Pixel Structure Research Articles

Liquid Crystal Display with High Transmittance and Excellent Image Quality

High transmittance and excellent image quality are two crucial requirements for thin-film transistor liquid crystal displays (TFT-LCDs). This work presents a novel pixel structure utilizing a vertical alignment liquid crystal (VA-LC) to improve both transmittance and image quality. The new pixel structure, called TCL-pixel, features a unique transparent conducting layer (TCL) that constructs an electric field shielding layer and a large transparent storage capacitor, resulting in good stability and a large aperture ratio. The 55" 8K product incorporating the TCL-pixel achieves high transmittance (3.87%) and a high contrast ratio (5100:1), attributed to the large aperture ratio. Additionally, it exhibits negligible vertical cross talk (0.7%), low color cross talk (3‰), low horizontal cross talk (JND 2.3), and enhanced variable refresh rate performance, confirming its good stability. Furthermore, the TCL-pixel demonstrates an improved viewing angle (CESI 0.03：65°) due to the multi-domain alignment produced by the transparent conducting layer.

Threshold Study for Hanzi Image Recognition: Defining Character and Component Limits in Chinese, Japanese, and Korean Script Processing

Chinese, Japanese, and Korean (CJK) Hanzi image recognition still faces significant challenges, particularly with pixel resolution, stroke count, character frequency and structure. This paper introduces the concepts of character and component thresholds to establish foundational parameters for Hanzi recognition, considering Unevenly Distributed Composite Character (UDCC), which account for up to 88% of Chinese characters. We compiled corpora of Simplified, Traditional characters, and Japanese Kanji, analyzing 3395 images with stroke counts ranging from 1 to 64, and developed the ZH-TC-IM965858 database, containing 33,950 images across 10 pixel resolutions. Using Euclidean distance and ResNet50 similarity analysis, we identified a character threshold of 26 strokes for 24[Formula: see text]×[Formula: see text]24 pixel images, a component threshold of 14 strokes, and a comprehensive threshold of 16 strokes. We found that 7.61% of 8105 common Chinese characters, 27.41% of 96,585 Traditional characters, and 5.99% of 2163 Japanese Kanji exceed this comprehensive threshold. Character Length and Character Frequency (CLCF) models were employed to explore relationships between stroke count, frequency, and thresholds. Additionally, Scale-invariant Feature Transform (SIFT) was applied to match radicals and components, providing insights for improving recognition accuracy. This research advances Hanzi image recognition and enhances multimodal Large Language Models (LLMs) for ideographic languages.

Transparent OLED displays for selective bidirectional viewing using ZnO/Yb:Ag cathode with highly smooth and low-barrier surface

Transparent organic light-emitting diode (TrOLED) displays represent cutting-edge technology posed to significantly enhance user experience. This study addresses two pivotal challenges in TrOLED development. Firstly, we focus on the innovation of transparent cathodes, a fundamental component in TrOLEDs, by introducing a ZnO/Yb:Ag cathode. This cathode employs a combination of seed layer and metal doping techniques to achieve a highly uniform surface morphology and a low surface energy barrier. The optimized Yb:Ag cathode on ZnO, with a mere thickness of 15 nm, exhibits remarkable properties: an extremely low surface roughness of 0.52 nm, sheet resistance of 11.6 Ω ϒ−1, an optical transmittance of 86.7% at 510 nm, and tunable work function (here, optimized to be 3.86 eV), ensuring superior electron injection capability. Secondly, we propose a novel TrOLED pixel structure that features selective bidirectional viewing, allowing different types of information to be selectively displayed on each side while preserving overall transparency and minimizing pixel complexity. This design innovation distinguishes itself from conventional TrOLEDs that display images on only one side. The bidirectional TrOLED design not only enhances openness and esthetic appeal but also holds promise for diverse applications across various user environments.

