{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T20:07:18Z","timestamp":1760386038944,"version":"build-2065373602"},"reference-count":40,"publisher":"Optica Publishing Group","issue":"30","license":[{"start":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T00:00:00Z","timestamp":1759708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR"},{"start":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T00:00:00Z","timestamp":1759708800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"funder":[{"name":"IRDE Lab","award":["Dir\/ECS\/IRDE\/Proc(BRR)\/23-24\/005 (CARS)"],"award-info":[{"award-number":["Dir\/ECS\/IRDE\/Proc(BRR)\/23-24\/005 (CARS)"]}]},{"name":"DFTM-DRDO","award":["DFTM\/03\/3203\/M\/01\/JATC"],"award-info":[{"award-number":["DFTM\/03\/3203\/M\/01\/JATC"]}]}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Appl. Opt."],"published-print":{"date-parts":[[2025,10,20]]},"abstract":"<jats:p>The identification of contraband materials poses a significant\n\t\t\t\t\tchallenge in law enforcement, particularly due to legal restrictions\n\t\t\t\t\tprohibiting search without a warrant, and with commercial X-ray\n\t\t\t\t\tscanning, one cannot distinguish between a legal and an illegal drug\n\t\t\t\t\twhen placed in dielectric packaging. Terahertz (THz) radiation,\n\t\t\t\t\tspanning frequencies from 0.1 to 10\u00a0THz, lying between the\n\t\t\t\t\tmicrowave and infrared regions of the electromagnetic spectrum,\n\t\t\t\t\tpenetrates such packages as long as they are not metallic in nature.\n\t\t\t\t\tSeveral compounds have unique spectral signatures in the THz regime,\n\t\t\t\t\tenabling the identification of controlled substances, even in cases of\n\t\t\t\t\tcomplex mixtures. This present work integrates evolutionary algorithms\n\t\t\t\t\tand machine learning approaches to highlight the potential to automate\n\t\t\t\t\tthe identification and quantification of several drug components\n\t\t\t\t\twithin complex, real-world mixtures, advancing the application of THz\n\t\t\t\t\tspectroscopy. Using fundamental optical properties derived from the\n\t\t\t\t\tTHz spectra, we focused on three representative compounds: caffeine\n\t\t\t\t\tand pseudo-scents of heroin and marijuana, with their respective\n\t\t\t\t\tabsorbance, extinction coefficient, and absorption coefficient as the\n\t\t\t\t\tkey indicators for the process. We trained a model to estimate drug\n\t\t\t\t\tconcentrations by aggregating their spectral data with the\n\t\t\t\t\tevolutionary micro-genetic algorithm (<jats:italic>\u03bc<\/jats:italic>GA) and partial least square regression.\n\t\t\t\t\tWith average errors around 4% for caffeine and 9% for pseudo-scents of\n\t\t\t\t\theroin and marijuana, our predictions closely match the true\n\t\t\t\t\tconcentrations, obtaining R<jats:sup>2<\/jats:sup> values around 0.99. These degrees of\n\t\t\t\t\taccuracy imply the potential for the approach to be developed into a\n\t\t\t\t\tpractical tool for non-invasive, reliable drug screening in sensitive\n\t\t\t\t\tenvironments like airports, mail facilities, and border control,\n\t\t\t\t\tintegrated with a sensitive and portable THz device.<\/jats:p>","DOI":"10.1364\/ao.569543","type":"journal-article","created":{"date-parts":[[2025,8,13]],"date-time":"2025-08-13T11:59:01Z","timestamp":1755086341000},"page":"F46","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evolutionary optimization of THz spectral data  for the quantitative identification of contraband substances"],"prefix":"10.1364","volume":"64","author":[{"given":"Arya","family":"Das","sequence":"first","affiliation":[{"name":"Indian Institute of Technology Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9510-5371","authenticated-orcid":true,"given":"Mayuri","family":"Kashyap","sequence":"additional","affiliation":[{"name":"CSIR\u2013Central Glass & Ceramic Research Institute (CSIR\u2013CGCRI)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0195-9171","authenticated-orcid":true,"given":"Amartya","family":"Sengupta","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1661-1266","authenticated-orcid":true,"given":"Aparajita","family":"Bandyopadhyay","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Delhi"},{"name":"Goethe-Universit\u00e4t Frankfurt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"285","published-online":{"date-parts":[[2025,10,6]]},"reference":[{"key":"ao-64-30-F46-R1","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1038\/s43586-023-00232-z","type":"journal-article","volume":"3","author":"Koch","year":"2023","journal-title":"Nature Reviews Methods\n\t\t\t\t\tPrimers"},{"key":"ao-64-30-F46-R2","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1038\/nphoton.2007.3","type":"journal-article","volume":"1","author":"Tonouchi","year":"2007","journal-title":"Nat. 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All rights,\n\t\t\t\t\tincluding for text and data mining (TDM), Artificial Intelligence (AI)\n\t\t\t\t\ttraining, and similar technologies, are\n\t\t\t\t\treserved.","name":"copyright","label":"Copyright"}]}}