Mainstream Technology Research Articles

Gaining Technological Autonomy and Soci-emotional Support: A Case Study of How and Why Chinese Older Adults Engage with a Semi-acquaintance Online Community

Older adults are often underserved and marginalized in technology engagement due to their reluctance and the barriers they face in adopting and engaging with mainstream technology. However, Pinxiaoquan, a social feature of an e-commerce platform in China, has gained a large number of older users. This work investigates how and why Chinese older adults use Pinxiaoquan, aiming to unveil the underlying logic and inspire technology-inclusive design for older adults. To this end, we conducted a mixed-methods qualitative study over two years, which included online observation, and semi-interview. We found that Pinxiaoquan's success among Chinese older adults is mainly due to its ability to inspire technological autonomy and provide social-emotional support. Rather than simply lowering technical barriers or asking them to seek assistance outside the platform, Pinxiaoquan builds a semi-acquaintance online community based on location and social ties that allows older adults to realize technical support mutually. Pinxiaoquan also fulfills their social-emotional needs, such as free online expression, memory creation and preservation, relationship expansion and maintenance, and a sense of value. Our research contributes to the HCI community by highlighting the importance of improving older adults' technology autonomy following their specific social and cultural background and social-emotional needs. This work also provides unique insights and implications for building inclusive technology for the growing aging population.

Review of Ni-Based Materials for Industrial Alkaline Hydrogen Production.

Hydrogen has been recognized as a green energy carrier, which can relieve energy shortage and environmental pollution. Currently, alkaline water electrolysis (AWE) driven by renewable energy to produce large-scale green hydrogen is a mainstream technology. However, tardy cathodic hydrogen evolution reaction (HER) and stability issue of catalysts make it challenging to meet the industrial requirements. Ni-based materials have attracted wide attention, thanks to their low cost and rich tuning possibilities, and many efforts have focused on their activity and stability. However, due to the significant discrepancy between laboratory and industrial conditions, these catalysts have not been widely deployed in industrial AWE. In this review, we first introduce the differences between laboratory and industrial stage, especially concerning equipment, protocols and evaluation metrics. To shorten these gaps, some strategies are proposed to improve the activity and stability of the Ni-based catalysts. Besides, some key issues related to the catalysts in industrial AWE device are also emphasized, including reverse-current and foreign ions in the electrolyte. Finally, the challenges and outlooks on the industrial alkaline AWE are discussed.

Enhanced anaerobic digestion of freezing and thawing pretreated cow manure with increasing solid content: kinetics and microbial community dynamics

High solid anaerobic digestion has proved the mainstream technology for the treatment of organic wastes. However, the high molecular weight and complex lignocellulosic structure of cow manure (CM) make it indigestible and inefficient, leading to limit the hydrolysis step of anaerobic digestion at high solid content. To mitigate this bottleneck, an improved cost-effective freezing and thawing pretreatment technique was proposed in this study. The freezing and thawing pretreatment of raw CM without any dilution was done for 20 days. The maximum cumulative methane yield (487 mL CH4 g− 1VS) was achieved at a total solid (TS) of 5% followed by TS of 10% and 15%, which was 13%, 20% and 21% higher than obtained from untreated CM, respectively. The kinetic results revealed that the biodegradable materials could be utilized at increasing TS with decreasing hydrolysis rate. The pretreatment significantly enhanced the methylotrophic methanogenic pathway during high solid anaerobic digestion, which was contrary to the general concept that the process is usually dominated by acetoclastic and hydrogenotrophic methanogens. This study is very important to understand the effect of solid content but also important to understand the effect of freezing and thawing pretreatment on process parameters and microbial community dynamics in high solid anaerobic digestion.

