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Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.
One of the great strengths of X-ray computed tomography over conventional inspection methods (ultrasound, thermography, radiography) is that it can image damage in 3D. However for curved or deformed composite panels, it can be difficult to automatically ascribe the damage to specific plies or inter-ply interfaces. An X-ray computed tomography (CT) data processing methodology is developed to extract the through-thickness distribution of damage in curved or deformed composite panels. The method is applied to [(0°/90°)2]s carbon fibre reinforced polymer (CFRP) panels subjected low velocity impact damage (5 J up to 20 J) providing 3D ply-by-ply damage visualisation and analysis. Our distance transform approach allows slices to be taken that approximately follow the composite curvature allowing the impact damage to be separated, visualised and quantified in 3D on a ply-by-ply basis. In this way the interply delaminations have been mapped, showing characteristic peanut shaped delaminations with the major axis oriented with the fibres in the ply below the interface. This registry to the profile of the panel constitutes a significant improvement in our ability to characterise impact damage in composite laminates and extract relevant measurements from X-ray CT datasets.