Infrared Physics & Technology最新文献

Standard spatial distribution of facial skin temperature: A preliminary study 面部皮肤温度的标准空间分布：初步研究

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-02-06 DOI: 10.1016/j.infrared.2026.106437

Kent Nagumo , Kosuke Oiwa , Akio Nozawa

This study presents a preliminary, exploratory longitudinal analysis of facial skin temperature (FST) spatial distributions using facial thermal imagery (FTI) acquired over six months from summer to winter. We aimed to quantify the typical spatial distribution of FST and assess intra- and inter-individual variability under controlled laboratory conditions. As an initial step toward defining a reference distribution, we compared FST spatial patterns measured during baseline sessions with those obtained under an experimentally induced, non-clinically validated abnormal condition. The results showed relatively small inter-individual variability in FST spatial distributions within the sampled population, suggesting a consistent pattern across participants. In contrast, the abnormal condition produced measurable deviations from the baseline pattern, particularly when distributions were expressed using Z-score normalization. Because this study did not include clinical validation, external control groups, or real-world testing, the findings should be interpreted as suggestive rather than definitive. Future work should include clinical trials and broader participant cohorts to validate the proposed reference distribution, evaluate additional confounders (e.g., circadian effects and environmental variability), and test robustness in real-world settings to support translational applications such as health monitoring.

本研究利用夏季至冬季6个月的面部热图像（FTI）对面部皮肤温度（FST）的空间分布进行了初步的探索性纵向分析。我们旨在量化FST的典型空间分布，并在受控的实验室条件下评估个体内部和个体间的变异。作为确定参考分布的第一步，我们将基线期间测量的FST空间模式与实验诱导的非临床验证的异常情况下获得的FST空间模式进行了比较。结果显示，样本群体中FST空间分布的个体间差异相对较小，表明参与者之间的模式一致。相反，异常情况与基线模式产生了可测量的偏差，特别是当使用z分数归一化表示分布时。由于本研究未包括临床验证、外部对照组或实际测试，因此研究结果应被解释为暗示性而非确定性。未来的工作应包括临床试验和更广泛的参与者队列，以验证建议的参考分布，评估其他混杂因素（例如，昼夜节律效应和环境变异性），并在现实环境中测试稳健性，以支持健康监测等转化应用。

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引用次数: 0

DWPCNNFusion: Deep pulse-coupled neural networks incorporating Weber’s law for efficient infrared and visible image fusion DWPCNNFusion：采用韦伯定律的深度脉冲耦合神经网络，用于有效的红外和可见光图像融合

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-29 DOI: 10.1016/j.infrared.2026.106417

Jia Zhao , Sirui Jia , Jing Di , Jing Lian , Yide Ma , Yuelan Xin , Jisheng Dang , Jizhao Liu

Infrared and visible image fusion is a key task in computer vision, aiming to combine complementary multimodal information to generate a salient and texture-rich image. However, existing deep learning-based fusion methods typically rely on increasing network depth to enhance performance, often overlooking the significant computational resources required, which leads to inefficiency. To address this, we propose a novel brain-inspired, end-to-end trainable infrared and visible image fusion method (DWPCNNFusion). Specifically, in the feature extraction stage, we design a deep pulse-coupled neural networks based on Weber’s law (DWPCNN) , where the coupling weight matrix is treated as a learnable parameter, enabling the network to flexibly adapt to varying data characteristics. Additionally, linking strength coefficients are set according to Weber’s law, simulating the nonlinear perception of brightness in the human visual system, which effectively mitigates detail loss in low-light environments. To accommodate dynamic changes in input data over time, a time adaptive batch normalization method is proposed, and temporal information is integrated via a rate encoding scheme, allowing DWPCNN to be efficiently incorporated into existing deep learning frameworks. Furthermore, pulse convolutional dense blocks (PCDB) are employed to extract high-level semantic features, further enhancing the model’s feature representation capability. Experimental results on the TNO and MSRS datasets, compared with 15 representative methods using both objective and subjective metrics, demonstrate that the proposed method excels in detail preservation while achieving a better balance between computational efficiency and fusion performance.

