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arxiv: 2603.12640 · v2 · submitted 2026-03-13 · ⚛️ physics.optics

Gas temperature measurement based on contrast reversal in mid-infrared CO2 images

Hideki T. Miyazaki , Takeshi Kasaya , Masahiro Saito , Kazuya Kimoto , Yutaro Tsuiki , Tetsuyuki Ochiai This is my paper

Pith reviewed 2026-05-15 12:20 UTC · model grok-4.3

classification ⚛️ physics.optics
keywords gas temperaturemid-infrared imagingCO2 absorptioncontrast reversaloptical gas imagingline reversalnoninvasive measurementengine exhaust
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The pith

Gas temperature is given by the background temperature where the CO2 image contrast reverses in mid-infrared.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper demonstrates a method to measure gas temperature noninvasively using optical gas imaging with a mid-infrared camera tuned to the CO2 absorption at 4.3 micrometers. Gas flows appear bright or dark depending on whether they are hotter or cooler than the background. By varying the background temperature, the image of the gas vanishes at the point where temperatures match, and then contrast reverses. This vanishing point directly indicates the gas temperature. The approach revives the classical line reversal method with modern infrared technology and enables two-dimensional and dynamic measurements.

Core claim

When the background temperature is varied continuously, the gas image vanishes transiently and then the contrast reverses. The specific background temperature at the point when the gas image disappears provides the gas temperature. This is an evolved implementation of the classical line reversal method made possible by advanced infrared devices.

What carries the argument

Contrast reversal in narrowband mid-infrared images at the CO2 absorption wavelength of 4.3 micrometers, where the gas becomes invisible to the camera when its temperature equals the background temperature.

If this is right

  • Two-dimensional temperature mapping of gas flows becomes possible.
  • Dynamic temperature emissions from engine exhaust can be measured.
  • Human breathing can be analyzed for temperature changes.
  • Noninvasive measurement avoids physical probes in the gas flow.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • This method might apply to other infrared-absorbing gases with appropriate camera filters.
  • Combining it with concentration measurements could yield simultaneous temperature and density maps.
  • Real-time applications in industrial monitoring or medical diagnostics could follow from the dynamic capability.

Load-bearing premise

The contrast reversal occurs exactly when the gas temperature equals the background temperature without significant effects from scattering, non-uniform concentration, or camera issues.

What would settle it

Compare the background temperature at image disappearance against a thermocouple measurement of the gas temperature in a controlled uniform flow.

Figures

Figures reproduced from arXiv: 2603.12640 by Hideki T. Miyazaki, Kazuya Kimoto, Masahiro Saito, Takeshi Kasaya, Tetsuyuki Ochiai, Yutaro Tsuiki.

Figure 1
Figure 1. Figure 1: Overview of gas temperature measurement based on contrast reversal. (a) Proposed [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Spectra related to radiative transfer for [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Contrast reversal behavior for CO2-containing gas at temperature 𝑇୥ = 50°C observed by a CO2 imaging camera with responsivity 𝑅஝ and a finite bandwidth. (a) Relationship of signal difference Δ𝐼ୖ to light source temperature 𝑇ୱ for uniform gas with temperature 𝑇୥ = 50°C and various column densities 𝜁 (50°C) shown in legend. (b) Δ𝐼ୖ–𝑇ୱ relation for nonuniform gas with Gaussian-distributed temperature and conc… view at source ↗
Figure 4
Figure 4. Figure 4: Measurement system. (a) Setup for measuring gas temperature [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Gas temperature determination by contrast reversal for a 10% CO [PITH_FULL_IMAGE:figures/full_fig_p012_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Gas temperature determination by contrast reversal for a 1% CO [PITH_FULL_IMAGE:figures/full_fig_p014_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Gas temperature determination by contrast reversal for a 10% CO [PITH_FULL_IMAGE:figures/full_fig_p015_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Temperature measurement of air from a hair dryer. (a) Measurement setup. A cylinder [PITH_FULL_IMAGE:figures/full_fig_p017_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Temperature measurement of exhaust gas from a diesel engine. (a) Measurement setup. [PITH_FULL_IMAGE:figures/full_fig_p018_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Temperature measurement of human breath. (a) Measurement setup. (b) Signal [PITH_FULL_IMAGE:figures/full_fig_p020_10.png] view at source ↗
read the original abstract

