2020
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Hung, J -H; Patra, T K; Simmons, D S: Forecasting the experimental glass transition from short time relaxation data. Journal of Non-Crystalline Solids, 544 , 2020, ISSN: 00223093. (Type: Journal Article | Links | BibTeX)@article{Hung2020,
title = {Forecasting the experimental glass transition from short time relaxation data},
author = {J -H Hung and T K Patra and D S Simmons},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086470297&doi=10.1016%2fj.jnoncrysol.2020.120205&partnerID=40&md5=95a4fbe1e5b66f4b391c47c1c4c5dae3},
doi = {10.1016/j.jnoncrysol.2020.120205},
issn = {00223093},
year = {2020},
date = {2020-01-01},
journal = {Journal of Non-Crystalline Solids},
volume = {544},
publisher = {Elsevier B.V.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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Loeffler, T D; Patra, T K; Chan, H; Sankaranarayanan, S K R S: Active learning a coarse-grained neural network model for bulk water from sparse training data. Molecular Systems Design and Engineering, 5 (5), pp. 902-910, 2020, ISSN: 20589689. (Type: Journal Article | Links | BibTeX)@article{Loeffler2020902,
title = {Active learning a coarse-grained neural network model for bulk water from sparse training data},
author = {T D Loeffler and T K Patra and H Chan and S K R S Sankaranarayanan},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092430734&doi=10.1039%2fc9me00184k&partnerID=40&md5=d6a145b49b7d675a9a2c64a1fb5198ae},
doi = {10.1039/c9me00184k},
issn = {20589689},
year = {2020},
date = {2020-01-01},
journal = {Molecular Systems Design and Engineering},
volume = {5},
number = {5},
pages = {902-910},
publisher = {Royal Society of Chemistry},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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Loeffler, T D; Patra, T K; Chan, H; Cherukara, M; Sankaranarayanan, S K R S: Active Learning the Potential Energy Landscape for Water Clusters from Sparse Training Data. Journal of Physical Chemistry C, 124 (8), pp. 4907-4916, 2020, ISSN: 19327447. (Type: Journal Article | Links | BibTeX)@article{Loeffler20204907,
title = {Active Learning the Potential Energy Landscape for Water Clusters from Sparse Training Data},
author = {T D Loeffler and T K Patra and H Chan and M Cherukara and S K R S Sankaranarayanan},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080957117&doi=10.1021%2facs.jpcc.0c00047&partnerID=40&md5=646ddab0a1c466e35625d622a5cebca1},
doi = {10.1021/acs.jpcc.0c00047},
issn = {19327447},
year = {2020},
date = {2020-01-01},
journal = {Journal of Physical Chemistry C},
volume = {124},
number = {8},
pages = {4907-4916},
publisher = {American Chemical Society},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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2019
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Patra, T K; Loeffler, T D; Chan, H; Cherukara, M J; Narayanan, B; Sankaranarayanan, S K R S: A coarse-grained deep neural network model for liquid water. Applied Physics Letters, 115 (19), 2019, ISSN: 00036951. (Type: Journal Article | Links | BibTeX)@article{Patra2019,
title = {A coarse-grained deep neural network model for liquid water},
author = {T K Patra and T D Loeffler and H Chan and M J Cherukara and B Narayanan and S K R S Sankaranarayanan},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074690793&doi=10.1063%2f1.5116591&partnerID=40&md5=b7ad3de05c40b44a7c8863894af6cd52},
doi = {10.1063/1.5116591},
issn = {00036951},
year = {2019},
date = {2019-01-01},
journal = {Applied Physics Letters},
volume = {115},
number = {19},
publisher = {American Institute of Physics Inc.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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Patra, T K; Chan, H; Podsiadlo, P; Shevchenko, E V; Sankaranarayanan, S K R S; Narayanan, B: Ligand dynamics control structure, elasticity, and high-pressure behavior of nanoparticle superlattices. Nanoscale, 11 (22), pp. 10655-10666, 2019, ISSN: 20403364. (Type: Journal Article | Links | BibTeX)@article{Patra201910655,
title = {Ligand dynamics control structure, elasticity, and high-pressure behavior of nanoparticle superlattices},
author = {T K Patra and H Chan and P Podsiadlo and E V Shevchenko and S K R S Sankaranarayanan and B Narayanan},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066989708&doi=10.1039%2fc8nr09699f&partnerID=40&md5=159589be5a97556b97a47123971df9ac},
doi = {10.1039/c8nr09699f},
issn = {20403364},
year = {2019},
date = {2019-01-01},
journal = {Nanoscale},
volume = {11},
number = {22},
pages = {10655-10666},
publisher = {Royal Society of Chemistry},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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Hung, J -H; Patra, T K; Meenakshisundaram, V; Mangalara, J H; Simmons, D S: Universal localization transition accompanying glass formation: Insights from efficient molecular dynamics simulations of diverse supercooled liquids. Soft Matter, 15 (6), pp. 1223-1242, 2019, ISSN: 1744683X. (Type: Journal Article | Links | BibTeX)@article{Hung20191223,
title = {Universal localization transition accompanying glass formation: Insights from efficient molecular dynamics simulations of diverse supercooled liquids},
author = {J -H Hung and T K Patra and V Meenakshisundaram and J H Mangalara and D S Simmons},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061142255&doi=10.1039%2fc8sm02051e&partnerID=40&md5=800b14fb637b3277e7cc2168e64d17da},
doi = {10.1039/c8sm02051e},
issn = {1744683X},
year = {2019},
date = {2019-01-01},
journal = {Soft Matter},
volume = {15},
number = {6},
pages = {1223-1242},
publisher = {Royal Society of Chemistry},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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2018
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Cheng, Y; Yang, J; Hung, J -H; Patra, T K; Simmons, D S: Design Rules for Highly Conductive Polymeric Ionic Liquids from Molecular Dynamics Simulations. Macromolecules, 51 (17), pp. 6630-6644, 2018, ISSN: 00249297. (Type: Journal Article | Links | BibTeX)@article{Cheng20186630,
title = {Design Rules for Highly Conductive Polymeric Ionic Liquids from Molecular Dynamics Simulations},
author = {Y Cheng and J Yang and J -H Hung and T K Patra and D S Simmons},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052876851&doi=10.1021%2facs.macromol.8b00572&partnerID=40&md5=ab74950339eb59dfd4fddd338243b65e},
doi = {10.1021/acs.macromol.8b00572},
issn = {00249297},
year = {2018},
date = {2018-01-01},
journal = {Macromolecules},
volume = {51},
number = {17},
pages = {6630-6644},
publisher = {American Chemical Society},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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