Mid-infrared Imaging Research Articles

Mid-infrared edge-enhanced imaging via angle-selective nonlinear filtering

We propose a novel, to the best of our knowledge, scheme for mid-infrared upconversion imaging with high tunability between bright-field and edge-enhanced modalities. The involved engineering of the nonlinear process favors shaping the optical transfer function of the imaging system. Consequently, a nonlinear angle-selective filter can be configured to perform an all-optical Fourier processing of the image, which highly depends on phase-matching parameters. We numerically demonstrate the ability to switch modalities between the bright-field and edge-enhanced imaging by tuning the crystal temperature and simultaneously acquiring both information by dichromatic illumination. Notably, the achieved reconfigurability is realized without changing the imaging settings, which contrasts with previous instantiations based on pump adaptation. Therefore, the proposed architecture of upconversion imagers would pave a novel way to implement layout-compact and all-optical processing for infrared images.

Impacts of scattering of non-gray gas particulate mixtures on radiative heat transfer and mid-infrared image temperature in a 2D oxy-coal combustion furnace

Impacts of scattering of non-gray gas particulate mixtures on radiative heat transfer and mid-infrared image temperature in a 2D oxy-coal combustion furnace

High-resolution mid-infrared image transport by a chalcogenide multi-core fiber

Abstract We have successfully demonstrated high-resolution mid-infrared image transport by a multi-core fiber made of chalcogenide glasses.
The fiber cores are arranged on a triangular lattice, and adjacent cores have different core diameters to reduce cross-talk between them.
We tested the resolution of the fiber using different fineness patterns and found that it can resolve better than 25 lp/mm at a wavelength of 9.3 μm.
This demonstrates the potential of the fiber for high-resolution thermal imaging inside the human body.

Integrated mid-infrared sensing and ultrashort lasers based on wafer-level Td-WTe2 Weyl semimetal

There is an urgent need for infrared (IR) detection systems with high-level miniaturization and room-temperature operation capability. The rising star of two-dimensional (2D) semimetals with extraordinary optoelectronic properties can fulfill these criteria. However, the formidable challenges with regard to large-scale patterning and substrate-selective requirements limit material deposition options for device fabrication. Here, we report a convenient and straightforward eutectic-tellurization transformation method for the wafer-level synthesis of 2D type-II Weyl semimetal WTe2. The non-cryogenic WTe2/Si Schottky junction device displays an ultrawide detection range covering 10.6 μm with a high detectivity of ∼109 Jones in the mid-infrared (MIR) region and a short response time of 1.3 μs. The detection performance has surpassed most reported IR sensors. On top of that, on-chip device arrays based on Schottky junction display an outstanding MIR imaging capability without cryogenic cooling, and 2D WTe2 Weyl semimetal can serve as a saturable absorber for stable Q-switched and mode-locked laser operation applications. Our work offers a viable route for wafer-scale vdW preparation of 2D semimetals, showcasing their intriguing potential in on-chip integrated MIR detection systems and ultrafast laser photonics.

Unveiling the HD 95086 system at mid-infrared wavelengths with JWST/MIRI

Context. Mid-infrared imaging of exoplanets and disks is now possible with the coronographs of the Mid-InfraRed Instrument (MIRI) on the James Webb Space Telescope (JWST). This wavelength range unveils new features of young directly imaged systems and allows us to obtain new constraints for characterizing the atmosphere of young giant exoplanets and associated disks. Aims. These observations aim to characterize the atmosphere of the planet HD 95086 b by adding mid-infrared information so that the various hypotheses about its atmospheric parameters values can be unraveled. Improved images of cirsumstellar disks are provided. Methods. We present the MIRI coronagraphic imaging of the system HD 95086 obtained with the F1065C, F1140, and F2300C filters at central wavelengths of 10.575 µm, 11.3 µm, and 23 µm, respectively. We explored the method for subtracting the stellar diffraction pattern in the particular case when bright dust emitting at short separation is present. Furthermore, we compared different methods for extracting the photometry of the planet. Using the atmospheric models Exo-REM and ATMO, we measured the atmospheric parameters of HD 95086 b. Results. The planet HD 95086 b is detected at the two shortest MIRI wavelengths F1065C and F1140C. The contribution from the inner disk of the system is also detected. It is similar to that in the HR 8799 system. The outer colder belt is imaged at 23 µm. Background objects are observed in all filters. The mid-infrared photometry provides better constraints on the atmospheric parameters. We evaluate a temperature of 800–1050 K, consistent with one previous hypothesis that only used near-infrared data. The radius measurement of 1.0–1.14 RJup is better aligned with evolutionary models, but still smaller than predicted. These observations allow us to refute the hypothesis of a warm circumplanetary disk. Conclusions. HD 95086 is one of the first exoplanetary systems to be revealed at mid-infrared wavelengths. This highlights the interests and challenges of observations at these wavelengths.

