Generating realistic data through modeling and parametric probability for the numerical evaluation of data processing algorithms in two-dimensional chromatography.

Background: Comprehensive two-dimensional chromatography generates complex data sets, and numerous baseline correction and noise removal algorithms have been proposed in the past decade to address this challenge. However, evaluating their performance objectively is currently not possible due to a lack of objective data.

Result: To tackle this issue, we introduce a versatile platform that models and reconstructs single-trace two-dimensional chromatography data, preserving peak parameters.

Comprehensive two-dimensional gas chromatography- A discussion on recent innovations.

Although comprehensive 2-D GC is an established and often applied analytical method, the field is still highly dynamic thanks to a remarkable number of innovations. In this review, we discuss a number of recent developments in comprehensive 2-D GC technology. A variety of modulation methods are still being actively investigated and many exciting improvements are discussed in this review.

Detection of nanoparticles in Dutch surface waters.

Nano-enabled consumer products are a likely source of nanoparticles in the environment and a number of studies have shown the release of nanoparticles from commercial products. Predicted environmental concentrations have been calculated but there is a need for real measurement data to validate these calculations. However, the detection of engineered nanoparticles in environmental matrices is challenging because of the low predicted environmental concentrations which may be in the ng/L range.