Wearable ultrasound devices represent a transformative advancement in therapeutic applications,offering noninvasive,continuous,and targeted treatment for deep tissues.These systems leverage flexible materials(e.g.,pie...Wearable ultrasound devices represent a transformative advancement in therapeutic applications,offering noninvasive,continuous,and targeted treatment for deep tissues.These systems leverage flexible materials(e.g.,piezoelectric composites,biodegradable polymers)and conformable designs to enable stable integration with dynamic anatomical surfaces.Key innovations include ultrasound-enhanced drug delivery through cavitation-mediated transdermal penetration,accelerated tissue regeneration via mechanical and electrical stimulation,and precise neuromodulation using focused acoustic waves.Recent developments demonstrate wireless operation,real-time monitoring,and closed-loop therapy,facilitated by energy-efficient transducers and AI-driven adaptive control.Despite progress,challenges persist in material durability,clinical validation,and scalable manufacturing.Future directions highlight the integration of nanomaterials,3D-printed architectures,and multimodal sensing for personalized medicine.This technology holds significant potential to redefine chronic disease management,postoperative recovery,and neurorehabilitation,bridging the gap between clinical and home-based care.展开更多
Two viologen derivatives containing fluorine substituent(F)with an asymmetric structures,1,1'-bis(4-(trifluoromethyl)phenyl)-[4,4'-bipyridine]dihexafluorophosphate(DFPV)and 1-benzyl-1'-(4-(trifluoromethyl)...Two viologen derivatives containing fluorine substituent(F)with an asymmetric structures,1,1'-bis(4-(trifluoromethyl)phenyl)-[4,4'-bipyridine]dihexafluorophosphate(DFPV)and 1-benzyl-1'-(4-(trifluoromethyl)phenyl)-[4,4'-bipyridine]di-hexafluorophosphate(Bn-FPV),were synthesized.These viologen derivatives as active materials were used to assemble both flexible and rigid electrochromic devices(ECDs).ECDs based on DFPV exhibited reversible color change from colorless to deep green and ECDs based on Bn-FPV exhibited reversible color change from colorless to blue-green within applied voltage.It was found that the devices based on DFPV showed cycle stability,which could still maintain more than 90% after 1000 cycles.In addition,the modulation rate of the device to the solar irradiance is also calculated to characterize its application potential in smart windows.Among them,the rigid device(R-DFPV)based on the DFPV has a large solar irradiance modulation rate of 54.66%,which has the potential to be used as smart windows.展开更多
Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement ...Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement fails to reconcile ecological responsibility with advanced functional performance.By incorporating tailored fillers into cement matrices,the resulting composites achieve enhanced thermoelectric(TE)conversion capabilities.These materials can harness solar radiation from building envelopes and recover waste heat from indoor thermal gradients,facilitating bidirectional energy conversion.This review offers a comprehensive and timely overview of cementbased thermoelectric materials(CTEMs),integrating material design,device fabrication,and diverse applications into a holistic perspective.It summarizes recent advancements in TE performance enhancement,encompassing fillers optimization and matrices innovation.Additionally,the review consolidates fabrication strategies and performance evaluations of cement-based thermoelectric devices(CTEDs),providing detailed discussions on their roles in monitoring and protection,energy harvesting,and smart building.We also address sustainability,durability,and lifecycle considerations of CTEMs,which are essential for real-world deployment.Finally,we outline future research directions in materials design,device engineering,and scalable manufacturing to foster the practical application of CTEMs in sustainable and intelligent infrastructure.展开更多
Changshu Textile Machinery Works Co.,Ltd.was founded in 1958 and is a professional R&D and manufacturing enterprise of looms shedding device in China.The company's products cover three series of shedding devic...Changshu Textile Machinery Works Co.,Ltd.was founded in 1958 and is a professional R&D and manufacturing enterprise of looms shedding device in China.The company's products cover three series of shedding devices for looms(Dobby,Jacquard,Cam Motion),forming a series of products with electronic shedding devices as the main products,and mechanical shedding devices as the auxiliary products.D2876pro electronic dobby The D2876pro electronic dobby is a high-performance equipment designed for a maximum operating speed of 800rpm.It has 16 cams,and 12mm of pitch,with a high installation type.The shedding type is double lift and full clear open.Its maximum wefts is 12,800 and 100,000.It has a two-stage filtration lubrication with a gerotor pump oil recycle system,and it is suitable for water-jet looms.展开更多
In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.Ho...In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.展开更多
We are delighted to introduce this Special Issue of Acta Metallurgica Sinica(English Letters)dedicated to"Thermoelectric Materials and Devices."Thermoelectric materials and devices have emerged as a promisin...We are delighted to introduce this Special Issue of Acta Metallurgica Sinica(English Letters)dedicated to"Thermoelectric Materials and Devices."Thermoelectric materials and devices have emerged as a promising technology for sustainable energy solutions,enabling efficient conversion between heat and electricity.This special collection highlights the latest advancements in the field,showcasing cutting-edge research and fostering interdisciplinary collaboration among researchers worldwide.展开更多
In recent years,as the dimensions of the conventional semiconductor technology is approaching the physical limits,while the multifunction circuits are restricted by the relatively fixed characteristics of the traditio...In recent years,as the dimensions of the conventional semiconductor technology is approaching the physical limits,while the multifunction circuits are restricted by the relatively fixed characteristics of the traditional metal−oxide−semiconductor field-effect transistors,reconfigurable devices that can realize reconfigurable characteristics and multiple functions at device level have been seen as a promising method to improve integration density and reduce power consumption.Owing to the ultrathin structure,effective control of the electronic characteristics and ability to modulate structural defects,two-dimensional(2D)materials have been widely used to fabricate reconfigurable devices.In this review,we summarize the working principles and related logic applications of reconfigurable devices based on 2D materials,including generating tunable anti-ambipolar responses and demonstrating nonvolatile operations.Furthermore,we discuss the analog signal processing applications of anti-ambipolar transistors and the artificial intelligence hardware implementations based on reconfigurable transistors and memristors,respectively,therefore highlighting the outstanding advantages of reconfigurable devices in footprint,energy consumption and performance.Finally,we discuss the challenges of the 2D materials-based reconfigurable devices.展开更多
