PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
November 16, 2020Advanced Materials Interfaces47 citations

Stabilization of Metal Single Atoms on Carbon and TiO2 Supports for CO2 Hydrogenation: The Importance of Regulating Charge Transfer

View Full Paper
CRCamila Rivera‐CárcamoCSCanio ScarfielloAGAna B. Garcı́a

Key Points

Key points are not available for this paper at this time.

Abstract

Abstract Supported single atoms constitute excellent models for understanding heterogenous catalysis and have achieved breakthroughs during the past years. How to prevent the aggregation and modulate activity of these species via metal‐support interaction should be considered for practical applications. This work presents simple methods involving the creation of carbon‐ (on carbon nanotube (CNT)) or oxygen‐vacancies (on TiO 2 ) to stabilize nickel and ruthenium single atoms. The defective supports and the resulting catalysts are characterized by a large variety of techniques. These analyses show that this strategy is efficient for the preparation of ultra‐dispersed catalysts. Comparison of the catalytic performances of these catalysts for the CO 2 hydrogenation reaction is also reported. Catalysts supported on TiO 2 are more active and sometimes more stable than those deposited on CNT. Nickel catalysts are very selective for the production of CO, and ruthenium catalysts are more selective for the production of methane. Most importantly, it is shown that, in the case of Ru, a direct correlation exists between the electronic density on the metal and the selectivity; electron‐rich species produce selectively methane, while electron‐deficient species orientate the selectivity toward CO. This work may figure a new way for the synthesis of ultra‐dispersed catalysts for various applications.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Rivera‐Cárcamo et al. (2020) studied this question.

synapsesocial.com/papers/69d7c7d7319e71454dbed9e7https://doi.org/10.1002/admi.202001777
Ask AI
Helpful
Bookmark
Share
View Full Paper