红外图像与可见光图像融合是计算机视觉中的一项关键任务，其目的是将互补的多模态信息结合在一起，生成显著且纹理丰富的图像。然而，现有的基于深度学习的融合方法通常依赖于增加网络深度来提高性能，往往忽略了所需的大量计算资源，从而导致效率低下。为了解决这个问题，我们提出了一种新颖的脑启发，端到端可训练的红外和可见光图像融合方法（DWPCNNFusion）。具体而言，在特征提取阶段，我们设计了基于韦伯定律的深度脉冲耦合神经网络（DWPCNN），将耦合权矩阵作为可学习参数，使网络能够灵活地适应不同的数据特征。此外，根据韦伯定律设置连接强度系数，模拟人类视觉系统对亮度的非线性感知，有效减轻了弱光环境下的细节损失。为了适应输入数据随时间的动态变化，提出了一种时间自适应批归一化方法，并通过速率编码方案集成时间信息，使DWPCNN能够有效地融入现有的深度学习框架。此外，采用脉冲卷积密集块（PCDB）提取高级语义特征，进一步增强了模型的特征表示能力。在TNO和MSRS数据集上的实验结果表明，该方法在计算效率和融合性能之间取得了更好的平衡，并与15种具有代表性的客观和主观度量方法进行了比较。

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引用次数: 0

HFIENet: Hierarchical feature information exchange network for infrared and visible image fusion HFIENet：用于红外和可见光图像融合的分层特征信息交换网络

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-27 DOI: 10.1016/j.infrared.2026.106428

Xiangcan Du, Kun Qian, Haojie Zhou, Hongbin Yu

Infrared and visible image fusion (IVIF) is a highly important research field. Through algorithmic fusion, the resulting image contains both the rich texture details present in visible images and the unique thermal information from infrared images. Although numerous approaches have been explored and significant progress has been made, extracting effective modality-specific features and developing robust fusion strategies and rules remain major challenges in IVIF. To address this issue, we propose a novel Hierarchical Feature Information Exchange Network (HFIENet), which comprises two main components: the Information Exchange (IE) module and the Selective Feature Fusion (SFF) module. The IE module employs the cross-attention strategy and differential weighting operation to perform information exchange, thereby enabling the network to extract more significant and comprehensive features from each modality. Due to the different importance of shallow and deep features, the SFF module adaptively integrates essential features for image reconstruction by leveraging attention mechanisms across both channel and spatial dimensions. Extensive experiments conducted on four publicly available datasets demonstrate that HFIENet consistently outperforms current state-of-the-art methods in both qualitative visual analysis and quantitative metric evaluations. Furthermore, under the same experimental settings, it also improves the performance of downstream semantic segmentation and object detection tasks. Our code and pre-trained model will be available at https://github.com/vonnovx/HFIENet.

红外与可见光图像融合（IVIF）是一个非常重要的研究领域。通过算法融合，得到的图像既包含可见光图像中丰富的纹理细节，又包含红外图像中独特的热信息。尽管已经探索了许多方法并取得了重大进展，但提取有效的模式特异性特征和开发强大的融合策略和规则仍然是IVIF的主要挑战。为了解决这个问题，我们提出了一种新的分层特征信息交换网络（HFIENet），它由两个主要部分组成：信息交换（IE）模块和选择性特征融合（SFF）模块。IE模块采用交叉注意策略和差分加权运算进行信息交换，使网络能够从各模态中提取出更重要、更全面的特征。由于浅特征和深特征的重要性不同，SFF模块通过利用跨通道和空间维度的注意机制，自适应地集成图像重建的基本特征。在四个公开数据集上进行的广泛实验表明，HFIENet在定性视觉分析和定量度量评估方面始终优于当前最先进的方法。此外，在相同的实验设置下，它还提高了下游语义分割和目标检测任务的性能。我们的代码和预训练模型可以在https://github.com/vonnovx/HFIENet上获得。

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引用次数: 0

Construction and photothermal properties of microsphere-modified cavity resonator absorbers with ultra-wide infrared spectrum absorption 超宽红外光谱吸收微球修饰腔谐振器的结构及光热性能

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-27 DOI: 10.1016/j.infrared.2026.106425

Ruinan Zheng, Haigang Hou, Quanjiang Lv, Jianli Jiang, Junhui Gong, Guiwu Liu, Junlin Liu, Guanjun Qiao