We demonstrate noninvasive measurement of gas temperature based on the optical gas imaging. Gas flows containing carbon dioxide (CO2) appear as either bright or dark images, depending on the relative temperatures of the background and the gas, when using a narrowband mid-infrared camera tuned to the CO2 absorption wavelength at 4.3 micrometers. When the background temperature is varied continuously, the gas image vanishes transiently and then the contrast reverses. The specific background temperature at the point when the gas image disappears provides the gas temperature. This technique is an evolved implementation of the classical line reversal method, made possible by advanced infrared devices. We also apply this technique to two-dimensional temperature mapping and to dynamic emissions from engine exhaust and human breathing.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper claims a noninvasive gas temperature measurement technique using mid-infrared CO2 imaging at 4.3 μm with a narrowband camera. Gas flows appear bright or dark depending on the temperature difference with the background; by continuously varying the background temperature until the gas image vanishes (contrast reversal), the gas temperature is taken to equal that background temperature. The method is presented as an evolved line-reversal technique and is demonstrated for 2D temperature mapping as well as dynamic cases including engine exhaust and human breathing.

Significance. If the central claim holds with quantified accuracy, the approach would provide a simple, camera-based route to spatially resolved gas temperatures in flowing or transient systems without probes or lasers. It leverages existing optical gas imaging hardware and revives a classical spectroscopic principle for practical use in combustion diagnostics and respiratory monitoring.

major comments (2)
  1. [Abstract / contrast-reversal principle] Abstract and the description of the contrast-reversal principle: the claim that the gas image disappears precisely when T_gas equals background temperature holds only in the optically thick limit (τ ≫ 1). The observed radiance follows I = I_bg exp(−τ) + B(T_gas)(1 − exp(−τ)); for the moderate optical depths expected in engine exhaust or exhaled breath (τ ∼ 0.1–2), the null point shifts by an amount that depends on both τ and the filter transmission. No τ measurements, corrections, or sensitivity analysis are reported, so the quoted temperatures carry an unquantified systematic offset.
  2. [Applications to engine exhaust and human breathing] Applications section (engine exhaust and breathing examples): without reported error bars, repeated measurements, or independent validation (e.g., thermocouple or laser absorption), it is impossible to assess whether the observed reversal temperatures match the true gas temperature within the claimed precision.
minor comments (2)
  1. [Figures and methods] Figure captions and text should explicitly state the camera filter bandwidth and any assumptions about gas concentration uniformity.
  2. [Theory / methods] The manuscript would benefit from a short derivation or reference to the radiative-transfer expression used to interpret the reversal point.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the insightful comments on our manuscript. We have carefully considered the points raised and provide point-by-point responses below. Revisions have been made to clarify the underlying principle and to strengthen the presentation of the results.

read point-by-point responses

  1. Referee: [Abstract / contrast-reversal principle] Abstract and the description of the contrast-reversal principle: the claim that the gas image disappears precisely when T_gas equals background temperature holds only in the optically thick limit (τ ≫ 1). The observed radiance follows I = I_bg exp(−τ) + B(T_gas)(1 − exp(−τ)); for the moderate optical depths expected in engine exhaust or exhaled breath (τ ∼ 0.1–2), the null point shifts by an amount that depends on both τ and the filter transmission. No τ measurements, corrections, or sensitivity analysis are reported, so the quoted temperatures carry an unquantified systematic offset.

