Devices such as solar and fuel cells have been studied for many decades and noticeable improvements have been achieved. This paper proposes a Micro Photosynthetic Power Cell (μPSC) as an alternative energy-harvesting device based on photosynthesis of blue-green algae. The effect of important biodesign parameters on the performance of the device, such as no-load performance and voltage-current (V-I) characteristics, were studied. Open-circuit voltage as high as 993 mV was measured while a peak power of 175.37 μW was obtained under an external load of 850 Ω. The proposed μPSC device could produce a power density of 36.23 μW/ cm 2 , voltage density of 80 mV/cm 2 and current density of 93.38 μA /cm 2 under test conditions. INNOVATIONEnergy harvesting from photosynthesis of blue-green algae using microfluidic-based microdevices is presented in this paper. A new fabrication technique has been developed to reduce the thickness of the electrode in order to increase the effi ciency of electron transfer. Effi ciency of photosynthetic conversion to electricity will increase only if the cells are very close to the proton exchange membrane (PEM) as it occurs in microfl uidic devices. Th is energy-harvesting method using photosynthesis and polymer devices is greener than those based on photovoltaics and can eventually substitute for photovoltaic devices.
A simple first-principles mathematical model is developed to predict the performance of a micro photosynthetic power cell ([Formula: see text]PSC), an electrochemical device which generates electricity by harnessing electrons from photosynthesis in the presence of light. A lumped parameter approach is used to develop a model in which the electrochemical kinetic rate constants and diffusion effects are lumped into a single characteristic rate constant [Formula: see text]. A non-parametric estimation of [Formula: see text] for the [Formula: see text]PSC is performed by minimizing the sum square errors (SSE) between the experimental and model predicted current and voltages. The developed model is validated by comparing the model predicted [Formula: see text] characteristics with experimental data not used in the parameter estimation. Sensitivity analysis of the design parameters and the operational parameters reveal interesting insights for performance enhancement. Analysis of the model also suggests that there are two different operating regimes that are observed in this [Formula: see text]PSC. This modeling approach can be used in other designs of [Formula: see text]PSCs for performance enhancement studies.
Micro photosynthetic cell (µPSC) is an electrochemical device, which generates electricity, by harnessing the electrons from photosynthesis and respiration processes of the photoautotrophs. Till date, focus has been mostly on experimental aspects of and very little work has been pursued on the development of mathematical models for µPSC. Modeling a system like µPSC is complex due to the fact that the device operation depends on interactions of microorganisms with several operational parameters such as light intensity, quantum yield and so on. Further, the electrode structure and the electrochemical interactions at the surface of the electrodes affect the device performance. Modeling of µPSC could help in understanding the performance limiting step(s) in the series of processes that occur during the operation of device. The performance of the device can be improved by focusing on the rate of limiting steps. Modeling could also help in determining optimal design and operational parameters which can maximize the device performance. A simple mathematical model based on first principles is proposed to predict the performance of the µPSC. Sensitivity analysis is performed to obtain the most sensitive rate parameters of the model. The optimal values of sensitive rate constants are obtained from the experimental data through optimization. The developed model is validated by comparing the predictions of the model with the experimental data obtained from the response of the system to step changes in load. Figures 1 and 2 show the model performance in terms of i-V characteristics and comparison of experimental and estimated voltage profiles for step changes in external loads. Keywords:, First principles model, Parameter estimation, and Optimization and Sensitivity analysis. Figure 1
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