To address the increasing demand for massive data storage and processing,brain-inspired neuromorphic comput-ing systems based on artificial synaptic devices have been actively developed in recent years.Among the vario...To address the increasing demand for massive data storage and processing,brain-inspired neuromorphic comput-ing systems based on artificial synaptic devices have been actively developed in recent years.Among the various materials inves-tigated for the fabrication of synaptic devices,silicon carbide(SiC)has emerged as a preferred choices due to its high electron mobility,superior thermal conductivity,and excellent thermal stability,which exhibits promising potential for neuromorphic applications in harsh environments.In this review,the recent progress in SiC-based synaptic devices is summarized.Firstly,an in-depth discussion is conducted regarding the categories,working mechanisms,and structural designs of these devices.Subse-quently,several application scenarios for SiC-based synaptic devices are presented.Finally,a few perspectives and directions for their future development are outlined.展开更多
Rapid industrialization advancements have grabbed worldwide attention to integrate a very large number of electronic components into a smaller space for performing multifunctional operations.To fulfill the growing com...Rapid industrialization advancements have grabbed worldwide attention to integrate a very large number of electronic components into a smaller space for performing multifunctional operations.To fulfill the growing computing demand state-of-the-art materials are required for substituting traditional silicon and metal oxide semiconductors frameworks.Two-dimensional(2D)materials have shown their tremendous potential surpassing the limitations of conventional materials for developing smart devices.Despite their ground-breaking progress over the last two decades,systematic studies providing in-depth insights into the exciting physics of 2D materials are still lacking.Therefore,in this review,we discuss the importance of 2D materials in bridging the gap between conventional and advanced technologies due to their distinct statistical and quantum physics.Moreover,the inherent properties of these materials could easily be tailored to meet the specific requirements of smart devices.Hence,we discuss the physics of various 2D materials enabling them to fabricate smart devices.We also shed light on promising opportunities in developing smart devices and identified the formidable challenges that need to be addressed.展开更多
Point-of-care testing(POCT)refers to a category of diagnostic tests that are performed at or near to the site of the patients(also called bedside testing)and is capable of obtaining accurate results in a short time by...Point-of-care testing(POCT)refers to a category of diagnostic tests that are performed at or near to the site of the patients(also called bedside testing)and is capable of obtaining accurate results in a short time by using portable diagnostic devices,avoiding sending samples to the medical laboratories.It has been extensively explored for diagnosing and monitoring patients’diseases and health conditions with the assistance of development in biochemistry and microfluidics.Microfluidic paper-based analytical devices(μPADs)have gained dramatic popularity in POCT because of their simplicity,user-friendly,fast and accurate result reading and low cost.SeveralμPADs have been successfully commercialized and received excellent feedback during the past several decades.This review briefly discusses the main types ofμPADs,preparation methods and their detection principles,followed by a few representative examples.The future perspectives of the development inμPADs are also provided.展开更多
Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantage...Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantages,convertingthe external analog signals to spikes is an essential prerequisite.Conventionalapproaches including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area costs.Recent efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory system.They can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory systems.This review summarizesand benchmarks the recent progress of artificial sensory neurons.It starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial sensoryneurons.Furthermore,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also provided.Finally,we highlight the challenges and perspectives for the future development of artificial sensory neurons.展开更多
Batteries,as one of the most important classes of electrochemical energy storage systems,play a critical role in enabling energy sustainability and mobility.In recent years,we have witnessed a prosperous boom of resea...Batteries,as one of the most important classes of electrochemical energy storage systems,play a critical role in enabling energy sustainability and mobility.In recent years,we have witnessed a prosperous boom of research on battery chemistries and materials aimed at enhancing energy density,reducing costs,and enabling faster charging.While these advancements promote the applications of batteries in various engineering scenarios,they also raise significant safety concerns,particularly as higher energy densities increase the risk of catastrophic failures.Unfortunately,real-world incidents involving electric vehicles,consumer electronics,and largescale energy storage systems have demonstrated the devastating consequences of battery failures,where severe property damage and even loss of life are frequently observed.展开更多
