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气体传感器阵列与模式识别：电子鼻传感技术与应用研究进展
Gas sensor arrays and pattern recognition: Progress in electronic nose technology and applications
- 西北大学学报（自然科学版） 2025年55卷第6期 页码：1201-1219
- 作者机构：
1.西安电子科技大学 信息力学与感知工程学院，人工嗅觉陕西省高等学校重点实验室，陕西 西安 710126
2.以色列理工学院化工系，以色列 海法 3200003
3.成都中核高通同位素股份有限公司，四川 成都 610000
4.深圳市比亚迪锂电池有限公司，广东 深圳 518118
- 作者简介：
[ "吴巍炜，西安电子科技大学信息力学与感知工程学院教授，博士生导师，《西北大学学报（自然科学版》青年编委。入选陕西省人才，担任Rare Metal学术编辑、Nano-Micro Letters青年编委、人工嗅觉陕西省高等学校重点实验室主任、陕西省等离子体物理与应用技术重点实验室学术委员会委员、中国科学院合肥物质科学研究院核能安全技术研究所兼职特聘研究员、陕西省化学会理事。在疾病挥发物组学、人工嗅觉疾病诊断、核电池关键元件与系统等领域具有良好的工作积累。目前，在Chemical Review、Nano Letters、ACS Nano、Advanced Functional Materials、Nano Energy、Nano-micro Letters、Advanced Materials、Advanced Healthcare Materials、Applied Physics Reviews、Journal of Materials Chemistry A等期刊上发表论文70余篇，论文引用7 000余次，授权中国发明专利11项，美国发明专利1项。" ]
刘涛平，男，准聘副教授，从事电子鼻智能算法研究，liutaoping@xidian.edu.cn。
- 基金信息：国家自然科学基金青年项目(62501457);陕西省自然科学基金青年项目(2024JC-YBQN-0623)
DOI：10.16152/j.cnki.xdxbzr.2025-06-002
中图分类号： TP212.2;391.4收稿：2025-11-25，
纸质出版：2025-12-25
- 稿件说明：
移动端阅览
吴巍炜, 屈丹瑶, 姜雪, 等. 气体传感器阵列与模式识别：电子鼻传感技术与应用研究进展[J]. 西北大学学报（自然科学版）, 2025,55(6):1201-1219.
WU Weiwei, QU Danyao, JIANG Xue, et al. Gas sensor arrays and pattern recognition: Progress in electronic nose technology and applications[J]. Journal of Northwest University (Natural Science Edition), 2025, 55(6): 1201-1219.
吴巍炜, 屈丹瑶, 姜雪, 等. 气体传感器阵列与模式识别：电子鼻传感技术与应用研究进展[J]. 西北大学学报（自然科学版）, 2025,55(6):1201-1219. DOI： 10.16152/j.cnki.xdxbzr.2025-06-002.
WU Weiwei, QU Danyao, JIANG Xue, et al. Gas sensor arrays and pattern recognition: Progress in electronic nose technology and applications[J]. Journal of Northwest University (Natural Science Edition), 2025, 55(6): 1201-1219. DOI： 10.16152/j.cnki.xdxbzr.2025-06-002.
