Zixuan Zhang, Xiaogang Lu, Meng Jin, Runli Gao and Hongmei Wang
{"title":"解码化学战前体的合成途径:使用GC × GC- tofms -化学计量学混合平台对甲基膦硫代二氯化物进行高级杂质分析。","authors":"Zixuan Zhang, Xiaogang Lu, Meng Jin, Runli Gao and Hongmei Wang","doi":"10.1039/D5AY00870K","DOIUrl":null,"url":null,"abstract":"<p >The chemical identification of precursor synthesis pathways is crucial for enforcing the Chemical Weapons Convention (CWC) by facilitating the forensic tracking of organophosphorus nerve agents. This study introduces the initial systematic impurity-profiling platform for methylphosphonothioic dichloride, a critical precursor of V-series CWC-controlled substances. Our analysis identified 58 unique compounds, offering valuable insights using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry in conjunction with advanced chemometric workflows. We devised a hierarchical analytical approach: (1) unsupervised pattern recognition (HCA/PCA) revealed the inherent clustering of two primary synthetic pathways, (2) oPLS-DA modeling achieved 100% classification accuracy (<em>R</em><small><sup>2</sup></small> = 0.990) with 15 VIP-discriminating features, and (3) rigorous validation through permutation tests (<em>n</em> = 2000) and external samples (<em>n</em> = 12) demonstrated 100% prediction accuracy. Notably, traceability was established at impurity levels as low as 0.5%, exceeding the OPCW verification standards. The established impurity database, in combination with the dual-mode chemometric approach, provides a robust framework for identifying chemical warfare-related precursors.</p>","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 25","pages":" 5160-5169"},"PeriodicalIF":2.7000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Decoding synthetic pathways of chemical warfare precursors: advanced impurity profiling of methylphosphonothioic dichloride using GC × GC-TOFMS-chemometrics hybrid platforms†\",\"authors\":\"Zixuan Zhang, Xiaogang Lu, Meng Jin, Runli Gao and Hongmei Wang\",\"doi\":\"10.1039/D5AY00870K\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >The chemical identification of precursor synthesis pathways is crucial for enforcing the Chemical Weapons Convention (CWC) by facilitating the forensic tracking of organophosphorus nerve agents. This study introduces the initial systematic impurity-profiling platform for methylphosphonothioic dichloride, a critical precursor of V-series CWC-controlled substances. Our analysis identified 58 unique compounds, offering valuable insights using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry in conjunction with advanced chemometric workflows. We devised a hierarchical analytical approach: (1) unsupervised pattern recognition (HCA/PCA) revealed the inherent clustering of two primary synthetic pathways, (2) oPLS-DA modeling achieved 100% classification accuracy (<em>R</em><small><sup>2</sup></small> = 0.990) with 15 VIP-discriminating features, and (3) rigorous validation through permutation tests (<em>n</em> = 2000) and external samples (<em>n</em> = 12) demonstrated 100% prediction accuracy. Notably, traceability was established at impurity levels as low as 0.5%, exceeding the OPCW verification standards. The established impurity database, in combination with the dual-mode chemometric approach, provides a robust framework for identifying chemical warfare-related precursors.</p>\",\"PeriodicalId\":64,\"journal\":{\"name\":\"Analytical Methods\",\"volume\":\" 25\",\"pages\":\" 5160-5169\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Methods\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2025/ay/d5ay00870k\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Methods","FirstCategoryId":"92","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/ay/d5ay00870k","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Decoding synthetic pathways of chemical warfare precursors: advanced impurity profiling of methylphosphonothioic dichloride using GC × GC-TOFMS-chemometrics hybrid platforms†
The chemical identification of precursor synthesis pathways is crucial for enforcing the Chemical Weapons Convention (CWC) by facilitating the forensic tracking of organophosphorus nerve agents. This study introduces the initial systematic impurity-profiling platform for methylphosphonothioic dichloride, a critical precursor of V-series CWC-controlled substances. Our analysis identified 58 unique compounds, offering valuable insights using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry in conjunction with advanced chemometric workflows. We devised a hierarchical analytical approach: (1) unsupervised pattern recognition (HCA/PCA) revealed the inherent clustering of two primary synthetic pathways, (2) oPLS-DA modeling achieved 100% classification accuracy (R2 = 0.990) with 15 VIP-discriminating features, and (3) rigorous validation through permutation tests (n = 2000) and external samples (n = 12) demonstrated 100% prediction accuracy. Notably, traceability was established at impurity levels as low as 0.5%, exceeding the OPCW verification standards. The established impurity database, in combination with the dual-mode chemometric approach, provides a robust framework for identifying chemical warfare-related precursors.