MATLAB model of multiscale model for CO2 electrolysis
DOI: 10.4121/7fe30cea-7854-4b0f-9e62-fd9a012df8eb
Datacite citation style
Software
This Matlab script is a multi-scale modelling framework (ranging from the single channel scale over the electrolyser scale to the process scale) embedded in a techno-economic analysis for a CO2 electrolyser as described in the manuscript "Techno-economic assessment of CO2 electrolysis: How interdependencies propagate across scales" and the Chapter 4 of the PhD dissertation of Bagemihl. This framework allows to optimise the electrolyser performance under economic considerations and is the first of its kind which does not consider the electrolyser as blackbox. Instead mass transfer effects along the channel length are taken into account via the multi-scale model. This code is for the exemplary case of CO2 to ethylene conversion with the only side product being hydrogene. The code can be adapted for other catalysts and reactants by changing the kinetics in the single channel scale model.
History
- 2024-05-29 first online, published, posted
Publisher
4TU.ResearchDataAssociated peer-reviewed publication
Techno-economic Assessment of CO2 Electrolysis: How Interdependencies between Model Variables Propagate Across Different Modeling ScalesFunding
- Electron to Chemical Bonds consortium (grant code P17-08) [more info...] NWO
Organizations
TU Delft, Faculty of Applied Sciences, Department of Chemical EngineeringDATA
Files (33)
- 2,369 bytesMD5:
87041a927275c6784c207f009b377d80README.md - 878 bytesMD5:
e52e8a1aec89efb0b5438bc35986c78d10mL_consumption.txt - 2,494 bytesMD5:
bb25263f300788fdad4c8c45615abc0e10mL_conversion.txt - 960 bytesMD5:
b966fed88fa18ab0fad18d343b880fd815mL_consumption.txt - 3,625 bytesMD5:
b9a378390f30db3592a4e615c752f9f615mL_conversion.txt - 559 bytesMD5:
a41ec93a766d734af052ea9ed7acb5a25mL_consumption.txt - 1,705 bytesMD5:
25cde4054e4cac1975860ccae231bb6a5mL_conversion.txt - 10,464 bytesMD5:
4b4e9b2ac872cd841af05579f4eff927channelmodel_full.m - 12,736 bytesMD5:
9faabdbd25a691265e7cab6d0a6d67cachannelmodel_full_Ag.m - 10,457 bytesMD5:
056bd46582e7ce1a53ddcec28da8e19dchannelmodel_full_CO.m - 732 bytesMD5:
110610fe7290d893028f28a10710d69achannelmodel_simp.m - 138 bytesMD5:
10ba6ef5cc154221bc32b3500d0b19f6Choi_Conversion.txt - 6,597 bytesMD5:
11d03f0d34fb24f8b8514c0fb282c7cdcontourplots.m - 5,240 bytesMD5:
6dd645fad026f3a7d7154848cd6d2346Data.m - 4,289 bytesMD5:
8812db7b89d19d1ea82e6dfcda1d20dcData_Sensetivity.m - 1,354 bytesMD5:
7c0e5180ad8af3154853092231e6a302Datafitting.m - 2,462 bytesMD5:
a63044d8e56a981c1995fd5334ec7657Finances.m - 1,072 bytesMD5:
d1dea4425e51993ffe9b44c22cc65432LICENSE - 5,748 bytesMD5:
f50d3bbaaf60c1526f2a2df9290f0cb1LinePlots_Figure2and3.m - 293 bytesMD5:
2ecc6ce1b09b4410e6767bfa42ef9610Main.m - 821 bytesMD5:
8c63395f010dbe3674f96ee16938b916obj_func_full.m - 909 bytesMD5:
1bd112ae4e39bfd6038233afdef02bd7obj_func_simple.m - 2,133 bytesMD5:
7c47aeadc0b0ed43a8f0275389caa106Optimum.m - 6,290 bytesMD5:
03754972e57a00a4841e40e2889d1888Sensetivity_Analysis.m - 6,291 bytesMD5:
2f617411514e4ca5770d0ebec6b7f962Sensetivity_Analysis_full.m - 5,851 bytesMD5:
1a7440430b708631b8fcc47f801cad6aSensetivity_Analysis_simple.m - 382 bytesMD5:
04868859ed7a5b20f2514366a6f6a183SetupBest.m - 3,189 bytesMD5:
f07ee7dce7923d065197db7083b4a35aSupplementary.m - 37 bytesMD5:
caa427c19b4fa31c06cc14a60f1be781Tan_Conversion.txt - 153 bytesMD5:
df10bec509ab9df12883666d3624a8b0Tan_Flowrate_100mA.txt - 165 bytesMD5:
9bc1268346e8ca94527babc9a1adca0fTan_Flowrate_200mA.txt - 5,062 bytesMD5:
cfdb8ea653368af3c6fe575cf709f281TorPlot.m - 6,763 bytesMD5:
4f3f58a20907b6a5aa8f49ff7f96ef9dValidation_main.m -
download all files (zip)
112,218 bytes unzipped





