Feng, L. et al. Ultra-compact dual-channel integrated CO2 infrared gas sensor. Microsyst. Nanoeng. 10, 151 (2024).
Pan, Y. et al. A passive wireless surface acoustic wave (SAW) sensor system for detecting warfare agents based on fluoroalcohol polysiloxane film. Microsyst. Nanoeng. 10, 4 (2024).
Yuan, Y. et al. Analysis of the acoustoelectric response of SAW gas sensors using a COM model. Microsyst. Nanoeng. 10, 69 (2024).
Li, Y., Wei, X., Zhou, Y., Wang, J. & You, R. Research progress of electronic nose technology in exhaled breath disease analysis. Microsyst. Nanoeng. 9, 129 (2023).
Jung, G. et al. Reconfigurable Manipulation of Oxygen Content on Metal Oxide Surfaces and Applications to Gas Sensing. ACS Nano 17, 17790–17798 (2023).
Zegebreal, L. T., Tegegne, N. A. & Hone, F. G. Recent progress in hybrid conducting polymers and metal oxide nanocomposite for room-temperature gas sensor applications: a review. Sens. Actuators A 359, 114472 (2023).
Zhou, Y., Xu, K., Zheng, Z., He, X. & Zhang, C. Quartz crystal microbalance sensor based on ZnO nanofilm for methanol detection. IEEE Sens. J. 24, 204–214 (2024).
Tang, Y., Zhao, Y. & Liu, H. Room-temperature semiconductor gas sensors: challenges and opportunities. ACS Sens. 7, 3582–3597 (2022).
Su, Y.-D. et al. Multiparameter optical fiber sensing for energy infrastructure through nanoscale light-matter interactions: From hardware to software, science to commercial opportunities. APL Photonics 9, 120902 (2024).
Huma, H., Shabbir, M., Seo, S. E. & Kwon, O. S. Frontiers in point-of-care testing: a comprehensive review. Appl. Sci. Convergence Technol. 33, 117–125 (2024).
Yuan, H., Li, N., Fan, W., Cai, H. & Zhao, D. Metal-organic framework based gas sensors. Adv. Sci. 9, e2104374 (2022).
Zhao, X. et al. Integrated near-infrared fiber-optic photoacoustic sensing demodulator for ultra-high sensitivity gas detection. Photoacoustics 33, 100560 (2023). 100560.
Zhou, H., Li, D., Hui, X. & Mu, X. Infrared metamaterial for surface-enhanced infrared absorption spectroscopy: pushing the frontier of ultrasensitive on-chip sensing. Int. J. Optomechatronics 15, 97–119 (2021).
Paterova, A. V., Toa, Z. S. D., Yang, H. Z. & Krivitsky, L. A. Broadband quantum spectroscopy at the fingerprint mid-infrared region. ACS Photonics 9, 2151–2159 (2022).
Trieu-Vuong, D., Choi, I.-Y., Son, Y.-S. & Kim, J.-C. A review on non-dispersive infrared gas sensors: Improvement of sensor detection limit and interference correction. Sens. Actuators B 231, 529–538 (2016).
Wang, C., He, T., Zhou, H., Zhang, Z. & Lee, C. Artificial intelligence enhanced sensors – enabling technologies to next-generation healthcare and biomedical platform. Bioelectron. Med. 9, 17 (2023).
Zhou, J. et al. Artificial-intelligence-enhanced mid-infrared lab-on-a-chip for mixture spectroscopy analysis. Laser Photonics Rev. 19, 2400754 (2024).
Yan, Y., Feng, H., Wang, C. & Ren, W. On-chip photothermal gas sensor based on a lithium niobate rib waveguide. Sens. Actuators B 405, 135392 (2024).
Consani, C. et al. Mid-infrared photonic gas sensing using a silicon waveguide and an integrated emitter. Sens. Actuators B 274, 60–65 (2018).
Zhou, H. et al. Surface plasmons-phonons for mid-infrared hyperspectral imaging. Sci. Adv. 10, eado3179 (2024).
Zhou, H. et al. Dynamic construction of refractive index-dependent vibrations using surface plasmon-phonon polaritons. Nat. Commun. 14, 7316 (2023).
Li, D. et al. Ultrasensitive molecular fingerprint retrieval using strongly detuned overcoupled plasmonic nanoantennas. Adv. Mater. 35, e2301787 (2023).
Zhou, H., Li, D. & Lee, C. Technology landscape review of in-sensor photonic intelligence from optical sensors to smart devices. AI Sens. 1, 5 (2025).
Kozmin, A. et al. Wavelet-based machine learning algorithms for photoacoustic gas sensing. Optics 5, 207–222 (2024).
Zhou, H. et al. Bionic ultra-sensitive self-powered electromechanical sensor for muscle-triggered communication application. Adv. Sci. 8, 2101020 (2021). e2101020.
Russell, B. J., Meng, J. & Crozier, K. B. Mid-infrared gas classification using a bound state in the continuum metasurface and machine learning. IEEE Sens. J. 23, 22389–22398 (2023).
Pareek, V., Chaudhury, S. & Singh, S. Hybrid 3DCNN-RBM network for gas mixture concentration estimation with sensor array. IEEE Sens. J. 21, 24263–24273 (2021).
Yang, J., Caruso, A., Li, J. & Lin, P. T. Mid-infrared spectrum sensing algorithm applying micro-resonator arrays. IEEE Sens. J. 22, 13387–13394 (2022).
Torrisi, F., Amato, E., Corradino, C., Mangiagli, S. & Del Negro, C. Characterization of volcanic cloud components using machine learning techniques and SEVIRI infrared images. Sensors 22, 7712 (2022).
Sonkar, S. K., Kumar, P., George, R. C., Philip, D. & Ghosh, A. K. Detection and estimation of natural gas leakage using UAV by machine learning algorithms. IEEE Sens. J. 22, 8041–8049 (2022).
Ramou, E., Palma, S. I. C. J. & Roque, A. C. A. Nanoscale events on cyanobiphenyl-based self-assembled droplets triggered by gas analytes. ACS Appl. Mater. Interfaces 14, 6261–6273 (2022).
Mansouri, T. S., Wang, H., Mariotti, D. & Maguire, P. Methane detection to 1 ppm using machine learning analysis of atmospheric pressure plasma optical emission spectra. J. Phys. D: Appl. Phys. 55, 225205 (2022).
Yu, J., Wang, D., Tipparaju, V. V., Tsow, F. & Xian, X. Mitigation of humidity interference in colorimetric sensing of gases. ACS Sens 6, 303–320 (2021).
Yu, J., Tsow, F., Mora, S. J., Tipparaju, V. V. & Xian, X. Hydrogel-incorporated colorimetric sensors with high humidity tolerance for environmental gases sensing. Sens Actuators B Chem. 345, 130404 (2021).
Galstyan, V. Quantum dots: Perspectives in next-generation chemical gas sensors—a review. Anal. Chim. Acta 1152, 238192 (2021).
Chen, Z. et al. Real-time, noise and drift resilient formaldehyde sensing at room temperature with aerogel filaments. Sci. Adv. 10, eadk6856 (2024).
Li, D., Zhou, H., Ren, Z. & Lee, C. Advances in MEMS, optical MEMS, and nanophotonics technologies for volatile organic compound detection and applications. Small Sci. 5, 202400250 (2024).
Zhou, H., Li, D., Lv, Q. & Lee, C. Integrative plasmonics: optical multi-effects and acousto-electric-thermal fusion for biosensing, energy conversion, and photonic circuits. Chem. Soc. Rev. 54, 5342–5432 (2025).