A CMOS-based image sensor pixel structure and application design

A CMOS-based image sensor pixel structure and application design

Design of Wideband Microstrip-to-Microstrip Vertical Transition With Pixel Structures Based on Reinforcement Learning

Design of Wideband Microstrip-to-Microstrip Vertical Transition With Pixel Structures Based on Reinforcement Learning

A Universal Method for Quantitatively Measuring Land Surface Anomaly Intensity Using Multiscale Remote Sensing Features

Land surface anomalies refer to various activities on the Earth’s surface that consist of short-term and sudden changes due to external disturbances. These anomalies are closely related to the safety of human life and property. Remote sensing offers irreplaceable advantages such as broad coverage, high temporal dynamics, and comprehensive observations, so it is the most effective tool for monitoring land surface anomalies and measuring their intensities. However, existing studies have limitations such as unclear sensitivity features, uncertain applicability, and a lack of quantitative expression at different scales. Therefore, this study develops a quantitative assessment framework for land surface anomaly intensity across four scales: the pixel scale, structure scale, object scale, and scene scale. This framework enables an adaptive and flexible weight determination of the intensity of land surface anomalies from a satellite perspective. Using the Chongqing fire as an example of a land surface anomaly, this study evaluates its land surface anomaly intensity. Moreover, we demonstrate the method’s applicability to other land surface anomaly events, such as floods and earthquakes. The experiments reveal that the land surface anomaly intensity evaluation framework, which is constructed based on pixel-scale, structure-scale, object-scale, and scene-scale features, can quantitatively express the land surface anomaly intensity with an accuracy of 75.25% and more effectively represent severely affected areas. The weights of the features at the four scales sequentially decrease: structure scale (0.2974), pixel scale (0.3225), object scale (0.1867), and scene scale (0.1932). The extensive application of this method to other land surface anomaly events provides accurate quantitative expressions of the land surface anomaly intensity. This remote sensing-based multiscale feature assessment method is adaptable and applicable to various land surface anomalies and offers critical decision support for land surface anomaly intensity warning systems.

A spike-based background light suppression lock-in pixel for 2D&3D synchronous imaging

In this paper, a 32 × 32 ToF image sensor with a spike-based lock-in pixel is presented. The pixel has an in-pixel background light suppression circuit which converts the infrared light into spike number and realizes self-suppression of the background light without filter. This pixel structure can realize 2D and 3D synchronous imaging. This ToF image sensor is implemented in a 110 nm one-poly four-metal CMOS technology with a size of 3903 μm × 3330 μm. The lock-in pixel as the key part of this sensor has a size of 27.5 μm × 27.5 μm. Measurement results show that this ToF image sensor can image in the range of 20 cm–45 cm under the background light range of 0–12000 lux without filter and the maximum relative error is 3.6 %. Therefore, this ToF image sensor with the proposed lock-in pixel can suppress background light effectively without filter and realize 2D and 3D synchronous imaging.

Research on high dynamic pixel structure based on adaptive integral capacitor

Infrared image sensing technology has attracted wide attention due to its advantages such as being unaffected by the environment, good target recognition, and strong anti-interference ability. However, with the improvement of the integration of infrared focal planes, the constraints between the dynamic range, noise, and full-shade of the optoelectronic system are particularly prominent. Therefore, in order to solve the contradiction between noise in weak light and full-shade capacity in strong light, in a 5 T infrared pixel circuit, the relationship between the capacitance value and voltage of the inverted MOS capacitor in a specific voltage range is used to make the integral capacitance of the infrared image sensor automatically change from 6.5 fF to 37.5 fF. A high dynamic pixel structure based on adaptive integral capacitance is proposed. Based on 55 nm CMOS process technology, 12288 × 12288its performance parameters are studied in a pixel-scale infrared sensor. The research results show that 5.5m × 5.5mthe small-size pixel has a large full-shade capacity of 1.31 Me- and a variable conversion gain, a noise of less than 0.43 e, and a dynamic range of more than 130 dB.

Impact of Display Sub-Pixel Arrays on Perceived Gloss and Transparency.

In recent years, improvements in display image quality have made it easier to perceive rich object information, such as gloss and transparency, from images, known as shitsukan. Do the different display specifications in the world affect their appearance? Clarifying the effects of differences in pixel structure on shitsukan perception is necessary to realize shitsukan management for displays with different hardware structures, which has not been fully clarified before. In this study, we experimentally investigated the effects of display pixel arrays on the perception of glossiness and transparency. In a visual evaluation experiment, we investigated the effects of three types of sub-pixel arrays (RGB, RGBW, and PenTile) on the perception of glossiness and transparency using natural images. The results confirmed that sub-pixel arrays affect the appearance of glossiness and transparency. A general relationship of RGB > PenTile > RGBW for glossiness and RGB > RGBW > PenTile for transparency was found; however, detailed analysis, such as cluster analysis, confirmed that the relative superiority of these sub-pixel arrays may vary depending on the observer and image content.