The continuous advancement of infrared detection technology has not only expanded the application scope of infrared thermal detectors but also imposed increasingly stringent requirements on the absorption performance of novel photothermal materials across ultra-broadband infrared spectra. In response, this study designs and fabricates two types of microsphere-modified cavity resonator absorbers with ultra-broadband infrared absorption capabilities by integrating material optics and structural optics principles with multilayer thin-film deposition technology. These include an arc reflector cavity resonator (AR-CR) and an arc composite dielectric cavity resonator (ACD-CR). For comparative analysis, a traditional non-arc cavity resonator (NA-CR) was also prepared as a reference. Compared to the conventional NA-CR absorber, the microsphere-modified resonator absorbers not only facilitate light absorption via plasmonic effects but also excite multilevel interference effects, thereby effectively broadening the absorption bandwidth and enhancing the overall absorption performance. Benefiting from the synergistic enhancement between multilevel interference and plasmonic effects, both the AR-CR and ACD-CR absorbers exhibit significantly improved average absorptivity within the 2.5–20 μm wavelength range, which showed 43.98% and 49.83% enhancement, respectively, over the NA-CR. Furthermore, in the far-infrared band, the photothermal conversion efficiencies of the AR-CR and ACD-CR absorbers reach 83.6% and 75.3%, respectively. This work provides a novel structural design strategy for high-performance infrared photothermal conversion materials and demonstrates their promising potential for applications in infrared detection and energy conversion.

红外探测技术的不断进步，不仅扩大了红外热探测器的应用范围，而且对新型光热材料在超宽带红外光谱上的吸收性能提出了越来越严格的要求。为此，本研究将材料光学和结构光学原理与多层薄膜沉积技术相结合，设计并制造了两种具有超宽带红外吸收能力的微球修饰腔谐振器吸收器。其中包括电弧反射腔谐振器（AR-CR）和电弧复合介质腔谐振器（ACD-CR）。为了进行对比分析，还制作了传统的无弧腔谐振器（NA-CR）作为参考。与传统的NA-CR吸收器相比，微球修饰的谐振腔吸收器不仅可以通过等离子体效应吸收光，还可以激发多级干涉效应，从而有效地拓宽了吸收带宽，提高了整体吸收性能。得益于多能级干涉和等离子体效应的协同增强，AR-CR和ACD-CR吸收剂在2.5 ~ 20 μm波长范围内的平均吸光度均显著提高，分别比NA-CR提高43.98%和49.83%。在远红外波段，AR-CR和ACD-CR吸收剂的光热转换效率分别达到83.6%和75.3%。本研究为高性能红外光热转换材料提供了一种新的结构设计策略，并展示了其在红外探测和能量转换方面的应用潜力。

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引用次数: 0

HFFN: Hierarchical feature fusion network for RGB-infrared object detection HFFN: rgb -红外目标检测的分层特征融合网络

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-26 DOI: 10.1016/j.infrared.2026.106429

Jinhang Zhang, Min Gao, Yi Wang, Chaowang Li, Dan Fang, Zhuang Wei

In recent years, multimodal object detection techniques based on visible(RGB) and infrared(IR) images have gained attention as a research hotspot. These techniques leverage the complementary characteristics of RGB and IR images to overcome the environmental adaptability limitations of single-modality methods. The fusion of RGB and IR images is crucial for object detection under complex lighting conditions. By effectively integrating the complementary information of the two modality images, the robustness and accuracy of detection are enhanced. However, current image fusion methods often encounter issues of inaccurate modality alignment and insufficient representation of fused features during feature extraction and fusion. We propose a Hierarchical Feature Fusion Network (HFFN) that achieves efficient extraction and accurate alignment of multimodal features using an Adaptive Pooling Transformer (APT) and an Invertible Detail Extraction (IDE), significantly enhancing the fusion quality. The APT combines pooling operations and the Transformer structure, enabling it to capture global information and expand the receptive field of features; The IDE focuses on extracting local detail features, including edges and texture information, to enhance the fineness and clarity of the fused image. We constructed object detectors based on the HFFN to validate its effectiveness. Extensive experiments on datasets demonstrate the superior performance of our method.

