Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor
The assembly of primary nanoparticles to form hierarchical ultra-porous architectures is of great interest in various fields because of their extremely large surface area and porosity. In this work, the 3D ultra-porous γ-Fe2O3 nanocubes were synthesized by a simple method, which was derived from per...
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oai:localhost:PNK-59042022-08-17T05:54:55Z Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor Ho, Van Minh Hai Nguyen, Duc Cuong Hien Duy, Mai Ultra-porous Nanocubes The assembly of primary nanoparticles to form hierarchical ultra-porous architectures is of great interest in various fields because of their extremely large surface area and porosity. In this work, the 3D ultra-porous γ-Fe2O3 nanocubes were synthesized by a simple method, which was derived from perfect Prussian Blue nanocubes by the oxidative decomposition process. The as-synthesized 3D γ-Fe2O3 nanocubes possess a large specific surface area and high porosity, which arise from the self-assembly of ultrafine nanoparticles. The 3D ultra-porous γ-Fe2O3 nanocubes-based sensors showed superior detection of acetone and ethanol with excellent sensitivity and rapid response time. The fantastic gas-sensing platform of 3D γ-Fe2O3 nanocubes could originate from their unique structures and interesting gas-sensing mechanisms. The linear discriminant analysis (LDA) algorithm was effectively used to discriminate between acetone and ethanol. 2022-07-13T01:59:52Z 2022-07-13T01:59:52Z 2022 Bài trích https://www.sciencedirect.com/science/article/abs/pii/S0925400522003793?via%3Dihub https://dlib.phenikaa-uni.edu.vn/handle/PNK/5904 https://doi.org/10.1016/j.snb.2022.131737 en Elsevier |
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Ultra-porous Nanocubes |
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Ultra-porous Nanocubes Ho, Van Minh Hai Nguyen, Duc Cuong Hien Duy, Mai Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor |
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The assembly of primary nanoparticles to form hierarchical ultra-porous architectures is of great interest in various fields because of their extremely large surface area and porosity. In this work, the 3D ultra-porous γ-Fe2O3 nanocubes were synthesized by a simple method, which was derived from perfect Prussian Blue nanocubes by the oxidative decomposition process. The as-synthesized 3D γ-Fe2O3 nanocubes possess a large specific surface area and high porosity, which arise from the self-assembly of ultrafine nanoparticles. The 3D ultra-porous γ-Fe2O3 nanocubes-based sensors showed superior detection of acetone and ethanol with excellent sensitivity and rapid response time. The fantastic gas-sensing platform of 3D γ-Fe2O3 nanocubes could originate from their unique structures and interesting gas-sensing mechanisms. The linear discriminant analysis (LDA) algorithm was effectively used to discriminate between acetone and ethanol. |
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Bài trích |
author |
Ho, Van Minh Hai Nguyen, Duc Cuong Hien Duy, Mai |
author_facet |
Ho, Van Minh Hai Nguyen, Duc Cuong Hien Duy, Mai |
author_sort |
Ho, Van Minh Hai |
title |
Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor |
title_short |
Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor |
title_full |
Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor |
title_fullStr |
Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor |
title_full_unstemmed |
Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor |
title_sort |
superior detection and classification of ethanol and acetone using 3d ultra-porous γ-fe2o3 nanocubes-based sensor |
publisher |
Elsevier |
publishDate |
2022 |
url |
https://www.sciencedirect.com/science/article/abs/pii/S0925400522003793?via%3Dihub https://dlib.phenikaa-uni.edu.vn/handle/PNK/5904 https://doi.org/10.1016/j.snb.2022.131737 |
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