Synthesis Technology Research Articles

On the Issue of Legal Regulation of Deep Synthesis Technologies in China

On the Issue of Legal Regulation of Deep Synthesis Technologies in China

Voice interactive information metasurface system for simultaneous wireless information transmission and power transfer

Intelligent voice interaction offers a flexible and powerful way to connect individuals with smart devices beyond our expectations. The real-time nature of voice communication enables smart devices to comprehend the user language, execute the corresponding instructions, and facilitate seamless communications, transforming our lives in unprecedented ways. Owing to self-adaptive and reprogrammable functionalities, information metasurface (IMS) opens up a new avenue for smart home and smart cities. To further enhance the intelligence of IMS, we propose an IMS system via intelligent voice interaction and information processing. The voice interaction enables the efficient remote control on the IMS in a flexible, convenient, touchless manner. Leveraging speech recognition, speech synthesis, target detection, and communication technologies, the IMS system achieves automatic beam manipulation capabilities for wireless information transmissions and wireless power transfers. The IMS system is designed to operate in two distinct modes: instruction mode, wherein the user instructs the operations, and autonomous mode, wherein the automatic detections govern the actions, in which seamless mode switching through the voice commands is supported. Users can flexibly achieve precise control over the functions of the intelligent metasurface system through voice interaction at a distance, without the need for close-range manual touch control, which greatly simplifies the operation difficulty and is particularly suitable for remote control and complex application scenarios. A series of experiments, including wireless video transmissions and wireless power transfers are conducted to demonstrate the flexibility and convenience of the IMS system. The incorporation of intelligent voice interaction technology with the IMS presents a novel paradigm for the applications of programmable and information metasurfaces.

Bilayer C60 Polymer/h-BN Heterostructures: A DFT Study of Electronic and Optic Properties.

Interest in fullerene-based polymer structures has renewed due to the development of synthesis technologies using thin C60 polymers. Fullerene networks are good semiconductors. In this paper, heterostructure complexes composed of C60 polymer networks on atomically thin dielectric substrates are modeled. Small tensile and compressive deformations make it possible to ensure appropriate placement of monolayer boron nitride with fullerene networks. The choice of a piezoelectric boron nitride substrate was dictated by interest in their applicability in mechanoelectric, photoelectronic, and electro-optical devices with the ability to control their properties. The results we obtained show that C60 polymer/h-BN heterostructures are stable compounds. The van der Waals interaction that arises between them affects their electronic and optical properties.

An improved image texture synthesis based on algorithm convolution neural network

In recent years, texture synthesis technology has made great progress and has become one of the research hotspots in the fields of computer graphics, computer vision and image processing. Texture synthesis is proposed to solve problems such as seam aliasing in texture mapping. With the development of artificial intelligence technology, texture synthesis methods can achieve more effective results. Therefore, this paper improves the traditional texture synthesis method based on convolutional neural network. By using the VGGnet network model of the convolutional neural network and adding the Batch Normalization (BN) layer to individual convolutional layer affiliated to the network, the network training speed is improved. In this paper, the source texture image and an image initialized by white noise are respectively input into the convolutional neural network. After the forward propagation process, the texture features of the images are extracted, the loss function is constructed, and then the network is trained to update the composite image. Extensive results of experiments indicate that our proposed approach outperforms other texture synthesis methods in terms of image synthesis quality.

Securing brand trust and reputation in an era of political polarisation and AI-driven disinformation

This paper analyses the seismic reputational risks now facing brands as two major sociotechnical forces converge — the rise of ideological polarisation and the emergence of AI’s ability to generate synthetic media impersonating organisations. It examines how brands have embraced polarised stances on social issues to build deeper connections with values-driven consumers, especially younger demographics like millennials and Gen Z. By adopting partisan positions. Brands also become targets for ideological attacks seeking to erode trust. Meanwhile, rapid advances in generative AI empower malicious actors to disseminate disinformation, attacking brands with harmful narratives, misinformation and disinformation on an unprecedented scale and realism to do financial and reputational harm. The paper provides an in-depth examination of both dynamics. It explores how younger consumers increasingly demand corporate advocacy on divisive issues, forcing brands to navigate complex sociopolitical fault lines. Taking progressive stances risks a backlash from ideological opponents ready to instigate reputation-damaging retaliation. The paper also details the exponential threats introduced by AI synthesis technologies like generative adversarial networks. It explains how even modestly resourced attackers could soon produce unlimited volumes of fake content, misinformation and disinformation to target brands across all digital channels and media types. To address these converging risks, the paper recommends that brands invest in capabilities including monitoring sociocultural tensions, technologically authenticating communications, establishing early disinformation warning systems, educating consumers on resisting manipulation, crafting proactive narratives, practicing radical transparency and testing defences. It emphasises the need for holistic ‘narrative intelligence’ combining data analysis, cultural discernment and human wisdom. With deliberate strategies focused on verification, transparency and continuous learning, brands can foster resilience and enduring trust despite inevitable disruptions. The paper concludes that competence in navigating partisan debates and AI deception will become a competitive advantage in determining which brands lead in this complex future.

