最新刊期
卷 41 ， 期 4 ， 2026
- 摘要：Blue phase liquid crystals（BPLCs）， as self-organized three-dimensional photonic crystals， have demonstrated broad application prospects in tunable photonic devices and spectral modulation. To broaden their range of reflection， we propose an electrically tunable polymer-stabilized blue phase liquid crystal （PSBPLC） system and validate it through theoretical analysis and experimental characterization. First， uniform monodomain BPLC is obtained via photoalignment， followed by photopolymerization to form polymer networks， thereby enhancing the structural stability. Subsequently， by applying a direct current （DC） voltage upon the liquid crystal cell， lattice deformation is induced， enabling wide-range tuning of the reflection spectrum. Furthermore， optical phase information is encoded into the orientation distribution of liquid crystal molecules， enabling holographic display applications via patterned alignment of PSBPs. Results indicate that， under the influence of DC electric field， the central wavelength of the reflection spectrum can be reversibly tuned from 439 nm to 662 nm. The corresponding reflective holographic phase design can reconstruct color images across the visible spectrum. This work provides a viable approach for developing stable， electrically tunable materials with a broad reflection range， showing promising potential in fields such as information display， optical encryption and photonic devices.关键词：liquid crystals;polymer-stabilized blue phase;electrically tunable;photoalignment;holography263|135|0更新时间：2026-09-12
- 摘要：Cholesteric liquid crystal elastomers （CLCEs） have attracted considerable attention in smart color-changing materials owing to their unique helical structures and tunable optical responses. However， the thermal color-change range of CLCEs is often limited by the constraints of the polymer network， resulting in a relatively narrow color-change range or requiring elevated temperatures to achieve significant optical variation. In this work， a series of cholesteric liquid crystal films （CLCFs） with varying crosslinking densities were prepared by introducing different amounts of the chain extender EDDET. The influence of crosslinking density on both thermochromic and mechanochromic behaviors was systematically investigated. Increasing the EDDET content effectively reduces the crosslinking density， leading to a significantly broadened thermochromic range. Within 20~100 ℃， a maximum red shift of 259 nm in the reflection wavelength was observed. Meanwhile， the thermal sensitivity was markedly enhanced， reaching a local maximum of 8.2 nm·℃-1 in the 60~80 ℃ range. Mechanical tests reveal that lower crosslinking density improves the elongation at break and enlarges the strain-induced blue-shift range. After pre-stretching treatment， the thermally induced wavelength shift of the CLCF can be extended to 340 nm， with an average thermal sensitivity of 4.31 nm·℃-1. These CLCFs， featuring a wide thermochromic range and high sensitivity， are promising candidates for smart sensing， information encryption， and wearable optical devices.关键词：cholesteric liquid crystal;polymer;thermochromism;optical sensing362|383|0更新时间：2026-09-12
Material Physics
- 摘要：To address the problem of voltage gradient and phase distribution non-uniformity in traditional comb-electrode liquid crystal（LC） lens， this study designs a electrode structure to improve optical performance. By optimizing the electrode layout without increasing the number of driving voltages， the issue of uneven voltage distribution between adjacent electrodes is resolved. The novel and conventional electrode LC lens samples were fabricated via photolithography. Their wavefront patterns and root-mean-square（RMS） errors were then analyzed through interferometry. Finally， the phase distribution and imaging performance of the LC lenses were analyzed. The results show that the novel electrode structure eliminates voltage gradient unevenness. The wavefront pattern exhibits a regular circular distribution， with wavefront RMS reduced by approximately 19.4% compared to the conventional structure. Both phase distribution and imaging performance are improved. This study confirms the effectiveness of electrode structure optimization in enhancing LC lens performance， and offers a technical approach for developing high-precision tunable-focus optical devices.关键词：liquid crystal lens;electrode structure;phase distribution;parabola185|221|0更新时间：2026-09-12
