of application-specific atomistic force fields TD Huan, R Batra, J Chapman, C Kim, A Chandrasekaran, R Ramprasad The Journal of Physical Chemistry C 123 (34), 20715-20722, 2019 | 21 | 2019 |
| Active learning accelerates design and optimization of hole-transporting materials for organic electronics H Abroshan, HS Kwak, Y An, C Brown, A Chandrasekaran, P Winget, ... Frontiers in Chemistry 9, 800371, 2022 | 19 | 2022 |
| 66‐3: Active Learning for the Design of Novel OLED Materials H Abroshan, A Chandrasekaran, P Winget, Y An, S Kwak, CT Brown, ... SID Symposium Digest of Technical Papers 53 (1), 885-888, 2022 | 15 | 2022 |
Huan TranGeorgia Institute of Technology & Matmerize, Inc.Verified email at mse.gatech.edu
