Atomic control of ionic processes in resistive memory devices

从制造业到社交网络，从大型组织到个人消费者，当今社会的各个方面都在不断产生大量数据，而且这种趋势还在加速发展。为了快速有效地存储和分析数据，需要更好更快的存储技术。与此同时，传统的存储技术正面临着基本的扩展限制和主要的实际限制，这使得它越来越难以跟上需求。该项目旨在开发一种全新的存储技术，通过在原子尺度上改变材料的内部结构来存储数据，从而显著提高设备性能。该计划将显著推进基础科学研究，并增强对纳米级界面控制、离子和电子输运以及混合器件集成的理解。从这个nsf资助的项目中获得的结果也可能导致成功的技术转移，从而产生行业领先的存储产品，并对关键的半导体行业产生变革性影响。该计划开发的工具，方法和技术可以应用于广泛的纳米级设备和系统，以刺激广泛领域的研究。该计划将为研究生和本科生提供跨学科的培训，并吸引不同水平和背景的学生广泛参与合作研究和教育。该器件基于电阻式随机存取存储器（RRAM）的概念，具有出色的可扩展性和其他几个性能指标。然而，该技术仍然面临着根本性的挑战，包括大的器件变化，高编程电流和小的开/关比，这些都阻碍了器件的实际应用。该项目旨在实现对RRAM中电阻变化的基本离子过程的原子水平控制，并生产具有显着性能改进和新器件功能的器件。具体来说，该装置利用原子薄的石墨烯作为离子阻断层，通过石墨烯薄膜中的纳米级开口来调节氧空位（VO）的产生和迁移。灯丝的形成将进一步被限制在开关层内部的局部通道中，这有利于通过受控掺杂进行VO的传输和存储。实验研究将得到理论计算和建模的支持，包括预测VO形成能量和O-O距离的第一性原理计算，以及预测VO分布和动态迁移过程的数值模拟。所提出的方法将消除开关层中过多的VOs，并将显著改善RRAM器件的开/关比、编程电流和器件可变性。同时，利用新兴材料与新兴器件的独特性能，推进纳米器件研究的前沿，自然促进物理学、材料研究和器件工程的紧密结合。

Large amounts of data are being generated constantly in every aspect of today's society, from manufacturing to social networks, from large organizations to individual consumers, and this trend is continuing at an accelerated pace. Better and faster memory technologies are needed to store and analyze the data quickly and efficiently. At the same time, traditional memory technologies are facing fundamental scaling limits and major practical constraints that make it ever more challenging to keep up with the demand. This project aims to develop a fundamentally new memory technology that can store data by changing the material's internal configuration at the atomic scale, leading to significantly improved device performance. The proposed program will significantly advance fundamental scientific research and enhance the understanding of interface control, ionic and electronic transport and hybrid device integration at the nanoscale. Results obtained from this NSF-funded program will also likely lead to successful technology transfers that can result in industry-leading memory products, and have a transformative impact on the crucial semiconductor industry sector. The tools, methods and techniques developed in the program can be applied to a wide range of nanoscale devices and systems to stimulate research in a broad range of areas. The project will in turn provide interdisciplinary training of graduate and undergraduate students, and draw broad participation of students of different levels and backgrounds in collaborative research and education.The proposed device is based on the concept of resistive random-access memory (RRAM), which has shown excellent scalability and several other performance metrics. However, the technology still faces fundamental challenges, including large device variations, high programming current and small on/off ratio, which prevent the device from practical applications. The proposed project aims to achieve atomic-level control of the fundamental ionic processes underlying the resistance changes in RRAM, and produce devices with significant performance improvements and new device functions. Specifically, the proposed device exploits atomically-thin graphene as an ion-blocking layer to regulate oxygen vacancy (VO) generation and migration through nanoscale openings in the graphene film. The filament formation will further be confined inside the switching layer to localized channels that are favorable for VO transport and storage through controlled doping. The experimental studies will be supported by theoretical calculations and modeling, including first-principles calculations that predict the VO formation energy and O-O distance, as well as numerical modeling that predicts the VO distribution and dynamic migration processes. The proposed approaches will eliminate excessive VOs in the switching layer and will significantly improve the on/off ratio, programming current, and device variability of RRAM devices. In the meantime, by leveraging unique properties of emerging materials with emerging devices, the proposed project advances the frontier of nanoscale device research and naturally promotes a tight integration with physics, materials research and device engineering.