{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T15:32:27Z","timestamp":1767108747321,"version":"build-2065373602"},"reference-count":51,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:00:00Z","timestamp":1643846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A fully integrated sensor array assisted by pattern recognition algorithm has been a primary candidate for the assessment of complex vapor mixtures based on their chemical fingerprints. Diverse prototypes of electronic nose systems consisting of a multisensory device and a post processing engine have been developed. However, their precision and validity in recognizing chemical vapors are often limited by the collected database and applied classifiers. Here, we present a novel way of preparing the database and distinguishing chemical vapor mixtures with small data acquisition for chemical vapors and their mixtures of interest. The database for individual vapor analytes is expanded and the one for their mixtures is prepared in the first-order approximation. Recognition of individual target vapors of NO2, HCHO, and NH3 and their mixtures was evaluated by applying the support vector machine (SVM) classifier in different conditions of temperature and humidity. The suggested method demonstrated the recognition accuracy of 95.24%. The suggested method can pave a way to analyze gas mixtures in a variety of industrial and safety applications.<\/jats:p>","DOI":"10.3390\/s22031169","type":"journal-article","created":{"date-parts":[[2022,2,6]],"date-time":"2022-02-06T20:40:18Z","timestamp":1644180018000},"page":"1169","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Identification of Chemical Vapor Mixture Assisted by Artificially Extended Database for Environmental Monitoring"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1232-5203","authenticated-orcid":false,"given":"Hi Gyu","family":"Moon","sequence":"first","affiliation":[{"name":"Center for Ecological Risk Assessment, Korea Institute of Toxicology (KIT), Jinju 52834, Korea"}]},{"given":"Youngmo","family":"Jung","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]},{"given":"Beomju","family":"Shin","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1994-1540","authenticated-orcid":false,"given":"Donggeun","family":"Lee","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]},{"given":"Kayoung","family":"Kim","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]},{"given":"Deok Ha","family":"Woo","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]},{"given":"Seok","family":"Lee","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]},{"given":"Sooyeon","family":"Kim","sequence":"additional","affiliation":[{"name":"Center for Ecological Risk Assessment, Korea Institute of Toxicology (KIT), Jinju 52834, Korea"}]},{"given":"Chong-Yun","family":"Kang","sequence":"additional","affiliation":[{"name":"Center for Electronic Materials, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"},{"name":"KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Korea"}]},{"given":"Taikjin","family":"Lee","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9806-5122","authenticated-orcid":false,"given":"Chulki","family":"Kim","sequence":"additional","affiliation":[{"name":"Sensor System Research Center, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3986","DOI":"10.1021\/acsami.7b16859","article-title":"Multifunctional Sensor Based on Porous Carbon Derived from Metal\u2013Organic Frameworks for Real Time Health Monitoring","volume":"10","author":"Zhao","year":"2018","journal-title":"ACS Appl. Mater. Interfaces"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Dincer, C., Bruch, R., Costa-Rama, E., Fern\u00e1ndez-Abedul, M.T., Merko\u00e7i, A., Manz, A., Urban, G.A., and G\u00fcder, F. (2019). Disposable Sensors in Diagnostics, Food, and Environmental Monitoring. Adv. Mater., 31.","DOI":"10.1002\/adma.201806739"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4675","DOI":"10.1039\/C8CS90066C","article-title":"Nanomaterials Properties Tuned by Their Environment: Integrating Supramolecular Concepts into Sensing Devices","volume":"47","author":"Biscarini","year":"2018","journal-title":"Chem. Soc. Rev."