T. Dalgaty, E. Esmanhotto, N. Castellani, D. Querlioz, E. Vianello
Neural networks cannot typically be trained locally in edge‐computing systems due to severe energy constraints. It has, therefore, become commonplace to train them “ex situ” and transfer the resulting model to a dedicated inference hardware. Resistive memory arrays are of particular interest for realizing such inference hardware, because they offer an extremely low‐power implementation of the dot‐product operation. However, the transfer of high‐precision software parameters to the imprecise and random conductance states of resistive memories poses significant challenges. Here, it is proposed that Bayesian neural networks can be more suitable for model transfer, because, such as device conductance states, their parameters are described by random variables. The ex situ training of a Bayesian neural network is performed, and then, the resulting software model is transferred in a single programming step to an array of 16 384 resistive memory devices. On an illustrative classification task, it is observed that the transferred decision boundaries and the prediction uncertainties of the software model are well preserved. This work demonstrates that resistive memory‐based Bayesian neural networks are a promising direction in the development of resistive memory compatible edge inference hardware.
{"title":"Ex Situ Transfer of Bayesian Neural Networks to Resistive Memory‐Based Inference Hardware","authors":"T. Dalgaty, E. Esmanhotto, N. Castellani, D. Querlioz, E. Vianello","doi":"10.1002/aisy.202000103","DOIUrl":"https://doi.org/10.1002/aisy.202000103","url":null,"abstract":"Neural networks cannot typically be trained locally in edge‐computing systems due to severe energy constraints. It has, therefore, become commonplace to train them “ex situ” and transfer the resulting model to a dedicated inference hardware. Resistive memory arrays are of particular interest for realizing such inference hardware, because they offer an extremely low‐power implementation of the dot‐product operation. However, the transfer of high‐precision software parameters to the imprecise and random conductance states of resistive memories poses significant challenges. Here, it is proposed that Bayesian neural networks can be more suitable for model transfer, because, such as device conductance states, their parameters are described by random variables. The ex situ training of a Bayesian neural network is performed, and then, the resulting software model is transferred in a single programming step to an array of 16 384 resistive memory devices. On an illustrative classification task, it is observed that the transferred decision boundaries and the prediction uncertainties of the software model are well preserved. This work demonstrates that resistive memory‐based Bayesian neural networks are a promising direction in the development of resistive memory compatible edge inference hardware.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"95 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80465352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The advances of neural recording techniques have fostered rapid growth of the number of simultaneously recorded neurons, opening up new possibilities to investigate the interactions and dynamics inside neural circuitry. The high recording channel counts, however, pose significant challenges for data analysis because the required time and computational resources grow superlinearly with the data volume. Herein, the feasibility of real‐time reconstruction of neural functional connectivity using a second‐order memristor network is analyzed. Spike‐timing‐dependent plasticity, natively implemented by the internal dynamics of the memristor device, leads to the successful discovery of temporal correlations between pre‐ and postsynaptic spikes of the simulated neural circuits in an unsupervised fashion. The proposed system demonstrates high classification accuracy under a wide range of parameter settings considering indirect connections, synaptic weights, transmission delays, connection density, and so on, and enables the capturing of dynamic connectivity evolutions. The influence of device nonideal factors on detection accuracy is systematically evaluated, and the system shows robustness to initial weight randomness, and cycle‐to‐cycle and device‐to‐device variations. The proposed method allows direct mapping of neural connectivity onto the artificial memristor network and can lead to efficient front‐end data analysis of high‐density neural recording systems and potentially directly coupled bioartificial networks.
