Advanced Process Technology Research Articles

Latest advances: Improving the anti-inflammatory and immunomodulatory properties of PEEK materials.

Excellent biocompatibility, mechanical properties, chemical stability, and elastic modulus close to bone tissue make polyetheretherketone (PEEK) a promising orthopedic implant material. However, biological inertness has hindered the clinical applications of PEEK. The immune responses and inflammatory reactions after implantation would interfere with the osteogenic process. Eventually, the proliferation of fibrous tissue and the formation of fibrous capsules would result in a loose connection between PEEK and bone, leading to implantation failure. Previous studies focused on improving the osteogenic properties and antibacterial ability of PEEK with various modification techniques. However, few studies have been conducted on the immunomodulatory capacity of PEEK. New clinical applications and advances in processing technology, research, and reports on the immunomodulatory capacity of PEEK have received increasing attention in recent years. Researchers have designed numerous modification techniques, including drug delivery systems, surface chemical modifications, and surface porous treatments, to modulate the post-implantation immune response to address the regulatory factors of the mechanism. These studies provide essential ideas and technical preconditions for the development and research of the next generation of PEEK biological implant materials. This paper summarizes the mechanism by which the immune response after PEEK implantation leads to fibrous capsule formation; it also focuses on modification techniques to improve the anti-inflammatory and immunomodulatory abilities of PEEK. We also discuss the limitations of the existing modification techniques and present the corresponding future perspectives.

Obstruction of modern silicon semiconductor and its future development

In the past 50 years, silicon-based semiconductors have progressed rapidly, billions of transistors have been packed into a tiny area, and computer performance has increased by leaps and bounds; everything is systematically following Moore’s Law. In recent years, however, silicon transistors research and development has stagnated to a considerably lesser amount than in the past. Due to the material’s physical property, humans are unable to prevent silicon from reaching its physical constraints in both power and chip semiconductors as a result of advances in process technology and human technological requirements. Now, scientists are attempting several solutions to this problem. In the future, scientists will find a better material to replace silicon, alter the architectures of FETs, and create a new transistor with a completely different operating principle. This paper explores these three general directions for new types of semiconductors with a literature review method and based on current research findings. This paper is a good way to summarize what humans have accomplished to date and could serve as a guide for future endeavors.

Future of education in the era of generative artificial intelligence: Consensus among Chinese scholars on applications of ChatGPT in schools

AbstractChatGPT is an artificial intelligence chatbot that utilizes advanced natural language processing technologies, including large language models, to produce human‐like responses to user queries spanning a wide range of topics from programming to mathematics. As an emerging generative artificial intelligence (GAI) tool, it presents novel opportunities and challenges to the ongoing digital transformation of education. This article employs a systematic review approach to summarize the viewpoints of Chinese scholars and experts regarding the implementation of GAI in education. The research findings indicate that a majority of Chinese scholars support the cautious integration of GAI into education as it serves as a learning tool that offers personalized educational experiences for students. However, it also raises concerns related to academic integrity and the potential hindrance to students' critical thinking skills. Consequently, a framework called DATS, which outlines an optimization path for future GAI applications in schools, is proposed. The framework takes into account the perspectives of four key stakeholders: developers, administrators, teachers, and students.

Cluster-based test vector re-ordering for reduced power dissipation in digital circuits

Optimizing testing power is a paramount concern in modern digital circuit design, particularly as the intricacy of circuits continues to rise. This issue becomes even more pronounced with the scaling down of feature sizes due to advancements in process technology. The increase in testing power dissipation, beyond the regular operational state, raises red flags for both designers and test engineers. This paper introduces a novel cluster-based approach, shedding light on the efficient reordering of test vectors to mitigate the heightened switching activity. This technique aims to reduce the power consumption during testing, while still ensuring efficient error detection, maintaining the test period, and preserving the original order of the scan chain. Importantly, this reordering method does not introduce any additional area or test time overhead, minimizing the risks associated with these factors. The potential impact of this approach is demonstrated through concrete examples drawn from ISCAS’89 benchmark circuits. The results showcase a notable 11% reduction in switching activity, all while preserving fault coverage levels.

