Infrared Physics & Technology最新文献

{"title":"All-fiber pressure-adaptive CO2 concentration monitoring based on negative curvature anti-resonance hollow core fiber","authors":"Kaiyu Chai ,&nbsp;Yipeng Zheng ,&nbsp;Bo Hu ,&nbsp;Zihao Zhou ,&nbsp;Kaili Ren ,&nbsp;Dongdong Han ,&nbsp;Lipeng Zhu ,&nbsp;Yongkai Wang ,&nbsp;Lei Liang ,&nbsp;Linlin Zhang","doi":"10.1016/j.infrared.2025.105879","DOIUrl":"10.1016/j.infrared.2025.105879","url":null,"abstract":"<div><div>Greenhouse gas detection is a key foundation for combating climate change and provides indispensable data support for scientific assessment of carbon emissions and their environmental impacts. In this study, an all-fiber pressure-adaptive gas concentration monitoring system based on tunable diode laser absorption spectroscopy-wavelength modulation spectroscopy is presented. Within a negative curvature-anti-resonant hollow-core optical fiber, the system achieves simultaneous gas concentration detection and ambient pressure monitoring. A pressure compensation algorithm is implemented to dynamically compensate measured gas concentrations to standardized values at the target pressure under fluctuating ambient pressures. The method effectively suppresses concentration measurement instability induced by pressure fluctuations. Experimental results demonstrate a significant improvement: under 20 kPa pressure variations, the 1-h relative standard deviation of CO₂ concentration measurement is reduced from 3.60 % to 1.36 %. Simultaneously, the minimum detection limit is optimized from 121.4 ppm to 34.3 ppm at a 10-s integration time.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105879"},"PeriodicalIF":3.1,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Infrared radiation and energy evolution effects of coal rock under hydrodynamic coupling","authors":"Guanghui Cao ,&nbsp;Liqiang Ma ,&nbsp;Wei Liu ,&nbsp;Qiangqiang Gao ,&nbsp;Naseer Muhammad Khan ,&nbsp;Arienkhe Endurance Osemudiamhen ,&nbsp;Zezhou Guo ,&nbsp;Kunpeng Yu","doi":"10.1016/j.infrared.2025.105877","DOIUrl":"10.1016/j.infrared.2025.105877","url":null,"abstract":"<div><div>Given the escalating issues of water intrusion in underground engineering, there is an urgent need for predictive warning systems regarding water-related disasters. This paper investigates the infrared radiation and energy evolution effects of coal-rock under hydromechanical coupling conditions through laboratory experiments, aiming to anticipate water outbursts resulting from the fracturing of coal-rock. Red sandstone specimens containing internal cavities with a diameter of 50 mm and a depth of 60 mm were subjected to water pressure of 0 MPa, 0.2 MPa, 0.4 MPa, and 0.6 MPa, applied internally via a hydraulic pump, while uniaxial loading was conducted in the vertical direction. This study analyzed the characteristics of Stress-Strain behavior, Energy evolution, Average Infrared Radiation Temperature (AIRT), and Variance of Successive Minus Infrared Image Temperature (VSMIT) during the rock failure and subsequent water outburst events. In addition, a novel indicator, the Pixel Standard Deviation of temperature (PSD), is introduced for enhanced assessment of these phenomena. The results indicate that water pressure significantly reduces the uniaxial compressive strength of the rock, with a decrease of 37.09 % observed at 0.6 MPa compared to 0 MPa. The ratio of elastic energy to dissipated energy (K_ED) evolves over time in a manner reminiscent of a peak shape, with distinct maxima that may serve as precursors to rock failure and water outbursts. The variations in the AIRT curve exhibit a high degree of consistency with those of the stress curve; specifically, as water pressure increases, the amplitude of AIRT fluctuations diminishes. At the moment of peak stress, the VSMIT experiences abrupt pulse changes, and the frequency of these VSMIT fluctuations is correlated with the occurrence of stress drop phenomena: an increase in the number of stress drop events corresponds to a greater number of VSMIT sudden changes. The PSD image stabilizes at approximately 70 % of the final failure time, at which point the proportions of stress at peak values under different water pressures are 67.76 % σ_p, 77.62 % σ_p, 81.54 % σ_p, and 53.69 % σ_p, respectively. Based on this, it can be utilized to predict the timing and morphology of coal and rock failure and water outbursts under varying water pressure conditions. Artificial Neural Network (ANN) model is effective for predicting rock failure and water outbursts; the predictions related to stress–strain behavior and K_ED from the neural network closely align with actual results, suggesting that temporal and infrared indicators can serve as effective inputs in forecasting sandstone failure and associated water outbursts.