Solid-state battery developer Factorial has launched a new proprietary simulation platform designed to accelerate the development of next-generation batteries by improving how battery performance is predicted, validated and optimized.
Factorial built its new Gammatron as a necessity-driven tool to address critical delays in battery development. Unlike traditional platforms focused solely on system-level modeling, Gammatron fuses electrochemistry, thermodynamic, and high-fidelity lab data to simulate and optimize battery behavior at both the material and cell-system level.
“Validating a new cell design can take years, but with Gammatron, we’ve demonstrated that we can dramatically shorten that timeline—forecasting long-term performance from just two weeks of early testing, instead of the typical three to six months,” said Siyu Huang, CEO of Factorial. “By combining automation with data-driven insights, we’re accelerating development with greater speed and control.”
Gammatron features a digital twin for battery cells that’s designed to accurately deliver cell state of health predictions, and to accelerate fast charging optimization that maximizes capacity and minimizes degradation and internal stress, while ensuring battery safety and longevity.
The system accelerates electrolyte formulation using molecular modeling and machine learning to engineer compositions for specific performance targets based on a deep understanding of molecular interactions.
Physics-based modeling simulates internal battery behavior, including stress, heat and degradation, that can’t be directly observed in testing.
Used in Factorial’s joint development with Stellantis, Gammatron helped forecast battery performance before full test completion—a key factor in advancing the validation program ahead of its original schedule. In some cases, Gammatron-enabled protocol tuning has doubled cycle life without altering cell chemistry, according to the company.
“Batteries are complex dynamic chemical systems. Gammatron combines machine learning with scientific feature engineering,” said Raimund Koerver, VP of Business Development at Factorial. “Where most platforms hit a wall with shallow machine learning, Gammatron goes deeper and shows engineers which material and design changes will unlock longer life and higher performance. It’s not just about predicting outcomes—it’s about enabling better ones.”
Gammatron will be operated in-house for co-development with select partners. The platform is available for solid-state battery development and legacy lithium-ion programs.
Source: Factorial