The challenge: Maximize SOFC reliability and lifetime and reduce development costs

High-temperature fuel cells such as SOFCs are particularly interesting for the stationary supply of energy, because relatively little effort is required for the preparation of fuel gas. In the energy conversion process, SOFC systems generate both electricity and heat, which can then be used in a variety of ways. Intensive research and development work is needed to reach the full potential of these fuel cells. Significant improvements are still required, particularly with regard to the aging and service life of the high-temperature fuel cells. 

The GeoDict software solution for fuel cells enables precise analysis of the fuel cell materials at the micro level. GeoDict allows the user to reliably characterize the material properties and simulate the material behavior, for example due to thermal or mechanical influences. Digital material development with GeoDict not only provides valuable data for improved fuel cell performance, but significantly reduces development costs at the same time.

Highlights of the GeoDict Solution at a Glance

  • AI-assisted identification of binders and individual grains and particles in 3D image data 
  • Generation of realistic statistical Digital Twins of the materials at the microscale
  • Determination of important geometric and physical parameters
  • Quantitative and high-performance simulation of physical properties 
  • Automated parameter studies for the design of better performing fuel cell materials

You are interested? Our team of fuel cells experts will be happy to provide you with more information!

Go to contact form

Digital Development of SOFC Materials with GeoDict

Whether GDL, MPL, CAT, PEM, BPP or a complete cell: Analyze, understand, create and optimize your material on the microscale. Math2Market enables you to digitize your materials research and development with GeoDict.


Data preprocessing

3D image data can be imported and processed with GeoDict. Latest AI technology based on artificial neural networks (KNN) enables the identification of all material constituents and all objects. Individual grains can thus be recognized and characterized.

Material Analysis

Through in-depth analysis of constituents and objects, GeoDict's structure generators can create realistic Digital Twins of the materials. Random generators are used to create statistical variance to minimize statistical errors in the simulations. Together with a database that assigns the respective material properties to all constituents, the Statistical Digital Twin is created.

Modeling & Design

GeoDict determines the important geometric and physical parameters of real or artificially created microstructures: porosity, grain and pore size distribution, active surface area, tortuosity, three-phase boundary, Gurley value, etc.

Automation & Interfaces

The Python-based automation enables the coupling of simulations and work steps to extensive parameter studies. Even complex problems such as the optimization of transport properties under mechanical compression can thus be digitally processed.

The GeoDict Solution for Fuel Cell Research

The software package consists of all necessary GeoDict modules for the research and development of fuel cell materials, including GeoDict Base.

Module Recommendations

Image Processing & Image Analysis ImportGeo-Vol          
Characterization & Analysis GrainFind-AI FiberFind-AI PoroDict + MatDict      
Modeling & Design GrainGeo FiberGeo WeaveGeo      
Simulation & Prediction DiffuDict ConductoDict FlowDict ElastoDict AddiDict SatuDict

The modules that best fit your needs depend on your specific application in fuel cell Research & Development. Contact us for more information on your project.