Mass Production Research Articles

SPEED: an integrated, smartphone-operated, handheld digital PCR Device for point-of-care testing

This study elaborates on the design, fabrication, and data analysis details of SPEED, a recently proposed smartphone-based digital polymerase chain reaction (dPCR) device. The dPCR chips incorporate partition diameters ranging from 50 μm to 5 μm, and these partitions are organized into six distinct blocks to facilitate image processing. Due to the superior thermal conductivity of Si and its potential for mass production, the dPCR chips were fabricated on a Si substrate. A temperature control system based on a high-power density Peltier element and a preheating/cooling PCR protocol user interface shortening the thermal cycle time. The optical design employs four 470 nm light-emitting diodes as light sources, with filters and mirrors effectively managing the light emitted during PCR. An algorithm is utilized for image processing and illumination nonuniformity correction including conversion to a monochromatic format, partition identification, skew correction, and the generation of an image correction mask. We validated the device using a range of deoxyribonucleic acid targets, demonstrating its potential applicability across multiple fields. Therefore, we provide guidance and verification of the design and testing of the recently proposed SPEED device.

Single-exposure femtosecond laser direct writing of Salvinia-inspired micropatterned functional surface

Bioinspired functional surfaces have attracted considerable attention within multiple scientific and industrial fields. In particular, the hollow hierarchical structure and chemical heterogeneity endow Salvinia leaves with superhydrophobicity and underwater air retention capability. However, replicating complex three-dimensional Salvinia-like patterns at the microscale currently relies on time-consuming additive manufacturing methods, preventing their wide adoption in industrial applications. Here, we report a high-throughput femtosecond laser direct writing strategy based on the quadrifurcate abruptly autofocusing beam for the single-exposure fabrication of Salvinia-like microstructures. Combined with chemical functionalization, both the hollow morphology and heterogeneous chemical properties of the natural counterpart were mimicked. The obtained bioinspired surfaces can repel and manipulate water droplets, and maintain superhydrophobicity even immersed underwater. The proposed single-exposure fabrication strategy is expected to contribute to the mass production of Salvinia-inspired surfaces, whose unique wetting properties promise great potential in chemical engineering, micro bioanalysis, and microfluidic devices.

Half bridge configurated magneto-resistive sensors with flux guide structure for enhancing sensitivity

We demonstrate the enhancement in sensitivity of half Wheatstone bridge configurated magneto-resistive sensors with a design of the magnetic flux guide. The efficacy of our flux guide design, in comparison to the conventional micro-magnetic flux concentrator for improving the flux gain, is studied using finite element method and verified with the experimental result. We observed a sensitivity of 260%/mT for our half Wheatstone bridge sensor with a very small coercivity of 0.01 mT at room temperature. Our work will contribute to paving a road map for mass production of sensitive magneto-resistive sensors with small footprints (2.5 mm2 in this study).

A novel method for air assisted nanosecond pulsed fiber laser beam transmission micro-channelling on thick PMMA material

The demand for scaling up polymeric materials for mass production or scaling down for microscale applications is at its peak in the modern era. Laser beam technology enables the formation of micro-channels on polymers, specifically polymethyl methacrylate (PMMA). This study examines the viability and cost-effectiveness of employing the diode pump fiber laser transmission technique to create micro-channels on thick, transparent PMMA under air-assisted circumstances for biomedical engineering and micro-fluidics applications. The analysis has included process variables such as pulse frequency, power, and cutting speed, as well as machining parameters including depth of cut, kerf width, and heat-affected zone (HAZ) width. The results of multi-objective optimization indicate that the following parameters—a pulse frequency of 51.30 kHz, a working power of 13 % of 50 W, and a cutting speed of 0.60 mm/s—contribute to the desired microfluidics response values: 12.54 µm depth of cut, 24.05 µm kerf width, and 5.98 µm HAZ width.