A differential network with multiple gated reverse attention for medical image segmentation

UNet architecture has achieved great success in medical image segmentation applications. However, these models still encounter several challenges. One is the loss of pixel-level information caused by multiple down-sampling steps. Additionally, the addition or concatenation method used in the decoder can generate redundant information. These limitations affect the localization ability, weaken the complementarity of features at different levels and can lead to blurred boundaries. However, differential features can effectively compensate for these shortcomings and significantly enhance the performance of image segmentation. Therefore, we propose MGRAD-UNet (multi-gated reverse attention multi-scale differential UNet) based on UNet. We utilize the multi-scale differential decoder to generate abundant differential features at both the pixel level and structure level. These features which serve as gate signals, are transmitted to the gate controller and forwarded to the other differential decoder. In order to enhance the focus on important regions, another differential decoder is equipped with reverse attention. The features obtained by two differential decoders are differentiated for the second time. The resulting differential feature obtained is sent back to the controller as a control signal, then transmitted to the encoder for learning the differential feature by two differential decoders. The core design of MGRAD-UNet lies in extracting comprehensive and accurate features through caching overall differential features and multi-scale differential processing, enabling iterative learning from diverse information. We evaluate MGRAD-UNet against state-of-theart (SOTA) methods on two public datasets. Our method surpasses competitors and provides a new approach for the design of UNet.

Integrated 3D printing of reconfigurable soft machines with magnetically actuated crease-assisted pixelated structures

Reconfigurable magnetic soft machines have a wide range of applications in soft robotics, aerospace, medical devices and flexible electronics. However, the high-precision reconfiguration of magnetically actuated soft machines is hindered by the absence of rational structural design and integrated manufacturing techniques. Here, we report an innovative design and manufacturing approach to realize magnetically actuated high-precision reconfigurability. We present a crease-assisted pixelated design using a mixture of magnetic particles and phase-change medium as the pixel points, with an elastomer as the crease to connect the pixel points, simulating origami. The design of elastomer creases improves pixel stiffness without loss of reconfigurable accuracy, thereby significantly improves the magnetic particle concentration in the pixel. An effective multi-material 3D printing technique is used to achieve the integrated printing of the designed structure. The resulting magnetically actuated soft machines exhibit remarkable capabilities, achieving small curvature bending and precise reconfiguration with weaker actuating magnetic fields (100mT). The superior performance of this design has been confirmed through demonstrations of crawling and rolling machines, magnetically controlled switches, and logic circuits. The work enhances the reconfiguration accuracy of magnetically actuated soft machines, increasing their potential for soft robotics and flexible electronics applications.

Design and Initial Tests of a Fast Neutron Radiography Detector Prototype with Silicon Photomultiplier Readouts

Among non-destructive testing (NDT) techniques, fast neutron radiography with a higher penetration capability has achieved rapid advancements. However, the application of the radiography detector in many fast neutron imaging systems is limited by unfavorable detection efficiency and imaging spatial resolution. In this paper, a fast neutron radiography detector was designed, which was composed of a pixelated EJ200 scintillator array, a 16 × 16 silicon photomultiplier (SiPM) array, and capacitive multiplexing network readout electronics. The main parameters of the detector were optimized using Monte Carlo simulations. In addition, the prototype of the detector was fabricated and tested under a 14 MeV D-T neutron source. The preliminary test results demonstrated that the spatial resolution of the prototype reached 1.2 mm. Moreover, the conflict between spatial resolution and detection efficiency could be mitigated by using a pixelated scintillator structure. Overall, SiPMs enabled the extensive application of the imaging system because of their excellent photon detection performance, relatively low price, and joint possibility for large areas.

