About
Accelerating the discovery, design and integration of new energy materials by extracting knowledge from large-scale data assets and performing AI-driven analytics.
Research Topics
- Data Extraction and Management
- AI/ML Models
- Simulations
- Image Analysis
- Cloud Applications
Data models & management
- Optimierte DatenpipelineData management (mining, extraction, curation)
- Data models
- Ontology & materials linguistics
- Optimized data pipeline
- Autonomous workflow
AI/ML models & methods
- Inverse design for energy materials
- Predictive analytics & AI-ready data models
- Automated image analysis
- Accelerated simulations
Application & tool deployment
- Materials intelligence
- Automated data extraction tools
- Cloud-based big-data solutions and data services
- Mix-reality data visualization (XR4MAT)
Members
External partners and guests
- Sahand Behnam
- Dr. Titichai Navessin
- Sarvin Golravesh Fekri
- Armin Gheytarani
Research
AI/ML Models and Methods
Accelerating design, integration and scale-up
- Inverser design for new AEM membranes
- Accelerating simulations and automated FF parametrization
- Automated image analysis
Data Modeling and Management
Scalable and deployable data management and correlation models
- Automated data pipelines and workflow optimization for PEFC/PEWE component fabrication
- AI-based data handling and workflow optimization
- Graph database development for OER/ORR electrocatalysts
- ES materials to devices
Keywords: Ontologies for CL-Link, developing workflows, data mining and visualization
Last Modified: 01.03.2023