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Anand Chandrasekaran
Anand Chandrasekaran
Schrodinger LLC
Verified email at schrodinger.com
Title
Cited by
Cited by
Year
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
3432018
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
2502019
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
2162017
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
1822018
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
1682019
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
1582020
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
1282013
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
1152019
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
1052019
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
902019
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
702020
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
542020
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
442020
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
442019
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
292018
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
292016
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
242020
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
212019
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
162022
Solving the electronic structure problem with machine learning. npj Computational Materials, 5: 22
A Chandrasekaran, D Kamal, R Batra, C Kim, L Chen, R Ramprasad
Feburary, 2019
122019
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