Line Edge Research Articles

Experimental and numerical investigation of thermal fatigue life in wedge specimens made of Ni-resist D5S cast iron

Thermal fatigue experiments were performed on a single-edge wedge specimen of Ni-resist D5S cast iron to reproduce the conditions to which exhaust manifolds are subjected during service. The leading edge temperature was cycled between 20°C and 850°C, and the temperature distribution on the specimen surface was measured with thermocouples during thermal cycling. Due to the complexity of the loads, a uncoupled thermomechanical computation of the problem was performed using the three-dimensional finite element code ABAQUS to evaluate the temperature, stress and strain distribution over a thermal fatigue specimen. The heat fluxes and forced convection coefficients generated by the thermal fatigue benchmark were optimized in both heating and cooling phases by reverse engineering to reproduce the experimental temperature-time profiles measured by thermocouples on the surface of the specimen. Then, an elastic-viscoplastic tow-layer model was used to simulate the mechanical behavior of the studied material. It was found that the maximum stress value was located in the center of the specimen at the edge of the wedge. This result was confirmed by experimental observations. The crack initiation zone is located in the edge zone and the direction of crack propagation is perpendicular to the edge line toward the thick part of the specimen. The saturation of the main crack propagation near the uniform specimen zone was mainly explained by the rapid decrease of the energy dissipated per cycle.

Impact of process variations on splitter-tree-based integrated optical phased arrays.

We consider the impact of intra-wafer systematic spatial variation, pattern density mismatch, and line edge roughness on splitter-tree-based integrated optical phased arrays. These variations can substantially affect the emitted beam profile in the array dimension. We study the effect on different architecture parameters, and the analysis is shown to be consistent with experimental results.

Design of a Novel Efficient High-Gain Ultra-Wide-Band Slotted H-Shaped Printed 2×1 Array Antenna for Millimeter-Wave Applications with Improvement of Bandwidth and Gain via the Feed Line and Elliptical Edges

This paper describes design procedure of a high-performance miniaturized antenna with an array configuration, which contributes to enhancing the communication system’s performance. The basic antenna features a compact size (6 x 6) mm2, and its single element is an H-shaped slotted patch printed on the top side of a Rogers RT5880 substrate, with a relative permittivity and thickness of 2.2 and 0.3 mm, respectively. The edge-to-edge distance of the 2 × 1 array antenna is 9 x 14 mm2, and the isolation between its radiation elements is 4.5 mm. To increase the capabilities of the antenna in terms of gain and bandwidth, we proceeded to use the 2 × 1 array configuration and then optimized the model via either the width of the feed line or the elliptical edges of the patch. The miniaturized array antenna achieved a peak gain of 12.56 dB, a directivity of 13.11 dBi, and a return loss of -47.52 dB at a resonance frequency of 91.5 GHz, with a radiation efficiency of more than 91% over an operating bandwidth of 15.83 GHz, ranging from 79.7 GHz to 95.6 GHz. The design and simulation results of the proposed antenna were obtained using the CST Studio software.

Buckle Pose Estimation Using a Generative Adversarial Network

The buckle before the lens coating is still typically disassembled manually. The difference between the buckle and the background is small, while that between the buckles is large. This mechanical disassembly can also damage the lens. Therefore, it is important to estimate pose with high accuracy. This paper proposes a buckle pose estimation method based on a generative adversarial network. An edge extraction model is designed based on a segmentation network as the generator. Spatial attention is added to the discriminator to help it better distinguish between generated and real graphs. The generator thus generates delicate external contours and center edge lines with help from the discriminator. The external rectangle and the least square methods are used to determine the center position and deflection angle of the buckle, respectively. The center point and angle accuracies of the test datasets are 99.5% and 99.3%, respectively. The pixel error of the center point distance and the absolute error of the angle to the horizontal line are within 7.36 pixels and 1.98°, respectively. This method achieves the highest center point and angle accuracies compared to Hed, RCF, DexiNed, and PidiNet. It can meet practical requirements and boost the production efficiency of lens coatings.