- 摘要：Leakage of light is a common phenomenon when a Liquid Crystal Display （LCD） screen displays a black pattern， mainly caused by the combination of the screen structure and the characteristics of the backlight system. A common and simple yet effective way to address this issue is to reduce the overall screen brightness， which can significantly decrease the visibility of the leakage. This paper systematically studies the variation rule of the liquid crystal response time after activating the dynamic backlight control， and measures the liquid crystal response time data under black and white pattern with different PWM（Pulse Width Modulation） duties output by the Timing Controller （TCON）. This is achieved through the Dynamic Backlight Control （DBC） function in the TCON， where the PWM duty output by the TCON is 40% of the input PWM when displaying a black pattern， and 100% of the input PWM when displaying a white pattern to the Light Emitting Diode （LED） driver. This method can improve the leakage of the black pattern， but in Direct Current （DC） dimming applications， combined with the mechanism of the LED driver identifying the PWM duty and then outputting the LED current， it will lead to an increase in the liquid crystal response time. The test result of the optical instrument is 51.9 ms， which seriously exceeds the design specification of Max 25 ms. To address this issue， this paper proposes an optimized scheme： the PWM duty for the white pattern output is adjusted to 99.6%， while the maximum brightness of the LCD screen remains unchanged. The measured liquid crystal response time can be shortened to 24.7 ms， which not only solves the problem of black pattern leakage but also meets the liquid crystal response time specification.关键词：LCD;LED;dynamic backlight control;liquid crystal response time276|223|0更新时间：2026-09-12
- 摘要：To address the issue of oblique-angle light leakage （azimuth angle ψ=45°， polar angle θ=60°） for ADS LCDs， an optical compensation film was designed and integrated into the polarizer. The study further investigated the oblique-angle light leakage and color shift of LCDs incorporating this optical compensation film. First， based on the mechanism of oblique-angle light leakage （off-axis light leakage） in ADS LCDs， TechWiz software was used to simulate a combination scheme of liquid crystal and compensation film that can effectively reduce oblique angle light leakage. Next， polarizers with different compensation values were produced and attached to the LCD screen. Finally， optical testing equipment was used to measure light leakage and color shift. Based on the combined results， the optimal optical compensation film solution was determined. The experimental results indicate that both compensation film schemes can reduce the brightness of oblique angle light leakage by more than 95%：Configuration ①： Negative liquid crystal （90°） + （+B） +（-C） compensation films （+B film： R₀=a， Rth=-a； -C film： R₀=0， Rth=a）. Configuration ②： Negative liquid crystal （90°） + （+C） + （+A） compensation films （+C film： R₀=0， Rth=-b； +A film： R₀=c， Rth=d）. The polarizer integrated with this optical compensation film can improve the phenomenon of whitening in ADS LCD at oblique viewing angle.关键词：liquid crystal display;optical compensation film;off-axis light leakage;color shift453|398|0更新时间：2026-09-12
- 摘要：Oxide semiconductor thin-film transistor（OS TFT） has become a core driving component of high-end display technology due to its advantages such as high mobility， excellent uniformity and low manufacturing cost， and is gradually expanding into integrated system fields such as sensors， memory， and neuromorphic computing. Based on the Web of Science and Incopat databases， this paper conducts a systematic analysis on the scientific research papers and patent data in the field of OS TFT from 2016 to 2025. Research has found that global R&D activities are highly concentrated in East Asia， with China and South Korea leading in the output of papers and patents. However， there is a clear academic-industry imbalance in this field： over 90% of the papers come from universities and research institutes， while 81.01% of the patents are held by enterprises， and the transformation of research into applications is insufficient. Meanwhile， the concentration of patents is relatively low， and technological barriers have yet to be formed. The key upstream material， sputtering targets， are still dominated by Japan （accounting for 54.55%）， posing a potential risk to the security of China’s industrial chain. In the future， OS TFT is poised to move beyond conventional display driving， forging deep convergence with sensor， memory， and neuromorphic computing.关键词：oxide semiconductor thin-film transistors;display;sensor;memory;neuromorphic computing443|351|0更新时间：2026-09-12
Device Physics and Device Preparation
- 摘要：Materials science research is trying to develop deep learning-based computer vision methods， but currently limited experimental data is difficult to support the exploration of such big data-based methods. This paper proposes an improved boundary equilibrium generative adversarial network （BEGAN） data augmentation model to address this issue. Firstly， replacing the normalization method in the generator network with spectral normalization reduces the requirement for training sample size compared to batch normalization； Secondly， adding residual modules to the generator/decoder of the model avoids overfitting and accelerates model training； Finally， a self-attention mechanism is added to enhance the model’s ability to extract defect details， resulting in smoother and faster convergence of loss parameters during the training process. This paper conducted ablation experiments and comparative experiments using a public dataset of steel defects. Through two evaluation metrics and classification network accuracy， the experiments demonstrated that the improved model significantly outperforms four mainstream generative models. Compared to the BEGAN model’s generative dataset， the image classification performance improved by 5.55%； the FID value decreased by 54.35%； the IS value increased by 18.18%. The performance of generated specimens proved this improved method is sufficient as an image enhancement method to cope with small sample problems.关键词：steel surface defect;data augmentation;neural network;generative adversarial network;self-attention mechanism260|441|0更新时间：2026-09-12
