Mass Production Efficiency Research Articles

Facile access to spirobifluorene-fused chiral multi-resonance materials with ultra-narrowband blue emission

Narrowband multiple resonance (MR) emitters with circularly polarized luminescence (CPL) hold significant promise for three dimension organic light-emitting diode (3D-OLED) displays. In this work, we present a simple method for developing a new type of 9,9’-spirobifluorene-based CP-MR emitters by a recrystallization resolution technology and chlorine (Cl)-directed electrophilic borylation reaction, both of which significantly enhances the efficiency and scalability for mass production. This approach allows for integrating an asymmetric 9,9’-spirobifluorene core between two MR frameworks to achieve optically active CP-MR emitters. The highly rigid spirobifluorene framework minimizes structural relaxation, and meanwhile, the introduction of a cyano (CN) group enhances the MR emission characteristics, leading to an ultra-narrowband blue emission with full width at half maximum (FWHM) of 14 nm. As a result, these molecules facilitate the assembly of narrowband blue CPL-OLEDs with a maximum external quantum efficiency (EQEmax) of 30.7% and an impressive narrow FWHM of 16 nm, representing the first instance of an FWHM below 20 nm in CPL-OLEDs.

Reviews on Flexible Force Sensors Based on Fiber Assemblies with Mass Production Efficiency

AbstractFlexible force sensors show great potential applications in smart wearable devices based on their softness and ease of deformation. Textiles are extremely compatible with the human body, where mechanical forces generated by human movements and physiological activities create rich application scenarios for flexible force sensors. Currently, the bottleneck in the development of flexible sensors depends on the breakthrough of mass production efficiency, which has been a research focus in recent years to accelerate the application of smart textiles in various fields. This work reviews the research progress of flexible force sensors based on fiber assemblies with mass production efficiency, which is discussed in four aspects: sensing mechanisms, structure design, preparation methods, and application. Finally, the challenges faced by mass production of flexible force sensors are analyzed and summarized, and a few inspirations for their future development direction are provided.

Unveiling the powerhouses of AI: A comprehensive study of GPU, FPGA, and ASIC accelerators

In the ever-evolving realm of technology, Artificial Intelligence (AI) has ushered in a transformative era, reshaping our interactions with digital systems, and expanding the horizons of machine capabilities. At the core of this AI revolution are specialized hardware entities known as AI accelerators. These accelerators, including Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs), and Application-Specific Integrated Circuits (ASICs), play a pivotal role in advancing AI applications across diverse domains. This paper delves into these accelerators, offering an in-depth exploration of their unique attributes and application domains. GPUs, initially designed for graphics, have evolved into versatile tools, thanks to their parallel computing prowess and efficient memory utilization. FPGAs, with reconfigurability and low latency, prove valuable in aerospace and neural network implementations, though they come with cost and expertise challenges. ASICs, engineered for specific functions, excel in performance and power efficiency for mass production but require significant time and resources for development. Furthermore, this paper presents practical application analyses, showcasing how these accelerators are effectively deployed in real-world scenarios. With this comprehensive exploration, readers gain a deeper understanding of AI accelerators and their transformative impact on the AI landscape.

Study on P-a-Si:H properties of N-type heterogeneous junction solar cells manufactured by large-area parallel plate PECVD machine

P-type hydrogenated amorphous silicon (P-a-Si:H) plays an important role in heterojunction solar cells. On the one hand, P-a-Si:H processed by plasma enhanced vapor deposition (PECVD) can selectively collect carrier holes on the rear of N-type silicon based heterojunctions with intrinsic thin layer (HJT) solar cells (in this article, the back ride of the cell is P-a-Si:H); On the other hand, the ohmic contact between P-a-Si:H and conductive ITO film is beneficial for hole transport. Therefore, the performance of P-a-Si:H has very significant impact on the property of HJT solar cells. The electrical conductivity, impurity activation energy, and passivation performance of silicon wafer surface are the core performance indicators of P-a-Si:H materials themselves. In this paper, we systematically research the optimal RF power density, doping concentration (diborane doped), hydrogen dilution ratio and plate spacing for the growth process of P-a-Si:H using a self-developed large-area parallel plate PECVD equipment (Jincheng Machine). The results show that the P-a-Si:H has an electrical conductivity of 1.27 × 10−3 S/cm and an activation energy of 251 meV, and the maximum mass production efficiency of the HJT solar cell is 25.21%, Voc is 741 mV and Jsc is 41.57 mA/cm2.

