Data-driven pilot optimization for electrochemical CO mass production. Issue 33 (5th August 2020)
- Record Type:
- Journal Article
- Title:
- Data-driven pilot optimization for electrochemical CO mass production. Issue 33 (5th August 2020)
- Main Title:
- Data-driven pilot optimization for electrochemical CO mass production
- Authors:
- Kim, Kyeongsu
Lee, Woong Hee
Na, Jonggeol
Hwang, YunJeong
Oh, Hyung-Suk
Lee, Ung - Abstract:
- Abstract : Pilot plant optimization of CO2 RR system to produce CO via Ag electrodes have been performed and the results are intensely studied via correlation analysis. Abstract : Electroreduction systems to convert CO2 into CO via Ag electrodes have been intensely studied as a means of producing carbon-neutral fuels or chemical products. However, despite many efforts to maximize the performance of CO-producing systems, the performance of electrochemical cells that produce CO has not yet reached the level of economic viability. Moreover, compared with electrode development attempts, studies on the optimization of large-scale CO-producing systems are lacking, thus impeding the commercialization of electrochemical CO2 reduction systems. In this study, we present optimization results of a pilot-scale CO production system. Operating conditions such as pressure, temperature, and cell voltage were considered as the optimization variables to improve the CO partial current density. To facilitate experiment-based optimization of the pilot-scale operation, we adopted an efficient design of the experiment, for which data points were decided by input–output relations. As a result, the maximum CO partial current reached 2.56 A using a 50 cm 2 electrode within 25 experiments. In addition, regression analysis results were provided for future studies on the systematic optimization of electrochemical systems. The operating temperature and CO2 solubility were more highly correlated with theAbstract : Pilot plant optimization of CO2 RR system to produce CO via Ag electrodes have been performed and the results are intensely studied via correlation analysis. Abstract : Electroreduction systems to convert CO2 into CO via Ag electrodes have been intensely studied as a means of producing carbon-neutral fuels or chemical products. However, despite many efforts to maximize the performance of CO-producing systems, the performance of electrochemical cells that produce CO has not yet reached the level of economic viability. Moreover, compared with electrode development attempts, studies on the optimization of large-scale CO-producing systems are lacking, thus impeding the commercialization of electrochemical CO2 reduction systems. In this study, we present optimization results of a pilot-scale CO production system. Operating conditions such as pressure, temperature, and cell voltage were considered as the optimization variables to improve the CO partial current density. To facilitate experiment-based optimization of the pilot-scale operation, we adopted an efficient design of the experiment, for which data points were decided by input–output relations. As a result, the maximum CO partial current reached 2.56 A using a 50 cm 2 electrode within 25 experiments. In addition, regression analysis results were provided for future studies on the systematic optimization of electrochemical systems. The operating temperature and CO2 solubility were more highly correlated with the current density and selectivity than was the applied cell voltage, and the CO current density could be predicted with high accuracy. … (more)
- Is Part Of:
- Journal of materials chemistry. Volume 8:Issue 33(2020)
- Journal:
- Journal of materials chemistry
- Issue:
- Volume 8:Issue 33(2020)
- Issue Display:
- Volume 8, Issue 33 (2020)
- Year:
- 2020
- Volume:
- 8
- Issue:
- 33
- Issue Sort Value:
- 2020-0008-0033-0000
- Page Start:
- 16943
- Page End:
- 16950
- Publication Date:
- 2020-08-05
- Subjects:
- Materials -- Research -- Periodicals
Chemistry, Analytic -- Periodicals
Environmental sciences -- Research -- Periodicals
543.0284 - Journal URLs:
- http://pubs.rsc.org/en/journals/journalissues/ta ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/d0ta05607c ↗
- Languages:
- English
- ISSNs:
- 2050-7488
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5012.205100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 13886.xml