@article{DantismRoehlenDahmenetal.2020,
  author    = {Dantism, Shahriar and R{\"o}hlen, Desiree and Dahmen, Markus and Wagner, Torsten and Wagner, Patrick and Sch{\"o}ning, Michael Josef},
  title     = {LAPS-based monitoring of metabolic responses of bacterial cultures in a paper fermentation broth},
  series = {Sensors and Actuators B: Chemical},
  volume    = {320},
  journal   = {Sensors and Actuators B: Chemical},
  number    = {Art. 128232},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0925-4005},
  doi       = {10.1016/j.snb.2020.128232},
  year      = {2020},
  abstract  = {As an alternative renewable energy source, methane production in biogas plants is gaining more and more attention. Biomass in a bioreactor contains different types of microorganisms, which should be considered in terms of process-stability control. Metabolically inactive microorganisms within the fermentation process can lead to undesirable, time-consuming and cost-intensive interventions. Hence, monitoring of the cellular metabolism of bacterial populations in a fermentation broth is crucial to improve the biogas production, operation efficiency, and sustainability. In this work, the extracellular acidification of bacteria in a paper-fermentation broth is monitored after glucose uptake, utilizing a differential light-addressable potentiometric sensor (LAPS) system. The LAPS system is loaded with three different model microorganisms (Escherichia coli, Corynebacterium glutamicum, and Lactobacillus brevis) and the effect of the fermentation broth at different process stages on the metabolism of these bacteria is studied. In this way, different signal patterns related to the metabolic response of microorganisms can be identified. By means of calibration curves after glucose uptake, the overall extracellular acidification of bacterial populations within the fermentation process can be evaluated.},
  language  = {en}
}
@article{DotzauerPfeifferLaueretal.2019,
  author    = {Dotzauer, Martin and Pfeiffer, Diana and Lauer, Markus and Pohl, Marcel and Mauky, Eric and B{\"a}r, Katharina and Sonnleitner, Matthias and Z{\"o}rner, Wilfried and Hudde, Jessica and Schwarz, Bj{\"o}rn and Faßauer, Burkhardt and Dahmen, Markus and Rieke, Christian and Herbert, Johannes and Thr{\"a}n, Daniela},
  title     = {How to measure flexibility - Performance indicators for demand driven power generation from biogas plants},
  series = {Renewable Energy},
  journal   = {Renewable Energy},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0960-1481},
  doi       = {10.1016/j.renene.2018.10.021},
  pages     = {135 -- 146},
  year      = {2019},
  language  = {en}
}
@article{RiekeStollenwerkDahmenetal.2018,
  author    = {Rieke, Christian and Stollenwerk, Dominik and Dahmen, Markus and Pieper, Martin},
  title     = {Modeling and optimization of a biogas plant for a demand-driven energy supply},
  series = {Energy},
  volume    = {145},
  journal   = {Energy},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0360-5442},
  doi       = {10.1016/j.energy.2017.12.073},
  pages     = {657 -- 664},
  year      = {2018},
  abstract  = {Due to the Renewable Energy Act, in Germany it is planned to increase the amount of renewable energy carriers up to 60\%. One of the main problems is the fluctuating supply of wind and solar energy. Here biogas plants provide a solution, because a demand-driven supply is possible. Before running such a plant, it is necessary to simulate and optimize the process. This paper provides a new model of a biogas plant, which is as accurate as the standard ADM1 model. The advantage compared to ADM1 is that it is based on only four parameters compared to 28. Applying this model, an optimization was installed, which allows a demand-driven supply by biogas plants. Finally the results are confirmed by several experiments and measurements with a real test plant.},
  language  = {en}
}