I'm a chemist with some rudimentary programming skills (getting started with python) and in the middle of the year I'll be starting a Ph.D. project that uses computers to describe magnetism in molecular systems.
Most of the time I get my results after several simulations and experiments, so, I know that one of the hardest tasks in molecular magnetism is to predict the nature of magnetic interactions. That's why I'll try to tackle this problem with Machine Learning (because such interactions are dependent, basically, of distances, angles and number of unpaired electrons). The idea is to feed the computer with a large training set (with number of unpaired electrons, XYZ coordinates of each molecule and experimental magnetic couplings) and see if it can predict the magnetic couplings (J(AB)) of new systems: (see example in the attached image) Can Scikit-Learn handle the task, knowing that the matrix used to represent atomic coordinates will probably have a different number of atoms (because some molecules have more atoms than others)? Or is this a job better suited for another software/approach? -- *Henrique C. S. Junior* Industrial Chemist - UFRRJ M. Sc. Inorganic Chemistry - UFRRJ Data Processing Center - PMP Visite o Mundo Químico <http://mundoquimico.com.br>
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