    Authors: We appreciate the referee highlighting this aspect of the radiative transfer. However, the background radiance I_bg is not constant; it corresponds to the blackbody emission B(T_bg) at the varying background temperature. The equation then becomes I = B(T_bg) exp(−τ) + B(T_gas)(1 − exp(−τ)). For the observed intensity I to equal the background intensity B(T_bg), it follows directly that B(T_gas) = B(T_bg), or T_gas = T_bg, independent of the value of τ. This holds as long as the same narrowband filter is used for both the gas emission and the background, which it is. We have added an explicit derivation of this result to the revised manuscript to prevent misunderstanding. Consequently, no corrections for optical depth or sensitivity analysis are required, and there is no systematic offset. revision: yes

  2. Referee: [Applications to engine exhaust and human breathing] Applications section (engine exhaust and breathing examples): without reported error bars, repeated measurements, or independent validation (e.g., thermocouple or laser absorption), it is impossible to assess whether the observed reversal temperatures match the true gas temperature within the claimed precision.

    Authors: We agree that the applications would benefit from additional quantitative support. In the revised version, we have added error bars to the reported temperatures, derived from the temporal variation in the image contrast during the background temperature sweep. For the engine exhaust measurements, we now include data from multiple trials showing consistency within the estimated uncertainty. The human breathing example is presented primarily to illustrate the dynamic capability of the method; we have added a note acknowledging the lack of independent validation for this case and the challenges in performing such validation for transient human breath. We believe these additions allow better assessment of the method's precision. revision: partial

Circularity Check

0 steps flagged

No circularity; temperature from contrast null follows directly from radiative transfer without reduction to fitted inputs or self-citations

full rationale

The manuscript derives the gas temperature from the background temperature at image disappearance by invoking the classical line-reversal principle applied to CO2 absorption at 4.3 μm. The abstract and description state that the null occurs when gas and background radiances match, which is a direct consequence of the radiative transfer equation I = I_bg * exp(-τ) + B(T_gas) * (1 - exp(-τ)) evaluated at the observed contrast reversal. No parameter is fitted to data and then re-used as a prediction; no uniqueness theorem or ansatz is imported via self-citation; the result is not a renaming of an empirical pattern. The derivation chain is therefore self-contained against external optical physics benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the domain assumption that contrast zero corresponds exactly to temperature equality, with no free parameters or new entities introduced in the abstract description.

axioms (1)
  • domain assumption Contrast reversal occurs exactly when gas and background temperatures are equal
    This is the foundational principle of the line reversal method applied to imaging.

pith-pipeline@v0.9.0 · 5439 in / 1100 out tokens · 48279 ms · 2026-05-15T12:20:14.222617+00:00 · methodology

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Reference graph

Works this paper leans on

59 extracted references · 59 canonical work pages

  1. [1]

    H. D. Baker, E. A. Ryder, and N. H. Baker, Temperature Measurement in Engineering, Vol. II (Wiley, 1961)

    work page 1961

  2. [2]

    Review of temperature measurement,

    P. R. N. Childs, J. R. Greenwood, and C. A. Long, “Review of temperature measurement,” Rev. Sci. Instrum. 71(8), 2959–2978 (2000)

    work page 2000

  3. [3]

    Measurement of flame temperature distribution by IR emission computed tomography,

    H. Uchiyama, M. Nakajima, and S. Yuta, “Measurement of flame temperature distribution by IR emission computed tomography,” Appl. Opt. 24(23), 4111–4116 (1985)

    work page 1985

  4. [4]

    Two-dimensional temperature determination in sooting flames by filtered Rayleigh scattering,

    D. Hoffman, K.-U. Münch, and A. Leipertz, “Two-dimensional temperature determination in sooting flames by filtered Rayleigh scattering,” Opt. Lett. 21(7), 525–527 (1996)

    work page 1996

  5. [5]

    Rotational Raman interferometric measurement of flame temperatures,

    E. J. Burlbaw and R. L. Armstrong, “Rotational Raman interferometric measurement of flame temperatures,” Appl. Opt. 22(18), 2860–2866 (1983)

    work page 1983

  6. [6]

    CARS temperature and species measurements in augmented jet engine exhausts,

    A. C. Eckbreth, G. M. Dobbs, J. H. Stufflebeam, et al., “CARS temperature and species measurements in augmented jet engine exhausts,” Appl. Opt. 23(9), 1328–1339 (1984)

    work page 1984

  7. [7]

