A study on CO-free hydrogen production and adsorbent design for selective carbon dioxide removal

Abstract

The aim of this research study was to design and construct a fuel processor prototype (FPP), to determine its optimum steady state operation conditions, to model its dynamic performance, and to design and develop high performance AC based adsorbents for selective CO2 capture in order to reduce its CO2 emission. In this context, an FPP consisting of OSR, WGS and PROX units was designed and constructed; propane/methane individual and serial reaction tests were performed on Pt-Ni/δ-Al2O3 (OSR), Au-Re/ZrO2, Au-Re/CeO2 and Pt-Re-V/CeO2 (WGS), and Pt-Sn/AC (PROX) catalysts. In propane reaction tests, simultaneous use of high temperature (723 K) and S/C feed ratio (5) led to increased H2 (70%) and decreased CO concentrations (0.58%) in accordance with the fuel processing targets. The stability of the catalysts were confirmed during 75 hours TOS test. C3H8 and O2 were totally consumed, whereas the new WGS catalyst Pt-Re-V/CeO2 gave higher CO conversions (55-60%) than Au-Re/ZrO2 (45-50%). In methane reaction tests, O2 was totally consumed, whereas CH4 conversions were 73%, CO and H2 concentrations were obtained as 0.66% and 66%, respectively. The experimental product distributions/trends were consistent with the thermodynamics. Comparison of the conversions obtained through the kinetic experiments and modeling by the use of formerly obtained power law type kinetics gave the average error as 16.3%. Sensing time of a step change by the MS was 4.5 minutes at the FPP exit, and 36 minutes were required for reaching a new steady state. CO2 and CH4 concentrations were the most reliable parameters during real operation of the FPP (~0.6 L). 1.46, 2.19 and -0.60 combination as C3H8, O2 and H2O rate orders gave the min error in the correction of the OSR rate expression. A new methodology for the determination of selective adsorption capacity of the adsorbent under multicomponent gas mixture flow. The highest CO2 adsorption capacity was measured on AC1-N-600 sample (10.4%) and the best data fit was obtained in Dubinin-Radushkevich isotherm model with correlation coefficients > 0.999