SBIR Phase I: Paramagnetic Spin-Probes for Corrosion Inhibition

这项小型企业创新研究（SBIR）项目具有更广泛的影响和商业潜力，旨在为石油和天然气等行业的项目提供一种优化缓蚀机制。据估计，仅腐蚀每年就给美国工业造成1700亿美元的损失。由于石油和天然气行业的生产技术复杂且要求苛刻，而且如果组件失效，会对环境造成威胁，因此石油和天然气行业在这些成本中所占的份额高于平均水平。目前，油气行业的标准抑制机制是注入化学抑制剂，通常是表面活性剂，可以涂覆油田管柱内部，避免腐蚀。由于故障的高成本，表面活性剂的过量注入是非常常见的，导致成本过高，并且浪费了不需要的化学品送到炼油厂。不幸的是，之前并没有一个很好的方法来判断表面活性剂过量是否真的过量。这是这一创新带来的具体新方面。提出了一种利用表面活性剂在非常大的磁场和GHz射频激励下的量子化学性质实时检测表面活性剂是否充足的机制。SBIR一期项目建议从一种特殊设计的试剂中提取化学光谱，该试剂可以添加到采出液样品中，其中化学光谱将根据是否有足够的表面活性剂来产生缓蚀作用而变化。更具体地说，它将测量试剂的一些量子化学性质，称为超精细结构，它会在表面活性剂胶束的存在下发生变化。本质上，胶束在试剂中的自由基电子周围形成了一个密封屏障，从而改变了这些电子在磁铁和射频激发的组合中共振的方式。该项目的第一阶段将解决该方法面临的多重挑战，包括试剂的选择以及将超细数据转换为临界胶束浓度量化的稳健算法的开发，其中算法需要能够容忍油田流体中发现的典型杂质。第一阶段还将验证一种光谱方法，该方法可以将超精细数据发送到云端，在云端，基于人工智能的算法可以将光谱信息简化为操作员可操作的信息。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。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project addresses a mechanism to optimize corrosion inhibition for projects covering the oil and gas industry and beyond. Corrosion costs US industries alone an estimated $170 billion a year. The oil and gas industry takes an above average share of these costs because of its complex and demanding production techniques, and the environmental threat should components fail. Today, the standard inhibition mechanism for the oil and gas industry is to inject a chemical inhibitor, typically a surfactant, that can coat the interior of the oilfield tubular and avoid corrosion. Because of the high cost of failure, it is extremely common to over-inject surfactant quantities resulting in excessive costs and the waste of unwanted chemicals sent to the refinery. Unfortunately, there has not previously been a good way to tell when too much surfactant was in fact too much. That is the specific new aspect brought by this innovation. It proposes a mechanism to detect in real-time that there is sufficient surfactant by taking advantage of quantum chemical properties of those surfactants when they are subject to very large magnetic fields and GHz radio-frequency excitation.This SBIR Phase I project proposes to extract a chemical spectrum from a specially designed reagent that can be added to a sample of produced fluid, where that chemical spectrum will change depending on whether there is sufficient surfactant to cause corrosion inhibition. More specifically it is going to measure some quantum chemical properties of the reagent called its hyperfine structure that will change in the presence of surfactant micelles. Essentially the micelles form a containment barrier around free radical electrons within that reagent and thereby change the way those electrons can resonate in the combination of the magnet and RF excitation. Phase 1 of the project will resolve multiple challenges in this approach, including the choice of reagent and the development of robust algorithms to convert hyperfine data into quantification of critical micelle concentration, where the algorithm needs to be able to tolerate typical impurities found in oilfield fluids. Phase 1 will also validate a spectroscopic approach that can result in the hyperfine data being sent to the cloud where AI-based algorithms can reduce the spectral information to actionable information for the operator.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.