基于CsPbBr3-MXene纳米结构的高线性度突触光电晶体管用于图像分类和边缘检测

扫码查看

原文链接

NETL
NSTL
万方数据

中文摘要：人工光突触为克服数据存储和处理中的冯诺依曼瓶颈,提供了一种有效的解决方案.人工光突触通过消除带宽连接密度的权衡和低功耗,展现了其相较于电突触的优势.钙钛矿量子点由于其易于合成和良好的光电性能,在人工光突触中引起了广泛的关注.然而,有限的载流子迁移率和非线性性能阻碍了它在神经形态中的应用.本研究提出了一种吸附CsPbBr3的MXene纳米结构(CsPbBr3-MXene),即在MXene纳米片上原位生长CsPbBr3量子点,并将其作为光电突触晶体管的吸光层,CsPbBr3和MXene形成的异质结构增强了光电流的产生.在相同的光脉冲刺激下,与仅含CsPbBr3的突触晶体管相比,CsPbBr3-MXene突触晶体管的兴奋性突触后电流(EPSC)提高了24.6％.经过计算和比较,其线性度有了明显的改善(从4.586到1.099);此外,其对手写数字分类的识别准确率也显著提高(从86.13％到92.05％);边缘检测的F1分数也有所提高(从0.8165到0.9065),更加接近于1.这些提升表明这项工作将有助于神经计算领域的进一步发展.

外文标题：A high-linearity synaptic phototransistor based on CsPbBr3-attached MXene nanostructures for image classification and edge detection tasks

外文摘要：Artificial photonic synapses offer an efficient solution for overcoming the von Neumann bottleneck in data storage and processing,providing advantages over electrical synapses by eliminating the bandwidth-connection-density tradeoff and exhibiting low power consumption.Perovskite quantum dots(QDs)have garnered significant attention in artificial photonic synapses due to their facile synthesis and favorable optoelectronic properties.However,challenges such as limited carrier mobility and nonlinearity impede their performance in neuromorphic applications.In this study,CsPbBr3-attached MXene nanostructures(CsPbBr3-MXene),in-situ growth of CsPbBr3 QDs on MXene nanosheets,were proposed as the light-absorbing layer of a synaptic photo-transistor.The heterostructure formed by CsPbBr3 and MXene enhances photocurrent generation.Comparative ana-lyses between CsPbBr3-MXene synapse transistor and that containing only CsPbBr3 revealed a 24.6％higher excitatory postsynaptic current(EPSC)in the CsPbBr3-MXene one under identical light pulse stimulation.Following calculations and comparisons,the linearity exhibited significant improvement,decreasing from 4.586 to 1.099.Furthermore,the recognition accuracy in handwritten digit classification notably increased,rising from 86.13％to 92.05％.Moreover,the Fl score in edge detection had improvement,advancing from 0.8165 to 0.9065,approaching closer to 1.These improvements have demon-strated substantial assistance in the field of neural computing.

外文关键词：

in-situ growthCsPbBr3-attached MXenesynaptic phototransistorpattern recognition accuracyimage preproces-sing

作者：

代岩、陈耿旭、黄伟龙、许晨晖、刘常飞、黄紫玉、郭太良、陈惠鹏

展开 >

作者单位：

National & Local United Engineering Laboratory of Flat Panel Display Technology,Institute of Optoelectronic Display,College of Physics and Information Engineering,Fuzhou University,Fuzhou 350108,China

Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China,Fuzhou 350100,China

关键词：

in-situ growth CsPbBr3-attached MXene synaptic phototransistor pattern recognition accuracy image preproces-sing

基金：

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Key Research and Development Program of ChinaNational Key Research and Development Program of ChinaNatural Science Foundation of Fujian ProvinceNatural Science Foundation of Fujian ProvinceFujian Science & Technology Innovation Laboratory for Optoelectronic Information of ChinaFujian Science & Technology Innovation Laboratory for Optoelectronic Information of ChinaCooperation Project of Tianjin University & Fuzhou University Independent Innovation Fund

项目编号：

6227403562374033U21A20497619740292022YFB36038032022YFB36038022020J051042020J060122021ZZ1292021ZZ130TF2023-10

出版年：

2024

DOI：

10.1007/s40843-024-2965-0

中国科学:材料科学(英文)

CSTPCD

ISSN：

年,卷(期)：2024.67(7)