A neural-network-like catalyst structure for the oxygen reduction reaction: carbon nanotube bridged hollow PtCo alloy nanoparticles in a MOF-like matrix for energy technologies. Issue 34 (15th August 2019)
- Record Type:
- Journal Article
- Title:
- A neural-network-like catalyst structure for the oxygen reduction reaction: carbon nanotube bridged hollow PtCo alloy nanoparticles in a MOF-like matrix for energy technologies. Issue 34 (15th August 2019)
- Main Title:
- A neural-network-like catalyst structure for the oxygen reduction reaction: carbon nanotube bridged hollow PtCo alloy nanoparticles in a MOF-like matrix for energy technologies
- Authors:
- Wang, Jian
Wu, Guangping
Wang, Wanglan
Xuan, Wenhui
Jiang, Jingxia
Wang, Jianchuan
Li, Li
Lin, Wen-Feng
Ding, Wei
Wei, Zidong - Abstract:
- Abstract : Inspired by the brain neural systems, an ideal multi-scale model for high level utilization of constitutional unit, a neural-network-like catalyst structure was produced with a remarkable Pt utilization efficiency of 98 mgPt kW −1 in the fuel cell. Abstract : The rational design of a catalytic layer in a membrane-electrode assembly is the key to achieve high performances from proton exchange membrane fuel cells (PEMFCs). Herein, inspired by the neural-network structure of the brain, we constructed a bionic catalytic network for the oxygen reduction reaction (ORR), via setting up Pt-organic ligands–Co 2+ –organic ligands–Pt connections and then thermally transforming them into a metal-organic-framework (MOF)-like matrix in which hollow PtCo alloy nanoparticles (NPs) with an average particle size of 4.4 nm are bridged together by carbon nanotubes (PtCo@CNTs-MOF). The bionic catalytic network provides highly efficient linkages of various species-transport channels to active sites; as a result, an order of magnitude improvement is achieved in mass transfer efficiency as compared to the traditional Pt/C catalytic layer. Besides, the hollow PtCo alloy derived from Pt NPs shows a high initial mass activity of 852 mA mgPt −1 @ 0.90 V and an undetectable decay in an accelerated aging test. Accordingly, a remarkable Pt utilization efficiency of 58 mgPt kW −1 in the fuel cell cathode and 98 mgPt kW −1 in both the anode and cathode was eventually achieved, respectively. TheAbstract : Inspired by the brain neural systems, an ideal multi-scale model for high level utilization of constitutional unit, a neural-network-like catalyst structure was produced with a remarkable Pt utilization efficiency of 98 mgPt kW −1 in the fuel cell. Abstract : The rational design of a catalytic layer in a membrane-electrode assembly is the key to achieve high performances from proton exchange membrane fuel cells (PEMFCs). Herein, inspired by the neural-network structure of the brain, we constructed a bionic catalytic network for the oxygen reduction reaction (ORR), via setting up Pt-organic ligands–Co 2+ –organic ligands–Pt connections and then thermally transforming them into a metal-organic-framework (MOF)-like matrix in which hollow PtCo alloy nanoparticles (NPs) with an average particle size of 4.4 nm are bridged together by carbon nanotubes (PtCo@CNTs-MOF). The bionic catalytic network provides highly efficient linkages of various species-transport channels to active sites; as a result, an order of magnitude improvement is achieved in mass transfer efficiency as compared to the traditional Pt/C catalytic layer. Besides, the hollow PtCo alloy derived from Pt NPs shows a high initial mass activity of 852 mA mgPt −1 @ 0.90 V and an undetectable decay in an accelerated aging test. Accordingly, a remarkable Pt utilization efficiency of 58 mgPt kW −1 in the fuel cell cathode and 98 mgPt kW −1 in both the anode and cathode was eventually achieved, respectively. The latter is almost 3 times higher than that of the traditional catalytic layer. Moreover, no decay was detected during continuous operation at 1 A cm −2 for 130 hours from the bionic catalytic network based fuel cell. This strategy offers a new concept for designing an ultra-low Pt loading yet highly active and durable catalytic layer for fuel cell applications and beyond. … (more)
- Is Part Of:
- Journal of materials chemistry. Volume 7:Issue 34(2019)
- Journal:
- Journal of materials chemistry
- Issue:
- Volume 7:Issue 34(2019)
- Issue Display:
- Volume 7, Issue 34 (2019)
- Year:
- 2019
- Volume:
- 7
- Issue:
- 34
- Issue Sort Value:
- 2019-0007-0034-0000
- Page Start:
- 19786
- Page End:
- 19792
- Publication Date:
- 2019-08-15
- Subjects:
- Materials -- Research -- Periodicals
Chemistry, Analytic -- Periodicals
Environmental sciences -- Research -- Periodicals
543.0284 - Journal URLs:
- http://pubs.rsc.org/en/journals/journalissues/ta ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c9ta06712d ↗
- Languages:
- English
- ISSNs:
- 2050-7488
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5012.205100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 11449.xml