Infrared Imaging Technique Research Articles

Thermo-electric behavior analysis and coupled model characterization of 21,700 cylindrical ternary lithium batteries affected by cyclic aging

In order to achieve a balance between the precision of thermal behavior simulation of lithium batteries affected by cyclic aging and the practicality of engineering popularization and application, a simple degraded battery thermal model needs to be constructed. In this article, a characterization approach for the coupled battery thermo-electric model affected by cyclic aging is designed. This method is suitable for simulating the thermal behavior of lithium degraded batteries with different materials and shapes under different environmental temperatures. This paper introduces the idea by taking the 21,700 cylindrical ternary lithium batteries as an example. Firstly, based on the interaction mechanism between the growth of the solid electrolyte interface film on the battery negative electrode surface at the microscopic level and the battery thermoelectric coupling characteristics at the macro level, the paper constructs a theoretical model of the degraded battery. Further, it conducts experiments to analyze the battery charging and discharging behaviors in the process of cyclic aging. Based on experimental data, this paper conducts multiple fitting calculations to extract essential modeling parameters. Subsequently, this paper builds the battery physical model in the simulation software based on the above modeling parameters. It applies the battery physical model to simulate the thermal characteristics and temperature field. Then, it conducts experiments to demonstrate the precision of the model. This paper uses the infrared imaging technique to visualize and analyze temperature field variations on the battery surface. And it uses thermocouple temperature sensors to capture the battery surface temperature changes. The simulation results are compared with the experimental data, the errors are less than 5 %. Compared with other existing battery thermal models, the model of this paper is more suitable for engineering popularization and application of thermal behavior simulation of lithium batteries affected by cyclic aging.

Broadband infrared imaging governed by guided-mode resonance in dielectric metasurfaces

Nonlinear metasurfaces have experienced rapid growth recently due to their potential in various applications, including infrared imaging and spectroscopy. However, due to the low conversion efficiencies of metasurfaces, several strategies have been adopted to enhance their performances, including employing resonances at signal or nonlinear emission wavelengths. This strategy results in a narrow operational band of the nonlinear metasurfaces, which has bottlenecked many applications, including nonlinear holography, image encoding, and nonlinear metalenses. Here, we overcome this issue by introducing a new nonlinear imaging platform utilizing a pump beam to enhance signal conversion through four-wave mixing (FWM), whereby the metasurface is resonant at the pump wavelength rather than the signal or nonlinear emissions. As a result, we demonstrate broadband nonlinear imaging for arbitrary objects using metasurfaces. A silicon disk-on-slab metasurface is introduced with an excitable guided-mode resonance at the pump wavelength. This enabled direct conversion of a broad IR image ranging from >1000 to 4000 nm into visible. Importantly, adopting FWM substantially reduces the dependence on high-power signal inputs or resonant features at the signal beam of nonlinear imaging by utilizing the quadratic relationship between the pump beam intensity and the signal conversion efficiency. Our results, therefore, unlock the potential for broadband infrared imaging capabilities with metasurfaces, making a promising advancement for next-generation all-optical infrared imaging techniques with chip-scale photonic devices.

A thermal infrared imaging observation system for the measurement of overland flow velocities under controlled laboratory conditions

Flow velocity is an important physical parameter in characterizing the hydraulics of water flow. The accurate measurement of overland flow velocities has great significance for understanding and modeling sediment transport and soil erosion. In this study, a Thermal Infrared Imaging Observation System (TIIOS) based on thermal infrared imaging techniques and computer vision recognition technology was established to measure overland flow velocities under controlled laboratory conditions. TIIOS has three subsystems including thermal tracer control, image acquisition and transmission, and image storage and processing. It can be used to dynamically monitor changes in shallow flow velocity by means of automatic control of thermal tracer, instantaneous image acquisition, image correction, noise removal and centroid determination. The observation precision was high with a standard deviation of 0.004 m·s−1 for flow velocity, a temporal resolution of 1/9th s, and a spatial resolution of 2 mm. The new system achieved higher accuracy compared to the traditional dye tracing and salt tracing techniques in observing the dynamic transport process of thermal tracer movement. The relative errors of the centroid velocity measured by the TIIOS ranged from −9.83 % to 6.40 %; whereas the relative errors of centroid velocity measured by salt tracer ranged from −21.36 % to 17.22 %. Measurements by the established TIIOS under different hydraulic conditions demonstrate that the relative errors of the centroid velocity are all smaller than those of the leading-edge velocity. This observational system provided a reliable way to measure shallow flow velocity for better understanding the mechanisms of water erosion processes and showed its potential to be used in field experiments under natural conditions.

