Josef Heiland Receives Eberhard Gerstel Award
Josef Heiland has been awarded the 2018 Eberhard Gerstel Prize for his publication “Temperature Gradient Elution and Superheated Eluents in Chip-HPLC” (1), which was published in the journal Analytical Chemistry.
Photo Credit: Gerstel GmbH & Co.KG
Josef Heiland has been awarded the 2018 Eberhard Gerstel Prize for his publication “Temperature Gradient Elution and Superheated Eluents in Chip-HPLC” (1), which was published in the journal Analytical Chemistry.
The Eberhard Gerstel Prize is awarded by the Working Group Separation Sciences of the Analytical Division of the German Chemical Society for an outstanding publication in the field of separation sciences and is handed out in honour of the late Eberhard Gerstel Sr., founder of Gerstel.
In his work, Heiland presented a novel concept of temperature programmed microchip HPLC. The paper explains that because of the relatively low mass of the lab-on-a-chip hardware, it is well suited for temperature programming. This means that isocratic separations can be performed at a speed not previously achieved even using pure water and it opens up the possibility of using other environmentally friendly eluents such as supercritical CO2 and ethanol.
In order to be considered for the prize named after the Gerstel company founder, Eberhard Gerstel (1927–2004), scientists can apply in person or their candidature can be proposed by others. The selection of the prize winner is performed by a jury of five internationally renowned scientists. The next round of applications for the 2020 Eberhard Gerstel Prize will be opened in 2019.
For more information, please visit: www.gerstel.com
Reference
- J.J. Heiland, C. Lotter, V. Stein, L. Mauritz, and D. Belder, Anal. Chem.89(6), 3266–3271 (2017).
GC–TOF-MS Finds 250 Volatile Compounds in E-Cigarette Liquids
November 1st 2024A study has used gas chromatography coupled to a time-of-flight mass spectrometer to build an electron ionization mass spectra database of more than 250 chemicals classified as either volatile or semi-volatile compounds. An additional, confirmatory layer of liquid chromatography–mass spectrometry analysis was subsequently performed.
AI and GenAI Applications to Help Optimize Purification and Yield of Antibodies From Plasma
October 31st 2024Deriving antibodies from plasma products involves several steps, typically starting from the collection of plasma and ending with the purification of the desired antibodies. These are: plasma collection; plasma pooling; fractionation; antibody purification; concentration and formulation; quality control; and packaging and storage. This process results in a purified antibody product that can be used for therapeutic purposes, diagnostic tests, or research. Each step is critical to ensure the safety, efficacy, and quality of the final product. Applications of AI/GenAI in many of these steps can significantly help in the optimization of purification and yield of the desired antibodies. Some specific use-cases are: selecting and optimizing plasma units for optimized plasma pooling; GenAI solution for enterprise search on internal knowledge portal; analysing and optimizing production batch profitability, inventory, yields; monitoring production batch key performance indicators for outlier identification; monitoring production equipment to predict maintenance events; and reducing quality control laboratory testing turnaround time.
Multivariate Design of Experiments for Gas Chromatographic Analysis
November 1st 2024Recent advances in green chemistry have made multivariate experimental design popular in sample preparation development. This approach helps reduce the number of measurements and data for evaluation and can be useful for method development in gas chromatography.