Adaptive structured illumination optical-sectioning microscopy based on the prior knowledge of sample structure

Fast and accurate online detection is of great significance to improve mass production efficiency and reduce the costs of semiconductor chips and other micro-nano devices. Compared with other 3D imaging detection techniques, structured illumination optical-sectioning microscopy has faster 3D imaging because it uses wide-field sinusoidal fringe structured illumination. However, commercial structured illumination optical-sectioning microscopes are designed for general needs, and the orientations of the fringe patterns they project are not optimized for the structures of the sample. To obtain an isotropic result, they need to project multiple sinusoidal fringe patterns with different orientations and perform multiple optical-sectioning imaging, and then average the optical-sectioning results, resulting in low imaging efficiency. This paper proposes an adaptive structured illumination optical-sectioning microscopy. It exploits prior knowledge of the sample structure to design the sinusoidal fringe orientation for each local structure and generates an adaptive structured illumination. In this way, we can achieve the best imaging effect with only one optical-sectioning imaging, thereby improving the imaging efficiency, which is beneficial to the improvement of the mass production efficiency of products. The method proposed in this paper will provide useful guidance on how to correctly and efficiently use structured illumination optical-sectioning microscopy to detect defects of micro-nano devices such as semiconductor chips with known designed structures.

One-pot and one-step preparation of “living” cellulose nanofiber hydrogel with active double-bond via chemical vapor deposition

Due to the existence of water, it is still a challenge to conduct chemical modification on cellulose nanofiber (CNF) hydrogels with active double bonds. A simple one-pot and one-step method for constructing “living” CNF hydrogel with double bond was created at room temperature. The chemical vapor deposition (CVD) of methacryloyl chloride (MACl) was used to introduce physical-trapped, chemical-anchored and functional double bonds into TEMPO-oxidized cellulose nanofiber (TOCN) hydrogels. TOCN hydrogel could be fabricated within just 0.5 h, the minimum dosage of MACl could be reduced to 3.22 mg/g (MACl/TOCN hydrogel). Furthermore, the CVD methods showed high efficiency for mass production and recyclability. Moreover, the chemical “living” reactivity of the introduced double bonds were verified by the freezing and UV crosslinking, radical polymerization and thiol-ene click reaction. Compared with pure TOCN hydrogel, the obtained functionalized TOCN hydrogel exhibited remarkable improvements in mechanical properties, with enhancements of 12.34 times and 2.04 times, as well as an increase in hydrophobicity by 2.14 times and a fluorescence performance improvement of 2.93 times.

Statistical and Artificial Intelligence Analyses of Blast Treatment Condition Effects on Blast-Assisted Injection Molded Direct Joining

Efficient hybrid joining methods are required for joining metals and plastics in the automobile and airplane industries. Injection molded direct joining (IMDJ) is a direct joining technique that uses metal pretreatment and injection molding of plastic to form joints without using any additional parts. This joining technique has attracted attention from industries for its advantages of high efficiency and low cost in mass production. Blast-assisted IMDJ, an IMDJ technique that employs blasting as the metal pretreatment, has become suitable for the industry because metal pretreatment can be performed during the formation of the metal surface structure without chemicals. To satisfy industry standards, the blast-assisted IMDJ technique needs to be optimized under blasting conditions to improve joining performance. The number of parameters and their interactions make this problem difficult to solve using conventional control variable methods. We propose applying statistical and artificial intelligence analyses to address this problem. We used multiple linear regression and back propagation neural networks to analyze the experimental data. The results elucidated the relationship between the blasting conditions and joining strength. According to the machine learning predicted results, the best joining strength in blast-assisted IMDJ reached 22.3 MPa under optimized blasting conditions. This study provides new insights into similar engineering problems.