Influence of printing parameters on the thermal properties of 3D-printed construction structures

3D printing in the construction sector is a promising, sustainable approach with the potential to build energy-efficient buildings. However, there is a lack of studies on the thermal properties of 3D-printed structures, which are fundamental to their energy efficiency. This study investigates the impact of printing parameters on thermal conductivity and defect development in 3D-printed concrete structures. Heat flow meter, scanning electron microscope and infrared imaging techniques were employed to assess the thermal properties and microstructure of 3D-printed samples. The results demonstrate that printing parameters significantly influence the porosity, void formation, and microstructural characteristics of 3D-printed concrete, ultimately affecting thermal properties. An increase in extrusion rate leads to higher thermal conductivity, whereas an increase in speed and standoff distance reduces thermal conductivity. Excessive spacing between printed lines can induce voids and gaps, contributing to lower thermal conductivity, while minimal spacing can promote higher porosity and larger pores. Infrared imaging revealed nonuniform thermal distribution in 3D-printed structures caused by the layered structure and voids in interlayer gaps. This study provides valuable insights for designing and constructing energy-efficient 3D-printed buildings, contributing to the development of sustainable building practices and the advancement of additive manufacturing in construction.

Infrared imaging with nonlinear silicon resonator governed by high-Q quasi-BIC states

Nonlinear light-matter interactions have emerged as a promising platform for various applications, including imaging, nanolasing, background-free sensing, etc. Subwavelength dielectric resonators offer unique opportunities for manipulating light at the nanoscale and miniturising optical elements. Here, we explore the resonantly enhanced four-wave mixing (FWM) process from individual silicon resonators and propose an innovative FWM-enabled infrared imaging technique that leverages the capabilities of these subwavelength resonators. Specifically, we designed high-Q silicon resonators hosting dual quasi-bound states in the continuum at both the input pump and signal beams, enabling efficient conversion of infrared light to visible radiation. Moreover, by employing a point-scanning imaging technique, we achieve infrared imaging conversion while minimising the dependence on high-power input sources. This combination of resonant enhancement and point-scanning imaging opens up new possibilities for nonlinear imaging using individual resonators and shows potential in advancing infrared imaging techniques for high-resolution imaging, sensing, and optical communications.

Quantification and characterization of microplastics in coastal environments: Insights from laser direct infrared imaging

The study identified and quantified nine plastic polymers frequently detected in the environment by collecting sediment and seawater samples from coastal areas in Auckland, New Zealand. Polymer types, size distributions, and number of microplastics (MPs) were analyzed using a laser direct infrared (LDIR) imaging technique. Compared to conventional spectroscopic or microscopic methods, LDIR enabled capturing and quantifying MPs in much lower size ranges (20–5000 μm). The results demonstrated the widespread occurrence of MPs in the Auckland coastal environment, with polyethylene terephthalate (PET) being the most frequently detected plastic polymer. MP contamination levels ranged from 13 to 83 particles per liter of coastal water and from 1200 to 3400 particles/kg of dry sand in beach sediments. Six additional locations were investigated to assess the contribution of MPs from stormwater drains to the coastal environment. The total count of identified MPs extracted from sediments near stormwater drains reached a maximum of 18,000 particles/kg of dry sand, representing an order of magnitude increase compared to MP levels found in beach sediments at the same location. In contrast to the prevalence of PET and polyamide observed in beach sediments and coastal waters, polyurethane and polyethylene emerged as the predominant plastic polymers in the vicinity of stormwater drain sediments, implying that the variation could potentially stem from distinct sources of plastics. This significant disparity in quality and quantity underscored the potential link between urban runoff and MP pollution in marine ecosystems. A sample preparation method using 100 g sediment samples was developed and used to assess and compare MPs detection in sediment samples. The commonly used 5 g sample method showed higher extraction efficiency and better detection of the most abundant MPs, but the new 100 g method enabled the detection of previously missed, less abundant plastics.