Ionizing Radiation Effects on Hole Collection Backside-Illuminated p-Type Deep-Trench-Pinned Photo-MOS Pixels Under Image Acquisition

Dark current degradation, origins, and annealing behavior after x-ray irradiation are studied in a P-type, hole collecting, backside-illuminated image sensor currently being developed at STMicroelectronics and based on deep-trenched photo-MOS pixels. Different biasing conditions during irradiation, i.e. grounded or biased and sequenced, are compared. The dark current increase with total ionizing dose (TID) and the dark current annealing behavior seem to be driven by the backside interface between the P-epitaxy of the pixels and the ONO stack. Despite still being under development, this pixel architecture already exhibits both very good electro-optical performance and a better radiation hardness than pinned photodiode-based CMOS Image sensors that benefit from the same advanced CIS processing technologies. At high total dose range, the photogate challenges custom Radiation-Hardened-by-Design photodiodes by exhibiting a comparable radiation tolerance while bringing new features such as high-resolution or Correlated Double Sampling.

New insights into the degradation mechanism and risk assessment of HFPO-DA by advanced oxidation processes based on activated persulfate in aqueous solutions

Hexafluoropropylene oxide dimer acid (HFPO-DA) is widely used as a substitute for perfluorooctanoic acid (PFOA). HFPO-DA exhibits high water solubility and low adsorption potential, conferring significant fluidity in aquatic environments. Given that the toxicity of HFPO-DA is similar to PFOA, it is necessary to control its content in aquatic environments. Electrochemical and thermally-activated persulfates have been successfully used to degrade HFPO-DA, but UV-activated persulfates cannot degrade the compound. Given that research on degradation mechanisms is still incomplete and lacks kinetic research, the mechanism and kinetic calculations of oxidative degradation were studied in detail using DFT calculations. And the toxicity of HFPO-DA degradation intermediates and products was evaluated to reveal the feasibility of using advanced oxidation process (AOP) technology based on persulfate to degrade HFPO-DA in wastewater. The results showed that the committed step of HFPO-DA degradation was initiated by the electron transfer reaction of SO4•- radicals. This reaction is not spontaneous at room temperature and requires sufficient electrical or thermal energy to be absorbed from the external environment. The perfluoroalcohol produced during this reaction can subsequently undergo four possible reactions: H atom abstraction from alcohol groups by an OH radical; H atom abstraction by SO4•-; direct HF removal; and HF removal with water as the catalyst. The final degradation products of HFPO-DA mainly include CO2, CF3CF2COOH, CF3COOH, FCOOH and HF, which has been identified through previous experimental analysis. Ecotoxicity assessment indicates that degradation does not produce highly toxic intermediates, and that the final products are non-toxic, supporting the feasibility of persulfate-based AOP technologies.

Limited Benefits of Technological Advances in Human Service Organizations: Going beyond the Hype Using Sociotechnical Knowledge Management System

This study investigates the issue of underwhelming effectiveness in Information Communication Technology (ICT) by employing a sociotechnical knowledge management system (KMS) framework. The conceptual model highlights the combined contributions of the Technical KMS representing ICT, and the Sociocultural KMS in facilitating the syntactic, semantic, and pragmatic processes of Knowledge Integration, ultimately enhancing Organizational Effectiveness. This cross-sectional survey explores the role of ICT in supporting practitioners within human services organizations as they navigate the complexities of addressing their clients’ diverse needs. The study involves a sample of 1,708 frontline caseworkers who participated in the 2022 Survey of Employee Engagement (SEE). Results demonstrate that both Technological KMS and Sociocultural KMS contribute to enhancing Organizational Effectiveness through improved Knowledge Integration. While caseworkers are more satisfied with Technological KMS, Sociocultural KMS yields greater benefits. Additional analyses comparing the 2008 and current survey data reveal ongoing underwhelming effectiveness despite technological advancements. These findings highlight the importance of integrating advanced technology and business processes, advocating for a paradigm shift toward a knowledge-based and sociotechnical perspective. The potential of Artificial Intelligence (AI) is discussed, contingent on addressing ethical concerns, cybersecurity, and privacy. Future research should explore the sociotechnical KMS applications and examine their impact on organizational effectiveness.

