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Sample preparation for mass spectrometry is used for the optimization of a sample for analysis in a mass spectrometer (MS). Each ionization method has certain factors that must be considered for that method to be successful, such as volume, concentration , sample phase, and composition of the analyte solution.
Standard solutions are generally prepared by dissolving a solute of known mass into a solvent to a precise volume, or by diluting a solution of known concentration with more solvent. [1] A standard solution ideally has a high degree of purity and is stable enough that the concentration can be accurately measured after a long shelf time. [2]
GC–MS is used for the analysis of unknown organic compound mixtures. One critical use of this technology is the use of GC–MS to determine the composition of bio-oils processed from raw biomass. [29] GC–MS is also utilized in the identification of continuous phase component in a smart material, magnetorheological (MR) fluid. [30]
Software by SpectralWorks for vendor-independent 'Open Access' client/server-based solutions to provide a "walk-up and use" LC-MS and GC-MS data system. Instrument control and data processing support for multiple vendors' hardware. NMR instrumentation and data processing are also supported. Scaffold Proprietary
Suppose there are known concentrations of nickel in a set of calibration solutions: 0 ppm, 1.6 ppm, 3.2 ppm, 4.8 ppm, 6.4 ppm, and 8 ppm. Each solution also has 5 ppm yttrium to act as an internal standard. If these solutions are measured using ICP-OES, the intensity of the yttrium signal should be consistent across all solutions.
Mixing of the isotopic standard with the sample effectively "dilutes" the isotopic enrichment of the standard and this forms the basis for the isotope dilution method. Isotope dilution is classified as a method of internal standardisation, because the standard (isotopically enriched form of analyte) is added directly to the sample. In addition ...
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For example, the ionic strength of the solution can have an effect on the activity coefficients of the analytes. [3] [4] The most common approach for accounting for matrix effects is to build a calibration curve using standard samples with known analyte concentration and which try to approximate the matrix of the sample as much as possible. [2]