Automate Your Sample Analysis with Vacuum-Assisted HS-SPME

Iain Dallas

10th October 2023


Do you use Headspace Solid-Phase Microextraction (HS-SPME) to analyse your samples?

Have you ever encountered the challenges of prolonged extraction times and high extraction temperatures, which can potentially introduce unwanted artifacts into your final sample analysis?

If so, there is an additional parameter you can control and exploit during HS-SPME method optimisation. Applying vacuum conditions during sampling (Vacuum-assisted HS-SPME or Vac-HS-SPME) can allow you to speed up extraction kinetics, resulting in higher extraction efficiencies and sensitivities with shorter sampling times and at milder sampling temperatures.

Collaborations are crucial to driving innovation, and we at Element Lab Solutions value them greatly. Over the past two years, we have had the opportunity to work closely with Prof. Elia Psillakis to assess and implement vacuum-assisted headspace SPME in our solutions.

Vacuum-assisted HS-SPME methods use identical analytical instrumentation and settings of standard methods — the only extra step needed is the removal of air from the sample container prior to SPME. Air evacuation is usually performed manually, either using a gas-tight syringe to withdraw the volume of air from the sample vial or using a vacuum pump fitted with a connecting tubing with a Luer lock attachment to pierce the septum. A key component required to accommodate air evacuation and retain the vacuum during sampling is the use of custom-made vial closures, which ensure a gastight seal on standard headspace vials, post evacuation of air.

This approach is normally performed offline, prior to analysis, hence automation of the process would be significantly beneficial in reducing analyst touch time and offer a seamless online solution.

This work describes the development and testing of the automation of the air evacuation process using the GERSTEL Multipurpose Sampler and a selection of dedicated modules to perform the required tasks. The automated solutions were then tested to compare performances with the manual approach and evaluate robustness.

Discover the future of sample analysis — learn more about this automated solution by reading the app note.