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The methanol content within these blends significantly influences their quality and combustion performance. This study explores the qualitative and qualitative analysis of methanol\u2013gasoline blends using Raman spectroscopy coupled with machine learning methods. Experimentally, methanol\u2013gasoline blends with varying methanol concentrations were artificially configured, commencing with initial market samples. For qualitative analysis, the partial least squares discriminant analysis (PLS-DA) model was employed to classify the categories of blends, demonstrating high prediction performance with an accuracy of nearly 100% classification. For the quantitative analysis, a consensus model was proposed to accurately predict the methanol content. It integrates member models developed on clustered variables, using the unsupervised clustering method of the self-organizing mapping neural network (SOM) to accomplish the regression prediction. The performance of this consensus model was systemically compared to that of the PLS model and uninformative variable elimination (UVE)\u2013PLS model. Results revealed that the unsupervised consensus model outperformed other models in predicting the methanol content across various types of methanol gasoline blends. The correlation coefficients for prediction sets consistently exceeded 0.98. Consequently, Raman spectroscopy emerges as a suitable choice for both qualitative and quantitative analysis of methanol\u2013gasoline blend quality. This study anticipates an increasing role for Raman spectroscopy in analysis of fuel composition.<\/jats:p>","DOI":"10.3390\/molecules29071427","type":"journal-article","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T10:03:59Z","timestamp":1711101839000},"page":"1427","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Unsupervised Clustering-Assisted Method for Consensual Quantitative Analysis of Methanol\u2013Gasoline Blends by Raman Spectroscopy"],"prefix":"10.3390","volume":"29","author":[{"given":"Biao","family":"Lu","sequence":"first","affiliation":[{"name":"School of Information and Engineering, Suzhou University, Suzhou 234000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shilong","family":"Wu","sequence":"additional","affiliation":[{"name":"Suzhou Vocational and Technical College, Suzhou 234000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deliang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information and Engineering, Suzhou University, Suzhou 234000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenping","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information and Engineering, Suzhou University, Suzhou 234000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information and Engineering, Suzhou University, Suzhou 234000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5255-4687","authenticated-orcid":false,"given":"Lei-ming","family":"Yuan","sequence":"additional","affiliation":[{"name":"College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"114231","DOI":"10.1016\/j.rser.2023.114231","article-title":"Integrated sustainability assessment framework for geothermal energy technologies: A literature review and a new proposal of sustainability indicators for Mexico","volume":"192","author":"Santoyo","year":"2024","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.energy.2017.05.052","article-title":"Temporally-explicit and spatially-resolved global onshore wind energy potentials","volume":"131","author":"Bosch","year":"2017","journal-title":"Energy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.marpol.2018.08.017","article-title":"Analysing the potentials and effects of multi-use between tidal energy development and environmental protection and monitoring: A case study of the inner sound of the Pentland Firth","volume":"96","author":"Sangiuliano","year":"2018","journal-title":"Mar. Policy"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"5910","DOI":"10.1016\/j.rser.2012.05.039","article-title":"A review on bio-oil production from biomass by using pyrolysis method","volume":"16","author":"Isahak","year":"2012","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"109763","DOI":"10.1016\/j.rser.2020.109763","article-title":"Lignocellulose biomass pyrolysis for bio-oil production: A review of biomass pre-treatment methods for production of drop-in fuels","volume":"123","author":"Kumar","year":"2020","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1016\/j.applthermaleng.2006.12.024","article-title":"Study of spark ignition engine fueled with methanol\/gasoline fuel blends","volume":"27","author":"Liu","year":"2007","journal-title":"Appl. Therm. