期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 117, 期 12, 页码 6316-6322出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1903721117
关键词
combinatorial; high-throughput synthesis; multimetallic nanoclusters; thermal shock; oxygen reduction reaction
资金
- Maryland Nanocenter, its Surface Analysis Center
- AIMLab
- NSF Division of Materials Research Award [1809439]
- Young Investigator Program of the Army Research Office [W911 NF-15-1-0123]
- Office of Science of the US Department of Energy [DE-SC0004993]
- DOE Office of Science [DE-AC02-06CH11357]
- Division Of Materials Research
- Direct For Mathematical & Physical Scien [1809439] Funding Source: National Science Foundation
Multimetallic nanoclusters (MMNCs) offer unique and tailorable surface chemistries that hold great potential for numerous catalytic applications. The efficient exploration of this vast chemical space necessitates an accelerated discovery pipeline that supersedes traditional trial-and-error experimentation while guaranteeing uniform microstructures despite compositional complexity. Herein, we report the high-throughput synthesis of an extensive series of ultrafine and homogeneous alloy MMNCs, achieved by 1) a flexible compositional design by formulation in the precursor solution phase and 2) the ultrafast synthesis of alloy MMNCs using thermal shock heating (i.e., similar to 1,650 K, similar to 500 ms). This approach is remarkably facile and easily accessible compared to conventional vapor-phase deposition, and the particle size and structural uniformity enable comparative studies across compositionally different MMNCs. Rapid electrochemical screening is demonstrated by using a scanning droplet cell, enabling us to discover two promising electrocatalysts, which we subsequently validated using a rotating disk setup. This demonstrated high-throughput material discovery pipeline presents a paradigm for facile and accelerated exploration of MMNCs for a broad range of applications.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据