Numerical analysis of a protective coating for mining industry feed chute

The selection of materials for the protective coating of a crusher’s feed chute significantly influences the mean time between failures (MTBF) and operational costs associated with the mass production of sulfuric acid at MMG/Kinsevere. Neglecting the condition of the protective coating can pose a serious challenge to production efficiency and result in increased downtime. This study focuses on enhancing industrial productivity in Sulfuric Acid production with minimal maintenance. The investigation explores the quality and type of materials used for the protective coating of the feed chute in the mining industry, particularly at MMG/Kinsevere, utilizing Ansys Fluent and SOLIDWORKS Software for analysis. The paper proposes a Ceramic protective liner for the crusher feed chute due to its superior resistance to erosion compared to other liners. Different feed chute models, constructed with materials like halogenated butyl rubber, 316 stainless steel, and ceramic, underwent analysis. The evaluation of the potential impact on the mean time between failures (MTBF) for different materials used in a protective coating, considering the rate of erosion through computational fluid dynamics (CFD) with ANSYS FLUENT software, is a central aspect of this study. The detailed modeling and simulation reveal that the ceramic material exhibits the most favorable protective coating characteristics, with an erosion rate density of 06.636753 kg/m2s, outperforming halogenated butyl rubber (3.326576 kg/m2s) and 316 stainless steel (2.186633 kg/m2s). The simulation yielded results corresponding to flow rates of 284.19 kg/s for the solid phase and 123.14 kg/s for the liquid phase.

The trend of “films as tourism promotion”: from picturesque landscapes to eco-consciousness in Vietnamese masses

Along with the intense globalisation process in Vietnam since the early 21st century, there has been a bloom of commercial films shot in the famous places of this country named ‘films as tourism promotion’. However, behind the eye-catching frames, the picturesque landscape, and the smooth cinematography, whether those films accompany the ecological discourse of preserving the indigenous natural environment is another complicated problem that needs to be challenged in this research. Since then, we will consider the effects of socialist nationalism and capitalism’s mass production on the eco-consciousness of the film audiences/masses, how they give the viewers a firm belief in the indestructible and sustainable beauty of the national landscapes, and how they distract the audience’s visual interest from practical issues. Also, we aim to examine the ecological status of these tourist sites after the movies were released to determine the chain-related environmental consequences of this cinematic trend.

Core-shell 3D printed biodegradable calcium phosphate cement—Alginate scaffolds for possible bone regeneration applications

The core/shell 3D printing process using CPC and alginate is intended to create biodegradable scaffolds that have a similar stability to bone tissue and also offer sufficient and continuous antibiotic release. In this way, a patient-specific and patient-friendly process will be established, which should optimally support the human organism in its regeneration. To generate the best possible strength values, the printed scaffolds underwent various post-treatments and were then tested in a material test. The test methods included self-setting, storage in a drying cabinet with a water-saturated atmosphere at 37°C, followed by incubation in PBS, freeze-drying, and coating the samples with alginate. Additionally, a degradation test at pH 7.4 and pH 5 was carried out to test stability under in vitro conditions. It was shown that the untreated and freeze-dried samples failed at a maximum load of 30–700 N, while the remaining scaffolds could withstand a load of at least 2,000 N. At this failure load, most of the test series showed an average deformation of 43.95%. All samples, therefore, remained below the strength of cancellous bone. However, based on a 20% load after surgery, the coated scaffolds represented the best possible alternative, with a Young’s modulus of around 1.71 MPa. We were able to demonstrate that self-setting occurs in core-shell printed CPC/alginate scaffolds after only 1 day, and that mass production is possible. By coating with alginate, the compressive strength could be increased without the need for additional post-treatment. The mechanical strength was sufficient to be available as a scaffold for bone regeneration and additionally as a drug delivery device for future applications and experiments.

Mechanical shear flow regulates the malignancy of colorectal cancer cells.

Colorectal cancer (CRC) is notable for its high mortality and high metastatic characteristics. The shear force generated by bloodstream provides mechanical signals regulating multiple responses of cells, including metastatic cancer cells, dispersing in blood vessels. We, therefore, studied the effect of shear flow on circulating CRC cells in the present study. The CRC cell line SW620 was subjected to shear flow of 12.5 dynes/cm2 for 1 and 2 h separately. Resulting elevated caspase-9 and -3 indicated that shear flow initiated the apoptosis of SW620. Enlarged cell size associated with a higher level of cyclin D1 was coincident with the flow cytometric results indicating that the cell cycle was arrested at the G1 phase. An elevated phosphor-eNOSS1177 increased the production of nitric oxide and led to reactive oxygen species-mediated oxidative stress. Shear flow also regulated epithelial-mesenchymal transition (EMT) by increasing E-cadherin and ZO-1 while decreasing Snail and Twist1. The migration and invasion of sheared SW620 were also substantially decreased. Further investigations showed that mitochondrial membrane potential was significantly decreased, whereas mitochondrial mass and ATP production were not changed. In addition to the shear flow of 12.5 dynes/cm2, the expressions of EMT were compared at lower (6.25 dynes/cm2) and at higher (25 dynes/cm2) shear flow. The results showed that lower shear flow increased mesenchymal characteristics and higher shear flow increased epithelial characteristics. Shear flow reduces the malignancy of CRC in their metastatic dispersal that opens up new ways to improve cancer therapies by applying a mechanical shear flow device.