Hu, J. et al. Ultra-high sensitivity gas pressure sensor based on cascaded Mach-Zehnder interferometer and Sagnac interferometer. Optik 276, 170655 (2023).
Tan, X. et al. Non-dispersive infrared multi-gas sensing via nanoantenna integrated narrowband detectors. Nat. Commun. 11, 5245 (2020).
Bi, X., Czajkowsky, D. M., Shao, Z. & Ye, J. Digital colloid-enhanced Raman spectroscopy by single-molecule counting. Nature 628, 771–775 (2024).
Li, D. et al. Multifunctional chemical sensing platform based on dual-resonant infrared plasmonic perfect absorber for on-chip detection of poly(ethyl cyanoacrylate). Adv. Sci. 8, e2101879 (2021).
Hui, X. et al. Infrared plasmonic biosensor with tetrahedral DNA nanostructure as carriers for label-free and ultrasensitive detection of miR-155. Adv. Sci. 8, e2100583 (2021).
Zhou, H. et al. Metal-organic framework-surface-enhanced infrared absorption platform enables simultaneous on-chip sensing of greenhouse gases. Adv. Sci. 7, 2001173 (2020).
Zhou, H. et al. Terahertz biosensing based on bi-layer metamaterial absorbers toward ultra-high sensitivity and simple fabrication. Appl. Phys. Lett. 115, 143507 (2019).
Zhou, H. et al. Integrating a microwave resonator and a microchannel with an immunochromatographic strip for stable and quantitative biodetection. ACS Appl. Mater. Interfaces 11, 14630–14639 (2019).
Zhou, H. et al. Multi-band sensing for dielectric property of chemicals using metamaterial integrated microfluidic sensor. Sci. Rep. 8, 14801 (2018).
Zhou, H., Xu, L., Ren, Z., Zhu, J. & Lee, C. Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics. Nanoscale Adv. 5, 538–570 (2023).
Wijesinghe, D. R., Zobair, M. A. & Esmaeelpour, M. A review on photoacoustic spectroscopy techniques for gas sensing. Sensors 24, 6577 (2024).
Zhou, H., Ren, Z., Xu, C., Xu, L. & Lee, C. MOF/polymer-integrated multi-hotspot mid-infrared nanoantennas for sensitive detection of CO2 gas. Nano-Micro Lett. 14, 207 (2022).
Zhou, H., Li, D., Ren, Z., Mu, X. & Lee, C. Loss-induced phase transition in mid-infrared plasmonic metamaterials for ultrasensitive vibrational spectroscopy. InfoMat 4, e12349 (2022).
Li, D. et al. Advances and applications of metal-organic frameworks (MOFs) in emerging technologies: a comprehensive review. Glob. Chall. 8, 2300244 (2024).
Ghosal, P. S. & Gupta, A. K. Determination of thermodynamic parameters from Langmuir isotherm constant-revisited. J. Mol. Liq. 225, 137–146 (2017).
Ramanathan, A. et al. Light-driven nanonetwork assembly of gold nanoparticles via 3d printing for optical sensors. ACS Appl. Nano Mater. 7, 27998–28007 (2024).
Gu, S., Chen, B., Xu, X., Han, F. & Chen, S.-C. 3D nanofabrication via directed material assembly: mechanism, method, and future. Adv. Mater. 37, e2312915 (2025).
Matsuo, T., Tanikubo, H. & Hayashi, S. Facile wet-process to free-standing whispering gallery mode resonators mixed with spherical silica gel and π-conjugated molecules. Adv. Opt. Mater. 12, 2401119 (2024).
Chawla, A. et al. Recent advances in synthesis methods and surface structure manipulating strategies of copper selenide (CuSe) nanoparticles for photocatalytic environmental and energy applications. J. Environ. Chem. Eng. 12, 113125 (2024).
Wang, Y., Yu, Z., Smith, C. S. & Caneva, S. Site-specific integration of hexagonal boron nitride quantum emitters on 2d dna origami nanopores. Nano Lett. 24, 8510–8517 (2024).
Kilic, U. et al. Controlling the broadband enhanced light chirality with L-shaped dielectric metamaterials. Nat. Commun. 15, 3757 (2024).
Zhang, J. et al. Plateau-Rayleigh instability enhanced electrohydrodynamic jet printing for direct-writing of micro/nano optical device arrays. Opt. Express 33, 12012–12025 (2025).
Kim, H.-M., Yang, S.-C., Park, J.-H. & Lee, S.-K. Fabrication of top-down-based optical fiber nanoprobes and their diagnostic application for pancreatic cancer. IEEE Sens. J. 24, 11966–11973 (2024).
Raub, A. A. M., Bahru, R., Nashruddin, S. N. A. M. & Yunas, J. A review on vertical aligned zinc oxide nanorods: Synthesis methods, properties, and applications. J. Nanopart. Res. 26, 186 (2024).
Pillanagrovi, J. & Dutta-Gupta, S. Controlling and monitoring laser-mediated localized synthesis of silver nanoparticles within gold nanoapertures. Nano Futures 8, 045001 (2024).
Zhang, Y., Liu, B., Liu, Z. & Li, J. Research progress in the synthesis and biological application of quantum dots. N. J. Chem. 46, 20515–20539 (2022).
Wang, N. et al. Highly tunable 2D silicon quantum dot array with coupling beyond nearest neighbors. Nano Lett. 24, 13126–13133 (2024).
Xia, H. et al. A RGB-type quantum dot-based sensor array for sensitive visual detection of trace formaldehyde in air. Sci. Rep. 6, 36794 (2016).
Zhang, X. et al. Conductive colloidal perovskite quantum dot inks towards fast printing of solar cells. Nat. Energy 9, 1378–1387 (2024).
Lv, W., Song, Y., Pei, H. & Mo, Z. Synthesis strategies and applications of metal–organic framework-quantum dot (MOF@QD) functional composites. J. Ind. Eng. Chem. 128, 17–54 (2023).
Boroviks, S. et al. Extremely confined gap plasmon modes: when nonlocality matters. Nat. Commun. 13, 3105 (2022).
Yue, X. et al. Composite metamaterial of hyperbolic nanoridges and gold nanoparticles for biosensing. Nanoscale 17, 7271–7280 (2025).
Chen, C., Liu, Z., Cai, C. & Qi, Z. -m. Facile fabrication of nanoporous gold films for surface plasmon resonance (SPR) sensing and SPR-based SERS. J. Mater. Chem. C. 9, 6815–6822 (2021).
Barelli, M., Giordano, M. C., Gucciardi, P. G. & Buatier de Mongeot, F. Self-organized nanogratings for large-area surface plasmon polariton excitation and surface-enhanced raman spectroscopy sensing. ACS Appl. Nano Mater. 3, 8784–8793 (2020).
Jaworski, P. et al. Antiresonant hollow-core fiber-based dual gas sensor for detection of methane and carbon dioxide in the near- and mid-infrared regions. Sensors 20, 3813 (2020).
Kim, K. J. et al. Sorption-induced fiber optic plasmonic gas sensing via small grazing angle of incidence. Adv. Mater. 35, 2301293 (2023).
Wang, Z. et al. Ethanol sensor based on cascaded tapered optical fiber with surface modification of ZIF-8. Sens. Actuators B 402, 135084 (2024).