{"title":"Neural Functional Connectivity Reconstruction with Second‐Order Memristor Network","authors":"Yuting Wu, John Moon, Xiaojian Zhu, W. Lu","doi":"10.1002/aisy.202000276","DOIUrl":"https://doi.org/10.1002/aisy.202000276","url":null,"abstract":"The advances of neural recording techniques have fostered rapid growth of the number of simultaneously recorded neurons, opening up new possibilities to investigate the interactions and dynamics inside neural circuitry. The high recording channel counts, however, pose significant challenges for data analysis because the required time and computational resources grow superlinearly with the data volume. Herein, the feasibility of real‐time reconstruction of neural functional connectivity using a second‐order memristor network is analyzed. Spike‐timing‐dependent plasticity, natively implemented by the internal dynamics of the memristor device, leads to the successful discovery of temporal correlations between pre‐ and postsynaptic spikes of the simulated neural circuits in an unsupervised fashion. The proposed system demonstrates high classification accuracy under a wide range of parameter settings considering indirect connections, synaptic weights, transmission delays, connection density, and so on, and enables the capturing of dynamic connectivity evolutions. The influence of device nonideal factors on detection accuracy is systematically evaluated, and the system shows robustness to initial weight randomness, and cycle‐to‐cycle and device‐to‐device variations. The proposed method allows direct mapping of neural connectivity onto the artificial memristor network and can lead to efficient front‐end data analysis of high‐density neural recording systems and potentially directly coupled bioartificial networks.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84542996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher M. Shaffer, Atharva Deo, Andrew Tudor, Rahul Shenoy, Cameron D. Danesh, Dhruva Nathan, Lawren L. Gamble, D. Inman, Yong Chen
Unlike artificial intelligent systems based on computers which have to be programmed for specific tasks, the human brain “self‐programs” in real time to create new tactics and adapt to arbitrary environments. Computers embedded in artificial intelligent systems execute arbitrary signal‐processing algorithms to outperform humans at specific tasks, but without the real‐time self‐programming functionality, they are preprogrammed by humans, fail in unpredictable environments beyond their preprogrammed domains, and lack general intelligence in arbitrary environments. Herein, a synaptic resistor circuit that self‐programs in arbitrary and unpredictable environments in real time is demonstrated. By integrating the synaptic signal processing, memory, and correlative learning functions in each synaptic resistor, the synaptic resistor circuit processes signals and self‐programs the circuit concurrently in real time with an energy efficiency about six orders higher than those of computers. In comparison with humans and a preprogrammed computer, the self‐programming synaptic resistor circuit dynamically modifies its algorithm to control a morphing wing in an unpredictable aerodynamic environment to improve its performance function with superior self‐programming speeds and accuracy. The synaptic resistor circuits potentially circumvent the fundamental limitations of computers, leading to a new intelligent platform with real‐time self‐programming functionality for artificial general intelligence.
{"title":"Self‐Programming Synaptic Resistor Circuit for Intelligent Systems","authors":"Christopher M. Shaffer, Atharva Deo, Andrew Tudor, Rahul Shenoy, Cameron D. Danesh, Dhruva Nathan, Lawren L. Gamble, D. Inman, Yong Chen","doi":"10.1002/aisy.202100016","DOIUrl":"https://doi.org/10.1002/aisy.202100016","url":null,"abstract":"Unlike artificial intelligent systems based on computers which have to be programmed for specific tasks, the human brain “self‐programs” in real time to create new tactics and adapt to arbitrary environments. Computers embedded in artificial intelligent systems execute arbitrary signal‐processing algorithms to outperform humans at specific tasks, but without the real‐time self‐programming functionality, they are preprogrammed by humans, fail in unpredictable environments beyond their preprogrammed domains, and lack general intelligence in arbitrary environments. Herein, a synaptic resistor circuit that self‐programs in arbitrary and unpredictable environments in real time is demonstrated. By integrating the synaptic signal processing, memory, and correlative learning functions in each synaptic resistor, the synaptic resistor circuit processes signals and self‐programs the circuit concurrently in real time with an energy efficiency about six orders higher than those of computers. In comparison with humans and a preprogrammed computer, the self‐programming synaptic resistor circuit dynamically modifies its algorithm to control a morphing wing in an unpredictable aerodynamic environment to improve its performance function with superior self‐programming speeds and accuracy. The synaptic resistor circuits potentially circumvent the fundamental limitations of computers, leading to a new intelligent platform with real‐time self‐programming functionality for artificial general intelligence.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90378610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaochen Shi, Yan Chen, Hong-Lan Jiang, Du-Li Yu, Xiaoliang Guo
Driving toward the goal of gaining a high level of intelligence and agility that mimics or surpasses that of humans, sensing systems have been widely investigated. As a complex network, tactile sense converts environmental stimuli into electrical impulses through various sensory receptors, which has been exploited in a large number of revolutionary applications, including robotics, prosthetics, and health‐monitoring devices. However, it remains significantly difficult to mimic all the functionalities of human skin. Herein, a machine tactile sensing system is proposed based on machine vision, which is commonly referred to as “electronic skin” or “e‐skin.” With a high density of 625 sensing points per square centimeter similar to that of human skin, the proposed sensing system can successfully measure 3D force and temperature distribution simultaneously. Based on this information, the shape, weight, texture, stiffness, and viscosity of objects can be obtained, comprehensively mimicking the human tactile system. Moreover, the experimental results show that the proposed e‐skin achieves excellent repeatability, reproducibility, and stability compared to those based on other principles such as the piezoresistive effect and capacitive effect.
