Book Chapter


1. Patra T K, Khan S, Srivastava R and Singh J K; Understanding wetting transitions using molecular simulations, Nanoscale and Microscale Phenomena, Edited by Joshi Y M and Khandekar S, Springer 2015 (ISBN 978-81-322-2288-0)

Preprints


3. Ramesh P S and Patra T K, Polymer Sequence Design via Active Learning, arXiv:2111.09659 (2021)

2. Bhattacharya D and Patra T K, Deep learning order parameter for polymer phase transition, arXiv:2102.12009 (2021)

1. Bale A A and Patra T K, Sequence engineering of copolymers using evolutionary computing, arXiv:2107.06439 (2021)

Journal Publications


25. Patra T K, Data-Driven Methods for Accelerating Polymer Design, ACS Polymers Au, (2021)

24. Dwivedi N, Neogi A, Patra T K, Dhand C, Dutta T, Yeo R J, Kumar R, Hashmi S A R, Srivastava A K, Tripathy S, Saifullah M S M, Sankaranarayanan S K R S, and Bhatia C. S., Angstrom-Scale Transparent Overcoats: Interfacial Nitrogen-Driven Atomic Intermingling Promotes Lubricity and Surface Protection of Ultrathin Carbon, Nano Letters 21, 8960 (2021)

23. Bhattacharya D and Patra T K, dPOLY: Deep learning of polymer phases and phase transition, Macromolecules 54, 3065 (2021).

22. Loeffler T D, Banik S, Patra T K, Sternberg M, Sankaranarayanan S KRS, Reinforcement learning in discrete action space applied to inverse defect design, Journal of Physics Communications (2021).

21. Patra T K, Loeffler T D, Sankaranarayanan S KRS, Accelerating copolymer inverse design using Monte Carlo Tree Seach, Nanoscale 12, 23563 (2020).

20. Manna S, Loeffler T D, Patra T K, Chan H, Narayanan B, Sankaranarayanan S KRS, Active learning a neural network model for gold clusters and bulk from sparse first principles training data, ChemCatChem (2020).

19. Hung J, Patra T K, and Simmons D S, Forecasting the experimental glass transition temperature from short time relaxation data, Journal of Non-Crystalline Solids 544, 120205 (2020)

18. Loeffler T D, Patra T K, Chan H, Cherukara M J, Sankaranarayanan S KRS, Active learning a coarse-grained neural network model for bulk water from sparse training data, Molecular System Design and Engineering 5, 902 (2020)

17. Loeffler T D, Patra T K, Chan H, Cherukara M J, Sankaranarayanan S KRS, Active learning the potential energy landscape for water clusters from sparse training data, The Journal of Physical Chemistry C 124, 4907 (2020)

16. Dwivedi N, Patra T K, Lee J-B, Yeo J R, Srinivasan S, Dutta T, Sasikumar K, Dhand C, Tripathy S, Saifullah M. S. M, Danner A, Hashmi S. A. R, Srivastava A. K., Ahn J-H, Sankaranarayanan S. K. R. S., Yang H, and Bhatia C. S., Slippery and wear-resistant surfaces enabled by interface engineered graphene, Nano Letters 20, 905 (2020).

15. Patra T K, Loeffler T D, Chan H, Cherukara M J, Narayanan B, Sankaranarayanan S KRS, A coarse-grained deep neural network model for liquid water, Applied Physics Letters 115, 193101 (2019).

14. Patra T K, Chan H, Shevchenko E V, Sankaranarayanan S KRS, Narayanan B, Ligand dynamics control structure, elasticity, and high-pressure behavior of nanoparticles supercrystals, Nanoscale 11, 10655 (2019)

13. Hung J, Patra T K, Meenakshisundaram V, Mangalara J H and Simmons D S, Universal localization transition underlying glass formation: insights from efficient molecular dynamics simulations of diverse supercooled liquids, Soft Matter 15, 1223 (2019)

12. Cheng Y, Yang J, Hung H, Patra T K, and Simmons D S, Design rules for highly conductive polymeric ionic liquids from molecular dynamics simulations, Macromolecules 51, 6630 (2018)

11. Patra T K, Zhang F, Schulman D; Chan H, Cherukara M, Terrones M; Das S, Narayanan B, Sankaranarayanan S KRS, Defect dynamics in 2D materials probed by combining machine learning, molecular simulation and high-resolution microscopy, ACS Nano 12, 8006 (2018)

10. Patra T K, Meenakshisundaram V, Hung J, and Simmons D S, Neural network biased genetic algorithm for materials design: Evolutionary algorithms that learn, ACS Combinatorial Science 19, 96 (2017)

9. Meenakshisundaram V, Hung J, Patra T K Simmons D S, Designing sequence specific copolymer compatibilizers using a molecular-dynamics-simulation-based genetic algorithm, Macromolecules 50, 1155 (2017)

8. Katiyar P, Patra T K, Singh J K, Sarkar D and Pramanik A, Understanding adsorption behavior of silica nanoparticles over a cellulose surface in an aqueous medium, Chemical Engineering Science 141, 293 (2016)

7. Patra T K, Katiyar P and Singh J K, Substrate directed self-assembly of anisotropic nanoparticles, Chemical Engineering Science 121, 16 (2015)

6. Patra T K and Singh J K, Localization and stretching of polymers at the junction of two surfaces, Journal of Chemical Physics 140, 204909 (2014)

5. Patra T K and Singh J K, Polymer directed aggregation and dispersion of anisotropic nanoparticles, Soft Matter 10, 1823 (2014)

4. Patra T K and Singh J K, Coarse-grain molecular dynamics simulations of nanoparticle-polymer melts: Dispersion vs. Agglomeration, Journal of Chemical Physics 138, 144901 (2013)

3. Patra T K, Hens A, Singh JK, Vapor-liquid phase coexistence and transport properties of two-dimensional oligomers, Journal of Chemical Physics 137, 084701 (2012)

2. Ghosh A, Patra T K, Rishikant, Singh R K, Singh J K and Bhattacharya S, Surface electrophoresis of ds-DNA across orthogonal pair of surfaces, Applied Physics Letters 98, 164102 (2011)

1. B Ashok and Patra T K, Locating phase transitions in computationally hard problems, Pramana-Journal of Physics 75, 549 (2010)