Current Mainstream Technologies Research Articles

Polymer Additives Promoted Texturization on Monocrystalline Silicon for Solar Cell

The solar photovoltaic was well recognized as one of the major constituent parts in future green energy system to achieving carbon neutrality. Among various technological routes to improve photoelectric conversion efficiency, rational surface texturization on monocrystalline silicon is one of the most crucial and fundamental processing steps, so as to well control the micro/nano surface structure and obtain lower light reflectivity. Chemical wet etching was the current mainstream technology in photovoltaic industry, yet there is an urgent need to update green, efficient, customized texturization additives to meet the industrial demand. This minireview summarizes the history, key breakthrough and recent advance in texturization additives based on organic and polymer molecules as crucial chemicals, and provides perspective to development directions of future texturization additives.

Infrared and Visible Image Fusion Technology and Application: A Review

The images acquired by a single visible light sensor are very susceptible to light conditions, weather changes, and other factors, while the images acquired by a single infrared light sensor generally have poor resolution, low contrast, low signal-to-noise ratio, and blurred visual effects. The fusion of visible and infrared light can avoid the disadvantages of two single sensors and, in fusing the advantages of both sensors, significantly improve the quality of the images. The fusion of infrared and visible images is widely used in agriculture, industry, medicine, and other fields. In this study, firstly, the architecture of mainstream infrared and visible image fusion technology and application was reviewed; secondly, the application status in robot vision, medical imaging, agricultural remote sensing, and industrial defect detection fields was discussed; thirdly, the evaluation indicators of the main image fusion methods were combined into the subjective evaluation and the objective evaluation, the properties of current mainstream technologies were then specifically analyzed and compared, and the outlook for image fusion was assessed; finally, infrared and visible image fusion was summarized. The results show that the definition and efficiency of the fused infrared and visible image had been improved significantly. However, there were still some problems, such as the poor accuracy of the fused image, and irretrievably lost pixels. There is a need to improve the adaptive design of the traditional algorithm parameters, to combine the innovation of the fusion algorithm and the optimization of the neural network, so as to further improve the image fusion accuracy, reduce noise interference, and improve the real-time performance of the algorithm.

The Exploration of Microbial Natural Products and Metabolic Interaction Guided by Mass Spectrometry Imaging.

As an impressive mass spectrometry technology, mass spectrometric imaging (MSI) can provide mass spectra data and spatial distribution of analytes simultaneously. MSI has been widely used in diverse fields such as clinical diagnosis, the pharmaceutical industry and environmental study due to its accuracy, high resolution and developing reproducibility. Natural products (NPs) have been a critical source of leading drugs; almost half of marketed drugs are derived from NPs or their derivatives. The continuous search for bioactive NPs from microorganisms or microbiomes has always been attractive. MSI allows us to analyze and characterize NPs directly in monocultured microorganisms or a microbial community. In this review, we briefly introduce current mainstream ionization technologies for microbial samples and the key issue of sample preparation, and then summarize some applications of MSI in the exploration of microbial NPs and metabolic interaction, especially NPs from marine microbes. Additionally, remaining challenges and future prospects are discussed.

Equilibrium Approximating and Online Learning for Anti-Jamming Game of Satellite Communication Power Allocation

Satellite communication systems are increasingly facing serious environmental challenges such as malicious jamming, monitoring, and intercepting. As a current development of artificial intelligence, intelligent jammers with learning ability can effectively perceive the surrounding spectrum environment to dynamically change their jamming strategies. As a result, the current mainstream satellite communication anti-jamming technology based on wide interval high-speed frequency hopping is unable to deal with this problem effectively. In this work, we focus on anti-jamming problems in the satellite communication domain, and reformulate the power allocation problem under two kinds of confrontation scenarios as one-shot and repeated games model. Specifically, for the problem of multi-channel power allocation under a one-shot confrontation scenario, we firstly model the problem of allocating limited power resource between communication parties and a jammer on multi-channel based on a BG (Blotto Game) model. Secondly, a DO-SINR (Double Oracle-Signal to Interference plus Noise Ratio) algorithm is designed to approximate the Nash equilibrium of the game between two parties. Experiments show that the DO-SINR algorithm can effectively obtain the approximate Nash equilibrium of the game. For the problem of multi-channel power allocation under a repeated confrontation scenario, we firstly transform the problem into an online shortest path problem with a graph structure to make the problem solving process more intuitive, and then design the Exp3-U (Exp3-Uniform) algorithm which utilizes the graph structure to solve the multi-channel power allocation problem. Experiments show that our algorithm can minimize the expected regret of communication parties during online confrontation, while maintaining good operating efficiency. The two power allocation problems constructed in this paper are common problem formed in confrontation scenarios. Our research and analysis can simulate some actual confrontation scenarios of the satellite communication power allocation, which can be used to improve the adaptability of satellite communication systems in complex environments.

