Additive manufacture of ultrasoft bioinspired metamaterials

超材料 动载荷 动态范围压缩 航空航天 材料科学 设计工具 智能材料 机械工程 计算机科学 纳米技术 工程类 航空航天工程 复合材料 光电子学
作者
Zhenyang Gao,Pengyuan Ren,Hongze Wang,Zijue Tang,Yi Wu,Haowei Wang
出处
期刊:International Journal of Machine Tools & Manufacture [Elsevier BV]
卷期号:195: 104101-104101 被引量:21
标识
DOI:10.1016/j.ijmachtools.2023.104101
摘要

The dynamic loading behavior of materials plays a vital role in various engineering applications, such as aerospace protective components, armor, marine infrastructures, and automotive crash safety. The advent of additive manufacturing technologies has enabled the design of metamaterials that exhibit exceptional mechanical performance and artificially engineered properties not found in nature. However, fabricating ideal materials that resist dynamic loading is challenging because of the complexity of dynamic mechanical processes and varying requirements across different applications. In this study, a novel hierarchical design is proposed that combines natural fiber-inspired frameworks with graphene-inspired parent structures. This design aims to produce metamaterials, with characteristics such as reduced dynamic compressive strength, high energy absorption, and programmable dynamic loading, via advanced manufacturing technologies. An additive-manufacturing-oriented digital design approach and machine learning techniques were employed to engineer the dynamic loading performance of graphene-inspired metamaterials using the bonding principles inspired by natural fibers, to facilitate the design of next-generation metamaterial for advanced manufacturing. Experimental results illustrate the significant improvements achieved with our metamaterials compared to their existing counterparts. These improvements include a decrease in dynamic compressive strength of up to 86 %, while maintaining a remarkable 682 % enhancement in energy absorption during dynamic compressions, with a 42 % reduction in the energy decay rate. A compositional design strategy and programmable dynamic compression curve methodology is proposed that enable the tailored optimization of dynamic loading behaviors without modifying the base topology of metamaterials. This research offers a promising pathway for the development of next-generation materials, engineered to withstand dynamic loadings with intelligent and programmable performances suitable for aerospace, defense, and other high-value applications. By leveraging the advantages of natural fiber-inspired structures and graphene-inspired metamaterials, this work contributes to the advancement of materials with tailored resistance to dynamic loading and opens new possibilities for intelligent dynamic loading performance.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
leinuo077完成签到,获得积分10
刚刚
西瓜完成签到,获得积分10
刚刚
鲤鱼小蕾完成签到,获得积分10
1秒前
YAOYAO完成签到,获得积分0
2秒前
隐形曼青应助虚幻妙柏采纳,获得10
2秒前
Mintz完成签到,获得积分10
2秒前
123567完成签到 ,获得积分10
2秒前
i羽翼深蓝i完成签到,获得积分10
2秒前
现代的代丝完成签到,获得积分10
2秒前
小蘑菇应助拓跋灭龙采纳,获得10
2秒前
Ll完成签到,获得积分10
2秒前
Luffy完成签到,获得积分10
3秒前
调皮又蓝完成签到,获得积分10
4秒前
坦率的谷雪完成签到,获得积分10
4秒前
小苏打完成签到,获得积分10
4秒前
深情安青应助kyle采纳,获得10
4秒前
酷波er应助kyle采纳,获得30
4秒前
4秒前
4秒前
5秒前
FYX完成签到,获得积分10
5秒前
CO2完成签到,获得积分10
5秒前
小黑完成签到,获得积分10
6秒前
Zzx完成签到,获得积分10
6秒前
壮观听芹完成签到,获得积分10
6秒前
萝卜不困完成签到,获得积分10
6秒前
eye完成签到,获得积分10
6秒前
hongtaoli2024完成签到 ,获得积分10
7秒前
7秒前
HoldenX完成签到,获得积分10
7秒前
隐形曼青应助Likz采纳,获得10
9秒前
狄百招完成签到,获得积分10
9秒前
9秒前
wanci应助HandsomeBoy采纳,获得10
9秒前
9秒前
大气指甲油完成签到,获得积分10
9秒前
CHENDQ完成签到,获得积分10
9秒前
9秒前
10秒前
刚果王子完成签到,获得积分10
10秒前
高分求助中
Clinical Epidemiology: The Essentials, 6e 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Graphene Handbook (2019 Edition) 800
Adhesion Science: Principles & Practice 800
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
久松真一著作集〈第5巻〉禅と芸術 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6555301
求助须知:如何正确求助?哪些是违规求助? 8339577
关于积分的说明 17866208
捐赠科研通 5672857
什么是DOI,文献DOI怎么找? 2940215
邀请新用户注册赠送积分活动 1916123
关于科研通互助平台的介绍 1786088