Precisely tuning band gaps of graphene/h-BN lateral heterostructures toward enhanced photocatalytic hydrogen evolution

Constructing heterojunctions is a proven strategy for developing efficient photocatalytic hydrogen evolution catalysts. In this work, we design graphene/hexagonal boron nitride (h-BN) lateral heterostructures that combine graphene's exceptional charge transport with h-BN's stability. Using state-of-the-art many-body green's function theory (MBGFT) simulations, we establish a band engineering framework through dimensional control, demonstrating that precise modulation of graphene and h-BN domain sizes enables continuous visible-spectrum band gap tuning for efficient hydrogen generation. The prototypical 66BN-33Gr heterostructure exemplifies this tunability, exhibiting an optimal optical band gap of 2.00 eV with superior photon harvesting characteristics. Notably, this catalyst demonstrates remarkably low exciton binding energies in the visible region, ensuring efficient charge separation. Mechanistic studies of the hydrogen evolution reaction (HER) disclose an exceptionally small energy barrier (0.21 eV) in photoexcited states, thermodynamically favoring spontaneous hydrogen generation. Furthermore, the AA-stacked architecture exhibits remarkable band gap modulation capabilities, enabling broadband optical absorption spanning the visible to near-infrared spectral regions. These fundamental insights lay the theoretical foundation for rationally engineering graphene/h-BN heterostructures as efficient photocatalytic hydrogen evolution catalysts.

Authors

Institutions

Publication Details

Journal
Physical Chemistry Chemical Physics
Published
2025-01-01
DOI
https://doi.org/10.1039/d5cp02176f
Citations
2
Primary Topic
Advanced Photocatalysis Techniques
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Precisely tuning band gaps of graphene/h-BN lateral heterostructures toward enhanced photocatalytic hydrogen evolution

Lingling Sun, Feng Jin, Honglei Yuan, Liwei Wang et al.
2 citations
Physical Chemistry Chemical Physics
Advanced Photocatalysis Techniques
0.73
article

Precisely tuning band gaps of graphene/h-BN lateral heterostructures toward enhanced photocatalytic hydrogen evolution

Lingling Sun, Feng Jin, Honglei Yuan, Liwei Wang, Yulong Wang, Chunyan Wang, Huizhong Ma, Zhuang Ma
article en
2 citations

Abstract

Constructing heterojunctions is a proven strategy for developing efficient photocatalytic hydrogen evolution catalysts. In this work, we design graphene/hexagonal boron nitride (h-BN) lateral heterostructures that combine graphene's exceptional charge transport with h-BN's stability. Using state-of-the-art many-body green's function theory (MBGFT) simulations, we establish a band engineering framework through dimensional control, demonstrating that precise modulation of graphene and h-BN domain sizes enables continuous visible-spectrum band gap tuning for efficient hydrogen generation. The prototypical 66BN-33Gr heterostructure exemplifies this tunability, exhibiting an optimal optical band gap of 2.00 eV with superior photon harvesting characteristics. Notably, this catalyst demonstrates remarkably low exciton binding energies in the visible region, ensuring efficient charge separation. Mechanistic studies of the hydrogen evolution reaction (HER) disclose an exceptionally small energy barrier (0.21 eV) in photoexcited states, thermodynamically favoring spontaneous hydrogen generation. Furthermore, the AA-stacked architecture exhibits remarkable band gap modulation capabilities, enabling broadband optical absorption spanning the visible to near-infrared spectral regions. These fundamental insights lay the theoretical foundation for rationally engineering graphene/h-BN heterostructures as efficient photocatalytic hydrogen evolution catalysts.

Physical Chemistry Chemical PhysicsVol. 27(32)
Qufu Normal University (CN), Zhoukou Normal University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 30%
Advanced Photocatalysis Techniques
0.73
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.