Liu, H. et al. A highly sensitive sensor of methane and hydrogen in tellurite photonic crystal fiber based on four-wave mixing. Opt. Quantum Electron. 54, 215 (2022).
Strutynski, C. et al. Stack-and-draw applied to the engineering of multi-material fibers with non-cylindrical profiles. Adv. Funct. Mater. 31, 2011063 (2021).
Islam, M. S. et al. Single-step tabletop fabrication for low-attenuation terahertz special optical fibers. Adv. Photonics Res. 2, 2100165 (2021).
Cai, S. et al. Fast-response oxygen optical fiber sensor based on PEA2SnI4 perovskite with extremely low limit of detection. Adv. Sci. 9, 2104708 (2022).
Kelly, T. W. et al. Gas-induced differential refractive index enhanced guidance in hollow-core optical fibers. Optica 8, 916–920 (2021).
Seguin, A., Becerra-Deana, R. I., Virally, S., Boudoux, C. & Godbout, N. Fabrication and characterization of indium fluoride multimode fused fiber couplers for the mid-infrared. Opt. Express 31, 33670–33678 (2023).
Horikawa, S., Yang, S., Tanaka, T., Aoki, T. & Kato, S. High-finesse nanofiber Fabry-Pérot resonator in a portable storage container. Rev. Sci. Instrum. 95, 073103 (2024).
Xu, M., Tian, W., Lin, Y., Xu, Y. & Tao, J. Development of a compact NDIR CO2 gas sensor for a portable gas analyzer. Micromachines 15, 1203 (2024).
Jha, R. K. Non-dispersive infrared gas sensing technology: a review. IEEE Sens. J. 22, 6–15 (2022).
Teng, G. et al. Extracting mechanical quality factor and eliminating feedthrough using harmonics of thermal-piezoresistive micromechanical resonators. Microsyst. Nanoeng. 11, 30 (2025).
Li, E., Zhong, J., Jian, J., Hao, Y. & Chang, H. On enhancing the accuracy of inclinometer based on multiple dual-axis MEMS accelerometers fusion. J. Mech. Sci. Technol. 39, 1329–1337 (2025).
Tian, L., Zhao, H., Shen, Q. & Chang, H. A toroidal SAW gyroscope with focused IDTs for sensitivity enhancement. Microsyst. Nanoeng. 10, 37 (2024).
Hao, Y., Wang, Y., Liu, Y., Yuan, W. & Chang, H. An SOI-based post-fabrication process for compliant MEMS devices. J. Micromech. Microeng. 34, 045005 (2024).
Xue, L. et al. Design of optimal estimation algorithm for multi-sensor fusion of a redundant MEMS gyro system. IEEE Sens. J. 23, 4577–4588 (2023).
Chang, H. Serial and Parallel Connections of Micromechanical Resonators for Sensing: Theories and Applications. J. Microelectromech. Syst. 32, 213–228 (2023).
Zhang, P. et al. A MEMS inertial switch with large scale bi-directional adjustable threshold function. J. Microelectromech. Syst. 31, 124–133 (2022).
Tao, K. et al. Investigation of multimodal electret-based MEMS energy harvester with impact-induced nonlinearity. J. Microelectromech. Syst. 27, 276–288 (2018).
Lai, L. et al. Rapidly modulated wide-spectrum infrared source made of super aligned carbon nanotube film for greenhouse gas monitoring. Adv. Funct. Mater. 33, 2208891 (2022).
Thakkar, P. et al. Coupled strip-array waveguides for integrated mid-IR gas sensing. Photonics 10, 55 (2023).
Yao, C., Yan, W., Dong, R., Dou, S. & Yang, L. Superlattice assembly strategy of small noble metal nanoparticles for surface-enhanced Raman scattering. Commun. Mater. 5, 65 (2024).
Zhao, Y., Kumar, A. & Yang, Y. Unveiling practical considerations for reliable and standardized SERS measurements: lessons from a comprehensive review of oblique angle deposition-fabricated silver nanorod array substrates. Chem. Soc. Rev. 53, 1004–1057 (2024).
Zheng, X. et al. Recent progress in SERS monitoring of photocatalytic reactions. Chem. Soc. Rev. 53, 656–683 (2024).
Che, Y. et al. A strategy for accurate SERS gas detection: skillful integration of mass-productive wafer-scale SERS substrate and machine learning-assisted multifeature profiling. ACS Photonics 11, 3331–3342 (2024).
Shin, H. et al. Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers. Nat. Commun. 14, 1644 (2023).
Zhu, K. et al. Wearable SERS sensor based on omnidirectional plasmonic nanovoids array with ultra-high sensitivity and stability. Small 18, 2201508 (2022). e2201508.
Senica, U. et al. Planarized THz quantum cascade lasers for broadband coherent photonics. Light Sci. Appl. 11, 347 (2022).
Lee, S. et al. SERS-based microdevices for use as in vitro diagnostic biosensors. Chem. Soc. Rev. 53, 5394–5427 (2024).
Zhang, L. et al. Emerging metasurfaces for refractometric sensing: fundamental and applications. J. Phys. D: Appl. Phys. 57, 393001 (2024).
Yun, T. G. et al. Extrinsic and intrinsic factors governing the electrochemical oxidation of propylene in aqueous solutions. J. Am. Chem. Soc. 147, 12318–12330 (2025).
Bylinkin, A. et al. On-chip phonon-enhanced IR near-field detection of molecular vibrations. Nat. Commun. 15, 8907 (2024).
Ye, K. et al. Molecular level insights on the pulsed electrochemical CO2 reduction. Nat. Commun. 15, 9781 (2024).
Luo, S. et al. Broadband multiple resonant metasurface for mixture surface-enhanced infrared absorption based on polarization-sensitive folded nanoantennas. Opt. Laser Technol. 181, 111685 (2025).
Wei, J., Yang, J., Qin, M., Yang, L. & Cao, S. Designing a one-dimensional photonic crystal sensor for dimethyl methylphosphonate detection leveraging a hydrogen-bonding-based acidic strategy. Sens. Actuators B: Chem. 423, 136722 (2025).
Zhang, R. et al. Electrochemical synthesis of urea: co-reduction of nitrite and carbon dioxide on binuclear cobalt phthalocyanine. Small 20, e2403285 (2024).
Li, D., Zhou, H., Ren, Z., Xu, C. & Lee, C. Tailoring light-matter interactions in overcoupled resonator for biomolecule recognition and detection. Nano-Micro Lett. 17, 10 (2025).
Li, D., Wu, X., Chen, Z., Liu, T. & Mu, X. Surface-enhanced spectroscopy technology based on metamaterials. Microsyst. Nanoeng. 11, 60 (2025).
Ren, Z., Zhang, Z., Wei, J., Dong, B. & Lee, C. Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy. Nat. Commun. 13, 3859 (2022).
Zhang, Z., Liu, X., Zhou, H., Xu, S. & Lee, C. Advances in machine-learning enhanced nanosensors: from cloud artificial intelligence toward future edge computing at chip level. Small Struct. 5, 2300325 (2023).
Xu, C. et al. Near-field coupling induced less chiral responses in chiral metamaterials for surface-enhanced vibrational circular dichroism. Adv. Funct. Mater. 34, 202314482 (2023).
Xu, C. et al. Expanding chiral metamaterials for retrieving fingerprints via vibrational circular dichroism. Light Sci. Appl. 12, 154 (2023).
Li, D., Xu, C., Xie, J. & Lee, C. Research progress in surface-enhanced infrared absorption spectroscopy: from performance optimization, sensing applications, to system integration. Nanomaterials 13, 2377 (2023).