NDT Method for Line Laser Welding Based on Deep Learning and One-Dimensional Time-Series Data

Welding testing is particularly important in industrial systems, but there are still some deficiencies in terms of testing performance, anti-noise capability and defect identification in current mainstream welding non-destructive testing technologies. With the development of structured-light non-destructive testing technology, deep learning technology, signal processing technology and other fields, various possibilities have emerged that make it possible to propose new ideas for welding non-destructive testing. This study used a laser sensor to propose a non-destructive method for testing welding defects in seam contours. In order to solve the problems of low sampling rates and poor recognition accuracy in traditional methods of welding defect detection, the proposed method introduces image coding into laser sensors and applies deep-learning algorithms to the classification and detection of weld defect images. By preprocessing the weld seam by encoding one-dimensional data as two-dimensional images, this method develops a framework for the detection and classification of pre-coded laser weld seam images. After taking the original extracted weld image center trajectory data as one-dimensional sequence data, we utilized the method of encoding one-dimensional time series data as two-dimensional time-series images. In doing so, the one-dimensional laser data can be encoded into the corresponding two-dimensional images and, with the application of a deep neural network, welding defect classification and detection can be realized. Experimentation was used to verify that the proposed method is of higher accuracy than traditional methods for classifying and detecting defects directly from two-dimensional welding images.

Simultaneous Surface Display and Holography Enabled by Flat Liquid Crystal Elements

AbstractAs a fundamental material in the current mainstream display technology, liquid crystal (LC) exhibits excellent properties including controllable and reconfigurable LC orientation, high‐efficiency pure‐phase modulation, active tunability, etc., and becomes one of the most attractive candidates for the development of next‐generation flat optical devices. Current LC elements are suffering from the single functionality as only one type of the optical manipulation is involved. Integrating several functions together brings great flexibility and high integration but remains an urgent task. Here, flat LC elements are proposed to simultaneously accomplish near‐field display and far‐field holography. The anisotropic nature of the LC allows a complex amplitude modulation with a sinusoidal variation, promising a continuous amplitude change, and a binary phase modulation. Specifically, several two‐channel LC elements are experimentally demonstrated, which simultaneously generate a grayscale pattern at sample surface and project an independent holographic image in the far field. Furthermore, the position and spatial multiplexing methodologies are introduced to further improve the information capacity. The proposed LC elements with simple anisotropic structure and large fabrication size can empower the multifunctional design and have promising prospects in information multiplexing, image displaying, data storage, etc.

Quantum dot-integrated GaN light-emitting diodes with resolution beyond the retinal limit

Near-eye display technology is a rapidly growing field owing to the recent emergence of augmented and mixed reality. Ultrafast response time, high resolution, high luminance, and a dynamic range for outdoor use are all important for non-pixelated, pupil-forming optics. The current mainstream technologies using liquid crystals and organic materials cannot satisfy all these conditions. Thus, finely patterned light-emissive solid-state devices with integrated circuits are often proposed to meet these requirements. In this study, we integrated several advanced technologies to design a prototype microscale light-emitting diode (LED) arrays using quantum dot (QD)-based color conversion. Wafer-scale epilayer transfer and the bond-before-pattern technique were used to directly integrate 5-µm-scale GaN LED arrays on a foreign silicon substrate. Notably, the lithography-level alignment with the bottom wafer opens up the possibility for ultrafast operation with circuit integration. Spectrally pure color conversion and solvent-free QD patterning were also achieved using an elastomeric topographical mask. Self-assembled monolayers were applied to selectively alter the surface wettability for a completely dry process. The final emissive-type LED array integrating QD, GaN, and silicon technology resulted in a 1270 PPI resolution that is far beyond the retinal limit.

