no code implementations • LREC 2022 • Ankan Mullick, Shubhraneel Pal, Tapas Nayak, Seung-Cheol Lee, Satadeep Bhattacharjee, Pawan Goyal
In the last few years, several attempts have been made on extracting information from material science research domain.
no code implementations • 18 Jan 2024 • Ankan Mullick, Akash Ghosh, G Sai Chaitanya, Samir Ghui, Tapas Nayak, Seung-Cheol Lee, Satadeep Bhattacharjee, Pawan Goyal
Material science literature is a rich source of factual information about various categories of entities (like materials and compositions) and various relations between these entities, such as conductivity, voltage, etc.
1 code implementation • 9 Jun 2023 • Kishalay Das, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly
In this work, we leverage textual descriptions of materials to model global structural information into graph structure and learn a more robust and enriched representation of crystalline materials.
1 code implementation • 14 Jan 2023 • Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly
To leverage these untapped data, this paper presents CrysGNN, a new pre-trained GNN framework for crystalline materials, which captures both node and graph level structural information of crystal graphs using a huge amount of unlabelled material data.
no code implementations • 15 Sep 2020 • Souradip Guha, Ankan Mullick, Jatin Agrawal, Swetarekha Ram, Samir Ghui, Seung-Cheol Lee, Satadeep Bhattacharjee, Pawan Goyal
The number of published articles in the field of materials science is growing rapidly every year.
1 code implementation • 2 Sep 2020 • Sudipta Kundu, Satadeep Bhattacharjee, Seung-Cheol Lee, Manish Jain
We formulate Wannier orbital overlap population and Wannier orbital Hamilton population to describe the contribution of different orbitals to electron distribution and their interactions.
Computational Physics Materials Science