Technical University of Munich
Professur für Digitale und automatisierte Katalyse (Prof. Stein)
Lichtenbergstr. 4
85748 Garching b. München
We utilize digital tools like data management, machine learning, and robotics to catalyze battery and catalysis research acceleration. We don't just discover and optimize materials, components, and processes but try to investigate non-linear effects originating from a materials-in-systems perspective, such as batteries and chemical reactors. Research in our group is predominantly experimental, emphasizing (hardware and software) engineering in chemical engineering. We also research on accelerating the very way how research is executed and deploy Materials Acceleration Platforms. Currently, we investigate aqueous and solid-state batteries, oxidation, and hydrogenation catalysis, as well as data generation for foundational models in the natural sciences (see research overview).
Advanced Science
Abstract: Accurate prediction of battery behavior under different dynamic operating conditions is critical for both fundamental research and practical applications. However, the diversity of emerging materials…
ChemPhotoChem
Abstract: “Blue titania” is widely applied in photocatalysis, but comparative studies on the influence of the TiO2 phase on color evolution and stability are rare. Here, this knowledge gap is closed by…
Batteries and Supercaps
Abstract: Accelerated formation protocols that utilize pulsed charging offer an unprecedented wealth of electrochemical data. Herein, methods are presented to extract diagnostic data relating to pseudodiffusion…
Advanced Energy Materials
Abstract: High-performance batteries need accelerated discovery and optimization of new anode materials. Herein, we explore the Si─Ge─Sn ternary alloy system as a candidate fast-charging anode materials system…
Applied Energy
Abstract: The growing market for electric vehicles and portable electronics requires the reliability assessment of Li-ion batteries, especially in terms of nonlinear capacity degradation. For this purpose, a…
Energy and Fuels
Abstract: Efforts to enhance the state of health (SOH) estimation for lithium-ion batteries have increasingly focused on diverse machine learning methods, especially with the promising artificial intelligence…
Advanced Energy Materials
Abstract: High-performance batteries need accelerated discovery and optimization of new anode materials. Herein, we explore the Si─Ge─Sn ternary alloy system as a candidate fast-charging anode materials system…
ChemSusChem
Abstract: P2-type cobalt-free MnNi-based layered oxides are promising cathode materials for sodium-ion batteries (SIBs) due to their high reversible capacity and well chemical stability. However, the phase…
Batteries and Supercaps
Abstract: The formation of the solid electrolyte interphase (SEI) on HC composite electrodes plays a crucial role in enhancing the performance and operational stability of sodium (Na+) ion batteries. It has…
Chemistry of Materials
Abstract: The discovery and optimization of new materials for energy storage are essential for a sustainable future. High-throughput experimentation (HTE) using a scanning droplet cell (SDC) is suitable for the…
| Title | Dates | Duration | Type | Lecturer (assistant) |
|---|---|---|---|---|
| High-Throughput Methods and Practices (NAT0125) |
|
4 | VI | |
| Methods of Catalysis (CH3242a) |
|
2 | VO | |
| Methods of Catalysis, Seminar (CH3242b) |
|
1 | SE | |
| Seminar and Current Topics in Digital Catalysis (NAT0126) |
|
2 | SE | |
| Theory and Practice on Data Management in Chemistry (NAT0127) |
|
2 | VI |
| Title | Dates | Duration | Type | Lecturer (assistant) |
|---|---|---|---|---|
| Chemistry Graduation Ceremony |
|
0.1 | KO | |
| High-Throughput Methods and Practices (NAT0125) |
|
4 | VI | |
| Programming and Data Science (CH0103) |
|
4 | UE | |
| Programming, Numerical Methods and Applications in Chemical Engineering (NAT0411) |
|
4 | VI | |
| Seminar and Current Topics in Digital Catalysis (NAT0126) |
|
2 | SE |