Nanoscale Phase Change Material Array by Sub-Resolution Assist Feature for Storage Class Memory Application

High density phase change memory array requires both minimized critical dimension (CD) and maximized process window for the phase change material layer. High in-wafer uniformity of the nanoscale patterning of chalcogenides material is challenging given the optical proximity effect (OPE) in the lithography process and the micro-loading effect in the etching process. In this study, we demonstrate an approach to fabricate high density phase change material arrays with half-pitch down to around 70 nm by the co-optimization of lithography and plasma etching process. The focused-energy matrix was performed to improve the pattern process window of phase change material on a 12-inch wafer. A variety of patternings from an isolated line to a dense pitch line were investigated using immersion lithography system. The collapse of the edge line is observed due to the OPE induced shrinkage in linewidth, which is deteriorative as the patterning density increases. The sub-resolution assist feature (SRAF) was placed to increase the width of the lines at both edges of each patterning by taking advantage of the optical interference between the main features and the assistant features. The survival of the line at the edges is confirmed with around a 70 nm half-pitch feature in various arrays. A uniform etching profile across the pitch line pattern of phase change material was demonstrated in which the micro-loading effect and the plasma etching damage were significantly suppressed by co-optimizing the etching parameters. The results pave the way to achieve high density device arrays with improved uniformity and reliability for mass storage applications.

Optimization of shadow evaporation and oxidation for reproducible quantum Josephson junction circuits

The most commonly used physical realization of superconducting qubits for quantum circuits is a transmon. There are a number of superconducting quantum circuits applications, where Josephson junction critical current reproducibility over a chip is crucial. Here, we report on a robust chip scale Al/AlOx/Al junctions fabrication method due to comprehensive study of shadow evaporation and oxidation steps. We experimentally demonstrate the evidence of optimal Josephson junction electrodes thickness, deposition rate and deposition angle, which ensure minimal electrode surface and line edge roughness. The influence of oxidation method, pressure and time on critical current reproducibility is determined. With the proposed method we demonstrate Al/AlOx/Al junction fabrication with the critical current variation (sigma /langle {I_{c} } rangle ) less than 3.9% (from 150 × 200 to 150 × 600 nm2 area) and 7.7% (for 100 × 100 nm2 area) over 20 × 20 mm2 chip. Finally, we fabricate separately three 5 × 10 mm2 chips with 18 transmon qubits (near 4.3 GHz frequency) showing less than 1.9% frequency variation between qubits on different chips. The proposed approach and optimization criteria can be utilized for a robust wafer-scale superconducting qubit circuits fabrication.

Enhanced etching resolution of self-assembled PS-b-PMMA block copolymer films by ionic liquid additives

Polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) is one of the most widely studied block copolymers for direct self-assembly because of its excellent compatibility with traditional processes. However, pattern transfer of PS-b-PMMA block copolymers (BCPs) remains a great challenge for its applications due to the insufficient etching resolution. In this study, the effect of ionic liquid 1-hexyl-3-methylimidazolium hexafluorophosphate (HMHF) additives on the line edge roughness (LER) performances of PS-b-PMMA self-assembled patterns was studied. Trace addition of HMHF kept the photolithography compatibility of PS-b-PMMA block copolymer films, but obviously increased their Flory–Huggins interaction parameter (χ) and enabled phase separation of disordered low molecular weight BCPs. LER value was effectively decreased by blending HMHF directly with PS-b-PMMA or from a supplying top layer of polyvinylpyrrolidone containing HMHF additives. This study shows an excellent strategy to improve the deficiencies of existing block copolymers.