Analysis of New Energy Generation Technology Based on the "Dual Carbon" Goal

With the increasingly severe global climate change issues, achieving the "dual carbon" goal has become a common pursuit for China and the world. The development of new energy power generation technology is of great significance for reducing greenhouse gas emissions and optimizing energy structure. This article first outlines the background and significance of the "dual carbon" goal, and analyzes its driving effect on new energy power generation technology. Subsequently, this paper discusses in detail several mainstream new energy power generation technologies, including wind energy, solar energy, biomass energy, and geothermal energy, and systematically analyzes their development status and challenges. In the part of technological innovation, this paper focuses on the application and innovation trend of smart grid technology, energy storage technology and power electronics technology in the field of new energy power generation. In addition, this paper also evaluates the economy of new energy power generation technology, including cost-benefit analysis and the impact of policy environment. Finally, this paper summarizes the research results and puts forward the direction and suggestions for future research.

A Review of Abnormal Crowd Behavior Recognition Technology Based on Computer Vision

Abnormal crowd behavior recognition is one of the research hotspots in computer vision. Its goal is to use computer vision technology and abnormal behavior detection models to accurately perceive, predict, and intervene in potential abnormal behaviors of the crowd and monitor the status of the crowd system in public places in real time, to effectively prevent and deal with public security risks and ensure public life safety and social order. To this end, focusing on the abnormal crowd behavior recognition technology in the computer vision system, a systematic review study of its theory and cutting-edge technology is conducted. First, the crowd level and abnormal behaviors in public places are defined, and the challenges faced by abnormal crowd behavior recognition are expounded. Then, from the dimensions based on traditional methods and based on deep learning, the mainstream technologies of abnormal behavior recognition are discussed, and the design ideas, advantages, and limitations of various methods are analyzed. Next, the mainstream software tools are introduced to provide a comprehensive reference for the technical framework. Secondly, typical abnormal behavior datasets at home and abroad are sorted out, and the characteristics of these datasets are compared in detail from multiple perspectives such as scale, characteristics, and uses, and the performance indicators of different algorithms on the datasets are compared and analyzed. Finally, the full text is summarized and the future development direction of abnormal crowd behavior recognition technology is prospected.

Spurring Innovation in AAC Technology through Collaborative Dreaming and Needs Finding with Individuals with Developmental Disabilities Who Use AAC.

Millions of individuals who have limited or no functional speech use augmentative and alternative communication (AAC) technology to participate in daily life and exercise the human right to communication. While advances in AAC technology lag significantly behind those in other technology sectors, mainstream technology innovations such as artificial intelligence (AI) present potential for the future of AAC. However, a new future of AAC will only be as effective as it is responsive to the needs and dreams of the people who rely upon it every day. AAC innovation must reflect an iterative, collaborative process with AAC users. To do this, we worked collaboratively with AAC users to complete participatory qualitative research about AAC innovation through AI. We interviewed 13 AAC users regarding (1) their current AAC engagement; (2) the barriers they experience in using AAC; (3) their dreams regarding future AAC development; and (4) reflections on potential AAC innovations. To analyze these data, a rapid research evaluation and appraisal was used. Within this article, the themes that emerged during interviews and their implications for future AAC development will be discussed. Strengths, barriers, and considerations for participatory design will also be described.

Audiovisual Speech Recognition Method Based on Connectionism

Audio-visual speech recognition technology has greatly improved the performance of pure speech recognition by combining visual speech information and acoustic speech information, but there are problems such as large data demand, audio and video data alignment, and noise robustness. Scholars have proposed many solutions to these problems. Among them, deep learning algorithms, as representatives of connectionist artificial intelligence technology, have good generalization ability and portability, and are easier to migrate to different tasks and fields. They are becoming one of the mainstream technologies for audio-visual speech recognition. This paper mainly studies and analyzes the application of deep learning technology in the field of audio-visual speech recognition, especially the audio-visual speech recognition model of the end-to-end framework. Through experimental comparative analysis, relevant data sets and evaluation methods are summarized, and finally hot issues that need to be further studied and solved are proposed.