Optical lateral flow assays in early diagnosis of SARS-CoV-2 infection.

So far, the 2019 novel coronavirus (COVID-19) is spreading widely worldwide. The early diagnosis of infection by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is essential to provide timely treatment and prevent its further spread. Lateral flow assays (LFAs) have the advantages of rapid detection, simple operation, low cost, ease of mass production, and no need for special devices and professional operators, which make them suitable for self-testing at home. This review focuses on the early diagnosis of SARS-CoV-2 infection based on optical LFAs including colorimetric, fluorescent (FL), chemiluminescent (CL), and surface-enhanced Raman scattering (SERS) LFAs for the detection of SARS-CoV-2 antigens and nucleic acids. The types of recognition components, detection modes used for antigen detection, labels employed in different optical LFAs, and strategies to improve the detection sensitivity of LFAs were reviewed. Meanwhile, LFAs coupled with different nucleic acid amplification techniques and CRISPR-Cas systems for the detection of SARS-CoV-2 nucleic acids were summarized. We hope this review provides research mentalities for developing highly sensitive LFAs that can be used in home self-testing for the early diagnosis of SARS-CoV-2 infection.

A New Integration Scheme to Prevent Chemical Attack on Floating Polysilicon Gate of Non-Volatile Memory

—Silicon pitting has been observed on floating gate polysilicon layer of embedded non-volatile memory(e-NVM) process due to chemical attack caused by HBr residual interacting with moisture. This paper successfully demonstrates a new integration scheme for a robust floating gate process against silicon attack for embedded stacked/split gate non-volatile memory process. Firstly, CF4 was introduced into floating gate polysilicon etch recipe to replace HBr, which has been CMOS gate polysilicon etch gas in traditional logic process due to the advantage of higher selectivity despite the disadvantage of low vaporability, for better or cleaner process control. Secondly, an additional plasma removal stripping (PRS) clean step was added before chemical removal stripping (CRS) to give better etch by-product cleaning, even though there is no photoresist and lithography involved on the poly blanket etch for the better etch by-product cleaning. This new scheme has been verified using inline optical inspection defect-scan to prove the sufficient process margin for better mass production control that came from improved manufacturing Queue-time margin (longer waiting time) between dry-etch step, CRS step, and subsequent downstream process steps.

Analytical and Experimental Research for Development of the Airless Tires for Urban Micromobility Means

It is currently recognized that electric vehicles are the optimal type of passenger transport for urban usage. However, there are very few people willing to buy them, since today electric cars are very expensive. So the development of the personal light electric transport segment (electric bicycles, scooters, motorcycles, etc.) becomes very relevant. At the same time, the introduction of new technologies (in particular, 3D printing) and constructions (airless wheels) for their mass production is of particular importance. The range of problems that can be solved by modern additive technologies is expanding every day. FDM technology is one of the most commonly used additive methods. It is not only widely available, but it also provides significant possibilities for decision-making. However, most developments in this area are focused on obtaining the geometric accuracy of shapes without taking into account the mechanical properties of materials used. Therefore, the purpose of this study is to investigate experimentally the influence of filling density of parts manufactured by 3D printing on their mechanical properties and application of obtained results for the production of airless tires by using FDM technology.

Coprecipitation Strategy for Halide-Based Solid-State Electrolytes and Atmospheric-Dependent In Situ Analysis.

In the continuous pursuit of an energy-efficient alternative to the energy-intensive mechanochemical process, we developed a coprecipitation strategy for synthesizing halide-based solid-state electrolytes that warrant both structural control and commercial scalability. In this study, we propose a new coprecipitation approach to synthesized Li3InCl6, exhibiting both structural and electrochemical performance stability, with a high ionic conductivity of 1.42 × 10-3 S cm-1, comparable to that of traditionally prepared counterparts. Through the in situ synchrotron X-ray diffraction technique, we unveil the stability mechanisms and rapid chemical reactions of Li3InCl6 under dry Ar, dry O2, and high-humidity atmosphere, which were not previously reported. Furthermore, the fast reversibility capability of moisture-exposed Li3InCl6 was tracked under vacuum, revealing the optimal recovery conditions at low temperatures (150-200 °C). This work addresses the critical challenges in structural engineering and sustainable mass production and provides insights into chemical reactions under real-world conditions.

