T. Patra

发表

Coarse-grain molecular dynamics simulations of nanoparticle-polymer melt: dispersion vs. agglomeration.

J. Singh, T. Patra, 2013, The Journal of chemical physics.

Localization and stretching of polymer chains at the junction of two surfaces.

J. Singh, T. Patra, 2014, The Journal of chemical physics.

Design Rules for Highly Conductive Polymeric Ionic Liquids from Molecular Dynamics Simulations

T. Patra, Jui-Hsiang Hung, D. Simmons, 2018, Macromolecules.

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Badri Narayanan, Subramanian Sankaranarayanan, Tarak K Patra, 2020 .

Polymer directed aggregation and dispersion of anisotropic nanoparticles.

J. Singh, T. Patra, J. Singh, 2014, Soft matter.

Understanding Wetting Transitions Using Molecular Simulation

J. Singh, T. Patra, Sandip Khan, 2015 .

Angstrom-Scale Transparent Overcoats: Interfacial Nitrogen-Driven Atomic Intermingling Promotes Lubricity and Surface Protection of Ultrathin Carbon.

C. S. Bhatia, S. Sankaranarayanan, A. Srivastava, 2021, Nano letters.

Slippery and Wear Resistant Surfaces Enabled by Interface Engineered Graphene.

C. S. Bhatia, A. Srivastava, A. Danner, 2019, Nano letters.

Deep learning potential of mean force between polymer grafted nanoparticles.

T. Patra, S. Gautham, 2022, Soft matter.

When does deep learning fail and how to tackle it? A critical analysis on polymer sequence-property surrogate models

T. Patra, Himanshu, 2022, ArXiv.

nanoNET: machine learning platform for predicting nanoparticles distribution in a polymer matrix.

T. Patra, K. Ayush, A. Seth, 2022, Soft matter.

Active Learning the Coarse-Grained Energy Landscape For Water Clusters From Sparse Training Data

M. Cherukara, S. Sankaranarayanan, T. Patra, 2019, 1909.11654.

Realization of fluoride sensor using two dimensional photonic structures and machine learning model

G. Palai, S. Behera, T. Patra, 2020, Microsystem Technologies.

Data-Driven Methods for Accelerating Polymer Design

T. Patra, 2021, ACS polymers Au.

Universal localization transition accompanying glass formation: insights from efficient molecular dynamics simulations of diverse supercooled liquids.

T. Patra, Venkatesh Meenakshisundaram, Jui-Hsiang Hung, 2019, Soft matter.

Designing Sequence-Specific Copolymer Compatibilizers Using a Molecular-Dynamics-Simulation-Based Genetic Algorithm

Tarak K. Patra, Jui-Hsiang Hung, T. Patra, 2017 .

Defect Dynamics in 2-D MoS2 Probed by Using Machine Learning, Atomistic Simulations, and High-Resolution Microscopy.

Daniel S Schulman, Badri Narayanan, Mauricio Terrones, 2018, ACS nano.

Neural-Network-Biased Genetic Algorithms for Materials Design: Evolutionary Algorithms That Learn.

Tarak K Patra, Venkatesh Meenakshisundaram, Jui-Hsiang Hung, 2017, ACS combinatorial science.

Forecasting the experimental glass transition from short time relaxation data

T. Patra, Jui-Hsiang Hung, D. Simmons, 2020 .

Understanding adsorption behavior of silica nanoparticles over a cellulose surface in an aqueous medium

J. Singh, A. Pramanik, T. Patra, 2016 .

A simple calculation of the heavy-ion optical potential using a finite-range density-dependent Brink-Boeker effective interaction

T. Patra, K. C. Panda, 1991 .

Comparison of folding model and energy density model for the heavy-ion optical potential

T. Patra, K. C. Panda, 1988 .

Spin-density terms and heavy-ion optical potential

T. Patra, K. C. Panda, 1990 .

Active Learning the Potential Energy Landscape for Water Clusters from Sparse Training Data

Subramanian K. R. S. Sankaranarayanan, Tarak K. Patra, Henry Chan, 2020 .

Active Learning the Coarse-Grained Energy Landscape For Water Clusters From Sparse Data

M. Cherukara, S. Sankaranarayanan, T. Patra, 2019 .

Locating phase transitions in computationally hard problems

B. Ashok, T. K. Patra, T. Patra, 2010, ArXiv.

Substrate directed self-assembly of anisotropic nanoparticles

J. Singh, T. Patra, P. Katiyar, 2015 .

Reinforcement learning in discrete action space applied to inverse defect design

S. Sankaranarayanan, T. Patra, T. Loeffler, 2021, Journal of Physics Communications.

Accelerating copolymer inverse design using monte carlo tree search.

Tarak K Patra, Subramanian K R S Sankaranarayanan, Troy D Loeffler, 2020, Nanoscale.

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

B. Narayanan, S. Sankaranarayanan, Sukriti Manna, 2020, ChemCatChem.

Accelerating Copolymer Inverse Design using AI Gaming algorithm

Troy D. Loeffler, Tarak K Patra, Subramanian K R S Sankaranarayanan, 2020, 2006.03413.

Sequence Engineering of Copolymers using Evolutionary Computing

T. Patra, Ashwin A. Bale, Ashwin Bale, 2021, 2107.06439.

Experimental Study on The Adsorption of Malachite Green in Simulated and Real Effluent by Bio-Based Adsorbents

K. Sheeba, S. Jaisankar, T. Patra, 2015 .

Ligand dynamics control structure, elasticity, and high-pressure behavior of nanoparticle superlattices.

Elena V. Shevchenko, Badri Narayanan, Subramanian K. R. S. Sankaranarayanan, 2019, Nanoscale.

Active learning a coarse-grained neural network model for bulk water from sparse training data

Subramanian K. R. S. Sankaranarayanan, Troy D. Loeffler, Tarak K. Patra, 2020 .

A coarse-grained deep neural network model for liquid water

B. Narayanan, M. Cherukara, S. Sankaranarayanan, 2019, Applied Physics Letters.

Predicting Pair Correlation Functions of Glasses using Machine Learning

T. Patra, P. Sahu, S. Ali, 2023, 2308.11151.

Vapor-liquid phase coexistence and transport properties of two-dimensional oligomers.

J. Singh, T. Patra, Abhiram Hens, 2012, The Journal of chemical physics.

Accelerated Design of Block Copolymers: An Unbiased Exploration Strategy via Fusion of Molecular Dynamics Simulations and Machine Learning

B. Sumpter, S. Sankaranarayanan, T. Russell, 2023, 2308.08226.

Polymer Sequence Design via Active Learning

T. Patra, P. Ramesh, 2021, 2111.09659.

Dynamic crosslinking compatibilizes immiscible mixed plastics

Sanat K. Kumar, T. Patra, T. Rovis, 2023, Nature.

Extrapolative ML Models for Copolymers

T. Patra, Himanshu, Israrul H. Hashmi, 2024, 2409.09691.

Understanding Ion Distribution and Diffusion in Solid Polymer Electrolytes.

T. Patra, G. K. Rajahmundry, 2024, Langmuir : the ACS journal of surfaces and colloids.