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有机磷神经毒剂及其模拟物与金属盐的结合。

Binding of Organophosphorus Nerve Agents and Their Simulants to Metal Salts.

机构信息

Department of Chemical and Biological Engineering, University of Wisconsin - Madison, Madison, Wisconsin 53706, United States.

Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14853, United States.

出版信息

ACS Appl Mater Interfaces. 2020 Jul 8;12(27):30941-30953. doi: 10.1021/acsami.0c05777. Epub 2020 Jun 25.

DOI:10.1021/acsami.0c05777
PMID:32506901
Abstract

Nerve agents (NAs) pose a great threat to society because they are easy to produce and are deadly in nature, which makes developing methods to detect, adsorb, and destroy them crucial. To enable the development of these methods, we report the use of first principles electronic structure calculations to understand the binding properties of NAs and NA simulants on metal salt surfaces. We report calculated Gibbs free binding energies () for four NAs (tabun (GA), sarin (GB), soman (GD), and venomous X (VX)) and five NA simulants (dimethyl methylphosphonate (DMMP), dimethyl chlorophosphate (DMCP), trimethyl phosphate (TMP), methyl dichlorophosphate (MDCP), and di-isopropyl methylphosphonate (DIMP)) on metal perchlorate and metal nitrate salts using density functional theory. Our results indicate a general trend in the binding strength of NAs and NA simulants to metal salt surfaces: MDCP < DMCP < GA < GD ≈ GB < TMP < VX ≈ DMMP < DIMP. Based on their binding properties on salt surfaces, we identify the most effective simulant for each of the studied NAs as follows: DMCP for GA, TMP for GB and GD, and DMMP for VX. To illustrate the utility of the binding energies calculated in our study, we address the design of NA sensors based on the competitive binding of NAs and liquid crystalline compounds on metal salts. We compare our results with previous experimental findings and provide a list of promising combinations of liquid crystal and metal salt systems to selectively and sensitively detect NAs. Our study highlights the great value of computational chemistry for designing selective and sensitive NA sensors while minimizing the number of very dangerous experiments involving NAs.

摘要

神经毒剂(NAs)对社会构成了巨大威胁,因为它们易于生产且性质致命,这使得开发检测、吸附和破坏它们的方法至关重要。为了能够开发这些方法,我们报告了使用第一性原理电子结构计算来理解 NAs 和 NA 模拟物在金属盐表面上的结合特性。我们报告了四种 NAs(塔崩(GA)、沙林(GB)、梭曼(GD)和毒液 X(VX))和五种 NA 模拟物(二甲甲基膦酸酯(DMMP)、二甲基氯膦酸酯(DMCP)、三甲磷酸酯(TMP)、甲基二氯膦酸酯(MDCP)和二异丙基甲基膦酸酯(DIMP))在金属高氯酸盐和硝酸盐盐上的吉布斯自由结合能(),使用密度泛函理论。我们的结果表明 NAs 和 NA 模拟物与金属盐表面结合强度的一般趋势:MDCP<DMCP<GA<GD≈GB<TMP<VX≈DMMP<DIMP。根据它们在盐表面上的结合特性,我们确定了每种研究 NAs 的最有效模拟物,如下所示:DMCP 用于 GA,TMP 用于 GB 和 GD,DMMP 用于 VX。为了说明我们在研究中计算的结合能的实用性,我们根据 NAs 和液晶化合物在金属盐上的竞争性结合来解决 NA 传感器的设计问题。我们将我们的结果与以前的实验结果进行了比较,并提供了一组有前途的液晶和金属盐系统组合,以选择性和灵敏地检测 NAs。我们的研究强调了计算化学在设计选择性和灵敏的 NA 传感器方面的巨大价值,同时最大限度地减少了涉及 NAs 的非常危险的实验数量。

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