Development of an automated system for the soldering of USB cables

Large demand for soldering multi-wire cables (e.g., USB cables, earphone cables, etc.) is reflected in the rapidly expanding 3C industry (i.e., Computer, Communication and Consumer electronics). Currently, several pre-processing steps need to be first carried out: separating → sorting → pressing . These steps are challenging for the robot, mainly because of the deformable nature, small size, and couplings between multiple wires. As such, existing solutions are entirely manual. In this paper, a new automated system for the soldering of multi-wire cable is proposed, in which the whole procedure, including all the pre-processing steps, is fully automated. The key novelty is the development of a series of new mechanical modules that are able to disentangle multiple wires then manipulate them into the structured configuration, laying the foundation for the subsequent soldering operation. The transition between multiple modules is automatically achieved using a deep vision network to guarantee high accuracy (i.e., < 1 mm ) under different levels of illumination and/or cluttered backgrounds. Moreover, an optimization scheme has been proposed for wire sorting to shorten the operation time and improve mass production efficiency. Experimental results show that the speed of manufacturing is around 112 pics/hr and the success rate for each module is above 93%, thereby proving the feasibility of the developed robot. • The development of a fully-automatic system for the soldering of multi-wire cable. • The construction of a deep vision network for accurate detection of wires in the presence of changes in illumination and cluttered background. • The design of an optimization scheme capable of shortening the time of wire sorting and improving mass production efficiency.

Enhancing the Performance of the Photonic Integrated Sensing System by Applying Frequency Interrogation.

Lab-on-a-chip systems are currently one of the most promising areas in the development of ultra-compact sensor systems, used primarily for gas and liquid analysis to determine the concentration of impurities. Integrated photonics is an ideal basis for designing "lab-on-a-chip" systems, advantageous for its compactness, energy efficiency, and low cost in mass production. This paper presents a solution for "lab-on-a-chip" device realization, consisting of a sensor and an interrogator based on a silicon-on-insulator (SOI) integrated photonics platform. The sensor function is performed by an all-pass microring resonator (MRR), installed as a notch filter in the feedback circuit of an optoelectronic oscillator based on an electro-optic phase modulator. This structure realizes the frequency interrogation of the sensor with high accuracy and speed using a conventional single-mode laser source. The system sensitivity for the considered gases is 13,000 GHz/RIU. The results show that the use of frequency interrogation makes it possible to increase the intrinsic LoD by five orders. The proposed solution opens an opportunity for fully integrated implementation of a photonic "laboratory-on-a-chip" unit.

Research progress of perovskite/crystalline silicon tandem solar cells with efficiency of over 30%

Double junction tandem solar cells consisting of two absorbers with designed different band gaps show great advantage in breaking the Shockley-Queisser limit efficiency of single junction solar cell by differential absorption of sunlight in a wider range of wavelengths and reducing the thermal loss of photons. Owing to the advantages of adjustable band gap and low cost of perovskite cells, perovskite/crystalline silicon tandem solar cells have become a research hotspot in photovoltaics. We systematically review the latest research progress of perovskite/crystalline silicon tandem solar cells. Focusing on the structure of perovskite top cells, intermediate interconnection layers and crystalline silicon bottom cells, we summarize the design principles of high-efficiency tandem devices in optical and electrical aspects. We find that the optical and electrical engineering of each layer structure in perovskite/crystalline silicon tandem solar cells goes through the whole process of device preparation. We also summarize the challenges of limiting the further improvement of the efficiency of the perovskite/crystalline silicon tandem solar cells and the corresponding improvement measures, which covers the following respects: 1) Improving the balance between &lt;i&gt;V&lt;/i&gt;&lt;sub&gt;oc&lt;/sub&gt; and &lt;i&gt;J&lt;/i&gt;&lt;sub&gt;sc&lt;/sub&gt; of the broadband perovskite cell through additive engineering and interface engineering; 2) improving the bandgap matching between the electrical layers and reducing the carrier transport barrier through adjusting the work function or conductivity of layers; 3) improving the photocurrent coupling between sub-cells and the photocurrent of tandem solar cells by using light engineering and conformal deposition technology of perovskite cells. At present, there have been many technologies to improve the stability of perovskite solar cells, such as additive engineering and interface engineering, but the problem has hardly been solved. Therefore, improving the stability of broadband gap perovskite solar cells to the level of crystalline silicon solar cells will become an important challenge to limit its large-scale application. In terms of efficiency, the mass production efficiency of perovskite/crystalline silicon tandem solar cells is far lower than that of the laboratory level. One of the reasons is that it is difficult to achieve low-cost and deposition of uniform large area perovskite solar cells. Therefore improving the stability of broadband gap perovskite solar cells and developing low-cost large-area perovskite deposition technology will become extremely critical. Finally we look forward to the next generation of higher efficient low-cost tandem solar cells. We believe that with the increasing demand for higher efficiency photovoltaic devices, the triple junction solar cells based on the perovskite/crystalline silicon stack structure will become the future photovoltaics.