Basic and acidic electrolyte mediums impact on MnO2-Mn2O3/Poly-2-methylaniline hexagonal nanocomposite pseudo-supercapacitor

A highly efficient MnO2-Mn2O3/Poly-2-methylaniline (MnO2-Mn2O3/P2MA) hexagonal nanocomposite is synthesized using a one-pot technique involving oxidation polymerization. The hexagonal morphology and crystalline nature of this nanocomposite, as evidenced by the XRD pattern, affirm its exceptional characteristics. The electrical properties are assessed through charge/discharge behavior and cyclic voltammetry curves, elucidating the storage capabilities of this pseudo supercapacitor using different electrolytes NaOH and HCl. The fabricated supercapacitor exhibits impressive efficiency values of 22 F g−1 in a basic medium and a notably higher 72 F g−1 in an acidic medium at a current density of 0.2 A/g. Similarly, the power density values are calculated at 480 and 478 W.kg−1 for the basic and acidic electrolyte, correspondingly. In the basic medium, the series resistance (RS) and charge transfer resistance (RCT) are 5.2 and 0.7 Ω, respectively. In the acidic medium, these values are notably lower, with RS at 2.82 Ω and RCT at 0.2 Ω. Remarkably, even after 500 cycles, the supercapacitor stability remains high at 95% in both media, underscoring the enduring stability attributed to the oxides and polymer materials within the supercapacitor. The combination of cost-effectiveness, ease of fabrication, and potential for mass production positions this supercapacitor as a promising candidate for industrial applications of polymer-based supercapacitors.

Mechanical Integrity and Reinforcement Efficiency of Graphene Grown on Liquid Copper by Chemical Vapor Deposition

AbstractGraphene is a perfect 2D crystal of covalently bonded carbon atoms and constitutes the building block for all graphitic structures. Its superior properties make it an attractive material for a variety of technological applications. However, mass production does not meet the initial expectations. Chemical Vapor Deposition (CVD) is currently the only available method for large‐scale automated production, but the produced graphene sheets suffer from structural and morphological defects that degrade considerably the mechanical and other physical properties of synthesized graphene. Recently, the use of liquid metal catalysts (LMCat) has been proposed as an alternative platform for facile and high‐quality synthesis of single‐crystal graphene. Herein, simultaneous Raman spectroscopy combined with mechanical testing is adopted confirming that the reinforcing efficiency of the LMCat graphene is greatly improved. In fact, the effective Young's modulus of LMCat graphene has been found ≈630 GPa, which is significantly higher than the graphene grown on solid Cu substrate due to differences in the morphology of Cu substrate. Overall, this work paves the way for the development of defect‐free graphene of quality comparable to exfoliated flakes, and this will have a major technological impact for many applications.

What is beyond 50G: future standards of optical access networks [Invited

In the past two decades, optical access networks have been widely deployed by operators around the world. The global optical access network market reaches about 1 billion users with a revenue of over 10 billion US dollars. As strategic tools to facilitate mass production, the optical access network standards play a crucial role in driving the product deployment and market growth. This paper overviews the latest effort in international standards bodies on the next generation optical access networks. It discusses projects in this area within the International Telecommunication Union’s Telecommunication Standardization Section (ITU-T), the IEEE, and the European Telecommunications Standards Institute (ETSI). Promising technologies are investigated with the goal of providing rates beyond 50 Gbps. Challenges are highlighted to satisfy the requirements on balancing access rates, loss budgets, and cost. Candidate systems are analyzed in three categories: point-to-multipoint (PtMP), point-to-point (PtP), and new applications. These standardization endeavors will jointly guarantee optical access networks as the premiere solution of wireline broadband access.

Big data analytics for quality variation over work shifts in manufacturing systems

ABSTRACT In the manufacturing industry, mass production enables manufacturers to produce parts with high precision and lower costs. Multiple shifts operate production processes to maximize efficiency. Several researches have been conducted on the impact of shift work on labor’s health and habits. However, there have been few studies on the influence of shift work on the consistency of product quality. This paper provides a methodology to analyze the impact of different work shifts in a real electronic board manufacturing industry. The study uses big data and analytics to assess product quality from data. Non-parametric kernel density estimation is used to approximate the distribution of good products in each work slot. Then several metrics are used to measure the dissimilarity between the estimated densities. The approach can be leveraged in various problems related to process performance and quality. The obtained results show that there is no significant difference in terms of product quality between work shifts. These prove the consistency of the manufacturing processes and the homogeneity of performance across work shifts in the studied factory. Compared to the literature, the paper presents the first quantitative analysis to compare production process performance and product quality over shift works.