Flexible sensors,a class of devices that can convert external mechanical or physical signals into changes in resistance,capacitance,or current,have developed rapidly since the concept was first proposed.Due to the spe...Flexible sensors,a class of devices that can convert external mechanical or physical signals into changes in resistance,capacitance,or current,have developed rapidly since the concept was first proposed.Due to the special properties and naturally occurring excellent microstructures of biomaterials,it can provide more desirable properties to flexible devices.This paper systematically discusses the commonly used biomaterials for bio-based flexible devices in current research applications and their deployment in preparing flexible sensors with different mechanisms.According to the characteristics of other properties and application requirements of biomaterials,the mechanisms of their functional group properties,special microstructures,and bonding interactions in the context of various sensing applications are presented in detail.The practical application scenarios of biomaterial-based flexible devices are highlighted,including human-computer interactions,energy harvesting,wound healing,and related biomedical applications.Finally,this paper also reviews in detail the limitations of biobased materials in the construction of flexible devices and presents challenges and trends in the development of biobased flexible sensors,as well as to better explore the properties of biomaterials to ensure functional synergy within the composite materials.展开更多
Neuromorphic computing extends beyond sequential processing modalities and outperforms traditional von Neumann architectures in implementing more complicated tasks,e.g.,pattern processing,image recognition,and decisio...Neuromorphic computing extends beyond sequential processing modalities and outperforms traditional von Neumann architectures in implementing more complicated tasks,e.g.,pattern processing,image recognition,and decision making.It features parallel interconnected neural networks,high fault tolerance,robustness,autonomous learning capability,and ultralow energy dissipation.The algorithms of artificial neural network(ANN)have also been widely used because of their facile self-organization and self-learning capabilities,which mimic those of the human brain.To some extent,ANN reflects several basic functions of the human brain and can be efficiently integrated into neuromorphic devices to perform neuromorphic computations.This review highlights recent advances in neuromorphic devices assisted by machine learning algorithms.First,the basic structure of simple neuron models inspired by biological neurons and the information processing in simple neural networks are particularly discussed.Second,the fabrication and research progress of neuromorphic devices are presented regarding to materials and structures.Furthermore,the fabrication of neuromorphic devices,including stand-alone neuromorphic devices,neuromorphic device arrays,and integrated neuromorphic systems,is discussed and demonstrated with reference to some respective studies.The applications of neuromorphic devices assisted by machine learning algorithms in different fields are categorized and investigated.Finally,perspectives,suggestions,and potential solutions to the current challenges of neuromorphic devices are provided.展开更多
The development of electronic circuits designed to emulate the functionality of biological neural networks has increased significantly in recent years.Specifically,memristor-based neuromorphic operation has been demon...The development of electronic circuits designed to emulate the functionality of biological neural networks has increased significantly in recent years.Specifically,memristor-based neuromorphic operation has been demonstrated using various material combinations.One class of devices replicates the ion-concentrationgradient buildup that precedes neurotransmitter release in biological synapses.Some of these devices incorporate amino-acid-rich solutions as an active layer.This work presents a density functional theory study of such a device.The interaction between an Ag-filamentary memristor and different Hydrogen concentrations in a tyrosine-rich environment was evaluated.Two mutually exclusive structures were studied,and the resulting source-to-drain currents were compared with experimental observations.One structure was based on Tyrosine-H blocks linked to Ag atoms as a charge conduction path,while the other placed these blocks in parallel with Ag partial filaments between the source and drain.The results indicate that the second aligns with experiments and supports the hypothesis that tyrosine can act as an enabler for proton-mediated charge transport.Furthermore,the insights into the electronic transport properties of specific molecules can provide a theoretical background for designing advanced Hydrogen sensors and amino acid detectors.展开更多
Cancer remains the leading cause of death globally.Early diagnosis and intervention play deterministic roles in improving clinical prognosis.Traditional cancer management heavily depends on central hospital-based imag...Cancer remains the leading cause of death globally.Early diagnosis and intervention play deterministic roles in improving clinical prognosis.Traditional cancer management heavily depends on central hospital-based imaging and invasive diagnostics,which are intermittent and costly.Moreover,these strategies show limitations to patient compliance and real-time diagnosis.The emergence of wearable biomedical devices(WBDs)has offered a compelling alternative,enabling continuous,non-invasive in situ monitoring of bio-signals and real-time tissue imaging in daily settings.In particular,these devices have recently been integrated with therapeutic modules and artificial intelligence(AI)and have been adapted to closed-loop interventions,allowing for precise,on-demand drug delivery and localized therapy.In this review,we provide an overview of AI-integrated WBDs with their applications in cancer screening,diagnosis,and therapy.To solve the remaining issues of inaccurate screening,delayed intervention and severe side effects,the innovation of WBDs mainly includes conformable wearing structures,adhesive materials and integrated sensors/drug delivery modules.The integration of AI into WBDs has demonstrated high performance in improving signal-to-noise ratio(SNR)and real-time data processing,which significantly enhance the capabilities in long-term monitoring,and patient-specific bio-signal variations.The last session provides future directions for AI-integrated WBDs,focusing on improving SNR,reducing false positives caused by high sensitivity,and addressing patient data privacy concerns during AI training.展开更多