Innovations in Building Diagnostics and Condition Monitoring: A Comprehensive Review of Infrared Thermography Applications

Infrared thermography is a non-destructive technique that uses infrared radiation to visualize surface temperature variations. It is a versatile tool that can be used to detect a variety of problems in buildings, including insulation deficiencies, moisture intrusion, structural compromise, and electrical faults. The review paper discusses the fundamental principles of infrared thermography, the different types of infrared approaches, and the condition monitoring of buildings using infrared imaging techniques. It also discusses research showing how infrared thermography has been applied to recognize and solve different building-related problems. The article highlights the potential for infrared thermography to advance while also acknowledging its current limits. Infrared thermography is predicted to become an even more effective technique for building diagnostics with the development of more sensitive cameras and the incorporation of artificial intelligence.

Green Synthesis of Zinc Oxide Nanoparticles to Study its Effect on the Skin using IR Thermography

The aim of the research is the infrared imaging technique IR Imaging was used to detect temperature changes and their effects on the skin.In this study, ZnO nanoparticles (ZnO NPs) were prepared by Green's synthesis method. This method is considered the safest, easiest, and cheapest way to manufacture nanomaterials. The optical and structural properties of ZnO NPs have been studied by various techniques such as UV visible, X-ray diffraction, Field emission scanning electron microscopy, and Transmission electron microscopy. ZnO NPs had a UV- visible absorption peak at around 300 nm. ZnO's average crystallite diameter was calculated to be 15.41 nm using Scherrer's equation, which was derived from the width at half maximum of the peak more intense on the 101 planes at 36.28°. The Field emission scanning electron microscopy data showed that the synthesized ZnO NPs have a consistent shape and size throughout their range, these NPs are characterized by their diameter and were assembled into cylindrical clusters of varying diameters, with an average size of 106. Different magnifications of the ZnO NPs examined by Transmission electron microscopy showed that the majority of the particles were homogeneously scattered. Infrared thermal imaging technique (IRT) is used to clarify the change in temperature with the effect of the substance on the skin. The material was placed on the skin in two ways and put on the rabbit's front and back feet. When mixing the powder material of ZnO NPs with distilled water, and mixing the powder material of ZnO NPs with commercial Vaseline, we notice in both cases a temperature rise. The radiance was calculated for each image related to the change of temperature in the band (3-5) µm. The highest value in the range (3-5) µm for image R2 with radiation was (0.9209). The total spectral radioactive emission is proportional to the area under the curves and shifts towards shorter wavelengths with increasing temperature.

Recognition and monitoring of gas leakage using infrared imaging technique with machine learning

Recognition and monitoring of gas leakage using infrared imaging technique with machine learning

Instant testing and non-contact diagnosis for photovoltaic cells using K-means clustering and associated hyperspectral imaging

Renewable energy, particularly solar energy, has experienced remarkable growth in recent years. However, the integrity of solar photovoltaic (PV) cells can degrade over time, necessitating non-destructive testing and evaluation (NDT-NDE) for quality control during production and in-service inspection. Hyperspectral (HS) imaging has emerged as a promising technique for defect identification in PV cells based on their spectral signatures. This study utilizes a HS imager to establish a diffuse reflectance spectra signature for two groups of PV cells: working and non-working. A non-contact photoluminescence imaging-based methodology is employed, using a halogen lamp as an illumination source to replicate sunlight. Our findings reveal that non-working PV regions can be differentiated from working regions within the 400–600 nm wavelength range, with an optimal candidate peak frequency of 450 nm. To accurately group active PV regions in the constructed HS images at 450 nm, we employ an image processing strategy that combines K-means clustering (K-mc) with contour delineation. Specifically, K-mc with K = 8 is used to efficiently and precisely group active PV regions. We demonstrate the effectiveness of this proposed approach and compare it with traditional infrared (IR) imaging techniques. This imaging clustering approach can be implemented using a conventional camera and a 450 nm wavelength filter for NDT-NDE on exterior-mounted PV panels. Overall, the proposed HS imaging technique, coupled with K-mc, offers a rapid and effective means of identifying defects in PV cells, outperforming conventional IR imaging techniques. This advancement contributes to increased efficiency and extended lifespan of solar PV panels.