Xu, C., Ren, Z., Wei, J. & Lee, C. Reconfigurable terahertz metamaterials: From fundamental principles to advanced 6G applications. iScience 25, 103799 (2022).
Otto, A. Excitation of nonradiative surface plasma waves in silver by the method of frustrated total reflection. Z. Phys. A: Hadrons Nucl. 216, 398–410 (1968).
Altug, H., Oh, S. H., Maier, S. A. & Homola, J. Advances and applications of nanophotonic biosensors. Nat. Nanotechnol. 17, 5–16 (2022).
Oh, S. H. et al. Nanophotonic biosensors harnessing van der Waals materials. Nat. Commun. 12, 3824 (2021).
Jahani, Y. et al. Imaging-based spectrometer-less optofluidic biosensors based on dielectric metasurfaces for detecting extracellular vesicles. Nat. Commun. 12, 3246 (2021).
Aigner, A., Weber, T., Wester, A., Maier, S. A. & Tittl, A. Continuous spectral and coupling-strength encoding with dual-gradient metasurfaces. Nat. Nanotechnol. 19, 1804–1812 (2024).
Pavlov, D. et al. Coaxial hole array fabricated by ultrafast femtosecond-laser processing with spatially multiplexed vortex beams for surface enhanced infrared absorption. Appl. Surf. Sci. 541, 148602 (2021).
Gopalan, K. K. et al. Scalable and Tunable Periodic Graphene Nanohole Arrays for Mid-Infrared Plasmonics. Nano Lett. 18, 5913–5918 (2018).
Liu, W. et al. Suspended silicon waveguide platform with subwavelength grating metamaterial cladding for long-wave infrared sensing applications. Nanophotonics 10, 1861–1870 (2021).
Liu, W. et al. Larger-Than-unity external optical field confinement enabled by metamaterial-assisted comb waveguide for ultrasensitive long-wave infrared gas spectroscopy. Nano Lett. 22, 6112–6120 (2022).
Pi, M. Q. et al. Surface-enhanced infrared absorption spectroscopic chalcogenide waveguide sensor using a silver island film. ACS Appl. Mater. Interfaces 13, 32555–32563 (2021).
Ma, Y. et al. Heterogeneously integrated graphene/silicon/halide waveguide photodetectors toward chip-scale zero-bias long-wave infrared spectroscopic sensing. ACS Nano 15, 10084–10094 (2021).
Dong, B. W. et al. Compact low loss mid-infrared wavelength-flattened directional coupler (WFDC) for arbitrary power splitting ratio enabled by rib waveguide dispersion engineering. IEEE J. Sel. Top. Quantum Electron. 24, 1–8 (2018).
Fu, M. et al. Slot waveguides with silicon-rich materials for nonlinear applications. IEEE Photonics J. 13, 1–9 (2021).
Wang, C. et al. Optical waveguide sensors for measuring human temperature and humidity with gel polymer electrolytes. ACS Appl. Mater. Interfaces 13, 60384–60392 (2021).
Lialiou, P. & Maglogiannis, I. Students’ burnout symptoms detection using smartwatch wearable devices: a systematic literature review. AI Sens. 1, 2 (2025).
He, T. et al. Epidermal electronic-tattoo for plant immune response monitoring. Nat. Commun. 16, 3244 (2025).
Zhou, J. et al. Denoising-autoencoder-facilitated MEMS computational spectrometer with enhanced resolution on a silicon photonic chip. Nat. Commun. 15, 10260 (2024).
Zhang, Z., Guo, X. & Lee, C. Advances in olfactory augmented virtual reality towards future metaverse applications. Nat. Commun. 15, 6465 (2024).
Cho, S. et al. Advances in 3D-printed triboelectric nanogenerators and supercapacitors for self-sustainable energy systems. Mater. Today 85, 189–211 (2025).
Wang, L. et al. Sensing technologies for outdoor/indoor farming. Biosensors 14, 629 (2024).
Zhang, Z., Zhao, Z., Chen, C. & Wu, L. Chemiresistive gas sensors made with PtRu@SnO2 nanoparticles for machine learning-assisted discrimination of multiple volatile organic compounds. ACS Appl. Mater. Interfaces 16, 67944–67958 (2024).
Huang, W., Dong, Z. & Lin, L. Density functional theory and machine learning of transition metals in Mo2C for gas sensors. ACS Appl. Nano Mater. 7, 22189–22199 (2024).
Harun-Or-Rashid, M., Mirzaei, S. & Nasiri, N. Nanomaterial innovations and machine learning in gas sensing technologies for real-time health diagnostics. ACS Sens. 10, 1620–1640 (2025).
Moon, D.-B., Bag, A., Chouhdry, H. H., Hong, S. J. & Lee, N.-E. Selective identification of hazardous gases using flexible, room-temperature operable sensor array based on reduced graphene oxide and metal oxide nanoparticles via machine learning. ACS Sens. 9, 6071–6081 (2024).
Wang, Z., Hu, X. & Zhou, Y. Accelerated screening of highly sensitive gas sensor materials for greenhouse gases based on DFT and machine learning methods. ACS Sens 10, 563–572 (2025).
Yang, Z. et al. General model for predicting response of gas-sensitive materials to target gas based on machine learning. ACS Sens 9, 2509–2519 (2024).
Yuan, Z., Luo, X. & Meng, F. Machine learning-assisted research and development of chemiresistive gas sensors. Adv. Eng. Mater. 26 (2024).
Lee, S. W., Yoon, J. A., Kim, M. D., Kim, B. H. & Seo, Y. H. A machine learning-based electronic nose system using numerous low-cost gas sensors for real-time alcoholic beverage classification. Anal. Methods 16, 5909–5919 (2024).
Itoh, T. et al. Discrimination ability and concentration measurement accuracy of effective components in aroma essential oils using gas sensor arrays with machine learning. Appl. Sci. -Basel 14, 8859 (2024).
Kwon, Y. M. et al. Enhancing selectivity and sensitivity in gas sensors through noble metal-decorated ZnO and machine learning. Appl. Surf. Sci. 693, 162750 (2025).
Guo, Y., Yang, M., Huang, G. & Zheng, Y. Machine-learning-enabled exploitation of gas-sensing descriptors: a case study of five pristine metal oxides. Chem. Eng. J. 492, 152280 (2024).
Han, D. et al. Machine-learning-assisted n-GaN-Au/PANI gas sensor array for intelligent and ultra-accurate ammonia recognition. Chem. Eng. J. 495, 153705 (2024).
Khandakar, A. et al. Compost maturity prediction and gas emissions monitoring: A sensor-based and interpretable machine learning approach. Comput. Electr. Eng. 123 (2025).
Parlak, I. H., Milli, M. & Milli, N. S. Machine learning-based detection of olive oil adulteration using BME688 gas sensor matrix. Food Anal. Methods 9, 74–1464 (2025).
Acharyya, S., Ghosh, A., Nag, S., Majumder, S. B. & Guha, P. K. Smart and selective gas sensor system empowered with machine learning over IoT platform. IEEE Internet Things J. 11, 4218–4226 (2024).
Wang, J., Parra, L., Lacuesta, R., Lloret, J. & Lorenz, P. Wearable low-cost and low-energy consumption gas sensor with machine learning to recognize outdoor areas. IEEE Sens. J. 24, 30845–30852 (2024).