{"title":"High‐Density Force and Temperature Sensing Skin Using Micropillar Array with Image Sensor","authors":"Xiaochen Shi, Yan Chen, Hong-Lan Jiang, Du-Li Yu, Xiaoliang Guo","doi":"10.1002/aisy.202000280","DOIUrl":"https://doi.org/10.1002/aisy.202000280","url":null,"abstract":"Driving toward the goal of gaining a high level of intelligence and agility that mimics or surpasses that of humans, sensing systems have been widely investigated. As a complex network, tactile sense converts environmental stimuli into electrical impulses through various sensory receptors, which has been exploited in a large number of revolutionary applications, including robotics, prosthetics, and health‐monitoring devices. However, it remains significantly difficult to mimic all the functionalities of human skin. Herein, a machine tactile sensing system is proposed based on machine vision, which is commonly referred to as “electronic skin” or “e‐skin.” With a high density of 625 sensing points per square centimeter similar to that of human skin, the proposed sensing system can successfully measure 3D force and temperature distribution simultaneously. Based on this information, the shape, weight, texture, stiffness, and viscosity of objects can be obtained, comprehensively mimicking the human tactile system. Moreover, the experimental results show that the proposed e‐skin achieves excellent repeatability, reproducibility, and stability compared to those based on other principles such as the piezoresistive effect and capacitive effect.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86080596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Q. Hong, Qian Ma, Xinxin Gao, Che Liu, Qiang Xiao, Shabab Iqbal, T. Cui
Recently, programmable metasurfaces have aroused great attention for various applications such as beam manipulation, wireless communication, and holograms by modulating the spatial phase or amplitude. However, programmable amplitude‐coding modulations have rarely been investigated due to the difficulty in realizing dynamic control of amplitude. Herein, a real‐time programmable amplitude‐coding metasurface with multifrequency modulation is proposed by integrating PIN diodes and chip attenuators to the metaelement. The element is encoded as “11,” “10,” and “00,” corresponding to the ON/OFF states of two diodes. By switching the two states of the PIN diode, the metaelement exhibits distinctly reflected amplitude responses in three frequencies (2.98, 4.11, and 5.73 GHz). For the whole metasurface, the magnitude of the reflected beam can be modulated with some specific coding patterns. To verify the performance, six coding patterns with 10 × 10 metaelements are designed, and four of them are measured. Experimental results are fundamentally consistent with theoretical designs and simulations. Further a wireless communication demonstration is designed and implemented to perform direct modulation of digital signals without using mixers required in the conventional wireless communication systems. It is envisioned that this work will find applications in new architecture encrypted communication and imaging systems.
{"title":"Programmable Amplitude‐Coding Metasurface with Multifrequency Modulations","authors":"Q. Hong, Qian Ma, Xinxin Gao, Che Liu, Qiang Xiao, Shabab Iqbal, T. Cui","doi":"10.1002/aisy.202000260","DOIUrl":"https://doi.org/10.1002/aisy.202000260","url":null,"abstract":"Recently, programmable metasurfaces have aroused great attention for various applications such as beam manipulation, wireless communication, and holograms by modulating the spatial phase or amplitude. However, programmable amplitude‐coding modulations have rarely been investigated due to the difficulty in realizing dynamic control of amplitude. Herein, a real‐time programmable amplitude‐coding metasurface with multifrequency modulation is proposed by integrating PIN diodes and chip attenuators to the metaelement. The element is encoded as “11,” “10,” and “00,” corresponding to the ON/OFF states of two diodes. By switching the two states of the PIN diode, the metaelement exhibits distinctly reflected amplitude responses in three frequencies (2.98, 4.11, and 5.73 GHz). For the whole metasurface, the magnitude of the reflected beam can be modulated with some specific coding patterns. To verify the performance, six coding patterns with 10 × 10 metaelements are designed, and four of them are measured. Experimental results are fundamentally consistent with theoretical designs and simulations. Further a wireless communication demonstration is designed and implemented to perform direct modulation of digital signals without using mixers required in the conventional wireless communication systems. It is envisioned that this work will find applications in new architecture encrypted communication and imaging systems.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77227771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Julia A. Carpenter, T. Eberle, S. Schuerle, A. Rafsanjani, A. Studart
Magnetically driven soft actuators are unique because they are fast, remote‐controlled, conformal to rigid objects, and safe to interact with humans. Despite these multiple functionalities, a broader utilization of such actuators is hindered by the high cost and equipment‐intensive nature of currently available manufacturing processes. Herein, a simple fabrication route for magneto‐responsive soft actuators is described using cost‐effective and broadly available raw materials and equipment. The method utilizes castable silicone resins that are loaded with magnetic particles and subsequently magnetized under an external magnetic field. The experimental investigation of silicone‐based composites prepared with particles of distinct chemistries, sizes, and morphologies enables the identification of the raw materials and magnetization conditions required for the process. This leads to functional soft actuators with programmable magnetic patterns that are capable of performing pick‐and‐place, lifting, catching, and moving tasks under the remote action of an external magnetic field. By removing manufacturing hurdles associated with costly raw materials and equipment, the proposed approach is expected to facilitate the design, implementation, and exploitation of the unique functionalities of magneto‐controlled soft actuators in a wider number of applications.