摘要
电子鼻是一种利用气体传感器阵列结合模式识别算法，对复杂气味进行整体感知与分析的人工嗅觉系统。然而，人工嗅觉相较其他类人感知长期滞后。为此，从体系化视角构建了电子鼻技术的全链条认知框架，围绕以下6个核心内容展开综述：①梳理电子鼻技术发展脉络，厘清各阶段技术特征与演进逻辑；②阐释其工作原理与系统架构，明确各功能模块协同机制；③聚焦敏感元件这一硬件核心，从响应机理、材料特性及结构设计展开解析；④剖析传统数据处理与模式识别方法与前沿智能算法的差异、适用性及发展趋势；⑤结合典型领域实证案例，论述技术落地现状与挑战；⑥探讨前沿研究方向，分析产业化瓶颈并提出未来路径。当前电子鼻技术已从机械鼻、阵列式化学传感器演进至商用系统，其中材料的纳米化与算法的智能化显著提升了性能，并在疾病诊断、农业监测、公共安全及能源等领域的应用得到广泛探索。未来电子鼻技术的突破将不再依赖单一层面的局部优化，而在于构建多层协同的体系化架构。综述构建了电子鼻技术的完整知识框架，可为电子鼻传感技术研究及其转化和应用提供参考。
Abstract
An electronic nose (e-nose) is an artificial olfaction system that employs an array of gas sensors combined with pattern recognition algorithms to achieve holistic perception and analysis of complex odors. Compared with other human-like sensory modalities
artificial olfaction has long lagged. Accordingly
this review constructs a comprehensive
system-level framework of electronic nose technology from a holistic perspective as follows: ① tracing the development trajectory of electronic nose technology and clarifying the characteristics and evolution of each stage; ② explaining its working principles and system architecture
highlighting the coordination among functional modules; ③ analyzing the sensing elementsthrough their response mechanisms
material properties
and structural design; ④ comparing traditional data processing and pattern recognition methods with advanced intelligent algorithms in terms of differences
applicability
and development trends; ⑤ summarizing practical deployment and challenges based on representative application cases; and ⑥ discussing frontier research directions and identifying industrial bottlenecks. E-nose technology has progressed from mechanical devices and array-based chemical sensors to commercial systems
with material nanostructuring and intelligent algorithms significantly enhancing performance. These advances have enabled applications in disease diagnosis
agriculture
public safety
and energy. Future breakthroughs will depend on coordinated innovations across sensing materials
device design
intelligent algorithms
and system architecture. This review provides a comprehensive
holistic reference for researchers and practitioners
guiding both the study and practical deployment of electronic nose systems.
关键词
Keywords
references
WANG J W , WANG C , CAI P Q , et al . Artificial sense technology: Emulating and extending biological senses [J ] . ACS Nano , 2021 , 15 ( 12 ): 18671 - 18678 .
LONG Z H , ZHOU Y , DING Y C , et al . Biomimetic optoelectronics with nanomaterials for artificial vision [J ] . Nature Reviews Materials , 2025 , 10 ( 2 ): 128 - 146 .
HONG S J , LEE Y R , BAG A , et al . Bio-inspired artificial mechanoreceptors with built-in synaptic functions for intelligent tactile skin [J ] . Nature Materials , 2025 , 24 ( 7 ): 1100 - 1108 .
CLARK G M . The multichannel cochlear implant for severe-to-profound hearing loss [J ] . Nature Medicine , 2013 , 19 ( 10 ): 1236 - 1239 .
GAO F P , LIU C X , ZHANG L C , et al . Wearable and flexible electrochemical sensors for sweat analysis: A review [J ] . Microsystems & Nanoengineering , 2023 , 9 : 1 .
HU W W , WAN L T , JIAN Y Y , et al . Electronic noses: From advanced materials to sensors aided with data processing [J ] . Advanced Materials Technologies , 2019 , 4 ( 2 ): 1800488 .
MONCRIEFF R W . An instrument for measuring and classifying odors [J ] . Journal of Applied Physiology , 1961 , 16 ( 4 ): 742 - 749 .
WILKENS W F , HARTMAN J D . An electronic analog for the olfactory processes a [J ] . Journal of Food Science , 1964 , 29 ( 3 ): 372 - 378 .
BEETS M G L . Structure-activity relationship in human chemoreception [M ] . London : Applied Science Publishers , 1978 : 13 - 28 .
SAUERBREY G . Verwendung von Schwingquarzen zur Wägung dünner Schichten und zur Mikrowägung [J ] . Zeitschrift Für Physik , 1959 , 155 ( 2 ): 206 - 222 .
PERSAUD K , DODD G . Analysis of discrimination mechanisms in the mammalian olfactory system using a model nose [J ] . Nature , 1982 , 299 ( 5881 ): 352 - 355 .