COUNTERSAVIOR: AIoMT and IIoT-Enabled Adaptive Virus Outbreak Discovery Framework for Healthcare Informatics

In the current pandemic, global issues have caused health issues as well as economic downturns. At the beginning of every novel virus outbreak, lockdown is the best possible weapon to reduce the virus spread and save human life as the medical diagnosis followed by treatment and clinical approval takes significant time. The proposed COUNTERSAVIOR system aims at an Artificial Intelligence of Medical Things (AIoMT), and an edge line computing enabled and Big data analytics supported tracing and tracking approach that consumes global positioning system (GPS) spatiotemporal data. COUNTERSAVIOR will be a better scientific tool to handle any virus outbreak. The proposed research discovers the prospect of applying an individual’s mobility to label mobility streams and forecast a virus such as COVID-19 pandemic transmission. The proposed system is the extension of the previously proposed COUNTERACT system. The proposed system can also identify the alternative saviour path concerning the confirmed subject’s cross-path using GPS data to avoid the possibility of infections. In the undertaken study, dynamic meta direct and indirect transmission, meta behavior, and meta transmission saviour models are presented. In conducted experiments, the machine learning and deep learning methodologies have been used with the recorded historical location data for forecasting the behavior patterns of confirmed and suspected individuals and a robust comparative analysis is also presented. The proposed system produces a report specifying people that have been exposed to the virus and notifying users about available pandemic saviour paths. In the end, we have represented 3-D tracker movements of individuals, 3-D contact analysis of COVID-19 and suspected individuals for 24 h, forecasting and risk classification of COVID-19, suspected and safe individuals.

Determination of the Accuracy of the Straight Bevel Gear Profiles by a Novel Optical Coaxial Multi-Ring Measurement Method.

Straight bevel gears are widely used in mining equipment, ships, heavy industrial equipment, and other fields due to their high capacity and robust transmission. Accurate measurements are essential in order to determine the quality of bevel gears. We propose a method for measuring the accuracy of the top surface profile of the straight bevel gear teeth based on binocular visual technology, computer graphics, error theory, and statistical calculations. In our method, multiple measurement circles are established at equal intervals from the small end of the top surface of the gear tooth to the large end, and the coordinates of the intersection points of these circles with the tooth top edge lines of the gear teeth are extracted. The coordinates of these intersections are fitted to the top surface of the tooth based on NURBS surface theory. The surface profile error between the fitted top surface of the tooth and the designed surface is measured and determined based on the product use requirements, and if this is less than a given threshold, the product is acceptable. With a module of 5 and an eight-level precision, such as the straight bevel gear, the minimum surface profile error measured was -0.0026 mm. These results demonstrate that our method can be used to measure surface profile errors in the straight bevel gears, which will broaden the field of in-depth measurements for the straight bevel gears.

Computer Vision Method for In Situ Measuring Forming Accuracy of 3D Sand Mold Printing

The three-dimensional sand mold printing technology (3DSP) for casting sand molds via a binding jet is a breakthrough in the casting mold-making process. It is a favorable combination of digital forming technology and sand casting, which is a significantly interesting research area in the foundry industry. This study has proposed an edge extraction approach for the forming region in the sand bed image. With the edge information, the study measures the forming accuracy of the printed molds, which offers a basis for assessing the forming quality after 3DSP. The extracted edges essentially match the original image through the validation of cube printing. The error between the measured and actual size is below 0.6 mm, and the standard deviation of the straight line edge is below 0.170 mm, which fulfills the accuracy requirements for 3D sand mold printing.

Effect of trimming line design and edge extension of orthodontic aligners on force transmission: A 3D finite element study