Sarkar, L., Paul, S., Sett, A., Kumari, A. & Bhattacharyya, T. K. Classification of gases with single FET-based gas sensor through gate voltage sweeping and machine learning. IEEE Trans. Electron Devices 72, 376–382 (2025).
Sun, R. et al. A NDIR CO sensor enhanced by machine learning algorithm applying in gas outburst Early warning. Infrared Phys. Technol. 147, 105801 (2025).
Ku, W. et al. Rational design of hybrid sensor arrays combined synergistically with machine learning for rapid response to a hazardous gas leak environment in chemical plants. J. Hazard. Mater. 466, 133649 (2024).
Mahmood, L., Ghommem, M. & Bahroun, Z. Smart gas sensors: materials, technologies, practical applications, and use of machine learning—a review. J. Appl. Computational Mech. 9, 775–803 (2023).
Chen, Q. et al. Optical frequency comb-based aerostatic micro pressure sensor aided by machine learning. IEEE Sens. J. 23, 21078–21083 (2023).
Armas, D., Zubiate, P., Zamarreno, C. R. & Matias, I. R. Ammonia gas optical sensor based on lossy mode resonances. IEEE Sens. Lett. 7, 1–4 (2023).
Zhao, Z., Xie, F., Ren, T. & Zhao, C. Atmospheric CO2 retrieval from satellite spectral measurements by a two-step machine learning approach. J. Quant. Spectrosc. Radiat. Transf. 278, 108006 (2022).
Han, J., Li, H., Cheng, J., Ma, X. & Fu, Y. Advances in metal oxide semiconductor gas sensor arrays based on machine learning algorithms. J. Mater. Chem. C 13, 4285–4303 (2025).
Zeng, Q. et al. Machine learning-assisted development of TMDs-type gas-sensitive materials for dissolved gases in oil-immersed transformer oils. Mater. Today Chem. 44, 102583 (2025).
Naganaboina, V. R., Jana, S. & Singh, S. G. Chemiresistive sensor array for quantitative prediction of CO and NO2 gas concentrations in their mixture using machine learning algorithms. Microchim. Acta 191, 756 (2024).
Singh, S. et al. Metal oxide-based gas sensor array for VOCs determination in complex mixtures using machine learning. Microchim. Acta 191, 196 (2024).
Luo, W., Dai, F., Liu, Y., Wang, X. & Li, M. Pulse-driven MEMS gas sensor combined with machine learning for selective gas identification. Microsyst. Nanoeng. 11, 72 (2025).
Wekalao, J. High-sensitivity terahertz gas sensor using graphene-enhanced metasurfaces with machine learning optimization. Plasmonics https://doi.org/10.1007/s11468-025-03079-0 (2025).
Wekalao, J. & Elamri, O. Dual-resonator mxene metasurface-based gas sensor with machine learning-enhanced surface plasmon resonance detection. Plasmonics https://doi.org/10.1007/s11468-025-02936-2 (2025).
Borozdin, P. et al. Temperature-based long-term stabilization of photoacoustic gas sensors using machine learning. Sensors 24, 7518 (2024).
Li, P., Lin, G., Chen, J. & Wang, J. Off-axis integral cavity carbon dioxide gas sensor based on machine-learning-based optimization. Sensors 24, 5226 (2024).
Hu, D., Yang, Z. & Huang, S. Machine learning prediction of perovskite sensors for monitoring the gas in lithium-ion battery. Sens. Actuators A: Phys. 369, 143835 (2024).
Karami, H. et al. Advanced evaluation techniques: gas sensor networks, machine learning, and chemometrics for fraud detection in plant and animal products. Sens. Actuators A—Phys. 370, 115192 (2024).
Mahdavi, H., Rahbarpour, S., Hosseini-Golgoo, S. M. & Jamaati, H. A single gas sensor assisted by machine learning algorithms for breath-based detection of COPD: A pilot study. Sens. Actuators A-Phys. 376, 115650 (2024).
Viet, N. N., Phuoc, P. H., Thong, L. V., Chien, N. V. & Van Hieu, N. A comparative study of machine learning models for identifying noxious gases through thermal fingerprint measurements and MOS sensors. Sens. Actuators A: Phys. 375, 115510 (2024).
Zhang, A. et al. Dual-gas sensing via SnO2-TiO2 heterojunction on MXene: Machine learning-enhanced selectivity and sensitivity for hydrogen and ammonia detection. Sens. Actuators B: Chem. 429, 137340 (2025).
Zhang, H., Zhao, Z., Chen, C. & Wu, L. PtRu nanoalloys decorated In2O3 nanoparticles: gas sensing performance, mechanism study and machine learning-assisted discrimination of multiple volatile organic compounds. Sens. Actuators B: Chem. 425, 136973 (2025).
Su, M., Guo, Y., Hong, X. & Zheng, Y. Machine-learning for discovery of descriptors for gas-sensing: a case study of doped metal oxides. Talanta 287, 127594 (2025).
Wang, Q., Xing, M., Sun, Y., Pan, X. & Jing, Y. Optical gas imaging for leak detection based on improved deeplabv3+model. Opt. Lasers Eng. 175, 108058 (2024).
Wang, J., Huang, Z., Xu, Y. & Xie, D. Gas-liquid two-phase flow measurement based on optical flow method with machine learning optimization model. Appl. Sci.: Basel 14, 3717 (2024).
Mansouri, T. S., Wang, H., Mariotti, D. & Maguire, P. Distinguishing methane from other hydrocarbons using machine learning and atmospheric pressure plasma optical emission spectroscopy. J. Phys. D: Appl. Phys. 57, 345202 (2024).
Kang, M., Son, J., Lee, B. & Nam, H. Reconstruction of the chemical gas concentration distribution using partial convolution-based image inpainting. Sensors 24, 4470 (2024).
Hu, J., Qian, H., Han, S., Zhang, P. & Lu, Y. Light-activated virtual sensor array with machine learning for non-invasive diagnosis of coronary heart disease. Nano-Micro Lett. 16, 274 (2024).
Guan, G. et al. Near-infrared off-axis cavity-enhanced optical frequency comb spectroscopy for CO2/CO dual-gas detection assisted by machine learning. ACS Sens 9, 820–829 (2024).
Golyak, I. S. et al. A hybrid learning approach to better classify exhaled breath’s infrared spectra: a noninvasive optical diagnosis for socially significant diseases. J. Biophotonics 17, 202400151 (2024).
Leng, T., Li, L. & Lee, C. Journal editorial: welcome to the new era of AI-enabled sensing. AI Sens. 1, 1361945 (2025).
Cho, I. et al. Deep-learning-based gas identification by time-variant illumination of a single micro-LED-embedded gas sensor. Light Sci. Appl. 12, 95 (2023).
Zeng, X. et al. An enhanced gas sensor data classification method using principal component analysis and synthetic minority over-sampling technique algorithms. Micromachines 15, 1501 (2024).
Wang, Y. et al. An artificial optical nose integrated by metal-organic frameworks three-dimensional photonic crystal array for identification of trace hazardous gases through machine learning integration. J. Environ. Chem. Eng. 13, 117043 (2025).
Tariq, A. et al. Modelling, mapping and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote sensing data. Heliyon 9, e13212 (2023).
Liu, H., Li, Q. & Gu, Y. A multi-task learning framework for gas detection and concentration estimation. Neurocomputing 416, 28–37 (2020).
Fan, H., Schaffernicht, E. & Lilienthal, A. J. Ensemble learning-based approach for gas detection using an electronic nose in robotic applications. Front. Chem. 10, 863838 (2022).