IKEGAMI A , KANEYASU M . Olfactory detection using integrated sensors [C ] // 1985 Proceedings of the 3rd International Conference on Solid-State Sensors and Actuators and Microsystems . June 11-June 14, 1985 . Philadelphia, USA . IEEE , 1985 : 136 - 139 .
TAN L D , FENG Z H , ZHENG H L , et al . Development trend of electronic nose technology in closed cabins gas detection: A review [J ] . Applied Sciences , 2022 , 12 ( 18 ): 9326 .
GARDNER J W , BARTLETT P N . Sensors and Sensory Systems for an Electronic Nose [M ] . Dordrecht : Springer Netherlands , 1992 : vii - viii .
HATFIELD J V , NEAVES P , HICKS P J . Towards an integrated electronic nose using conducting polymer sensors [J ] . Sensors and Actuators B: Chemical , 1994 , 18 ( 1/2/3 ): 221 - 228 .
GARDNER J W , BARTLETT P N . A brief history of electronic noses [J ] . Sensors and Actuators B: Chemical , 1994 , 18 ( 1/2/3 ), 210 - 211 .
GÖPEL W . Chemical imaging: I. Concepts and visions for electronic and bioelectronic noses1Presented in part as plenary talk at EUROSENSORS 1997 (Warsaw, PL).1 [J ] . Sensors and Actuators B: Chemical , 1998 , 52 ( 1/2 ): 125 - 142 .
PENG G , TISCH U , ADAMS O , et al . Diagnosing lung cancer in exhaled breath using gold nanoparticles [J ] . Nature Nanotechnology , 2009 , 4 ( 10 ): 669 - 673 .
ZHAO Y , HE X L , LI J P , et al . Enhanced gas sensing properties of aligned porous SnO 2 nanofibers [J ] . Chinese Physics Letters , 2012 , 29 ( 7 ): 070701 .
MA J H , REN Y , ZHOU X R , et al . Pt nanoparticles sensitized ordered mesoporous WO 3 semiconductor: Gas sensing performance and mechanism study [J ] . Advanced Functional Materials , 2018 , 28 ( 6 ): 1705268 .
ASSAD O , HAICK H . Chemically sensitive Field Effect Transistors of oxide-free silicon nanowires-towards detection of volatile biomarkers of cancer [C ] // 2008 IEEE International Symposium on Industrial Electronics . June 30-July 2, 2008 . Cambridge, UK . IEEE , 2008 : 2040 - 2044 .
YAO M S , TANG W X , WANG G E , et al . MOF thin film-coated metal oxide nanowire array: Significantly improved chemiresistor sensor performance [J ] . Advanced Materials , 2016 , 28 ( 26 ): 5229 - 5234 .
LIU Q J , YE W W , XIAO L D , et al . Extracellular potentials recording in intact olfactory epithelium by microelectrode array for a bioelectronic nose [J ] . Biosensors and Bioelectronics , 2010 , 25 ( 10 ): 2212 - 2217 .
KIM T H , LEE S H , LEE J , et al . Single-carbon-atomic-resolution detection of odorant molecules using a human olfactory receptor-based bioelectronic nose [J ] . Advanced Materials , 2009 , 21 ( 1 ): 91 - 94 .
ZHU Y H , YUAN H , XU J Q , et al . Highly stable and sensitive humidity sensors based on quartz crystal microbalance coated with hexagonal lamelliform monodisperse mesoporous silica SBA-15 thin film [J ] . Sensors and Actuators B: Chemical , 2010 , 144 ( 1 ): 164 - 169 .
MIURA N , NAKATOU M , ZHUIYKOV S . Impedancemetric gas sensor based on zirconia solid electrolyte and oxide sensing electrode for detecting total NO at high temperature [J ] . Sensors and Actuators B: Chemical , 2003 , 93 ( 1/2/3 ): 221 - 228 .
RÖCK F , BARSAN N , WEIMAR U . Electronic nose: Current status and future trends [J ] . Chemical Reviews , 2008 , 108 ( 2 ): 705 - 725 .