A Deep Echo State Network-Based Novel Signal Processing Approach for Underwater Wireless Optical Communication System with PAM and OFDM Signals

Underwater wireless optical communication (UWOC) plays key role in the underwater wireless sensor networks (UWSNs), which have been widely employed for both scientific and commercial applications. UWOC offers high transmission data rates, high security, and low latency communication between nodes in UWSNs. However, significant absorption and scattering loss in underwater channels, due to ocean water conditions, can introduce highly non-linear distortion in the received signals, which can severely deteriorate communication quality. Consequently, addressing the challenge of processing UWOC signals with low optical signal-to-noise ratios (OSNRs) is critical for UWOC systems. Increasing the transmitting optical power and investigating more advanced signal processing technologies to recover transmitted symbols are two primary approaches to improve system tolerance in noisy UWOC signal channels. In this paper, we propose and demonstrate the application of deep echo state networks (DeepESNs) for channel equalization in high-speed UWOC systems to enhance system performance with both PAM and QPSK-OFDM modulations. Our experimental results demonstrate the effectiveness of DeepESNs in UWOC systems, achieving error-free underwater transmission over 40.5 m with data rates up to 167 Mbps. Moreover, we compare the performance of DeepESNs to conventional echo state networks and provide suggestions on the configuration of a DeepESN for UWOC signals.

DAMPAK MAKANAN HARAM

Allah commands His servants to consume halal and good food. Halal is everything that is permitted by Allah. Conversly, something that is categorized as subhat or unlawful must be avoided. In fact, everything that God has created for mankind is permissible unless there are instructions that state it is unlawful. Based on the word of Allah and the Sunnah, only a small portion of food is unlawful to consume. The Qur’an and Sunnah only explain in general about foods that are forbidden to eat. However, with the times and advances in food processing technology, more detailed rules are needed to regulate the food that is declared halal. In tis case, The government has issued Technical Guidelines for Halal Production Syastem and Law Number 33 of 2014 concerning Guantees for Halal Products. This technical manual and Law number 33 state that the halaness of food products is not only determined by the raw materials and mixed ingredients, but includes the halal process starting from the supply of goods, processing, storage, packaging, distribution and presentation. The unlawfulness of food affects one’s religion, soul and mind, one of which is if a person consumes prohibited food, then his request will be rejected because Allah is not pleased with him.

The Impact of Advanced Food Processing Technologies on Agricultural Value Addition

Purpose: The study aimed at investigating the impact of advanced food processing technologies on agricultural value addition
 Methodology: This study adopted a desktop methodology. This study used secondary data from which include review of existing literature from already published studies and reports that was easily accessed through online journals and libraries.
 Findings: The study revealed that the adoption of advanced food processing technologies enhances value addition by preserving nutritional quality, extending shelf life, improving sensory attributes, optimizing processing efficiency, and ensuring microbial safety. The study also found out that advance food processing technologies have significant advantages over conventional processing methods, such as increased yield of bioactive compounds, improved rehydration properties, reduced drying time, and better maintenance of color, flavor, and texture.
 Unique Contribution to Theory, Practice and Policy: The study was anchored on Innovation Systems theory which was developed by Christopher Freeman and the Diffusion of Innovations Theory which was propounded by Everett Rogers. The study recommends the adoption of advanced food processing technologies can facilitate the development of innovative food products that meet consumer demands for healthier, safer, and more convenient options.

Chatbot-Based Natural Language Interfaces for Data Visualisation: A Scoping Review