Effect of nitrogen- and oxygen-containing functional groups on adsorption of styrene by activated carbon: A theoretical study by density functional theory

Activated carbon adsorption is one of the mainstream technologies for controlling VOCs emissions such as styrene, with surface functional groups significantly influencing its adsorption capacity. The adsorption mechanism of styrene on functionalized AC was studied using DFT calculations. Results show that nitrogen and oxygen doping altered the local electrostatic potential of AC, reduced the average LOLIPOP index of the internal ring, and enhanced styrene adsorption to varying degrees. AC with hydroxyl and pyrrolic groups significantly improved styrene adsorption (Ead = -13.76, -12.86 kcal/mol). Styrene adsorption on AC is a physisorption process, primarily dominated by π-π stacking, with dispersion interactions as the main contributor (61–70 %). In addition to π-π stacking, weak hydrogen bonds between styrene and AC functionalized with hydroxyl, amino, and pyrrolic N groups further enhance the adsorption capacity. Enhancing the synergistic effect of hydrogen bonding and π-π stacking is key to significantly improving adsorption capacity.

Silicon heterojunction back-contact solar cells by laser patterning.

Back-contact silicon solar cells, valued for their aesthetic appeal because they have no grid lines on the sunny side, find applications in buildings, vehicles and aircraft and enable self-power generation without compromising appearance1-3. Patterning techniques arrange contacts on the shaded side of the silicon wafer, which offers benefits for light incidence as well. However, the patterning process complicates production and results in power loss. We employed lasers to streamline the fabrication of back-contact solar cells and enhance the power-conversion efficiency. Using this approach, we produced a silicon solar cell that exceeded 27% efficiency. Hydrogenated amorphous silicon layers were deposited onto the wafer for surface passivation and to collect light-generated carriers. A dense passivating contact, which differs from conventional technology practice, was developed. Pulsed picosecond lasers operating at different wavelengths were used to create the back-contact patterns. The approach developed is a streamlined process for producing high-performance back-contact silicon solar cells, with a total effective processing time of about one-third that of the emerging mainstream technology. To meet the terawatt demand, we developed indium-less cells at 26.5% efficiency and precious silver-free cells at 26.2% efficiency. Thus, the integration of solar solutions into buildings and transportation is poised to expand with these technological advances.

Gold Nanowire Sponge Electrochemistry for Permeable Wearable Sweat Analysis Comfortably and Wirelessly.

Electrochemistry-based wearable and wireless sweat analysis is emerging as a promising noninvasive method for real-time health monitoring by tracking chemical and biological markers without the need for invasive blood sampling. It offers the potential to remotely monitor human sweat conditions in relation to metabolic health, stress, and electrolyte balance, which have implications for athletes, patients with chronic conditions, and individuals for the early detection and management of health issues. The state-of-the-art mainstream technology is dominated by the concept of a wearable microfluidic chip, typically based on elastomeric PDMS. While outstanding sensing performance can be realized, the design suffers from the poor permeability of PDMS, which could cause skin redness or irritation. Here, we introduce an omnidirectionally permeable, deformable, and wearable sweat analysis system based on gold nanowire sponges. We demonstrate the concept of all-in-one soft sponge electrochemistry, where the working, reference, and counter electrodes and electrolytes are all integrated within the sponge matrix. The intrinsic porosity of sponge in conjunction with vertically aligned gold nanowire electrodes gives rise to a high electrochemically active surface area of ∼67 cm2. Remarkably, this all-in-one sponge-based electrochemical system exhibited stable performance under a pressure of 10 kPa and 300% omnidirectional strain. The gold sponge biosensing electrodes could be sandwiched between two biocompatible sweat pads, which can serve as natural sweat collection and outflow layers. This naturally biocompatible and permeable platform can be integrated with wireless communication circuits, leading to a wireless sweat analysis system for the real-time monitoring of glucose, lactate, and pH during exercise.

Comparing the impact of conventional and non-conventional processing technologies on water-soluble vitamins and color in strawberry nectar – a pilot scale study

A comprehensive comparison was conducted on the effect of conventional thermal processing (TT), high-pressure processing (HP), pulse electric field (PF), and ohmic heating (OH) on water-soluble vitamins and color retention in strawberry nectar. The ascorbic acid (AA) content increased by 15- and 9-fold after TT and OH treatment, respectively, due to rupturing of cells under heat stress and release of intracellular AA. Dehydroascorbic acid (DHA) content did not change considerably after TT and PF treatment but significantly decreased after HP and OH treatment. TT treatment offered the highest total vitamin C retention. The B vitamins remained largely unchanged after processing, with the highest loss of 34 % for riboflavin in OH-treated samples. All the technologies resulted in similar color retention after processing. The study concludes with a standardized comparison of mainstream preservation technologies using pilot-scale equipment. Such an approach significantly increases the applicability of the results presented in the study.