ObjectivesTo investigate in a numerical study the effect of the geometry and the extension of orthodontic aligner edges and the aligner thickness on force transmission to upper right central incisor tooth (Tooth 11). MethodsA three-dimensional (3D) digital model, obtained from a 3D data set of a complete dentulous maxilla, was imported into 3-matic software. Aligners with four different trimming line designs (scalloped, straight, scalloped extended, straight extended) were designed, each with four different thicknesses (0.3, 0.4, 0.5, and 0.6 mm). The models were exported to a finite element (FE) software (Marc/Mentat). A facial 0.2 mm bodily malposition of tooth 11 was simulated. ResultsThe maximum resultant force was in the range of (7.5 - 55.2) N. The straight trimming designs had higher resultant force than the scalloped designs. The resultant force increases with increasing the edge extension of the aligner. The normal contact forces were unevenly distributed over the entire surface and were concentrated in six areas: Incisal, Mesio-Incisal, Disto-Incisal, Middle, Mesio-Cervical, and Disto-Cervical. The resultant force increases super linearly with increasing thickness. ConclusionsThe design of the trimming line, the edge extension, and the thickness of the aligner affect significantly the magnitude of the resultant force and the distribution of normal contact force. The straight extended trimming design exhibited better force distribution that may favor a bodily tooth movement. Clinical relevanceA straight extended trimming design of an orthodontic aligner may improve the clinical outcomes. In addition, the manufacturing procedures of the straight design are much simpler compared to the scalloped design.

Does the Condition of the Road Markings Have a Direct Impact on the Performance of Machine Vision during the Day on Dry Roads?

The forthcoming arrival of automated vehicles (AV) on the roads requires the re-evaluation or even adaptation of existing infrastructures as they are currently designed on the basis of human perception. Indeed, advanced driver-assistance systems (ADAS) do not necessarily have the same needs as drivers to detect road markings. One of the main challenges related to AV is the optimisation of the vehicle–infrastructure pair in order to guarantee the safety of all users. In this context, we compared the performance of a vehicle equipped with an ADAS machine-vision system with a dynamic retroreflectometer during the daytime on a road section. Our results questioned the reliability of the literature thresholds of the luminance contrast ratio on a dry road under sunny conditions. Despite the presence of old and worn road markings, the ADAS camera was able to detect the edge lines in more than 90% of the cases. The non-detections were not related to the poor condition of the markings but to the environmental conditions or the complexity of the infrastructure.

Line-encoded structured light measurement method in measuring shiny and transparent objects

Structured light measurement (SLM) has been widely used in acquiring the three-dimensional (3D) shape of objects because of its high precision and high speed. However, the intensity based structured light coding strategies like sinusoidal patterns is difficult to measure transparent and shiny objects with high dynamic range surface reflectance due to inaccurate light intensity information. Divergent multi-line structured light projection and traditional gray-code method avoids this problem by extracting lines. However, traditional gray-code method requires additional many patterns to distinguish the order of lines, which reduces the measurement efficiency. To overcome defects, this paper proposes a line-encoded few-pattern SLM method in measuring shiny and transparent objects. In this method, we simultaneously extract the edge line, the center line and obtain their orders by projecting only five patterns. Many experiments were implemented to prove its accuracy and robustness. Because only five patterns are required, the proposed method greatly accelerate the process of reconstruction, which is indispensable for 3D real-time reconstruction. We conducted a dental model dynamic scanning experiment to prove it.

Geo‐information mapping improves Canny edge detection method

AbstractAiming at the shortcomings of the current Canny edge detection method in terms of noise removal, threshold setting, and edge recognition, this paper proposes a method for improving Canny edge detection by geo‐information mapping. The shortcomings of the traditional Canny edge detection method are analyzed by using the Canny optimal criterion and Tobler's First Law, which points out the direction of edge detection optimization by using the difference between edge properties and noise properties. The property characteristics and spatial distribution rules of edge points and edge lines are inspected using the geographic information mapping theory and technical methods, and edge identification criteria are defined at two levels of edge points and edge lines. Finally, the method model of improved Canny edge detection is constructed by combining guided filtering. The experimental results show that the improved edge detection method has the advantages of enriched edge details, accurate edge recognition, and strong self‐adaptive capability. This is a new attempt of geo‐information mapping theory and technical method in image edge detection, which has certain theoretical significance and strong practical guidance.

Investigation and Prediction of Nano-Silver Line Quality upon Various Process Parameters in Inkjet Printing Process Based on an Experimental Method.