Computational Exploration Toward Tunnel Oxide Passivated Contact (TOPCon) Solar Cells: Tailoring Higher Efficiency

AbstractDespite the inescapable technical challenges and unclear operating mechanisms, the last few years have witnessed considerable advances in tunnel oxide passivated contact (TOPCon) structured solar cells, most of which are centered around improving the device performance so as to truly become a step forward from current mainstream technologies. However, a systematic numerical exploration is urgently required to gain a thorough understanding of the effect of the core parameters of the device on the final performance. Here, the numerical simulation way is used to explore the potential of TOPCon technology, focused on the pursuit of higher efficiency. An exhaustive analysis concerning tunnel SiOx and doped polysilicon (poly‐Si) with field passivation effect is carried out to tailor excellent surface passivation. The simulation also suggests that the ultra‐thin SiOx with extremely low pinhole density can suppress the recombination of carriers, thus promoting the passivation quality. Additionally, simulation research is conducted on the potential of using poly‐SiOx(n+) as the doped layer, and an efficiency of 27.60% is realized via adjusting the optimal band gap and dopant concentration. Briefly, this work presents a comprehensive computational analysis of the tunnel oxide, doped layer and their synergistic impacts on the final performance.

Classification technology of domestic waste from 2000 to 2019: a bibliometrics-based review.

Waste classification is to reduce solid waste and its associated environmental pollution. This paper applied bibliometrics to assess publications related to classification technology of domestic waste from 2000 to 2019. A total of 466 publications were retrieved. The results showed the number of citations and papers increased rapidly. The major publication type regarding waste classification technology is article and English is the primary language for academic communication. The research is multidisciplinary and interdisciplinary, and its research directions are mainly divided into "Engineering," "Environmental Sciences Economics," and "Chemistry." It was identified that Waste Management (85) published most of papers in this topic. Meanwhile, China (93) contributed the most of publications, followed by the USA (42), France (40), Japan (36), and Italy (28). European countries are in the leading position in the study of garbage classification technology. Plastics and waste metals were the existing focus of waste classification technology, and waste identification and classification has become an important classification method. In addition, we also summarized the current mainstream technology progress and possible research challenges.

Design and optimization of integrated energy management network system based on internet of things technology

In recent years, China's economy continues to develop at a high speed, but also faces the enormous pressure of energy shortage and environmental deterioration. As an energy-saving discipline, we should actively adopt advanced energy-saving management methods and technologies for energy utilization management. The purpose of this paper is to study an integrated energy pipeline system based on Internet of things technology. In this paper, the actual data of a university is used to establish a prediction model to predict energy consumption, so as to better carry out energy-saving planning. Based on the theoretical basis of Internet of things technology, combined with the current mainstream technology, windows + Apache + MySQL + PHP as the development environment, ThinkPHP framework as the development framework, and a set of integrated energy data query and energy trend analysis management system. The platform integrates system login, energy consumption data query, historical energy consumption and energy consumption trend analysis, Energy saving report, and provide security and scalable features. The system test shows that the performance of the system designed in this paper is stable and can meet the actual needs. In this paper, four groups of different number of users are simulated. The average response time is less than 5S, and the CPU utilization is less than 70 %.

One-Shot Voice Conversion Algorithm Based on Representations Separation

Voice Conversion (VC) is a method of converting the source speaker's speech into the target speaker's speech without changing the source speaker's speech content. The current VC methods have the following problems: (1) they are only applicable to a limited number of speakers, not to any speakers, as a result, the application scenarios are greatly restricted; (2) the representation (feature) separation(RS) effect of the current mainstream technology is not ideal on the source speaker speech and the target speaker speech; and (3) the voice conversion quality of most models is unsatisfactory, and hence needs to be improved. Therefore, in this paper, we constructed a one-shot VC model of Representation Separation, called RS-VC model, implemented by the encoder-decoder structure. The encoder is composed of a content encoder and a speaker encoder. The content encoder separates the content information of the source speaker voice and generates a content representation. The speaker encoder separates the target speaker information of the target speaker voice and generates a speaker representation. The decoder synthesizes the content representation and the speaker representation to generate the converted voice. In this paper, we obtained the optimized speaker verification model SVIGEN2E (Speaker Verification with Instance Normalization using Generalized End-to-End loss) by improving the speaker verification (SV) model. The model SVIGEN2E is used as the speaker encoder. This speaker encoder needs to be trained in advance prior to RS-VC model training, and the pre-trained model of SVINGE2E directly extracts speaker representation of the target speaker's voice, and is used for training and testing RS-VC model. A progressive training method is proposed then for training RS-VC model. Experiments show that the progressive training method can effectively improve the quality of the converted voice. Compared with the basic speaker verification model, both SVINGE2E and RS-VC deliver the impressive improvements in EER (Equal Error Rate).