Rapid growth in the generation of data from various sources has made data visualisation a valuable tool for analysing data. However, visual analysis can be a challenging task, not only due to intricate dashboards but also when dealing with complex and multidimensional data. In this context, advances in Natural Language Processing technologies have led to the development of Visualisation-oriented Natural Language Interfaces (V-NLIs). In this paper, we carry out a scoping review that analyses synergies between the fields of Data Visualisation and Natural Language Interaction. Specifically, we focus on chatbot-based V-NLI approaches and explore and discuss three research questions. The first two research questions focus on studying how chatbot-based V-NLIs contribute to interactions with the Data and Visual Spaces of the visualisation pipeline, while the third seeks to know how chatbot-based V-NLIs enhance users’ interaction with visualisations. Our findings show that the works in the literature put a strong focus on exploring tabular data with basic visualisations, with visual mapping primarily reliant on fixed layouts. Moreover, V-NLIs provide users with restricted guidance strategies, and few of them support high-level and follow-up queries. We identify challenges and possible research opportunities for the V-NLI community such as supporting high-level queries with complex data, integrating V-NLIs with more advanced systems such as Augmented Reality (AR) or Virtual Reality (VR), particularly for advanced visualisations, expanding guidance strategies beyond current limitations, adopting intelligent visual mapping techniques, and incorporating more sophisticated interaction methods.

Additive technologies in aircraft manufacturing

During the preparation of educational material for the distance training course for higher education applicants in the specialty 134 Aviation and rocket-space engineering, a study of the specifics of the application of various technological processes in the manufacture of parts was conducted. In particular, it was determined how widely additive technologies are used at the enterprises of the world's leading companies, how effectively justified their use in such a special direction of mechanical engineering. The analysis demonstrated the extraordinary efficiency of the 3D printing process for the manufacture of a wide range of parts for various purposes – from exposed to high temperatures to that must withstand significant sign-changing loads. The activities of the employees of the department of laser technology and physical and technical technologies for the implementation of 3D modeling and 3D printing technologies in the educational process to demonstrate the capabilities of advanced technological processes were also considered.

Towards Natural Language Interfaces for Data Visualization: A Survey.

Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary input modality to direct manipulation for visual analytics can provide an engaging user experience. It enables users to focus on their tasks rather than having to worry about how to operate visualization tools on the interface. In the past two decades, leveraging advanced natural language processing technologies, numerous V-NLI systems have been developed in academic research and commercial software, especially in recent years. In this article, we conduct a comprehensive review of the existing V-NLIs. In order to classify each article, we develop categorical dimensions based on a classic information visualization pipeline with the extension of a V-NLI layer. The following seven stages are used: query interpretation, data transformation, visual mapping, view transformation, human interaction, dialogue management, and presentation. Finally, we also shed light on several promising directions for future work in the V-NLI community.

Separation process characteristics of phenolic compounds from organic purple‐fleshed sweet potatoes (Ipomoea batatas L.) leaves using macroporous resins

AbstractCurrent trends have been noticed in to study of unedible parts of food as sources of phytochemicals or as ingredients in order to develop new uses for discarded materials and to promote sustainability. This study aimed to evaluate the performance of six macroporous resins (XAD 16, XAD 7HP, XAD 2, XAD 4, DAX 8, and XAD 1180 N) in purification of phenolic compounds from organic purple‐fleshed sweet potatoes. Static adsorption and desorption showed that XAD16 and XAD7HP had the highest adsorption and desorption ratio and recovery yield. The process temperature did not affect the adsorption capacity of XAD16. However, XAD7HP showed higher adsorption capacity when performed at 30°C, compared with 40 and 50°C. The process of equilibrium adsorption isotherms for phenolics was better described using Freundlich isotherm model. Dynamic adsorption process on XAD7HP resin showed that phenolic compounds in the water extracts of leaves started to break through after 4.5 bed volumes of extract was loaded. The purification of phytochemicals using adsorption is an alternative to replace organic solvents and provide a safety process for industrial application.Practical ApplicationsRecently, phenolic compounds have been explored due to their significant biological and antioxidant properties; phenolic compounds are also related to decreasing the risk of cardiovascular diseases, cancer, oxidative stress, diabetes, fatness, cancer, and several degenerative diseases. In addition, there is the potential use of phenolic compounds such as anthocyanin as safe colorimetric pH indicators in innovative packaging due to the relationship between levels of pH and anthocyanin colors. Therefore, using advanced processing technologies, phenolic compound purification can be essential for many applications related to food safety, quality, nutrition, and food waste. Furthermore, purified phenolic compounds can be used as raw materials in the pharmaceutical area and food industries.

