Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this uniq...Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.展开更多
Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common d...Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.展开更多
Large volumetric expansion of cathode hosts and sluggish transport kinetics in the cathode–electrolyte interface,as well as dendrite growth and hydrogen evolution at Zn anode side are considered as the system problem...Large volumetric expansion of cathode hosts and sluggish transport kinetics in the cathode–electrolyte interface,as well as dendrite growth and hydrogen evolution at Zn anode side are considered as the system problems that cause the electrochemical failure of aqueous Zn-vanadium oxide battery.In this work,a multifunctional anti-proton electrolyte was proposed to synchronously solve all those issues.Theoretical and experimental studies confirm that PEG 400 additive can regulate the Zn^(2+) solvation structure and inhibit the ionization of free water molecules of the electrolyte.Then,smaller lattice expansion of vanadium oxide hosts and less associated by-product formation can be realized by using such electrolyte.Besides,such electrolyte is also beneficial to guide the uniform Zn deposition and suppress the side reaction of hydrogen evolution.Owing to the integrated synergetic modifica-tion,a high-rate and ultrastable aqueous Zn-V_(2)O_(3)/C battery can be constructed,which can remain a specific capacity of 222.8 m Ah g^(-1)after 6000 cycles at 5 A g^(-1),and 121.8 m Ah g^(-1) even after 18,000 cycles at 20 A g^(-1),respectively.Such“all-in-one”solution based on the electrolyte design provides a new strategy for developing high-performance aqueous Zn-ion battery.展开更多
Human–machine interactions using deep-learning methods are important in the research of virtual reality,augmented reality,and metaverse.Such research remains challenging as current interactive sensing interfaces for ...Human–machine interactions using deep-learning methods are important in the research of virtual reality,augmented reality,and metaverse.Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes,signal crosstalk,propagation delay,and demanding configuration requirements.Here,an all-inone multipoint touch sensor(AIOM touch sensor)with only two electrodes is reported.The AIOM touch sensor is efficiently constructed by gradient resistance elements,which can highly adapt to diverse application-dependent configurations.Combined with deep learning method,the AIOM touch sensor can be utilized to recognize,learn,and memorize human–machine interactions.A biometric verification system is built based on the AIOM touch sensor,which achieves a high identification accuracy of over 98%and offers a promising hybrid cyber security against password leaking.Diversiform human–machine interactions,including freely playing piano music and programmatically controlling a drone,demonstrate the high stability,rapid response time,and excellent spatiotemporally dynamic resolution of the AIOM touch sensor,which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.展开更多
The absence of tactile perception limits the dexterity of a prosthetic hand and its acceptance by amputees.Recreating the sensing properties of the skin using a flexible tactile sensor could have profound implications...The absence of tactile perception limits the dexterity of a prosthetic hand and its acceptance by amputees.Recreating the sensing properties of the skin using a flexible tactile sensor could have profound implications for prosthetics,whereas existing tactile sensors often have limited functionality with cross-interference.In this study,we propose a machine-learning-assisted multifunctional tactile sensor for smart prosthetics,providing a human-like tactile sensing approach for amputations.This flexible sensor is based on a poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)-melamine sponge,which enables the detection of force and temperature with low cross-coupling owing to two separate sensing mechanisms:the open-circuit voltage of the sensor as a force-insensitive intrinsic variable to measure the absolute temperature and the resistance as a temperature-insensitive extrinsic variable to measure force.Furthermore,by analyzing the unsteady heat conduction and characterizing it using real-time thermal imaging,we demonstrated that the process of open-circuit voltage variation resulting from the unsteady heat conduction is closely correlated with the heatconducting capabilities of materials,which can be utilized to discriminate between substances.Assisted by the decision tree algorithm,the device is endowed with thermal conductivity sensing ability,which allows it to identify 10 types of substances with an accuracy of 94.7%.Furthermore,an individual wearing an advanced myoelectric prosthesis equipped with the above sensor can sense pressure,temperature,and recognize different materials.We demonstrated that our multifunctional tactile sensor provides a new strategy to help amputees feel force,temperature and identify the material of objects without the aid of vision.展开更多
Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. I...Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.展开更多
基金the National Natural Science Foundation of China(Grant No.52072041)the Beijing Natural Science Foundation(Grant No.JQ21007)+2 种基金the University of Chinese Academy of Sciences(Grant No.Y8540XX2D2)the Robotics Rhino-Bird Focused Research Project(No.2020-01-002)the Tencent Robotics X Laboratory.
文摘Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.
基金supported by National Natural Science Foundation of China(52202117,52232006,52072029,and 12102256)Collaborative Innovation Platform Project of Fu-Xia-Quan National Independent Innovation Demonstration Zone(3502ZCQXT2022005)+3 种基金Natural Science Foundation of Fujian Province of China(2022J01065)State Key Lab of Advanced Metals and Materials(2022-Z09)Fundamental Research Funds for the Central Universities(20720220075)the Ministry of Education,Singapore,under its MOE ARF Tier 2(MOE2019-T2-2-179).