Denitration by oxidation-absorption with polypropylene hollow fiber membrane contactor

Development of cost-efficient denitration technologies has been a challenging task in chemical industry. Here we proposed a new denitration method by using polypropylene hollow fiber membrane contactor, through which the NO gas from a simulative flue gas was absorbed into a saline aqueous solution, and then oxidized by the added H2O2. We demonstrated that the numerous pores in the semipermeable membrane and the addition of NaCl gave rise to a high-efficient oxidation-absorption process. By combining with a theoretical study upon both classical and quantum density functional theories, we extensively examined the effects of different operation parameters including the gas and liquid flow rates, the concentrations of H2O2 and NaCl in the solution and SO2 in the mimic flue gas, the absorption temperature and the circulating time. The optimal operation parameters were identified. Finally, along with a designed industrial flow chart we evaluated the cost-efficiency of this proposed method, and found that this method could be more competitive than the current mainstream technologies for flue gas denitration.

Maximizing cellulosic ethanol potentials by minimizing wastewater generation and energy consumption: Competing with corn ethanol

Energy consumption and wastewater generation in cellulosic ethanol production are among the determinant factors on overall cost and technology penetration into fuel ethanol industry. This study analyzed the energy consumption and wastewater generation by the new biorefining process technology, dry acid pretreatment and biodetoxification (DryPB), as well as by the current mainstream technologies. DryPB minimizes the steam consumption to 8.63GJ and wastewater generation to 7.71tons in the core steps of biorefining process for production of one metric ton of ethanol, close to 7.83GJ and 8.33tons in corn ethanol production, respectively. The relatively higher electricity consumption is compensated by large electricity surplus from lignin residue combustion. The minimum ethanol selling price (MESP) by DryPB is below $2/gal and falls into the range of corn ethanol production cost. The work indicates that the technical and economical gap between cellulosic ethanol and corn ethanol has been almost filled up.

The research of net carbon reduction model for CCS-EOR projects and cases study

This paper develops a calculation model of net carbon reduction for CCS-EOR, which is calculated by one minus the new generation CO2 by energy consumption during the processes of capture, transportation, injection and the recovery, meanwhile adding the re-injection CO2 content. By taking the CCS-EOR projects with the capacity of 0.5 million tons CO2 per year in the coal-fired power plant, coal chemical plant and chemical fertiliser plant as examples, we calculate the actual emission reductions and energy consumption per ton of CO2 with referencing to the current mainstream technology level. The results show that the net carbon reduction values in the two situations without and with recovery process of associated gas are respectively 0.4965 and 0.3951, 0.7624 and 0.6610, 0.7815 and 0.68 tons CO2, and the energy consumption values are 5.7405 and 6.6117, 2.7095 and 3.5807, 2.49185 and 3.36305 GJ in the three different plants.

The research of net carbon reduction model for CCS-EOR projects and cases study

This paper develops a calculation model of net carbon reduction for CCS-EOR, which is calculated by one minus the new generation CO2 by energy consumption during the processes of capture, transportation, injection and the recovery, meanwhile adding the re-injection CO2 content. By taking the CCS-EOR projects with the capacity of 0.5 million tons CO2 per year in the coal-fired power plant, coal chemical plant and chemical fertiliser plant as examples, we calculate the actual emission reductions and energy consumption per ton of CO2 with referencing to the current mainstream technology level. The results show that the net carbon reduction values in the two situations without and with recovery process of associated gas are respectively 0.4965 and 0.3951, 0.7624 and 0.6610, 0.7815 and 0.68 tons CO2, and the energy consumption values are 5.7405 and 6.6117, 2.7095 and 3.5807, 2.49185 and 3.36305 GJ in the three different plants.

Low-Temperature Bonding for Silicon-Based Micro-Optical Systems

Silicon-based integrated systems are actively pursued for sensing and imaging applications. A major challenge to realize highly sensitive systems is the integration of electronic, optical, mechanical and fluidic, all on a common platform. Further, the interface quality between the tiny optoelectronic structures and the substrate for alignment and coupling of the signals significantly impacts the system’s performance. These systems also have to be low-cost, densely integrated and compatible with current and future mainstream technologies for electronic-photonic integration. To address these issues, proper selection of the fabrication, integration and assembly technologies is needed. In this paper, wafer level bonding with advanced features such as surface activation and passive alignment for vertical electrical interconnections are identified as candidate technologies to integrate different electronics, optical and photonic components. Surface activated bonding, superior to other assembly methods, enables low-temperature nanoscaled component integration with high alignment accuracy, low electrical loss and high transparency of the interface. These features are preferred for the hybrid integration of silicon-based micro-opto-electronic systems. In future, new materials and assembly technologies may emerge to enhance the performance of these micro systems and reduce their cost. The article is a detailed review of bonding techniques for electronic, optical and photonic components in silicon-based systems.