LÄNGKVIST M , LOUTFI A . Unsupervised feature learning for electronic nose data applied to bacteria identification in blood [C ] // NIPS Workshop on Deep Learning and Unsupervised Feature Learning . Granada, Spain , December 16-17, 2011 . Red Hook : Curran Associates, Inc. , 2011 .
VERGARA A , VEMBU S , AYHAN T , et al . Chemical gas sensor drift compensation using classifier ensembles [J ] . Sensors and Actuators B: Chemical , 2012 , 166/167 : 320 - 329 .
ZHANG L , ZHANG D . Domain adaptation extreme learning machines for drift compensation in E-nose systems [J ] . IEEE Transactions on Instrumentation and Measurement , 2015 , 64 ( 7 ): 1790 - 1801 .
ZHANG L , TIAN F C , ZHANG D . Electronic Nose: Algorithmic Challenges [M ] . Singapore : Springer Singapore , 2018 : 11 - 20 .
LIU T P , GUO L H , WANG M , et al . Review on algorithm design in electronic noses: Challenges, status, and trends [J ] . Intelligent Computing , 2023 , 2 : 12 .
LIU H X , LI Q , GU Y . A multi-task learning framework for gas detection and concentration estimation [J ] . Neurocomputing , 2020 , 416 : 28 - 37 .
JIAN Y Y , ZHANG N , BI Y Z , et al . TC-sniffer: A transformer-CNN bibranch framework leveraging auxiliary VOCs for few-shot UBC diagnosis via electronic noses [J ] . ACS Sensors , 2025 , 10 ( 1 ): 213 - 224 .
QU D Y , LIU T P , CHENG Y Y , et al . Volatilomics in diseases odour and electronic nose diagnosis [J ] . TrAC Trends in Analytical Chemistry , 2025 , 193 : 118，440 .
LIU T Q , ZHU Y J , GUO L H , et al . Controlling fluidic behavior for ultra-sensitive volatile sensing [J ] . Applied Physics Reviews , 2023 , 10 ( 2 ): 021408 .
CHEN H , HUO D X , ZHANG J L . Gas recognition in E-nose system: A review [J ] . IEEE Transactions on Biomedical Circuits and Systems , 2022 , 16 ( 2 ): 169 - 184 .
OU Y C , WANG B , XU N N , et al . Tandem electric-fields prolong energetic hot electrons lifetime for ultra-fast and stable NO 2 detection [J ] . Advanced Materials , 2024 , 36 ( 30 ): 2403215 .
JIANG X , QU D Y , ZHANG J N , et al . Confronting pressure and humidity limitations in gold nanoparticle sensors array for enhancing electronic nose technology in real-world applications [J ] . Rare Metals , 2025 , 44 ( 11 ): 8789 - 8801 .
KOO W T , QIAO S P , OGATA A F , et al . Accelerating palladium nanowire H 2 sensors using engineered nanofiltration [J ] . ACS Nano , 2017 , 11 ( 9 ): 9276 - 9285 .
MAZUMDER J T , JHA R K , KIM H W , et al . Capacitive toxic gas sensors based on oxide composites: A review [J ] . IEEE Sensors Journal , 2023 , 23 ( 16 ): 17842 - 17853 .
YUAN H Y , LI N X , FAN W D , et al . Metal-organic framework based gas sensors [J ] . Advanced Science , 2022 , 9 ( 6 ): 2104374 .
THANGAVEL S , PONNUSAMY S . Application of 3D printed polymer composite as capacitive sensor [J ] . Sensor Review , 2020 , 40 ( 1 ): 54 - 61 .
ZHANG C C , CHEN P L , HU W P . Organic field-effect transistor-based gas sensors [J ] . Chemical Society Reviews , 2015 , 44 ( 8 ): 2087 - 2107 .
WANG B , HUYNH T P , WU W W , et al . A highly sensitive diketopyrrolopyrrole-based ambipolar transistor for selective detection and discrimination of xylene isomers [J ] . Advanced Materials , 2016 , 28 ( 21 ): 4012 - 4018 .
