Ep. 48: From Fortran to Field Flow Fractionation

Welcome to “Analytically Speaking,” the podcast from LCGC International and Spectroscopy.
In this episode, podcast co-hosts Dr. Dwight Stoll and Dr. James Grinias talk with Dr. Mark Schure, who has worked in separation science for over 35 years in both industry and academia. Over a 28-year period, he worked for Digital Equipment Corporation, the Rohm and Haas Company, and the Dow Chemical Company. Since then, he has served as Chief Technology Officer for Kroungold Analytical, and he has been an adjunct professor in the Department of Chemical and Biomolecular Engineering at the University of Delaware for over 20 years. Dr. Schure is a widely recognized expert in separation science who has published more than 110 papers, holds numerous patents, and edited the book Multidimensional Liquid Chromatography. His scientific interests encompass the fundamental separation science of complex molecules, polymers, and colloids, alongside 2D chromatography, retention mechanisms, and field flow fractionation. He has received numerous accolades, including the Eastern Analytical Symposium Award in Separation Science and the Uwe Neue Award from the HPLC conference.
In a wide ranging conversation recorded live at the HPLC 2026 conference in Indianapolis following a memorial session for Prof. Peter Carr, we explore Mark’s unique entry into separation science, which benefited from prior experiences building amplifiers and electronics before transitioning to write Fortran software as a consultant for chemists at Northeastern University. We then discuss Mark’s foundational simulation work in field flow fractionation (FFF), including his approaches to modeling Coriolis effects and sedimentation. We also spend some time talking about Mark’s pioneering theoretical contributions to 2D chromatography on topics including sampling rate and detection limits. Finally, Mark shares his perspective on the intense inter-diffusion of information between his modeling group and Pete Carr and Ilja Siepmann at the University of Minnesota, the future of analytical chemistry, the need for improved analytical strategies for complex matrices like exosomes, and the potential for artificial intelligence to help identify unknown compounds in complex mixtures.