CNN-Cap: Effective Convolutional Neural Network-based Capacitance Models for Interconnect Capacitance Extraction

Accurate capacitance extraction is becoming more important for designing integrated circuits under advanced process technology. The pattern matching-based full-chip extraction methodology delivers fast computational speed but suffers from large error and tedious efforts on building capacitance models of the increasing structure patterns. In this work, we propose an effective method for building convolutional neural network (CNN)-based capacitance models (called CNN-Cap) for two-dimensional (2-D) and three -dimensional (3-D) interconnect structures. With a novel grid-based data representation, the proposed method is able to model 2-D pattern structure and 3-D window structure with a variable number of conductors to largely reduce the number of patterns or increase the accuracy. Based on the ability of ResNet architecture on capturing spatial information and the proposed training skills, the obtained CNN-Cap exhibits much better performance over the multilayer perception neural network-based capacitance model while being more versatile. Extensive experiments on a 55 nm and a 15 nm process technologies have demonstrated that the error of total capacitance produced with 2-D CNN-Cap is always within 1.3%, and the error of produced coupling capacitance is less than 10% in over 99.5% probability. For 3-D structures, CNN-Cap predicts the total capacitance with less than 5% error in 99% probability and with a maximum error of 7.7%. For the tested 2-D and 3-D structures, the CNN-Cap run on a GPU server is more than 4,000× and 12,000×, respectively, faster than the conventional field solver Raphael, while consuming negligible memory.

The Potential of Duplex Stainless Steel Processed by Laser Powder Bed Fusion for Biomedical Applications: A Review

The austenitic stainless steels utilized in the production of osteosynthesis devices are susceptible to crevice corrosion. Several studies have compared the corrosive behavior of austenitic and duplex stainless steels (DSS), both of which are recognized as viable biomaterials for tissue engineering applications. All of the in vitro and in vivo studies on animals and clinical results reported to date indicate that austeno-ferritic duplex stainless steel can be recommended as a suitable alternative to ASTM F138 steel, since it is resistant to crevice corrosion in the human body and presents superior mechanical properties. The use of DSS for biomedical applications is still under discussion, mainly due to the lack of knowledge of its behavior in terms of device heating or induced movement when exposed to magnetic fields, a potentially harmful effect for the human body. As a breakthrough production technology, additive manufacturing (AM) has demonstrated significant benefits for the fabrication of metal devices with patient-specific geometry. Laser powder bed fusion has particularly been used to manufacture DSS-based components. A fine control of the processing conditions allows for an understanding of DSS microstructural evolution, which is essential for selecting processing parameters and estimating performance, including mechanical properties and corrosion resistance. Furthermore, scientific investigation is necessary for determining the relationships among material, process, and magnetic properties, in order to establish the underlying principles and critical responses. The purpose of this review is to highlight the key performances of DSS for biomedical applications and to point out the relevant role of advanced processing technologies such as additive manufacturing.

The Investigation of General Properties of Carbon Fiber (CF) Composites - Preliminary Study

The most commonly used materials in the production of high-performance CFs are cellulose, polyacrylonitrile, and pitch. Polyacrylonitrile (PAN)-based fibers dominate the market (representing nearly 90% of total CF production), with some companies producing more than 10,000 tons per year. However, the current technique's high cost (the combined cost of the precursors and stabilization accounts for 70% of total CF synthesis cost) limits the technology's applicability. Carbon fiber manufacturing is characterized by a high energy demand due to long processing times and energy intensive thermal processes. PAN-based CFs are difficult to commercialize due to the time-consuming pre-oxidation step, which significantly raises the manufacturing cost. As a result, advanced processing technologies aimed at reducing CF production costs should be developed. They were consisting of a thin but strong crystalline filament of carbon. This experimental study was to learn the mechanical properties of carbon fiber using Universal Testing Machine (UTM). There was a section where we made a phone case out of Polyacrylonitrile (PAN) carbon fiber and compared it to other materials for phone cases. The phone cases of carbon fiber composites as the one examples of consumer product was made from the woven carbon fiber then was hardened by hard epoxy mixed with resin epoxy. Then, the phone cases were tested with UTM machine to compare the tensile strength and high modulus. Other than that, there were few samples with different composition of PAN powder mixed with different composition of sodium thiocyanate. The results of the testing shows that the carbon fiber had the high tensile strength than the other materials of phone cases which were silicone and thermoplastic polyurethanes (TPU). The microstructure of carbon fiber has a significant impact on its mechanical properties.