Solution to the issue of high-order diffraction images for cylindrical computer-generated holograms

The cylindrical computer-generated hologram (CCGH), featuring a 360° viewing zone, has garnered widespread attention. However, the issue of high-order diffraction images due to pixelated structure in CCGH has not been previously reported and solved. For a cylindrical model offering a 360° viewing zone in the horizontal direction, the high-order diffraction images always overlap with the reconstruction image, leading to quality degradation. Furthermore, the 4f system is commonly used to eliminate high-order diffraction images in planar CGH, but its implementation is predictably complex for a cylindrical model. In this paper, we propose a solution to the issue of high-order diffraction images for CCGH. We derive the cylindrical diffraction formula from the outer hologram surface to the inner object surface in the spectral domain, and based on this, we subsequently analyze the effects brought by the pixel structure and propose the high-order diffraction model. Based on the proposed high-order diffraction model, we use the gradient descent method to optimize CCGH accounting for all diffraction orders simultaneously. Furthermore, we discuss the issue of circular convolution due to the periodicity of the Fast Fourier Transform (FFT) in cylindrical diffraction. The correctness of the proposed high-order diffraction model and the effectiveness of the proposed optimization method are demonstrated by numerical simulation. To our knowledge, this is the first time that the issue of high-order diffraction images in CCGH has been proposed, and we believe our solution can offer valuable guidance to practitioners in the field.

Flexibly Designable 2D Chiral Metasurfaces with Pixelated Topological Structure Based on Machine Learning

Abstract2D chiral metasurface have been widely used for planar circular dichroism (CD) devices. However, the design of 2D metasurfaces usually means a time‐consuming search of effective structures, which are typically limited to regular geometries and compromised performances. Here, an efficient method for 2D chiral metasurfaces with pixelated topological structure based on machine learning (ML) is proposed and demonstrated from which simultaneous high CD and extinction ratio (ER) either over broadband or at specific wavelength can be efficiently achieved. The proposed ML method combines both advantages of high efficiency of neural network (NN) and superior goal evolution ability of microbial genetic algorithm (MGA). Unlike traditional empirical‐driven methods, the hybrid framework and pixelated topologically deformable structures can fully exploit the potential of design space and push design capability to its physical limit. An average CD of 94.7% and ER of 15 dB over wavelength from 1.45–1.65 µm and a CD of >90%/ER of >27 dB at freely‐selected wavelength of 1.54 and 1.616 µm are obtained. Experiments with fabricated topological structures validate the theoretical predictions. The proposed pixelated structures with ML provide a universal method for precise tailoring of optical properties of metasurfaces which is otherwise unattainable with conventional regular geometries.

Gate-controlled gain tuning of fully depleted silicon-on-insulator-based 1 T pixel for in-sensor white balance

White balance (WB) is a critical back-end processing function in image sensors to keep color constancy under various lighting conditions by adjusting the RGB color channel gain values. In this work, we proposed a novel gate-controlled gain-tuning method for a fully depleted silicon-on-insulator (FDSOI) one-transistor (1 T) pixel to achieve WB inside the sensor. Based on the pixel structure of a p-well under the buried oxide for sensing and an n-type nMOSFET on the top for readout, the 1 T pixel output gain is modulated by the MOSFET gate according to the transistor transfer characteristics. About 5x gain modulation range in RGB spectrum photoresponse (nonlinearity < 3%) is experimentally demonstrated in the devices fabricated by 22 nm FDSOI-based technology. The scheme for in-sensor WB demonstration is provided with a novel 1 T pixel array design, and the evaluation result shows in-sensor WB achieving an almost equivalent performance (Delta-E deviation < 1) compared with using conventional back-end WB.

Discussion of Mechanical Shock Test Stress for Ultra-large-scale CMOS Image Sensors

The ultra-large-scale CMOS image sensors are significantly different from the traditional CMOS image sensors in terms of pixel size, chip size and structure. CMOS image sensors generally come with an optical window structure that is sealed to the ceramic housing by means of adhesive. The optical window material is generally sapphire, and the larger the image element size, the larger the required glass optical window area. Ultra-large size CMOS image sensors in the package before the general optical window thickness, parallelism, light window average transmittance assessment. The object of mechanical impact test assessment is the CMOS image sensor optical window structure and capping process. The paper mainly discusses the typical failure cases of ultra-large-scale CMOS image sensors on the basis of the applicability of mechanical shock test standards, and investigates how to define the mechanical shock test stress from simulation, limit test and the requirements by users. This paper provides the qualification assessment basis of mechanical shock for newly developed products.