Neuromorphic devices,inspired by the intricate architecture of the human brain,have garnered recognition for their prodigious computational speed and sophisticated parallel computing capabilities.Vision,the primary mo...Neuromorphic devices,inspired by the intricate architecture of the human brain,have garnered recognition for their prodigious computational speed and sophisticated parallel computing capabilities.Vision,the primary mode of external information acquisition in living organisms,has garnered substantial scholarly interest.Notwithstanding numerous studies simulating the retina through optical synapses,their applications remain circumscribed to single-mode perception.Moreover,the pivotal role of temperature,a fundamental regulator of biological activities,has regrettably been relegated to the periphery.To address these limitations,we proffer a neuromorphic device endowed with multimodal perception,grounded in the principles of light-modulated semiconductors.This device seamlessly accomplishes dynamic hybrid visual and thermal multimodal perception,featuring temperature-dependent paired pulse facilitation properties and adaptive storage.Crucially,our meticulous examination of transfer curves,capacitance–voltage(C–V)tests,and noise measurements provides insights into interface and bulk defects,elucidating the physical mechanisms underlying adaptive storage and other functionalities.Additionally,the device demonstrates a variety of synaptic functionalities,including filtering properties,Ebbinghaus curves,and memory applications in image recognition.Surprisingly,the digital recognition rate achieves a remarkable value of 98.8%.展开更多
The rapid advancement of modern electronics has led to a surge in solid electronic waste,which poses significant environmental and health challenges.This review focuses on recent developments in paper-based electronic...The rapid advancement of modern electronics has led to a surge in solid electronic waste,which poses significant environmental and health challenges.This review focuses on recent developments in paper-based electronic devices fabricated through low-cost,hand-printing techniques,with particular emphasis on their applications in energy harvesting,storage,and sensing.Unlike conventional plastic-based substrates,cellulose paper offers several advantages,including biodegradability,recyclability,and low fabrication cost.By integrating functional nanomaterials such as two-dimensional chalcogenides,metal oxides,conductive polymers,and carbon-based structures onto paper,researchers have achieved high-performance devices such as broadband photodetectors(responsivity up to 52 mA/W),supercapacitors(energy density~15.1 mWh/cm^(2)),and pressure sensors(sensitivity~18.42 kPa^(-1)).The hand-printing approach,which eliminates the need for sophisticated equipment and toxic solvents,offers a promising route for scalable,sustainable,and disposable electronics.This review outlines fabrication methods and key performance metrics,and discusses the current challenges and future directions for realizing robust,flexible devices aligned with green technology and the United Nation’s Sustainable Development Goals.展开更多
Wearable signal analysis is an important technology for monitoring physiological signals without interfering with an individual’s daily behavior.As detecting cardiovascular diseases can dramatically reduce mortality,...Wearable signal analysis is an important technology for monitoring physiological signals without interfering with an individual’s daily behavior.As detecting cardiovascular diseases can dramatically reduce mortality,arrhythmia recognition using ECG signals has attracted much attention.In this paper,we propose a singlechannel convolutional neural network to detect Atrial Fibrillation(AF)based on ECG signals collected by wearable devices.It contains 3 primary modules.All recordings are firstly uniformly sized,normalized,and Butterworth low-pass filtered for noise removal.Then the preprocessed ECG signals are fed into convolutional layers for feature extraction.In the classification module,the preprocessed signals are fed into convolutional layers containing large kernels for feature extraction,and the fully connected layer provides probabilities.During the training process,the output of the previous pooling layer is concatenated with the vectors of the convolutional layer as a new feature map to reduce feature loss.Numerous comparison and ablation experiments are performed on the 2017 PhysioNet/CinC Challenge dataset,demonstrating the superiority of the proposed method.展开更多
TriboElectric NanoGenerators(TENGs),introduced in 2012 by Wang et al.,have revolutionized the way we harvest energy,converting mechanical energy into electrical power with remarkable efficiency.Since their inception,T...TriboElectric NanoGenerators(TENGs),introduced in 2012 by Wang et al.,have revolutionized the way we harvest energy,converting mechanical energy into electrical power with remarkable efficiency.Since their inception,TENGs have unlocked innumerable applications,driving a surge in innovative research and development.This study utilizes the Scopus database to conduct a bibliographic analysis,highlighting the diverse applications,influential authors,and citation patterns that define the TENG landscape.Through the use of MATLAB and VOSviewer,we provide a visually compelling analysis that not only shows the integration of artificial intelligence in scientific literature but also explores the challenges and future potential of TENG technology.The document concludes by discussing TENGs challenges and the promising paths for their future applications.展开更多
基金the support from the start-up of the University of Missouri-Columbia。
文摘Wearable ultrasound devices represent a transformative advancement in therapeutic applications,offering noninvasive,continuous,and targeted treatment for deep tissues.These systems leverage flexible materials(e.g.,piezoelectric composites,biodegradable polymers)and conformable designs to enable stable integration with dynamic anatomical surfaces.Key innovations include ultrasound-enhanced drug delivery through cavitation-mediated transdermal penetration,accelerated tissue regeneration via mechanical and electrical stimulation,and precise neuromodulation using focused acoustic waves.Recent developments demonstrate wireless operation,real-time monitoring,and closed-loop therapy,facilitated by energy-efficient transducers and AI-driven adaptive control.Despite progress,challenges persist in material durability,clinical validation,and scalable manufacturing.Future directions highlight the integration of nanomaterials,3D-printed architectures,and multimodal sensing for personalized medicine.This technology holds significant potential to redefine chronic disease management,postoperative recovery,and neurorehabilitation,bridging the gap between clinical and home-based care.
