Master's Project
Master's Project
Embedded Files
Accelerating Search for Superconductors using Machine Learning
Adiga, S., & Waghmare, U. V. , Accelerating the Search for Superconductors Using Machine Learning, Comput. Mater. Sci., 263, 114453 (2026) [Link]
Search for new superconductors has traditionally relied on trial and error methods.
Theoretical approaches like DFT are effective in prediction of critical temperature only for conventional superconductors.
To address these limitations, we used machine learning models to predict the critical temperature.
Quantum Structure Diagram based descriptors have been used to train the model
Database and codes are made open source on GitHub.
Bachelor's Project
Bachelor's Project
Toy Model to Explain Superconductivity
Toy Model to Explain Superconductivity
S. Adiga, M. Dahiya, and A. Palakkandy, “Toy model to explain superconductivity” (2025) [Accepted in The Physics Teacher]
(Movie: Attraction between electrons due to lattice vibration)
Charges with the same polarity typically repel each other.
Superconductivity is a phenomenon where like-charged particles (electrons) form bound pairs called Cooper pairs.
The BCS theory explains Cooper pair formation in conventional superconductors using a quantum mechanical approach.
In this work, we present a toy model that shows how two repelling electrons can experience an effective attraction.
This attraction arises due to lattice vibrations and is demonstrated using a classical mechanics approach.
Page updated
Google Sites
Report abuse