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3964","DOI":"10.1021\/acsnano.8b01557","article-title":"Skin-Inspired Hierarchical Polymer Architectures with Gradient Stiffness for Spacer-Free, Ultrathin, and Highly Sensitive Triboelectric Sensors","volume":"12","author":"Ha","year":"2018","journal-title":"ACS Nano"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1038\/s41565-018-0209-9","article-title":"Nanosensors for Water Quality Monitoring","volume":"13","author":"Vikesland","year":"2018","journal-title":"Nat. Nanotechnol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1146\/annurev-publhealth-040617-013702","article-title":"From Crowdsourcing to Extreme Citizen Science: Participatory Research for Environmental Health","volume":"39","author":"English","year":"2018","journal-title":"Annu. Rev. Public Health"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Nyarku, M., Mazaheri, M., Jayaratne, R., Dunbabin, M., Rahman, M.M., Uhde, E., and Morawska, L. (2018). Mobile Phones as Monitors of Personal Exposure to Air Pollution: Is This the Future?. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0193150"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3461","DOI":"10.1038\/s41598-018-19939-1","article-title":"Acute Effects of Air Pollution on Respiratory Disease Mortalities and Outpatients in Southeastern China","volume":"8","author":"Mo","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s10653-015-9720-1","article-title":"Air Pollution and Public Health: Emerging Hazards and Improved Understanding of Risk","volume":"37","author":"Kelly","year":"2015","journal-title":"Environ. Geochem. Health"},{"key":"ref_10","first-page":"266","article-title":"Web Based Air Pollution Monitoring System (Air Pollution Monitoring Using Smart Phone)","volume":"5","author":"Khodve","year":"2016","journal-title":"Int. J. Sci. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2161","DOI":"10.1111\/ijfs.14392","article-title":"Application of an Electronic Nose for Determination of Pre-pressing Treatment of Rapeseed based on The Analysis of Volatile Compounds Contained in Pressed Oil","volume":"5","author":"Rusinek","year":"2020","journal-title":"Int. J. Food Sci. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kim, J.-H., Mirzaei, A., Kim, H.W., Kim, H.J., Vuong, P.Q., and Kim, S.S. (2019). A Novel X-ray Radiation Sensor based on Networked SnO2 Nanowires. Appl. Sci., 9.","DOI":"10.3390\/app9224878"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Marek, G., Dobrza\u0144ski, B., Oniszczuk, T., Combrzy\u0144ski, M., \u0106wik\u0142a, D., and Rusinek, R. (2020). Detection and Differentiation of Volatile Compound Profiles in Roasted Coffee Arabica Beans from Different Countries using an Electronic Nose and GC-MS. Sensors, 20.","DOI":"10.3390\/s20072124"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Garbacz, M., Malec, A., Saternus, S.D., Suchorab, Z., Guz, \u0141., and \u0141ag\u00f3d, G. (2020). Methods for Early Detection of Microbiological Infestation of Buildings based on Gas Sensor Technologies. Chemosensors, 8.","DOI":"10.3390\/chemosensors8010007"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Rusinek, R., Jele\u0144, H., Tobo\u0142a, U.M., Molenda, M., and Gancarz, M. (2020). Influence of Changes in The Level of Volatile Compounds Emitted During Rapeseed Quality Degradation on the Reaction of MOS Type Sensor-Array. Sensors, 20.","DOI":"10.3390\/s20113135"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Slimani, S., Bultel, E., Cubizolle, T., Herrier, C., Rousselle, T., and Livache, T. (2020). Opto-electronic Nose Coupled to a Silicon Micro Pre-concentrator Device for Selective Sensing of Flavored Waters. Chemosensors, 8.","DOI":"10.3390\/chemosensors8030060"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"13780","DOI":"10.1021\/jacs.5b09600","article-title":"Chemiresistive Sensor Arrays from Conductive 2D Metal\u2013Organic Frameworks","volume":"137","author":"Campbell","year":"2015","journal-title":"J. Am. Chem. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.snb.2017.10.153","article-title":"All Villi-Like Metal Oxide Nanostructures-Based Chemiresistive Electronic Nose for an Exhaled Breath Analyzer","volume":"257","author":"Moon","year":"2018","journal-title":"Sens. Actuators B"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Nasiri, N., and Clarke, C. (2019). Nanostructured Chemiresistive Gas Sensors for Medical Applications. Sensors, 19.","DOI":"10.3390\/s19030462"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Liu, B., Luo, Y., Li, K., Wang, H., Gao, L., and Duan, G. (2019). Room-Temperature NO2 Gas Sensing with Ultra-Sensitivity Activated by Ultraviolet Light Based on SnO2 Monolayer Array Film. Adv. Mater. Interface, 6.","DOI":"10.1002\/admi.201900376"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Nazemi, H., Joseph, A., Park, J., and Emadi, A. (2019). Advanced Micro- and Nano-Gas Sensor Technology: A Review. Sensors, 19.","DOI":"10.3390\/s19061285"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"34683","DOI":"10.1021\/acsami.8b08050","article-title":"Handwriting Method for Low-Cost Gas Sensors","volume":"10","author":"Loghin","year":"2018","journal-title":"ACS Appl. Mater. Interfaces"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Szulczy\u0144ski, B., Wasilewski, T., Wojnowski, W., Majchrzak, T., Dymerski, T., Namie\u015bnik, J., and G\u0119bicki, J. (2017). Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odor Nuisance in a Vicinity of Municipal Processing Plants. Sensors, 17.","DOI":"10.3390\/s17112671"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"5099","DOI":"10.3390\/s90705099","article-title":"Applications and Advances in Electronic-Nose Technologies","volume":"9","author":"Wilson","year":"2009","journal-title":"Sensors"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5129","DOI":"10.1016\/j.watres.2010.06.013","article-title":"Monitoring Techniques for Odour Abatement Assessment","volume":"44","author":"Sivret","year":"2010","journal-title":"Water Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2432","DOI":"10.1021\/acssensors.8b00987","article-title":"Ionic Liquid-Carbon Nanotube Sensor Arrays for Human Breath Related Volatile Organic Compounds","volume":"3","author":"Park","year":"2018","journal-title":"ACS Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5311","DOI":"10.1039\/C7CS00007C","article-title":"Toward High Value Sensing: Monolayer-Protected Metal Nanoparticles in Multivariable Gas and Vapor Sensors","volume":"46","author":"Potyrailo","year":"2017","journal-title":"Chem. Soc. Rev."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"5057","DOI":"10.1021\/acs.nanolett.8b01866","article-title":"Temperature-Dependent Gas Mixture Permeation and Separation through Suspended Nanoporous Single-Layer Graphene Membranes","volume":"18","author":"Yuan","year":"2018","journal-title":"Nano Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"4815","DOI":"10.1021\/acs.analchem.8b00273","article-title":"Conjugated Polymer Nanoparticles Based Fluorescent Electronic Nose for the Identification of Volatile Compounds","volume":"90","author":"Zhao","year":"2018","journal-title":"Anal. Chem."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Wang, J., Bryant-Genevier, J., Nu\u00f1overo, N., Zhang, C., Kraay, B., Zhan, C., Scholten, K., Nidetz, R., Buggaveeti, S., and Zellers, E.T. (2018). Compact Prototype Microfabricated Gas Chromatographic Analyzer for Autonomous Determinations of VOC Mixtures at Typical Workplace Concentrations. Microsyst. Nanoeng., 4.","DOI":"10.1038\/micronano.2017.101"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/J.ENG.2016.04.018","article-title":"Heading toward Artificial Intelligence 2.0","volume":"2","author":"Pan","year":"2016","journal-title":"Engineering"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.eng.2018.01.002","article-title":"Toward New-Generation Intelligent Manufacturing","volume":"4","author":"Zhou","year":"2018","journal-title":"Engineering"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.comnet.2017.06.013","article-title":"The role of big data analytics in Internet of Things","volume":"129","author":"Ahmed","year":"2017","journal-title":"Comput. Netw."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1039\/C8ME00097B","article-title":"Field-Effect Transistor Array Modified by a Stationary Phase to Generate Informative Signal Patterns for Machine Learning-Assisted Recognition of Gas-Phase Chemicals","volume":"4","author":"Yoshizumi","year":"2019","journal-title":"Mol. Syst. Des. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2142","DOI":"10.1016\/j.jece.2017.04.007","article-title":"Modeling of Expanded Granular Sludge Bed Reactor using Artificial Neural Network","volume":"5","year":"2017","journal-title":"J. Environ. Chem. Eng."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Byli\u0144ski, H., Sobecki, A., and G\u0119bicki, J. (2019). The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process. Sustainability, 11.","DOI":"10.3390\/su11164407"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.resconrec.2009.08.012","article-title":"Modeling and Optimization of Biogas Production from a Waste Digester using Artificial Neural Network and Genetic Algorithm","volume":"54","author":"Qdais","year":"2010","journal-title":"Resour. Conserv. Recycl."