Modified Freeze-granulation method for fabricating Li2TiO3 ceramic tritium breeding pebbles

Lithium metatitanate (Li2TiO3) ceramic is an important candidate for tritium breeding material in fusion reactor blanket. Nevertheless, mass production has become an important factor restricting the application of Li2TiO3 pebbles. In this paper, freeze-granulation method is innovatively modified by drying frozen pebbles in acetone. The principle of modified freeze-granulation method is explained in detail. Influence of PVA content, sintering temperature and sintering time on mechanical performance of frozen pebbles dried in acetone are carefully discussed. The modified process could shorten the drying time in 30 min under the premise of good crushing load and thus conducive to improve the efficiency of mass production of tritium breeding ceramic pebbles potentially in the future. Finally, the Li2TiO3 pebbles present good sphericity, high average crushing load (38 N), abundant and uniform pores which are beneficial to tritium release.

Chemical Composition, in vitro Gas Production and Ruminal Fermentation of Cottonseed Meal and Certain Conventional Protein Sources in Buffalo Inoculum

Background: The price of conventional protein sources like soybean and peanut has increased markedly in recent years resulting in urgent need for exploring alternate protein sources. Due to increase in availability of cottonseed meal (CSM) in cotton-growing areas of India as compared to other oil seed meals, CSM is becoming one of the major components of concentrate mixture (CM) fed to animals. Methods: A study was undertaken to assess the chemical composition and in vitro nutritional worth of CSM in comparison to conventional oilseed cakes used in livestock feeding. Result: The CP content of protein sources varied from 47.85% in CSM to 47.76% in soybean meal (SBM). The net gas production (NGP, ml/g DM/24h) in CSM (160.48) was lower (P less than 0.05) than SBM (198.04) and MC (199.55). The metabolizable energy (ME, MJ/kg DM) was higher (P less than 0.05) in MC and lowest (P less than 0.05) in DMC. The partitioning factor (PF, mg/ml), OM digestibility (%), DM digestibility (%), NDF digestibility (%), efficiency of microbial mass production (EMMP, %), fermented CO2 was reported to be higher (P less than 0.05) in CSM compared to conventional oilseed cakes. The TVFA (mM/dl) production in CSM (6.63) was higher (P less than 0.05) than GNC (6.45) but lower (P less than 0.05) than SBM (6.97), MC (7.11) and DMC (7.25). The fermentation efficiency (FE, %) in CSM (74.70) and GNC (74.97) was higher (P less than 0.05) than conventional oilseed cakes. The VFA utilization index (VFA UI) was highest (P less than 0.05) in SBM (3.81) and lowest (P less than 0.05) in GNC (3.39). The results revealed that CSM has the potential to be used as a protein source for livestock feeding.

Digital Twin of a Flexible Manufacturing System for Solutions Preparation

In the last few decades, there has been a growing necessity for systems that handle market changes and personalized customer needs with near mass production efficiency, defined as the new mass customization paradigm. The Industry 5.0 vision further enhances the human-centricity aspect, in the necessity for manufacturing systems to cooperate with workers, taking advantage of their problem-solving capabilities, creativity, and expertise of the manufacturing process. A solution is to develop a flexible manufacturing system capable of handling different customer requests and real-time decisions from operators. This paper tackles these aspects by proposing a digital twin of a robotic system for solution preparation capable of making real-time scheduling decisions and forecasts using a simulation model while allowing human interventions. A discrete event simulation model was used to forecast possible system improvements. The simulation handles real-time scheduling considering the possibility of adding identical parallel machines. Results show that processing multiple jobs simultaneously with more than one machine on critical processes, increasing the robot speed, and using heuristics that emphasize the shortest transportation time can reduce the overall completion time by 82%. The simulation model has an animated visualization window for a deeper understanding of the system.