Yuan, X. et al. A cloud-edge collaborative framework for adaptive quality prediction modeling in IIoT. IEEE Sens. J. 24, 33656–33668 (2024).
Kumar, M., Walia, G. K., Shingare, H., Singh, S. & Gill, S. S. AI-based sustainable and intelligent offloading framework for IIoT in collaborative cloud-fog environments. IEEE Trans. Consum. Electron. 70, 1414–1422 (2024).
Haji-Aghajany, S., Rohm, W., Kryza, M. & Smolak, K. Machine learning-based wet refractivity prediction through GNSS troposphere tomography for ensemble troposphere conditions forecasting. IEEE Trans. Geosci. Remote Sens. 62, 1–18 (2024).
Zhao, D., Zhou, J., Zhai, J. & Li, K. A reinforcement learning based framework for holistic energy optimization of sustainable cloud data centers. IEEE Trans. Serv. Comput. 18, 15–28 (2025).
Nagnure, H. M., Prasad, T. & Kundu, D. Selective gas adsorption using graphitic carbon nitride: Exploring the role of molecular descriptors by artificial intelligence frameworks. J. Environ. Manag. 376, 124432 (2025).
Corradino, C., Jouve, P., La Spina, A. & Del Negro, C. Monitoring earth’s atmosphere with sentinel-5 TROPOMI and artificial intelligence: quantifying volcanic SO2 emissions. Remote Sens. Environ. 315, 114463 (2024).
Merenda, M., Porcaro, C. & Iero, D. Edge machine learning for AI-enabled IoT devices: a review. Sensors 20, 2533 (2020).
Sethi, P. & Sarangi, S. R. Internet of things: architectures, protocols, and applications. J. Electr. Comput. Eng. 2017, 1–25 (2017).
Gonzalez, E. et al. LoRa sensor network development for air quality monitoring or detecting gas leakage events. Sensors 20, 6225 (2020).
Edje, A. E., Abd Latiff, M. S. & Chan, W. H. IoT data analytic algorithms on edge-cloud infrastructure: a review. Digital Commun. Netw. 9, 1486–1515 (2023).
Zhang, L. et al. Near-infrared mobile cloud OA-ICOS sensor system for atmospheric carbon dioxide monitoring. Anal. Chem. 97, 4021–4030 (2025).
Hu, K. et al. A review of satellite-based CO2 data reconstruction studies: methodologies, challenges, and advances. Remote Sens 16, 3818 (2024).
Xue, C. et al. Smartphone case-based gas sensing platform for on-site acetone tracking. ACS Sens 7, 1581–1592 (2022).
Olawade, D. B. et al. Artificial intelligence in environmental monitoring: Advancements, challenges, and future directions. Hyg. Environ. Health Adv. 12, 1417568 (2024).
Cao, J. et al. Recent development of gas sensing platforms based on 2D atomic crystals. Research 2021, 9863038 (2021).
Wu, X. et al. Bionic olfactory neuron with in-sensor reservoir computing for intelligent gas recognition. Adv. Mater. 37, 2419159 (2025).
Cho, J. et al. A mixture-gas edge-computing multisensor device with generative learning framework. IEEE Sens. J. 24, 15023–15032 (2024).
Van Quang, T. et al. AI management platform for privacy-preserving indoor air quality control: Review and future directions. J. Build. Eng. 100, 111712 (2025).
Yuan, H., Yang, H., Li, R., Wang, J. & Tian, L. Personal safety monitoring system of electric power construction site based on AIoT Technology. J. Intell. Fuzzy Syst. 46, 493–504 (2024).
Winkler, N. P. et al. Super-resolution for gas distribution mapping. Sens. Actuators B: Chem. 419, 136267 (2024).
Liu, X. et al. Artificial intelligence-enhanced waveguide “photonic nose”- augmented sensing platform for VOC gases in mid-infrared. Small 20 (2024).
Xiao, Z. et al. Multimodal in-sensor computing system using integrated silicon photonic convolutional processor. Adv. Sci. 11, e2408597 (2024).
Wu, C. et al. Freeform direct-write and rewritable photonic integrated circuits in phase-change thin films. Sci. Adv. 10, 1361 (2024).
Xiao, Z. et al. Recent progress in silicon-based photonic integrated circuits and emerging applications. Adv. Opt. Mater. 11, 2301028 (2023).
Dong, B. et al. Higher-dimensional processing using a photonic tensor core with continuous-time data. Nat. Photonics 17, 1080–1088 (2023).
Huang, C. et al. Prospects and applications of photonic neural networks. Adv. Phys.: X 7 (2021).
Zhang, Y. et al. Reconfigurable electro-optic FET based on ferroelectric electrostatic doping toward optical field programmable gate arrays. ACS Photonics 11, 4761–4768 (2024).
Dong, Z. et al. Monolithic barium titanate modulators on silicon-on-insulator substrates. ACS Photonics 10, 4367–4376 (2023).
Wang, C. et al. Lithium tantalate photonic integrated circuits for volume manufacturing. Nature 629, 784–790 (2024).
Xu, S., Liu, W., Le, X. & Lee, C. Unveiling efficient acousto-optic modulation in silicon photonic devices via lithium niobate using transfer printing. Nano Lett. 24, 12964–12972 (2024).
Gao, L., Kou, D., Lin, R., Ma, W. & Zhang, S. Visual recognition of volatile organic compounds by photonic nose integrated with multiple metal-organic frameworks. Small 20, 2308641 (2024).
Yoon, M. et al. Scalable photonic nose development through corona phase molecular recognition. ACS Sens 9, 6311–6319 (2024).
Phan-Quang, G. C. et al. Tracking airborne molecules from afar: three-dimensional metal-organic framework-surface-enhanced raman scattering platform for stand-off and real-time atmospheric monitoring. ACS Nano 13, 12090–12099 (2019).
Meng, J., Balendhran, S., Sabri, Y., Bhargava, S. K. & Crozier, K. B. Smart mid-infrared metasurface microspectrometer gas sensing system. Microsyst. Nanoeng. 10, 74 (2024).
Kwon, S., Park, J.-H., Jang, H.-D., Nam, H. & Chang, D. E. A Sensor drift compensation method with a masked autoencoder module. Appl. Sci. 14, 2604 (2024).
Heng, Y., Zhou, Y., Nguyen, D. H., Nguyen, V. D. & Jiao, M. An electronic nose drift compensation algorithm based on semi-supervised adversarial domain adaptive convolutional neural network. Sens. Actuators B 422, 136642 (2025).
Se, H. et al. Online drift compensation framework based on active learning for gas classification and concentration prediction. Sens. Actuators B 398, 134716 (2024).
Xie, X. et al. SERS-based AI diagnosis of lung and gastric cancer via exhaled breath. Spectrochim. Acta A: Mol. Biomol. Spectrosc. 314, 124181 (2024).
SharathKumar, M., Heuvelink, E. & Marcelis, L. F. M. Vertical farming: moving from genetic to environmental modification. Trends Plant Sci. 25, 724–727 (2020).
Lochbaum, A. et al. Compact mid-infrared gas sensing enabled by an all-metamaterial design. Nano Lett. 20, 4169–4176 (2020).
Damdam, A. N. et al. IoT-enabled electronic nose system for beef quality monitoring and spoilage detection. Foods 12, 2227 (2023).
Butt, M. A. & Piramidowicz, R. Integrated photonic sensors for the detection of toxic gasses—a review. Chemosensors 12, 143 (2024).
