Material Synthesis and Design
Division 6.7
The division contributes to BAM’s mission “Safety in Technology and Chemistry” by fundamentally transforming and accelerating the development of new materials through automation, digitalization, and artificial intelligence. Our goal is to develop materials with tailored properties faster, more sustainably, and more safely – for applications that protect people and the environment and address societal challenges.
Our focus is on automated and AI/ML-driven processes for the development, synthesis, optimization, and characterization of novel materials, particularly nano- and advanced materials, within Self-Driving Labs and Materials Acceleration Platforms. The required technology stack for laboratory automation is continuously expanded and tested under real-world conditions. Data-driven approaches enable accelerated development and validation of new functional materials with enhanced sustainability and safety in line with the Safe and Sustainable by Design (SSbD) concept. For example, critical raw materials are avoided as much as possible already during the design phase. Application areas include functional coatings and additives, sensors, and – mid-term – energy generation, storage, and transmission.
Projects:
STOP – Surface Transfer of Pathogens
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Fields of Expertise
- Automated synthesis and characterization of nano- and advanced materials
- Development of the complete technology stack for Self-Driving Labs (SDLs) and Materials Acceleration Platforms (MAPs) [Video]
- AI/ML-supported synthesis planning and control, material optimization, and data analysis
- Hardware and software solutions for automated synthesis and characterization methods and workflows
- (Meta)data management, knowledge graphs, and ontologies for SDLs and MAPs
- Development of open-source software for AI-based image analysis, LLM-driven workflow generation, and hardware integration and orchestration in MAPs/SDLs
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Main Activities
- Development of nano- and advanced materials for applications such as functional coatings, additives, sensors, and reference materials
- Continuous advancement of the technology stack for MAPs/SDLs
- Automation approaches for synthesis, characterization, experiment planning, active learning in feedback loops, and data-driven material design and development
- Establishment and use of MAPs/SDLs to accelerate the design-experiment-analysis cycle and rapidly transfer material lead candidates into prototypes
- Integration of digital methods (simulation, machine learning, workflow automation, digitalization, synthesizability predictions, knowledge graphs) with experimental synthesis and characterization to:
- Accelerate material development
- Minimize uncertainties
- Increase reproducibility and reliability
- Avoid critical raw materials through targeted material design and predictive modeling of properties, sustainability impacts, and synthesis pathways (SSbD)
- Deliver high-quality transfer results for research and industry
- Regulation and standardization in laboratory automation and nano-/advanced materials
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Publications of the division
In the database PUBLICA you will find publications by BAM employees.
Publications of the division Material Synthesis and Design in PUBLICA
