activity
20102026
most citeddPOLY: Deep Learning of Polymer Phases and Phase Transition

47 citations · 108 across the 28 of their papers we have counts for

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Showing cond-mat.softShow all

13 papers · 1 filter

cond-mat.soft2025

Breaking Ion Clusters: Size Asymmetry for Faster Ion Transport in Polymer Electrolytes

Ganesh K Rajahmundry, Tarak K Patra

Solid polymer electrolytes (SPEs) are ion-containing solid materials composed of a polymer matrix that enables ionic transport while maintaining the mechanical stability. The conve…

cond-mat.soft2025

Packing, Phase Separation and Interface Compatibility in Reversibly Crosslinked Polymers

Abhishek S. Chankapure, Rahul Karmakar, Srikanth Sastry +2

Vitrimers are a class of crosslinked polymer that are capable of undergoing bond exchange reactions, allowing structural reorganization while maintaining overall network integrity.…

cond-mat.soft2025

Sequence-Defined Phase Behavior of Poly(N-Isopropylacrylamide-co-Acrylamide) in Water

Sandeep Parma, R. Nagaranajan, Tarak K Patra

The precise arrangement of different chemical moieties in a polymer determines its thermophysical properties. How the sequence of moieties impacts the properties of a polymer is an…

cond-mat.soft2025

Microphase Separation Controls the Dynamics of Associative Vitrimers

Rahul Karmakar, Abhishek S. Chankapure, Srikanth Sastry +2

Vitrimers are a class of polymers characterized by dynamic covalent networks, where specific monomer units, which are know as stickers, form reversible crosslinks that enable netwo…

cond-mat.soft2025

Rouse Mode Analysis of Chain Relaxation in Reversibly Crosslinked Polymer Melts

Rahul Karmakar, Srikanth Sastry, Sanat K. Kumar +1

Polymer melts with chains undergoing reversible crosslinking have distinctively favorable dynamic properties, e.g., self healing and reprocessability. In these situations there are…

cond-mat.soft2024

Extrapolative ML Models for Copolymers

Israrul H. Hashmi, Himanshu, Rahul Karmakar +1

Machine learning models have been progressively used for predicting materials properties. These models can be built using pre-existing data and are useful for rapidly screening the…

cond-mat.soft2024

Understanding Ion Distribution and Diffusion in Solid Polymer Electrolytes

Ganesh K Rajahmundry, Tarak K Patra

Solid polymer electrolytes exhibit ion conduction and high mechanical properties, thus are promising materials for future energy storage devices. The ion conductivity in an SPE is…

cond-mat.soft2024

Entropic Cohesion in Vitrimers

Rahul Karmakar, Himanshu, Srikanth Sastry +2

Vitrimers are polymer networks that can undergo bond exchange reactions. They dynamically rearrange their structures while maintaining their overall integrity, thus resulting in un…

cond-mat.soft2023★ 1 cited

Predicting Pair Correlation Functions of Glasses using Machine Learning

Kumar Ayush, Pooja Sahu, Sk Musharaf Ali +1

Glasses offer a broad range of tunable thermophysical properties that are linked to their compositions. However, it is challenging to establish a universal composition-property rel…

cond-mat.soft2023★ 2 cited

Explainability and Transferability of Machine Learning Models for Predicting the Glass Transition Temperature of Polymers

Agrim Babbar, Sriram Ragunathan, Debirupa Mitra +2

Machine learning offers promising tools to develop surrogate models for polymer structure-property relations. Surrogate models can be built upon existing polymer data and are usefu…

cond-mat.soft2023★ 1 cited

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

Jan Michael Y. Carrillo, Vijith P, Tarak K. Patra +5

Star block copolymers (s-BCPs) have potential applications as novel surfactants or amphiphiles for emulsification, compatbilization, chemical transformations and separations. s-BCP…

cond-mat.soft2020★ 47 cited

dPOLY: Deep Learning of Polymer Phases and Phase Transition

Debjyoti Bhattacharya, Tarak K Patra

Machine learning (ML) and artificial intelligence (AI) have the remarkable ability to classify, recognize, and characterize complex patterns and trends in large data sets. Here, we…

cond-mat.soft2020★ 1 cited

Accelerating Copolymer Inverse Design using AI Gaming algorithm

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

There exists a broad class of sequencing problems, for example, in proteins and polymers that can be formulated as a heuristic search algorithm that involve decision making akin to…