All projectsScientific machine learning

Calibrating granular models

Accelerated parameter optimization

Granular modelsOptimizationCalibration
Concept illustration — Scientific machine learning
Concept illustration

The question

How can parameter optimization support granular models of battery manufacturing?

Method and workflow

This study examines accelerated parameter optimization for granular manufacturing models. The project will document how the physical model, optimization process, and evaluation criteria fit together.

Research output

Accelerated Parameter Optimization of Granular Models of Battery Manufacturing is listed in the June 2026 CV as a preprint under review. The preprint is available through the linked DOI.

Results and insights

The detailed optimization workflow, evaluation figures, and interpretation of the results will be added here after selecting the material for public presentation.

My contribution

A specific statement of my role is to be added.

Scope and limitations

The conceptual workflow does not report numerical performance. Claims about acceleration, accuracy, or transferability should be read in the source manuscript and will not be inferred from the title alone.