Machine learning-assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues.

Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor-microenvironment where fibrillar collagen's architectural changes are associated with cancer progression. To address this need, we present a multimodal computational imaging method where mid-infrared spectral imaging (MIRSI) is employed with second harmonic generation (SHG) microscopy to identify fibrillar collagen in biological tissues. To demonstrate a multimodal approach where a morphology-specific contrast mechanism guides an MIRSI method to detect fibrillar collagen based on its chemical signatures. We trained a supervised machine learning (ML) model using SHG images as ground truth collagen labels to classify fibrillar collagen in biological tissues based on their mid-infrared hyperspectral images. Five human pancreatic tissue samples (sizes are in the order of millimeters) were imaged by both MIRSI and SHG microscopes. In total, 2.8million MIRSI spectra were used to train a random forest (RF) model. The other 68million spectra were used to validate the collagen images generated by the RF-MIRSI model in terms of collagen segmentation, orientation, and alignment. Compared with the SHG ground truth, the generated RF-MIRSI collagen images achieved a high average boundary -score (0.8 at 4-pixel thresholds) in the collagen distribution, high correlation (Pearson's 0.82) in the collagen orientation, and similarly high correlation (Pearson's 0.66) in the collagen alignment. We showed the potential of ML-aided label-free mid-infrared hyperspectral imaging for collagen fiber and tumor microenvironment analysis in tumor pathology samples.

Rapid Hyperspectral Photothermal Mid-Infrared Spectroscopic Imaging from Sparse Data for Gynecologic Cancer Tissue Subtyping.

Ovarian cancer detection has traditionally relied on a multistep process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled data sets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology.

Measurement of unburned methane emissions in laboratory flames using mid-infrared hyperspectral imaging

In this study, we present a novel method for measuring unburned methane (CH4) emissions in laboratory flames using mid-infrared hyperspectral imaging. Given the environmental significance of methane’s global warming potential, accurately quantifying emissions from combustion processes is critical. Our approach integrates an extended-area blackbody as the infrared source and a bandpass interference filter to mitigate issues of noise, low signal levels and detector saturation. This setup enabled high-resolution spectral analysis, capturing detailed concentration and temperature maps of methane around the flame. We tracked the dynamics of methane pockets escaping the flame using the hyperspectral imaging system in high-speed camera mode, providing insights into the behavior of unburned gases, such as the velocity of methane pockets. The study demonstrates the feasibility of this technique for assessing combustion efficiency by quantifying the flow of unburned methane through a control surface. Our findings suggest that mid-infrared hyperspectral imaging is a robust tool for remote sensing of methane emissions, offering significant advancements in the accurate measurement and analysis of combustion processes, and providing a benchmarking platform for measurement approaches intended for field applications.

Mid-infrared chemical imaging of living cells enabled by plasmonic metasurfaces.

Mid-Infrared (MIR) chemical imaging provides rich chemical information of biological samples in a label-free and non-destructive manner. Yet, its adoption to live-cell analysis is limited by the strong attenuation of MIR light in water, often necessitating cell culture geometries that are incompatible with the prolonged viability of cells and with standard high-throughput workflow. Here, we introduce a new approach to MIR microscopy, where cells are imaged through their localized near-field interaction with a plasmonic metasurface. Chemical contrast of distinct molecular groups provided sub-cellular resolution images of the proteins, lipids, and nucleic acids in the cells that were collected using an inverted MIR microscope. Time-lapse imaging of living cells demonstrated that their behaviors, including motility, viability, and substrate adhesion, can be monitored over extended periods of time using low-power MIR light. The presented approach provides a method for the non-perturbative MIR imaging of living cells, which is well-suited for integration with modern high-throughput screening technologies for the label-free, high-content chemical imaging of living cells.

Measurement of slagging thickness on the heating surfaces of a 330 MW subcritical boiler based on mid-infrared imaging technology

In this paper, a mid-infrared thermal imager and a Complementary Metal Oxide Semiconductor (CMOS) imaging device were employed to measure the slagging thickness on the heating surface in a 330 MW subcritical drum boiler. A way to establish the relationship between the slagging temperature and emissivity was proposed based on the Boom emissivity model and the Hadley thermal conductivity model, and then the slagging thickness was calculated by the Newtonian iterative method. In the superheater area, the average slagging thickness of the lower section was 8.6 mm, and it was 1.71 mm higher than that of the upper section. In the water-cooled wall area, the average slagging thickness of the right wall was 10.8 % larger than that of the left wall. To verify the accuracy of the calculated slagging thickness, the slagging image was measured by the direct visual probe, and the relative error was 7.69 %.

