ML-Based Pb-Free Solar Cells

Optimizing Solar Cell Materials with Machine Learning

Developed a web-based tool for material analysis using machine learning to optimize Pb-free perovskite solar cells. This project leverages Python, Flask, MySQL, HTML, and React to provide a powerful and user-friendly platform for material optimization and analysis.

Frameworks & Tools Used

Python

Used for machine learning algorithms and backend logic.

Flask

Used for building the backend API and server.

MySQL

Used for storing and managing material data.

HTML

Used for structuring the web interface.

React

Used for building a dynamic and responsive frontend.

Features

Machine Learning

Uses advanced ML algorithms to optimize solar cell materials.

Data Analysis

Provides detailed analysis and insights into material performance.

User-Friendly Interface

Offers an intuitive and easy-to-use web interface.

About ML-Based Pb-Free Solar Cells

ML-Based Pb-Free Solar Cells is a web-based tool designed to optimize Pb-free perovskite solar cells using machine learning. Built with Python, Flask, MySQL, HTML, and React, it provides a powerful platform for material analysis and optimization.

With features like machine learning-based optimization, detailed data analysis, and a user-friendly interface, this tool ensures efficient and accurate material selection for solar cell development. Future updates will include support for additional materials, enhanced ML models, and advanced visualization tools.