Research
Active material processing and recycling
A sustainable battery ecosystem starts with how we source, process, and recover critical raw materials. At our center, we work across the full spectrum of active material production—from ore to electrode and back again. Our research addresses both primary and secondary pathways, linking mineral processing, chemical synthesis, and materials engineering with digital modeling and real-time control. In upstream processes, we develop efficient and low-emission methods for crushing, grinding, leaching, and refining battery-relevant materials such as lithium, nickel, manganese, graphite, and silicon. Downstream, we focus on active material synthesis and surface modification tailored for next-generation cell chemistries. We also lead in recycling innovation, pioneering cathode-to-cathode regeneration, closed-loop process control, and material tracking via digital product passports. Our work supports circular value chains by integrating metallurgy, process simulation, and system-level optimization. Through close collaboration with mining companies, recycling startups, and battery OEMs, we ensure that material processing and recycling innovations are scalable, cost-effective, and aligned with EU critical raw material strategies and Swedish industrial priorities.
Battery cell manufacturing
From laboratory lines to gigafactories, battery cell manufacturing is evolving rapidly—and we are at the forefront of shaping this transformation. Our work spans the full production flow: slurry mixing, electrode coating and drying, calendering, cell assembly, electrolyte filling, formation, and aging.We combine deep process understanding with cutting-edge digitalization. Through multi-physics process simulation—capturing thermal, fluidic, mechanical, and electrochemical interactions—we provide predictive insights into how cells behave during production. These simulations inform process design, control strategies, and defect prevention across the entire chain. In parallel, we develop and apply advanced experimental mechanics to observe and quantify material behavior in real-time. Our infrastructure supports X-ray imaging, high-speed photography, laser Doppler vibrometry, and 3D surface scanning—enabling non-invasive measurement of deformations, thickness variations, wetting dynamics, and mechanical stresses during manufacturing. These techniques provide the empirical foundation to validate simulation models and tune production parameters with precision. We also pioneer TLP (Technical Language Processing) methods that automate knowledge extraction from technical manuals, process logs, and scientific literature. This helps generate intelligent test protocols, benchmark processes across factories, and structure decision support systems for production engineers. All of this feeds into our digital twin ecosystems and IT/OT integration frameworks. By combining model-based control, inline measurement technologies, and edge AI for defect detection, we accelerate the deployment of smarter, faster, and more sustainable battery manufacturing. We collaborate closely with equipment suppliers, material producers, and battery OEMs to ensure that research translates directly into industrial practice—with demonstrators, testbeds, and open infrastructure for scalable innovation.
Battery cell development
The development of advanced battery cells requires the seamless integration of materials science, electrochemistry, systems engineering, and data analytics. Our center builds the tools and methods to accelerate this process—supporting everything from material selection to full-cell performance evaluation and digital twin deployment. We specialize in simulation-driven cell design, combining electrochemical, thermal, and mechanical modeling across multiple scales. Our approach allows researchers and developers to virtually explore how changes in materials, geometry, and manufacturing conditions influence real-world cell behavior. We also integrate data-driven methods—including machine learning and technical language processing (TLP)—to accelerate design iteration and test planning. TLP techniques are a cornerstone of our material innovation strategy. By extracting structured knowledge from vast volumes of technical documents, patents, and scientific literature, we identify promising material combinations, parameter regimes, and design heuristics that would otherwise remain hidden. This enables faster convergence on high-performing cell chemistries and interfaces, even in emerging domains like sodium-ion and solid-state batteries. A key focus is creating interoperable and modular platforms for cell development. We support experimental validation through advanced test rigs, including dynamic electrochemical impedance spectroscopy (dEIS), ultrasonic imaging, and multi-physics test environments. These platforms feed into digital twins that connect lab-scale results to industrial conditions, enabling predictive control and system-level optimization. Whether for LFP, NMC, sodium-ion, Li-S or solid-state cells, our methods help shorten development cycles, reduce material waste, and support faster deployment into vehicles, energy storage, and industrial applications.
Updated: