Infrared Physics & Technology最新文献_第3页

Confocal dual-excitation PAS oxygen sensor utilizing 760 nm LED and reshaped differential resonator

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-06 DOI: 10.1016/j.infrared.2024.105707

Ze Han , Yongkang Gong , Shuo Pang , Jiachen Sun , Fupeng Wang

{"title":"Confocal dual-excitation PAS oxygen sensor utilizing 760 nm LED and reshaped differential resonator","authors":"Ze Han , Yongkang Gong , Shuo Pang , Jiachen Sun , Fupeng Wang","doi":"10.1016/j.infrared.2024.105707","DOIUrl":"10.1016/j.infrared.2024.105707","url":null,"abstract":"<div><div>Oxygen (O<sub>2</sub>) is a crucial component of the atmospheric environment, which serves not only as the foundation of life processes but also as an indispensable element in numerous chemical reactions and industrial activities. In this work, a highly sensitive O<sub>2</sub> sensor based on photoacoustic spectroscopy (PAS) is developed, and a confocal optical path is realized based on two 760 nm LEDs to enhance the photoacoustic signal. Doublet lens is used to converge the light beam and meanwhile a new differential resonator is custom-designed to accommodate the beam quality of the LED light source. Compared with laser source operating at 760 nm, the LED can provide higher optical power to boost the photoacoustic excitation at a very low economic cost. As a result, a 1<span><math><mi>σ</mi></math></span> noise equivalent detection sensitivity of 245 ppm is achieved with an integration time of one second. Compared with single LED excitation, the style of confocal dual-excitation successfully improves the detection efficiency by 1.9 times, and the detection sensitivity by 1.5 times.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105707"},"PeriodicalIF":3.1,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102035","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}

引用次数: 0

Metal-Dielectric mirrors utilizing three gradient refractive index dielectric materials for 10.6 μm wavelength applications

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-05 DOI: 10.1016/j.infrared.2025.105709

Jianwen Jiang , Meng Guo , Jing Jiang , Li Xiang , Yuchuan Shao , Anlian Pan

{"title":"Metal-Dielectric mirrors utilizing three gradient refractive index dielectric materials for 10.6 μm wavelength applications","authors":"Jianwen Jiang , Meng Guo , Jing Jiang , Li Xiang , Yuchuan Shao , Anlian Pan","doi":"10.1016/j.infrared.2025.105709","DOIUrl":"10.1016/j.infrared.2025.105709","url":null,"abstract":"<div><div>Thin films are crucial in optics, particularly in fabricating high-reflectivity mirrors for high-power lasers. We propose a novel approach that transcends traditional low–high refractive index (LH) structures by designing a metal-dielectric mirror composed of three materials with gradient refractive indices. The optimal process was selected by thoroughly investigating the properties of ZnSe and YbF<sub>3</sub> thin films under varying ion-assisted energies. Using Macleod software, we meticulously designed the optical thicknesses of the ZnSe and YbF<sub>3</sub> coatings, striking a delicate balance between reflection and absorption within the mirror’s dielectric layer, thereby minimizing the overall reflection loss. The resulting mirrors exhibited a remarkable reflectivity of 99.92 % at a wavelength of 10.6 μm, coupled with a significantly low stress level of −18.66 MPa. These results boost the efficiency and durability of laser systems, underscoring the potential of mirrors for various industrial applications.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105709"},"PeriodicalIF":3.1,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102020","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}

引用次数: 0

Enhancing the generalization ability of blueberry impact damage classification model based on SEM-STMMN-SVM

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-04 DOI: 10.1016/j.infrared.2024.105703

Xiaoxiong Sun , Liangkuan Zhu , Dayang Liu

{"title":"Enhancing the generalization ability of blueberry impact damage classification model based on SEM-STMMN-SVM","authors":"Xiaoxiong Sun , Liangkuan Zhu , Dayang Liu","doi":"10.1016/j.infrared.2024.105703","DOIUrl":"10.1016/j.infrared.2024.105703","url":null,"abstract":"<div><div>To improve the generalization ability of the model, this study proposed the Structural Equation Modeling-Source to Target Min-Max Normalization-Support Vector Machine (SEM-STMMN-SVM) model to classify impact damage in blueberries from different regions and varieties. First, the spectral relative reflectance of samples in the range of 935 nm-1720 nm was measured, and the changes in the internal substances of the fruit before and after bruising were analyzed. Subsequently, the spectral relative reflectance corresponding to 90 feature bands related to blueberry damage, including water content, pigments (anthocyanins), cell structure and tissue state, and biochemical composition (sugars and acids) changes, was selected as input factors. SEM was used to establish correlations between the source domain and the target domain. Then, the STMMN algorithm was used to map the correlated source and target domains to the same data range. Finally, an SVM classification model was constructed. The experimental results indicated that the SEM-STMMN-SVM model outperformed the SVM model in classification accuracy for 12 transfer tasks. The average accuracy in the target domains D1, D2, D3, and D4 increased from 60.26 %, 65.53 %, 61.40 %, and 64.24 % to 87.04 %, 87.04 %, 88.89 %, and 87.74 %, respectively. Overall, the proposed method showed potential in predicting impact damage in blueberries from different sources and varieties. The following research will explore the model transfer effects between different fruits.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105703"},"PeriodicalIF":3.1,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098107","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}

引用次数: 0

Peak shift near-infrared metamaterial absorber with VO2 phase transition grating layer

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-03 DOI: 10.1016/j.infrared.2025.105712

Mei Ming , Zhibin Ren , Wangyang Yu , Haifeng Zhang , Mengdan Liu

引用次数: 0

EAFF-Net: Efficient attention feature fusion network for dual-modality pedestrian detection

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-03 DOI: 10.1016/j.infrared.2024.105696

Ying Shen, Xiaoyang Xie, Jing Wu, Liqiong Chen, Feng Huang

{"title":"EAFF-Net: Efficient attention feature fusion network for dual-modality pedestrian detection","authors":"Ying Shen, Xiaoyang Xie, Jing Wu, Liqiong Chen, Feng Huang","doi":"10.1016/j.infrared.2024.105696","DOIUrl":"10.1016/j.infrared.2024.105696","url":null,"abstract":"<div><div>The pedestrian detection network utilizing a combination of infrared and visible image pairs can improve detection accuracy by fusing their complementary information, especially in challenging illumination conditions. However, most existing dual-modality methods only focus on the effectiveness of feature maps between different modalities while neglecting the issue of redundant information in the modalities. This oversight often affects the detection performance in low illumination conditions. This paper proposes an efficient attention feature fusion network (EAFF-Net), which suppresses redundant information and enhances the fusion of features from dual-modality images. Firstly, we design a dual-backbone network based on CSPDarknet53 and combine with an efficient partial spatial pyramid pooling module (EPSPPM), improving the efficiency of feature extraction in different modalities. Secondly, a feature attention fusion module (FAFM) is built to adaptively weaken modal redundant information to improve the fusion effect of features. Finally, a deep attention pyramid module (DAPM) is proposed to cascade multi-scale feature information and obtain more detailed features of small targets. The effectiveness of EAFF-Net in pedestrian detection has been demonstrated through experiments conducted on two public datasets.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105696"},"PeriodicalIF":3.1,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102034","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}

引用次数: 0

A tea classification method based on near infrared spectroscopy (NIRS) and transfer learning

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-03 DOI: 10.1016/j.infrared.2025.105713

Long Liu , Bin Wang , Xiaoxuan Xu , Jing Xu

{"title":"A tea classification method based on near infrared spectroscopy (NIRS) and transfer learning","authors":"Long Liu , Bin Wang , Xiaoxuan Xu , Jing Xu","doi":"10.1016/j.infrared.2025.105713","DOIUrl":"10.1016/j.infrared.2025.105713","url":null,"abstract":"<div><div>Tea is one of the most popular and widely consumed beverages worldwide, and accurately identifying its type is important for consumers. NIRS, a technology that uses near-infrared light for material analysis, is often employed for this purpose. Traditionally, automatic identification of NIRS has relied on classical machine learning methods. However, these conventional algorithms tend to lack accuracy when dealing with complex spectra. This article proposes a tea classification method based on a 1-dimensional residual network(1DResNet) model combined with transfer learning. The method is implemented in several steps. First, the 1DResNet model is pre-trained using a pre-training dataset. Then, the parameters of the feature extraction layers are frozen, and the model is fine-tuned using a fine-tuning dataset. Finally, the fine-tuned 1DResNet model is tested on a separate test dataset. Compared to traditional machine learning algorithms like Partial Least Squares Discriminant Analysis (PLS-DA), K-Nearest Neighbor (KNN), and Multilayer Perceptron (MLP), the fine-tuned 1DResNet model demonstrates significantly improved classification accuracy (by more than 4.32%). Furthermore, compared to a 1DResNet model without fine-tuning, accuracy improves by 4.96%. When compared to a fine-tuned 1-dimensional Convolutional Neural Network (1DCNN), the accuracy increases by 4%.This notable improvement highlights the potential of the fine-tuned 1DResNet model in handling complex spectral data. The method also performs well in transfer learning tasks; both black tea and green tea classification results demonstrate that the 1DResNet model with fine-tuning has strong potential for migration tasks. Overall, this classification method offers broader application prospects.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105713"},"PeriodicalIF":3.1,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098118","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}