As an emerging additive manufacturing technology, inkjet printing has been increasingly applied in microelectronics field. However, due to the impacting and rebounding behaviors of conductive ink droplets impinging onto flat substrates, it is challenging to fabricate conductive lines with desired quality, such as suitable line width and line thickness, and matching resistance when it is used for interconnecting multifarious electronic components if there is not a proper configuration of operating parameters. To address this research gap, this article aims to investigate the effect of process parameters on the quality of conductive lines, including the platform temperature, printing speed, number of layers, and delay time (droplet interarrival time), are selected to conduct a full factorial experiment. First, the approximate parameter ranges for ensuring the continuity of conductive lines are determined. Second, this study analyzes the interactive effect among process parameters on line quality. Third, an artificial neural network (ANN) is constructed to predict the quality of printed lines. Results show that the line width does not increase with an increased number of layers, while the line thickness shows an increasing trend. The low resistance and high aspect ratio of printed line are achieved by printing 5 layers with the platform temperature of 70°C, the delay time of 12.2 ms, and the printing speed of 1139.39 mm/min. Moreover, the ANN model can be used to predict line width and line thickness with excellent performance, except for the resistance due to the irregular line edge. This study provides a useful guide for the selection of appropriate printing parameters to realize a diverse range of quality properties for 3D printed conductive lines in integrated circuits.

STRENUOUS: Edge-Line Computing, AI, and IIoT Enabled GPS Spatiotemporal Data-Based Meta-Transmission Healthcare Ecosystem for Virus Outbreaks Discovery

COVID-19 is not the last virus; there would be many others viruses we may face in the future. We already witnessed the loss of economy and daily life through the lockdown. In addition, vaccine, medication, and treatment strategies take clinical trials, so there is a need to tracking and tracing approach. Suitably, exhibiting and computing social evolution is critical for refining the epidemic, but maybe crippled by location data ineptitude of inaccessibility. It is complex and time consuming to identify and detect the chain of virus spread from one person to another through the terabytes of spatiotemporal GPS data. The proposed research aims an HPE edge line computing and big data analytic supported virus outbreak tracing and tracking approach that consumes terabytes of spatiotemporal data. The proposed STRENUOUS system discovers the prospect of applying an individual’s mobility to label mobility streams and forecast a virus-like COVID-19 epidemic transmission. The method and the mechanical assembly further contained an alert component to demonstrate a suspected case if there was a potential exposure with the confirmed subject. The proposed system tracks location data related to a suspected subject in the confirmed subject route, where the location data expresses one or more geographic locations of each user over a period. It recognizes a subcategory of the suspected subject who is expected to transmit a contagion based on the location data. System measure an exposure level of a carrier to the infection based on contaminated location data and a subset of carriers connected with the second location carrier. They investigated whether the people in the confirmed subject’s cross-path can be infected and suggest quarantine followed by testing. The proposed STRENUOUS system produces a report specifying that the people have been exposed to the virus.

Vegetation recovery and edge effects of low impact seismic lines over eight-year period in boreal uplands of northern Alberta

As of the mid-1990 s, low impact seismic (LIS) line construction (<3 m wide) became common practice in western Canada and replaced construction of wider (5–10 m) conventional seismic lines, with the intention of mitigating the known negative environmental impacts (e.g., severe soil damage and minimal vegetation recovery) of these long, narrow corridors used by the Oil and Gas (O&G) industry for exploration. Though the apparent disturbance severity on LIS lines is lower compared to conventional lines and it is expected that succession would proceed more readily towards the conditions resembling pre-disturbance forested state in the upland boreal, there is little scientific evidence that supports this. Here, we assess environmental conditions, successional trajectories and potential edge effects extending into the adjacent forest from the LIS line edges three (2014) and eight (2019) years after their construction in 2011, in the southern upland boreal forest of Swan Hills region in northwestern Alberta, to determine if active restoration measures should be recommended. Soil moisture and light were higher on the lines compared to the adjacent forest. Bryophytes (particularly feathermosses associated with late-succession forests) recovered well within eight years of disturbance (attaining nearly 90 % cover in 2019, from a relatively low cover (∼25 %) on the lines in 2014, compared to ∼ 80–90 % in the adjacent forest in both years), while the shrub and herbaceous layers recovered minimally, and tree species were still mostly absent on these lines. Herbaceous species also had a lower cover in the ∼ 2 m zone away from the line edges compared to the interior 75 m away, indicating edge effects in both years. Our results indicate that LIS lines appear to possess a unique combination of similarities and differences to other common boreal disturbances (fire, harvest), resulting in the equally unique successional trajectories that do not generally follow patterns known to occur in upland boreal forests. Long-term monitoring is imperative to determine whether LIS lines will eventually return to the pre-disturbance conditions or whether human intervention will be required to promote the growth of the canopy cover, especially as they constitute part of the habitat for Woodland caribou, an important threatened wildlife species.