基金Funded by the Natural Science Foundation of Guangdong(Nos.2014A030313241,2014B090901068,and 2016A010103003)。
文摘Two viologen derivatives containing fluorine substituent(F)with an asymmetric structures,1,1'-bis(4-(trifluoromethyl)phenyl)-[4,4'-bipyridine]dihexafluorophosphate(DFPV)and 1-benzyl-1'-(4-(trifluoromethyl)phenyl)-[4,4'-bipyridine]di-hexafluorophosphate(Bn-FPV),were synthesized.These viologen derivatives as active materials were used to assemble both flexible and rigid electrochromic devices(ECDs).ECDs based on DFPV exhibited reversible color change from colorless to deep green and ECDs based on Bn-FPV exhibited reversible color change from colorless to blue-green within applied voltage.It was found that the devices based on DFPV showed cycle stability,which could still maintain more than 90% after 1000 cycles.In addition,the modulation rate of the device to the solar irradiance is also calculated to characterize its application potential in smart windows.Among them,the rigid device(R-DFPV)based on the DFPV has a large solar irradiance modulation rate of 54.66%,which has the potential to be used as smart windows.
基金supported by the National Natural Science Foundation of China(No.52242305).
文摘Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement fails to reconcile ecological responsibility with advanced functional performance.By incorporating tailored fillers into cement matrices,the resulting composites achieve enhanced thermoelectric(TE)conversion capabilities.These materials can harness solar radiation from building envelopes and recover waste heat from indoor thermal gradients,facilitating bidirectional energy conversion.This review offers a comprehensive and timely overview of cementbased thermoelectric materials(CTEMs),integrating material design,device fabrication,and diverse applications into a holistic perspective.It summarizes recent advancements in TE performance enhancement,encompassing fillers optimization and matrices innovation.Additionally,the review consolidates fabrication strategies and performance evaluations of cement-based thermoelectric devices(CTEDs),providing detailed discussions on their roles in monitoring and protection,energy harvesting,and smart building.We also address sustainability,durability,and lifecycle considerations of CTEMs,which are essential for real-world deployment.Finally,we outline future research directions in materials design,device engineering,and scalable manufacturing to foster the practical application of CTEMs in sustainable and intelligent infrastructure.
文摘Changshu Textile Machinery Works Co.,Ltd.was founded in 1958 and is a professional R&D and manufacturing enterprise of looms shedding device in China.The company's products cover three series of shedding devices for looms(Dobby,Jacquard,Cam Motion),forming a series of products with electronic shedding devices as the main products,and mechanical shedding devices as the auxiliary products.D2876pro electronic dobby The D2876pro electronic dobby is a high-performance equipment designed for a maximum operating speed of 800rpm.It has 16 cams,and 12mm of pitch,with a high installation type.The shedding type is double lift and full clear open.Its maximum wefts is 12,800 and 100,000.It has a two-stage filtration lubrication with a gerotor pump oil recycle system,and it is suitable for water-jet looms.
基金supported in part by STI 2030-Major Projects(2022ZD0209200)in part by National Natural Science Foundation of China(62374099)+2 种基金in part by Beijing Natural Science Foundation−Xiaomi Innovation Joint Fund(L233009)Beijing Natural Science Foundation(L248104)in part by Independent Research Program of School of Integrated Circuits,Tsinghua University,in part by Tsinghua University Fuzhou Data Technology Joint Research Institute.
文摘In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.
文摘We are delighted to introduce this Special Issue of Acta Metallurgica Sinica(English Letters)dedicated to"Thermoelectric Materials and Devices."Thermoelectric materials and devices have emerged as a promising technology for sustainable energy solutions,enabling efficient conversion between heat and electricity.This special collection highlights the latest advancements in the field,showcasing cutting-edge research and fostering interdisciplinary collaboration among researchers worldwide.
基金support from the National Key Research and Development Program of China(Grant nos.2024YFA1409700 and 2023YFA1407000)the National Natural Science Foundation of China(Grant no.62374158).
