Template Quality Dependent Conversion Synthesis of Boron Nitride Coated Graphene Hybrid Aerogels for Ultrasensitive and Selective Ammonia Sensing

Abstract Recently, hexagonal boron nitride (h‐BN) nanomaterials, e.g., nanosheets and nanotubes, have been predicted to be effective materials for reversible gas adsorption with high selectivity once charged. However, despite the encouraging theoretical predictions, sensing with h‐BN is difficult to realize experimentally due to its electrically insulating nature stemming from its large band gap. In this research, the controlled synthesis of high surface area hybrid h‐BN/graphene aerogel is reported, using high‐quality graphene as a template, and its application for selective gas sensing. It is discovered for the first time in this system that the difficulty of conversion in template synthesis of h‐BN is positively correlated with the quality of the carbon template, an observation that is verified on both graphene nanosheets and carbon nanotubes. The application of this hybrid material for gas sensing yields ppb level of detection limit and high selectivity for NH 3 . Through density functional theory calculations, the adsorption energy and charge transfer between NH 3 molecules and aerogel are greatly enhanced. Therefore, this innovative approach promises new possibilities for the application of h‐BN in gas sensing, with the potential to play a significant role in gas capture, environmental monitoring, and other related fields.

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Publication Details

Journal
Advanced Functional Materials
Published
2024-11-13
DOI
https://doi.org/10.1002/adfm.202416251
Citations
8
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
Field-Weighted Citation Impact
1.67

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article

Template Quality Dependent Conversion Synthesis of Boron Nitride Coated Graphene Hybrid Aerogels for Ultrasensitive and Selective Ammonia Sensing

Tielin Shi, Guanglan Liao, Hu Long, Sally Turner et al.
8 citations
Advanced Functional Materials
Gas Sensing Nanomaterials and Sensors
1.67
article

Template Quality Dependent Conversion Synthesis of Boron Nitride Coated Graphene Hybrid Aerogels for Ultrasensitive and Selective Ammonia Sensing

Tielin Shi, Guanglan Liao, Hu Long, Sally Turner, Alex K. Zettl, Roya Maboudian, Carlo Carraro, Aiming Yan, Zhen Yuan, Guangliang Li, Amin Azizi
article en
8 citations

Abstract

Abstract Recently, hexagonal boron nitride (h‐BN) nanomaterials, e.g., nanosheets and nanotubes, have been predicted to be effective materials for reversible gas adsorption with high selectivity once charged. However, despite the encouraging theoretical predictions, sensing with h‐BN is difficult to realize experimentally due to its electrically insulating nature stemming from its large band gap. In this research, the controlled synthesis of high surface area hybrid h‐BN/graphene aerogel is reported, using high‐quality graphene as a template, and its application for selective gas sensing. It is discovered for the first time in this system that the difficulty of conversion in template synthesis of h‐BN is positively correlated with the quality of the carbon template, an observation that is verified on both graphene nanosheets and carbon nanotubes. The application of this hybrid material for gas sensing yields ppb level of detection limit and high selectivity for NH 3 . Through density functional theory calculations, the adsorption energy and charge transfer between NH 3 molecules and aerogel are greatly enhanced. Therefore, this innovative approach promises new possibilities for the application of h‐BN in gas sensing, with the potential to play a significant role in gas capture, environmental monitoring, and other related fields.

Advanced Functional MaterialsVol. 35(9)
Lawrence Berkeley National Laboratory (US), University of Electronic Science and Technology of China (CN), University of California, Santa Cruz (US), Kavli Energy NanoScience Institute (US), Huazhong University of Science and Technology (CN), University of California, Berkeley (US)
National Science Foundation, U.S. Department of Energy, National Natural Science Foundation of China, Office of Science, Wuhan Science and Technology Project, Basic Energy Sciences
Openalex Percentile: Top 15%
Gas Sensing Nanomaterials and Sensors
1.67
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