{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T21:39:41Z","timestamp":1773869981451,"version":"3.50.1"},"reference-count":72,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T00:00:00Z","timestamp":1773792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Yangzhou Municipal-University Collaboration Special Program","award":["YZ2024233"],"award-info":[{"award-number":["YZ2024233"]}]},{"name":"Open Research Program of China\u2019s State Key Laboratory of Millimeter Waves","award":["KN202502-15"],"award-info":[{"award-number":["KN202502-15"]}]},{"DOI":"10.13039\/501100013254","name":"National College Students Innovation and Entrepreneurship Training Program","doi-asserted-by":"publisher","award":["202513989003G"],"award-info":[{"award-number":["202513989003G"]}],"id":[{"id":"10.13039\/501100013254","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>High-precision detection of hazardous gases with low refractive indices ranging from 1.000 to 1.100, specifically including methane, carbon monoxide, and sulfur dioxide, is critical for industrial safety, yet conventional sensors often suffer from limited sensitivity and severe thermal cross-sensitivity. This work presents a Magneto-Optical Differential Photonic Crystals Sensor (MO-DPCS) utilizing indium antimonide (InSb) to address these constraints. Employing the Multi-Objective Dragonfly Algorithm (MODA), the system was inversely optimized to maximize magneto-optical polarization splitting while rigorously maintaining an ultra-high transmission efficiency. Crucially, an angular interrogation architecture operating under oblique incidence was established to maximize the magneto-optical non-reciprocity, where the detection was realized by fixing the terahertz source frequency and monitoring the precise angular displacements of the steep spectral edges. A differential detection technique was employed to utilize the non-reciprocal phase changes wherein Transverse Electric (TE) and Transverse Magnetic (TM) modes display contrasting kinematic characteristics in the presence of an external magnetic field. The findings indicate that with an adjusted magnetic field of 0.033 T, the MO-DPCS attains an exceptional differential sensitivity of 30.8\u00b0\/RIU, much above the 0.8\u00b0\/RIU seen in the unmagnetized condition. The differential approach efficiently eliminates common-mode thermal noise, minimizing temperature-induced drift to below 0.35\u00b0 across a 1 K range. The suggested MO-DPCS offers a robust, self-referencing solution for stable and high-sensitivity gas sensing applications with a detection limit of 4.18 \u00d7 10\u22124 RIU.<\/jats:p>","DOI":"10.3390\/s26061914","type":"journal-article","created":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T14:14:05Z","timestamp":1773843245000},"page":"1914","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["High-Sensitivity and Temperature-Robust Gas Sensor Based on Magnetically Induced Differential Mode Splitting in InSb Photonic Crystals"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9510-1038","authenticated-orcid":false,"given":"Jin","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Electronic Engineering, Tongda College of Nanjing University of Posts and Telecommunications, Yangzhou 225127, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8521-4469","authenticated-orcid":false,"given":"Leyu","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Tongda College of Nanjing University of Posts and Telecommunications, Yangzhou 225127, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7236-8168","authenticated-orcid":false,"given":"Chenxi","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9890-8345","authenticated-orcid":false,"given":"Hai-Feng","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Tongda College of Nanjing University of Posts and Telecommunications, Yangzhou 225127, China"},{"name":"College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1109\/JSEN.2018.2879248","article-title":"An In-Pipe Leak Detection Robot With a Neural-Network-Based Leak Verification System","volume":"19","author":"Waleed","year":"2019","journal-title":"IEEE Sens. 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