Perspective on pulse compression favorable infrared imaging techniques for non-destructive testing and evaluation of solids

Abstract Inspection reliability of sub-surface defects is imperative for safer functionality of critical components/materials/structures used in a wide variety of applications in various industries. The need for reliable, fast, remote, safe inspection and evaluation methods for detection of hidden defects increases in parallel with the demand for more sustainable solutions which helps in inherent modifications in design and manufacturing specifications. During in-service operation, the hidden defects are typically originated from various loading conditions leading to catastrophic failure. This perspective explores the best possible reliable, fast, remote, safe, and easy to implement for field inspection and evaluation experimental method and the associated post-processing approach using InfraRed Imaging (IRI) for Thermal Non-Destructive Testing and Evaluation (TNDT&E) of Glass Fibre Reinforced Polymer (GFRP) materials having delamination defects. This perspective further explores the state-of-the-art infrared imaging modalities used in TNDT&E by highlighting their advantages and limitations in terms of the detection sensitivity and depth resolvability to detect the subsurface defects located at interior of material. Most of the proposed experimental and post-processing techniques presented in the literature for TNDT&E, explore the observed spatial thermal contrast over the defective region of sample to provide the depth resolvability from the reconstructed thermograms even though it is obtained from the temporal data processing on the captured image sequence. This perspective provides an insight on the state-of-the-art research in the field of thermal/infrared non-destructive testing and evaluation and associated post-processing approaches to visualize the hidden subsurface defects not only resolved by spatial thermal gradients but also simultaneously provide temporal thermal gradients to locate defective regions.

Interfacial Effects during Phase Change in Multiple Levitated Tetrahydrofuran Hydrate Droplets

Recent strategies developed to examine the nucleation of crystal structures like tetrahydrofuran (THF) hydrates without the effects of a solid interface have included acoustic levitation, where only a liquid-gas interface initially exists. However, the ability now exists to levitate and freeze multiple droplets simultaneously, which could reveal interdroplet effects and provide further insight into interfacial nucleation phenomena. In this study, using direct digital and infrared imaging techniques, the freezing of up to three simultaneous THF hydrate droplets was investigated for the first time. Nucleation was initiated at the aqueous solution-air interface. Two pseudo-heterogeneous mechanisms created additional nucleation interfaces: one from cavitation effects entraining microbubbles and another from subvisible ice particles, also called hydrate-nucleating particles (HNPs), impacting the droplet surface. For systems containing droplets in both the second and third positions, nucleation was statistically simultaneous between all droplets. This effect may have been caused by the high liquid-solid interfacial pressures that developed at nucleation, causing some cracking in the initial hydrate shell around the droplet and releasing additional HNPs (now of hydrate) into the air. During crystallization, the THF hydrate droplets developed a completely white opacity, termed optical clarity loss (OCL). It was suggested that high hydrate growth rates within the droplet resulted in the capture of tiny air bubbles within the solid phase. In turn, light refraction through many smaller bubbles resulted in the OCL. These bubbles created structural inhomogeneities, which may explain how the volumetric expansion of the droplets upon complete solidification was 23.6% compared with 7.4% in pure, stationary THF hydrate systems. Finally, the thermal gradient that developed between the top and bottom of the droplet during melting resulted in a surface tension gradient along the air-liquid interface. In turn, convective cells developed within the droplet, causing it to spin rapidly about the horizontal axis.

Experimental and numerical study on heat transfer characteristics of tangential effusion cooling for a combustor liner

A great number of studies have been conducted on effusion cooling, which is based on the flat plate. However, the differences in flow and heat transfer characteristics between a flat plate and a circular combustor restricted the immediate application of the previous studies to the design of combustor cooling. In this study, a new type of effusion cooling with tangential injection based on the cylinder, which was fabricated by electric discharging machining, is employed in the present investigation using infrared imaging technique. With the blowing ratio ranging from 2.2 to 17.9, the results of proposed structure were compared with that of effusion holes based on the flat plate. The compound angles (β) of tangential effusion are 45°, 60°,75°, 95° respectively. Results show that compared to the effusion cooling based on the flat plate, the cooling jets of the tangential effusion based on the cylinder have a large tangential velocity component, which keeps the cooling jets attached to the wall and flowing spiral forward. The overall cooling effectiveness of tangential effusion is about 50% higher than effusion holes based on the flat plate. This also indicates that the existing conclusions of effusion cooling based on the flat plate cannot be directly applied to the combustion chamber. The cooling performance of tangential effusion cooling is greatly influenced by the compound angle and the 75° is optimal among them. In the studied range of blowing ratio, the overall cooling effectiveness of tangential effusion is above 0.8, and there is a significant cooling enhanced with the increase of blowing ratio. This provides a reference and database for the cooling design for low-emission combustion chambers with low cooling consumption.

