Search Results (56)

Background/Objectives: Three-dimensional (3D) cell culture models more accurately simulate the in vivo tissue environments as compared to conventional two-dimensional (2D) monolayer cultures. Among these, spheroid cultures are particularly valuable for pharmaceutical research, as they allow for the study of tumor growth, drug responses, and cell–cell interactions in a physiologically relevant manner. Superhydrophobic surfaces (SHSs) have shown a promise in enhancing spheroid formation by reducing cell–substrate adhesion and promoting cell–cell aggregation. This study aims to evaluate the effectiveness of two different SHS coatings (SHS1: fluorinated; SHS2: silicone-based) in generating co-culture spheroids composed of non-tumoral fibroblasts (3T3) and tumoral epidermoid carcinoma cells (A431), thereby mimicking aspects of the tumor microenvironment. Methods: Co-cultures of 3T3 and A431 cells were seeded at varying ratios onto SHS1 and SHS2 substrates to assess their ability to support 3D spheroid formation. Spheroids were characterized by measurements of circularity and size distribution, viability through live/dead staining, and surface topography using 3D profilometry. Results: Spheroid formation was significantly influenced by both the surface properties and the fibroblast-to-carcinoma cell ratio. The fluorinated SHS1 surface facilitated superior cell viability and promoted the formation of well-rounded, uniform spheroids. In contrast, the silicone-based SHS2 surface resulted in less defined spheroidal structures and lower overall viability. Profilometry confirmed more consistent and compact 3D architectures on SHS1. Conclusions: This study demonstrates that SHS1, a fluorinated superhydrophobic coating, is more effective than SHS2 in supporting the formation of viable and structurally coherent 3D co-culture spheroids. These findings underscore the potential of SHS1 as a low-cost, tunable platform for developing in vitro cancer models and advancing the study of tumor–stroma interactions. Full article

Swimming goggles still face numerous challenges in practical use, including deterioration and failure of anti-fog coatings, residual water marks on lens surfaces, and relatively short service life in complex environments. When swimming outdoors during winter, goggles also present an icing problem. To address these problems and enhance the performance of swimming goggles, this study employs a combination of plasma cleaning and mechanical spraying methods, utilizing HB-139 SiO₂ to modify the surface of goggle lenses, thereby fabricating lenses with superhydrophobic properties. The changes in lens surfaces before and after friction and immersion treatments were characterized using three-dimensional profilometry and scanning electron microscopy, further investigating the hydrophobic, drag-reducing, wear-resistant, and anti-icing properties of the lenses. Experimental results demonstrate that SiO₂ can enhance the hydrophobic, drag-reducing, durability, and anti-icing performance of the lenses. Under standard conditions, the contact angle of modified samples reached 162.33 ± 3.15°, representing a 48.77 ± 2.15% improvement over original samples. Under friction conditions, modified samples exhibited a 45.86 ± 2.53% increase in contact angle compared to original samples, with Sa values decreasing by 58.64 ± 3.21%. Under immersion conditions, modified samples showed a 54.37 ± 2.44% increase in contact angle relative to original samples. The modified samples demonstrated excellent droplet bouncing performance at temperatures of −10 °C, 10 °C, and 30 °C. De-icing efficiency improved by 14.94 ± 2.37%. Throughout the experimental process, SiO₂ demonstrated exceptional hydrophobic, drag-reducing, durability, and anti-icing capabilities. This establishes a robust foundation for the exemplary performance of swimming goggles in both training and competitive contexts. Full article

This article is used to reconstruct mechanical parts with highly reflective surfaces. Three-dimensional reconstruction based on Phase Measuring Profilometry (PMP) is a key technology in non-contact optical measurement and is widely applied in the intelligent inspection of mechanical components. Due to the high reflectivity of metallic parts, direct utilization of the captured high-dynamic-range images often results in significant information loss in the oversaturated areas and excessive noise in the dark regions, leading to geometric defects and reduced accuracy in the reconstructed point clouds. Many image-fusion-based solutions have been proposed to solve these problems. However, unknown geometric structures and reflection characteristics of mechanical parts lead to the lack of effective guidance for the design of important imaging parameters. Therefore, an adaptive high-precision 3D reconstruction method of highly reflective mechanical parts based on optimization of exposure time and projection intensity is proposed in this article. The projection intensity is optimized to adapt the captured images to the linear dynamic range of the hardware. Image sequence under the obtained optimal intensities is fused using an integration of Genetic Algorithm and Stochastic Adam optimizer to maximize the image information entropy. Then, histogram-based analysis is employed to segment regions with similar reflective properties and determine the optimal exposure time. Experimental validation was carried out on three sets of typical mechanical components with diverse geometric characteristics and varying complexity. Compared with both non-saturated single-exposure techniques and conventional image fusion methods employing fixed attenuation steps, the proposed method reduced the average whisker range of reconstruction error by 51.18% and 25.09%, and decreased the median error by 42.48% and 25.42%, respectively. These experimental results verified the effectiveness and precision performance of the proposed method. Full article

