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来开发，以在表面上生成材料图案。该过程是可重复的，不需要使用昂贵的设备或大量培训，确保了该技术的广泛可用性。该研究项目还通过一系列实践教学活动、本科生暑期研究项目和社区非正式学习活动，鼓励弱势群体的学生进行研究和研究生院学习。此外，非专业观众还可以了解基于手机的生物传感器的基础科学和技术以及仿生学和分形数学的概念。最后，该研究项目中开发的传感器平台具有许多潜在的应用，包括能源存储、生物医学设备和太阳能电池。这项研究的目标是开发一种用于生物传感中微/纳米结构图案化的新工艺。提出了一种新的仿生熵图案技术来改善信号转导和耐久性，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共振生物传感器的耐用性、灵敏度、检测限和准确性。该假设是根据研究人员提出的？对 30 多种电化学传感模式（包括无标度和非无标度模式）进行了初步探索性分析。通过测试包含各种图案化纳米材料的电化学和等离子体传感器，首次建立了图案化纳米材料的熵和信号转导之间的相关性。图案的熵通过计算机二维模型进行调整，并使用激光划线或纳米光刻等技术在传感器表面上对纳米材料进行图案化。该研究项目将创建一个多用途传感器平台，使用基于移动电话的采集系统进行需求点传感，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（激光刻写石墨烯、喷墨印刷、纳米压印光刻），并且该协议将由具有不同技能和设备的多个传感器实验室通过正式的二次验证过程进行测试。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。

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.