Advanced molecular separations and data interpretation tools

本研究项目的重点是提高气相色谱（GC）分析所收集信息的数量和质量。GC和多维GC是常规用于分离、量化和识别小有机分子的工具（在计算机上扩展我们的库，使用基于分子结构预测性质的技术）。最终目标是在给定的GC实验中绘制分子并预测其行为的能力。该程序的这两个方面的结合将导致智能搜索算法，以发现样品中的重要分子并假设其分子结构。这将是几十年来GC领域的第一个重大进展。它将改变人们使用这项技术的方式。我们将应用这些方法来识别新兴的设计类固醇，识别合成大麻素的结构，以及石油样品的详细分子表征。***HQP还将研究一些分析物的分离机制和化学反应的基本原理，用GC柱（应该是分离分子而不进行化学反应），以及研究家用材料的热解。后者是为了支持我们正在进行的自动化工具的工作，用于探测火灾碎片中的可燃液体。最后，假设设备拨款成功，我们还将探索一种新的GC光谱探测器

This research program focuses on improving the quantity and quality of information that can be gleaned from gas chromatographic (GC) analyses. GC and multidimensional GC are tools that are routinely used to separate, quantify, and identify small organic molecules (in silico expansion of our library using techniques for predicting properties based on molecular structures. The ultimate goal is the ability to draw a molecule and predict its behaviour in a given GC experiment. The marriage of these two aspects of the program will lead to an intelligent search algorithm to find important molecules in samples and postulate their molecular structures. This will be the first major advancement in this area of GC in decades. It will change how people use the technology. We will apply these methods to problems of identifying emerging designer steroids, identifying structures for synthetic cannabinoids, and detailed molecular characterization of petroleum samples.***HQP will also study fundamentals of separation mechanisms and chemical reactions of some analytes with the GC column (which is supposed to separate molecules without undergoing a chemical reaction) as well as studies of the pyrolysis of household materials. The latter is in support of our ongoing work into automated tools for the detection of ignitable liquids in fire debris. Finally, assuming that an equipment grant is successful, we will also explore a new spectroscopic detector for GC.**