Research on Quantum State Implementation Based on Topological Insulators

Abstract This paper first introduces the mainstream technology route of quantum computing. The analysis provides the role and advantages of topological insulators in quantum computing, such as providing stable quantum bits, enhancing the coherence and non-locality of quantum bits, and enabling the transmission of quantum information and entanglement allocation. This paper then proposes a quantum state implementation scheme based on Bi2Se3, based on the characteristics and advantages of the quantum Hall effect of topological insulators. It includes calculating the eigenstates of the Hamiltonian of topological insulators, obtaining the spatial distribution of wave functions, and generating a quantum bit platform based on topological insulators. A quantum state implementation system based on topological insulator (Bi2Se3) was constructed, and the system framework and reference configuration were provided. The solution presented in this article is an important research achievement in topological quantum computing, providing more possibilities for the implementation of feasible fault-tolerant quantum computer prototypes.

Artificial Amacrine Retinal Circuits.

Event-based imaging represents a new paradigm in visual information processing that addresses the speed and energy efficiency shortcomings inherently present in the current complementary metal oxide semiconductor-based machine vision. Realizing such imaging systems has previously been sought using very large-scale integration technologies that have complex circuitries consisting of many photodiodes, differential amplifiers, capacitors, and resistors. Here, we demonstrate that event-driven sensing can be achieved using a simple one-resistor, one-capacitor (1R1C) circuit, where the capacitor is modified with colloidal quantum dots (CQDs) to have a photoresponse. This sensory circuit emulates the motion-tracking function of the biological retina, in which the amacrine cells in the bipolar-to-ganglion synaptic pathway produce a transient spiking signal only in response to changes in light intensity but remain inactive under constant illumination. When extended to a 2D imaging array, the individual sensors work independently and output signals only when a change in the light intensity is detected; hence, the concept of the frame in image processing is thereby removed. In this work, we present the fabrication and characterization of a CQD photocapacitor-based 1R1C circuit that has a spectral response at 1550 nm in the short-wave infrared (SWIR). We report on the key performance parameters including peak responsivity, noise, and optical noise equivalent power and discuss the operating mechanism that is responsible for spiking responses in these artificial retinal circuits. The present work sets the foundation for expanding the bioinspired vision sensor capability toward midwave infrared (MWIR) and long-wave infrared (LWIR) spectral regions that are invisible to human eyes and mainstream semiconductor technologies.

Exploring corpus-invariant emotional acoustic feature for cross-corpus speech emotion recognition

Unsupervised cross-corpus speech emotion recognition (SER) is the task where the labeled training (source) and unlabeled testing (target) speech come from different corpora. Subspace transfer learning is one of the mainstream technologies for tackling cross-corpus SER challenges, which is achieved by utilizing projection matrices to learn common corpus-invariant feature representations between the source and target corpus. However, these methods mainly focus on mapping modeling from the input low-level descriptor (LLD) feature space to the corpus-invariant emotional feature space, which is an implicit feature mapping process that lacks interpretability for the selected features. This omission leads to an inability to pinpoint which acoustic features possess corpus invariance. To bridge this gap, we first propose a new transfer subspace learning framework with feature selection capabilities, i.e., the Corpus-Invariant Emotional Acoustic Feature Seeker (CAFS). Specifically, the CAFS integrates two core terms into the transfer regression loss function: (1) the emotion preservation term: This term includes emotional regression and the l2,1 norm, which is mainly used to select features and ensure that these features are related to emotions. (2) the corpus invariance preservation term: This item is mainly used to measure the difference in feature distribution between the source and target corpora. Minimizing this term bridges the gap between the source and target domains, ensuring that the chosen acoustic features are corpus-invariant. Subsequently, we conducted extensive cross-corpus SER experiments to explore corpus-invariant emotional acoustic features under various commonly used acoustic feature sets (IS09 and eGeMAPS). Through statistical analysis of the acoustic features sought by the CAFS framework, some acoustic features (e.g., Mel-Frequency Cepstral Coefficients (MFCC) and Formant) reveal their corpus-invariant properties, which could provide insights for feature selection in cross-corpus SER. These findings also lay the groundwork for a solid theoretical and empirical foundation for future research and applications in cross-corpus SER.