PAGHI A , MARIANI S , BARILLARO G . 1D and 2D field effect transistors in gas sensing: A comprehensive review [J ] . Small , 2023 , 19 ( 15 ): 2206100 .
MAO S , CHANG J B , PU H H , et al . Two-dimensional nanomaterial-based field-effect transistors for chemical and biological sensing [J ] . Chemical Society Reviews , 2017 , 46 ( 22 ): 6872 - 6904 .
QU D Y , CHENG B L , SHAO X Y , et al . Advances in metals and metal hybrids-based gas sensors and their applications [J ] . Rare Metals , 2025 .
LIANG H Q , ZHANG X , SUN H H , et al . Light-regulated electrochemical sensor array for efficiently discriminating hazardous gases [J ] . ACS Sensors , 2017 , 2 ( 10 ): 1467 - 1473 .
HUANG Z R , TANG Q Q , HE J , et al . High-temperature CO 2 Sensor with second-level response for diesel engine exhaust gas detection applications [J ] . ACS Sensors , 2025 , 10 ( 10 ): 8078 - 8089 .
WU Z P , ZHANG X D , CHEN L N , et al . Ultra-low-power, extremely stable, highly linear-response thermal conductivity sensor based on a suspended device with single bare Pt nanowire [J ] . ACS Sensors , 2024 , 9 ( 9 ): 4721 - 4730 .
OGAWA S , FUJIMOTO T , KANAI T , et al . Hydrogen storage property of the Pd nanoparticle with clean surfaces studied by QCM [J ] . E-Journal of Surface Science and Nanotechnology , 2015 , 13 : 343 - 346 .
SUN S Q , ZHAO C , ZHANG Z H , et al . Highly selective QCM sensor based on functionalized hierarchical hollow TiO 2 nanospheres for detecting ppb-level 3-hydroxy-2-butanone biomarker at room temperature [J ] . Chinese Chemical Letters , 2025 , 36 ( 5 ): 109939 .
CHENG G L , LI Y Z , REN L , et al . A QCM gas sensor based on Ce-MOF-808 and graphene oxide nanocomposite for rapid and sensitive detection of trimethylamine [J ] . Journal of Food Composition and Analysis , 2025 , 148 : 108604 .
YAN J , GUO X Z , DUAN S K , et al . Electronic nose feature extraction methods: A review [J ] . Sensors , 2015 , 15 ( 11 ): 27804 - 27831 .
SHAKYA P , KENNEDY E , ROSE C , et al . High-dimensional time series feature extraction for low-cost machine olfaction [J ] . IEEE Sensors Journal , 2020 , 21 ( 3 ): 2495 - 2504 .
LIU T P , ZHANG W T , WANG L , et al . Numerical differentiation from noisy signals: A kernel regularization method to improve transient-state features for the electronic nose [J ] . IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2024 , 54 ( 6 ): 3497 - 3511 .
YOO Y , KIM H I , CHOI S I . Robust classification of largely corrupted electronic nose data using deep neural networks [J ] . IEEE Sensors Journal , 2021 , 21 ( 4 ): 5052 - 5059 .
EKLÖV T , MÅRTENSSON P , LUNDSTRÖM I . Enhanced selectivity of MOSFET gas sensors by systematical analysis of transient parameters [J ] . Analytica Chimica Acta , 1997 , 353 ( 2/3 ): 291 - 300 .
LIU T P , ZHANG W T , YE L , et al . A novel multi-odour identification by electronic nose using non-parametric modelling-based feature extraction and time-series classification [J ] . Sensors and Actuators B: Chemical , 2019 , 298 : 126690 .
LIU T P , ZHANG W T , LI J , et al . A multiscale wavelet kernel regularization-based feature extraction method for electronic nose [J ] . IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2022 , 52 ( 11 ): 7078 - 7089 .
DISTANTE C , LEO M , SICILIANO P , et al . On the study of feature extraction methods for an electronic nose [J ] . Sensors and Actuators B: Chemical , 2002 , 87 ( 2 ): 274 - 288 .
