Conjugated Polymers and Composites for Energy, Electronics and Sensing

用于能源、电子和传感的共轭聚合物和复合材料

• 批准号: RGPIN-2019-04671
• 负责人: Freund, Michael
• 金额: $ 3.5万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689655
• 关键词: Conjugated; Polymers; Composites; Energy; Electronics

This research program will focus on developing conducting polymer composites to impact the fields of renewable energy, electronics and sensing.******Given the scale of projected energy needs as well as the rapid climate change associated with growing carbon dioxide levels in the atmosphere, there is a major push by governments to increase the rate of innovation and discovery in the area of carbon-neutral solar fuel production. This program will help address this need by developing membranes that will be a key component of standalone artificial photosynthetic devices to directly produce solar fuels. Currently, the production of membranes for these devices represents a technology gap that must be addressed so that catalysts and light absorbers being developed by researchers around the world can be integrated into a working system. Existing collaborations with world-renowned researchers at Caltech and MIT with programs developing light absorbers and catalysts will allow rapid translation of advances in membrane design into proof of concept devices and will therefore have a significant impact in this quickly advancing field. Trainees involved in these studies will gain unique skills and will be highly desirable in the rapidly growing renewable energy sector of the Canadian economy.******Organic-based electronics provide new mechanisms of operation that promise to overcome current limitations of silicon-based devices, including cost and miniaturization. However, there remain significant challenges for integrating organic materials into devices such as memory and transistors. The proposed research program will focus on the development of new conducting polymer composites for use in dynamic random-access memory (DRAM), commonly used in electronic devices. In collaboration with electrical and computer engineers, the efforts will focus on increasing read/write speeds, memory retention (i.e., reducing volatility) and scaling laws (i.e., how small can they be made). In addition, issues ranging from device fabrication to integration into existing electronic platforms and processes will be addressed.******The invention of the charge coupled device (CCD) chip has revolutionized the interface between technology and its environment. By pixelating optical images of its surroundings, devices can use sophisticated image processing and pattern recognition algorithms to perform increasingly complex tasks associated with visual perception. The proposed research will focus on creating a chemically diverse sensor array chip that mimics the olfactory system to provide the next revolution in sensory input for technology. Working in collaboration with electrical and computer engineers, integrated circuit sensor arrays will be developed, novel methods for creating large numbers of chemically diverse polymer sensing materials on these chips (i.e., chemical programming) will be demonstrated, and new machine learning algorithms will be explored for processing olfactory data streams.**

该研究项目将专注于开发导电聚合物复合材料，以影响可再生能源、电子和传感领域。******考虑到预计能源需求的规模以及与大气中二氧化碳含量增加相关的快速气候变化，各国政府正在大力推动碳中性太阳能燃料生产领域的创新和发现速度。这个项目将通过开发膜来帮助解决这一需求，膜将成为直接生产太阳能燃料的独立人工光合装置的关键组成部分。目前，用于这些装置的膜的生产代表了一个必须解决的技术差距，以便世界各地的研究人员开发的催化剂和光吸收剂可以集成到一个工作系统中。目前与加州理工学院和麻省理工学院的世界知名研究人员合作开发光吸收剂和催化剂，将使膜设计的进步迅速转化为概念设备的验证，因此将对这一快速发展的领域产生重大影响。参与这些研究的学员将获得独特的技能，并将在加拿大经济快速增长的可再生能源部门非常可取。******有机电子产品提供了新的操作机制，有望克服当前硅基设备的局限性，包括成本和小型化。然而，将有机材料集成到存储器和晶体管等器件中仍然存在重大挑战。拟议的研究计划将侧重于开发新的导电聚合物复合材料，用于动态随机存取存储器（DRAM），通常用于电子设备。在与电气和计算机工程师的合作下，他们的努力将集中在提高读写速度、内存保留（即减少波动性）和缩放定律（即它们可以做得多小）上。此外，将解决从设备制造到集成到现有电子平台和流程中的问题。******电荷耦合器件（CCD）芯片的发明彻底改变了技术与环境之间的接口。通过对周围环境的光学图像进行像素化处理，设备可以使用复杂的图像处理和模式识别算法来执行与视觉感知相关的日益复杂的任务。拟议的研究将集中于创造一种化学上多样化的传感器阵列芯片，模仿嗅觉系统，为技术的感官输入提供下一次革命。与电气和计算机工程师合作，将开发集成电路传感器阵列，将展示在这些芯片上创建大量化学多样性聚合物传感材料的新方法（即化学编程），并将探索用于处理嗅觉数据流的新机器学习算法