Case Study: Lawrence Berkeley National Laboratory accelerates global materials research with Plotly Dash and Python

Berkeley Lab powers materials research for 200,000 users with Plotly Dash

Lawrence Berkeley National Laboratory (Berkeley Lab) faced the challenge of accelerating materials science research, a process that is traditionally time-insensitive and costly, especially for discovering new materials for clean energy and other applications. They needed a way to provide global researchers with access to supercomputing resources and data without requiring a large, dedicated web development team. They turned to Plotly and its Dash framework in Python to build a solution.

Plotly's Dash enabled Berkeley Lab's small core team to build the Materials Project website, a platform featuring over a dozen interactive data exploration apps. This solution eliminated the need for a full-stack development team and allowed materials scientists to contribute directly using Python. The results are significant, with over 200,000 registered users analyzing nearly 150,000 materials. The project runs 100 million CPU hours annually and its research has been cited over 19,000 times, fostering worldwide collaboration on technologies like better batteries and carbon capture.

Lawrence Berkeley National Laboratory (Berkeley Lab)