Huiyuan Zhu

Huiyuan Zhu

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Huiyuan Zhu

Department of Chemistry, University of Virginia, 409 McCormick Rd, Charlottesville, VA 22904, USA

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 September 2015 in ACS Catalysis
Verified
Journal Article
Closed access
HZHuiyuan Zhu
Huiyuan Zhu
PZPengfei Zhang
Pengfei Zhang
SDSheng Dai
Sheng Dai

29 April 2022 in Nature Communications
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Journal Article
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QGQiang Gao
Qiang Gao
HPHemanth Somarajan Pillai
Hemanth Somarajan Pillai
YHYang Huang
Yang Huang
SLShikai Liu
Shikai Liu
QMQingmin Mu
Qingmin Mu
HZHuiyuan Zhu
Huiyuan Zhu
The electrochemical nitrate reduction reaction (NO3RR) to ammonia is an essential step toward restoring the globally disrupted nitrogen cycle. In search of highly efficient electrocatalysts, tailoring catalytic sites with ligand and strain effects in random alloys is a common approach but remains limited due to the ubiquitous energy-scaling relations. With interpretable machine learning, we unravel a mechanism of breaking adsorption-energy scaling relations through the site-specific Pauli repulsion interactions of the metal d-states with adsorbate frontier orbitals. The non-scaling behavior can be realized on (100)-type sites of ordered B2 intermetallics, in which the orbital overlap between the hollow *N and subsurface metal atoms is significant while the bridge-bidentate *NO3 is not directly affected. Among those intermetallics predicted, we synthesize monodisperse ordered B2 CuPd nanocubes that demonstrate high performance for NO3RR to ammonia with a Faradaic efficiency of 92.5% at −0.5 VRHE and a yield rate of 6.25 mol h−1 g−1 at −0.6 VRHE. This study provides machine-learned design rules besides the d-band center metrics, paving the path toward data-driven discovery of catalytic materials beyond linear scaling limitations.

22 July 2016 in Angewandte Chemie International Edition
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Journal Article
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Wenshuai ZhuWenshuai Zhu
Wenshuai Zhu
XGXiang Gao
Xiang Gao
Qian LiQian Li
Qian Li
HLHongping Li
Hongping Li
YCYanhong Chao
Yanhong Chao
SDSheng Dai
Sheng Dai

22 August 2016 in ACS Catalysis
Verified
Journal Article
Closed access
ZZZhiyong Zhang
Zhiyong Zhang
MCMiaofang Chi
Miaofang Chi
GVGabriel M. Veith
Gabriel M. Veith
PZPengfei Zhang
Pengfei Zhang
DLDaniel A. Lutterman
Daniel A. Lutterman
HZHuiyuan Zhu
Huiyuan Zhu

9 June 2017 in Nature Communications
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Journal Article
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Wenshuai ZhuWenshuai Zhu
Wenshuai Zhu
ZWZili Wu
Zili Wu
GFGuo Shiou Foo
Guo Shiou Foo
XGXiang Gao
Xiang Gao
MZMingxia Zhou
Mingxia Zhou
HZHuiyuan Zhu
Huiyuan Zhu
Taming interfacial electronic effects on Pt nanoparticles modulated by their concomitants has emerged as an intriguing approach to optimize Pt catalytic performance. Here, we report Pt nanoparticles assembled on vacancy-abundant hexagonal boron nitride nanosheets and their use as a model catalyst to embrace an interfacial electronic effect on Pt induced by the nanosheets with N-vacancies and B-vacancies for superior CO oxidation catalysis. Experimental results indicate that strong interaction exists between Pt and the vacancies. Bader charge analysis shows that with Pt on B-vacancies, the nanosheets serve as a Lewis acid to accept electrons from Pt, and on the contrary, when Pt sits on N-vacancies, the nanosheets act as a Lewis base for donating electrons to Pt. The overall-electronic effect demonstrates an electron-rich feature of Pt after assembling on hexagonal boron nitride nanosheets. Such an interfacial electronic effect makes Pt favour the adsorption of O2, alleviating CO poisoning and promoting the catalysis.

9 March 2023 in Nature Synthesis
Verified
Journal Article
Closed access
PDF file
QGQiang Gao
Qiang Gao
BYBingqing Yao
Bingqing Yao
HPHemanth Somarajan Pillai
Hemanth Somarajan Pillai
WZWenjie Zang
Wenjie Zang
XHXue Han
Xue Han
HZHuiyuan Zhu
Huiyuan Zhu