DECISION SUPPORT METHOD FOR THE APPLICABILITY OF HARD TURNING

In this study the applicability of hard turning is analyzed in the case of disc-shaped parts (gear wheels). The relevance of such parts has been increasing in the automotive industry; therefore, the efficiency of large series or mass production has high priority. The novelty of this paper is the collection of factors that has to be considered in preparation for applicability decisions of hard turning in order to ensure efficient machining. This can be the basis of the IT support, i.e. an automation solution for technologists. The introduced process is elaborated on the basis of theoretical considerations and production shop-floor experience.

Open-Digital-Industrial and Networking pilot lines using modular components for scalable production – ODIN project approach

While robots have very well proven their flexibility and efficiency in mass production and are recognized as the production resource of the future, their adoption in lower volume, diverse environment is heavily constrained. The main reason for this is the high integration and deployment complexity that overshadows the performance benefits of this technology. This paper presents the vision of ODIN European funded project which is to strengthen the EU production companies’ trust in utilizing advanced robotics, by demonstrating that novel robot-based production systems are not only technically feasible, but also efficient and sustainable for immediate introduction at the shopfloor. To achieve that, ODIN brings together, by means of hardware and software, the latest technological advancements in the fields of a) collaborating robots and human robot collaborative workplaces, b) autonomous robotics and AI based task planning, c) mobile robots and reconfigurable tooling, d) Digital Twins and Virtual Commissioning and e) Service Oriented Robotics Integration and Communication Architectures. ODIN will provide a systematic approach for integrating these technologies under modular and reconfigurable large-scale robotic pilots. The performance of these robotic pilots will be tested and validated in three case studies, from the automotive, the white goods and the aeronautics industry.

Research on the Industrial Mass Production Route of N-Type Passivated Contact Silicon Solar Cells With Over 23% Efficiency

Due to the high efficiency, low light-induced degradation and high bifaciality, n-type tunnel oxide passivated contact (TOPCon) solar cell is widely researched and currently being implemented in mass production. In this article, three different TOPCon cell production routes are tested and compared, two routes with phosphorus (P) diffusion first, followed by boron (B) diffusion (Routes 1 and 2) and one route with B diffusion first, followed by P diffusion (Route 3). The differences in process control, manufacturing difficulty, front and rear side passivation, shunting, mass production efficiency, and yield are analyzed. In this article, the results demonstrate that Route 3, with 23.37% efficiency, has the highest cell efficiency and potential to further improve the yield, likely the most suitable TOPCon manufacturing route for industrialization. However, Route 2 also has the opportunity to obtain high efficiency and yield after further optimization.

Mass personalization-oriented integrated optimization of production task splitting and scheduling in a multi-stage flexible assembly shop

Aiming to produce personalized products at mass production efficiency, mass personalization has attained considerable interests in recent years. This paper considers an integrated task splitting and scheduling problem in the context of mass personalization, which converts customer requirements into a few production tasks at different levels and simultaneously optimizes the sizes as well as the scheduling sequence of the tasks. An integrated optimization model for this problem is formulated to minimize makespan and two transfer strategies for the model are investigated. To solve the model, an improved whale optimization algorithm (IWOA) is proposed, where a first-whale search is designed to guide the search direction. Besides, an ocean current impact factor and differential evolution operators are combined in IWOA to enhance the search ability. Extensive computational experiments are performed to validate the proposed algorithm. Results show that compared with the comparison algorithms, IWOA can find the best solution and take relatively less time. Furthermore, statistical analysis proves that the results of multiple runs of IWOA are more concentrated, indicative of better stability of IWOA. Finally, a case study is presented in the paper to demonstrate the application of the proposed model and algorithm.

