New High-Performance HS-20 Series Headspace Samplers Provide Reliable and Robust Solution for Volatile Compound Analyses
Shimadzu Scientific Instruments has launched the HS-20 Series of headspace samplers, which provides a reliable and robust headspace solution for any application analyzing volatile components in a difficult matrix. The HS-20 Series consists of two models: a Loop model for the traditional static headspace methods, and a Trap model, which adds the dynamic headspace technique for applications requiring greater sensitivity.
The HS-20 Series achieves a new industry standard for repeatability through precise control of gas flow rates, and a mechanism that allows a sample vial to enter the oven from the bottom. This technique minimizes heat loss and thermal instability during the equilibration step. The oven can be heated to 300 °C, enabling accurate analysis of higher-boiling compounds. Additionally, both models have been engineered with a short, inert sample pathway to minimize carryover from one sample to the next.
The HS-20 Series tray holds up to 90 sample vials. It accommodates both 10-mL and 20-mL headspace vials within the same sequence without the need for special attachments. The open architecture of the HS-20 tray provides easy access to all vials for loading and enables stress-free maintenance from the top of the instrument for improved productivity and minimal downtime.
The automated shutdown feature switches the system to standby at the end of a sequence to save on electricity and carrier gas. An optional barcode reader records sample ID for reliable traceability. The HS-20 headspace sampler is also compliant with CFR 21 Part 11 through LabSolutions chromatography data system.
The HS-20 Series has been proven in a wide variety of headspace applications, such as analysis of residual solvents in pharmaceutical products, determination of blood alcohol, QA/QC of foods and beverages, competitive analysis of the essential ingredients in flavor/fragrance samples, and quantitation of VOCs in environmental matrices.