Bridging theoretical chemistry with computational modeling

Chemolytica exists as a bridge between theoretical chemistry and computational science. It serves as a lens that sharpens and reinforces what we see in the lab.

Chemolytica exists to make that lens more accessible, to encourage more people to combine molecular modeling fundamentals with modern techniques such as machine learning. 

Chemolytica exists to help you go beyond the surface of molecules, to see through the “black box”, to make sense of the algorithm, and to develop a deep and profound fascination with the field of computational chemistry.

Chemolytica exists not only as a platform but as a commitment to new ways of thinking — one where chemistry and computation work together to push the boundaries of discovery.

I’m Martin Solomon, currently an undergraduate BS Chemistry student at the University of the Philippines – Los Baños. My current interests lie in reinforcement learning, stochastic processes, Monte Carlo, as well as density functional theory.

I made this website to document my learning journey in computational chemistry and to share what I know with the public. I also want to share insights and summaries of research I’ve read, comments on AI in science, and tools I use for my personal projects.

As such, this website is a place where I organize my thoughts, record what I learn, and develop ideas at the intersection of chemistry and computation.