HE A X , YU J , WEI G F , et al . Short-time Fourier transform and decision tree-based pattern recognition for gas identification using temperature modulated microhotplate gas sensors [J ] . Journal of Sensors , 2016 , 2016 : 7603931 .
WANG X R , LIZIER J T , NOWOTNY T , et al . Feature selection for chemical sensor arrays using mutual information [J ] . PLoS One , 2014 , 9 ( 3 ): e89840 .
QIAN J H , LU M C , TIAN F C , et al . Array optimization based on weighted and Hilbert-Schmidt schemes of multisensor detection system [J ] . IEEE Transactions on Industrial Informatics , 2023 , 19 ( 5 ): 7044 - 7054 .
SUN H , TIAN F C , LIANG Z F , et al . Sensor array optimization of electronic nose for detection of bacteria in wound infection [J ] . IEEE Transactions on Industrial Electronics , 2017 , 64 ( 9 ): 7350 - 7358 .
PARDO M , KWONG L G , SBERVEGLIERI G , et al . Data analysis for a hybrid sensor array [J ] . Sensors and Actuators B: Chemical , 2005 , 106 ( 1 ): 136 - 143 .
GARDNER J W , BOILOT P , HINES E L . Enhancing electronic nose performance by sensor selection using a new integer-based genetic algorithm approach [J ] . Sensors and Actuators B: Chemical , 2005 , 106 ( 1 ): 114 - 121 .
LIU T P , ZHANG W T , MCLEAN P , et al . Electronic nose-based odor classification using genetic algorithms and fuzzy support vector machines [J ] . International Journal of Fuzzy Systems , 2018 , 20 ( 4 ): 1309 - 1320 .
YAN K , ZHANG D . Feature selection and analysis on correlated gas sensor data with recursive feature elimination [J ] . Sensors and Actuators B: Chemical , 2015 , 212 : 353 - 363 .
JIAN Y Y , ZHANG N , LIU T P , et al . Artificially intelligent olfaction for fast and noninvasive diagnosis of bladder cancer from urine [J ] . ACS Sensors , 2022 , 7 ( 6 ): 1720 - 1731 .
NGUYEN Q D N , LE H V A , NAKANO T , et al . Wine quality assessment through lightweight deep learning: integrating 1D-CNN and LSTM for analyzing electronic nose VOCs signals [J/OL ] . ( 2024-03-01 ) [ 2025-12-23 ] . https://www.emerald.com/aci/article/doi/10.1108/ACI-10-2023-0098/1250224/Wine-quality-assessment-through-lightweight-deep https://www.emerald.com/aci/article/doi/10.1108/ACI-10-2023-0098/1250224/Wine-quality-assessment-through-lightweight-deep .
MA X , WU F , YAN J , et al . TF-TCN: A time-frequency combined gas concentration prediction model for E-nose data [J ] . Sensors and Actuators A: Physical , 2024 , 376 : 115654 .
JIAN Y Y , BI Y Z , FAN J H , et al . Urinary bladder cancer screening with electronic noses based on few-shot contrastive representation learning and open-set recognition [J ] . IEEE Sensors Journal , 2025 , 25 ( 1 ): 125 - 134 .
YAN K , ZHANG D . Correcting instrumental variation and time-varying drift: A transfer learning approach with autoencoders [J ] . IEEE Transactions on Instrumentation and Measurement , 2016 , 65 ( 9 ): 2012 - 2022 .
CHENG Y C , CHOU T I , CHIU S W , et al . A concentration-based drift calibration transfer learning method for gas sensor array data [J ] . IEEE Sensors Letters , 2020 , 4 ( 10 ): 1 - 4 .
FANG C , LI H Y , LI L , et al . Smart electronic nose enabled by an all-feature olfactory algorithm [J ] . Advanced Intelligent Systems , 2022 , 4 ( 7 ): 2270032 .
YANG Y , LIU H X , GU Y . A model transfer learning framework with back-propagation neural network for wine and Chinese liquor detection by electronic nose [J ] . IEEE Access , 2020 , 8 : 105278 - 105285 .