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"104822","DOI":"10.1016\/j.microc.2020.104822","article-title":"Zeolite-based catalysts for methanol to gasoline process: A review","volume":"156","author":"Kianfar","year":"2020","journal-title":"Microchem. J."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.ejpe.2019.08.006","article-title":"Properties of gasoline-ethanol-methanol ternary fuel blend compared with ethanol-gasoline and methanol-gasoline fuel blends","volume":"28","author":"Amine","year":"2019","journal-title":"Egypt. J. Pet."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1016\/j.talanta.2011.02.049","article-title":"Classification of gasoline by octane number and light gas condensate fractions by origin with using dielectric or gas-chromatographic data and chemometrics tools","volume":"84","author":"Rudnev","year":"2011","journal-title":"Talanta"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"120565","DOI":"10.1016\/j.fuel.2021.120565","article-title":"Fuel performance for stable homogeneous gasoline-methanol-ethanol blends","volume":"294","author":"Waluyo","year":"2021","journal-title":"Fuel"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1723","DOI":"10.1016\/j.matpr.2017.02.013","article-title":"Review on the Detection of Adulteration in Fuels through Computational Techniques","volume":"4","author":"Babu","year":"2017","journal-title":"Mater. Today Proc."},{"key":"ref_12","first-page":"713","article-title":"Investigations on the effects of ethanol\u2013methanol\u2013gasoline blends in a spark-ignition engine: Performance and emissions analysis","volume":"18","author":"Elfasakhany","year":"2015","journal-title":"Eng. Sci. Technol. Int. J."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3542","DOI":"10.1021\/ef300277c","article-title":"Gasoline, Kerosene, and Diesel Fingerprinting via Polar Markers","volume":"26","author":"Haddad","year":"2012","journal-title":"Energy Fuels"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2168","DOI":"10.1016\/j.fuel.2007.11.003","article-title":"Influence of solvent addition on the physicochemical properties of Brazilian gasoline","volume":"87","author":"Takeshita","year":"2008","journal-title":"Fuel"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"8363","DOI":"10.1016\/j.aej.2022.01.072","article-title":"Review of artificial neural networks for gasoline, diesel and homogeneous charge compression ignition engine","volume":"61","author":"Veza","year":"2022","journal-title":"Alex. Eng. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1016\/j.fuel.2015.11.018","article-title":"Comparison of Raman and IR spectroscopy for quantitative analysis of gasoline\/ethanol blends","volume":"166","author":"Corsetti","year":"2016","journal-title":"Fuel"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1016\/j.fuel.2007.07.018","article-title":"Gasoline classification by source and type based on near infrared (NIR) spectroscopy data","volume":"87","author":"Balabin","year":"2008","journal-title":"Fuel"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Sales, R.d.F., C\u00e1ssio Barbosa-Patr\u00edcio, L., da Silva, N.C., Rodrigues e Brito, L., Eduarda Fernandes da Silva, M., and Fernanda Pimentel, M. (2023). Gasoline discrimination using infrared spectroscopy and virtual samples based on measurement uncertainty. Spectrochim. Acta Part A Mol. Biomol. Spectrosc., 303.","DOI":"10.1016\/j.saa.2023.123248"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/j.snb.2012.07.012","article-title":"A hard modeling approach to determine methanol concentration in methanol gasoline by Raman spectroscopy","volume":"173","author":"Li","year":"2012","journal-title":"Sens. Actuators B-Chem."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"120112","DOI":"10.1016\/j.fuel.2020.120112","article-title":"Recent trends for introducing promising fuel components to enhance the anti-knock quality of gasoline: A systematic review","volume":"291","author":"Abdellatief","year":"2021","journal-title":"Fuel"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.trac.2011.12.006","article-title":"Characterization of petroleum-based products by infrared spectroscopy and chemometrics","volume":"35","author":"Khanmohammadi","year":"2012","journal-title":"TrAC Trends Anal. Chem."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"12286","DOI":"10.1021\/acs.energyfuels.9b03021","article-title":"Data Fusion of Raman and Near-Infrared Spectroscopies for the Rapid Quantitative Analysis of Methanol Content in Methanol-Gasoline","volume":"33","author":"Li","year":"2019","journal-title":"Energy Fuels"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1007\/s11430-007-0078-9","article-title":"Raman characteristics of hydrocarbon and hydrocarbon inclusions","volume":"50","author":"Zhang","year":"2007","journal-title":"Sci. China Ser. D-Earth Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1016\/j.saa.2004.10.008","article-title":"Qualitative study of ethanol content in tequilas by Raman spectroscopy and principal component analysis","volume":"61","year":"2005","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"8456","DOI":"10.1021\/ac061220j","article-title":"Determination of lycopene and beta-carotene content in tomato fruits and related products: Comparison of FT-Raman, ATR-IR, and NIR spectroscopy","volume":"78","author":"Baranska","year":"2006","journal-title":"Anal. Chem."