Caltech Postdoc L(a)unch Seminar

Dr. Prabhat Prakash
Some History and Some Frontiers of Atomistic Models of Water

Atomistic models of water play a crucial role in understanding its unique properties in a variety of physical, chemical and biomolecular processes. Classical models, such as SPC/E, TIP4P, and TIP5P, approximate water molecules using rigid structures and empirical potential functions, while ab-initio methods provide quantum mechanical insights into electronic interactions. In the recent times, reactive models integrating machine learning techniques have been developed to enhance accuracy and to lower computational cost. In my talk, I will discuss partly the history of these developments and partly some advances achieved from physics-based and machine-learned models in the last few decades.

Dr. Sabrina Wahler
Putting an End to the Handcuffs of the Periodic Table: Using Atomic Features for Predicting Detonation Velocity

In this study, a Gaussian process regressor is used to predict the detonation velocity. As features atomic values were used, which allows the application of the model to explosives of any elemental compositions. This approach does not require reparameterization for every element and can provide useful estimations for the detonation velocity of explosives. For initial validation purposes, this study will interpolate from materials containing elements from the first and second periods to explosives-containing materials in the third period.

For more information, please contact Sejun Kim by email at [email protected] or visit this link to fill up the form and nominate yourself as a speaker.

Lunch will be served at 11:45 AM