New research into flow modulation methods in valve-based two-dimensional gas chromatography (GC×GC) has produced an effective alternative to traditional pulse modulation.1 Described as “pattern modulation”, this new method increases effluent to the secondary column with flow rates compatible with most chromatographs and spectrometers.
Photo Credit: John Lund/Getty Images
New research into flow modulation methods in valve-based two-dimensional gas chromatography (GC×GC) has produced an effective alternative to traditional pulse modulation.1 Described as “pattern modulation”, this new method increases effluent to the secondary column with flow rates compatible with most chromatographs and spectrometers.
Researcher John Seeley from Oakland University in Rochester, Michigan, USA, said the new approach is easy to implement with existing instrumentation. “Pattern modulation can be produced with the exact same valve-based hardware used to conduct conventional pulse modulation separations”, he said, “and requires only simple software commands”.
Standard gas chromatographs require a modulator to produce comprehensive separations. These modulators convert effluent peaks emerging from the primary column into a series of sharp pulses injected into the secondary column. However, pulse generation with valve-based modulation requires a large increase in secondary column flow rate or only a small amount of primary effluent being transferred to the secondary column.
Today, most GC×GC separations are performed with thermal modulation, but that is an expensive approach. As Seeley commented, “When cost is not a factor thermal modulation will provide the best performance. But when resources are tight, valve-based modulation in all of its forms can be an extremely effective tool for generating high–resolution separations.”
Unlike pulse modulation, where narrow pulses are injected, pattern modulation uses an intricate injection pattern. This approach allows the majority of the primary effluent to reach the secondary column. However, the detector signal generated from this process must be transformed to extract a conventional pulsed signal. This is key to the analysis.
Initial results using pattern modulation were incredibly positive, but the research recognizes that there is a point where the complexity of the sample can overwhelm the signal transformation process. At this point, traditional pulse modulation is preferred.
Currently, Seeley and his team are trying to establish quantitatively when pattern modulation is superior to pulse modulation. He said, “We want to be able to recognize when pattern modulation is the best alternative for producing valve-based GC×GC separations”. - L.B.
Reference
J.V. Seeley and S.K. Seeley, J. Chrom. A1421, 114–122 (2015).
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.