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Armando Alcaraz

Researcher at Lawrence Livermore National Laboratory

Publications -  19
Citations -  260

Armando Alcaraz is an academic researcher from Lawrence Livermore National Laboratory. The author has contributed to research in topics: Mass spectrometry & Solid phase extraction. The author has an hindex of 10, co-authored 19 publications receiving 199 citations.

Papers
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Part 1: Tracing Russian VX to its synthetic routes by multivariate statistics of chemical attribution signatures.

TL;DR: The utility of this methodology for attributing VR samples to a particular production method is demonstrated, demonstrating the utility of the CAS in synthesized batches of crude VR in diverse batches and matrices.
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Effective methylation of phosphonic acids related to chemical warfare agents mediated by trimethyloxonium tetrafluoroborate for their qualitative detection and identification by gas chromatography-mass spectrometry.

TL;DR: The work described herein represents the first report on the use of TMO·BF4 as a viable, stable and safe agent for the methylation of phosphonic acids and their half esters and within the context of an OPCW Proficiency Test sample analysis.
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Analysis of tetrodotoxin

TL;DR: In this article, an illegal shipment of a chemical suspected to be an illicit drug was interdicted, and the substance was identified as tetrodotoxin, a potent marine neurotoxin.
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Nuclear forensics in law enforcement applications

TL;DR: The Livermore Forensic Science Center has conducted analyses of nuclear-related samples in conjunction with domestic and international criminal investigations as mentioned in this paper, including nuclear smuggling and the proliferation of alleged fissionable materials, nonradioactive hoaxes such as Red Mercury, and the interdiction of illegal laboratories engaged in methamphetamine synthesis.
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Part 2: Forensic Attribution Profiling of Russian VX in Food Using Liquid Chromatography-Mass Spectrometry

TL;DR: The sourcing of VR present in food based on chemical analysis of attribution signatures by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with multivariate data analysis is described.