Applying Precision Agriculture to Artificial Waterfowl Hatching, Using the Black Muscovy Duck as an Example

(1) Background: agriculture practices adopt homogenization-farming processes to enhance product characteristics, with lower costs, standardization, mass production, and production efficiency. (2) Problem: conventional agriculture practices eliminate products when these products are slightly different from the expected status in each phase of the lifecycle due to the changing natural environment and climate. However, this elimination of products can be avoided when they receive customized care to the expected developing path via a universal prediction model, for the quantitative description of biomass changing with time and the environment, and the corresponding automatic environmental controls. (3) Methods: in this study, we built a prediction model to quantitatively predict the hatching rate of each egg by observing the biomass development path along the waterfowl-like production lifecycle and the corresponding environment settings. (4) Results: two experiments using black Muscovy duck hatching as a case study were executed. The first experiment involved finding out the key characteristics, out of 25 characteristics, and building a prediction model to quantitatively predict the survivability of the black Muscovy duck egg. The second experiment was adopted to validate the effectiveness of our prediction mode; the hatching rate rose from 47% in the first experiment to 62% in the second experiment without any human interference from experienced farmers. (5) Contributions: this research builds on an AI-based precision agriculture system prototype as the reference for waterfowl research. The results show that our proposed model is capable of decreasing the training costs and enhancing the product qualification rate for individual agricultural products.

Effect of Camellia sinensis, Punica granatum Peel, and Quercus persica Extracts on in vitro Fermentation Parameters

This experiment was conducted to study the effects of aqueous and alcoholic extracts of Camellia sinensis leaves (green tea), Punica granatum peel (pomegranate-peel), and Quercus persica (oak) at different concentrations on ruminal fermentation, dry matter and organic matter digestibility, methane production and protozoa population using gas production method. Experimental treatments were: control, 50, 100, and 200 μg/ ml aqueous and methanolic extract of Camellia sinensis, Punica granatum peel, and Quercus persica (19 treatments in total). Cumulative gas production was recorded at 2, 4, 6, 8, 12, 24, 36, 48, 72, and 96 h after incubation. Dry matter digestibility (DMD), organic matter digestibility (OMD), metabolizable energy (ME), pH, and short-chain fatty acids (SCFA) were calculated after 24 h incubation. Gas production at different times, methane production, and protozoa population were also measured. DMD, OMD, and pH were decreased by adding extracts. Microbial mass production (MCP) and microbial mass production efficiency (EMCP) significantly increased at a low level (50 μg/ ml) and significantly decreased at high levels of extracts containing tannins (100 and 200 μg/ ml) (p < 0.01). The treatments also increased short-chain fatty acids (SCFA), reduced methane concentration, and reduced PF and protozoa populations only at the highest levels of extracts (p <0.05).

A Three-Dimensional Micromixer Using Oblique Embedded Ridges.

A micromixer is one of the most significant components in a microfluidic system. A three-dimensional micromixer was developed with advantages of high efficiency, simple fabrication, easy integration, and ease of mass production. The designed principle is based on the concepts of splitting–recombination and chaotic advection. A numerical model of this micromixer was established to characterize the mixing performance for different parameters. A critical Reynolds number (Re) was obtained from the simulation results. When the Re number is smaller than the critical value, the fluid mixing is mainly dependent on the mechanism of splitting–recombination, therefore, the length of the channel capable of complete mixing (complete mixing length) increases as the Re number increases. When the Re number is larger than the critical value, the fluid mixing is dominated by chaotic advection, and the complete mixing length decreases as the Re number increases. For normal fluids, a complete mixing length of 500 µm can be achieved at a very small Re number of 0.007 and increases to 2400 µm as the Re number increases to the critical value of 4.7. As the Re number keep increasing and passes the critical Re number, the complete mixing length continues to descend to 650 µm at the Re number of 66.7. For hard-to-mix fluids (generally referring to fluids with high viscosity and low diffusion coefficient, which are difficult to mix), even though no evidence of strong chaotic advection is presented in the simulation, the micromixer can still achieve a complete mixing length of 2550 µm. The mixing performance of the micromixer was also verified by experiments. The experimental results showed a consistent trend with the numerical simulation results, which both climb upward when the Re number is around 0.007 (flow rate of 0.03 μm/min) to around 10 (flow rate of 50 μm/min), then descend when the Re number is around 13.3 (flow rate of 60 µm/min).