Absolute quantum yield of short-wave infrared luminescence of GdVO4:Yb3+, Er3+, Zn2+ nano- and microparticles

Orthovanadate (GdVO4) nano- and microparticles doped with lanthanide ions are of interest for anti-counterfeiting and plastics recycling applications due to their emission in the short-wave infrared (SWIR) region. The unique aspect of this study is the measurement of the absolute photoluminescence quantum yield (QY) of the SWIR (1533 nm) emission for the orthovanadate nano- and microparticles co-doped withF Yb3+ and Er3+ using an integrating sphere. This is the first demonstration that doping with optically neutral Zn2+ ion significantly improves the QY of SWIR emission. A low QY of 0.1% was observed for the GdVO4:Yb3+, Er3+, Zn2+ nanoparticles synthesized by the co-precipitation method. However, the QY can be significantly increased (QY of 27.2%) after a 700 °C calcination step. This performance is approximately double that of a reference phosphor – Zn2+-free GdVO4:Yb3+,Er3+ synthesized by solid-phase reaction at 1050 °C – which achieved only QY of 13.0%. When micron-sized GdVO4:Yb3+, Er3+, Zn2+ particles are dispersed in water, a decrease in QY was observed (2.3%), which is explained by reabsorption of the luminescence by water. However, the water environment strongly quenched the SWIR luminescence (QY < 0.1%) in case of GdVO4:Yb3+, Er3+, Zn2+ nanoparticles with size of 125 nm. In summary, GdVO4:Yb3+, Er3+, Zn2+ microparticles with a QY of 27.2% can be used as bright luminescent markers in an advanced plastics processing technology - tracer-based sorting.

Development of ways to saving energy when operating winding machines

Energy efficiency or energy saving is the practical implementation of scientific, technical, economic and industrial measures aimed at the efficient use of energy resources. Therefore, one of the challenges facing the textile industry is energy saving in technological processes in the production of products. To solve this problem, it is proposed to introduce into production advanced technological processes with low energy costs, the use of technological equipment equipped with electric motors with high rates of consumed electrical energy. This problem is also inherent in winders and similar machines equipped with a bobbin changer. Since most of the time of operation of these devices is wasted and, accordingly, electricity is also wasted. However, to date, these issues have not been given due attention, and studies on this subject have not been conducted. In this work, the operation of the apparatus for changing bobbins in winding and similar machines has been studied in order to reduce power consumption. As a result of the study, a mathematical model of the relationship between the operating mode and technological parameters of machines and apparatuses was obtained, which makes it possible to identify ways to eliminate shortcomings in their work. Discontinuous, on signal and sectional methods of operation of the apparatus for changing bobbins have been developed, which make it possible to reduce power consumption on winding machines by 2.8–4.2 times compared to the existing method of operation. And the autonomous method of operation of the device, proposed in the work, completely eliminates the consumption of electricity consumed by the device for changing bobbins. The results of the study can be used in spinning and weaving mills.

Entity graphs for exploring online discourse.

A vast amount of human communication occurs online. These digital traces of natural human communication along with recent advances in natural language processing technology provide for computational analysis of these discussions. In the study of social networks, the typical perspective is to view users as nodes and concepts as flowing through and among the user nodes within the social network. In the present work, we take the opposite perspective: we extract and organize massive amounts of group discussion into a concept space we call an entity graph where concepts and entities are static and human communicators move about the concept space via their conversations. Framed by this perspective, we performed several experiments and comparative analysis on large volumes of online discourse from Reddit. In quantitative experiments, we found that discourse was difficult to predict, especially as the conversation carried on. We also developed an interactive tool to visually inspect conversation trails over the entity graph; although they were difficult to predict, we found that conversations, in general, tended to diverge to a vast swath of topics initially, but then tended to converge to simple and popular concepts as the conversation progressed. An application of the spreading activation function from the field of cognitive psychology also provided compelling visual narratives from the data.