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Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)
Discoveries of novel electrolyte–electrode combinations require comprehensive structure–property–interface correlations. Herein, we …
Fuzhan Rahmanian, Stefan Fuchs, Maximilian Fichtner, Helge Sören Stein
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Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)
Attention towards chemistry agnostic and explainable battery lifetime prediction
Predicting and monitoring battery life early and across chemistries is a significant challenge due to the plethora of degradation …
Fuzhan Rahmanian, Robert M Lee, Dominik Linzner, Kathrin Michel, Leon Merker, Balazs B Berkes, Leah Nuss, Helge Sören Stein
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Attention towards chemistry agnostic and explainable battery lifetime prediction
Conductivity experiments for electrolyte formulations and their automated analysis
Electrolytes are considered crucial for the performance of batteries, and therefore indispensable for future energy storage research. …
Dr.-Ing. Fuzhan Rahmanian, Monika Vogler, Christian Wälke, Peng Yen, Stefan Fuchs, Martin Winter, Isidora Cekic-Laskovic, Helge Sören Stein
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Conductivity experiments for electrolyte formulations and their automated analysis
One-Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity
Conductivity optimization for battery electrolytes is a cumbersome task, especially at different temperatures. Herein optimally high conducting electrolytes for any temperature are discovered through combined high-throughput experimentation and machine learning.
Dr.-Ing. Fuzhan Rahmanian, Monika Vogler, Christian Wölke, Peng Yan, Martin Winter, Isidora Cekic-Laskovic, Helge S Stein
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One-Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity
Enabling Modular Autonomous Feedback-Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration
Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high-throughput …
Dr.-Ing. Fuzhan Rahmanian, Jackson Flowers, Dan Guevarra, Matthias Richter, Maximilian Fichtner, Phillip Donnely, John M Gregoire, Helge S Stein
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Enabling Modular Autonomous Feedback-Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration
The potential of scanning electrochemical probe microscopy and scanning droplet cells in battery research
Spatially resolved characterization of electrode surfaces or electrode–electrolyte interfaces is of fundamental interest in battery …
Sven Daboss, Dr.-Ing. Fuzhan Rahmanian, Helge S. Stein, Christine Kranz
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The potential of scanning electrochemical probe microscopy and scanning droplet cells in battery research
From materials discovery to system optimization by integrating combinatorial electrochemistry and data science
Insight generation from electrochemical experiments augmented by data science requires broad, systematic, and well-defined parameter …
Helge S. Stein, Alexey Sanin, Dr.-Ing. Fuzhan Rahmanian, Bojing Zhang, Monika Vogler, Jackson K. Flowers, Leon Fischer, Stefan Fuchs, Nirmal Choudhary, Lisa Schroeder
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From materials discovery to system optimization by integrating combinatorial electrochemistry and data science
High-throughput experimentation and computational freeway lanes for accelerated battery electrolyte and interface development research
The timely arrival of novel materials plays a key role in bringing advances to society, as the pace at which major technological …
Benayad Anass, Diddens Diddo, Dr.-Ing. Fuzhan Rahmanian, Heuer Andreas
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High-throughput experimentation and computational freeway lanes for accelerated battery electrolyte and interface development research
Data Management Plans: the Importance of Data Management in the BIG-MAP Project
Standardization and ontology have the role of homogenizing the data and make them interoperable. Data Management Plans are increasingly important for accelerating research. Here, we describe the case of BIG-MAP, a cross-disciplinary project targeting disruptive battery-material discoveries. Central in the project is the role of data and its infrastructure to store and exchange research data. Standards and an ontology further ensures data that can be interoperated across different domains, from theory to experiments and artificial intelligence.
Prof. Ivano E. Castelli, Daniel J. Arismendi-Arrieta, Dr.-Ing. Fuzhan Rahmanian
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Data Management Plans: the Importance of Data Management in the BIG-MAP Project