近年来，基于可见光（RGB）和红外（IR）图像的多模态目标检测技术作为一个研究热点备受关注。这些技术利用RGB和IR图像的互补特性来克服单模态方法的环境适应性限制。RGB和IR图像的融合对于复杂光照条件下的目标检测至关重要。通过有效地整合两模态图像的互补信息，提高了检测的鲁棒性和准确性。然而，目前的图像融合方法在特征提取和融合过程中经常遇到模态对齐不准确和融合特征表示不充分的问题。我们提出了一种分层特征融合网络（HFFN），该网络利用自适应池化变压器（APT）和可逆细节提取（IDE）实现了多模态特征的高效提取和精确对齐，显著提高了融合质量。APT结合了池化操作和Transformer结构，使其能够捕获全局信息并扩展特征的接受域；IDE专注于提取局部细节特征，包括边缘和纹理信息，以增强融合图像的精细度和清晰度。我们构建了基于HFFN的目标检测器来验证其有效性。大量的数据集实验证明了该方法的优越性能。

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引用次数: 0

Stable high temperature meta-film for visible and infrared compatible camouflage 用于可见光和红外兼容伪装的稳定高温元膜

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-23 DOI: 10.1016/j.infrared.2026.106427

Wenzhuang Ma , Yang Xiang , Gefei Shen , Yujia Zhou , Kewei You , Yang Zhou , Ningtao Wang , Li Zhang

The advancement of multispectral detection has spurred the development of camouflage materials for both visible and infrared spectra. This is especially challenging for hypersonic vehicles, where extreme heat during flight demands highly durable materials. However, research on high-temperature visible-infrared camouflage remains limited. Here, we propose a high-temperature-resistant visible-infrared camouflage strategy. The designed material enables tunable coloration in the visible spectrum while maintaining low infrared emissivity (<0.25) in dual infrared bands (3-5 and 8-14 μm), effectively minimizing thermal radiation leakage. Our findings reveal that the spectral degradation of conventional Pt/Al₂O₃/Pt multilayers at high temperatures primarily stems from film structural degradation and intrinsic material property alterations, particularly the irregular agglomeration of the top Pt layer, which disrupts film continuity and causes unpredictable spectral shifts. By introducing an Al₂O₃ protective layer, we suppress Pt agglomeration, enabling a transition from three-dimensional disorder to two-dimensional order, thereby enhancing spectral predictability. Building on these insights, we propose an innovative pre-aging strategy, wherein the material’s optical properties in a stabilized post-annealing state are reverse-engineered and pre-aged through thermal treatment to achieve the target spectral performance. This approach ensures long-term high-temperature stability for effective camouflage functionality. Experimental results demonstrate that the designed material retains its camouflage efficacy for over 100 hours at 600°C. This study lays the foundation for the intelligent design and fabrication of next-generation high-temperature-resistant camouflage materials for future applications.

多光谱探测技术的进步促进了可见光和红外光谱伪装材料的发展。这对高超音速飞行器来说尤其具有挑战性，因为飞行过程中的极端高温需要高度耐用的材料。然而，对高温可见红外伪装的研究仍然有限。在此，我们提出了一种耐高温的可见-红外伪装策略。设计的材料可以在可见光谱中实现可调的颜色，同时在双红外波段（3-5 μm和8-14 μm）保持低红外发射率（<0.25），有效地减少热辐射泄漏。我们的研究结果表明，传统Pt/Al2O3/Pt多层膜在高温下的光谱退化主要源于薄膜结构退化和材料固有性质的改变，特别是顶层Pt层的不规则团聚，这破坏了薄膜的连续性并导致不可预测的光谱位移。通过引入Al2O3保护层，我们抑制了Pt团聚，实现了从三维无序到二维有序的转变，从而提高了光谱的可预测性。基于这些见解，我们提出了一种创新的预老化策略，其中材料在稳定的退火状态下的光学特性被逆向工程和通过热处理预老化以达到目标光谱性能。这种方法确保了有效伪装功能的长期高温稳定性。实验结果表明，该材料在600℃下可保持100小时以上的伪装效果。该研究为下一代耐高温伪装材料的智能化设计和制造奠定了基础。

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引用次数: 0

DSHANet: Dual-path sampling and hybrid attention network for infrared image destriping DSHANet：用于红外图像去条纹的双路径采样和混合关注网络

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-23 DOI: 10.1016/j.infrared.2026.106421

Xue Li , Hongying Zhang , Lijun Yang , Xi Yang , Song Liu

Infrared images are often severely degraded by stripe noise, which significantly hinders subsequent image analysis and applications. To address the limitations of existing destriping methods in distinguishing noise from image details and modeling cross-scale feature correlations, this paper proposes a dual-path sampling and hybrid attention-based approach for infrared image destriping. The method implicitly splits feature branches through the designed residual dual-path downsampling module. One branch uses adaptive pooling to suppress stripe noise, while the other retains image edge details via grouped strided convolution. These two branches are fused using dynamic weights. Additionally, a hybrid attention module is proposed to separately capture noise patterns and structural features via 1 × 3 convolution and vertical strip attention, respectively, with a self-calibration branch adaptively modulating feature responses to suppress stripe noise while enhancing target integrity. Experiments demonstrate that the proposed method outperforms existing approaches on the INFRARED, ICSRN, CVC09, BSD68, and SIDD benchmark datasets, as well as real data. Specifically, it achieves an average Peak Signal-to-Noise Ratio of 37.96 dB across four typical stripe noise scenarios, surpassing the state-of-the-art method by 0.34 dB while effectively suppressing stripe noise.