    CO concentration and temperature sensor for combustion gases using quantum-cascade laser absorption near 4.7 μm,

    W. Ren, A. Farooq, D. F. Davidson, et al., “CO concentration and temperature sensor for combustion gases using quantum-cascade laser absorption near 4.7 μm,” Appl. Phys. B 107, 849–860 (2012)

    work page 2012

  8. [8]

    Optical methods for the determination of flame temperatures. I. two-color and line-reversal techniques,

    S. S. Penner, “Optical methods for the determination of flame temperatures. I. two-color and line-reversal techniques,” Am. J. Phys. 17(7), 422–429 (1949)

    work page 1949

  9. [9]

    Über eine einfache Methode, die Temperatur leuchtender Flammen zu bestimmen,

    F. Kurlbaum, “Über eine einfache Methode, die Temperatur leuchtender Flammen zu bestimmen,” Physikalische Zeits. 3(9), 187–188 (1902)

    work page 1902

  10. [10]

    Zur Temperaturbestimmung von Flammen,

    O. Lummer and E. Pringsheim, “Zur Temperaturbestimmung von Flammen,” Physikalische Zeits. 3(11), 233– 235 (1902)

    work page 1902

  11. [11]

    Sur la température des flammes,

    C. Féry, “Sur la température des flammes,” Comptes Rendus 137, 909–912 (1903)

    work page 1903

  12. [12]

    Sur le rayonnement et la température des flammes de bec Bunsen,

    E. Bauer, “Sur le rayonnement et la température des flammes de bec Bunsen,” Comptes Rendus 147, 1397– 1400 (1908)

    work page 1908

  13. [13]

    Prüfung der Strahlungsgesetze der Bunsenflamme,

    H. Schmidt, “Prüfung der Strahlungsgesetze der Bunsenflamme,” Ann. d. Physik 334(10), 971–1028 (1909)

    work page 1909

  14. [14]

    Die Temperatur der Acetylen-Sauerstoffflamme,

    F. Henning and C. Tingwaldt, “Die Temperatur der Acetylen-Sauerstoffflamme,” Z. Physik 48(11–12), 805– 823 (1928)

    work page 1928

  15. [15]

    Vollmer and K.-P

    M. Vollmer and K.-P. Mollmann, Infrared Thermal Imaging, 2nd ed. (Wiley, 2018), pp. 561–613

    work page 2018

  16. [16]

    Survey of autonomous gas leak detection and quantification with snapshot infrared spectral imaging,

    N. Hagen, “Survey of autonomous gas leak detection and quantification with snapshot infrared spectral imaging,” J. Opt. 22(10), 103001 (2020)

    work page 2020

  17. [17]

    Hyperspectral quantitative imaging of gas sources in the mid- infrared,

    M. A. Rodríguez-Conejo and J. Meléndez, “Hyperspectral quantitative imaging of gas sources in the mid- infrared,” Appl. Opt. 54(2), 141–149 (2015)

    work page 2015

  18. [18]

    Thermocamera, a macroscopic method for the study of pollution with nitrous oxide in operating theatres,

    C. Allander, P. Carlsson, B. Hallén, et al., “Thermocamera, a macroscopic method for the study of pollution with nitrous oxide in operating theatres,” Acta Anaesth. Scand. 25(1), 21–24 (1981)

    work page 1981

  19. [19]

    Imaging of hydrocarbon vapours and gases by infrared thermography,

    D. C. Strachan, N. A. Heard, W. J. Hossack, et al., “Imaging of hydrocarbon vapours and gases by infrared thermography,” J. Phys. E 18(6), 492–498 (1985)

    work page 1985

  20. [20]

    Gas imaging by infrared gas-correlation spectrometry,

    J. Sandsten, H. Edner, and S. Svanberg, “Gas imaging by infrared gas-correlation spectrometry,” Opt. Lett. 21(23), 1945–1947 (1996)

    work page 1945

  21. [21]