Leveraging everyday technology for people living with dementia: a case study

Purpose– The purpose of this paper is to present the self-described “journey” of a person with dementia (Brian; author 3) in his re-learning of old technologies and learning of new ones and the impact this had on his life.Design/methodology/approach– This is a single case study detailing the participant's experiences collaborating with a researcher to co-create methods of facilitating this learning process, which he documented in the form of an online blog and diary entries. These were analysed using NVivo to reveal the key themes.Findings– Brian was able to relearn previously used technologies and learn two new ones. This lead to an overarching theme of positive outlook on life supported by person-centredness, identity and technology, which challenged negative perceptions about dementia.Research limitations/implications– The paper provides an example of how learning and technology improved the life of one person with dementia. By sharing the approach the authors hope to encourage others to embrace the challenge of designing and developing innovative solutions for people with a dementia diagnosis by leveraging both current mainstream technology and creating novel bespoke interventions for dementia.Originality/value– The personal perspective of a person with dementia and his experiences of (re-) learning provide a unique insight into the impact of technology on his life.

Ultra-High Tensile Stress Capping Layer Using Novel Excimer Laser Annealing Technology for 32nm nMOSFET and Beyond

A novel processing technology for stressed capping-layer by 248nm KrF excimer laser is reported. The treated tensile capping layer is composed of silicon nitride fabricated by normal PECVD. The effects of laser annealing with different conditions on tensile nitride are extensively investigated. The number of excimer laser pulses is from 3 to 15 and energy density from 500mJ/cm2 to 800mJ/cm2. Different from conventional post-processing techniques applied in current mainstream CMOS technology for tensile SiN curing, the excimer laser annealing demonstrated much higher energy efficency and as a result, the laser annealing broke more silicon-hydrogen and nitrogen-hydrogen bonds within a much shorter time during film curing. The maximum stress of this cured layer is about 2.2GPa through typical Raman spectroscopy measuring, which much larger than that just after tensile nitride film deposition. This new process supplies one of promising solution for stress-enhancement degradation in sub-32nm CMOS technology.

An Incremental Innovation Design Process Model Based on TRIZ

In the current market, most of the innovation is incremental innovation whose features are identifying problems based on the changing needs and solving problems without changing the current mainstream technology. An incremental innovation design process model based on TRIZ is proposed in this paper. First, with the method of product functional component tree, product without missing and redundant functions can be got through cutting the needless functions and adding the missing ones. Base on this, through constructing performance state diagram of technical subsystem, the performance which can not meet or over meet design requirements can be found. At last, construct the product’s three components -function model to transform the performances which do not meet demand into inventive problems which will be solved by the TRIZ tools. The approaches in the process model take full advantage of existing product which has known structure and performance. It avoids duplication of design and reduces design costs.

Rapid pacing rotational angiography with three-dimensional reconstruction: use and benefits in structural heart disease interventions

High quality three-dimensional imaging is one of the cornerstones in structural heart disease interventions. Current mainstream technology to acquire three-dimensional imaging utilises computed tomography or magnetic resonance imaging. Incorporation of these data with conventional angiographic images may not be sufficient. We describe a new imaging technique consisting of rotational angiography combined with rapid pacing to obtain real-time, high-quality, three-dimensional images in the catheterisation laboratory. Rotational angiography is performed with breath holding and rapid pacing on a large format digital flat-panel angiographic system. During a 200 degrees rotation, 150 angiographic images are acquired in five seconds and automatically reconstructed in less than 30 seconds. This imaging technique was used in six patients (mean age 32 +/- 10 years) to guide structural heart disease interventions. No complications were associated with rapid pacing. This imaging technique allowed acquisition of high-quality, three-dimensional images with a low volume of contrast media. Volume renderings helped appreciation of the lesions and optimisation of the working views. Multiplanar visualisation allowed true orthogonal measurements of vascular diameter during the procedures. The advantages of this imaging technique include rapid image acquisition and precise imaging of complex structures using low volume of contrast media.