Ionic fluidic devices are gaining interest due to their role in enabling self-powered neuromorphic computing systems.In this study,we present an approach that integrates an iontronic fluidic memristive(IFM)device with...Ionic fluidic devices are gaining interest due to their role in enabling self-powered neuromorphic computing systems.In this study,we present an approach that integrates an iontronic fluidic memristive(IFM)device with low input impedance and a triboelectric nanogenerator(TENG)based on ferrofluid(FF),which has high input impedance.By incorporating contact separation electromagnetic(EMG)signals with low input impedance into our FF TENG device,we enhance the FF TENG’s performance by increasing energy harvesting,thereby enabling the autonomous powering of IFM devices for self-powered computing.Further,replicating neuronal activities using artificial iontronic fluidic systems is key to advancing neuromorphic computing.These fluidic devices,composed of soft-matter materials,dynamically adjust their conductance by altering the solution interface.We developed voltage-controlled memristor and memcapacitor memory in polydimethylsiloxane(PDMS)structures,utilising a fluidic interface of FF and polyacrylic acid partial sodium salt(PAA Na^(+)).The confined ion interactions in this system induce hysteresis in ion transport across various frequencies,resulting in significant ion memory effects.Our IFM successfully replicates diverse electric pulse patterns,making it highly suitable for neuromorphic computing.Furthermore,our system demonstrates synapse-like learning functions,storing and retrieving short-term(STM)and long-term memory(LTM).The fluidic memristor exhibits dynamic synapse-like features,making it a promising candidate for the hardware implementation of neural networks.FF TENG/EMG device adaptability and seamless integration with biological systems enable the development of advanced neuromorphic devices using iontronic fluidic materials,further enhanced by intricate chemical designs for self-powered electronics.展开更多
Energy harvesting from ambient sources present in the environment is essential to replace traditional energy sources.These strategies can diversify the energy sources,reduce maintenance,lower costs,and provide near-pe...Energy harvesting from ambient sources present in the environment is essential to replace traditional energy sources.These strategies can diversify the energy sources,reduce maintenance,lower costs,and provide near-perpetual operation of the devices.In this work,a triboelectric nanogenerator(TENG)based on silane-coupled Linde type A/polydimethylsiloxane(LTA/PDMS)is developed for harsh environmental conditions.The silane-coupled LTA/PDMS-based TENG can produce a high output power density of 42.6μW/cm^(2) at a load resistance of 10 MQ and operates at an open-circuit voltage of 120 V and a short-circuit current of 15μA under a damping frequency of 14 Hz.Furthermore,the device shows ultra-robust and stable cyclic repeatability for more than 30 k cycles.The fabricated TENG is used for the physiological monitoring and charging of commercial capacitors to drive low-power electronic devices.Hence,these results suggest that the silane-coupled LTA/PDMS approach can be used to fabricate ultra-robust TENGs for harsh environmental conditions and also provides an effective path toward wearable self-powered microelectronic deVices.展开更多
The demand for sustainable energy sources to power small electronics like IoT devices has led to exploring innovative solutions like acoustic energy harvesting using piezoelectric nanogenerators(PENGs).Acoustic energy...The demand for sustainable energy sources to power small electronics like IoT devices has led to exploring innovative solutions like acoustic energy harvesting using piezoelectric nanogenerators(PENGs).Acoustic energy harvesting leverages ambient noise,converting it into electrical energy through the piezoelectric effect,where certain materials generate an electric charge in response to mechanical stress or vibrations.This review paper provides a comprehensive analysis of the advancements in PENG technology,emphasizing their role in acoustic energy harvesting.We begin by discussing the essential principles of piezoelectricity and the design considerations for nanogenerators to optimize energy capture from sound waves.The discussion includes a detailed examination of various piezoelectric materials,such as polyvinylidene fluoride(PVDF),lead zirconate titanate(PZT),and zinc oxide(ZnO)nanowires,which are known for their superior piezoelectric properties.A critical aspect of this review is the exploration of innovative structural designs and resonance devices that enhance the efficiency