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105877"},"PeriodicalIF":3.1,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of γ-irradiation on the response nonlinearity in HgCdTe infrared detectors","authors":"Yue Hu ,&nbsp;Hui Qiao ,&nbsp;Xiaoyang Yang ,&nbsp;Fuhao Liu ,&nbsp;Ke Jiang ,&nbsp;Xintian Chen ,&nbsp;Xiangyang Li ,&nbsp;Qiang Guo","doi":"10.1016/j.infrared.2025.105870","DOIUrl":"10.1016/j.infrared.2025.105870","url":null,"abstract":"<div><div>This work investigates the impact of γ-irradiation on the response nonlinearity in mercury cadmium telluride (HgCdTe) photovoltaic detectors. A dual-aperture test system with ± 1 % measurement uncertainty is assembled to quantify response nonlinearity over a wide dynamic range of photon irradiance at different doses of γ-irradiation. The results demonstrate that, at high photon irradiance displacement damage induced by γ-irradiation will reduce the minority carrier lifetime, potentially leading to a significant increase in response nonlinearity. At a total dose of 40 krad (Si), the response nonlinearity of some detectors increases about 20 %. Additionally, results show that dark current and spectral response remain unaffected during the shift testing, while the series resistance increases and the detectivity slightly decreases for some devices. In particular, γ-irradiation is observed to have a more substantial impact on long-wavelength detectors. Annealing treatments after irradiation heals majority of these performances. In contrast to conventional measurements to blackbody responsivity, response nonlinearity amplifies subtle signal variations caused by low-dose γ-irradiation, significantly enhancing the experimental precision and sensitivity.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105870"},"PeriodicalIF":3.1,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Near-infrared vascular image segmentation using multi-stage enhancement and TAU-Net","authors":"Zhen Tian ,&nbsp;Haoting Liu ,&nbsp;Qianru Ji ,&nbsp;Song Wang ,&nbsp;Qing Li ,&nbsp;Dewei Yi ,&nbsp;Xintao Liu","doi":"10.1016/j.infrared.2025.105875","DOIUrl":"10.1016/j.infrared.2025.105875","url":null,"abstract":"<div><div>Near-infrared optical imaging technology provides a non-invasive solution for visualization and monitoring of subcutaneous vascular structures. In order to solve the problems of low vascular image quality and inefficient and inaccurate manual segmentation, we propose a complete set of image processing methods. First, the blood vessel images are preprocessed by the background removal, Gaussian filtering, and contrast stretching. Then the image details are enhanced by a multi-stage enhancement method, which combines the Residual Convolutional AutoEncoder (RCAE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) to effectively improve the contrast between vascular region and other tissue regions. Finally, the images are segmented by our Triplet Attention U-Net (TAU-Net) model, which improves the efficiency and performance of attention mechanism. The TAU-Net introduces a triple attention module in U-Net for the first time, which strengthens the computational ability of spatial and channel attention models. The main segmentation head and auxiliary segmentation head are combined to improve the gradient information, promote the multi-scale learning of network. Numerous experimental results show that our model can flexibly process blood vessel images of various quality levels and distribution forms, and effectively segment their contours well.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105875"},"PeriodicalIF":3.1,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Random forest-assisted Raman spectroscopy and rapid detection of sweeteners","authors":"Yihan Ding ,&nbsp;Xuanpei He ,&nbsp;Rui Zhang ,&nbsp;Haotian Wu ,&nbsp;Yingaridi Bu","doi":"10.1016/j.infrared.2025.105871","DOIUrl":"10.1016/j.infrared.2025.105871","url":null,"abstract":"<div><div>Food safety is important for human healthand social stability. Of these, excessive using artificial sweeteners in food production will cause irreversible damage to the gastrointestinal tract. It is possible to accurately distinguish sweetener type in the food by using Raman spectroscopy. However, labeling the type generally relies on manual operations, which limits its application in rapid detection scenarios. This study introduced machine learning methods (Random Forest algorithm) into the data classification process of Raman detection that enables fast and efficient sweetener type detection. The results showed that the three sweeteners were identified with an accuracy of 1, 2 and 3. In addition, the detection process for the three sweeteners merely took 5–6 s. Considering the versatility of the methodology, this study provides a novel technological route for the rapid identification of ingredients in the food production.