EAGER: CDS&E: A Computational Roadmap for a Universal Gas Sensor

大多数气体传感器只能检测一种气体（例如烟雾探测器）。一些被称为“电子鼻”的更先进的气体传感器能够区分气体混合物中的几种气体。然而，目前还没有“通用”气体传感器，也没有一种单一的设备可以在广泛的工作条件下检测到非常广泛的气体光谱。本项目旨在利用计算建模和模拟开发这样一个设备的初步设计。便携式通用气体传感器将产生巨大的社会经济影响，其重要性与数码相机类似，并将彻底改变健康诊断。研究人员计划为第一个通用气体传感装置制定一个路线图，该装置的功能可以与狗的鼻子相媲美，甚至可能超过狗的鼻子。该方法将使用分子模拟来精确模拟挥发性有机化合物（VOCs）的行为。此外，大规模的计算优化将用于搜索可能的传感阵列的巨大组合空间。拟议研究的主要成果将是未来“电子鼻”研究的计算衍生路线图。通过为本科生和更广泛的公众制作高质量的科学电影，预计拟议的研究将产生重大的教育影响。研究人员将制作一部电影，内容将涵盖人体排放的复杂挥发性有机化合物混合物，涉及许多可以从大规模计算/模拟方法中受益的工程应用。提出的研究的总体目标是制定一个“计算路线图”，指导通用气体传感器的实验设计。研究表明，经过训练的狗可以通过气味识别各种疾病，这表明通过气体感应检测疾病是可能的。然而，之前的“电子鼻”还无法与狗的嗅觉能力竞争，因为研究人员一直狭隘地专注于由20-30个元素（或更少）组成的气体传感装置。另一方面，狗的鼻子有3亿个嗅觉感受器，相应的感受器类型有数千种。少于30个传感元件的电子鼻不可能与狗的鼻子匹配，就像少于30个像素的数码相机不可能与人眼匹配一样。此外，先前的工作完全是由实验驱动的——计算模型只用于分析事后产生的数据。设计大型数组（100-1000+元素）提出了一个组合挑战，因此是一个经典的“大数据”问题，只能使用计算数据科学和工程方法来解决。研究者将使用大规范蒙特卡罗模拟模拟复杂气体混合物在金属有机框架（mof）阵列中的吸附，这是一种晶体纳米多孔材料。通过计算探索mof的不同组合，研究者将在原则上确定哪种阵列可以匹配生物鼻子的传感性能基准。该项目将研究一些基本问题，包括：性能如何随数组大小而扩展；一个动物的嗅觉表现在多大的尺度上？哪些材料特性对传感性能影响最大？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。

Most gas sensors can only detect a single gas species (e.g., a smoke detector). Some more advanced gas sensors called "electronic noses" are able to distinguish among a few gas species in a gas mixture. However, there is still no "universal" gas sensor, or a single device that could detect a very broad spectrum of gases under a wide range of operating conditions. This project seeks develop a preliminary design of a such a device using computational modeling and simulations. A portable universal gas sensor would have enormous socioeconomic impact, similar in magnitude to the digital camera, and would revolutionize health diagnostics. The investigator plans to create a roadmap for the first universal gas sensing device whose capabilities could match, and potentially surpass, those of a dog's nose. The approach will use molecular simulations to accurately model the behavior of volatile organic compounds (VOCs). Also, large-scale computational optimization will be used to search the vast combinatorial space of possible sensing arrays. The primary outcome of the proposed research will be a computationally-derived roadmap for future "electronic nose" research. The proposed research is expected to have a significant educational impact via the production of high-quality scientific movies for both undergraduates and the broader public. The investigator will produce a movie that will cover the complex mixtures of VOCs emitted from the human body, touching on the many engineering applications that can benefit from large-scale computational/simulation approaches.The overall objective of the proposed research is to develop a "computational road map" guiding experimental design of a universal gas sensor. It has been shown that trained dogs can identify various illnesses through smell along, indicating that detection of diseases via gas sensing is possible. However, prior "electronic noses" have been unable to compete with canine olfactory abilities because researchers have been narrowly focused on gas sensing devices with arrays of 20-30 elements (or less). A dog's nose, on the other hand, has 300 million olfactory receptors, with corresponding receptor types numbering in the thousands. It is unlikely that an electronic nose with less than 30 sensing elements can match a dog's nose any more than a digital camera with less than 30 pixels can match a human eye. Moreover, prior work has been entirely experimentally driven - computational modeling has only been used to analyze the data generated after the fact. Designing large arrays (100-1000+ elements) presents a combinatorial challenge and hence is a classic "big data" problem, which can only be solved using computational data science and engineering methods. The investigator will use grand canonical Monte Carlo simulations to model complex gas mixture adsorption in arrays of metal-organic frameworks (MOFs), which are crystalline nanoporous materials. By computationally exploring different combinations of MOFs, the investigator will then determine, in principle, what kind of array could match the sensing performance benchmarks of a biological nose. The project will examine fundamental questing including: how does performance scale with array size; at what sizes does one cross benchmark olfactory performance of animals; and what material characteristics have the greatest influence on sensing performance?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.