of PENGs.We delve into the mechanisms and benefits of using Helmholtz resonators,quarter-wavelength tubes,and cantilever beams,which are instrumental in amplifying acoustic signals and improving energy conversion rates.Each device’s design parameters and operational principles are scrutinized to highlight their contributions to the field.The review addresses practical applications of PENGs in various domains.Environmental monitoring systems,wearable electronics,and medical devices stand to benefit significantly from the continuous and sustainable power supplied by PENGs.These applications can reduce reliance on batteries and minimize maintenance by harnessing ambient acoustic energy,leading to more efficient and longer-lasting operations.Despite the promising potential of PENGs,several challenges remain,including material degradation,efficiency limitations,and integrating these devices into existing technological frameworks.This paper discusses these obstacles in detail and proposes potential solutions to enhance the longevity and performance of PENG systems.Innovations in material science and engineering are crucial to overcoming these hurdles and realizing the full potential of acoustic energy harvesting.展开更多
By exploiting ion transport phenomena in a soft and flexible discrete channel,liquid material conductance can be controlled by using an electrical input signal,which results in analog neuromorphic behavior.This paper ...By exploiting ion transport phenomena in a soft and flexible discrete channel,liquid material conductance can be controlled by using an electrical input signal,which results in analog neuromorphic behavior.This paper proposes an ionic liquid(IL)multistate resistive switching device capable of mimicking synapse analog behavior by using IL BMIM FeCL_(4) and H_(2)O into the two ends of a discrete polydimethylsiloxane(PDMs)channel.The spike rate-dependent plasticity(SRDP)and spike-timing-dependent plasticity(STDP)behavior are highly stable by modulating the input signal.Furthermore,the discrete channel device presents highly durable performance under mechanical bending and stretching.Using the obtained parameters from the proposed ionic liquid-based synaptic device,convolutional neural network simulation runs to an image recognition task,reaching an accuracy of 84%.The bending test of a device opens a new gateway for the future of soft and flexible brain-inspired neuromorphic computing systems for various shaped artificial intelligence applications.展开更多
基金supported by the System on Chip Lab grant from the Khalifa University of Science and Technology under awards Nos.8474000134 and 8474000137.
文摘Ionic fluidic devices are gaining interest due to their role in enabling self-powered neuromorphic computing systems.In this study,we present an approach that integrates an iontronic fluidic memristive(IFM)device with low input impedance and a triboelectric nanogenerator(TENG)based on ferrofluid(FF),which has high input impedance.By incorporating contact separation electromagnetic(EMG)signals with low input impedance into our FF TENG device,we enhance the FF TENG’s performance by increasing energy harvesting,thereby enabling the autonomous powering of IFM devices for self-powered computing.Further,replicating neuronal activities using artificial iontronic fluidic systems is key to advancing neuromorphic computing.These fluidic devices,composed of soft-matter materials,dynamically adjust their conductance by altering the solution interface.We developed voltage-controlled memristor and memcapacitor memory in polydimethylsiloxane(PDMS)structures,utilising a fluidic interface of FF and polyacrylic acid partial sodium salt(PAA Na^(+)).The confined ion interactions in this system induce hysteresis in ion transport across various frequencies,resulting in significant ion memory effects.Our IFM successfully replicates diverse electric pulse patterns,making it highly suitable for neuromorphic computing.Furthermore,our system demonstrates synapse-like learning functions,storing and retrieving short-term(STM)and long-term memory(LTM).The fluidic memristor exhibits dynamic synapse-like features,making it a promising candidate for the hardware implementation of neural networks.FF TENG/EMG device adaptability and seamless integration with biological systems enable the development of advanced neuromorphic devices using iontronic fluidic materials,further enhanced by intricate chemical designs for self-powered electronics.
基金This publication is based upon work supported by the System on Chip Lab grant from Khalifa University of Science and Technology under award no.8474000134 and award no.8474000137the Competitive Internal Research Award(CIRA)(2020-034).