Integrated catalytic approach for advanced biofuel production from renewable ABE fermentation

This study focuses on advancing the production of sustainable aviation biofuels by employing a one-pot integrated catalytic approach to convert Clostridium beijerinckii strain SR-44 ABE fermentation products into higher-value compounds, specifically ketones, using Pd/Ni@BNNS bimetallic catalysts. The influence of various parameters, such as salting-out agents, temperature, catalyst loading, and reaction time, significantly improved the ABE conversion to 98% with 86% higher ketone (C5–C11) selectivity. Furthermore, the heterogeneity and recyclability of the Pd/Ni @BNNSs catalyst were investigated, confirming its suitability for industrial-scale applications. By advancing biofuel synthesis technology and overcoming the drawbacks of conventional biofuels, this study contributes to the mitigation of the environmental and energy challenges facing the aviation industry.

Electrochemical Technology for New Materials Synthesis and Reprocessing

It is difficult to underestimate the role of electrochemistry in the modern world [...]

A highly sensitive and selective fluorescent “on–off-on” peptide-based probe for sequential detection of Hg2+ and S2− ions: Applications in living cells and zebrafish imaging

Mercury ions (Hg2+) and sulfur ions (S2−), have caused serious harm to the ecological environment and human health as two kinds of highly toxic pollutants widely used. Therefore, the visual quantitative determination of Hg2+ and S2− is of great significance in the field of environmental monitoring and medical therapy. In this study, a novel fluorescent “on–off-on” peptide-based probe DNC was designed and synthesized using dipeptide (Asn-Cys-NH2) as the raw material via solid phase peptide synthesis (SPPS) technology with Fmoc chemistry. DNC displayed high selectivity in the recognition of Hg2+, and formed non-fluorescence complex (DNC-Hg2+) through 2:1 binding mode. Notably, DNC-Hg2+ complex generated in situ was used as relay response probe for highly selective sequential detection of S2− through reversible formation-separation. DNC achieved highly sensitive detection of Hg2+ and S2− with the detection limits (LODs) of 8.4 nM and 5.5 nM, respectively. Meanwhile, DNC demonstrated feasibility for Hg2+ and S2− detections in two water samples, and the considerable recovery rate was obtained. More importantly, DNC showed excellent water solubility and low toxicity, and was successfully used for consecutive discerning Hg2+ and S2− in test strips, living cells and zebrafish larvae. As an effective visual analysis method in the field, smartphone RGB Color Picker APP realized semi-quantitative detections of Hg2+ and S2− without the need for complicated device.

Sequencing by Binding rivals error-corrected Sequencing by Synthesis technology for accurate detection and quantification of minor (

Detecting very minor (< 1%) subpopulations using next-generation sequencing is a critical need for multiple applications including detection of drug resistant pathogens and somatic variant detection in oncology. To enable these applications, wet lab enhancements and bioinformatic error correction methods have been developed for 'sequencing by synthesis' technology to reduce its inherent sequencing error rate. A recently available sequencing approach termed 'sequencing by binding' claims to have higher base calling accuracy data "out of the box." This paper evaluates the utility of using 'sequencing by binding' for the detection of ultra-rare subpopulations down to 0.001%.

Rapid and large-scale synthesis of MoS2 via ultraviolet laser-assisted technology for photodetector applications