- 摘要：Accurate and efficient detection of steel surface defects is very important for industrial quality control. Although the RT-DETR model provides a good balance between speed and accuracy， its fixed feature extraction method and detection accuracy are still limited when dealing with complex and fine-grained defects. To this end， this paper proposes an improved detection algorithm based on RT-DETR-ICR-DETR. Firstly， UniRepLKNet is used as the backbone network to significantly improve the model’s perception of metal surface features. Secondly， the LWN-CS module is introduced into the neck network， which combines the learnable wavelet transform and channel shuffle mechanism to effectively enhance the high-frequency detail modeling and feature fusion capabilities. Finally， the Shape-WIoU loss function is designed， and the non-monotonic sample weighting mechanism of WIoU is fused with Shape-IoU to comprehensively model the shape feature and scale correlation of the bounding box， so as to improve the positioning accuracy and robustness. The experiment is carried out on the open steel surface defect dataset NEU-DET. The results show that ICR-DETR achieves 77.92% precision， 75.71% recall and 78.42% mAP， which is superior to the existing mainstream detection algorithms. In addition， in order to verify the generalization ability of the model， we conduct tests on the self-built sliding contact line shedding dataset ICRFD and heavy truck crack dataset FDMPI to verify its practicability and robustness in complex industrial environments. The experimental results show that the proposed ICR-DETR can effectively support high-precision defect detection tasks in complex industrial scenarios.关键词：defect detection;RT-DETR;sliding contact line;shape-IoU;NEU-DET260|279|0更新时间：2026-09-12
- 摘要：To address the challenges faced in citrus detection on fruit trees in natural environments， such as difficulty in distinguishing fruit maturity， severe occlusion from branches and leaves， high model complexity， and resource deployment limitations， this paper proposes a lightweight citrus maturity detection algorithm for fruit trees， YOLO-HiP， based on an improved YOLOv11. First， an improved HGNetv2-L network is used as the backbone， combined with a hierarchical feature extraction strategy， significantly enhancing the model’s capability to analyze complex scenes while effectively reducing computational complexity and resource consumption. Next， a lightweight hybrid attention module， C2PSA_iRMB， is designed. By integrating the C2PSA mechanism with the iRMB module， the computational cost is optimized， and the ability to process long-range information is enhanced， improving the module’s flexibility and computational efficiency. Finally， a C3k2_PConv module is constructed， further improving spatial feature extraction efficiency by reducing redundant computations and memory access. Experimental results show that YOLO-HiP achieves 94.3% mAP50， an improvement of 4.7% over the original model， with only 5.1M parameters （a 45.7% reduction）， a computational load of 13.9 GFLOPs （a 34.7% reduction）， and a frame rate of 227.4 FPS （a 25.1% increase）. This model significantly reduces model size while ensuring detection accuracy， providing an innovative and feasible solution for platforms with limited computational resources， such as citrus-picking robots and other embedded systems.关键词：citrus;maturity;YOLOv11;lightweight;object detection268|438|1更新时间：2026-09-12
- 摘要：Continual image segmentation suffers from catastrophic forgetting of previously learned classes， insufficient representation of newly introduced classes， and dynamic background semantic shifts in continual image segmentation.To address these issues， this paper proposes PAIS （Prototype-Aligned Incremental Segmentation）， a prototype-aligned incremental segmentation method for continual image segmentation. From the perspective of object-level representation stability， PAIS jointly models the initialization， evolution， and historical semantic compensation of decoder object queries during continual learning. Specifically， prototype-aware initialization（PAI） selects semantically salient positions from the current feature map to initialize object queries， thereby improving the modeling capability for new classes. Temporal consistency learning（TCL） constrains the consistency of key semantic positions and their response distributions across adjacent learning stages， which alleviates objectness degradation caused by feature drift. In addition， category-aware memory（CAM） maintains compact class-level memory representations to enhance old-class retention without relying on large-scale image replay. Experiments on continual panoptic segmentation and continual semantic segmentation on the ADE20K dataset demonstrate that the proposed method consistently outperforms representative methods such as ECLIPSE， BalConpas， and CoMFormer under multiple task settings， data splits， and input sequences. Under the setting covering 150 classes， the proposed method achieves a clear improvement in PQ while reducing storage requirements by approximately 10 times. These results show that PAIS provides a favorable balance among new-class adaptation， old-class retention， and memory efficiency.