We develop solutions for renewable energy, including biomass, solar and wind power, to enable a reliable energy transition. Our carbon capture research uses novel methods such as oxyfuel combustion, chemical looping and amine scrubbing to reduce emissions and reuse carbon dioxide. Advanced energy storage systems such as Power-to-X and thermal energy storage improve flexibility and grid stability. We also innovate pulp and paper mills as well as power plant technologies to improve efficiency. We support the effective use of solid fuels such as waste materials for electricity and heat generation as well as the synthesis of chemicals and fuels. We also use artificial intelligence to create efficient, sustainable energy systems.

Research areas

  • Energy storage systems (e.g. thermal energy storage, gravity batteries and power-to-X)
  • Renewable energy sources (e.g. biomass, solar energy, wind power)
  • Pulp and paper mills (wood-based processes and innovative stone paper)
  • Polygeneration and power plant technology (combined cycle power plants and fluidized bed)
  • Carbon capture and utilization (oxyfuel combustion, chemical-looping/carbonate-looping, amine scrubbing)
  • Biochemical and thermochemical conversion processes for solid fuels (e.g. waste, wind turbine blades, biomass, pulp mill sludge and refuse-derived fuels)
  • Process and CFD simulations with AI driven optimizations
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The Research Center for Carbon Capture and Utilization

600 m² laboratory is equipped with advanced instruments for research in carbon capture and utilization.
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Energy Storage Laboratories

We run a laboratory with advanced technology for investigating state-of-the-art energy storage system.
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Chemical Laboratories

We operate a 200 m² chemistry laboratory equipped with a wide range of instruments for the measurement and characterization of materials, including the study of heat and mass transfer and the physical properties of various feedstocks and material.
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Simulations and optimizations

Advanced numerical methods are utilized to simulate, analyze, and optimize complex industrial systems in order to save time, reduce costs, and ensure better performance across the energy, process, and environmental research projects.
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Artificial Intelligence (AI), Global optimization and sensitivity analysis

AI-based models can identify patterns, trends, relationships, and anomalies directly in data to support complex decision-making processes in diverse research domains. Global optimization and sensitivity analysis can be used to optimize equipment, plants, and processes by considering interactions between multiple inputs.
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