5 papers
Property-Guided Diffusion for Inverse Design of Crystalline Materials
Sourav Mal, Subhankar Mishra, Prasenjit Sen
Diffusion-based generative models with property guidance have emerged as a promising paradigm for inverse materials design by enabling the generation of crystalline materials with…
mCGCNN: A Dual-Stream Crystal Graph Convolutional Neural Network for the Efficient Prediction of Magnetic Properties of Crystalline Materials
Sourav Mal, Satadeep Bhattacharjee
Magnetic order in crystals is governed by moment-carrying sublattices and ligand-mediated exchange pathways, yet standard crystal graph neural networks treat all atoms homogeneousl…
DiffCrysGen: A Generative Diffusion Model for Accelerated Design of Inorganic Crystalline Materials
Sourav Mal, Nehad Ahmed, Junaid Jami +2
Efficient exploration of the vast chemical space is a fundamental challenge in materials design and discovery, particularly for designing functional inorganic crystalline materials…
Interfacial Control of both Magnetism and Polarization in a van der Waals Ferromagnet/Ferroelectric Heterostructure
Priyanshu Raj, Sourav Mal, Rana Saha +1
Two-dimensional multiferroic van der Waals heterostructures provide a promising platform for the simultaneous control of distinct ferroic orders, with potential applications in mag…
DiffCrysGen: A Score-Based Diffusion Model for Design of Diverse Inorganic Crystalline Materials
Sourav Mal, Subhankar Mishra, Prasenjit Sen
Crystal structure generation is a foundational challenge in materials discovery, particularly in designing functional inorganic crystalline materials with desired properties. Most…