{"title":"Facile Manufacturing Route for Magneto‐Responsive Soft Actuators","authors":"Julia A. Carpenter, T. Eberle, S. Schuerle, A. Rafsanjani, A. Studart","doi":"10.1002/aisy.202000283","DOIUrl":"https://doi.org/10.1002/aisy.202000283","url":null,"abstract":"Magnetically driven soft actuators are unique because they are fast, remote‐controlled, conformal to rigid objects, and safe to interact with humans. Despite these multiple functionalities, a broader utilization of such actuators is hindered by the high cost and equipment‐intensive nature of currently available manufacturing processes. Herein, a simple fabrication route for magneto‐responsive soft actuators is described using cost‐effective and broadly available raw materials and equipment. The method utilizes castable silicone resins that are loaded with magnetic particles and subsequently magnetized under an external magnetic field. The experimental investigation of silicone‐based composites prepared with particles of distinct chemistries, sizes, and morphologies enables the identification of the raw materials and magnetization conditions required for the process. This leads to functional soft actuators with programmable magnetic patterns that are capable of performing pick‐and‐place, lifting, catching, and moving tasks under the remote action of an external magnetic field. By removing manufacturing hurdles associated with costly raw materials and equipment, the proposed approach is expected to facilitate the design, implementation, and exploitation of the unique functionalities of magneto‐controlled soft actuators in a wider number of applications.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87461121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liquid‐crystalline elastomers (LCEs) are considered ideal soft actuator materials for a wide range of applications, especially the thriving soft robotics. However, 3D LCE actuators capable of precisely controllable stepwise actuation, which can enhance functionality and versatility of LCE robots for multifarious complicated applications, are still in urgent need for the reported LCE actuators mainly exploit the one‐step actuation upon the liquid‐crystallin (LC)‐isotropic phase transition temperature (Ti). Herein, a catalyst‐free LC‐vitrimer actuator with supercritical behavior is designed, which can perform precisely controllable stepwise actuation with extraordinary shape stability over a broad temperature range of about 70 °C. Moreover, supercritical behavior enables the actuator to be used in nematic phase, imparting the actuator with some extra advantages, such as higher mechanical strength and actuation stability, over the one used above Ti. Furthermore, the LCE can be reprogrammable into arbitrary 3D actuators, which can further be integrated into single‐material actuators with complex stepwise actuation, offering a generalized strategy of LCE actuators for sophisticated practical soft robots.