High-Precision Digital Clock Steering Method Based on Discrete Σ-Δ Modulation for GNSS

A high-precision time reference is fundamental to the positioning, navigation, and timing (PNT) of global navigation satellite systems (GNSS). The precision of clock steering determines the accuracy of practical applications that rely on the time–frequency reference. With the invention of direct digital synthesizer (DDS) technology, digital clock steering (DCS) has gradually become a mainstream technology. However, the key factor limiting DCS accuracy is the system quantization noise, which leads to a low frequency and phase adjustment accuracy. Here we propose a DCS method based on Σ-Δ modulation to address the issue of low resolution of DAC through shaping the quantization noise. A simulated GNSS time–frequency reference system experimental platform is constructed to validate the effectiveness of the proposed method. The experimental results demonstrate that this method achieves a phase adjustment accuracy of 0.48 ps and a frequency adjustment accuracy better than 0.48 pHz, which is two orders of magnitude higher than that of existing GNSS time–frequency reference systems. Thus, the proposed method offers a significant improvement in time–frequency reference systems, leading to better performance, reliability, and accuracy in a wide range of practical applications.

Assessment of wafer scale MoS2 atomic layers grown by metal-organic chemical vapor deposition using organo-metal, organo-sulfide, and H2S precursors.

Transition Metal Dichalcogenides (TMDs) are a unique class of materials that exhibit attractive electrical and optical properties which have generated significant interest for applications in microelectronics, optoelectronics, energy storage, and sensing. Considering the potential of these materials to impact such applications, it is crucial to develop a reliable and scalable synthesis process that is compatible with modern industrial manufacturing methods. Metal-organic chemical vapor deposition (MOCVD) offers an ideal solution to produce TMDs, due to its compatibility with large-scale production, precise layer control, and high material purity. Optimization of MOCVD protocols is necessary for effective TMD synthesis and integration into mainstream technologies. Additionally, improvements in metrology are necessary to measure the quality of the fabricated samples more accurately. In this work, we study MOCVD of wafer-scale molybdenum disulfide (MoS2) utilizing two common chalcogen precursors, H2S and DTBS. We then develop a metrology platform for wafer scale samples quality assessment. For this, the coalesced films were characterized using Raman spectroscopy, atomic force microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, and Kelvin probe force microscopy. We then correlate the structural analysis of these grown films with electrical performance by using aerosol jet printing to fabricate van der Pauw test structures and assess sheet resistance.

A Review on 3D Printing Processes in Pharmaceutical Engineering and Tissue Engineering: Applications, Trends and Challenges

AbstractAs a 3D rapid prototyping technology, 3D printing (3DP) technology has been widely applied in medical research, fabricating various medical devices or implants. With the development of biomaterials and cell‐related technologies, 3DP, especially bioprinting technology, is quietly bringing great changes and opportunities in the medical industry. Beyond surgical models, medical devices, and implants, traditional 3DP, cell‐based 3D bioprinting, and emerging 4D printing (4DP) have significantly aided in the advancement and manufacture of pharmaceuticals and biological alternatives for tissue engineering. It is envisioned that future healthcare systems, based on evolving 3DP technology and precision medicine, will deliver customized solutions that cater to the unique differences and needs of each patient. In this review work, several mainstream 3D bioprinting technologies are presented, with a focus on recent advances in 3DP for pharmaceutical engineering and important tissue engineering, including vascular and bone tissue engineering. Challenges and future prospects of 3DP for drug discovery, drug delivery systems, artificial blood vessels, vascular and bone tissue engineering scaffolds, and practical applications are also covered. Finally, the differences between 3DP and 4DP, as well as the advantages and disadvantages of different stimulus response mechanisms in 4DP and their potential applications are summarized.

