Hands-on Workshop on FAIR Workflows in Materials Science
Workshops | 15 Oct 2024 | Contributor(s): Arun Kumar Mannodi Kanakkithodi, Alejandro Strachan
Experimental data analysis and simulation workflows and models are at the core of the daily activities of material researchers and engineers worldwide. Making these workflows and the data they generate findable, accessible, interoperable, and reusable (FAIR) is critical to accelerate innovation...
Perovskite VASP-Data Extractor
Tools | 25 Mar 2024 | Contributor(s): Rushik Desai, Alejandro Strachan, Arun Kumar Mannodi Kanakkithodi
This tool would be used to extract important data from a perovskite VASP DFT run and store it on a queryable database.
MRS Computational Materials Science Tutorial
Tools | 04 May 2022 | Contributor(s): Panayotis Thalis Manganaris, Saaketh Desai, Arun Kumar Mannodi Kanakkithodi
Hands-on guide to the development of statistical models useful for materials design using python, sklearn, tensorflow, and intel extensions.
Machine Learning Framework for Impurity Level Prediction in Semiconductors
Online Presentations | 15 Dec 2020 | Contributor(s): Arun Kumar Mannodi Kanakkithodi
In this work, we perform screening of functional atomic impurities in Cd-chalcogenide semiconductors using high-throughput computations and machine learning.
Machine Learning Defect Behavior in Semiconductors
Tools | 10 Nov 2020 | Contributor(s): Arun Kumar Mannodi Kanakkithodi, Rushik Desai (editor)
Develop machine learning models to predict defect formation energies in chalcogenides
Hands-on Data Science and Machine Learning Training Series
Courses | 21 Apr 2020 | Contributor(s): Alejandro Strachan, Saaketh Desai, Arun Kumar Mannodi Kanakkithodi
his series of workshops introduces participants to important concepts and techniques in data science and machine learning in the context engineering and physical sciences applications. All workshops include hands-on activities.