关键词：continual image segmentation;prototype alignment;temporal consistency learning;category-aware memory;panoptic segmentation70|104|0更新时间：2026-09-12
- 摘要：To address the limitations of existing shadow removal methods， such as insufficient modeling of global contrast relationships， limited regional differentiation processing capabilities， and the tendency to produce shadow residuals and boundary artifacts， a shadow removal network based on regional contrast and boundary perception is proposed.Firstly， a multi-scale attention mechanism is designed to enhance the consistency of image structure by utilizing complementary spatial representations and key region enhancement. Secondly， a shadow perception module is constructed to apply differentiated feature processing strategies to shadow and non-shadow regions， improving the continuity of shadow boundaries and their transition areas. Then， a visual contrast attention mechanism is proposed to enhance the ability to define cross-regional contrast relationships at the global scale. Finally， a joint loss function is designed， with a dynamic weight adjustment strategy to guide the model to achieve a coordinated optimization of pixel accuracy， structural consistency， and color stability.The experimental results show that， compared with 8 representative methods on the ISTD dataset， the PSNR is improved by an average of 1.57 dB， and compared with 10 representative methods on the SRD dataset， the PSNR is improved by an average of 2.03 dB. Meanwhile， with 12.3M parameters， the proposed method achieves an effective balance between reconstruction quality and model complexity.This method significantly reduces pixel-level brightness errors and effectively suppresses shadow residuals and boundary artifacts， achieving a more natural and reliable shadow removal effect.关键词：shadow removal;Multi-scale attention;shadow aware;visual contrast attention;cross-regional comparison232|417|0更新时间：2026-09-12
- 摘要：Relative radiometric normalization is a fundamental technique in multi-temporal remote sensing analysis， yet traditional methods often face limitations when dealing with nonlinear distortions， outlier interference， and heterogeneous land-cover conditions. To address these challenges， this paper proposes a diffusion-based probabilistic framework that models radiometric inconsistency as a combination of deterministic residuals and stochastic perturbations. Within this framework， the forward process simulates the multi-source characteristics of radiometric distortions through the superposition of structured and random noise， while the reverse process relies on a dual-objective variational optimization strategy to reconstruct radiometric consistency while preserving the detailed features of the original imagery， thereby achieving refined modeling of complex radiometric distortions at the mathematical level. Its core design is a spatial-spectral attention network， which integrates spatial and spectral attention modules to dynamically enhance key spectral band responses and local texture structures during feature extraction， enabling efficient capture of cross-band dependencies and multi-scale spatial context. To further improve the model’s adaptability in complex scenes， a preprocessing strategy based on the structural similarity index （SSIM） is designed. By automatically selecting stable pseudo-invariant regions to guide model training， it effectively reduces interference from land-cover changes and enhances the representativeness of training samples and the stability of model convergence. Comprehensive experiments on multi-temporal Sentinel-2 datasets demonstrate that the proposed method consistently outperforms existing comparative approaches in quantitative evaluation metrics. It not only achieves higher radiometric correction accuracy and spectral fidelity but also exhibits significant advantages in vegetation index consistency and texture detail preservation. In summary， this diffusion-driven network provides a practically adaptable solution for large-scale relative radiometric normalization of remote sensing imagery， and can be further extended to applications such as multi-sensor fusion and time series analysis in the future.关键词：relative radiometric normalization;diffusion model;attention mechanism;deep learning289|314|0更新时间：2026-09-12
Image Processing
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