    Flow visualization of heated CO2 gas using thermal imaging,

    H. W. Yoon, M. H. Brenner, J. P. Rice, et al., “Flow visualization of heated CO2 gas using thermal imaging,” Proc. SPIE 6205, 62050U (2006)

    work page 2006

  22. [22]

    Infrared imagery of an air/CO2 axisymmetric jet,

    D. N. Gordge and R. H. Page, “Infrared imagery of an air/CO2 axisymmetric jet,” Exp. Fluids 14, 409–415 (1993)

    work page 1993

  23. [23]

    Visualization of air flow using infrared thermography,

    V. Narayanan, R. H. Page, and J. Seyed-Yagoobi, “Visualization of air flow using infrared thermography,” Exp. Fluids 34, 275–284 (2003)

    work page 2003

  24. [24]

    Induced infrared thermography: flow visualizations under the extreme conditions of an open volumetric receiver of a solar tower,

    A. Tiddens, K. Risthaus, M. Röger, et al., “Induced infrared thermography: flow visualizations under the extreme conditions of an open volumetric receiver of a solar tower,” Int. J. Heat Fluid Flow 65, 105-113 (2017). 25

    work page 2017

  25. [25]

    Patients wearing face masks during intravitreal injections may be at a higher risk of endophthalmitis,

    A. Hadayer, A. Zahavi, E. Livny, et al., “Patients wearing face masks during intravitreal injections may be at a higher risk of endophthalmitis,” Retina 40(9), 1651–1656 (2020)

    work page 2020

  26. [26]

    Optical gas imaging of carbon dioxide at tracheal extubation: a novel technique for visualising exhaled breath,

    B. Murphy, R. Cahill, C. McCaul, et al., “Optical gas imaging of carbon dioxide at tracheal extubation: a novel technique for visualising exhaled breath,” Br. J. Anaesth. 126(2), e77–e78 (2021)

    work page 2021

  27. [27]

    Quantifying the effect of a mask on expiratory flows,

    P. Bourrianne, N. Xue, J. Nunes, et al., “Quantifying the effect of a mask on expiratory flows,” Phys. Rev. Fluids 6(11), 110511 (2021)

    work page 2021

  28. [28]

    Relationship between surgical field contamination by patient's exhaled air and the state of the drapes during eye surgery,

    M. Morioka, Y. Takamura, H. T. Miyazaki, et al., “Relationship between surgical field contamination by patient's exhaled air and the state of the drapes during eye surgery,” Sci. Rep. 13, 5713 (2023)

    work page 2023

  29. [29]

    Quantitatively visualizing airborne disease transmission risks of different exhalation activities through CO2 imaging,

    Y. Peng and M. Yao, “Quantitatively visualizing airborne disease transmission risks of different exhalation activities through CO2 imaging,” Environ. Sci. Technol. 57(17), 6865–6875 (2023)

    work page 2023

  30. [30]

    Air flow temperature measurements using infrared thermography,

    N. Vinnichenko, Y. Plaksina, O. Yakimchuk, et al., “Air flow temperature measurements using infrared thermography,” Quant. InfraRed Thermogr. J. 14(1), 107–121 (2017)

    work page 2017

  31. [31]

    Gas temperature and boundary layer thickness measurements of an inert mixture using filtered broadband natural species emission (Part I),

    M. Al-Sadoon and O. Samimi-Abianeh, “Gas temperature and boundary layer thickness measurements of an inert mixture using filtered broadband natural species emission (Part I),” J. Quant. Spectrosc. Radiat. Transfer 241, 106749 (2020)

    work page 2020

  32. [32]

    Volume flow calculations on gas leaks imaged with infrared gas-correlation,

    J. Sandsten and M. Andersson, “Volume flow calculations on gas leaks imaged with infrared gas-correlation,” Opt. Express 20(18), 20318 (2012)

    work page 2012

  33. [33]

    Passive Fourier-transform infrared spectroscopy of chemical plumes: an algorithm for quantitative interpretation and real-time background removal,

    M. L. Polak, J. L. Hall, and K. C. Herr, “Passive Fourier-transform infrared spectroscopy of chemical plumes: an algorithm for quantitative interpretation and real-time background removal,” Appl. Opt. 34(24), 5406–5412 (1995)

    work page 1995

  34. [34]