{"title":"Reprogrammable 3D Liquid‐Crystalline Actuators with Precisely Controllable Stepwise Actuation","authors":"Qiaomei Chen, Weiwei Li, Yen Wei, Yan Ji","doi":"10.1002/aisy.202000249","DOIUrl":"https://doi.org/10.1002/aisy.202000249","url":null,"abstract":"Liquid‐crystalline elastomers (LCEs) are considered ideal soft actuator materials for a wide range of applications, especially the thriving soft robotics. However, 3D LCE actuators capable of precisely controllable stepwise actuation, which can enhance functionality and versatility of LCE robots for multifarious complicated applications, are still in urgent need for the reported LCE actuators mainly exploit the one‐step actuation upon the liquid‐crystallin (LC)‐isotropic phase transition temperature (Ti). Herein, a catalyst‐free LC‐vitrimer actuator with supercritical behavior is designed, which can perform precisely controllable stepwise actuation with extraordinary shape stability over a broad temperature range of about 70 °C. Moreover, supercritical behavior enables the actuator to be used in nematic phase, imparting the actuator with some extra advantages, such as higher mechanical strength and actuation stability, over the one used above Ti. Furthermore, the LCE can be reprogrammable into arbitrary 3D actuators, which can further be integrated into single‐material actuators with complex stepwise actuation, offering a generalized strategy of LCE actuators for sophisticated practical soft robots.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82668309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Min Pan, Chenggang Yuan, Tom Pickford, Jeff Tian, Christopher Ellingford, Ning Zhou, C. Bowen, C. Wan
Soft robots and devices exploit highly deformable materials that are capable of changes in shape to allow conformable physical contact for controlled manipulation. While soft robots are resilient to mechanical impact, they are susceptible to mechanical damage, such as tears and punctures. The development of self‐healing materials and actuators continues to attract increasing interest, in particular, with respect to integrating self‐healing polymers to create bioinspired soft self‐healing devices. Herein, a novel piezoelectric‐driven self‐healing leaf‐motion mimic actuator is designed by combining a thermoplastic methyl thioglycolate–modified styrene–butadiene–styrene (MGSBS) elastomer with a piezoelectric macrofiber composite (MFC) for self‐sensing applications. This article is the first demonstration of a self‐sensing and self‐healing actuator‐sensor system, which is driven by a piezoelectric actuator and can mimic leaf motion. The leaf‐motion actuator combines built‐in dynamic sensing and room‐temperature self‐healing capabilities to restore macroscale cutting damage with an intrinsically high bandwidth of up to 10 kHz. The feasibility and potential of the new actuator for use in complex soft autonomous systems are demonstrated. These new results help to address the emerging influence of self‐healing soft actuators and the challenges of sensing, actuation, and damage resistance in soft robotics.
{"title":"Piezoelectric‐Driven Self‐Sensing Leaf‐Mimic Actuator Enabled by Integration of a Self‐Healing Dielectric Elastomer and a Piezoelectric Composite","authors":"Min Pan, Chenggang Yuan, Tom Pickford, Jeff Tian, Christopher Ellingford, Ning Zhou, C. Bowen, C. Wan","doi":"10.1002/aisy.202000248","DOIUrl":"https://doi.org/10.1002/aisy.202000248","url":null,"abstract":"Soft robots and devices exploit highly deformable materials that are capable of changes in shape to allow conformable physical contact for controlled manipulation. While soft robots are resilient to mechanical impact, they are susceptible to mechanical damage, such as tears and punctures. The development of self‐healing materials and actuators continues to attract increasing interest, in particular, with respect to integrating self‐healing polymers to create bioinspired soft self‐healing devices. Herein, a novel piezoelectric‐driven self‐healing leaf‐motion mimic actuator is designed by combining a thermoplastic methyl thioglycolate–modified styrene–butadiene–styrene (MGSBS) elastomer with a piezoelectric macrofiber composite (MFC) for self‐sensing applications. This article is the first demonstration of a self‐sensing and self‐healing actuator‐sensor system, which is driven by a piezoelectric actuator and can mimic leaf motion. The leaf‐motion actuator combines built‐in dynamic sensing and room‐temperature self‐healing capabilities to restore macroscale cutting damage with an intrinsically high bandwidth of up to 10 kHz. The feasibility and potential of the new actuator for use in complex soft autonomous systems are demonstrated. These new results help to address the emerging influence of self‐healing soft actuators and the challenges of sensing, actuation, and damage resistance in soft robotics.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74021852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Minyung Song, K. Daniels, A. Kiani, Sahar Rashidnadimi, M. Dickey
Herein, this progress report summarizes recent studies of electrochemical oxidation to modulate the interfacial tension of gallium‐based alloys. These liquid alloys have the largest interfacial tension of any liquid at room temperature. The ability to modulate the tension offers the possibility to create forces that change the shape and position of small volumes of liquid metal. It has been known since the late 1800s that electrocapillarity—the use of potential to modulate the electric double layer on the surface of metals in electrolyte—lowers the interfacial tension of liquid metals. This phenomenon, however, can only achieve modest changes in interfacial tension since it is limited to potentials that avoid Faradaic reactions. A recent discovery suggests reactions driven by the electrochemical oxidation of gallium alloys cause the interfacial tension to decrease from ≈500 mN m−1 at 0 V to ≈0 mN m−1 at less than 1 V. This change in interfacial tension is reversible, controllable, and goes well‐beyond what is possible via conventional electrocapillarity or surfactants. This report aims to introduce beginners to this field and address misconceptions. The report discusses applications that utilize modulations in interfacial tension of liquid metal and concludes with remaining opportunities and challenges needing further investigation.
