Developing organic electronic materials and devices for neuromorphic computing

开发用于神经形态计算的有机电子材料和设备

• 批准号: 2433502
• 金额: --
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2433502
• 关键词: Developing; organic; electronic; materials; devices

Current computing technologies, based on the Von Neumann architecture, are facing several bottlenecks due to Moore's law and/or memory and heat limitations. New approaches are therefore required to circumvent the imminent bottlenecks that current technology faces. Furthermore, new computing technologies are also required to power the advances being made in big data and the internet of things, and machine learning applications as well as our natural desire to learn more about the origins of life and cognition. Neuromorphic computing, inspired by the human brain, has come into focus in recent years and is one of the most promising ways to overcome the limits of von Neumann chip architecture. Organic electronic materials have shown great promise for producing neuromorphic devices and have an added advantage of being biocompatible. There have been some breakthrough papers published in recent years on organic neuromorphic devices, particularly memristors and organic electrochemical transistors (OECTs). Most reports have employed very similar polymeric materials and there is thus a need to develop new organic materials for advancing the field. In this project, new organic electronic materials will be developed that are capable of ionic and electronic conduction, a key requirement in memristors and OECTs. These materials will then be employed to fabricate organic memristors and OECTs as well as exploring new approaches to neuromorphic devices. The project is expected to lead to key advances in neuromorphic computing, bioelectronics and perhaps answer deeper questions about cognition itself.

基于冯·诺伊曼体系结构的当前计算技术由于摩尔定律和/或内存和热限制而面临几个瓶颈。因此，需要新的方法来绕过当前技术面临的迫在眉睫的瓶颈。此外，还需要新的计算技术来推动大数据和物联网以及机器学习应用程序的进步，以及我们了解更多生命起源和认知的自然愿望。受人脑启发的神经形态计算近年来成为人们关注的焦点，是克服冯·诺伊曼芯片架构局限性的最有前途的方法之一。有机电子材料在制造神经形态设备方面显示出巨大的前景，并具有生物兼容性的额外优势。近年来，在有机神经形态器件，特别是记忆电阻和有机电化学晶体管(OECTS)方面发表了一些突破性的论文。大多数报告使用了非常相似的聚合物材料，因此需要开发新的有机材料来推动该领域的发展。在这个项目中，将开发能够离子和电子传导的新的有机电子材料，这是忆阻器和其他材料的关键要求。然后，这些材料将被用来制造有机忆阻器和Oect，以及探索神经形态设备的新方法。该项目预计将在神经形态计算、生物电子学方面取得关键进展，或许还会回答有关认知本身的更深层次问题。