文摘Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.
基金financially supported by the National Natural Science Foundation of China(Nos.22178221,51774203)Shenzhen Science and Technology Program(Nos.JCYJ20200109105805902,JCYJ20200109105801725)+1 种基金Natural Science Foundation of Guangdong Province(Nos.2021A1515110751)China Postdoctoral Science Foundation(Nos.2021M702255)。
文摘Large volumetric expansion of cathode hosts and sluggish transport kinetics in the cathode–electrolyte interface,as well as dendrite growth and hydrogen evolution at Zn anode side are considered as the system problems that cause the electrochemical failure of aqueous Zn-vanadium oxide battery.In this work,a multifunctional anti-proton electrolyte was proposed to synchronously solve all those issues.Theoretical and experimental studies confirm that PEG 400 additive can regulate the Zn^(2+) solvation structure and inhibit the ionization of free water molecules of the electrolyte.Then,smaller lattice expansion of vanadium oxide hosts and less associated by-product formation can be realized by using such electrolyte.Besides,such electrolyte is also beneficial to guide the uniform Zn deposition and suppress the side reaction of hydrogen evolution.Owing to the integrated synergetic modifica-tion,a high-rate and ultrastable aqueous Zn-V_(2)O_(3)/C battery can be constructed,which can remain a specific capacity of 222.8 m Ah g^(-1)after 6000 cycles at 5 A g^(-1),and 121.8 m Ah g^(-1) even after 18,000 cycles at 20 A g^(-1),respectively.Such“all-in-one”solution based on the electrolyte design provides a new strategy for developing high-performance aqueous Zn-ion battery.
基金supported by National Natural Science Foundation of China under Grants (U1805261 and 22161142024)A~*STAR SERC AME Programmatic Fund (A18A7b0058)
文摘Human–machine interactions using deep-learning methods are important in the research of virtual reality,augmented reality,and metaverse.Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes,signal crosstalk,propagation delay,and demanding configuration requirements.Here,an all-inone multipoint touch sensor(AIOM touch sensor)with only two electrodes is reported.The AIOM touch sensor is efficiently constructed by gradient resistance elements,which can highly adapt to diverse application-dependent configurations.Combined with deep learning method,the AIOM touch sensor can be utilized to recognize,learn,and memorize human–machine interactions.A biometric verification system is built based on the AIOM touch sensor,which achieves a high identification accuracy of over 98%and offers a promising hybrid cyber security against password leaking.Diversiform human–machine interactions,including freely playing piano music and programmatically controlling a drone,demonstrate the high stability,rapid response time,and excellent spatiotemporally dynamic resolution of the AIOM touch sensor,which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.
基金the funding support from the National Key R&D Program of China(2020YFB2008501)the National Science Fund for Distinguished Young Scholars of China(62125112)+4 种基金the National Natural Science Foundation of China(62071462,62071463)the Youth Promotion Association of Chinese Academy of Sciences(2020320)the Jiangxi Provincial Natural Science Foundation(20224ACB212001)the Foundation Research Project of Jiangsu Province(BK20201195)the Suzhou Key Industrial Technology Innovation Project(SYG202029).
文摘The absence of tactile perception limits the dexterity of a prosthetic hand and its acceptance by amputees.Recreating the sensing properties of the skin using a flexible tactile sensor could have profound implications for prosthetics,whereas existing tactile sensors often have limited functionality with cross-interference.In this study,we propose a machine-learning-assisted multifunctional tactile sensor for smart prosthetics,providing a human-like tactile sensing approach for amputations.This flexible sensor is based on a poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)-melamine sponge,which enables the detection of force and temperature with low cross-coupling owing to two separate sensing mechanisms:the open-circuit voltage of the sensor as a force-insensitive intrinsic variable to measure the absolute temperature and the resistance as a temperature-insensitive extrinsic variable to measure force.Furthermore,by analyzing the unsteady heat conduction and characterizing it using real-time thermal imaging,we demonstrated that the process of open-circuit voltage variation resulting from the unsteady heat conduction is closely correlated with the heatconducting capabilities of materials,which can be utilized to discriminate between substances.Assisted by the decision tree algorithm,the device is endowed with thermal conductivity sensing ability,which allows it to identify 10 types of substances with an accuracy of 94.7%.Furthermore,an individual wearing an advanced myoelectric prosthesis equipped with the above sensor can sense pressure,temperature,and recognize different materials.We demonstrated that our multifunctional tactile sensor provides a new strategy to help amputees feel force,temperature and identify the material of objects without the aid of vision.
基金the National Natural Science Foundation of China (Nos. 60772007 and 60672008)China Postdoctoral Sci-ence Foundation (No. 20070410258)
文摘Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.