Understanding and improving temporary road sign stability

Temporary road signage is used throughout road networks to regulate traffic and provide warnings to road users. Wind and other factors induce frequent falling of temporary road signage and are a major road safety concern that needs to be addressed. The main aim of this paper was to gain an understanding of temporary road sign stability in the presence of passing road trains and investigate the possibility of stabilising temporary road signage through appropriate design modifications. Simulations and experimental trials were carried out to assess the stability of current temporary road signs used in the industry. This analysis used Ansys Fluent to simulate fluid dynamics in order to infer road sign stability. A field experimental trial was performed in Western Australia’s Pilbara Region using a modified temporary road sign developed based on the outcome of the Ansys simulation. The findings from the simulations showed that the current design is unstable and highly prone to wind induced failure. The simulations suggest that road train transit at 100 km/h is capable of inducing approximately 8 m/s wind velocity in the proximity of the sign, which is greater than that permissible for a rigid sign with no leg mobility. Field trials showed that the modified sign remained stable at 1.2 m from the edge line although it was still prone to falling over at closer distances.

Canny Algorithm Enabling Precise Offline Line Edge Roughness Acquisition in High-Resolution Lithography.

The line edge roughness (LER) is one of the most critical indicators of photoresist imaging performance, and its measurement using a reliable method is of great significance for lithography. However, most studies only investigate photoresist resolution and sensitivity because LER measurements require an expensive and not widely available critical dimension scanning electron microscopy (SEM) technology; thus, the imaging performance of photoresist has not been adequately evaluated. Here, we report an image processing software developed for offline calculation of LER that can analyze lithographic patterns with resolutions up to ∼15 nm. This software can effectively process all graphic files obtained from commonly used SEM machines by utilizing the adjustable double threshold. To realize the effective detection of high-resolution patterns in advanced lithography, we used SEM images generated from extreme ultraviolet and electron beam lithography to develop and validate the software's graphic recognition algorithm. This image processing software can process typical SEM images and produce reliable LER in an efficient and user-friendly manner, constituting a powerful tool for promoting the development of high-performance photoresist materials.

A point cloud-based welding trajectory planning method for plane welds

Plane welds are a common type of weld in industrial sites. When the welding robot welds multiple types of plane welds at the same time, the traditional teaching and programming modes become relatively complicated. Therefore, in order to solve the problem of automatic robot welding of various types of plane welds, taking plane V-type butt, plane I-type butt, and plane lap welds as examples, this paper proposes a plane weld extraction method based on 3D vision. Firstly, in order to realize the line and plane segmentation of the workpiece point cloud, we establish the concept of plane point cloud density. Secondly, to segment workpiece edge lines, an iterative segmentation algorithm based on RANSAC is proposed. Then, based on the geometric features of the workpiece, a method for extracting weld feature points based on centroid positioning is proposed. Finally, the least squares method is used to fit the feature points of the welding seam to complete the welding trajectory planning. The experimental results show that the method can well solve the problem of automatic planning welding trajectory of plane V-type butt, plane I-type butt, and plane lap welds, to realize that the welding robot can simultaneously weld various plane welds without teaching and programming.