引用本文:葛世荣.智能表面工程[J].中国表面工程,2024,37(1):1~17
GE Shirong.Intelligent Surface Engineering[J].China Surface Engineering,2024,37(1):1~17
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智能表面工程
葛世荣1,2
1.中国矿业大学(北京)机电与信息工程学院 北京 100083;2.煤矿智能化与机器人创新应用应急管理部重点实验室 北京 100083
摘要:
表面工程自其诞生以来,经历了从传统表面工程向复合表面工程、纳米表面工程及表面工程自动化的发展,正在信息技术、生物技术、纳米科技等前沿领域中萌生。随着智能时代的来临,智能表面工程应运而生。智能表面工程是对摩擦表面赋予智能调控性能,使之具有自感知、自适应、自愈合能力,从而实现摩擦学行为的智能控制。介绍皮肤自感知、关节自感知、消化道自适应和表皮自愈合等人体表面智能性,触屏自感知表面、损伤自感知表面、摩擦自感知表面和触压自感知表面等自感知表面创新,自适应表面变色、自适应调光涂层、自适应疏水涂层、自清洁除尘表面、自适应隐身表面、自硬化耐磨表面和自减摩超滑表面等自适应表面创新,植物自愈合、自愈合聚合物膜、自愈合导电皮肤、自愈合离子皮肤、自修复防腐涂层、自愈合蛋白质体、自愈合关节软骨和自愈合磨损划痕等自愈合表面创新。以往的表面工程是对材料表面强化以提高其物理、化学、力学性能的技术和方法,而智能表面工程则是赋予材料表面自润滑、自抗磨、自耐蚀、自修复等功能的智能表面技术和方法。未来的智能装备离不开摩擦智能,摩擦智能必须有智能表面。智能表面制造须要深入研究仿生科学与表面工程技术交叉融合,因此在摩擦学、仿生学、低碳学等领域尚有许多需要探索的关键理论和技术问题,一旦取得突破,将促进智能表面工程领域的显著进步。可以预见,摩擦智能表面工程将支撑智能装备制造技术的发展,创造出更快、更强、更稳的机械系统;仿生智能表面工程将使机器人更智能地实现对自身运动的感觉、对空间的感知和对外部刺激的反应;低碳智能表面工程将降低摩擦系统能耗、减少建筑领域碳排放,从而使摩擦学及表面工程研究与人类命运共同体紧密结合在一起。
关键词:  智能表面工程  自感知  自适应  自愈合  智能控制
DOI:10.11933/j.issn.1007-9289.20231009001
分类号:TG156;TB114
基金项目:
Intelligent Surface Engineering
GE Shirong1,2
1.School of Mechanical Electronic & Information Engineering, China University of Mining andTechnology-Beijing, Beijing 100083 , China;2.Key Laboratory of Intelligent Mining and Robotics, Ministry of Emergency Management,Beijing 100083 , China
Abstract:
Since it was first reported, surface engineering has evolved from traditional surface engineering to composite surface engineering, nano-surface engineering, and surface engineering automation, and is now finding applications in frontier fields like information technology, biotechnology, and nano-technology. The advent of the intelligent era gave rise to intelligent surface engineering, which is aimed at endowing surfaces with intelligent control capabilities, allowing them to be self-sensing, self-adaptive, and self-healing, thereby achieving smart control over tribological behaviors. In this paper, the surface intelligence of the human body is introduced, including skin self-perception, joint self-perception, digestive tract self-adaptation, and epidermis self-healing. Innovations in self-sensing surfaces, such as touch screen self-sensing surfaces, damage self-sensing surfaces, friction self-sensing surfaces, and touch pressure self-sensing surfaces, are presented. Introductions to self-adaptive surface innovations are provided, which include self-adaptive surface discoloration, self-adaptive dimming coatings, self-adaptive hydrophobic coatings, self-cleaning dust removal surfaces, self-adaptive stealth surfaces, self-hardening wear-resistant surfaces, and self-friction reducing superlubricity surfaces. Self-healing surface innovations, such as plant self-healing, self-healing polymer films, self-healing conductive skins, self-healing ionic skins, self-healing anticorrosive coatings, self-healing proteomes, self-healing articular cartilages, and self-healing wear scratches, are discussed. The intersection and integration of bionic science and surface engineering technology should be thoroughly examined in intelligent surface manufacturing. In tribology, bionics, and low carbon science, many key theoretical and technical problems are yet to be explored. A breakthrough, when achieved, is expected to promote the significant advancement of intelligent surface engineering. It is anticipated that friction intelligent surface engineering will underpin the progress of intelligent equipment manufacturing technology and pave the way for a faster, stronger, and more stable mechanical system. Through bionic intelligent surface engineering, robots are expected to gain a more intelligent sense of their own movement, spatial perception, and responsiveness to external stimuli. Low-carbon intelligent surface engineering is predicted to decrease the energy consumption of the friction system and carbon emissions in the construction sector, thus intertwining tribology and surface engineering research with the responsibility of the community of shared future for mankind.
Key words:  intelligent surface engineering  self-sensing  self-adaptive  self-healing  intelligent control
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