Xie, J. et al. Artificial intelligence-enhanced “photonic nose” for mid-infrared spectroscopic analysis of trace volatile organic compound mixtures. Adv. Opt. Mater. 12, 2401582 (2024).
Zong, B. et al. Smart gas sensors: recent developments and future prospective. Nanomicro Lett. 17, 54 (2024).
Guo, S. et al. Development of a cloud-based epidermal MoSe2 device for hazardous gas sensing. Adv. Funct. Mater. 29 (2019).
Ren, Z. et al. Near-sensor edge computing system enabled by a CMOS compatible photonic integrated circuit platform using bilayer AlN/Si waveguides. Nanomicro Lett. 17, 261 (2025).
Shu, H. et al. Microcomb-driven silicon photonic systems. Nature 605, 457–463 (2022).
Liu, X. et al. Development of photonic in-sensor computing based on a mid-infrared silicon waveguide platform. ACS Nano 18, 22938–22948 (2024).
Liu, X. et al. Artificial intelligence-enhanced waveguide “photonic nose”-augmented sensing platform for VOC gases in mid-infrared. Small 20, e2400035 (2024).
Zhuge, Y. et al. Photonic Bayesian neural networks: leveraging programmable noise for robust and uncertainty-aware computing. Adv. Sci. 12, e2500525 (2025).
Pai, S. et al. Experimentally realized in situ backpropagation for deep learning in photonic neural networks. Science 380, 398–404 (2023).
Dong, B. et al. Partial coherence enhances parallelized photonic computing. Nature 632, 55–62 (2024).
Kim, S. et al. Nanoengineering approaches toward artificial nose. Front. Chem. 9, 629329 (2021).
Perkins, J. & Gholipour, B. Optoelectronic gas sensing platforms: from metal oxide lambda sensors to nanophotonic metamaterials. Adv. Photonics Res. 2, 2000141 (2021).
Nasrollah Gavgani, J., Tavakoli, N., Heidari, H. & Mahyari, M. Graphene-based nanocomposites sensors for detection of ammonia. Int. J. Environ. Anal. Chem. 104, 2834–2858 (2022).
Miah, M. R. et al. Polypyrrole-based sensors for volatile organic compounds (VOCs) sensing and capturing: a comprehensive review. Sens. Actuators A: Phys. 347, 113933 (2022).
Chowdhury, S. J. et al. On-chip hybrid integration of swept frequency distributed-feedback laser with silicon photonic circuits using photonic wire bonding. Opt. Express 32, 3085–3099 (2024).
Xie, Y. et al. Towards large-scale programmable silicon photonic chip for signal processing. Nanophotonics 13, 2051–2073 (2024).
Epping, R. & Koch, M. On-site detection of volatile organic compounds (VOCs). Molecules 28, 1598 (2023).
Alseekh, S. et al. Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices. Nat. Methods 18, 747–756 (2021).
Bajo-Fernandez, M., Souza-Silva, E. A., Barbas, C., Rey-Stolle, M. F. & Garcia, A. GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review. Front. Mol. Biosci. 10, 1295955 (2023).
Le, T. & Priefer, R. Detection technologies of volatile organic compounds in the breath for cancer diagnoses. Talanta 265, 124767 (2023).
Chen, X., Wreyford, R. & Nasiri, N. Recent advances in ethylene gas detection. Materials 15, 5813 (2022).
Lan, K., Liu, S., Wang, Z., Long, L. & Qin, G. High-performance pyramid-SiNWs biosensor for NH(3)gas detection. Nanotechnology 35, 105501 (2023).
Choi, D. et al. Bioelectrical nose platform using odorant-binding protein as a molecular transporter mimicking human mucosa for direct gas sensing. ACS Sens 7, 3399–3408 (2022).
Xiang, C. et al. 3D integration enables ultralow-noise isolator-free lasers in silicon photonics. Nature 620, 78–85 (2023).
Murtaza Rind, Y. et al. Broadband multifunctional metasurfaces enabling polarization multiplexed focused vortex array generation. Mater. Today Commun. 38, 107648 (2024).
Kacmoli, S. & Gmachl, C. F. Quantum cascade disk and ring lasers. Appl. Phys. Lett. 124 (2024).
Piotrowski, M. et al. Direct measurement of current-dependent optical losses in interband cascade lasers. Appl. Phys. Lett. 125 (2024).
Rodrigo, P. J. et al. Fast horizontal radial plume mapping of N2O using open-path absorption spectroscopy with a quantum-cascade laser. Atmos. Environ. 328, 120510 (2024).
Zhang, K., Mayer, R., Burghart, D., Boehm, G. & Belkin, M. A. Mid-infrared wavelength multiplexers on an InP platform. Nanophotonics https://doi.org/10.1038/s41598-017-07164-1 (2025).
Huang, W. et al. Simultaneous measurement of 13C-, 18O-, and 17O- isotopes of CO2 using a compact mid-infrared hollow waveguide gas sensor. Sensors Actuators B: Chem. 417 (2024).
Zhao, Y., Liu, Y., Liu, Q., Zhao, J. & Zhang, Y. -n Room-temperature operated fast reversible ammonia sensor based on hybrid optical fiber structure with temperature compensated function. Sens. Actuators B: -Chem. 408, 135472 (2024).
Matuck, L. et al. Towards smart and secure batteries: Linking pressure and temperature profiles with electrochemical behavior through hybrid optical fiber sensors. Chem. Eng. J. 500, 156806 (2024).
Dong, L. et al. Highly promising 2D/1D BP-C/CNT bionic opto-olfactory co-sensory artificial synapses for multisensory integration. Adv. Sci. 11 (2024).
Krochin-Yepez, P.-A., Scholz, U. & Zimmermann, A. CMOS-compatible measures for thermal management of phase-sensitive silicon photonic systems. Photonics 7, 6 (2020).
Ren, X. et al. Photorefractive and pyroelectric photonic memory and long-term stability in thin-film lithium niobate microresonators. npj Nanophotonics 2, 1 (2025).
Xie, W. et al. A versatile synthesis platform based on polymer cubosomes for a library of highly ordered nanoporous metal oxides particles. Adv. Mater. 36 (2024).
Solomatin, M. A. et al. Bottom-up designing nanostructured oxide libraries under a lab-on-chip paradigm towards a low-cost highly-selective E-nose. Anal. Chim. Acta 1333, 343387 (2025).
Gohel, V. R. et al. Multioxide combinatorial libraries: fusing synthetic approaches and additive technologies for highly orthogonal electronic noses. Lab Chip 24, 3810–3825 (2024).
Gong, X. et al. Size selective corona interactions from self-assembled rosette and single-walled carbon nanotubes. Small 18, e2104951 (2022).
Zheng, J. X. et al. Arbitrary fabrication of complex lithium niobate three-dimensional microstructures for second harmonic generation enhancement. Opt. Lett. 49, 850–853 (2024).
Tao, C., Xiao, R., Wang, Y., Qi, J. & Li, H. A general transitive transfer learning framework for cross-optical sensor remote sensing image scene understanding. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 16, 4248–4260 (2023).
Mena, M. d. C. R., Munoz, A., Sanz-Bobi, M. A., Gonzalez-Calvo, D. & Alvarez-Tejedor, T. Application of ensemble machine learning techniques to the diagnosis of the combustion in a gas turbine. Appl. Therm. Eng. 249 (2024).
Marvin, M. K. et al. Review of progress and implication of machine learning in geological carbon dioxide storage. Geosyst. Eng. https://doi.org/10.1080/12269328.2025.2499267 (2025).