Label-free visualization of photosynthetic microbial biofilms using mid-infrared photothermal and autofluorescence imaging.

The formation of photosynthetic microbial biofilms comprising multispecies biomolecules, such as extracellular polymeric substances (EPSs), and microbial cells play pivotal roles in maintaining or stimulating their biological functions. Although there are numerous studies on photosynthetic microbial biofilms, the spatial distribution of EPS components that are vital for microbial biofilm formation, such as exopolysaccharides and proteins, is not well understood. Visualization of photosynthetic microbial biofilms requires label-free methods, because labelling EPSs results in structural changes or aggregation. Raman spectroscopy is useful for label-free visualization of biofilm constituents based on chemical contrast. However, interference resulting from the bright autofluorescence of photosynthetic molecules and the low detection efficiency of Raman scattering make visualization a challenge. Herein, we visualized photosynthetic microbial biofilms in a label-free manner using a super-resolution optical infrared absorption imaging technique, called mid-infrared photothermal (MIP) microscopy. By leveraging the advantages of MIP microscopy, such as its sub-micrometer spatial resolution, autofluorescence-free features, and high detection sensitivity, the distribution of cyanobacteria and their extracellular polysaccharides in the biofilm matrix were successfully visualized. This showed that cyanobacterial cells were aligned along acidic/sulfated polysaccharides in the extracellular environment. Furthermore, spectroscopic analyses elucidated that during formation of biofilms, sulfated polysaccharides initially form linear structures followed by entrapment of cyanobacterial cells. The present study provides the foundation for further studies on the formation, structure, and biological functions of microbial biofilms.

Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer.

Mid-infrared spectroscopic imaging (MIRSI) is an emerging class of label-free techniques being leveraged for digital histopathology. Modern histopathologic identification of ovarian cancer involves tissue staining followed by morphological pattern recognition. This process is time-consuming and subjective and requires extensive expertise. This paper presents the first label-free, quantitative, and automated histological recognition of ovarian tissue subtypes using a new MIRSI technique. This optical photothermal infrared (O-PTIR) imaging technique provides a 10× enhancement in spatial resolution relative to prior instruments. It enables sub-cellular spectroscopic investigation of tissue at biochemically important fingerprint wavelengths. We demonstrate that the enhanced resolution of sub-cellular features, combined with spectroscopic information, enables reliable classification of ovarian cell subtypes achieving a classification accuracy of 0.98. Moreover, we present a statistically robust analysis from 78 patient samples with over 60 million data points. We show that sub-cellular resolution from five wavenumbers is sufficient to outperform state-of-the-art diffraction-limited techniques with up to 235 wavenumbers. We also propose two quantitative biomarkers based on the relative quantities of epithelia and stroma that exhibit efficacy in early cancer diagnosis. This paper demonstrates that combining deep learning with intrinsic biochemical MIRSI measurements enables quantitative evaluation of cancerous tissue, improving the rigor and reproducibility of histopathology.

Use of Infrared Imaging Techniques to Investigate Thermal Losses of Flat Plate Solar Collectors

The paper presents ways to use advanced infrared imaging techniques to study and analyze the thermal losses of a flat plate solar collector. The techniques allowed us to precisely locate and measure areas where unwanted thermal losses occurred on the surface of the collectors studied. The study showed that these losses have a key impact on the energy efficiency of these devices. It was found that using the proposed methodology allows not only the detection of defects in existing structures but also the optimization of the design process of new technical solutions. The temperature of the working medium has a significant effect on heat losses on all analyzed surfaces. However, the influence of the medium flow varies depending on the specific surface. The conclusions of the research suggest that infrared imaging is a valuable tool in developing solar thermal systems, contributing to the reliability and efficiency of these systems. The technique is an important step toward sustainable and economical use of solar energy. Increasing the efficiency of the equipment used to carry out the photothermal conversion process will allow more efficient use of available renewable energy sources. It will have a positive impact on environmental protection.