    Real-time gas-correlation imaging employing thermal background radiation,

    J. Sandsten, P. Weibring, H. Edner, et al., “Real-time gas-correlation imaging employing thermal background radiation,” Opt. Express 6(4), 92–103 (2000)

    work page 2000

  35. [35]

    Siegel and J

    R. Siegel and J. R. Howell, Thermal Radiation Heat Transfer, 2nd ed. (Hemisphere, 1980)

    work page 1980

  36. [36]

    The HITRAN2020 molecular spectroscopic database,

    I. E. Gordon, L. S. Rothman, R. J. Hargreaves, et al., “The HITRAN2020 molecular spectroscopic database,” J. Quant. Spectrosc. Radiat. Transfer 277, 107949 (2022)

    work page 2022

  37. [37]

    J. R. Howell, M. P. Menguec, K. Daun, et al., Thermal Radiation Heat Transfer, 7th ed. (CRC Press, 2020)

    work page 2020

  38. [38]

    Spectroscopic flame temperature measurements and their physical significance—I. theoretical concepts—a critical review,

    I. Reif, V. A. Fassel, and R. N. Kniseley, “Spectroscopic flame temperature measurements and their physical significance—I. theoretical concepts—a critical review,” Spectrochimica Acta 28B(3), 105–123 (1973)

    work page 1973

  39. [39]

    Temperature measurements in flames—a review,

    M. L. Elder and J. D. Winefordner, “Temperature measurements in flames—a review,” in Progress in Analytical Atomic Spectroscopy, Vol. 6 (Pergamon, 1983), pp. 293–427

    work page 1983

  40. [40]

    Some remarks on the temperature measurement of nonisothermal flames by the line reversal technique,

    Y. Sasaki, “Some remarks on the temperature measurement of nonisothermal flames by the line reversal technique,” Jpn. J. Appl. Phys. 5(5), 439–446 (1966)

    work page 1966

  41. [41]

    Effects of cold boundary layers on spectroscopic temperature measurements in combustion gas flows,

    J. W. Daily and C. H. Kruger, “Effects of cold boundary layers on spectroscopic temperature measurements in combustion gas flows,” J. Quant. Spectrosc. Radiat. Transfer 17(3), 327–338 (1977)

    work page 1977

  42. [42]

    Simultaneous fast response NO and HC measurements from a spark ignition engine,

    K. St. J. Reavell, N. Collings, M. Peckham, et al., “Simultaneous fast response NO and HC measurements from a spark ignition engine,” SAE Tech. Pap. 971610, 121–128 (1997)

    work page 1997

  43. [43]

    Cycle-to-cycle NO and NOx emissions from a HSDI diesel engine,

    F. Leach, M. Davy, and M. Peckham, “Cycle-to-cycle NO and NOx emissions from a HSDI diesel engine,” J. Eng. Gas Turbines Power 141(8), 081007 (2019)

    work page 2019

  44. [44]

    In-cylinder CO2 sampling using skip-firing method,

    M. Duckhouse, M. Peckham, B. Mason, et al., “In-cylinder CO2 sampling using skip-firing method,” J. Eng. Gas Turbines Power 141(8), 081018 (2019)

    work page 2019

  45. [45]

    Measurement of temperature and relative humidity in exhaled breath,

    E. Mansour, R. Vishinkin, S. Rihet, et al., “Measurement of temperature and relative humidity in exhaled breath,” Sens. Actuators, B 304, 127371 (2020)

    work page 2020

  46. [46]

    Temperature distribution over the human head, especially in the cold,

    M. Edwards and A. C. Burton, “Temperature distribution over the human head, especially in the cold,” J. Appl. Physiol. 15(2), 209–211 (1960)

    work page 1960

  47. [47]

    Thermographic mapping of the skin surface of the head in bald-headed male subjects,

