Congrats to all the co-authors: Finja Krebs, Holger Zagst, Matthias Stein, Ratih Ratih, Robert Minkner, Mais Olabi, Sophie Hartung, Christin Scheller, Blanca H. Lapizco-Encinas, Cari S. van de Griend, and Hermann Wätzig. Electrophoresis 44 (2023) 1279–1341
This work leverages the complexity of hydrogen-bond interactions to develop functional deep eutectic solvents, defined as those formed by molecules with specific functionality (antioxidants, in this case). Specifically, the proposed strategy utilizes established machine learning models to sequentially predict what antioxidants are likely to form synergistic mixtures and then, select predict which mixtures would also…
Besides showing some of the results collected during the last year, this event is a great opportunity to interact with incoming students, other groups, and colleagues. Functional Deep Eutectic Solvents to Boost Antioxidant Synergism in Edible Fats Emmanuel D. Dike, Lucas B. Ayres, Tomas E. Benavidez, Jorge Barroso, Vagner B. dos Santos and Carlos D.…
Thanks to Vagner’s team for the opportunity to collaborate and write a review on Combining Digital Imaging and Quantum Dots for Analytical Purposes, published by Analytical Methods.
Thanks for the opportunity to share some of our results linked to the use of AI in chemistry
Congrats to Justin on his first paper ever! The publication “Deciphering Antioxidant Interactions via Data Mining and RDKit” will soon appear in the journal Scientific Reports.
We described a model that can predict melting points of DES with an accuracy of 98% and that can be applied to DES based on halogen bonding.
Besides enabling the detection of S. aurus and COVID-19, we described a simple strategy to address cross-talk and analyze up to 48 droplets within ~8 min using amperometry.
Collaboration with the Brazilian Nanotechnology National Library leads to spike- and crown-like nanostructured microelectrodes (SC-NMEs).
Incredibly proud of the latest graduate from the lab 🙂