红外图像经常受到条纹噪声的严重影响，严重阻碍了后续的图像分析和应用。针对现有去条纹方法在图像细节噪声区分和跨尺度特征相关性建模方面的局限性，提出了一种基于双路径采样和混合注意的红外图像去条纹方法。该方法通过设计的残差双径下采样模块隐式分割特征分支。一个分支使用自适应池来抑制条纹噪声，而另一个分支通过分组跨行卷积来保留图像边缘细节。这两个分支使用动态权值进行融合。此外，提出了一种混合注意模块，分别通过1 × 3卷积和垂直条形注意分别捕获噪声模式和结构特征，并通过自校准分支自适应调制特征响应来抑制条形噪声，同时增强目标完整性。实验表明，该方法在红外、ICSRN、CVC09、BSD68和SIDD基准数据集以及实际数据上都优于现有方法。具体来说，在四种典型条纹噪声情况下，该方法的平均峰值信噪比为37.96 dB，在有效抑制条纹噪声的同时，比目前最先进的方法高出0.34 dB。

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引用次数: 0

Study on attenuation characteristics of graphite materials in infrared stealth 红外隐身中石墨材料衰减特性研究

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-22 DOI: 10.1016/j.infrared.2026.106424

Wen-Chien Huang , Kuo-Hui Wu , Je-Chuang Wang , Yin-Chiung Chang , Ching-Wei Lin

This study used instrumental analysis to compare the material properties and infrared shielding performance of military-grade graphite and two types of commercial graphite. Static attenuation tests were conducted using the potassium bromide (KBr) method and the polyethylene (PE) sheeting method, while dynamic tests were conducted using the smoke box test method to investigate the attenuation performance of graphite materials for infrared light (IR). The shielding effectiveness and extinction coefficient (α) of graphite materials were measured using a thermal imager and a Fourier transform infrared spectrometer (FTIR). The three graphite materials have similar microstructures, crystal structures, and surface phenomenon, so their infrared shielding effectiveness and α are not significantly different. The experimental results show that the average infrared transmittance (T; %) of the three graphite materials in the wavelength range of 3 ∼ 5/8 ∼ 14 μm is 6.96 ∼ 11.90/8.65 ∼ 12.26; the α (m²/g) is 4.10 ∼ 5.13/4.04 ∼ 4.71. In addition, the attenuation rate (ρ; %) of the three graphite materials to infrared (8 ∼ 14 μm) in the sheeting/smoke box is 90.70 ∼ 96.20/71.00 ∼ 87.00 respectively. This study successfully established analytical techniques and evaluation standards for the infrared shielding effectiveness of commercial graphite, providing a reference for the selection of military smoke shielding materials.

本研究采用仪器分析比较了军用级石墨和两种商用石墨的材料性能和红外屏蔽性能。采用溴化钾（KBr）法和聚乙烯（PE）片法进行静态衰减试验，采用烟箱试验法进行动态衰减试验，研究石墨材料对红外光（IR）的衰减性能。利用热成像仪和傅里叶变换红外光谱仪（FTIR）测量了石墨材料的屏蔽效能和消光系数（α）。三种石墨材料具有相似的显微结构、晶体结构和表面现象，因此它们的红外屏蔽效能和α没有显著差异。实验结果表明，三种石墨材料在3 ~ 5/8 ~ 14 μm波长范围内的平均红外透过率（T; %）为6.96 ~ 11.90/8.65 ~ 12.26；α (m2/g)为4.10 ~ 5.13/4.04 ~ 4.71。此外，三种石墨材料在薄片/烟盒中对红外（8 ~ 14 μm）的衰减率ρ； %分别为90.70 ~ 96.20/71.00 ~ 87.00。本研究成功建立了商用石墨红外屏蔽效能的分析技术和评价标准，为军用防烟材料的选择提供了参考。

