{"title":"Approach on the vibration damping and energy absorption through electrorheological/magnetorheological effects","authors":"Hang Li , Tianyu Gao , Meng Wang , Wenling Zhang","doi":"10.1016/j.susmat.2025.e01401","DOIUrl":null,"url":null,"abstract":"<div><div>Large-scale industrial equipment, aerospace vehicles, and military hardware are inevitably endured random vibrations or strong impact. Recently, intelligent soft matter has shown great potential in the field of shock and vibration protection owing to their tunable mechanical properties. Nevertheless, the softness of intelligent soft matter limits their application under high impact loads. Mechanical metamaterial is an innovative approach to develop high-overload impact buffering protective materials in extreme conditions. To monitor the vibrational information in real time is essential for adaptive suppression and control of vibration. Recently, self-powered triboelectric sensor provides a resilient solution to avoid damage of external batteries power under strong impact conditions, making them suit able for detecting intense shocks and vibrations. This review begins with the vibration suppression principles of intelligent soft matter, focusing particularly on electro/magnetorheological (ER/MR) material and shear thickening gel (STG). It summarizes the latest research on typical intelligent soft matter in shock and vibration reduction. Subsequently, the discussion highlights recent advances in mechanical metamaterial structures, exploring how structural design affects protective performance. The paper then outlines the application of TENGs as sensors in intelligent protective measures. Finally, the challenges and limitations faced by current intelligent protection has addressed and an efficient solution is proposed using machine learning to derive the nonlinear relationships of protective facilities, aiming to expedite the evolution towards smarter protective technologies, thereby enhancing the effectiveness and reliability of such systems in safeguarding human life and property.</div></div>","PeriodicalId":22097,"journal":{"name":"Sustainable Materials and Technologies","volume":"44 ","pages":"Article e01401"},"PeriodicalIF":8.6000,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Materials and Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214993725001691","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Large-scale industrial equipment, aerospace vehicles, and military hardware are inevitably endured random vibrations or strong impact. Recently, intelligent soft matter has shown great potential in the field of shock and vibration protection owing to their tunable mechanical properties. Nevertheless, the softness of intelligent soft matter limits their application under high impact loads. Mechanical metamaterial is an innovative approach to develop high-overload impact buffering protective materials in extreme conditions. To monitor the vibrational information in real time is essential for adaptive suppression and control of vibration. Recently, self-powered triboelectric sensor provides a resilient solution to avoid damage of external batteries power under strong impact conditions, making them suit able for detecting intense shocks and vibrations. This review begins with the vibration suppression principles of intelligent soft matter, focusing particularly on electro/magnetorheological (ER/MR) material and shear thickening gel (STG). It summarizes the latest research on typical intelligent soft matter in shock and vibration reduction. Subsequently, the discussion highlights recent advances in mechanical metamaterial structures, exploring how structural design affects protective performance. The paper then outlines the application of TENGs as sensors in intelligent protective measures. Finally, the challenges and limitations faced by current intelligent protection has addressed and an efficient solution is proposed using machine learning to derive the nonlinear relationships of protective facilities, aiming to expedite the evolution towards smarter protective technologies, thereby enhancing the effectiveness and reliability of such systems in safeguarding human life and property.
期刊介绍:
Sustainable Materials and Technologies (SM&T), an international, cross-disciplinary, fully open access journal published by Elsevier, focuses on original full-length research articles and reviews. It covers applied or fundamental science of nano-, micro-, meso-, and macro-scale aspects of materials and technologies for sustainable development. SM&T gives special attention to contributions that bridge the knowledge gap between materials and system designs.