引用次数: 0

Robust spatially regularized sparse unmixing of hyperspectral remote sensing images with spectral library pruning

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-03 DOI: 10.1016/j.infrared.2024.105697

Shaoquan Zhang , Yuyang Liu , Fan Li , Jiajun Zheng , Pengfei Lai , Chengzhi Deng , Mengxiong Tang , Shengqian Wang

{"title":"Robust spatially regularized sparse unmixing of hyperspectral remote sensing images with spectral library pruning","authors":"Shaoquan Zhang , Yuyang Liu , Fan Li , Jiajun Zheng , Pengfei Lai , Chengzhi Deng , Mengxiong Tang , Shengqian Wang","doi":"10.1016/j.infrared.2024.105697","DOIUrl":"10.1016/j.infrared.2024.105697","url":null,"abstract":"<div><div>With the widespread use of endmember spectral libraries, sparse regression techniques have become crucial in hyperspectral image unmixing. Recently, considering spatial information in sparse unmixing frameworks has become increasingly important, as it enhances the accuracy of mixed pixel decomposition. However, challenges such as spectral mismatch due to high correlation among endmember spectra and susceptibility to complex noise, like Gaussian and sparse noise, affect unmixing accuracy. To address these issues, this paper introduces the robust spatially regularized sparse unmixing algorithm with spectral library pruning (RSUSLP). The algorithm decomposes the unmixing process into multiple layers and prunes the spectral library at each layer to alleviate spectral mismatch. It models sparse noise within the unmixing framework and utilizes spectral weighting in conjunction with spatial weighting to increase row sparsity and spatial correlation, thus improving robustness. The optimization problem described in the algorithm is solved using the alternating direction method of multipliers (ADMM). As illustrated by experimental results from both simulated and real hyperspectral data, RSUSLP significantly surpasses current sparse unmixing methods by reducing spectral library interference and effectively handling noise, thereby enhancing the accuracy and performance of mixed pixel decomposition.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105697"},"PeriodicalIF":3.1,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102037","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}

引用次数: 0

A novel photoacoustic gas sensor for dual-component identification and concentration analysis

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-03 DOI: 10.1016/j.infrared.2025.105711

Jiachen Sun , Fupeng Wang , Lin Zhang , Jiankun Shao

{"title":"A novel photoacoustic gas sensor for dual-component identification and concentration analysis","authors":"Jiachen Sun , Fupeng Wang , Lin Zhang , Jiankun Shao","doi":"10.1016/j.infrared.2025.105711","DOIUrl":"10.1016/j.infrared.2025.105711","url":null,"abstract":"<div><div>In this study, a neural network-assisted photoacoustic gas sensor is proposed that enables dual-component identification and concentration analysis of methane and ethylene, effectively addressing the issue of cross-interference in photoacoustic spectroscopy (PAS) technology. This sensor identifies the unknown photoacoustic second harmonic signal using a self-built photoacoustic deep neural network-component identification model, and then determines the composition of the gas sample. The traditional concentration fitting equation method and the self-built Photoacoustic Deep Neural Network-Concentration Regression Model are integrated to analyze the gas samples composed of single- and dual-component. The sensor demonstrates exceptionally high linearity, accuracy and robustness. Additionally, the minimum detection limits (MDLs) for a single-component are determined to be 0.28 ppm for methane and 1.56 ppm for ethylene. For dual-component detection, the MDLs are 8.86 ppm for methane and 4.55 ppm for ethylene. The promising results of the present study demonstrate that deep learning algorithm provides a more effective, accurate, and stable solution for elimination of cross-interference in photoacoustic gas sensor.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105711"},"PeriodicalIF":3.1,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143097727","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}