文摘In recent years,as the dimensions of the conventional semiconductor technology is approaching the physical limits,while the multifunction circuits are restricted by the relatively fixed characteristics of the traditional metal−oxide−semiconductor field-effect transistors,reconfigurable devices that can realize reconfigurable characteristics and multiple functions at device level have been seen as a promising method to improve integration density and reduce power consumption.Owing to the ultrathin structure,effective control of the electronic characteristics and ability to modulate structural defects,two-dimensional(2D)materials have been widely used to fabricate reconfigurable devices.In this review,we summarize the working principles and related logic applications of reconfigurable devices based on 2D materials,including generating tunable anti-ambipolar responses and demonstrating nonvolatile operations.Furthermore,we discuss the analog signal processing applications of anti-ambipolar transistors and the artificial intelligence hardware implementations based on reconfigurable transistors and memristors,respectively,therefore highlighting the outstanding advantages of reconfigurable devices in footprint,energy consumption and performance.Finally,we discuss the challenges of the 2D materials-based reconfigurable devices.
基金supported by the Natural Science Foundation of Zhejiang Province(Grant No.LQ24F040007)the National Natural Science Foundation of China(Grant No.U22A2075)the Opening Project of State Key Laboratory of Polymer Materials Engineering(Sichuan University)(Grant No.sklpme2024-1-21).
文摘To address the increasing demand for massive data storage and processing,brain-inspired neuromorphic comput-ing systems based on artificial synaptic devices have been actively developed in recent years.Among the various materials inves-tigated for the fabrication of synaptic devices,silicon carbide(SiC)has emerged as a preferred choices due to its high electron mobility,superior thermal conductivity,and excellent thermal stability,which exhibits promising potential for neuromorphic applications in harsh environments.In this review,the recent progress in SiC-based synaptic devices is summarized.Firstly,an in-depth discussion is conducted regarding the categories,working mechanisms,and structural designs of these devices.Subse-quently,several application scenarios for SiC-based synaptic devices are presented.Finally,a few perspectives and directions for their future development are outlined.
文摘Rapid industrialization advancements have grabbed worldwide attention to integrate a very large number of electronic components into a smaller space for performing multifunctional operations.To fulfill the growing computing demand state-of-the-art materials are required for substituting traditional silicon and metal oxide semiconductors frameworks.Two-dimensional(2D)materials have shown their tremendous potential surpassing the limitations of conventional materials for developing smart devices.Despite their ground-breaking progress over the last two decades,systematic studies providing in-depth insights into the exciting physics of 2D materials are still lacking.Therefore,in this review,we discuss the importance of 2D materials in bridging the gap between conventional and advanced technologies due to their distinct statistical and quantum physics.Moreover,the inherent properties of these materials could easily be tailored to meet the specific requirements of smart devices.Hence,we discuss the physics of various 2D materials enabling them to fabricate smart devices.We also shed light on promising opportunities in developing smart devices and identified the formidable challenges that need to be addressed.
文摘Point-of-care testing(POCT)refers to a category of diagnostic tests that are performed at or near to the site of the patients(also called bedside testing)and is capable of obtaining accurate results in a short time by using portable diagnostic devices,avoiding sending samples to the medical laboratories.It has been extensively explored for diagnosing and monitoring patients’diseases and health conditions with the assistance of development in biochemistry and microfluidics.Microfluidic paper-based analytical devices(μPADs)have gained dramatic popularity in POCT because of their simplicity,user-friendly,fast and accurate result reading and low cost.SeveralμPADs have been successfully commercialized and received excellent feedback during the past several decades.This review briefly discusses the main types ofμPADs,preparation methods and their detection principles,followed by a few representative examples.The future perspectives of the development inμPADs are also provided.
基金supported by the Key-Area Research and Development Program of Guangdong Province(Grants No.2021B0909060002)National Natural Science Foundation of China(Grants No.62204219,62204140)Major Program of Natural Science Foundation of Zhejiang Province(Grants No.LDT23F0401).
文摘Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantages,convertingthe external analog signals to spikes is an essential prerequisite.Conventionalapproaches including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area costs.Recent efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory system.They can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory systems.This review summarizesand benchmarks the recent progress of artificial sensory neurons.It starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial sensoryneurons.Furthermore,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also provided.Finally,we highlight the challenges and perspectives for the future development of artificial sensory neurons.
文摘Batteries,as one of the most important classes of electrochemical energy storage systems,play a critical role in enabling energy sustainability and mobility.In recent years,we have witnessed a prosperous boom of research on battery chemistries and materials aimed at enhancing energy density,reducing costs,and enabling faster charging.While these advancements promote the applications of batteries in various engineering scenarios,they also raise significant safety concerns,particularly as higher energy densities increase the risk of catastrophic failures.Unfortunately,real-world incidents involving electric vehicles,consumer electronics,and largescale energy storage systems have demonstrated the devastating consequences of battery failures,where severe property damage and even loss of life are frequently observed.
基金supported financially by the National Natural Science Foundation of China(52205308,22208120)the China Postdoctoral Science Foundation(2022M711300).
