47 citations · 108 across the 28 of their papers we have counts for
10 papers · 1 filter
Polar-Domain Volume as a Unified Descriptor of Transport in Ionic Liquids
Ganesh K. Rajahmundry, Tarak K. Patra
Developing molecular scale structural descriptors that can quantitatively predict the macroscopic transport properties of ionic liquids remains a longstanding question, owing to th…
Stability by Design: Atomistic Insights into Hydrolysis-Driven MOF Degradation
Ashok Yacham, Tarak K. Patra, Jithin John Varghese +1
Metal-organic frameworks (MOFs) are porous materials formed by interconnected metal atoms via organic linkers, resulting in high surface area and tuneable porosity, making them exc…
Thickening of liquids using copolymer grafted nanoparticles
Prama Adhya, Sachin M. B. Gautham, Tarak K Patra +2
Precise control over the flow behavior of liquids is a critical problem and is demanding for multifaceted applications. Introducing surface-engineered nanoparticles into the liquid…
An Explainable AI Model for Binary LJ Fluids
Israrul H Hashmi, Rahul Karmakar, Marripelli Maniteja +2
Lennard-Jones (LJ) fluids serve as an important theoretical framework for understanding molecular interactions. Binary LJ fluids, where two distinct species of particles interact b…
When does deep learning fail and how to tackle it? A critical analysis on polymer sequence-property surrogate models
Himanshu, Tarak K Patra
Deep learning models are gaining popularity and potency in predicting polymer properties. These models can be built using pre-existing data and are useful for the rapid prediction…
nanoNET: Machine Learning Platform for Predicting Nanoparticles Distribution in a Polymer Matrix
Kumar Ayush, Abhishek Seth, Tarak K Patra
Polymer nanocomposites (PNCs) offer a broad range of thermophysical properties that are linked to their compositions. However, it is challenging to establish a universal compositio…
Deep Learning Potential of Mean Force between Polymer Grafted Nanoparticles
Sachin Gautham, Tarak Patra
Grafting polymer chains on nanoparticles surfaces is a well-known route to control their self assembly and distribution in a polymer matrix. A wide variety of self assembled struct…
Polymer Sequence Design via Active Learning
Praneeth S Ramesh, Tarak K Patra
Analysis of molecular scale interactions and chemical structure offers an enormous opportunity to tune material properties for targeted applications. However, designing materials f…
Sequence Engineering of Copolymers using Evolutionary Computing
Ashwin A Bale, Tarak K Patra
The correlations between the sequence of monomers in a polymer and its three-dimensional structure is a grand challenge in polymer science and biology. The properties and functions…
Deep Learning Order Parameter for Polymer Phase Transition
Debjyoti Bhattacharya, Tarak K Patra
We report a deep learning (DL) framework viz. deep autoencoder that autonomously discovers an appropriate order parameter from molecular dynamics (MD) simulation data to characteri…