Analysis for the Influence of Pixel Structure in Backside Illuminated CMOS Image Sensor

Analysis for the Influence of Pixel Structure in Backside Illuminated CMOS Image Sensor

Optimized design of nano-photonic devices for temperature self-regulating on vanadium dioxide thin films

Phase change materials can enable temperature self-regulation due to their drastic changes in optical properties accompanying the phase transition. Significant reduction of the optical absorption after the transition is the key ingredient for an enhanced regulating performance. However, the absorptivity of unpatterned vanadium dioxide (VO2) thin films can hardly be reduced after phase transition at visual-to-infrared band. In this work, we combine the direct binary search (DBS) and particle swarm optimization (PSO) algorithms for an optimized design of temperature self-regulating nano-photonic devices on VO2 thin films. For a given incident wavelength, a pixelated structure is firstly inverse-designed by the DBS algorithm which maximizes the absorption contrast before and after the transition. To overcome fabrication challenges as pixel size is at deep sub-wavelength scale, the pixelated structure can then be replaced by geometric shapes which are more tractable in manufacturing processes. The geometrical parameters are optimized by the PSO algorithm where our optimized device brings the absorptivity down to 33% after the transition. These results provide an effective way for the inverse design of optimized nano-photonic structures based on phase change materials.

High Dynamic Pixel Structure Based on an Adaptive Integrating Capacitor.

Infrared image sensing technology has received widespread attention due to its advantages of not being affected by the environment, good target recognition, and high anti-interference ability. However, with the improvement of the integration of the infrared focal plane, the dynamic range of the photoelectric system is difficult to improve, that is, the restrictive trade-off between noise and full well capacity is particularly prominent. Since the capacitance of the inversion MOS capacitor changes with the gate-source voltage adaptively, the inversion MOS capacitor is used as the capacitor in the infrared pixel circuit, which can solve the contradiction between noise in low light and full well capacity in high light. To this end, a highly dynamic pixel structure based on adaptive capacitance is proposed, so that the capacitance of the infrared image sensor can automatically change from 6.5 fF to 37.5 fF as the light intensity increases. And based on 55 nm CMOS process technology, the performance parameters of an infrared image sensor with a 12,288 × 12,288 pixel array are studied. The research results show that a small-size pixel of 5.5 µm × 5.5 µm has a large full well capacity of 1.31 Me- and a variable conversion gain, with a noise of less than 0.43 e- and a dynamic range of more than 130 dB.

A 3.0 µm Pixels and 1.5 µm Pixels Combined Complementary Metal-Oxide Semiconductor Image Sensor for High Dynamic Range Vision beyond 106 dB.

We propose a new concept image sensor suitable for viewing and sensing applications. This is a report of a CMOS image sensor with a pixel architecture consisting of a 1.5 μm pixel with four-floating-diffusions-shared pixel structures and a 3.0 μm pixel with an in-pixel capacitor. These pixels are four small quadrate pixels and one big square pixel, also called quadrate-square pixels. They are arranged in a staggered pitch array. The 1.5 μm pixel pitch allows for a resolution high enough to recognize distant road signs. The 3 μm pixel with intra-pixel capacitance provides two types of signal outputs: a low-noise signal with high conversion efficiency and a highly saturated signal output, resulting in a high dynamic range (HDR). Two types of signals with long exposure times are read out from the vertical pixel, and four types of signals are read out from the horizontal pixel. In addition, two signals with short exposure times are read out again from the square pixel. A total of eight different signals are read out. This allows two rows to be read out simultaneously while reducing motion blur. This architecture achieves both an HDR of 106 dB and LED flicker mitigation (LFM), as well as being motion-artifact-free and motion-blur-less. As a result, moving subjects can be accurately recognized and detected with good color reproducibility in any lighting environment. This allows a single sensor to deliver the performance required for viewing and sensing applications.