Lubricating greases with varying proportions of gold mine tailings or SiO₂ as additives were prepared, and their friction and wear performance were evaluated using a four-ball tribometer. Scanning electron microscopy and three-dimensional surface profilometry were employed to analyze the thickener properties and wear patterns on the steel balls. The results indicated that the addition of gold mine tailings significantly improved the friction-reducing and wear-resistant properties of the base grease compared with SiO₂. At the optimal concentration of 3 wt%, the addition of gold mine tailings reduced the coefficient of friction and wear scar diameter of the base grease by 43.2% and 21.1%, respectively, yielding the best performance among the 11 tested samples. Further analysis revealed that silicate and calcium carbonate particles in the gold mine tailings were deposited on the surface, forming a protective layer. This layer, along with the grease film, contributed to substantial reductions in both friction and wear. Full article

Addressing the challenge of manual dependency and the difficulty in automating the online detection of height discrepancies following engine oil seal assembly, this paper proposes a composite vision-based method for the post-assembly size inspection of engine oil seals. The proposed method enables non-contact, online three-dimensional measurement of oil seals already installed on the engine. To achieve accurate positioning of the inner and outer ring regions of the oil seals, the process begins with obtaining the center point and the major and minor axes through ellipse fitting, which is performed using progressive template matching and the least squares method. After scaling the ellipse along its axes, the preprocessed image is segmented using the peak–valley thresholding method to generate an annular ROI (region of interest) mask, thereby reducing the complexity of the image. By integrating three-frequency four-step phase-shifting profilometry with an improved RANSAC (random sample consensus)-based plane fitting algorithm, the height difference between the inner and outer rings as well as the press-in depth are accurately calculated, effectively eliminating interference from non-target regions. Experimental results demonstrate that the proposed method significantly outperforms traditional manual measurement in terms of speed, with the relative deviations of the height difference and press-in depth confined within 0.33% and 1.45%, respectively, and a detection success rate of 96.35% over 1415 samples. Compared with existing methods, the proposed approach not only enhances detection accuracy and efficiency but also provides a practical and reliable solution for real-time monitoring of engine oil seal assembly dimensions, highlighting its substantial industrial application potential. Full article

Fringe projection profilometry (FPP) is a widely employed technique owing to its rapid speed and high accuracy. However, when FPP is utilized to measure shiny surfaces, the fringes tend to be saturated or too dark, which significantly compromises the accuracy of the 3D measurement. To overcome this challenge, this paper proposes an efficient method for the 3D measurement of shiny surfaces based on FPP. Firstly, polarizers are employed to alleviate fringe saturation by leveraging the polarization property of specular reflection. Although polarizers reduce fringe intensity, a deep learning method is utilized to enhance the quality of fringes, especially in low-contrast regions, thereby improving measurement accuracy. Furthermore, to accelerate measurement efficiency, a dual-frequency complementary decoding method is introduced, requiring only two auxiliary fringes for accurate fringe order determination, thereby achieving high-efficiency and high-dynamic-range 3D measurement. The effectiveness and feasibility of the proposed method are validated through a series of experimental results. Full article

Three-dimensional shape measurement plays an important role in various fields. As a way of three-dimensional measurement, fringe projection profilometry (FPP) is widely used because of its non-contact, simple structure, and high stability. One of the key challenges affecting measurement accuracy is the gamma effect. With the development of FPP technology, multi-color channels are gradually applied to the measurement, and the response of different colors in the projector-camera system (pro-cam system) is not exactly the same. Therefore, more accurate gamma correction for different color channels is required. To solve this problem, a model of joint gamma correction for different color channels is proposed. In this model, the light is subdivided into three channels: red; green; and blue (RGB). In the pro-cam system, the different responses of different colors and the influence of background light intensity on gamma correction are comprehensively considered, and some error compensation is made for color crosstalk. Compared with the traditional gamma correction methods, the gamma correction method proposed in this paper is more accurate and has a larger effective working range after correction. This method is particularly beneficial in scenarios where multiple color channels are used for measurement, as it more accurately reflects the true measurement results for each channel. The effectiveness and accuracy of the method are validated through experiments. Full article