{"title":"Interfacial Tension Modulation of Liquid Metal via Electrochemical Oxidation","authors":"Minyung Song, K. Daniels, A. Kiani, Sahar Rashidnadimi, M. Dickey","doi":"10.1002/aisy.202100024","DOIUrl":"https://doi.org/10.1002/aisy.202100024","url":null,"abstract":"Herein, this progress report summarizes recent studies of electrochemical oxidation to modulate the interfacial tension of gallium‐based alloys. These liquid alloys have the largest interfacial tension of any liquid at room temperature. The ability to modulate the tension offers the possibility to create forces that change the shape and position of small volumes of liquid metal. It has been known since the late 1800s that electrocapillarity—the use of potential to modulate the electric double layer on the surface of metals in electrolyte—lowers the interfacial tension of liquid metals. This phenomenon, however, can only achieve modest changes in interfacial tension since it is limited to potentials that avoid Faradaic reactions. A recent discovery suggests reactions driven by the electrochemical oxidation of gallium alloys cause the interfacial tension to decrease from ≈500 mN m−1 at 0 V to ≈0 mN m−1 at less than 1 V. This change in interfacial tension is reversible, controllable, and goes well‐beyond what is possible via conventional electrocapillarity or surfactants. This report aims to introduce beginners to this field and address misconceptions. The report discusses applications that utilize modulations in interfacial tension of liquid metal and concludes with remaining opportunities and challenges needing further investigation.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82513749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding the external environment depends heavily on vision, audition, and touch. Like vision and audition, the human sense of touch is complex. Tactile perception is composed of multiple fundamental and physical experiences felt as changes in stiffness, texture, shape, size, temperature, and weight by the skin. While researchers and industries have made continuous efforts to abstract and recreate these haptic experiences, haptic devices are still limited in invoking intricate and rich sensations. Herein, the design, model, and experimental validation of a wearable skin‐like interface, able to recreate the roughness, shape, and size of a perceived object is presented; a platform for an interactive “physical” experience. The cogency of immersion through tactile feedback on moldable clay by the user response from the active haptic feedback, is examined. For the experimental test, a soft pneumatic actuator (SPA)‐skin interface (90 Hz bandwidth) with a complex actuation pattern is prototyped. The SPA‐skin's performance using three sets of simulated textures (<300 μm) and for reconstructing simulated contours (of a rectangle, circle, or trapezoid) in the virtual reality (VR) platform is investigated. The experimental results demonstrated for the first time how artificially created tactile feedback can indeed simulate physical interaction, with 83% average accuracy for contour reconstruction.
{"title":"Soft Touch using Soft Pneumatic Actuator–Skin as a Wearable Haptic Feedback Device","authors":"H. Sonar, Jian-Lin Huang, J. Paik","doi":"10.1002/aisy.202000168","DOIUrl":"https://doi.org/10.1002/aisy.202000168","url":null,"abstract":"Understanding the external environment depends heavily on vision, audition, and touch. Like vision and audition, the human sense of touch is complex. Tactile perception is composed of multiple fundamental and physical experiences felt as changes in stiffness, texture, shape, size, temperature, and weight by the skin. While researchers and industries have made continuous efforts to abstract and recreate these haptic experiences, haptic devices are still limited in invoking intricate and rich sensations. Herein, the design, model, and experimental validation of a wearable skin‐like interface, able to recreate the roughness, shape, and size of a perceived object is presented; a platform for an interactive “physical” experience. The cogency of immersion through tactile feedback on moldable clay by the user response from the active haptic feedback, is examined. For the experimental test, a soft pneumatic actuator (SPA)‐skin interface (90 Hz bandwidth) with a complex actuation pattern is prototyped. The SPA‐skin's performance using three sets of simulated textures (<300 μm) and for reconstructing simulated contours (of a rectangle, circle, or trapezoid) in the virtual reality (VR) platform is investigated. The experimental results demonstrated for the first time how artificially created tactile feedback can indeed simulate physical interaction, with 83% average accuracy for contour reconstruction.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83373854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：