文摘Flexible sensors,a class of devices that can convert external mechanical or physical signals into changes in resistance,capacitance,or current,have developed rapidly since the concept was first proposed.Due to the special properties and naturally occurring excellent microstructures of biomaterials,it can provide more desirable properties to flexible devices.This paper systematically discusses the commonly used biomaterials for bio-based flexible devices in current research applications and their deployment in preparing flexible sensors with different mechanisms.According to the characteristics of other properties and application requirements of biomaterials,the mechanisms of their functional group properties,special microstructures,and bonding interactions in the context of various sensing applications are presented in detail.The practical application scenarios of biomaterial-based flexible devices are highlighted,including human-computer interactions,energy harvesting,wound healing,and related biomedical applications.Finally,this paper also reviews in detail the limitations of biobased materials in the construction of flexible devices and presents challenges and trends in the development of biobased flexible sensors,as well as to better explore the properties of biomaterials to ensure functional synergy within the composite materials.
基金financially supported by the National Natural Science Foundation of China(No.52073031)the National Key Research and Development Program of China(Nos.2023YFB3208102,2021YFB3200304)+4 种基金the China National Postdoctoral Program for Innovative Talents(No.BX2021302)the Beijing Nova Program(Nos.Z191100001119047,Z211100002121148)the Fundamental Research Funds for the Central Universities(No.E0EG6801X2)the‘Hundred Talents Program’of the Chinese Academy of Sciencesthe BrainLink program funded by the MSIT through the NRF of Korea(No.RS-2023-00237308).
文摘Neuromorphic computing extends beyond sequential processing modalities and outperforms traditional von Neumann architectures in implementing more complicated tasks,e.g.,pattern processing,image recognition,and decision making.It features parallel interconnected neural networks,high fault tolerance,robustness,autonomous learning capability,and ultralow energy dissipation.The algorithms of artificial neural network(ANN)have also been widely used because of their facile self-organization and self-learning capabilities,which mimic those of the human brain.To some extent,ANN reflects several basic functions of the human brain and can be efficiently integrated into neuromorphic devices to perform neuromorphic computations.This review highlights recent advances in neuromorphic devices assisted by machine learning algorithms.First,the basic structure of simple neuron models inspired by biological neurons and the information processing in simple neural networks are particularly discussed.Second,the fabrication and research progress of neuromorphic devices are presented regarding to materials and structures.Furthermore,the fabrication of neuromorphic devices,including stand-alone neuromorphic devices,neuromorphic device arrays,and integrated neuromorphic systems,is discussed and demonstrated with reference to some respective studies.The applications of neuromorphic devices assisted by machine learning algorithms in different fields are categorized and investigated.Finally,perspectives,suggestions,and potential solutions to the current challenges of neuromorphic devices are provided.
文摘The development of electronic circuits designed to emulate the functionality of biological neural networks has increased significantly in recent years.Specifically,memristor-based neuromorphic operation has been demonstrated using various material combinations.One class of devices replicates the ion-concentrationgradient buildup that precedes neurotransmitter release in biological synapses.Some of these devices incorporate amino-acid-rich solutions as an active layer.This work presents a density functional theory study of such a device.The interaction between an Ag-filamentary memristor and different Hydrogen concentrations in a tyrosine-rich environment was evaluated.Two mutually exclusive structures were studied,and the resulting source-to-drain currents were compared with experimental observations.One structure was based on Tyrosine-H blocks linked to Ag atoms as a charge conduction path,while the other placed these blocks in parallel with Ag partial filaments between the source and drain.The results indicate that the second aligns with experiments and supports the hypothesis that tyrosine can act as an enabler for proton-mediated charge transport.Furthermore,the insights into the electronic transport properties of specific molecules can provide a theoretical background for designing advanced Hydrogen sensors and amino acid detectors.
基金supported by National Natural Science Foundation of China(grant numbers:62176013,62571019,92259205)Beijing Natural Science Foundation(grant number:L222021)+3 种基金National Key Research and Development Program of China(grant number:2022YFC2505105)Shandong Provincial Natural Science Foundation(grant number:ZR2024QF010)Science,Technology&Innovation Project of Xiongan New Area(grant number:2023XAGG0071)the Fundamental Research Funds for the Central Universities(grant number:JKF-2025071003351).
文摘Cancer remains the leading cause of death globally.Early diagnosis and intervention play deterministic roles in improving clinical prognosis.Traditional cancer management heavily depends on central hospital-based imaging and invasive diagnostics,which are intermittent and costly.Moreover,these strategies show limitations to patient compliance and real-time diagnosis.The emergence of wearable biomedical devices(WBDs)has offered a compelling alternative,enabling continuous,non-invasive in situ monitoring of bio-signals and real-time tissue imaging in daily settings.In particular,these devices have recently been integrated with therapeutic modules and artificial intelligence(AI)and have been adapted to closed-loop interventions,allowing for precise,on-demand drug delivery and localized therapy.In this review,we provide an overview of AI-integrated WBDs with their applications in cancer screening,diagnosis,and therapy.To solve the remaining issues of inaccurate screening,delayed intervention and severe side effects,the innovation of WBDs mainly includes conformable wearing structures,adhesive materials and integrated sensors/drug delivery modules.The integration of AI into WBDs has demonstrated high performance in improving signal-to-noise ratio(SNR)and real-time data processing,which significantly enhance the capabilities in long-term monitoring,and patient-specific bio-signal variations.The last session provides future directions for AI-integrated WBDs,focusing on improving SNR,reducing false positives caused by high sensitivity,and addressing patient data privacy concerns during AI training.