Three-dimensional (3D) reconstruction of high-dynamic-range (HDR) surfaces plays an important role in the fields of computer vision and image processing. Traditional 3D measurement methods often face the risk of information loss when dealing with surfaces that have HDR characteristics. To address this issue, this paper proposes a simple 3D reconstruction method, which combines the features of non-overexposed regions in polarized and unpolarized images to improve the reconstruction quality of HDR surface objects. The optimum fringe regions are extracted from images with different polarization angles, and the non-overexposed regions in normally captured unpolarized images typically contain complete fringe information and are less affected by specular highlights. The optimal fringe information from different polarized image groups is gradually used to replace the incorrect fringe information in the unpolarized image, resulting in a complete set of fringe data. Experimental results show that the proposed method requires only 24~36 images and simple phase fusion to achieve successful 3D reconstruction. It can effectively mitigate the negative impact of overexposed regions on absolute phase calculation and 3D reconstruction when reconstructing objects with strongly reflective surfaces. Full article

This paper presents an effective three-dimensional (3D) surface reconstruction technique aimed at profiling composite surfaces with both specular and diffuse reflectance. Three-dimensional measurements based on fringe projection techniques perform well on diffuse reflective surfaces; however, when the measurement targets contain both specular and diffuse components, the efficiency of fringe projection decreases. To address this issue, the proposed technique integrates digital holography into the fringe projection setup, enabling the simultaneous capture of both specular and diffuse reflected light in the same optical path for full-field surface profilometry. Experimental results demonstrate that this technique effectively detects and accurately reconstructs the 3D profiles of specular and diffuse reflectance, with fringe analysis providing the absolute phase of composite surfaces. The experiments validate the effectiveness of this technique in the 3D surface measurement of integrated circuit carrier boards with chips exhibiting composite surfaces. Full article

The rapid evolution of microelectronics and display technologies has driven the demand for advanced manufacturing techniques capable of precise, high-speed microchip transfer. As devices shrink in size and increase in complexity, scalable and contactless methods for microscale placement are essential. Laser-induced forward transfer (LIFT) has emerged as a transformative solution, offering the precision and adaptability required for next-generation applications such as micro-light-emitting diodes (μ-LEDs). This study optimizes the LIFT process for the precise transfer of silicon microchips designed to mimic μ-LEDs. Critical parameters, including laser energy density, laser pulse width, and dynamic release layer (DRL) thickness are systematically adjusted to ensure controlled blister formation, a key factor for successful material transfer. The DRL, a polyimide-based photoreactive layer, undergoes photothermal decomposition under 355 nm laser irradiation, creating localized pressure that propels microchips onto the receiver substrate in a contactless manner. Using advanced techniques such as three-dimensional profilometry, X-ray photoelectron spectroscopy, and ultrafast imaging, this study evaluates the rupture dynamics of the DRL and the velocity of microchips during transfer. Optimization of the DRL thickness to 1 µm and a transfer velocity of 20 m s⁻¹ achieves a transfer yield of up to 97%, showcasing LIFT’s potential in μ-LED manufacturing and semiconductor production. Full article

Three-dimensional(3D) shape measurement using point clouds has recently gained significant attention. Phase measuring profilometry (PMP) is widely preferred for its robustness against external lighting changes and high-precision results. However, PMP suffers from long computation times due to complex calculations and its high memory usage. It also faces a 2π ambiguity issue, as the measured phase is limited to the 2π range. This is typically resolved using dual-wavelength methods. However, these methods require separate measurements of phase changes at two wavelengths, increasing the data processing volume and computation times. Our study addresses these challenges by implementing a 3D shape measurement system on a System-on-Chip (SoC)-type Field-Programmable Gate Array (FPGA). We developed a PMP algorithm with dual-wavelength methods, accelerating it through high-level synthesis (HLS) on the FPGA. This hardware implementation significantly reduces computation time while maintaining measurement accuracy. The experimental results demonstrate that our system operates correctly on the SoC-type FPGA, achieving computation speeds approximately 11.55 times higher than those of conventional software implementations. Our approach offers a practical solution for real-time 3D shape measurement, potentially benefiting applications in fields such as quality control, robotics, and computer vision. Full article