    L. E. Hauvik and J. B. Mercer, “Thermographic mapping of the skin surface of the head in bald-headed male subjects,” J. Therm. Biol. 37(7), 510–516 (2012)

    work page 2012

  48. [48]

    A new evaluation of heat distribution on facial skin surface by infrared thermography,

    D. S. Haddad, M. L. Brioschi, M. G. Baladi, et al., “A new evaluation of heat distribution on facial skin surface by infrared thermography,” Dentomaxillofac Radiol. 45(4), 20150264 (2016)

    work page 2016

  49. [49]

    A unified model for light emission from solids,

    J. J. Greffet and A. Loirette-Pelous, “A unified model for light emission from solids,” Nat. Nanotechnol. 21(2), 184–197 (2026)

    work page 2026

  50. [50]

    Quantum cascade detectors,

    F. R. Giorgetta, E. Baumann, M. Graf, et al., “Quantum cascade detectors,” IEEE J. Quantum Electron. 45(8), 1039 (2009)

    work page 2009

  51. [51]

    Quantum cascade detectors: a review,

    A. Delga, “Quantum cascade detectors: a review,” in Mid-infrared Optoelectronics (Elsevier, 2020), pp. 337– 377

    work page 2020

  52. [52]

    Antenna-enhanced high-resistance photovoltaic infrared detectors based on quantum ratchet architecture,

    H. T. Miyazaki, T. Mano, T. Noda, et al., “Antenna-enhanced high-resistance photovoltaic infrared detectors based on quantum ratchet architecture,” Appl. Phys. Lett. 124(23), 231103 (2024)

    work page 2024

  53. [53]

    Infrared laser-absorption sensing for combustion gases,

    C. S. Goldenstein, R. M. Spearrin, J. B. Jeffries, et al., “Infrared laser-absorption sensing for combustion gases,” Prog. Energy Combustion Sci. 60, 132–176 (2017)

    work page 2017

  54. [54]

    Absorption measurements of water-vapor concentration, temperature, and line-shape parameters using a tunable InGaAsP diode laser,

    M. P. Arroyo and R. K. Hanson, “Absorption measurements of water-vapor concentration, temperature, and line-shape parameters using a tunable InGaAsP diode laser,” Appl. Opt. 32(30), 6104–6116 (1993)

    work page 1993

  55. [55]

    Near-infrared diode laser absorption diagnostic for temperature and water vapor in a scramjet combustor,

    J. T. C. Liu, G. B. Rieker, J. B. Jeffries, et al., “Near-infrared diode laser absorption diagnostic for temperature and water vapor in a scramjet combustor,” Appl. Opt. 44(31), 6701–6711 (2005)

    work page 2005

  56. [56]

    Tomographic imaging of carbon dioxide in the exhaust plume of large commercial aero-engines,

    A. Upadhyay, M. Lengden, G. Enemali, et al., “Tomographic imaging of carbon dioxide in the exhaust plume of large commercial aero-engines,” Appl. Opt. 61(28), 8540–8552 (2022). 26

    work page 2022

  57. [57]

    Application of UVAS and TDLAS-based multi-combustion-parameter diagnosis using computerized tomography,

    W. Zhou, R. Zhang, X. Qin, et al., “Application of UVAS and TDLAS-based multi-combustion-parameter diagnosis using computerized tomography,” Opt. Lasers Eng. 178, 108255 (2024)

    work page 2024

  58. [58]

    Three-dimensional reconstruction of a leaking gas cloud based on two scanning FTIR remote-sensing imaging systems,

    Y. Hu, L. Xu, H. Xu, et al., “Three-dimensional reconstruction of a leaking gas cloud based on two scanning FTIR remote-sensing imaging systems,” Opt. Express 30(14), 25581–25596 (2022)

    work page 2022

  59. [59]

    Concentration-aware real-time 3D reconstruction of leaking gas clouds based on two-view bandpass optical gas imaging,

    L. Cai, Z. Shi, C. Zi, et al., “Concentration-aware real-time 3D reconstruction of leaking gas clouds based on two-view bandpass optical gas imaging,” Opt. Express 33(3), 5310–5327 (2025)

    work page 2025