JWST MIRI flight performance: Imaging

The Mid-Infrared Instrument (MIRI) aboard the James Webb Space Telescope (JWST) provides the observatory with a huge advance in mid-infrared imaging and spectroscopy covering the wavelength range of 5–28 µm. This paper describes the performance and characteristics of the MIRI imager as understood during observatory commissioning activities, and through its first year of science operations. We discuss the measurements and results of the imager’s point spread function, flux calibration, background, distortion and flat fields as well as results pertaining to best observing practices for MIRI imaging, and discuss known imaging artefacts that may be seen during or after data processing. Overall, we show that the MIRI imager has met or exceeded all its pre-flight requirements, and we expect it to make a significant contribution to mid-infrared science for the astronomy community for years to come.

The Fraction of Dust Mass in the Form of Polycyclic Aromatic Hydrocarbons on 10–50 pc Scales in Nearby Galaxies

Polycyclic aromatic hydrocarbons (PAHs) are a ubiquitous component of the interstellar medium (ISM) in z ∼ 0 massive, star-forming galaxies and play key roles in ISM energy balance, chemistry, and shielding. Wide field-of-view, high-resolution mid-infrared (MIR) images from JWST provide the ability to map the fraction of dust in the form of PAHs and the properties of these key dust grains at 10–50 pc resolution in galaxies outside the Local Group. We use MIR JWST photometric observations of a sample of 19 nearby galaxies from the Physics at High Angular Resolution in Nearby GalaxieS (PHANGS) survey to investigate the variations of the PAH fraction. By comparison to lower-resolution far-infrared mapping, we show that a combination of the MIRI filters (R PAH = [F770W+F1130W]/F2100W) traces the fraction of dust by mass in the form of PAHs (i.e., the PAH fraction, or q PAH). Mapping R PAH across the 19 PHANGS galaxies, we find that the PAH fraction steeply decreases in H ii regions, revealing the destruction of these small grains in regions of ionized gas. Outside H ii regions, we find R PAH is constant across the PHANGS sample with an average value of 3.43 ± 0.98, which, for an illuminating radiation field of intensity 2–5 times that of the radiation field in the solar neighborhood, corresponds to q PAH values of 3%–6%.

Understanding the star formation efficiency in dense gas: Initial results from the CAFFEINE survey with ArTéMiS

Context. Despite recent progress, the question of what regulates the star formation efficiency (SFE) in galaxies remains one of the most debated problems in astrophysics. According to the dominant picture, star formation (SF) is regulated by turbulence and feedback, and the SFE is ~1–2% or less per local free-fall time on all scales from Galactic clouds to high-redshift galaxies. In an alternate scenario, the star formation rate (SFR) in galactic disks is linearly proportional to the mass of dense gas above some critical density threshold ~104 cm–3. Aims. We aim to discriminate between these two pictures thanks to high-resolution submillimeter and mid-infrared imaging observations, which trace both dense gas and young stellar objects (YSOs) for a comprehensive sample of 49 nearby massive SF complexes out to a distance of d ~ 3 kpc in the Galactic disk. Methods. We used data from CAFFEINE, a complete 350/450 µm survey with APEX/ArTéMiS of the densest portions of all southern molecular clouds at d ≲ 3 kpc, in combination with Herschel data to produce column density maps at a factor of ~4 higher resolution (8") than standard Herschel column density maps (36″). Our maps are free of any saturation effect around luminous high-mass pro-tostellar objects and resolve the structure of dense gas and the typical ~0.1 pc width of molecular filaments out to 3 kpc, which is the most important asset of the present study and is impossible to achieve with Herschel data alone. Coupled with SFR estimates derived from Spitzer mid-infrared observations of the YSO content of the same clouds, this allowed us to study the dependence of the SFE on density in the CAFFEINE clouds. We also combine our findings with existing SF efficiency measurements in nearby clouds to extend our analysis down to lower column densities. Results. Our results suggest that the SFE does not increase with density above the critical threshold and support a scenario in which the SFE in dense gas is approximately constant (independent of free-fall time). However, the SF efficiency measurements traced by Class I YSOs in nearby clouds are more inconclusive, since they are consistent with both the presence of a density threshold and a dependence on density above the threshold. Overall, we suggest that the SF efficiency in dense gas is primarily governed by the physics of filament fragmentation into protostellar cores.