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1080\/15435075.2012.727116","article-title":"Development of ANN-based Models to Predict Biogas and Methane Productions in Anaerobic Treatment of Molasses Wastewater","volume":"10","author":"Yetilmezsoy","year":"2013","journal-title":"Int. J. Green Energy."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.neucom.2015.03.101","article-title":"E-nose System by using Neural Networks","volume":"172","author":"Omatu","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3711","DOI":"10.1039\/C6AY00147E","article-title":"Ensemble-Based Support Vector Machine Classifiers as an Efficient Tool for Quality Assessment of Beef Fillets from Electronic Nose Data","volume":"8","author":"Mohareb","year":"2016","journal-title":"Anal. Methods"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1266","DOI":"10.1002\/anie.201505308","article-title":"Nanowire Chemical\/Biological Sensors: Status and a Roadmap for the Future","volume":"55","author":"Fennell","year":"2016","journal-title":"Angew. Chem. Int. Ed."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.bios.2008.04.014","article-title":"Towards Development of Chemosensors and Biosensors with Metal-Oxide-Based Nanowires or Nanotubes","volume":"24","author":"Liu","year":"2008","journal-title":"Biosens. Bioelectron."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Vanarse, A., Osseiran, A., and Rassau, A. (2017). An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems. Sensors, 17.","DOI":"10.3390\/s17112591"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"21263","DOI":"10.1021\/acsami.5b05479","article-title":"Chemical Gated Field Effect Transistor by Hybrid Integration of One-Dimensional Silicon Nanowire and Two-Dimensional Tin Oxide Thin Film for Low Power Gas Sensor","volume":"7","author":"Han","year":"2015","journal-title":"ACS Appl. Mater. Interfaces"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"5229","DOI":"10.1002\/adma.201506457","article-title":"MOF Thin Film-Coated Metal Oxide Nanowire Array: Significantly Improved Chemiresistor Sensor Performance","volume":"28","author":"Yao","year":"2016","journal-title":"Adv. Mater."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Moon, H.G., Jung, Y., Shin, B., Song, Y.G., Kim, J.H., Lee, T., Lee, S., Jun, S.C., Kaner, R.B., and Kang, C.-Y. (2020). On-Chip Chemiresistive Sensor Array for On-Road NOx Monitoring with Quantification. Adv. Sci., 7.","DOI":"10.1002\/advs.202002014"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1002\/elan.201500361","article-title":"Rapid Prototyping of Sensors and Conductive Elements by Day-to-Day Writing Tools and Emerging Manufacturing Technologies","volume":"28","author":"Dossi","year":"2016","journal-title":"Electroanalysis"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1021\/acssensors.5b00279","article-title":"Toward the Responsible Development and Commercialization of Sensor Nanotechnologies","volume":"1","author":"Fadel","year":"2016","journal-title":"ACS Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1468","DOI":"10.1002\/1521-4095(200110)13:19<1468::AID-ADMA1468>3.0.CO;2-O","article-title":"Tin Dioxide Opals and Inverted Opals: Near-Ideal Microstructures for Gas Sensors","volume":"13","author":"Scott","year":"2001","journal-title":"Adv. Mater."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"938","DOI":"10.1364\/AO.26.000938","article-title":"Real-Time Deformation Invariant Optical Pattern Recognition Using Coordinate Transformations","volume":"26","author":"Casasent","year":"1987","journal-title":"Appl. Opt."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.cam.2017.07.015","article-title":"An Iterative Reproducing Kernel Method in Hilbert Space for the Multi-Point Boundary Value Problems","volume":"328","author":"Azarnavid","year":"2018","journal-title":"J. Comput. Appl. Math."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1169\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:13:45Z","timestamp":1760134425000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1169"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,3]]},"references-count":51,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["s22031169"],"URL":"https:\/\/doi.org\/10.3390\/s22031169","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,2,3]]}}}