|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Significant Reduction of Interfacial Thermal Resistance and Phonon Scattering in Graphene/Polyimide Thermally Conductive Composite Films for Thermal Management显示文摘The developing flexible electronic equipment are greatly affected by the rapid accumulation of heat,which is urgent to be solved by thermally conductive polymer composite films.However,the interfacial thermal resistance(ITR)and the phonon scattering at the interfaces are the main bottlenecks limiting the rapid and efficient improvement of thermal conductivity coefficients(λ)of the polymer composite films.Moreover,few researches were focused on characterizing ITR and phonon scattering in thermally conductive polymer composite films.In this paper,graphene oxide(GO)was aminated(NH_(2)-GO)and reduced(NH_(2)-rGO),then NH_(2)-rGO/polyimide(NH_(2)-rGO/PI)thermally conductive composite films were fabricated.Raman spectroscopy was utilized to innovatively characterize phonon scattering and ITR at the interfaces in NH_(2)-rGO/PI thermally conductive composite films,revealing the interfacial thermal conduction mechanism,proving that the amination optimized the interfaces between NH_(2)-rGO and PI,reduced phonon scattering and ITR,and ultimately improved the interfacial thermal conduction.The in-planeλ(λ∥)and through-planeλ(λ_(⊥))of 15 wt%NH_(2)-rGO/PI thermally conductive composite films at room temperature were,respectively,7.13 W/mK and 0.74 W/mK,8.2 timesλ∥(0.87 W/mK)and 3.5 timesλ_(⊥)(0.21 W/mK)of pure PI film,also significantly higher thanλ∥(5.50 W/mK)andλ_(⊥)(0.62 W/mK)of 15 wt%rGO/PI thermally conductive composite films.Calculation based on the effective medium theory model proved that ITR was reduced via the amination of rGO.Infrared thermal imaging and finite element simulation showed that NH_(2)-rGO/PI thermally conductive composite films obtained excellent heat dissipation and efficient thermal management capabilities on the light-emitting diodes bulbs,5G high-power chips,and other electronic equipment,which are easy to generate heat severely. | Kunpeng Ruan Yongqiang Guo Chuyao Lu Xuetao Shi Tengbo Ma Yali Zhang Jie Kong Junwei Gu | 2021 | Research2021，，1： | 14 |
| 2 | Next-Generation Prosthetic Hand:from Biomimetic to Biorealistic显示文摘Integrating a prosthetic hand to amputees with seamless neural compatibility presents a grand challenge to neuroscientists and neural engineers for more than half century.Mimicking anatomical structure or appearance of human hand does not lead to improved neural connectivity to the sensorimotor system of amputees.The functions of modern prosthetic hands do not match the dexterity of human hand due primarily to lack of sensory awareness and compliant actuation.Lately,progress in restoring sensory feedback has marked a significant step forward in improving neural continuity of sensory information from prosthetic hands to amputees.However,little effort has been made to replicate the compliant property of biological muscle when actuating prosthetic hands.Furthermore,a full-fledged biorealistic approach to designing prosthetic hands has not been contemplated in neuroprosthetic research.In this perspective article,we advance a novel view that a prosthetic hand can be integrated harmoniously with amputees only if neural compatibility to the sensorimotor system is achieved.Our ongoing research supports that the next-generation prosthetic hand must incorporate biologically realistic actuation,sensing,and reflex functions in order to fully attain neural compatibility. | Ning Lan Manzhao Hao Chuanxin MNiu He Cui Yu Wang Ting Zhang Peng Fang Chih-hong Chou | 2021 | Research2021，，1： | 1 |
| 3 | Highly Robust and Wearable Facial Expression Recognition via Deep-Learning-Assisted, Soft Epidermal Electronics显示文摘The facial expressions are a mirror of the elusive emotion hidden in the mind,and thus,capturing expressions is a crucial way of merging the inward world and virtual world.However,typical facial expression recognition(FER)systems are restricted by environments where faces must be clearly seen for computer vision,or rigid devices that are not suitable for the time-dynamic,curvilinear faces.Here,we present a robust,highly wearable FER system that is based on deep-learning-assisted,soft epidermal electronics.The epidermal electronics that can fully conform on faces enable high-fidelity biosignal acquisition without hindering spontaneous facial expressions,releasing the constraint of movement,space,and light.The deep learning method can significantly enhance the recognition accuracy of facial expression types and intensities based on a small sample.The proposed wearable FER system is superior for wide applicability and high accuracy.The FER system is suitable for the individual and shows essential robustness to different light,occlusion,and various face poses.It is totally different from but complementary to the computer vision technology that is merely suitable for simultaneous FER of multiple individuals in a specific place.This wearable FER system is successfully applied to human-avatar emotion interaction and verbal communication disambiguation in a real-life environment,enabling promising human-computer interaction applications. | Meiqi Zhuang Lang Yin Youhua Wang Yunzhao Bai Jian Zhan Chao Hou Liting Yin Zhangyu Xu Xiaohui Tan YongAn Huang | 2022 | Research2022，，1： | 0 |
| 4 | Highly Robust and Wearable Facial Expression Recognition via Deep-Learning-Assisted,Soft Epidermal Electronics显示文摘The facial expressions are a mirror of the elusive emotion hidden in the mind,and thus,capturing expressions is a crucial way of merging the inward world and virtual world.However,typical facial expression recognition(FER)systems are restricted by environments where faces must be clearly seen for computer vision,or rigid devices that are not suitable for the time-dynamic,curvilinear faces.Here,we present a robust,highly wearable FER system that is based on deep-learning-assisted,soft epidermal electronics.The epidermal electronics that can fully conform on faces enable high-fidelity biosignal acquisition without hindering spontaneous facial expressions,releasing the constraint of movement,space,and light.The deep learning method can significantly enhance the recognition accuracy of facial expression types and intensities based on a small sample.The proposed wearable FER system is superior for wide applicability and high accuracy.The FER system is suitable for the individual and shows essential robustness to different light,occlusion,and various face poses.It is totally different from but complementary to the computer vision technology that is merely suitable for simultaneous FER of multiple individuals in a specific place.This wearable FER system is successfully applied to human-avatar emotion interaction and verbal communication disambiguation in a real-life environment,enabling promising human-computer interaction applications. | Meiqi Zhuang Lang Yin Youhua Wang Yunzhao Bai Jian Zhan Chao Hou Liting Yin Zhangyu Xu Xiaohui Tan YongAn Huang | 2021 | Research2021，，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员