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Autor(en) / Beteiligte
Titel
Modeling diurnal and annual ethylene generation from solar-driven electrochemical CO 2 reduction devices
Ist Teil von
  • Energy & environmental science, 2024-04, Vol.17 (7), p.2453-2467
Ort / Verlag
United Kingdom: Royal Society of Chemistry (RSC)
Erscheinungsjahr
2024
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards reducing carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimentally-determined CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated gaseous diurnal product outputs with and without the effects of ambient temperature. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne per year at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.
Sprache
Englisch
Identifikatoren
ISSN: 1754-5692
eISSN: 1754-5706
DOI: 10.1039/D4EE00545G
Titel-ID: cdi_osti_scitechconnect_2316097
Format

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