Optimised ICP-MS analysis helps improve analysis and can lead to better quality results.

Understanding interferences in AAS and techniques to mitigate against them during analyses

Knowing how to improve sensitivity in AAS to achieve better quality results from your analyses

GC-MS identifies unknowns through library searching, retention indices, deconvolution and spectral interpretation.

FTIR identifies unknown compounds through spectral library matching, isomer differentiation, quantitation and chemometric analysis.

LC-DAD identifies unknowns using spectral matching, peak purity assessment, retention times and isomer discrimination.

Understanding GC-MS spectral interpretation fundamentals improves compound identification beyond library search results.

Standard addition compensates for matrix effects, enabling accurate quantitation in complex analytical samples.

Hyper-dimensional datasets create false positives; QC filtering and multiple-testing corrections improve statistical reliability.