A Combined First Principles and Kinetic Monte Carlo study of Polyoxometalate based Molecular Memory Devices

P. Lapham, O. Badami, C. Medina-Bailón, F. Adamu-Lema, T. Dutta, D. Nagy, V. Georgiev, A. Asenov
{"title":"A Combined First Principles and Kinetic Monte Carlo study of Polyoxometalate based Molecular Memory Devices","authors":"P. Lapham, O. Badami, C. Medina-Bailón, F. Adamu-Lema, T. Dutta, D. Nagy, V. Georgiev, A. Asenov","doi":"10.23919/SISPAD49475.2020.9241606","DOIUrl":null,"url":null,"abstract":"In this paper, we combine Density Functional Theory with Kinetic Monte Carlo methodology to study the fundamental transport properties of a type of polyoxometalate (POM) and its behaviour in a potential flash memory device. DFT simulations on POM molecular junctions helps us demonstrate the link between underlying electronic structure of the molecule and its transport properties. Furthermore, we show how various electrode-molecule contact configurations determine the electron transport through the POM. Also, our work reveals that the orientation of the molecule to the electrodes plays a key role in the transport properties of the junction. With Kinetic Monte Carlo we extend this investigation by simulating the retention time of a POM-based flash memory device. Our results show that a POM based flash memory could potentially show multi-bit storage and retain charge for up to 10 years.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/SISPAD49475.2020.9241606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper, we combine Density Functional Theory with Kinetic Monte Carlo methodology to study the fundamental transport properties of a type of polyoxometalate (POM) and its behaviour in a potential flash memory device. DFT simulations on POM molecular junctions helps us demonstrate the link between underlying electronic structure of the molecule and its transport properties. Furthermore, we show how various electrode-molecule contact configurations determine the electron transport through the POM. Also, our work reveals that the orientation of the molecule to the electrodes plays a key role in the transport properties of the junction. With Kinetic Monte Carlo we extend this investigation by simulating the retention time of a POM-based flash memory device. Our results show that a POM based flash memory could potentially show multi-bit storage and retain charge for up to 10 years.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于多金属氧酸盐的分子记忆器件的第一性原理与动力学蒙特卡罗相结合研究
本文将密度泛函理论与动力学蒙特卡罗方法相结合,研究了一类多金属氧酸盐(POM)的基本输运性质及其在潜在闪存器件中的行为。聚甲醛分子结的DFT模拟有助于我们证明分子的潜在电子结构与其输运性质之间的联系。此外,我们展示了不同的电极-分子接触构型如何决定电子通过POM的传递。此外,我们的工作揭示了分子在电极上的取向在结的传输特性中起着关键作用。利用动力学蒙特卡罗,我们通过模拟基于pom的闪存设备的保留时间来扩展这一研究。我们的研究结果表明,基于POM的闪存有可能显示多比特存储,并保持电荷长达10年。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Power Device Degradation Estimation by Machine Learning of Gate Waveforms Numerical Solution of the Constrained Wigner Equation Nanoscale FET: How To Make Atomistic Simulation Versatile, Predictive, and Fast at 5nm Node and Below Fully Analog ReRAM Neuromorphic Circuit Optimization using DTCO Simulation Framework Analytical Formulae for the Surface Green’s Functions of Graphene and 1T’ MoS2 Nanoribbons
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1