activity
20232025
most citedAccelerating Defect Predictions in Semiconductors Using Graph Neural Networks

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2025

Let Cyclic Electrochemical Data Speak for Your Energy Storage Material and Processing

Vinod Sarky, P. Laxman Mani Kanta, Shivangi Keshri +3

Efforts to improve performance, like energy and power density of electrochemical energy storage devices (batteries, capacitors, and super-capacitors), are being made using a range…

cond-mat.mtrl-sci2025

Prediction of Mechanical Properties and Thermodynamic Stability of Ti-N system using MTP Interatomic Potential

Pradeep Kumar Rana, Atharva Vyawahare, Rohit Batra +1

Ti-N material system have range of compounds with different stoichiometry like Ti2N, Ti3N2, Ti6N5, Ti4N3 alongwith Ti , TiN and solid solutions of N in Ti with a maximum of 23% sol…

physics.chem-ph2025

Molecular Mechanisms of Polymer Crosslinking via Thermal Activation

Javed Akhtar, Jogeswar Chhatria, Sooraj Kunnikuruvan +2

Developing efficient and universal polymer crosslinking strategies is pivotal for advanced material design, especially for challenging matrixes like polyethylene, polypropylene, an…

cond-mat.mtrl-sci2024

Thermodynamics and Kinetics of Ti2N Formation by N Atom Intercalation in Ti

J. Varalakshmi, Satyesh Kumar Yadav

Although Ti2N and Ti belong to different crystal systems and Bravais lattices, we show that N intercalation in Hexagonal Close-Packed (HCP) Ti can lead to the formation of Ti2N by…

cond-mat.mtrl-sci2023★ 2 cited

Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks

Md Habibur Rahman, Prince Gollapalli, Panayotis Manganaris +5

Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of Group IV, III-V, and II-VI zinc blende (ZB) semicon…