Counter-Intuitive Evaporation in Nanofluids Droplets due to Stick-Slip Nature.

We experimentally investigate the evaporation characteristics of a sessile ethanol droplet containing Al2O3 and Cu nanoparticles of sizes 25 and 75 nm on a heated substrate using shadowgraphy and infrared imaging techniques. Our results demonstrate that the droplet contact line dynamics resulting from the presence of various nanoparticles plays a dominant role in the evaporation process. This is in contrast to the widely held assumption that the enhanced evaporation rate observed in sessile nanofluid droplets is due to the higher thermal conductivity of the added nanoparticles. We observe that even though the thermal conductivity of Al2O3 is an order of magnitude lower than that of Cu, droplets containing 25-nm-sized Al2O3 exhibit pinned contact line dynamics and evaporate much more rapidly than droplets containing Cu nanoparticles of both sizes and 75 nm Al2O3 nanoparticles that exhibit stick-slip behavior. We also found that the droplets with different nanoparticles display distinct thermal patterns due to the difference in contact line behavior, which alters the heat transfer inside the droplets. We establish this counter-intuitive observation by analyzing the temporal variations of the perimeter, free surface area, and deposition patterns on the substrate.

Aerothermal Computations for Laminar–Turbulent Transition Onset Measurement Using Infrared Imaging Technique

This paper deals with the computation of heat exchange in transitional boundary layers for the prediction of the laminar–turbulent transition detection using infrared thermography. An aerothermal coupling between a heat equation solver and a boundary-layer solver is presented here. This coupling is first used to provide guidelines in the academic framework of a flat plate, to achieve an enhanced temperature gradient at the transition onset in order to improve infrared imaging, and thus the transition position detection. The method is then successfully applied on a real case, by comparing the numerical predictions to measurements obtained during transonic wind-tunnel tests on a two-dimensional wing model.

Thermal Emission of Spinning Photons from Temperature Gradients

The fluctuational electrodynamic investigation of thermal radiation from nonequilibrium or nonisothermal bodies remains largely unexplored because it necessarily requires volume integration over the fluctuating currents inside the emitter, which quickly becomes computationally intractable. Here, we put forth a formalism combining fast calculations based on modal expansion and fluctuational electrodynamics to accelerate research at this frontier. We employ our formalism on a sample problem: a long silica wire held under temperature gradient within its cross section. We discover that the far-field thermal emission carries a nonzero spin, which is constant in direction and sign, and interestingly, is transverse to the direction of the power flow. We clearly establish the origin of this transverse spin as arising from the nonequilibrium intermixing of the cylindrical modes of the wire, and not from any previously studied or intuitively expected origins such as chiral or nonisotropic materials and geometries, magnetic materials or fields, and mechanical rotations. This finding of nonequilibrium spin texture of emitted heat radiation can prove useful for advancing the noninvasive thermal metrology or infrared-imaging techniques.

Novel FTIR and visible infrared imaging assessment of binary biofuel stability and abated NOx for clean environment assisting energy approach

To compensate the oil demand and pollution, scientists explore biodiesel as a pollution free alternate energy. But depending on one particular species of feedstock will lead to its extinction like diesel. For this intent, this research proposes a novelty on blending of binary non-edible high oil yielding species. As biodiesel is a natural constituent with elevated oxygen content, a stability analysis has to be performed to diminish its rapid decay. For stabilizing fuel properties synthetic antioxidants have been involved as inhibitors. Previous studies have been performed on the stability analysis individually as oxidation, thermal and storage stability without analyzing them mutually. This research fills the key gap by deeper mutual stability analysis, as the output parameters of these three stabilities are interrelated. Few samples have shown best stability output parameters which challenges in narrowing the best blend. To face this task, a multi objective optimization study has been done. NOx emission has been reduced with the aid of antioxidants as a twin reward. Two novel assessment tools for validating are, i) FTIR, by which the impact of molecular arrangements on stability variation has been evaluated and ii) Using Infrared Imaging Technique, by which the NOX has been analyzed visually correlating the emission level and engine combustion temperature.