Deciphering Mn modulated structure-activity interplay and rational statistical analysis for CO2 rich syngas hydrogenation to clean methanol. (15th March 2022)

• Record Type: Journal Article
• Authors: Tripathi, Komal; Gupta, Vrinda; Pant, Kamal Kishore; Upadhyayula, Sreedevi
• Is Part Of: Journal of cleaner production. Volume 340(2022)
• Publication Date: 2022-03-15
• Subjects: CO2 rich syngas -- CuZn:Mn[x] catalysts -- Methanol -- Response surface methodology -- Optimization; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.130794
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Methanol produced from chemical transformation of coal derived CO2 rich syngas can be a sustainable replacement for conventional crude oil based fuels with an impressive feature of reducing greenhouse gas emissions. Mostly industrial catalysts are promoted, however, lack of detailed insight into the mechanism of promotion has so far restricted the identification of non-precious promoter. In this work, a series of Cu–Zn–Mn oxide catalysts were synthesized by varying Mn loading from 0 to 30 mol% at pH near 7 and 70 °C via co-precipitation technique to elucidate the role of Mn-promoted malachite precursors in micro structural properties of catalyst. Investigation revealed that incorporating 20 mol% Mn (CuZn:Mn[0.2]) in malachite lattice resulted in better stabilization and dispersion of CuO domains owing to maximum dilution of Cu 2+ ions as compared to other three analogous catalysts. Consequently, CuZn:Mn[0.2] catalyst unveiled ∼1.4-fold and ∼1.2-fold increase in CO conversion and methanol selectivity respectively as compared to the unpromoted catalyst. However, Mn loading beyond 20 mol% showed a detrimental effect on the catalytic efficiency due to dominant presence of an additional aurichalcite by-phase which revokes dilution of Cu 2+ ions. Co-feeding CO2 in syngas improves dual active sites synergy (Cu 0 /Cu + ) which helps in understanding catalytic mechanism of methanol synthesis. For best performing catalyst, statistically validated non-linear mathematical models were derived using response surface methodology along with central composite design. These models forecasted the correlations between process parameters as well as identified the relative contribution of each parameter. For maximising both methanol selectivity and CO conversion, desirability function predicted the optimum values of reaction temperature, pressure, and feed gas molar ratio (CO/CO2 /H2 ) as 242 °C, 49 bar and 3 respectively. Under these conditions, 46% CO conversion and 93% methanol selectivity were obtained. Thus, the formulated coal to methanol process originating from catalyst design to optimization of process parameters paves the way for sustainable solutions referring to global "3E" issues, viz. energy, environment, and economic challenges. Graphical abstract: Image 1 Highlights: Mn endows stabilization of CuO of smaller size due to enhanced dilution effect. 1.4 -fold increase in CO conversion for CuZn:Mn[0.2] as compared to CuZn:Mn[0]. Statistical optimization of process parameters using response surface methodology. Optimal conditions for fixed bed reactor are T = 242 °C, P = 49 bar, H2 /COx = 3. Predicted XCO and SCH3OH under optimal conditions are 46% and 93%, respectively.