Retinomorphic X-ray detection using perovskite with hydrion-conductive organic cations

钙钛矿(结构) X射线 材料科学 导电体 化学 结晶学 物理 光学 复合材料
作者
Hang Yin,Jincong Pang,Shan Zhao,Haodi Wu,Zihao Song,Xing Li,Zhiping Zheng,Ling Xu,Jiang Tang,Guangda Niu
出处
期刊:The Innovation [Elsevier]
卷期号:5 (4): 100654-100654 被引量:5
标识
DOI:10.1016/j.xinn.2024.100654
摘要

X-ray detection is crucial across various sectors, but traditional techniques face challenges such as inefficient data transmission, redundant sensing, high power consumption, and complexity. The innovative idea of a retinomorphic X-ray detector shows great potential. However, its implementation has been hindered by the absence of active layers capable of both detecting X-rays and serving as memory storage. In response to this critical gap, our study integrates hybrid perovskite with hydrion-conductive organic cations to develop a groundbreaking retinomorphic X-ray detector. This novel device stands at the nexus of technological innovation, utilizing X-ray detection, memory, and preprocessing capabilities within a single hardware platform. The core mechanism underlying this innovation lies in the transport of electrons and holes within the metal halide octahedral frameworks, enabling precise X-ray detection. Concurrently, the hydrion movement through organic cations endows the device with short-term resistive memory, facilitating rapid data processing and retrieval. Notably, our retinomorphic X-ray detector boasts an array of formidable features, including reconfigurable short-term memory, a linear response curve, and an extended retention time. In practical terms, this translates into the efficient capture of motion projections with minimal redundant data, achieving a compression ratio of 18.06% and an impressive recognition accuracy of up to 98.6%. In essence, our prototype represents a paradigm shift in X-ray detection technology. With its transformative capabilities, this retinomorphic hardware is poised to revolutionize the existing X-ray detection landscape.
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
王二发布了新的文献求助10
刚刚
AB完成签到,获得积分10
刚刚
YixiaoWang发布了新的文献求助10
1秒前
幸福书琴完成签到,获得积分10
2秒前
迅速思萱完成签到 ,获得积分10
4秒前
zhangxr完成签到 ,获得积分10
5秒前
darkpigx发布了新的文献求助10
6秒前
科研通AI5应助朱问安采纳,获得10
7秒前
Niar完成签到 ,获得积分10
7秒前
恢复出厂设置完成签到 ,获得积分10
7秒前
王宇杰完成签到,获得积分10
8秒前
森花完成签到,获得积分10
8秒前
harden9159完成签到,获得积分10
9秒前
汉堡包应助唠叨的如冬采纳,获得10
9秒前
汉堡包应助Duke采纳,获得10
10秒前
玔堷应助鱼雷采纳,获得10
11秒前
11秒前
Xin完成签到,获得积分10
12秒前
阳佟冬卉完成签到,获得积分10
12秒前
小二郎应助乙酸乙酯采纳,获得10
13秒前
13秒前
13秒前
Dream完成签到 ,获得积分10
15秒前
CQ完成签到 ,获得积分10
15秒前
15秒前
木木发布了新的文献求助10
17秒前
17秒前
18秒前
LXl发布了新的文献求助10
19秒前
anan完成签到 ,获得积分10
19秒前
科研之光发布了新的文献求助10
20秒前
20秒前
乐乐应助笑点低诗双采纳,获得10
24秒前
25秒前
lbyscu完成签到 ,获得积分10
25秒前
谭平发布了新的文献求助10
26秒前
火星仙人掌完成签到 ,获得积分10
26秒前
27秒前
27秒前
李健的小迷弟应助geoman采纳,获得10
29秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Structural Load Modelling and Combination for Performance and Safety Evaluation 1000
Conference Record, IAS Annual Meeting 1977 820
England and the Discovery of America, 1481-1620 600
電気学会論文誌D(産業応用部門誌), 141 巻, 11 号 510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3572102
求助须知:如何正确求助?哪些是违规求助? 3142380
关于积分的说明 9447398
捐赠科研通 2843806
什么是DOI,文献DOI怎么找? 1563098
邀请新用户注册赠送积分活动 731575
科研通“疑难数据库(出版商)”最低求助积分说明 718603