Two-dimensional transition metal dichalcogenide (TMDC) thin films have been extensively employed in microelectronics research. Molybdenum disulfide (MoS2), as one of prominent candidates of this class, has been applied in photodetectors, integrated electronic devices, gas sensing, and electrochemical catalysis, owing to its extraordinary optoelectronic, chemical, and mechanical properties. Synthesis of MoS2 crystal film is the key to its application. However, the reported technology revealed several drawbacks, containing limited surface area, prolonged high-temperature environment, and unsatisfying crystallinity. In order to enhance the convenience of MoS2 applications, there is a pressing need for optimized fabrication technology, which could be quicker, with a large area, with adequate crystallinity and heat-saving. In this work, we presented an ultraviolet laser-assisted synthesis technology, accomplishing rapid growth (with the growth rate of about 40 μm s−1) of centimeter-scale MoS2 films at room temperature. To achieve this, we self-assembled a displaceable reaction chamber system, coupled with krypton fluoride ultraviolet pulse laser. The laser motion speed and trajectory could be customized in the software, allowing the maskless patterning of crystal films. As application, we exhibited a photodetector with the integration of synthesized MoS2 and lead sulfide colloidal quantum dots (PbS CQDs), displaying broadband photodetection from ultraviolet, visible to near-infrared spectrum (365–1550 nm), with the detectivity of 109–1010 Jones, and the rising time of 0.2–0.3 s. This work not only demonstrated a high-process-efficiency synthesis of TMDC materials, but also has opened up new opportunities for ultraviolet laser used in optoelectronics.

Review on the Use of Speech Synthesis Technology in Education

Speech synthesis technology, also known as text to speech conversion technology, can convert text information into natural and smooth speech output. In the field of education, the application of speech synthesis technology is becoming increasingly widespread, providing great convenience for teaching activities and learning processes. This article will provide an overview of the application of speech synthesis technology in education, analyze its effectiveness in teaching aids, learning aids, and assessment exams, and explore its future development trends.

The Significance of Speech Synthesis Technology for the Disabled

As an important component of society, the quality of life and social status of people with disabilities are important indicators for measuring the level of social civilization. However, due to physical or psychological barriers, people with disabilities often face many difficulties in their daily lives, among which communication barriers are particularly prominent. The emergence of speech synthesis technology has provided new possibilities for people with disabilities to solve communication problems. It not only provides a new way of communication for people with disabilities, but also greatly improves their quality of life and social integration. With the continuous progress of technology and the expansion of application scope, it is believed that speech synthesis technology will bring more convenience and well-being to people with disabilities in the future. At the same time, we should also pay attention to the problems and challenges that people with disabilities may encounter when using speech synthesis technology, actively seek solutions, and create a more inclusive and equal social environment for people with disabilities.

Synthetic Genomics: Repurposing Biological Systems for Applications in Engineering Biology.

Substantial improvements in DNA sequencing and synthesis technologies and increased understanding of genome biology have empowered the development of synthetic genomics. The ability to design and construct engineered living cells boosted up by synthetic chromosomes provides opportunities to tackle enormous current and future challenges faced by humanity and the planet. Here we review the progresses, considerations, challenges, and future direction of the "design-build-test-learn" cycle used in synthetic genomics. We also discuss future applications enabled by synthetic genomics as this emerging field shapes and revolutionizes biomanufacturing and biomedicine.

Progress Made in Non-Metallic-Doped Materials for Electrocatalytic Reduction in Ammonia Production

The electrocatalytic production of ammonia has garnered considerable interest as a potentially sustainable technology for ammonia synthesis. Recently, non-metallic-doped materials have emerged as promising electrochemical catalysts for this purpose. This paper presents a comprehensive review of the latest research on non-metallic-doped materials for electrocatalytic ammonia production. Researchers have engineered a variety of materials, doped with non-metals such as nitrogen (N), boron (B), phosphorus (P), and sulfur (S), into different forms and structures to enhance their electrocatalytic activity and selectivity. A comparison among different non-metallic dopants reveals their distinct effects on the electrocatalytic performance for ammonia production. For instance, N-doping has shown enhanced activity owing to the introduction of nitrogen vacancies (NVs) and improved charge transfer kinetics. B-doping has demonstrated improved selectivity and stability, which is attributed to the formation of active sites and the suppression of competing reactions. P-doping has exhibited increased ammonia generation rates and Faradaic efficiencies, likely due to the modification of the electronic structure and surface properties. S-doping has shown potential for enhancing electrocatalytic performance, although further investigations are needed to elucidate the underlying mechanisms. These comparisons provide valuable insights for researchers to conduct in-depth studies focusing on specific non-metallic dopants, exploring their unique properties, and optimizing their performance for electrocatalytic ammonia production. However, we consider it a priority to provide insight into the recent progress made in non-metal-doped materials and their potential for enabling long-term and efficient electrochemical ammonia production. Additionally, this paper discusses the synthetic procedures used to produce non-metal-doped materials and highlights the advantages and disadvantages of each method. It also provides an in-depth analysis of the electrochemical performance of these materials, including their Faradaic efficiencies, ammonia yield rate, and selectivity. It examines the challenges and prospects of developing non-metallic-doped materials for electrocatalytic ammonia production and suggests future research directions.