Improving the performance of industrial TOPCon solar cells through the insertion of intrinsic a-Si layer

Passivating contact solar cells have gradually become the mainstream cell technology due to their excellent performance, and further improving the conversion efficiency has become a focus of subsequent research. Typically, achieving excellent field-effect passivation and low contact resistivity in doped polycrystalline silicon (poly-Si) requires heavy phosphorus doping. However, this approach can lead to a predicament wherein excessive phosphorus diffuses into the silicon (Si) substrate during annealing, consequently causing recombination losses. In response to this challenge, a structure incorporating an intrinsic amorphous silicon (a-Si (i)) layer within the passivation layers has been introduced. The primary objective of this structure is to retard the diffusion of phosphorus into the Si substrate. This study entails comprehensive characterizations to delve into the underlying mechanisms of films with the integrated a-Si (i) layer, including surface microscopy, active dopants profile, crystallographic structure, elemental distribution, and electrical properties. Finally, we have fabricated the industrial-sized TOPCon solar cells with an average efficiency of 23.83 %, which is 0.25 % higher than that of Baseline counterparts (23.58 %) on the production line. The above results have demonstrated the introduction of a-Si (i) film can be a buffer layer, retarding the diffusion of phosphorus into the Si substrate and obtaining a better passivation effect, enabling us to further tailor the doping profile for high-efficiency solar cells. Our work highlights a promising strategy to improve the performance of TOPCon solar cells, showcasing the substantial potential for implementation in industrial manufacturing.

The development of cloaking techniques based on phase-modulated metasurfaces

Abstract More and more attention has been paid to explore the application background of cloaking techniques based on phase-modulated metasurfaces, which play an important role in modern engineering and military applications. Phase-modulated metasurfaces are an emerging field of research that explores how the propagation of electromagnetic waves can be manipulated by precisely controlling the phase on tiny elements. These tiny elements, usually nanoscale structures, are arranged on the metasurface to precisely control the propagation and scattering of electromagnetic waves in a specific frequency range. The thesis first reviews the development of metamaterial cloaking technology, introduces the realization of several mainstream metamaterial cloaking technologies, and points out the benefits of cloaking techniques based on phase-modulated metasurfaces compared with other cloaking technologies. Then the development history of cloaking techniques based on phase-modulated metasurfaces is introduced through four key time nodes. We can find that phase-modulated metasurfaces are not only getting thinner and thinner, but in addition to the stealth effect, i.e., the reduction of the RCS (Radar Cross Section), phase-modulated metasurfaces can also simulate different virtual shapes. Finally, the development and research progress of cloaking techniques based on phase-modulated metasurfaces are summarized, and personal opinions on its future development are put forward. This paper summarizes the advances in the field of phase-modulated metasurfaces over the last decade and presents some representative approaches to phase-modulated metasurfaces at various points in time, which can help readers better understand the field of metasurfaces and metamaterials.

Stress Wave Hybrid Imaging for Detecting Wood Internal Defects under Sparse Signals

Stress wave technology is very suitable for detecting internal defects of standing trees, logs, and wood and has gradually become the mainstream technology in this research field. Usually, 12 sensors are positioned equidistantly around the cross-section of tree trunks in order to obtain enough stress wave signals. However, the arrangement of sensors is time-consuming and laborious, and maintaining the accuracy of stress wave imaging under sparse signals is a challenging problem. In this paper, a novel stress wave hybrid imaging method based on compressive sensing and elliptic interpolation is proposed. The spatial structure of the defective area is reconstructed by using the advantages of compressive sensing in sparse signal representation and solution of stress waves, and the healthy area is reconstructed by using the elliptic space interpolation method. Then, feature points are selected and mixed for imaging. The comparative experimental results show that the overall imaging accuracy of the proposed method reaches 89.7%, and the high-quality imaging effect can be guaranteed when the number of sensors is reduced to 10, 8, or even 6.