Amorim, M. L. M. et al. Open-source data logger system for real-time monitoring and fault detection in bench testing. Inventions 9, 120 (2024).
Tang, C. et al. A comparative study on hydrocarbon detection using cepstrum-based methods. J. Appl. Geophys. 226, 105412 (2024).
Yu, L. & Zhang, M. Unsupervised gas pipeline network leakage detection method based on improved graph deviation network. J. Loss Prev. Process Ind. 91, 105396 (2024).
Zheng, X., Cheng, W., Xue, S. & Liao, R. Adaptive prediction and correction of low-concentration gas mixture concentration and abnormal concentration. Measurement 253, 117442 (2025).
Pereira, M. E., Deuermeier, J., Martins, R., Barquinha, P. & Kiazadeh, A. Unlocking neuromorphic vision: advancements in IGZO-based optoelectronic memristors with visible range sensitivity. ACS Appl. Electron. Mater. 6, 5230–5243 (2024).
Li, D., Zhou, H., Hui, X., He, X. & Mu, X. Plasmonic biosensor augmented by a genetic algorithm for ultra-rapid, label-free, and multi-functional detection of COVID-19. Anal. Chem. 93, 9437–9444 (2021).
Lemes, E. M. Raman spectroscopy—a visit to the literature on plant, food, and agricultural studies. J. Sci. Food Agric. 105, 2128–2133 (2025).
Kneipp, J., Seifert, S. & Garber, F. SERS microscopy as a tool for comprehensive biochemical characterization in complex samples. Chem. Soc. Rev. 53, 7641–7656 (2024).
Liu, Y. et al. Intelligent point-of-care biosensing platform based on luminescent nanoparticles and microfluidic biochip with machine vision algorithm analysis. Nanomicro Lett. 17, 215 (2025).
Ren, S. et al. A microchip based Z-cell absorbance detector integrating micro-lenses and slits for portable liquid chromatography. J. Chromatogr. A 1730, 465099 (2024).
Jiao, D. et al. Rapid detection of glycosylated hemoglobin levels by a microchip liquid chromatography system in gradient elution mode. Anal. Chim. Acta 1288, 342186 (2024).
Jiao, D. et al. Performance evaluation of a 3D split-and-recombination micromixer with asymmetric structures. J. Micromech. Microeng. 32, 075007 (2022).
Jiao, D. et al. Compact photometric detector integrated with separation microchip for potential portable liquid chromatography system. J. Chromatogr. A 1731, 465175 (2024).
Kumar, V., Raghuwanshi, S. K. & Kumar, S. Advances in nanocomposite thin-film-based optical fiber sensors for environmental health monitoring—a review. IEEE Sens. J. 22, 14696–14707 (2022).
Chowdhury, M. A. Z. & Oehlschlaeger, M. A. Deep learning for gas sensing via infrared spectroscopy. Sensors 24, 20240314 (2024).
Hashemitaheri, M., Ebrahimi, E., de Silva, G. & Attariani, H. Optical sensor for BTEX detection: Integrating machine learning for enhanced sensing. Adv. Sens. Energy Mater. 3, 100114 (2024).
Chowdhury, M. A. Z., Rice, T. E. & Oehlschlaeger, M. A. TSMC-Net: deep-learning multigas classification using THz absorption spectra. ACS Sens 8, 1230–1240 (2023).
Bae, G. et al. Impact of a diverse combination of metal oxide gas sensors on machine learning-based gas recognition in mixed gases. ACS Omega 6, 23155–23162 (2021).
Cho, S. Y. et al. Finding hidden signals in chemical sensors using deep learning. Anal. Chem. 92, 6529–6537 (2020).
Ma, N., Halley, S., Ramaiyan, K., Garzon, F. & Tsui, L.-k Comparison of machine learning algorithms for natural gas identification with mixed potential electrochemical sensor arrays. ECS Sens. 2, 011402 (2023).
Aliramezani, M., Norouzi, A. & Koch, C. R. A grey-box machine learning based model of an electrochemical gas sensor. Sens. Actuators B 321, 536–551 (2020).
Smith, K. R. et al. An improved low-power measurement of ambient NO2 and O3 combining electrochemical sensor clusters and machine learning. Atmos. Meas. Tech. 12, 1325–1336 (2019).
Tian, L. et al. Analysis of gas mixtures with broadband dual frequency comb spectroscopy and unsupervised learning neural network. Adv. Intell. Syst. 5 (2023).
Sun, Q., Liu, T., Xu, J., Li, H. & Huang, M. Rapid recognition and concentration prediction of gas mixtures based on SMLP. IEEE Trans. Instrum. Meas. 73, 1–9 (2024).
Ni, J., Yang, H., Yao, J., Li, Z. & Qin, P. Toxic gas dispersion prediction for point source emission using deep learning method. Hum. Ecol. Risk Assess.: Int. J. 26, 557–570 (2019).
Bao, N. et al. Sensing gas mixtures by analyzing the spatiotemporal optical responses of liquid crystals using 3d convolutional neural networks. ACS Sens 7, 2545–2555 (2022).
Sun, J. et al. Dual gas sensor with innovative signal analysis based on neural network. Sens. Actuators B 373, 132697 (2022).
Chowdhury, M. A. Z., Rice, T. E. & Oehlschlaeger, M. A. VOC-Net: a deep learning model for the automated classification of rotational THz spectra of volatile organic compounds. Appl. Sci. 12, 8447–1240 (2022).
Tian, L. et al. Retrieval of gas concentrations in optical spectroscopy with deep learning. Measurement 182, 109739 (2021).
Kornienko, V. V. et al. Machine learning for optical gas sensing: a leaky-mode humidity sensor as example. IEEE Sens. J. 20, 6954–6963 (2020).
Eo, M., Han, J. & Rhee, W. Deep learning framework with essential pre-processing techniques for improving mixed-gas concentration prediction. IEEE Access 11, 25467–25479 (2023).
Oh, J. et al. Machine learning-based discrimination of indoor pollutants using an oxide gas sensor array: High endurance against ambient humidity and temperature. Sens. Actuators B 364, 131894 (2022).
Djeziri, M. A. et al. A temporal-based SVM approach for the detection and identification of pollutant gases in a gas mixture. Appl. Intell. 52, 6065–6078 (2021).
Kang, M. et al. High accuracy real-time multi-gas identification by a batch-uniform gas sensor array and deep learning algorithm. ACS Sens 7, 430–440 (2022).
Narkhede, P. et al. Gas detection and identification using multimodal artificial intelligence based sensor fusion. Appl. Syst. Innov. 4, 3 (2021).
Kwon, D. et al. Low-power and reliable gas sensing system based on recurrent neural networks. Sens. Actuators B 340, 129258 (2021).
Qiao, Q. et al. MEMS-enabled on-chip computational mid-infrared spectrometer using silicon photonics. ACS Photonics 9, 2367–2377 (2022).
Yaqoob, U. & Younis, M. I. Chemical gas sensors: recent developments, challenges, and the potential of machine learning—a review. Sensors 21 (2021).
Seesaard, T., Goel, N., Kumar, M. & Wongchoosuk, C. Advances in gas sensors and electronic nose technologies for agricultural cycle applications. Comput. Electron. Agric. 193, 106673 (2022).
Hayasaka, T. et al. An electronic nose using a single graphene FET and machine learning for water, methanol, and ethanol. Microsyst. Nanoeng. 6, 50 (2020).