文摘Energy harvesting from ambient sources present in the environment is essential to replace traditional energy sources.These strategies can diversify the energy sources,reduce maintenance,lower costs,and provide near-perpetual operation of the devices.In this work,a triboelectric nanogenerator(TENG)based on silane-coupled Linde type A/polydimethylsiloxane(LTA/PDMS)is developed for harsh environmental conditions.The silane-coupled LTA/PDMS-based TENG can produce a high output power density of 42.6μW/cm^(2) at a load resistance of 10 MQ and operates at an open-circuit voltage of 120 V and a short-circuit current of 15μA under a damping frequency of 14 Hz.Furthermore,the device shows ultra-robust and stable cyclic repeatability for more than 30 k cycles.The fabricated TENG is used for the physiological monitoring and charging of commercial capacitors to drive low-power electronic devices.Hence,these results suggest that the silane-coupled LTA/PDMS approach can be used to fabricate ultra-robust TENGs for harsh environmental conditions and also provides an effective path toward wearable self-powered microelectronic deVices.
基金supported by the System on Chip Lab grant from the Khalifa University of Science and Technology under award No.8474000134 and award No.8474000137.
文摘The demand for sustainable energy sources to power small electronics like IoT devices has led to exploring innovative solutions like acoustic energy harvesting using piezoelectric nanogenerators(PENGs).Acoustic energy harvesting leverages ambient noise,converting it into electrical energy through the piezoelectric effect,where certain materials generate an electric charge in response to mechanical stress or vibrations.This review paper provides a comprehensive analysis of the advancements in PENG technology,emphasizing their role in acoustic energy harvesting.We begin by discussing the essential principles of piezoelectricity and the design considerations for nanogenerators to optimize energy capture from sound waves.The discussion includes a detailed examination of various piezoelectric materials,such as polyvinylidene fluoride(PVDF),lead zirconate titanate(PZT),and zinc oxide(ZnO)nanowires,which are known for their superior piezoelectric properties.A critical aspect of this review is the exploration of innovative structural designs and resonance devices that enhance the efficiency of PENGs.We delve into the mechanisms and benefits of using Helmholtz resonators,quarter-wavelength tubes,and cantilever beams,which are instrumental in amplifying acoustic signals and improving energy conversion rates.Each device’s design parameters and operational principles are scrutinized to highlight their contributions to the field.The review addresses practical applications of PENGs in various domains.Environmental monitoring systems,wearable electronics,and medical devices stand to benefit significantly from the continuous and sustainable power supplied by PENGs.These applications can reduce reliance on batteries and minimize maintenance by harnessing ambient acoustic energy,leading to more efficient and longer-lasting operations.Despite the promising potential of PENGs,several challenges remain,including material degradation,efficiency limitations,and integrating these devices into existing technological frameworks.This paper discusses these obstacles in detail and proposes potential solutions to enhance the longevity and performance of PENG systems.Innovations in material science and engineering are crucial to overcoming these hurdles and realizing the full potential of acoustic energy harvesting.
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2019R1A6A1A10072987)the Korean goverment(MSIP)(2020R1A2C101433),The authors appreciate the support by the State Key Laboratory on Advanced Displays and Optoelectronics Technologies HKUST for material processing and characterization。
文摘By exploiting ion transport phenomena in a soft and flexible discrete channel,liquid material conductance can be controlled by using an electrical input signal,which results in analog neuromorphic behavior.This paper proposes an ionic liquid(IL)multistate resistive switching device capable of mimicking synapse analog behavior by using IL BMIM FeCL_(4) and H_(2)O into the two ends of a discrete polydimethylsiloxane(PDMs)channel.The spike rate-dependent plasticity(SRDP)and spike-timing-dependent plasticity(STDP)behavior are highly stable by modulating the input signal.Furthermore,the discrete channel device presents highly durable performance under mechanical bending and stretching.Using the obtained parameters from the proposed ionic liquid-based synaptic device,convolutional neural network simulation runs to an image recognition task,reaching an accuracy of 84%.The bending test of a device opens a new gateway for the future of soft and flexible brain-inspired neuromorphic computing systems for various shaped artificial intelligence applications.