基金the financial support given by National Natural Science Foundation of China(52227808,62202285)the National Science Foundation for Distinguished Young Scholars of China(51725505)+1 种基金the Development Fund for Shanghai Talents(No.2021003)Shanghai Collaborative Innovation Center of Intelligent Perception Chip Technology。
文摘Neuromorphic devices,inspired by the intricate architecture of the human brain,have garnered recognition for their prodigious computational speed and sophisticated parallel computing capabilities.Vision,the primary mode of external information acquisition in living organisms,has garnered substantial scholarly interest.Notwithstanding numerous studies simulating the retina through optical synapses,their applications remain circumscribed to single-mode perception.Moreover,the pivotal role of temperature,a fundamental regulator of biological activities,has regrettably been relegated to the periphery.To address these limitations,we proffer a neuromorphic device endowed with multimodal perception,grounded in the principles of light-modulated semiconductors.This device seamlessly accomplishes dynamic hybrid visual and thermal multimodal perception,featuring temperature-dependent paired pulse facilitation properties and adaptive storage.Crucially,our meticulous examination of transfer curves,capacitance–voltage(C–V)tests,and noise measurements provides insights into interface and bulk defects,elucidating the physical mechanisms underlying adaptive storage and other functionalities.Additionally,the device demonstrates a variety of synaptic functionalities,including filtering properties,Ebbinghaus curves,and memory applications in image recognition.Surprisingly,the digital recognition rate achieves a remarkable value of 98.8%.
基金The Consortium for Scientific Research,Indore(CSR,Indore)(No.CRS/2021-22/01/426)is acknowledged by the authorsFor the research facilities,the authors are grateful to CHARUSAT University.
文摘The rapid advancement of modern electronics has led to a surge in solid electronic waste,which poses significant environmental and health challenges.This review focuses on recent developments in paper-based electronic devices fabricated through low-cost,hand-printing techniques,with particular emphasis on their applications in energy harvesting,storage,and sensing.Unlike conventional plastic-based substrates,cellulose paper offers several advantages,including biodegradability,recyclability,and low fabrication cost.By integrating functional nanomaterials such as two-dimensional chalcogenides,metal oxides,conductive polymers,and carbon-based structures onto paper,researchers have achieved high-performance devices such as broadband photodetectors(responsivity up to 52 mA/W),supercapacitors(energy density~15.1 mWh/cm^(2)),and pressure sensors(sensitivity~18.42 kPa^(-1)).The hand-printing approach,which eliminates the need for sophisticated equipment and toxic solvents,offers a promising route for scalable,sustainable,and disposable electronics.This review outlines fabrication methods and key performance metrics,and discusses the current challenges and future directions for realizing robust,flexible devices aligned with green technology and the United Nation’s Sustainable Development Goals.
基金funded by the National Natural Science Foundation of China(No.62171114)the Fundamental Research Funds for the Central Universities(No.DUT22RC(3)099)Xiaomi Young Talents Program.
文摘Wearable signal analysis is an important technology for monitoring physiological signals without interfering with an individual’s daily behavior.As detecting cardiovascular diseases can dramatically reduce mortality,arrhythmia recognition using ECG signals has attracted much attention.In this paper,we propose a singlechannel convolutional neural network to detect Atrial Fibrillation(AF)based on ECG signals collected by wearable devices.It contains 3 primary modules.All recordings are firstly uniformly sized,normalized,and Butterworth low-pass filtered for noise removal.Then the preprocessed ECG signals are fed into convolutional layers for feature extraction.In the classification module,the preprocessed signals are fed into convolutional layers containing large kernels for feature extraction,and the fully connected layer provides probabilities.During the training process,the output of the previous pooling layer is concatenated with the vectors of the convolutional layer as a new feature map to reduce feature loss.Numerous comparison and ablation experiments are performed on the 2017 PhysioNet/CinC Challenge dataset,demonstrating the superiority of the proposed method.
基金supported by the government of the Republic of Korea(MSIT)and the National Research Foundation(NRF)of Korea(2022R1A2C1003900,2023K2A9A 1A01098512(FY2023)).
文摘TriboElectric NanoGenerators(TENGs),introduced in 2012 by Wang et al.,have revolutionized the way we harvest energy,converting mechanical energy into electrical power with remarkable efficiency.Since their inception,TENGs have unlocked innumerable applications,driving a surge in innovative research and development.This study utilizes the Scopus database to conduct a bibliographic analysis,highlighting the diverse applications,influential authors,and citation patterns that define the TENG landscape.Through the use of MATLAB and VOSviewer,we provide a visually compelling analysis that not only shows the integration of artificial intelligence in scientific literature but also explores the challenges and future potential of TENG technology.The document concludes by discussing TENGs challenges and the promising paths for their future applications.