LIU C , MIYAUCHI H , HAYASHI K . DeepSniffer: A meta-learning-based chemiresistive odor sensor for recognition and classification of aroma oils [J ] . Sensors and Actuators B: Chemical , 2022 , 351 : 130960 .
UR REHMAN A , BERMAK A . Drift-insensitive features for learning artificial olfaction in E-nose system [J ] . IEEE Sensors Journal , 2018 , 18 ( 17 ): 7173 - 7182 .
FONOLLOSA J , FERNÁNDEZ L , GUTIÉRREZ-GÁLVEZ A , et al . Calibration transfer and drift counteraction in chemical sensor arrays using Direct Standardization [J ] . Sensors and Actuators B: Chemical , 2016 , 236 : 1044 - 1053 .
ARTURSSON T , EKLÖV T , LUNDSTRÖM I , et al . Drift correction for gas sensors using multivariate methods [J ] . Journal of Chemometrics , 2000 , 14 ( 5/6 ): 711 - 723 .
ZHANG L , ZHANG D . Efficient solutions for discreteness, drift, and disturbance (3D) in electronic olfaction [J ] . IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2018 , 48 ( 2 ): 242 - 254 .
ZHANG L , LIU Y , HE Z W , et al . Anti-drift in E-nose: A subspace projection approach with drift reduction [J ] . Sensors and Actuators B: Chemical , 2017 , 253 : 407 - 417 .
LEON-MEDINA J X , PINEDA-MUNOZ W A , BURGOS D A T . Joint distribution adaptation for drift correction in electronic nose type sensor arrays [J ] . IEEE Access , 2020 , 8 : 134413 - 134421 .
YAN K , KOU L , ZHANG D . Learning domain-invariant subspace using domain features and independence maximization [J ] . IEEE Transactions on Cybernetics , 2018 , 48 ( 1 ): 288 - 299 .
LIANG Z F , XUE Q , TIAN F C , et al . A sparse reconstruction domain transfer method for interference suppression in artificial olfactory system [J ] . IEEE Sensors Journal , 2022 , 22 ( 7 ): 6717 - 6730 .
LIU Q H , LI X , YE M , et al . Drift compensation for electronic nose by semi-supervised domain adaption [J ] . IEEE Sensors Journal , 2014 , 14 ( 3 ): 657 - 665 .
YAN K , ZHANG D . Calibration transfer and drift compensation of e-noses via coupled task learning [J ] . Sensors and Actuators B: Chemical , 2016 , 225 : 288 - 297 .
WEI G F , XU Y , LV X L , et al . An adaptive drift compensation method based on integrated dual-channel feature fusion for electronic noses [J ] . IEEE Sensors Journal , 2024 , 24 ( 16 ): 26814 - 26824 .
LI L , XIANG S H , HAN M Y , et al . Performance improvement of multisensor systems using autocompensation strategy-based LSTM [J ] . IEEE Transactions on Instrumentation and Measurement , 2024 , 73 : 1 - 11 .
CHEN X , YI L , LIU R . FEDA: A nonlinear subspace projection approach for electronic nose data classification [J ] . IEEE Transactions on Instrumentation and Measurement , 2023 , 72 : 1 - 11 .
PAULING L , ROBINSON A B , TERANISHI R , et al . Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography [J ] . Proceedings of the National Academy of Sciences of the United States of America , 1971 , 68 ( 10 ): 2374 - 2376 .
HU W W , WU W W , JIAN Y Y , et al . Volatolomics in healthcare and its advanced detection technology [J ] . Nano Research , 2022 , 15 ( 9 ): 8185 - 8213 .
SHEHADA N , BRÖNSTRUP G , FUNKA K , et al . Ultrasensitive silicon nanowire for real-world gas sensing: Noninvasive diagnosis of cancer from breath volatolome [J ] . Nano Letters , 2015 , 15 ( 2 ): 1288 - 1295 .