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引用次数: 0

Multivariate calibration models for ATR-FTIR spectroscopy analysis of olive oil adulterated with corn, sunflower, and palm oils 掺入玉米、向日葵和棕榈油的橄榄油的ATR-FTIR光谱分析的多变量校准模型

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-21 DOI: 10.1016/j.infrared.2026.106420

Esra modares Askari , Mohammadreza Khanmohammadi Khorrami , Mahsa Mohammadi , Miguel de la Guardia

Rapid analysis using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been developed for the detection of extra virgin olive oil (EVOO) adulterated with corn oil, sunflower oil (SFO), and palm oil. Measurements were conducted on EVOO and samples adulterated with varying contents of oils, ranging from 1.0 to 35% by weight. ATR-FTIR spectra were analyzed using a robust principal component analysis–multivariate adaptive regression splines (rPCA-MARS) model to assess the adulterated samples. Artificial neural networks (ANN) and support vector machines regression (SVM-R) were used to predict olive oil adulteration. The performance of these models, along with linear and cubic rPCA-MARS models, was evaluated using R² and RMSE. The linear rPCA-MARS model demonstrated the highest accuracy in predicting adulteration, with an R²pred value of 0.970 and MSE (pred) of 4.950. This model outperformed ANN, SVM-R, and piecewise cubic rPCA-MARS models based on key statistical metrics.

利用衰减全反射傅里叶变换红外（ATR-FTIR）光谱技术快速检测掺入玉米油、葵花籽油和棕榈油的特级初榨橄榄油（EVOO）。对EVOO和掺入不同含量油的样品进行了测量，重量从1.0到35%不等。ATR-FTIR光谱分析使用鲁棒主成分分析-多元自适应回归样条（rPCA-MARS）模型来评估掺假样品。采用人工神经网络（ANN）和支持向量机回归（SVM-R）对橄榄油掺假进行预测。使用R2和RMSE对这些模型以及线性和立方rPCA-MARS模型的性能进行评估。线性rPCA-MARS模型预测掺假的准确率最高，R2pred值为0.970,MSE （pred）为4.950。该模型在关键统计指标上优于ANN、SVM-R和分段立方rPCA-MARS模型。

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引用次数: 0

Five-channel terahertz switching enabled by a bilayer graphene metasurface with dual tuning mechanisms 具有双调谐机制的双层石墨烯超表面实现了五通道太赫兹开关

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-01-21 DOI: 10.1016/j.infrared.2026.106416

Wei Cui , Shasha Liang , Yixuan Wang , Zhihui He

To realize a terahertz/infrared absorber with a simple architecture, high absorption efficiency, and multi-frequency tunability, a compact bilayer graphene metasurface absorber is proposed. The design integrates etched rectangular graphene strips on the SiO₂ surface with a second continuous graphene layer embedded inside the dielectric, forming a five-frequency absorption metasurface, where the first four peaks exceed 98% (with two approaching 99%). Finite-difference time-domain (FDTD) simulations are used to examine the dependence of the absorption response on the polarization angle (PA) and the graphene Fermi level (E_f). Moreover, the interlayer spacing h is explored as a coupling parameter affecting the cavity confinement, while the resonance frequencies remain almost unchanged for incident angles up to 40°, showing excellent robustness to spacing variation and oblique illumination. Importantly, tuning PA and E_f enables five-channel switching with modulation depths (MD) above 99%, a minimum insertion loss (IL) of 0.0019 dB, and extinction ratios (ER) exceeding 20 dB, demonstrating outstanding multi-channel switching performance and strong application potential.

为了实现结构简单、吸收效率高、多频可调的太赫兹/红外吸收材料，提出了一种结构紧凑的双层石墨烯超表面吸收材料。该设计将在SiO2表面蚀刻的矩形石墨烯条与嵌入电介质内的第二层连续石墨烯层集成在一起，形成五频吸收超表面，其中前四个峰值超过98%（其中两个接近99%）。利用时域有限差分（FDTD）模拟研究了吸收响应与极化角（PA）和石墨烯费米能级（Ef）的关系。此外，研究了层间距h作为影响腔约束的耦合参数，而谐振频率在入射角为40°时几乎保持不变，对间距变化和倾斜照明表现出良好的鲁棒性。重要的是，调谐PA和Ef可以实现调制深度（MD）超过99%，最小插入损耗（IL）为0.0019 dB，消光比（ER）超过20 dB的五通道切换，显示出出色的多通道切换性能和强大的应用潜力。

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引用次数: 0