COLLABORATIVE: Biomimetic Entropic Patterning (BEP) of Nanobiosensors

该合作研究项目涉及开发用于食品和农业应用中的需求点测试的传感器，这些传感器可以检测食品或水中的受管制农药和/或致病菌。 传感器正在使用计算机算法开发，以在表面上生成材料的图案。该过程是可重复的，不需要使用昂贵的设备或大量的培训，确保该技术的广泛可用性。该研究项目还鼓励来自代表性不足群体的学生通过一系列实践教学活动，本科夏季研究项目和社区非正式学习活动来进行研究和研究生院。此外，非专家观众接触到的基本科学和技术的移动的手机为基础的生物传感器以及仿生学和分形数学的概念。最后，在本研究项目中开发的传感器平台具有许多潜在的应用，包括能量存储，生物医学设备和太阳能电池。本研究的目标是开发一种新的工艺，用于图案化微/纳米结构的生物传感。提出了一种新的仿生熵图案化技术，以提高信号转导和耐久性，特别是在具有挑战性的现场条件下。假设纳米材料的二维图案化导致与信号转导相关的熵的优化。这种优化提高了阻抗和表面等离子体共振生物传感器的耐久性、灵敏度、检测极限和准确性。该假设已经发展的基础上，研究人员？初步探索性分析了30多种电化学传感模式，包括无标度和非无标度模式。对于第一次，图案化的纳米材料和信号转导的熵之间的相关性是建立通过测试电化学和等离子体传感器，包含各种图案化的纳米材料。图案的熵由计算机二维模型调整，并且诸如激光划线或纳米光刻之类的技术用于在传感器表面上图案化纳米材料。该研究项目将创建一个多用途传感器平台，用于使用基于移动的手机的采集系统进行需求点感知，并应用于生态系统健康和食品安全生物传感领域。为了证明图案化原理的广泛适用性，使用了多种制造技术（激光雕刻石墨烯、喷墨印刷、纳米压印光刻），该协议将由多个传感器实验室通过正式的二次验证过程进行测试，这些实验室具有不同的技能和设备。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准。

This collaborative research project involves developing sensors for point-of-need testing in food and agricultural applications that can detect regulated pesticides and/or pathogenic bacteria in food or water. Sensors are being developed using computer algorithms to generate patterns of materials on surfaces. The process is reproducible and does not require the use of expensive equipment or significant training, ensuring the widespread availability of the technique. The research project also encourages students from underrepresented groups to pursue research and graduate school via a series of hands-on teaching activities, undergraduate summer research projects, and informal learning activities in the community. In addition, non-expert audiences are exposed to the underlying science and technology of mobile phone-based biosensors as well as the concepts of biomimicry and fractal mathematics. Finally, the sensor platform developed during this research project has many potential applications, including energy storage, biomedical devices, and solar cells. The goal of this research is to develop a new process for patterning micro/nanostructures in biosensing. A new biomimetic entropic patterning technique is proposed to improve signal transduction and durability, particularly under challenging field conditions. The hypothesis is that two-dimensional patterning of nanomaterials leads to optimization of entropy associated with signal transduction. This optimization improves durability, sensitivity, limit of detection, and accuracy of impedimetric and surface plasmon resonance biosensors. The hypothesis has been developed based on the researchers? preliminary exploratory analysis of over 30 patterns for electrochemical sensing, including scale free and non scale-free patterns. For the first time, a correlation between the entropy of patterned nanomaterials and signal transduction is established by testing electrochemical and plasmonic sensors that contain various patterned nanomaterials. The entropy of the pattern is tuned by an in silico two-dimensional model, and techniques such as laser scribing or nanolithography are used to pattern nanomaterials on the sensor surface. This research project will create a multipurpose sensor platform for point of need sensing using mobile phone-based acquisition systems with applications in the areas of ecosystem health and food safety biosensing. To demonstrate the broad applicability of the patterning principle, multiple fabrication techniques are used (laser inscribed graphene, inkjet printing, nanoimprint lithography), and the protocol will be tested by multiple sensor labs with varying skills and equipment through a formal secondary validation process.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.