Crystal Facet Engineering−Photoexcitation−Machine Learning Synergy on Cu 2 O/CuO Heterojunctions for High-Performance Triethylamine Sensing

ACS Sensors 2026

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Authors: Ziqi Gu, Xiaohong Zheng, Zhilei Li, Suyue Ren, Liangbo Bo, Jingwen Pan, Yufeng Liu
DOI: 10.1021/acssensors.5c04660
Cited by: 1
References: 65

Abstract

= 0.9966). This work provides an effective strategy for high-performance TEA detection in complex environments by integrating crystal facet engineering, photoexcitation, and machine learning.

Fields of Study & Subjects

Copper-based nanomaterials and applications Advanced Photocatalysis Techniques Advanced Memory and Neural Computing

Publication details

Journal / source
ACS Sensors
Publisher
American Chemical Society (ACS)
Volume
11
Issue
6
Pages
4500–4513
Publication date
14 May 2026
Language
EN