CAREER: Scalable Ionic Gated 2D Synapse (IG-2DS) with Programmable Spatio-Temporal Dynamics for Spiking Neural Networks

职业：可扩展离子门控二维突触（IG-2DS）与可编程时空动态脉冲神经网络seccs: 1943683PI：冯雄非技术：人工智能（AI）有潜力改变人们的生活。机器学习在医疗保健、交通运输和先进制造业中显示出前景，但需要大量的能源。人脑在模式识别等认知任务上甚至比超级计算机做得更好，而它只需要不到20瓦的功率。受人脑的启发，神经形态计算和人工神经网络最近引起了极大的兴趣。脉冲神经网络通过结合类似的时间动态来模拟生物过程。这种类型的计算为高带宽的节能计算提供了一条有前途的途径。然而，利用现有的数字电子设备在脉冲神经网络中实现短期和长期记忆等时空过程是具有挑战性和昂贵的。在这个项目中，PI将通过控制二维器件中的载流子浓度来开发一个严重缺失的元素，一个动态突触。这一突破将带来一个真正的神经现实计算系统，在能源效率、带宽和认知能力方面都有显著提高。这可能会导致人工智能的广泛应用，并通过认知计算、自动驾驶汽车和自动制造的进步彻底改变社会。PI将与当地社区参与中心合作，制定一项课后推广计划。来自代表性不足群体的学生将拥有设计和实验室经验，目的是吸引他们进入工程职业。技术：本项目的目标是阐明离子门控二维突触（IG-2DS）器件中的传输机制，并构建具有可编程时空动态、高精度、低功耗、良好可扩展性和良好可靠性的突触阵列，用于尖峰神经网络（snn）的硬件实现。尽管最近人工神经网络的发展取得了成功，但snn的硬件实现一直具有挑战性，因为现有的数字电子设备不具备动态突触所需的时空动态，而动态突触是snn的关键组成部分。在这个项目中，PI将采用一种新颖的方法，通过调节离子门控的挥发性掺杂效应和插层电荷转移掺杂的非挥发性掺杂效应，来证明二维突触的短期和长期可塑性。PI将开展以下三个研究任务：(1)阐明IG-2DS的短期和长期掺杂机制；(2)在IG-2DS中展示了snn硬件实现的可调时空动态；(3)研究IG-2DS在大规模集成中的扩展潜力。从根本上说，这项工作阐明了二维电子学中的电子和离子输运。实际上，这项工作将通过snn的硬件实现，在计算、自动驾驶、制造业自动化、柔性传感器和可穿戴电子等领域产生巨大影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

CAREER: Scalable Ionic Gated 2D Synapse (IG-2DS) with Programmable Spatio-Temporal Dynamics for Spiking Neural NetworksECCS : 1943683PI: Feng XiongNontechnical:Artificial intelligence (AI) has the potential to transform people's lives. Machine learning has shown promise in healthcare, transportation, and advanced manufacturing, but requires enormous amounts of energy. The human brain is better at cognitive tasks such as pattern recognition than even supercomputers while requiring less than 20W of power. Inspired by the human brain, neuromorphic computing and artificial neural networks have recently attracted immense interest. Spiking neural networks mimic biological processes by incorporating similar temporal dynamics. This type of computing offers a promising route for energy-efficient computing with high bandwidth. It is, however, challenging and expensive to implement spatio-temporal processes such as short-term and long-term memory in spiking neural networks with existing digital electronics. In this project, the PI will develop a critically missing element, a dynamic synapse, by controlling the charge carrier concentration in two-dimensional devices. This breakthrough will lead to a truly neuro-realistic computing system with dramatic improvements in energy efficiency, bandwidth, and cognitive capabilities. This can lead to the wide use of AI and revolutionize society through advances in cognitive computing, self-driving vehicles, and autonomous manufacturing. The PI will develop an afterschool outreach program in partnership with a local community engagement center. Students from underrepresented groups will have design and laboratory experiences with the aim of attracting them into engineering careers.Technical:The objective of this project is to elucidate the transport mechanisms in ionic gated two-dimensional synaptic (IG-2DS) devices and build synaptic arrays with programmable spatio-temporal dynamics, high precision, low power, good scalability, and good reliability for the hardware implementation of spiking neural networks (SNNs). Despite recent success in the development of artificial neural networks, the hardware implementation of SNNs has been challenging because existing digital electronics do not possess the spatio-temporal dynamics needed for a dynamic synapse-the key building block of SNNs. In this project, the PI will adopt a novel approach to demonstrate short-term and long-term plasticity in 2D synapses by modulating the volatile doping effect from ionic gating and the non-volatile doping effect from charge transfer doping via intercalation. The PI will carry out the following three research tasks: (1) elucidate the short- and long-term doping mechanisms in IG-2DS; (2) demonstrate tunable spatio-temporal dynamics in IG-2DS for the hardware implementation of SNNs; and (3) investigate the scaling potentials of IG-2DS for large-scale integration. Fundamentally, this work elucidates the electronic and ionic transport in 2D electronics. Practically, this work will have an immense impact in the fields of computing, self-driving, automation in manufacturing, flexible sensors, and wearable electronics through the hardware implementation of SNNs.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.