Identifying the Key Factors for Boosting NiFe-LDH with Optimized Bifunctional HER/OER Activities

Although nickel–iron layered double hydroxide (NiFe-LDH) demonstrates promising oxygen evolution reaction (OER) performance, its inherently limited hydrogen evolution reaction (HER) activity restricts its application as a bifunctional electrocatalyst for alkaline water splitting. This study describes the development of an ultrafast self-heating coprecipitation method for synthesizing low-crystallinity NiFe-LDH as a model catalyst, with precise control over the Ni/Fe atomic ratio, vacancy concentration, and crystallinity. Multivariate trend analysis was performed to systematically decouple the individual and synergistic effects of these parameters on the intrinsic OER and HER activities of NiFe-LDH. The findings of the study highlight the critical role of iron vacancies in boosting the bifunctional activities of NiFe-LDH by electronically modulating Ni sites, with a Ni/Fe atomic ratio of approximately 1:1 and sufficiently low crystallinity achieving optimized OER and HER activities. This study helps to establish mechanistic design rules for NiFe-LDH–based bifunctional electrocatalysts and demonstrates a broadly applicable synthesis–analysis framework for advancing cost-effective water splitting.

Authors

Institutions

Publication Details

Journal
ACS Sustainable Chemistry & Engineering
Published
2026-01-13
DOI
https://doi.org/10.1021/acssuschemeng.5c11409
Citations
2
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
19.58
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying the Key Factors for Boosting NiFe-LDH with Optimized Bifunctional HER/OER Activities

Baoxin Wu, Fujin Li, Ziyan Zhang, Shuguang Chen et al.
2 citations
ACS Sustainable Chemistry & Engineering
Electrocatalysts for Energy Conversion
19.58
article

Identifying the Key Factors for Boosting NiFe-LDH with Optimized Bifunctional HER/OER Activities

Baoxin Wu, Fujin Li, Ziyan Zhang, Shuguang Chen, Taotao Zeng, Feifei Zhang, Ganxin Yang, Peng Liu, Sihang You
article en
2 citations

Abstract

Although nickel–iron layered double hydroxide (NiFe-LDH) demonstrates promising oxygen evolution reaction (OER) performance, its inherently limited hydrogen evolution reaction (HER) activity restricts its application as a bifunctional electrocatalyst for alkaline water splitting. This study describes the development of an ultrafast self-heating coprecipitation method for synthesizing low-crystallinity NiFe-LDH as a model catalyst, with precise control over the Ni/Fe atomic ratio, vacancy concentration, and crystallinity. Multivariate trend analysis was performed to systematically decouple the individual and synergistic effects of these parameters on the intrinsic OER and HER activities of NiFe-LDH. The findings of the study highlight the critical role of iron vacancies in boosting the bifunctional activities of NiFe-LDH by electronically modulating Ni sites, with a Ni/Fe atomic ratio of approximately 1:1 and sufficiently low crystallinity achieving optimized OER and HER activities. This study helps to establish mechanistic design rules for NiFe-LDH–based bifunctional electrocatalysts and demonstrates a broadly applicable synthesis–analysis framework for advancing cost-effective water splitting.

ACS Sustainable Chemistry & EngineeringVol. 14(3)
Hong Kong Polytechnic University (HK), Jilin University (CN), Jilin Medical University (CN), Changsha University of Science and Technology (CN)
Clean water and sanitation
Openalex Percentile: Top 1%
Electrocatalysts for Energy Conversion
19.58
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.