PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 24, 2026AIChE Journal0 citations

Short Fe‐C bonds boost Fischer‐Tropsch catalyst for CO 2 to valuable C 2 + products

View Full Paper
XBXinze BiXYXudong YuRHRuosong He

Key Points

  • The central aim is to enhance Fischer-Tropsch catalysts through the design of shorter Fe-C bonds.
  • Developed an Fe-based Fischer-Tropsch catalyst with carbon quantum dots (CQDs).
  • Studied the effects of shorter Fe-C bonds on catalytic performance.
  • Measured CO2 conversion and product selectivity in controlled experiments.
  • Achieved 81.3% selectivity for C2+ products.
  • Recorded only 8.8% selectivity for CO.
  • Reached a CO2 conversion rate of 38.5%.
  • Increased C2+ products yield to 28.6%, setting a record among existing results.

Abstract

Abstract The coordination environment and orbital state of the active sites determine the catalytic performance, and the realization of their rational design is one of the ultimate goals in the research field of catalysis. Here we report an active Fe‐based Fischer‐Tropsch synthesis catalyst with shorter Fe‐C bond tuned by decorating carbon quantum dots (CQDs) for production of value‐added C 2+ products from CO 2 hydrogenation. Different from traditional in‐situ formed iron carbide active sites, the shorter Fe‐C bond endowed by strengthened electron transfer between Fe species and CQDs boosts CO* protonation and CC bond coupling. This novel active site delivers ultra‐high C 2+ products selectivity (81.3%) and extremely low CO selectivity (8.8%) at a CO 2 conversion of 38.5%, achieving a record‐breaking C 2+ products yield (28.6%) among the reported results. This work may shed a light on the rational design and optimization of metal carbide‐based catalysts for Fischer‐Tropsch synthesis of value‐added C 2+ products and beyond.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bi et al. (2026) studied this question.

synapsesocial.com/papers/6974610cbb9d90c67120af7bhttps://doi.org/10.1002/aic.70249
Ask AI
Helpful
Bookmark
Share
View Full Paper