MTCiting: Academia R&D

In a novel system, lab scale electrosynthesis of methanol oxidation to formate is performed in “feed and bleed” mode and compared to batch and single-pass methods. Key factors such as the feed flow rate and the electrolyte volume are investigated, and online FTIR monitors product concentration to provides quantitative insight on the flow cell operating characteristics. (ReactIR)

Baessler, J., Wehner, M., Mohseni, M., Neumann, J., Wessling, M., & Keller, R. (2025). Feed and Bleed Operating Mode for electrochemical flow cells: Challenges, solutions and practical insights. ChemElectroChem. https://doi.org/10.1002/celc.202500034

Sulfur(IV) fluorides can covert carboxylic acids to reactive intermediates and thus have potential as peptide coupling agents. This work synthesizes and captures key acyl fluorosulfite intermediates for peptide couplings without epimerization or column chromatography for purification. In mechanistic studies, in-situ FTIR measurements compare the dipeptide formation rate between starting from the acyl fluoride and starting from the free acid, ruling out a predominant acyl fluoride pathway. (ReactIR)

Lai, J., Bahri, C., Truong, M. P., Downey, K. T., & Sammis, G. M. (2025). Rapid peptide synthesis using a methylimidazolium sulfinyl fluoride salt. Communications Chemistry, 8(1). https://doi.org/10.1038/s42004-025-01456-8

Solid-liquid slurries are important in the pharmaceutical and chemical industries but the lack of real-time analytical methods to investigate these systems makes optimization and control problematic. This work uses orthogonal PAT methods including on-line HPLC and in-situ microscopic imaging for mechanistic insight that enables the optimization of the heterogeneous synthesis reaction of tetrabenazine. (DirectInject-LC, EasySampler, EasyViewer)

Sato, Y., Liu, J., Kukor, A. J., Culhane, J. C., Tucker, J. L., Kucera, D. J., Cochran, B. M., & Hein, J. E. (2021). Real-Time monitoring of Solid–Liquid slurries: Optimized synthesis of tetrabenazine. The Journal of Organic Chemistry, 86(20), 14069–14078. https://doi.org/10.1021/acs.joc.1c01098

Real-time monitoring of a cephalexin crystallization process is implemented using a computer vision model based on a convolutional neural network (CNN) in conjunction with an in-situ imaging probe. The goal is to create a tool for continuous pharmaceutical manufacturing processes that can examine in-situ images in order to monitor the state of a slurry, as well as detect, locate and inform about the presence of undesired crystals in the heterogenous mixture. (EasyViewer)

Salami, H., McDonald, M. A., Bommarius, A. S., Rousseau, R. W., & Grover, M. A. (2021). In Situ Imaging Combined with Deep Learning for Crystallization Process Monitoring: Application to Cephalexin Production. Organic Process Research & Development, 25(7), 1670–1679. https://doi.org/10.1021/acs.oprd.1c00136

This story was part of the METTLER TOLEDO AutoChem #MTCiting series. In this series we dive into the latest published research on innovative applications in research & development.

See other #MTCiting stories where we examine groundbreaking research that improves process safety and efficiency and contributes to sustainability in chemical manufacturing.