Cu pillars serve as interconnecting structures for 3D chip stacking in heterogeneous integration, whose height uniformity directly impacts chip yield. Compared to typical methods such as white-light interferometry and confocal microscopy for measuring Cu pillars, microscopic fringe projection profilometry (MFPP) offers obvious advantages in throughput, which has great application value in on-line bump height measurement in wafer-level packages. However, Cu pillars with large curvature and smooth surfaces pose challenges for signal detection. To enable the MFPP system to measure both the top region of the Cu pillar and the substrate, which are necessary for bump height measurement, we utilized rigorous surface scattering theory to solve the bidirectional reflective distribution function of the Cu pillar surface. Subsequently, leveraging the scattering distribution properties, we propose a hybrid bright-dark-field MFPP system concept capable of detecting weakly scattered signals from the top of the Cu pillar and reflected signals from the substrate. Experimental results demonstrate that the proposed MFPP system can measure the height of Cu pillars with an effective field of view of 15.2 mm × 8.9 mm and a maximum measurement error of less than 0.65 μm. Full article

Implants and other medical devices are prone to bacterial infections on their surface due to bacterial attachment and biofilm formation. In this study, silver nanoparticles were generated in situ onto regulated synthesized polydopamine particles, and the optimal amount of silver nitrate was determined. Composite micro–nano particles were then deposited on a titanium alloy surface. X-ray photoelectron spectroscopy and energy-dispersive X-ray spectroscopy were used to confirm that the titanium alloy surface was successfully coated with PDA-Ag. Scanning electron microscopy, transmission electron microscopy, and three-dimensional optical profilometry were utilized to analysis the morphology of the micro–nano particles and the surface morphology after deposition. The diameters of the polydopamine particles and silver nanoparticles were 150 nm and 25 nm, respectively. The surface roughness values decreased from 0.357 μm to 25.253 μm because of the coated PDA-Ag. Morphology and chemical composition analyses of the modified surface indicated that the PDA-Ag particles were uniformly bonded to the substrate surface. Antimicrobial assays illustrated that the PDA-Ag-modified surface possessed resistance against Escherichia coli and Staphylococcus aureus attachment, with an effectiveness of 96.14 and 85.78%, respectively. This work provides a new strategy and theoretical basis for tackling medical-related surface infections caused by bacterial adhesion. Full article

By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time–domain Gaussian fitting method is proposed in this paper. The concept of a time–domain Gaussian curve is firstly put forward, and the procedure of determining projector coordinates with a time–domain Gaussian curve is illustrated in detail. The neural network technique is applied to rapidly compute peak positions of time-domain Gaussian curves. Relying on the computing power of the neural network, the proposed method can reduce the computing time greatly. The binary defocusing technique can be combined with the neural network, and fast 3D profilometry with a large depth of field is achieved. Moreover, because the time–domain Gaussian curve is extracted from individual image pixel, it will not deform according to a complex surface, so the proposed method is also suitable for measuring a complex surface. It is demonstrated by the experiment results that our proposed method can extends the system DoF by five times, and both the data acquisition time and computing time can be reduced to less than 35 ms. Full article

The field of computer vision has been focusing on achieving accurate three-dimensional (3D) object representations from a single two-dimensional (2D) image through deep artificial neural networks. Recent advancements in 3D shape reconstruction techniques that combine structured light and deep learning show promise in acquiring high-quality geometric information about object surfaces. This paper introduces a new single-shot 3D shape reconstruction method that uses a nonlinear fringe transformation approach through both supervised and unsupervised learning networks. In this method, a deep learning network learns to convert a grayscale fringe input into multiple phase-shifted fringe outputs with different frequencies, which act as an intermediate result for the subsequent 3D reconstruction process using the structured-light fringe projection profilometry technique. Experiments have been conducted to validate the practicality and robustness of the proposed technique. The experimental results demonstrate that the unsupervised learning approach using a deep convolutional generative adversarial network (DCGAN) is superior to the supervised learning approach using UNet in image-to-image generation. The proposed technique’s ability to accurately reconstruct 3D shapes of objects using only a single fringe image opens up vast opportunities for its application across diverse real-world scenarios. Full article