Vignetting Compensation Method for CMOS Camera Based on LED Spatial Array

To solve the problem of pixel light intensity information distortion caused by camera vignetting in optical devices such as CMOS or CCD cameras, existing studies mainly focus on small spatial light fields and point light sources and adopt an integrating sphere and function model for vignetting correction, but it is not suitable for large LED optical composite display devices. Under this background, this paper innovatively proposes a camera vigneting compensation method based on an LED spatial array, independently develops a two-dimensional translation device driven by a high-precision guide rail, uses spatial array technology to obtain the brightness distribution of the corrected display screen to quantify its camera vigneting distortion characteristics, and adopts systematic mathematical operations and iterative compensation strategies. Industry standard tests show that the brightness uniformity of the display has been improved by 5.06%. The above research results have been applied to mass production and industrialization.

Fabrication of FeP2/C/CNTs@3D interconnected graphene aerogel composite for lithium-ion battery anodes and the electrochemical performance evaluation using machine learning

Featuring low cost and high theoretical capacity, phosphorus-rich iron diphosphides (FeP2) have emerged as excellent anode candidates for lithium-ion batteries. However, the typical chemical synthses involving high temperatures and toxic gases have restricted the mass production of FeP2. We now report a FeP2/C/CNTs@3D interconnected graphene aerogel composite synthesized by ball milling and low temperature heat treatment. Because of the unique microstructure and synergistic effect between well-dispersed FeP2 particles and graphene aerogel, the as-prepared FeP2/C/CNTs@GA-2.5% displays excellent lithium storage performance in terms of reversible capacity (886 mA h g−1 at 0.1 A g−1), cycling stability (476 mA h g−1 at 2 A g−1 even after 1000 cycles), and rate capability (685 mA h g−1 at 5 A g−1). Machine learning methods (decision tree and random forest algorithms) prove effective in evaluating and predicting electrochemical performance of the electrode materials.

Crowdsourcing RTK: a new GNSS positioning framework for building spatial high-resolution atmospheric maps based on massive vehicle GNSS data

High-quality spatial atmospheric delay correction information is essential for achieving fast integer ambiguity resolution (AR) in precise positioning. However, traditional real-time precise positioning frameworks (i.e., NRTK and PPP-RTK) depend on spatial low-resolution atmospheric delay correction through the expensive and sparsely distributed CORS network. This results in limited public appeal. With the mass production of autonomous driving vehicles, more cost-effective and widespread data sources can be explored to create spatial high-resolution atmospheric maps. In this study, we propose a new GNSS positioning framework that relies on dual base stations, massive vehicle GNSS data, and crowdsourced atmospheric delay correction maps (CAM). The map is easily produced and updated by vehicles equipped with GNSS receivers in a crowd-sourced way. Specifically, the map consists of between-station single-differenced ionospheric and tropospheric delays. We introduce the whole framework of CAM initialization for individual vehicles, on-cloud CAM maintenance, and CAM-augmented user-end positioning. The map data are collected and preprocessed in vehicles. Then, the crowdsourced data are uploaded to a cloud server. The massive data from multiple vehicles are merged in the cloud to update the CAM in time. Finally, the CAM will augment the user positioning performance. This framework forms a beneficial cycle where the CAM’s spatial resolution and the user positioning performance mutually improve each other. We validate the performance of the proposed framework in real-world experiments and the applied potency at different spatial scales. We highlight that this framework is a reliable and practical positioning solution that meets the requirements of ubiquitous high-precision positioning.

Prefrontal Correlates of Passengers’ Mental Activity Based on fNIRS for High-Level Automated Vehicles

AbstractWith the spread adoption of artificial intelligence, the great challenges confronted by the intelligent safety concern-safety of the intended functionality has become the biggest roadblock to the mass production of high-level automated vehicles, notably arising from perception algorithm deficiencies. This paper focuses a cut-in scenario, dividing this scenario into low-risk and high-risk segments predicated on the kinetic energy field, and the mental activities of passengers on prefrontal cortex, are analyzed within these delineated segments. Two experiments are then conducted, leveraging driving simulators and real-world vehicles, respectively. Experiment results indicate that high risk may result in the passengers’ mental activity on prefrontal cortex change. This revelation posits a potential avenue for augmenting the intended functionality of automated vehicle by using passengers’ physiological state.