NAKHLEH M K , AMAL H , JERIES R , et al . Diagnosis and classification of 17 diseases from 1404 subjects via pattern analysis of exhaled molecules [J ] . ACS Nano , 2017 , 11 ( 1 ): 112 - 125 .
JIN H , XUE C L , YANG F , et al . Unlocking pan-cancer detection with phenyl-β-d-glucuronide like exogenous agent and AI-driven induced breath analysis for non-invasive early discovery [J/OL ] . ( 2024-10-31 ) [ 2025-12-18 ] . https://www.researchsquare.com/article/rs-4976442/v1 https://www.researchsquare.com/article/rs-4976442/v1 .
WESOŁY M , PRZEWODOWSKI W , CIOSEK-SKIBI<inline-formula><alternatives><inline-graphic specific-use="print" xlink:href="media/1000-274X-2025-06-1201-E001.jpg" /><inline-graphic specific-use="big" xlink:href="alternativeImage/1000-274X-2025-06-1201-E001.jpg" /><inline-graphic specific-use="small" xlink:href="alternativeImage/1000-274X-2025-06-1201-E001c.jpg" /></alternatives></inline-formula>SKA P . Electronic noses and electronic tongues for the agricultural purposes [J ] . TrAC Trends in Analytical Chemistry , 2023 , 164 : 117082 .
GGÓMEZ A H , WANG J , HU G X , et al . Electronic nose technique potential monitoring mandarin maturity [J ] . Sensors and Actuators B: Chemical , 2006 , 113 ( 1 ): 347 - 353 .
KIKI M P A F , AHOUANDJINOU S A R M , ASSOGBA K M , et al . An E-nose using metal oxide semiconductor sensors array to recognize the odors of fall armyworm pest for its early detection in the farm [C ] // Innovations and Interdisciplinary Solutions for Underserved Areas . Cham : Springer , 2022 : 69 - 81 .
LUAN X Y , KONG C , YAO Z W , et al . Hierarchical electronic nose detection and assessment technology for the reusage of land contaminated with petroleum hydrocarbons [J ] . Sensors and Actuators B: Chemical , 2023 , 390 : 133940 .
PIŁAT-ROẐEK M , DZIADOSZ M , MAJEREK D , et al . Rapid method of wastewater classification by electronic nose for performance evaluation of bioreactors with activated sludge [J ] . Sensors , 2023 , 23 ( 20 ): 8578 .
MA Z , CHEN P , CHENG W , et al . Highly sensitive, printable nanostructured conductive polymer wireless sensor for food spoilage detection [J ] . Nano Letters , 2018 , 18 ( 7 ): 4570 - 4575 .
WANG D W , LI Z W , ZHOU J , et al . Simultaneous detection and removal of formaldehyde at room temperature: Janus Au@ZnO@ZIF-8 nanoparticles [J ] . Nano-Micro Letters , 2017 , 10 ( 1 ): 4 .
LICHTENSTEIN A , HAVIVI E , SHACHAM R , et al . Supersensitive fingerprinting of explosives by chemically modified nanosensors arrays [J ] . Nature Communications , 2014 , 5 : 4195 .
TANG M C , ZHANG D Z , SUN Y H , et al . Ultrasensitive detection and sensitivity mechanism of SO 2 F 2 in SF 6 decomposition product based on TiO 2 -NiS heterojunction [J ] . Sensors and Actuators B: Chemical , 2024 , 417 : 136062 .
WANG Z , ZHU L , LIU J W , et al . Gas sensing technology for the detection and early warning of battery thermal runaway: A review [J ] . Energy & Fuels , 2022 , 36 ( 12 ): 6038 - 6057 .
LV W , YANG J , XU Q , et al . Wide-range and high-accuracy wireless sensor with self-humidity compensation for real-time ammonia monitoring [J ] . Nature Communications , 2024 , 15 ( 1 ): 6936 .
AZZARELLI J M , MIRICA K A , RAVNSBÆK J B , et al . Wireless gas detection with a smartphone via rf communication [J ] . Proceedings of the National Academy of Sciences , 2014 , 111 ( 51 ): 18162 - 18166 .
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