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105871"},"PeriodicalIF":3.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143847777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MultiScale-enhanced detection network (MS-EDN) with dual encoder structure for infrared small target detection","authors":"Yanshu Jiang,&nbsp;Chi Cheng,&nbsp;Liwei Deng","doi":"10.1016/j.infrared.2025.105876","DOIUrl":"10.1016/j.infrared.2025.105876","url":null,"abstract":"<div><div>Infrared small target detection is vital in military, security, and rescue operations. While deep learning has achieved remarkable progress in general detection frameworks, its application to infrared imagery remains constrained by intrinsic feature representation challenges. Existing methods are often affected by complex backgrounds, causing small targets to be overlooked, especially in low-contrast environments where detailed information is easily lost. This paper proposes a dual encoder network with multi-scale enhanced detection to address these challenges. One branch incorporates a feature residual enhancement module that combines a residual convolutional block attention module with a feature enhancement module for efficient feature extraction. The other branch integrates a dynamically parallelized patch-aware attention module and employs a multi-branch extraction strategy to capture information across various scales. The multi-scale dynamic fusion module in the neck layer enhances feature representation, facilitating accurate detection and localization of small targets. Additionally, soft pooling is used in the downsampling process to better preserve important features while reducing information loss. Extensive experiments on the SIRST dataset demonstrate that the proposed method outperforms existing approaches in effectiveness and robustness, effectively extracting small target information in complex backgrounds.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105876"},"PeriodicalIF":3.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143847778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Re-parameterized feature attention distillation network for efficient thermal image super-resolution","authors":"Jun Shen ,&nbsp;DongDong Zhang","doi":"10.1016/j.infrared.2025.105849","DOIUrl":"10.1016/j.infrared.2025.105849","url":null,"abstract":"<div><div>Deep learning based infrared image super-resolution algorithms have achieved impressive reconstruction performance, but these models have complex structures and cannot be applied to handheld infrared thermal imagers with limited computing resources and memory size. To overcome these challenges, we propose a re-parameterized feature attention distillation network, named RepFADN, a simple yet efficient thermal image super-resolution network. Specifically, based on the characteristics of infrared images, the use of heavy parameter techniques and shallow residual connections has improved the feature extraction ability of standard convolution, allowing the network to achieve maximum benefits while maintaining portability. The reasonable use of multi branch convolution with 1 × 1 kernel effectively reduces the complexity of feature distillation structure and the introduction of attention branch further improves the performance. Extensive benchmark data experiments show that the proposed RepFADN outperforms CNN-based lightweight and efficient super-resolution networks in terms of performance evaluation indicators. Compared with the most advanced efficient super-resolution networks based on self-attention mechanism, e.g. SRFormer_light, the number of network parameters and FLOPs are 4 × smaller, the memory overhead is 18 × smaller, the inference speed is 40 × faster, and the network performance is similar or even better. Code will be available at <span><span>https://github.com/shenjun1994/RepFADN.git</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105849"},"PeriodicalIF":3.