Decision tree analysis for efficient CO2 utilization in electrochemical systems


Gunay M. E., Turker L., TAPAN N. A.

JOURNAL OF CO2 UTILIZATION, cilt.28, ss.83-95, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.jcou.2018.09.011
  • Dergi Adı: JOURNAL OF CO2 UTILIZATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.83-95
  • Anahtar Kelimeler: Exploratory data analysis, Decision trees, Box and Whisker plot, CO2, Electroreduction, GAS-DIFFUSION ELECTRODES, CARBON-DIOXIDE, FORMIC-ACID, HIGH-PERFORMANCE, FARADAIC EFFICIENCY, PAST PUBLICATIONS, METAL-ELECTRODES, CU ELECTRODES, REDUCTION, COPPER
  • Gazi Üniversitesi Adresli: Evet

Özet

In this work, a database of 471 experimental data points excerpted from 34 different publications on electro-catalytic reduction of CO2 was formed. Firstly, the database was examined by exploratory data analysis using box and whiskers plots. Then, decision tree analysis was applied to determine the significance of the variables and to reveal the conditions leading to higher faradaic efficiency, production rate and product selectivity. It was found that Cu content smaller than 71% resulted high faradaic efficiencies depending on the amount of Sn, catholyte type, applied potential and pH of electrolyte. In this case, applied potential and Cu content were found to have the highest significance among all the input variables. On the other hand, the most generalizable combination of variables leading to high level of rate occurred when the Cu content being less than 13%, using a membrane other than Selemion AMV, employing a backing layer such as TGP-H-60 and keeping the applied potential between -1.5 and -2.6 V; for which the applied potential and CO2 flow rate were determined as the highest significant variables. Finally, the most generalizable path for the case of selectivity was obtained with Sn content higher than 15% and Cu content less than 52%, which leaded to formic acid production having the highest production rates. It was then concluded that, exploratory data analysis and decision trees can provide useful information to determine the conditions leading to higher CO2-electroreduction performance that may guide the future studies in this area.