This paper, in collaboration with the Colón group, demonstrates the capability of Gaussian processes to correlate and predict physicochemical properties from sigma profiles. The new approach outperforms state-of-the-art neural networks from earlier studies and, most importantly, can be navigated using standard algorithms to find compounds having desired properties. Check it out here! https://doi.org/10.1073/pnas.2404676121
Author: Edward
Ryan, Ning, Dinis, and Yinke all graduate!
Ryan Smith, Dinis Abranches, and Ning Wang received their PhD degrees this spring, while Yinke Jiang received his MS degree. Congratulations all!
Congratulations, Ning and Dinis!
Ning Wang and Dinis Abranches both recently passed their candidacy exams. Congratulations!
Ning’s first paper in the group was published in the Journal of Ionic Liquids
Ning Wang’s first publication from our group was just published in the Journal of Ionic Liquids. In collaboration with Yong Zhang, Ning developed a force field for the two isomers of the FAP anion and then performed simulations of the ionic liquid [C6C1im][FAP]. She looked at the effect the relative concentration of the two [FAP] isomers has on properties (not much) and calculated several other physical properties. Nice work, Ning!
ACS Green Chemistry and Engineering Conference
Ning Wang, Ryan Smith, and Ed Maginn traveled to Reston, VA in June to present at the ACS Green Chemistry and Engineering Conference. We presented in a special symposium dedicated to various aspects of refrigeration and cooling technologies. Many members of our team planning for an NSF ERC project gathered to work on the proposal. The photo above shows some of us at lunch during a break in the meeting.
Two new PhD graduates!
The two latest PhD graduates of the group officially received their degrees. Congratulations to Dr. Haimeng Wang and Dr. Derrick Poe!
Dinis has his first group paper published in Chem. Comm.
Dinis Abranches published his first paper in our group in Chemical Communications. The paper shows how sigma profiles can be used as a powerful and general molecular descriptor in deep learning. The sigma profiles of 1432 compounds are used to train convolutional neural networks that accurately correlate and predict a wide range of physicochemical properties. The architectures developed are then exploited to include temperature as an additional feature. The work is a joint effort between our group and Prof. Colón’s. Congratulations Dinis!
Derrick defends his PhD thesis!
Derrick Poe successfully defended his PhD thesis entitled “Modeling Deep Eutectic Solvents: Linking Macroscopic Behavior and Molecular Level Features”. He will be leaving soon to take a postdoc position at Argonne National Lab. Congratulations, Derrick!
Group alumnus Cassiano Aimoli gives special seminar
Dr. Cassiano Aimoli (group alumnus, 2012-2014), a technical leader at the Brazilian oil company Petrobras, stopped by campus to give a special seminar to COMSEL on chemical engineering opportunities in the oil industry. It was great to have him visit the lab!
Haimeng Wang defends PhD thesis
Haimeng Wang successfully defended his PhD thesis “Molecular Dynamics Simulations of Molten Salts: Force Field Evaluation and Development” today. He was the first person in the group to work on molten salts, and was a key element of the modeling and simulation team of our EFRC “Molten Salts in Extreme Environments (MSEE)”. Haimeng is moving on to take a postdoc position at Argonne National Lab. Congratulations, Haimeng!