Near-infrared spectroscopy was utilized as a polymorph
screening method. A model compound (sulfathiazole) was
recrystallized from various solvents, and the crystals were
milled using a planetary ball mill and compressed using
a hydraulic press. The polymorphism of recrystallized and
processed samples and the effect of processing on the
polymorphism of sulfathiazole was studied by near-infrared (NIR) spectroscopy and verified by X-ray powder
diffraction (XRPD) and thermal analysis. Polymorphism
and the degree of crystallinity of the processed samples
were studied, and NIR spectroscopy proved to be a fast
tool for polymorph screening and monitoring the processing-induced transformations. After clustering of the NIR
spectra of various samples, XRPD and complementary
methods can be applied to a more thorough analysis of
different clusters. This approach provides a timesaving
improvement for the polymorph analysis in the case of
large number of samples.
Multi-model ensembles for sea surface temperature (SST), sea surface salinity (SSS), sea surface currents (SSC), and water transports have been developed for the North Sea and the Baltic Sea using outputs from several operational ocean forecasting models provided by different institutes. The individual models differ in model code, resolution, boundary conditions, atmospheric forcing, and data assimilation. The ensembles are produced on a daily basis. Daily statistics are calculated for each parameter giving information about the spread of the forecasts with standard deviation, ensemble mean and median, and coefficient of variation. High forecast uncertainty, i.e., for SSS and SSC, was found in the Skagerrak, Kattegat (Transition Area between North Sea and Baltic Sea), and the Norwegian Channel. Based on the data collected, longer-term statistical analyses have been done, such as a comparison with satellite data for SST and evaluation of the deviation between forecasts in temporal and spatial scale. Regions of high forecast uncertainty for SSS and SSC have been detected in the Transition Area and the Norwegian Channel where a large spread between the models might evolve due to differences in simulating the frontal structures and their movements. A distinct seasonal pattern could be distinguished for SST with high uncertainty between the forecasts during summer. Forecasts with relatively high deviation from the multi-model ensemble (MME) products or the other individual forecasts were detected for each region and each parameter. The comparison with satellite data showed that the error of the MME products is lowest compared to those of the ensemble members.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.