引用次数: 0

Exploring the optoelectronic properties of medium-wave dual-color detectors based on asymmetric InAs/InAsSb superlattice niBin structure

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-02 DOI: 10.1016/j.infrared.2025.105708

Wenya Huang , Shuai Yang , Yilun Yu , Beituo Liu , Rui Ge , Changsheng Xia , Fangyu Yue

{"title":"Exploring the optoelectronic properties of medium-wave dual-color detectors based on asymmetric InAs/InAsSb superlattice niBin structure","authors":"Wenya Huang , Shuai Yang , Yilun Yu , Beituo Liu , Rui Ge , Changsheng Xia , Fangyu Yue","doi":"10.1016/j.infrared.2025.105708","DOIUrl":"10.1016/j.infrared.2025.105708","url":null,"abstract":"<div><div>The short-mid-/mid-wave infrared (SMWIR/MWIR) detectors can capture target information in two bands simultaneously, enhancing the recognition accuracy in challenging interference scenarios by suppressing complex background. Here, we explore the optoelectrical properties of InAs/InAsSb-superlattice-based dual-band niBin detectors consisting of SMWIR/MWIR absorbers separated by an AlGaAsSb unipolar barrier. The experimental and simulated results show that: i) The bandgaps of both SMWIR and MWIR absorbers can be consistently determined via transmission and photocurrent spectra, giving cutoff wavelengths of ∼ 4.16 µm and ∼ 5.21 µm (77 K), respectively, well in line with the design values; ii) The device structure shows n-type conductivity by Hall measurements, based on which the conduction and scattering mechanisms at various temperatures can be clarified; iii) Dark current density analysis reveals the temperature dependent dominant current mechanisms, i.e., the generation-recombination current in 150 K − 210 K and the diffusion current above 210 K; and iv) The Burstein-Moss effect can make the determined optical bandgap slightly redshifted (∼34 meV), as compared to that of electrical techniques. This work provides new insights into bandgap engineering and structural design for MWIR dual-color detectors based on InAs/InAsSb superlattices.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105708"},"PeriodicalIF":3.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143097729","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}

引用次数: 0

Research on low-pressure water vapor measurement based on TDLAS technology

IF 3.1 3区物理与天体物理

Infrared Physics & Technology Pub Date : 2025-01-02 DOI: 10.1016/j.infrared.2024.105706

Junyue Ke , Xiaowei Xu , Feng Qian , Xiong Bao , Zhengxiang Tian , Mingzhao Wang , Chao Wang , Xuan Yang , Zunhua Zhang , Xiaofeng Guo

{"title":"Research on low-pressure water vapor measurement based on TDLAS technology","authors":"Junyue Ke , Xiaowei Xu , Feng Qian , Xiong Bao , Zhengxiang Tian , Mingzhao Wang , Chao Wang , Xuan Yang , Zunhua Zhang , Xiaofeng Guo","doi":"10.1016/j.infrared.2024.105706","DOIUrl":"10.1016/j.infrared.2024.105706","url":null,"abstract":"<div><div>In the field of accurate measurement of gas concentration by Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology, the fluctuation of environmental pressure becomes a constraint, which affects the gas absorption line and measurement accuracy. Therefore, it is very important to implement pressure compensation for the test system. This study takes water as the research object and innovatively designs a water vapor concentration sensor, which integrates multiple key components, including a laser emission module using direct absorption method and precision temperature control, an open Herriott gas absorption cell, and a high-precision signal acquisition and processing module. Under standard atmospheric conditions (normal temperature and pressure), a comprehensive performance test of the sensor was first carried out. The results showed that the detection limit was 0.01% and the rise time of the detection system was about 12s (30–1000 ppm), and the fall time was about 10s (1000–30 ppm). Secondly, the influence of pressure change on the absorption line shape is discussed. A series of water vapor concentration measurement experiments with variable pressure are carried out, and a pressure compensation method is proposed to effectively control the measurement error within 2%. Finally, in order to ensure the reliability and accuracy of the sensor in practical applications, this study tested the sensor from low pressure to high pressure, and successfully verified its stability and accuracy during long-term operation.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"145 ","pages":"Article 105706"},"PeriodicalIF":3.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102038","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}

引用次数: 0