CAREER: Scalable monolithic integration of Graphene/MoS2/Graphene artificial neurons and synapses for accelerated machine learning

非技术：集成电路的发展是电子黄金时代的一个里程碑。该项目将通过在同一材料平台上开发人工神经元和突触来复制这一壮举。 这将使我们能够创建能够模拟人类大脑进行模式匹配的能力和速度的系统，击败目前体积更大，速度更慢，更耗电的系统。这将彻底改变机器学习领域，并创建机器学习硬件接近传感器的设备，从而产生目前不可能创建的系统。基于这些设备的神经形态电路包括智能可穿戴设备，可以监测健康生物特征，并为独自在家的老年人提供第一级分类。它们可以改善陆地车辆的自动驾驶。这些电路将特别适用于航天器和太空漫游车，因为这些超轻电路不会成为火箭有效载荷的瓶颈。通过这些深度神经网络的快速模式识别能力将增强便携式电子设备中的语音识别，并改善交通分析和控制系统。与中央佛罗里达STEM联盟（CFSA）计划合作，来自当地社区学院的代表性不足的少数民族将在PI的实验室中获得动手研究的机会。定期的视频实验室图尔斯，以代表性不足的K-12学生和为期一周的实验室经验，为两个选定的K-12学生每年将培养他们对干教育的兴趣。突出这项研究的关键方面的展览将在奥兰多科学中心展出，以提高公众的认识。这些努力将引导电子行业通过佛罗里达高科技走廊在佛罗里达投资，为该州的工程师创造机会。技术：本提案的目标是开发可扩展的单片集成人工神经元和突触，使用全二维（全2D）石墨烯/MoS 2/石墨烯忆阻异质结构进行神经形态计算。在这些异质结构中，石墨烯用作电极，而二硫化钼用作开关介质。挥发性电阻开关中观察到的垂直站立的表的二硫化钼将利用实现集成和消防（IF）神经元，和他们的随机性质将被调查。人工突触与亚皮焦耳的能量需求，每个开关事件将开发使用多层次的非易失性开关在水平的二硫化钼片。背后的机制，这有趣的现象，挥发性电阻开关在垂直的二硫化钼片与非挥发性开关在水平的二硫化钼片将使用电气和材料表征技术进行研究。将证明异质结构中石墨烯电极的必要性。通过异质结构设计的工程化，人工神经元和突触的性能将被优化以创建随机连续切换IF神经元和低功率突触，其将被单片集成。石墨烯和MoS 2的机械柔性的优点将被利用来在柔性平台上制造和测试这些神经形态器件。拟议的研究计划旨在将两个新兴的研究领域结合在一起，形成一项尖端技术。虽然2D材料在冯·诺依曼范式中接替硅具有巨大的前景，但非冯·诺依曼方法总是处理传统材料。这种变革性的研究将把这两个世界的最好的东西结合在一起。大面积2D材料的使用将增强这些奇异器件的实际实现。石墨烯/MoS 2/石墨烯人工突触与稀疏点火石墨烯/MoS 2/石墨烯人工神经元的超低功耗操作将为节能的神经形态计算提供支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Nontechnical:Development of integrated circuits was a milestone in the golden age of electronics. That feat will be replicated by this project through the development of both artificial neurons and synapses on the same materials platform. This will allow us to create systems that can emulate the capacity and speed of the human brain for pattern matching, beating current systems that are bulkier, slower and more power hungry. This will revolutionize the field of machine learning and create devices where the machine-learning hardware is close to the sensor, giving rise to systems that are currently impossible to create. Neuromorphic circuits based on these devices include smart wearables that can monitor health biometrics and issue first level triage for elderly people alone at home. They can improve autonomous driving for terrestrial vehicles. These circuits will be especially useful for spacecrafts and space rovers because these ultra-light circuits will not be a bottleneck to the rocket's payload. Fast pattern recognition abilities through these deep neural networks will enhance speech recognition in portable electronics and improve traffic analysis and control systems. In collaboration with Central Florida STEM Alliance (CFSA) program, underrepresented minorities from local community colleges will be provided hands-on research opportunities in the lab of the PI. Regular video lab tours to underrepresented K-12 students and week-long lab experience for two selected K-12 students annually will foster their interest in STEM education. Banners highlighting key aspects of this research will be displayed at the Orlando Science Center for general public awareness. These efforts will lead the electronics industry to invest in Florida through the Florida High Technology Corridor, creating opportunities for engineers in the state.Technical:The objective of this proposal is to develop scalable monolithically integrated artificial neurons and synapses using all-two-dimensional (all-2D) graphene/MoS2/graphene memristive heterostructures for neuromorphic computing. In these heterostructures graphene acts as the electrodes and MoS2 as the switching medium. Volatile resistive switching observed in vertically-standing sheets of MoS2 will be harnessed to realize integrate-and-fire (IF) neurons, and the stochastic nature of their firing will be investigated. Artificial synapses with sub-picojoules of energy requirement per switching event will be developed using the multi-level non-volatile switching in horizontal MoS2 sheets. The mechanisms behind this intriguing phenomenon of volatile resistive switching in vertical MoS2 sheets versus non-volatile switching in horizontal MoS2 sheets will be investigated using electrical and materials characterization techniques. The necessity of graphene electrodes in the heterostructure will be justified. Through engineering of the heterostructure design, the performance of the artificial neurons and synapses will be optimized to create stochastic resistive-switching IF neurons and low-power synapses which will be integrated monolithically. The advantage of mechanical flexibility of graphene and MoS2 will be exploited to fabricate and test these neuromorphic devices on a flexible platform. The proposed research program aims at bringing together two emerging research areas cohesively into a cutting edge technology. While 2D materials have immense prospects in succeeding silicon within the von Neumann paradigm, non-von Neumann approaches have always dealt with conventional materials. This transformative research would bring together the best of both these worlds. The use of large-area 2D materials will enhance the practical realization of these exotic devices. Ultra-low power operation of graphene/MoS2/graphene artificial synapses with sparse firing graphene/MoS2/graphene artificial neurons will provide for energy-efficient neuromorphic computing.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.