Design and Implementation of Enablers in Materials Acceleration Platforms for Battery Research
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Beschreibung
This research introduces tools for Materials Acceleration Platforms to enhance autonomous experimentation and predictive analysis tailored for battery technology. It integrates laboratory devices, multiple software, data analysis, and management systems and leverages machine learning and deep learning algorithms for AI-accelerated experimental optimization. The goal is to expedite knowledge extraction and increase the reliability and reproducibility of high-throughput experimental frameworks.
Autor*in
Fuzhan Rahmanian
Themen in »Design and Implementation of Enablers in Materials Acceleration Platforms for Battery Research«
Technical University of Munich Artificial Intelligence Data Management TU Munich Research International Cooperation TUM School of Natural Sciences Programming European Project BIG-MAP Data Analysis Deep Learning Battery2030+ Machine Learning Automation