{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T14:53:47Z","timestamp":1791298427728,"version":"4.1.0"},"reference-count":29,"publisher":"Optica Publishing Group","issue":"29","license":[{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR"},{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Appl. Opt."],"published-print":{"date-parts":[[2026,10,10]]},"abstract":"<jats:p>A transfer-matrix framework is developed for dynamic optical fingerprinting of modeled tear-film perturbations using a thermally self-referenced multi-defect one-dimensional photonic crystal. Four coupled defect compartments represent aqueous-index variation, hydration-dependent optical-thickness change, mucin\/inhomogeneity-associated loss, and lipid-composite evolution, while a sealed reference cavity compensates common-mode thermal drift. Time-dependent transmission spectra are analyzed using corrected defect-mode shifts and local peak-transmission changes. The resulting hybrid fingerprints distinguish stable-film-like, evaporation-dominant-like, aqueous-deficient-like, lipid-deficient-like, and mucin-instability-like scenarios. The minimum terminal uncertainty-normalized separation was 16.43, exceeding the prescribed threshold of 3, and remained above this threshold from t=0.4s onward using a 0.10\u00a0s sampling interval. Monte Carlo analysis with 500 realizations yielded a terminal minimum separation of 17.19\u00b12.35, with all realizations exceeding the threshold. Under the matched-model thermal-only blank, temperature calibration suppresses simulated thermal drift by 99.85%\u201399.98%. These results establish a numerically grounded self-referenced framework for analyzing time-varying tear-film-like perturbations.<\/jats:p>","DOI":"10.1364\/ao.610390","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T15:00:06Z","timestamp":1788534006000},"page":"10212","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic optical response of a self-referenced multi-defect photonic crystal under modeled tear-film perturbations: a photonic modeling framework for ocular-surface analysis"],"prefix":"10.1364","volume":"65","author":[{"given":"Asala","family":"Bakry","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05pn4yv70","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Higher Technological Institute of Applied Health Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatma A.","family":"Sayed","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05pn4yv70","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rafat M.","family":"Amin","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05pn4yv70","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0795-378X","authenticated-orcid":true,"given":"Arafa H.","family":"Aly","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05pn4yv70","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Higher Technological Institute of Applied Health Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,10,6]]},"reference":[{"key":"ao-65-29-10212-R1","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1016\/j.jtos.2017.05.008","type":"journal-article","volume":"15","author":"Craig","year":"2017","journal-title":"Ocul. 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All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.","name":"copyright","label":"Copyright"}]}}