Synergistic CuZnAlZr Catalyst Enabling Efficient Coconversion of CO/CO <sub>2</sub> to Methanol

Direct methanol synthesis from CO2-rich syngas provides an effective route to eliminate the need for CO2 separation units in industrial applications. However, achieving efficient CO/CO2 coconversion remains a considerable challenge due to the distinct activation behaviors of the respective C–O bonds. Herein, a series of CuZnAlZr catalysts were prepared by tailoring Cu0 particle size and Cu–ZnO interaction applied for CO/CO2 cohydrogenation to methanol from CO2-rich syngas. The optimal catalyst achieved 100% methanol selectivity with a stable methanol space-time yield of 558 g/(kgcat·h) at CO and CO2 conversion of 70% and 20%, respectively. (H2/CO/CO2)-TPD results revealed that the synergy between moderate Cu0 particle size and strong Cu-ZnO interaction created an “H-rich/C-lean” microenvironment, which promoted the CO/CO2 cohydrogenation to methanol. In situ DRIFTS and atmosphere switching experiments indicated that the H2/CO/CO2 mixture promoted the formation of methoxy species and confirmed that CO2 served as the primary carbon source. Furthermore, DFT calculation and CO-TPSR-WGS-MS characterization confirmed that the strong Cu–ZnO interaction promoted the water–gas shift activity, which in turn led to higher CO conversion. This work provides insights for efficient catalyst design and is a promising candidate for industrial application.

Authors

Institutions

Publication Details

Journal
ACS Catalysis
Published
2026-01-22
DOI
https://doi.org/10.1021/acscatal.5c07614
Citations
1
Primary Topic
Catalysts for Methane Reforming
Type
article
Field-Weighted Citation Impact
12.85
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Synergistic CuZnAlZr Catalyst Enabling Efficient Coconversion of CO/CO 2 to Methanol

Can Zhu, Haijiao Xie, Yujing Weng, Yu Zhang et al.
1 citations
ACS Catalysis
Catalysts for Methane Reforming
12.85
article

Synergistic CuZnAlZr Catalyst Enabling Efficient Coconversion of CO/CO 2 to Methanol

Can Zhu, Haijiao Xie, Yujing Weng, Yu Zhang, Kegong Fang, Songxin Liu, Yange Wang, Chao Huang, Wei Song
article en
1 citations

Abstract

Direct methanol synthesis from CO2-rich syngas provides an effective route to eliminate the need for CO2 separation units in industrial applications. However, achieving efficient CO/CO2 coconversion remains a considerable challenge due to the distinct activation behaviors of the respective C–O bonds. Herein, a series of CuZnAlZr catalysts were prepared by tailoring Cu0 particle size and Cu–ZnO interaction applied for CO/CO2 cohydrogenation to methanol from CO2-rich syngas. The optimal catalyst achieved 100% methanol selectivity with a stable methanol space-time yield of 558 g/(kgcat·h) at CO and CO2 conversion of 70% and 20%, respectively. (H2/CO/CO2)-TPD results revealed that the synergy between moderate Cu0 particle size and strong Cu-ZnO interaction created an “H-rich/C-lean” microenvironment, which promoted the CO/CO2 cohydrogenation to methanol. In situ DRIFTS and atmosphere switching experiments indicated that the H2/CO/CO2 mixture promoted the formation of methoxy species and confirmed that CO2 served as the primary carbon source. Furthermore, DFT calculation and CO-TPSR-WGS-MS characterization confirmed that the strong Cu–ZnO interaction promoted the water–gas shift activity, which in turn led to higher CO conversion. This work provides insights for efficient catalyst design and is a promising candidate for industrial application.

ACS CatalysisVol. 16(3)
Chinese Academy of Sciences (CN), Institute of Coal Chemistry (CN), Henan Polytechnic University (CN)
Openalex Percentile: Top 3%
Catalysts for Methane Reforming
12.85
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.