ArticleJournal of separation science2026
Prediction of Thermal Modulated Comprehensive Two-Dimensional Gas Chromatographic Separation Using a Modular, Graph-Based Simulation Platform.
Article in Journal of separation science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Prediction of Thermal Modulated Comprehensive Two-Dimensional Gas Chromatographic Separation Using a Modular, Graph-Based Simulation Platform.Journal of separation science · 2026Article
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Authors and funding
3 authors.
Funding
Abstract
Comprehensive two-dimensional gas chromatography (GC×GC) offers exceptional separation performance, but method development remains time-consuming and sensitive to numerous system parameters. In this study, we present a modular simulation framework for GC×GC systems with thermal modulation, implemented in the open-source Julia package GasChromatographySystems.jl. The simulation is based on a graph-based abstraction of the GC system and models solute migration through column and modulator modules using previously established retention models. A simplified but effective model for thermal modulation enables the generation of realistic two-dimensional retention times and peak widths. Simulation results were validated against experimental measurements from a GC×GC-ToF-MS system using different modulation periods and temperature programs. Systematic deviations between simulated and measured retention times could be explained and corrected by adjusting parameters such as the actual modulation period and modulator shift. The final model achieved root mean squared error (
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Registered trials
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