The manual transfer of liquid standards and solutions is usually part of the daily activities throughout the analytical laboratory. For example, liquids must be transferred when creating calibration standard samples, pipetting solvents, and combining liquids. The accurate and precise transfer of liquids can be critical to the analytical results. Liquids with low boiling points or high viscosities pose several challenges to achieving accurate and precise delivery of desired volumes. Verifi cation of the volumes of liquids transferred would help verify the quality of the analytical procedure andensure the high quality of the resulting data.

The influence of variations in desorption temperature, desorption flow and sample preparation on VDA 278 analysis method [1] robustness and reproducibility is studied using a wide variety of samples from automobile interior materials: polypropylene (PP) granulate, polyurethane (PU) foam, leather, Duroplastic plastics and paint. It is shown that a temperature difference of just two degrees at 90 °C or at 120 °C can lead to an emission deviation of ± 20 percent. Also, desorption flow is shown to have significant influence on paint stripe emission values while there is little influence on samples like PP granulate.

Headspace gas chromatography (HS-GC) is frequently used for the analysis of aroma compounds in food due to its practical advantages of simplicity, amenability to full automation, less contamination from non-volatile constituents and elimination or reduction of solvent use. There are several established HS techniques, e.g. static headspace (SHS), dynamic headspace (DHS), and head space solid phase micro-extraction (HS-SPME). However, these techniques are more selective for volatile and/or hydrophobic compounds and result in a partial chromatogram with an under-representation of hydrophilic and/or low vapor pressure aroma compounds.

Rubber particles, sometimes derived from used tires, are used on artificial turf athletic fields, on playgrounds and as mulch. These particles can off-gas and leach compounds into the environment and may present a contact or inhalation hazard. Recent news reports in the US and Europe indicate a growing concern regarding potential health effects in athletes using these artificial turf fields.

Aroma Offi ce 2D (Gerstel K.K.) is an integrated software approach for simultaneous processing of both retention index (RI) and mass spectral (MS) data for rapid and improved identifi cation of fl avor compounds. The program can be integrated into Agilent Chemstation Software and searches are performed using CAS numbers of candidate compounds after library searching and corresponding automatically generated RI values. When MS signals are too weak to be used the software allows two RI values from orthogonal columns (after GC-O organoleptic evaluation) to be cross searched in the database. This offers a very useful additional identifi cation procedure for fl avor compounds.

One of the most important aspects of reducing pesticide exposure is monitoring of pesticide residues in foods. A number of analytical methods have been developed, many of them based on traditional liquid-liquid extraction in combination with GC-MS or LC-MS. The QuEChERS (quick, easy, cheap, effective, rugged, and safe) sample preparation methods have been developed to help monitor pesticides in a range of food samples [1]. The dispersive Solid Phase Extraction (SPE) used to clean up these extracts can leave co-extractants, which can result in interferences such as ion suppression with the analytical results.

IV bag components were analyzed for extractables using direct thermal desorption/thermal extraction combined with a unit mass resolution GC/MSD system. The results ...

In metabolomics studies, large sample sets have to be analyzed to allow statistical differentiation of sample types. Obviously, repeatability of the whole analytical workflow, including sample preparation, sample introduction, separation and detection, is hereby of the utmost importance. In this respect, automation of the sample preparation is very useful in order to reduce the analytical variability.

In metabolomics studies, large sample sets have to be analyzed to allow statistical differentiation of sample types. Obviously, repeatability of the whole analytical workflow, including sample preparation, sample introduction, separation and detection, is extremely important in order to achieve such a differentiation. Automating the sample preparation workflow is a very useful first step towards reducing analytical variability.

Liquid-liquid extractions have long been performed manually and are used to extract and concentrate analytes from aqueous matrices. Inclusion of liquid-liquid extraction ...