Knowledge Base

Learn more about the power of trace gas analysis using SIFT-MS. Download our latest brochures, application notes and white papers or watch an application-focused video. Questions? Contact us!

Whitepaper

Fast and Sustainable Workflows for Volatiles Analysis: Automated SIFT-MS

Discover how automated SIFT-MS enables fast, sustainable volatiles analysis by eliminating complex sample prep and reducing environmental impact. This whitepaper explores real-world workflows and evaluates SIFT-MS against modern green chemistry standards using the White Analytical Chemistry framework.

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Whitepaper

Eliminate Chromatography for Faster, Simpler Volatiles Analysis

This whitepaper showcases how SIFT-MS eliminates chromatography to deliver real-time, high-sensitivity VOC analysis with unmatched speed and simplicity. Learn how ditching columns unlocks faster workflows, reduced maintenance, and greater sustainability across labs and process environments.

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Whitepaper

Direct SIFT-MS Analysis of Packaging Materials

This whitepaper explores how direct SIFT-MS analysis enables high-throughput, real-time testing of packaging materials for volatile impurities. Learn how SIFT-MS enhances quality control, supports recycled content screening, and offers real-time process monitoring with unmatched speed and sensitivity.

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Whitepaper

Automated Food-Flavor Analysis Using SIFT-MS

Unlock rapid, high-throughput aroma analysis with automated SIFT-MS. This whitepaper explores how leading food and flavor brands are transforming product development, quality control, and authenticity testing by replacing slow, complex workflows with direct, real-time VOC analysis.

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Whitepaper

Semiconductor Cleanroom AMC Monitoring

This whitepaper explores the limitations of traditional AMC detection methods and introduces Syft’s real-time, high-sensitivity solution for monitoring airborne molecular contaminants (AMCs) in semiconductor fabs. Learn how Syft’s AMC Guardian and Explorer systems deliver accurate, speciated measurements with sub-ppbV detection limits, enabling rapid contamination response and maximizing wafer yield.

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Whitepaper

Direct, Real-Time Aroma Analysis Using SIFT-MS

This whitepaper presents a powerful new approach to aroma analysis using SIFT-MS. Designed for flavor scientists, food technologists, and product developers, it showcases how SIFT-MS enables real-time, high-sensitivity measurement of aroma compounds directly from food, beverages, and personal care products. Unlike traditional GC-MS methods, SIFT-MS delivers immediate insights into aroma release dynamics—critical for quality control, product development, and sensory research. Discover how this technology is transforming the way we analyze and understand aroma.

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Application Note

Odor Pollution Monitoring

This application note showcases SIFT-MS for mobile monitoring of odor pollutants using SyftEnviro software for simple, reliable data collection. Aligning with China’s T/ACEF 156 – 2024 guidelines, it bridges the gap between objective chemical analysis and human odor perception for better odor impact assessment and regulatory compliance.

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Document

Smaller = Greener: Automated Headspace SIFT-MS Analysis Using 2-ML

This technical note explores the latest advancements in miniaturization and energy efficiency, highlighting how smaller electronic components contribute to a greener future. Learn how innovative design strategies reduce material usage, improve performance, and lower environmental impact. Perfect for engineers and sustainability advocates looking to optimize technology for a more sustainable world.

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Application Note

Automating SIFT-MS Part 3: Workflow Benefits

This technical note highlights the significant workflow advantages of automating SIFT-MS. By comparing SIFT-MS with conventional GC methods, it demonstrates how faster analysis times, reduced calibration demands, and simplified processes enhance productivity. The document explores the economic and operational benefits across various applications, including headspace analysis, multiple headspace extraction (MHE), and method of standard additions (MoSA). Ideal for laboratories seeking improved throughput and streamlined operations, this guide showcases the efficiency gains achievable with automated SIFT-MS systems.

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Application Note

Automating SIFT-MS Part 2: Analytical Approaches

This technical note explores automated analytical approaches using SIFT-MS. Building on Part 1, it covers applications such as static headspace analysis (SHA), multiple headspace extraction (MHE), the method of standard additions (MoSA), and continuous headspace analysis (CHA). Additional techniques include thermal desorption, solid-phase microextraction, and gas sampling bags, offering rapid and robust analysis of volatile organic compounds (VOCs). Ideal for laboratories seeking efficient workflows, SIFT-MS automation enhances throughput and accuracy across diverse sample types.

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Application Note

Monitoring of Ozone Photochemical Precursors

This app note explores real-time monitoring of ozone photochemical precursors, including VOCs and nitrogen dioxide (NO₂). Unlike traditional air quality monitoring methods, SIFT-MS enables rapid, continuous analysis with high sensitivity. Integrated with SyftEnviro software, this technology streamlines data collection, visualization, and interpretation, providing a powerful tool for environmental monitoring, air quality management, and regulatory compliance.

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Document

Optimized Calibration of Automated SIFT-MS Instrumentation: 1. Gas-Phase Analysis

This technical note details an optimized gas-phase calibration workflow for automated SIFT-MS. It highlights the benefits of automation in streamlining calibration procedures, reducing hazardous solvent use, and improving efficiency in volatile organic compound (VOC) analysis. The document outlines a step-by-step approach for single- and two-step dilution methods, instrument configurations, and data processing techniques. By minimizing reliance on costly third-party calibration standards, this method enhances sustainability and operational cost-effectiveness.

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