JWST-FEAST: Feedback in Emerging extrAgalactic Star clusTers: Calibration of Star Formation Rates in the Mid-infrared with NGC 628

New JWST near-infrared imaging of the nearby galaxy NGC 628 from the JWST Cycle 1 program Feedback in Emerging extrAgalactic Star clusTers (JWST-FEAST) is combined with archival JWST mid-infrared imaging to calibrate the 21 μm emission as a star formation rate (SFR) indicator at ∼120 pc scales. The Paα (1.8756 μm) hydrogen recombination emission line targeted by FEAST provides a reference SFR indicator that is relatively insensitive to dust attenuation, as demonstrated by combining this tracer with Hubble Space Telescope Hα imaging. Our analysis is restricted to regions that appear compact in nebular line emission and are sufficiently bright to mitigate effects of both age and stochastic sampling of the stellar initial mass function. We find that the 21 μm emission closely correlates with the nebular line emission, with a power law with exponent = 1.07 ± 0.01, in agreement with past results. We calibrate a hybrid SFR indicator using a combination of Hα and 24 μm (extrapolated from 21 μm) tracers and derive the proportionality constant between the two tracers, b = 0.095 ± 0.007, which is ∼3–5 times larger than previous derivations using large regions/entire galaxies. We model these discrepancies as an increasing contribution to the dust heating by progressively older stellar populations for increasing spatial scale, in agreement with earlier findings that star formation is hierarchically distributed in galaxies. Thus, the use of hybrid SFR indicators requires prior knowledge of the mean age of the stellar populations dominating the dust heating, which makes their application uncertain. Conversely, nonlinear calibrations of SFRs from L(24) alone are more robust, with a factor ≲ 2.5 variation across the entire range of L(24) luminosities from H ii regions to galaxies.

Cervical Cancer Tissue Analysis Using Photothermal Midinfrared Spectroscopic Imaging.

Hyperspectral photothermal mid-infrared spectroscopic imaging (HP-MIRSI) is an emerging technology with promising applications in cervical cancer diagnosis and quantitative, label-free histopathology. This study pioneers the application of HP-MIRSI to the evaluation of clinical cervical cancer tissues, achieving excellent tissue type segmentation accuracy of over 95%. This achievement stems from an integrated approach of optimized data acquisition, computational data reconstruction, and the application of machine learning algorithms. The results are statistically robust, drawing from tissue samples of 98 cervical cancer patients and incorporating over 40 million data points. Traditional cervical cancer diagnosis methods entail biopsy, staining, and visual evaluation by a pathologist. This process is qualitative, subject to variations in staining and subjective interpretations, and requires extensive tissue processing, making it costly and time-consuming. In contrast, our proposed alternative can produce images comparable to those from histological analyses without the need for staining or complex sample preparation. This label-free, quantitative method utilizes biochemical data from HP-MIRSI and employs machine-learning algorithms for the rapid and precise segmentation of cervical tissue subtypes. This approach can potentially transform histopathological analysis by offering a more accurate and label-free alternative to conventional diagnostic processes.

Structural Mapping of Protein Aggregates in Live Cells Modeling Huntington's Disease.

While protein aggregation is a hallmark of many neurodegenerative diseases, acquiring structural information on protein aggregates inside live cells remains challenging. Traditional microscopy does not provide structural information on protein systems. Routinely used fluorescent protein tags, such as Green Fluorescent Protein (GFP), might perturb native structures. Here, we report a counter-propagating mid-infrared photothermal imaging approach enabling mapping of secondary structure of protein aggregates in live cells modeling Huntington's disease. By comparing mid-infrared photothermal spectra of label-free and GFP-tagged huntingtin inclusions, we demonstrate that GFP fusions indeed perturb the secondary structure of aggregates. By implementing spectra with small spatial step for dissecting spectral features within sub-micrometer distances, we reveal that huntingtin inclusions partition into a β-sheet-rich core and a ɑ-helix-rich shell. We further demonstrate that this structural partition exists only in cells with the [RNQ+] prion state, while [rnq-] cells only carry smaller β-rich non-toxic aggregates. Collectively, our methodology has the potential to unveil detailed structural information on protein assemblies in live cells, enabling high-throughput structural screenings of macromolecular assemblies.