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3785","DOI":"10.1016\/j.optcom.2009.06.034","article-title":"Rapid and quantitative detection of ethanol proportion in ethanol\u2013gasoline mixtures by Raman spectroscopy","volume":"282","author":"Ye","year":"2009","journal-title":"Opt. Commun."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"119430","DOI":"10.1016\/j.saa.2021.119430","article-title":"Hybrid variable selection strategy coupled with random forest (RF) for quantitative analysis of methanol in methanol-gasoline via Raman spectroscopy","volume":"251","author":"Li","year":"2021","journal-title":"Spectrochim. Acta A"},{"key":"ref_28","unstructured":"Brown, S., Tauler, R., and Walczak, B. (2009). Comprehensive Chemometrics, Elsevier. [2nd ed.]."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3851","DOI":"10.1021\/ac960321m","article-title":"Elimination of uninformative variables for multivariate calibration","volume":"68","author":"Centner","year":"1996","journal-title":"Anal. Chem."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1016\/j.dss.2012.11.015","article-title":"Partial Least Square Discriminant Analysis for bankruptcy prediction","volume":"54","year":"2013","journal-title":"Decis. Support Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3526","DOI":"10.1039\/C8AN00599K","article-title":"Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: A review of contemporary practice strategies and knowledge gaps","volume":"143","author":"Lee","year":"2018","journal-title":"Analyst"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1007\/s12161-017-1096-7","article-title":"A Novel Strategy of Clustering Informative Variables for Quantitative Analysis of Potential Toxics Element in Tegillarca Granosa Using Laser-Induced Breakdown Spectroscopy","volume":"11","author":"Yuan","year":"2018","journal-title":"Food Anal. Methods"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1002\/bimj.201700067","article-title":"Variable selection\u2014A review and recommendations for the practicing statistician","volume":"60","author":"Heinze","year":"2018","journal-title":"Biom. J."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3771","DOI":"10.1016\/j.asoc.2011.02.009","article-title":"A novel self-organizing map (SOM) neural network for discrete groups of data clustering","volume":"11","author":"Ghaseminezhad","year":"2011","journal-title":"Appl. Soft Comput."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Yuan, L.-M., Mao, F., Huang, G., Chen, X., Wu, D., Li, S., Zhou, X., Jiang, Q., Lin, D., and He, R. (2020). Models fused with successive CARS-PLS for measurement of the soluble solids content of Chinese bayberry by vis-NIRS technology. Postharvest Biol. Technol., 169.","DOI":"10.1016\/j.postharvbio.2020.111308"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"111067","DOI":"10.1016\/j.postharvbio.2019.111067","article-title":"Non-invasive measurements of \u2018Yunhe\u2019 pears by vis-NIRS technology coupled with deviation fusion modeling approach","volume":"160","author":"Yuan","year":"2020","journal-title":"Postharvest Biol. Technol."},{"key":"ref_37","first-page":"2099","article-title":"Study on Rapid Quantitative Analysis Method of Methanol Content in Methanol Gasoline by Raman Spectroscopy and Partial Least Squares","volume":"41","author":"Li","year":"2021","journal-title":"Spectrosc. Spect. Anal."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.snb.2010.01.041","article-title":"Determination of methanol ratio in methanol-doped biogasoline by a fiber Raman sensing system","volume":"146","author":"Xu","year":"2010","journal-title":"Sens. Actuators B Chem."}],"container-title":["Molecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1420-3049\/29\/7\/1427\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:18:09Z","timestamp":1760105889000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1420-3049\/29\/7\/1427"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,22]]},"references-count":38,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["molecules29071427"],"URL":"https:\/\/doi.org\/10.3390\/molecules29071427","relation":{},"ISSN":["1420-3049"],"issn-type":[{"value":"1420-3049","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,22]]}}}