A Comprehensive Review of Chemical Looping Ammonia Synthesis

Ammonia, being a vital chemical compound, has made substantial contributions to the progress of society. It addresses not only the issue of nitrogen fixation from the atmosphere but also helps alleviate the food crisis. Nevertheless, the conventional Haber-Bosch process for synthesizing ammonia is frequently associated with substantial greenhouse gas emissions and the consumption of fossil fuels. Consequently, in response to significant environmental challenges, the prospective trajectory for the synthetic ammonia sector involves the adoption of strategies such as carbon reduction, energy-efficient conversions, and the exploration of environmentally friendly and sustainable approaches to ammonia synthesis. Among the various methods for green ammonia synthesis, chemical looping ammonia synthesis (CLAS) technology is regarded as one of the most promising alternatives to conventional ammonia synthesis methods in the upcoming years. This can be attributed to the relatively mild operating conditions and the flexible and distributed characteristics of its processes. In this paper, the thermodynamic and kinetic properties of nitridation and ammoniation reactions were examined through the lens of CLAS. The design and regulation strategies of nitrogen carriers (NCs) are summarized based on various types of NCs. The process of CLAS was summarized in relation to various NCs. This paper serves as a foundational resource for the prospective advancement of the CLAS framework.

Supercritical CH3OH-Triggered Isotype Heterojunction and Groups in g-C3N4 for Enhanced Photocatalytic H2 Evolution.

The structure tuning of bulk graphitic carbon nitride (g-C3N4) is a critical way to promote the charge carriers dynamics for enhancing photocatalytic H2-evolution activity. Exploring feasible post-treatment strategies can lead to effective structure tuning, but it still remains a great challenge. Herein, a supercritical CH3OH (ScMeOH) post-treatment strategy (250-300 °C, 8.1-11.8 MPa) is developed for the structure tuning of bulk g-C3N4. This strategy presented advantages of time-saving (less than 10 min), high yield (over 80%), and scalability due to the enhanced mass transfer and high reactivity of ScMeOH. During the ScMeOH post-treatment process, CH3OH molecules diffused into the interlayers of g-C3N4 and subsequently participated in N-methylation and hydroxylation reactions with the intralayers, resulting in a partial phase transformation from g-C3N4 into carbon nitride with a poly(heptazine imide)-like structure (Q-PHI) as well as abundant methyl and hydroxyl groups. The modified g-C3N4 showed enhanced photocatalytic activity with an H2-evolution rate 7.2 times that of pristine g-C3N4, which was attributed to the synergistic effects of the g-C3N4/Q-PHI isotype heterojunction construction, group modulation, and surface area increase. This work presents a post-treatment strategy for structure tuning of bulk g-C3N4 and serves as a case for the application of supercritical fluid technology in photocatalyst synthesis.

A review of flame aerosol synthesis technology for the synthesis of nanoparticles and functional energy materials

The outstanding performance of nanomaterials in chemical, magnetic, electrical, catalytic, and mechanical properties has paved the way for the huge market in material fabrication, energy storage, electronics, and many other industries. Traditional synthesis methods are relatively stunted in industrial applicability and scalability due to complex manufacturing processes and long preparation times, hampering the development and commercialisation of nanomaterials. On the other hand, the flame synthesis method emerges as an inexpensive, efficient, and easily scalable method for the commercial production of nanoparticles. The present review aims to highlight the research status and applications of the nanomaterials synthesised by the flame aerosol method. The advancement of flame aerosol synthesis technologies is reviewed, with emphasis on the state-of-the-art flame reactor configuration and design. Critical flame parameters that govern the formation of nanoparticles in the flame are reviewed to provide an understanding of the formation criteria and growth of nanomaterials in the flame environment. The properties and characteristics of carbon-based, platinum group metal, metal oxide, bimetallic nanoparticles, perovskite and high entropy oxide nanomaterials produced by flame synthesis are extensively reviewed. In addition, commercial manufacturing of flame-synthesised materials along with applications of the nanomaterials in the field of thermal or photocatalytic energy storage, fuel cells, and gas sensing are presented.

Printed Thick Film Resistance Temperature Detector for Real-Time Tube Furnace Temperature Monitoring.