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid determination of free amino acids in Huangshan Maofeng tea using NIR spectra: Analysis and comparison of variable selection methods","authors":"Yuhan Ding ,&nbsp;Xi Chen ,&nbsp;Renhua Zeng ,&nbsp;Hui Jiang","doi":"10.1016/j.infrared.2025.105848","DOIUrl":"10.1016/j.infrared.2025.105848","url":null,"abstract":"<div><div>Tea is gaining global popularity appreciated for its valuable components and health benefits. This study investigated the non-destructive determination of free amino acids (FAA) content in Huangshan Maofeng tea using near-infrared (NIR) spectroscopy combined with chemometric methods. Firstly, preprocessing of the NIR signal was performed using the Savitzky–Golay method and Multiplicative Scatter Correction. Then, Competitive Adaptive Reweighted Sampling (CARS), Bootstrap Soft Shrinkage (BOSS), Iterative Variable Subset Optimization (IVSO) and Variable Combination Population Analysis (VCPA) were used to build support vector regression (SVR) models. Results in the current work showed that all four variable optimization algorithms enhanced the prediction accuracy of the models. Among them, the IVSO-SVR model performed the best. Its predictive determination coefficient (<span><math><msubsup><mrow><mi>R</mi></mrow><mrow><mi>p</mi></mrow><mrow><mn>2</mn></mrow></msubsup></math></span>) was 0.9615, and its root mean square error of prediction (RMSEP) was 0.0624. In summary, NIR spectroscopy combined with chemometric techniques provides a simple and efficient method for rapid, non-destructive quantitative detection of FAA content in tea, with potential for quality control applications.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105848"},"PeriodicalIF":3.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PoLP-ICOP: Cross-validation of Power of Linear Polarization and Infrared CRI-based Optimal Polarization for artificial object detection","authors":"Sungho Kim ,&nbsp;Sanghyuk An","doi":"10.1016/j.infrared.2025.105842","DOIUrl":"10.1016/j.infrared.2025.105842","url":null,"abstract":"<div><div>It is important to detect man-made objects in a natural background to reduce false detections in long-wave infrared for safety and security applications. The degree of linear polarization (DoLP) is used frequently to solve such problems. DoLP can provide important clues for man-made object signatures. On the other hand, DoLP cannot handle the polarization power because of normalization. First, a novel physics-driven power of linear polarization (PoLP) metric is proposed to find optimal infrared polarization conditions analytically. Second, a data-driven infrared polarization method is presented. Few studies have been conducted in terms of polarimetric optimization at a low level. This paper presents a novel polarimetric information utilization method by applying a two-layered neural network with the inverse contrast radiant intensity (CRI) loss function to find physical meaning. The proposed infrared CRI-based optimal polarimetry (ICOP) could extract the low-level contribution of each polarimetric image in discriminating artificial objects in a natural background. After optimization, the learned weights of the polarimetric images were sine-like, which produced optimal object and background separation. The experimental results for the outdoor scenario validated the optimality of the proposed ICOP in man-made object detection in a natural background. Finally, the physics-driven PoLP coincided with the data-driven ICOP in man-made object detection.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105842"},"PeriodicalIF":3.1,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minority carrier lifetime and operating voltage dependence on the barrier layer thickness in nBn infrared photodetectors","authors":"M. Tornay ,&nbsp;A. Ramiandrasoa ,&nbsp;M. Bouschet ,&nbsp;J.-P. Perez ,&nbsp;J.-L. Reverchon ,&nbsp;B. Simozrag ,&nbsp;C. Bonvalot ,&nbsp;I. Ribet ,&nbsp;N. Péré-Laperne ,&nbsp;P. Christol","doi":"10.1016/j.infrared.2025.105846","DOIUrl":"10.1016/j.infrared.2025.105846","url":null,"abstract":"<div><div>XBn InAs/InAsSb architectures are now a standard to design high performance mid-wave infrared photodetectors with increased operating temperatures. In this paper, the influence of barrier layer (<em>BL</em>) thickness on the electrical and electro-optical characteristics of such detectors is investigated. The study shows that this parameter has a key role on turn-on voltage and carrier lifetimes. A model is derived to analyze the dependence of this voltage on BL thickness and doping conditions. It is found that an optimum thickness comprised between 100 and 140 nm can minimize it. Additionally, a decrease in the lifetimes of minority carriers is observed as the BL thickness is increased. This behavior is studied as a function of temperature and applied bias voltage.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"148 ","pages":"Article 105846"},"PeriodicalIF":3.1,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}