Design and Implementation of Enablers in Materials Acceleration Platforms for Battery Research
Seiten
2024
TUM.University Press (Verlag)
978-3-95884-088-1 (ISBN)
TUM.University Press (Verlag)
978-3-95884-088-1 (ISBN)
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.
| Erscheinungsdatum | 29.11.2024 |
|---|---|
| Verlagsort | München |
| Sprache | englisch |
| Maße | 210 x 297 mm |
| Themenwelt | Naturwissenschaften ► Chemie ► Physikalische Chemie |
| Schlagworte | Artificial Intelligence • Automation • Battery2030+ • Battery Lifetime Prediction • Battery Material Optimization • BIG-MAP • Data Analysis • Data Management • Data Science • Deep learning • European project • High-Throughput Experimentation • International cooperation • laboratory automation • machine learning • Materials Acceleration Platform • programming • Reliability • reproducibility • Research • Technical University of Munich • TUM School of Natural Sciences • TU Munich |
| ISBN-10 | 3-95884-088-4 / 3958840884 |
| ISBN-13 | 978-3-95884-088-1 / 9783958840881 |
| Zustand | Neuware |
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