Accurately acquiring crucial data on tube furnaces and real-time temperature monitoring of different temperature zones is vital for material synthesis technology in production. However, it is difficult to achieve real-time monitoring of the temperature field of tube furnaces with existing technology. Here, we proposed a method to fabricate silver (Ag) resistance temperature detectors (RTDs) based on a blade-coating process directly on the surface of a quartz ring, which enables precise positioning and real-time temperature monitoring of tube furnaces within 100-600 °C range. The Ag RTDs exhibited outstanding electrical properties, featuring a temperature coefficient of resistance (TCR) of 2854 ppm/°C, an accuracy of 1.8% FS (full scale), and a resistance drift rate of 0.05%/h over 6 h at 600 °C. These features ensured accurate and stable temperature measurement at high temperatures. For demonstration purposes, an array comprising four Ag RTDs was installed in a tube furnace. The measured average temperature gradient in the central region of the tube furnace was 5.7 °C/mm. Furthermore, successful real-time monitoring of temperature during the alloy sintering process revealed approximately a 20-fold difference in resistivity for silver-palladium alloys sintered at various positions within the tubular furnace. The proposed strategy offers a promising approach for real-time temperature monitoring of tube furnaces.

Mesoporous Electrocatalysts with p-n Heterojunctions for Efficient Electroreduction of CO2 and N2 to Urea.

The electrocatalytic synthesis of high-value-added urea by activating N2 and CO2 is a green synthesis technology that has achieved carbon neutrality. However, the chemical adsorption and C-N coupling ability of N2 and CO2 on the surface of the catalyst are generally poor, greatly limiting the improvement of electrocatalytic activity and selectivity in electrocatalytic urea synthesis. Herein, novel hierarchical mesoporous CeO2/Co3O4 heterostructures are fabricated, and at an ultralow applied voltage of -0.2 V, the urea yield rate reaches 5.81 mmol g-1 h-1, with a corresponding Faraday efficiency of 30.05%. The hierarchical mesoporous material effectively reduces the mass transfer resistance of reactants and intermediates, making it easier for them to access active centers. The emerging space-charge regions at the heterointerface generate local electrophilic and nucleophilic regions, facilitating CO2 targeted adsorption in the electrophilic region and activation to produce *CO intermediates and N2 targeted adsorption in the nucleophilic region and activation to generate *N ═ N* intermediates. Then, the electrons in the σ orbitals of *N ═ N* intermediates can be easily accepted by the empty eg orbitals of Co3+ in CeO2/Co3O4, which presents a low-spin state (LS: t2g6eg0). Subsequently, *CO couples with *N ═ N* to produce the key intermediate *NCON*. Interestingly, it was discovered through in situ Raman spectroscopy that the CeO2/Co3O4 catalyst has a reversible spinel structure before and after the electrocatalytic reaction, which is due to the surface reconstruction of the catalyst during the electrocatalytic reaction process, producing amorphous active cobalt oxides, which is beneficial for improving electrocatalytic activity.

Humidity Diode Sensors Based on 1D Nanosized Silicon Structures

Introduction. Humidity measurement is essential in microelectronics, aerospace, biomedical, and food industries, as well as in households for climate control. Currently, various types of devices have been used as humidity sensors: capacitive, resistive, diode, gravimetric, optical structures, field-effect transistors and devices based on surface acoustic waves.Problem Statement. Today, there is a need to develop IC-compatible humidity sensors that have high sensitivityand low cost. To this end, silicon nanowires have been successfully used in resistive and capacitive humidity sensors. However, there is a lack of research on the nanowire effect on device parameters of diode-type humidity sensors.Purpose. To develop diode sensors based on silicon nanowires and to determine the effect of process parameters of synthesis and structural features of nanowires on the performance of humidity sensors.Materials and Methods. The process of sensor fabrication includes several steps: chemical cleaning of silicon wafer, synthesis of silicon nanowires using standard or modified metal-assisted chemical etching, phosphorus diffusion to create a p-n junction, front and back metallization. The surface morphology of the nanostructures has been studied by scanning electron microscopy. The humidity-sensitive characteristics have been studied with theuse of salt hygrostats.Results. It has been shown that the addition of one-dimensional silicon nanostructures to the diode-type sensor signifi cantly improves its characteristics. The rectification ratio increases from 161 to 1807, the response ups from 4.5 to 25, the sensitivity grows from 1.6 to 4.02 (%RH)–1, while the response time and recovery time are reduced from 85/90 to 25/30 s, the hysteresis value goes down from 75 to 16%, the signal deviation after cycling drops from 15to 3%, and the signal fluctuation during continuous device operation decreases from 17 to 15%.Conclusions. The results have shown that the use of a simple and cheap nanowire synthesis technology is effective to produce humidity sensors.