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Title: 
Superior detection and classification of ethanol and acetone using 3D ultra-porous γ-Fe2O3 nanocubes-based sensor
Authors: 
Ho, Van Minh Hai
Nguyen, Duc Cuong
Mai, Duy Hien
Hoang, Thai Long
Tran, Quy Phuong
Tran, Khoa Dang
Le, Viet Thong
Nguyen, Ngoc Viet
Nguyen,Van Hieu
Issue Date: 
2022
Publisher: 
Elsevier
Abstract: 
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
URI: 
https://www.sciencedirect.com/science/article/abs/pii/S0925400522003793?via%3Dihub
https://dlib.phenikaa-uni.edu.vn/handle/PNK/5760
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