Overview Results of JWST Observations of Star-forming Clusters in the Extreme Outer Galaxy

The extreme outer Galaxy (EOG), which we define as the region of the Milky Way with a galactocentric radius of more than 18 kpc, provides an excellent opportunity to study star formation in an environment significantly different from that in the solar neighborhood because of its lower metallicity and lower gas density. We carried out near- and mid-infrared (NIR and MIR) imaging observations toward two star-forming clusters located in the EOG using JWST NIRCam and MIRI with nine filters: F115W, F150W, F200W, F350W, F405N, F444W, F770W, F1280W, and F2100W. In this paper, we present an overview of the observations, data reduction, and initial results. The NIR sensitivity is approximately 10–80 times better than our previous observation with the Subaru 8.2 m telescope. Accordingly, the mass detection limit reaches to about 0.01–0.05 M ⊙, which is about 10 times better than the previous observations. At MIR wavelengths, the high sensitivity and resolution data enable us to resolve individual young stellar objects in such a distant region for the first time. The mass detection limit at MIR F770W filter reaches about 0.1–0.3 M ⊙. With these new observations, we have identified components of the clusters that previous surveys did not detect, including class 0 candidates, outflow/jet components, and distinctive nebular structures. These data will enable us to investigate the properties of star formation in the EOG at the same depth of detail as previous observations of star formation in the solar neighborhood.

Experimental Study to Visualize a Methane Leak of 0.25 mL/min by Direct Absorption Spectroscopy and Mid-Infrared Imaging

Tunable laser spectroscopy (TLS) with infrared (IR) imaging is a powerful tool for gas leak detection. This study focuses on direct absorption spectroscopy (DAS) that utilizes wavelength modulation to extract gas information. A tunable interband cascade laser (ICL) with an optical power of 5 mW is periodically modulated by a sawtooth injection current at 10 Hz across the methane absorption around 3271 nm. A fast and sensitive thermal imaging camera for the mid-infrared range between 3 and 5.7 µm is operated at a frame rate of 470 Hz. Offline processing of image stacks is performed using different algorithms (DAS-F, DAS-f and DAS-2f) based on the Lambert–Beer law and the HITRAN database. These algorithms analyze various features of gas absorption, such as area (F), peak (f) and second derivative (2f) of the absorbance. The methane concentration in ppm*m is determined on a pixel-by-pixel analysis without calibration. Leak localization for methane leak rates as low as 0.25 mL/min is accurately displayed in a single concentration image with pixelwise sensitivities of approximately 1 ppm*m in a laboratory environment. Concentration image sequences represent the spatiotemporal dynamics of a gas plume with high contrast. The DAS-2f concept demonstrates promising characteristics, including accuracy, precision, 1/f noise rejection, simplicity and computational efficiency, expanding the applications of DAS.

Miniature snapshot mid-infrared spectrometer based on metal-insulator-metal metasurface

Metasurfaces showcase the performance of light field manipulation at the subwavelength scale, generating tremendous applications in the field of optical imaging and sensing, especially in spectroscopic detection. Here, we demonstrate a spectral detector comprising metal-insulator-metal composite structures working in the mid-infrared band, which can effectively collect and restore target spectral characteristics in the mid-infrared band with a trained reconstruction algorithm. The proposed device consists of snapshot multichannel detection and spectral reconstruction, showing an average spectral reconstruction accuracy approaching 80% of the system. Moreover, we discuss the feasibility of applying this structural design to a miniature spectrometer over a wider infrared wavelength range by proposing a feasible design strategy. Our results provide a novel approach for low-cost and portable mid-infrared spectroscopic detection in ultracompact mid-infrared spectral imaging and sensing elements.

Supernova Ejecta with Crystalline Silicate Dust in the Supernova Remnant MSH 15–52

IRAS 15099-5856 in the young supernova remnant (SNR) MSH 15−52 is the first and only SNR-associated object with crystalline silicate dust detected so far, although its nature and the origin of the crystalline silicate are still unclear. In this paper, we present high-resolution mid-infrared (MIR) imaging observations of the bright central compact source IRS1 of IRAS 15099-5856 to study the spatial distributions of gas and dust and the analysis of its Spitzer MIR spectrum to explore the origin of IRS1. The MIR images obtained with the T-ReCS attached on the Gemini South telescope show a complicated, inhomogeneous morphology of IRS1 with bright clumps and diffuse emission in [Ne ii] 12.81 μm and Qa 18.30 μm, which confirms that IRS1 is an extended source externally heated by the nearby O star Muzzio 10, a candidate for the binary companion of the progenitor star. The Spitzer MIR spectrum reveals several ionic emission lines including a strong [Ne ii] 12.81 μm line, but no hydrogen line is detected. We model the spectrum using the photoionization code Cloudy with varying elemental composition. The elemental abundance of IRS1 derived from the model is close to that of supernova (SN) ejecta with depleted hydrogen and enhanced metals, particularly neon, argon, and iron. Our results imply that IRS1 originates from the SN ejecta and suggest the possibility of the formation of crystalline silicate in newly formed SN dust.