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Theoretical & Computational Chemistry

Read about my work in developing data-driven many-body energy
(MB-nrg) potential energy functions (PEFs) to study large molecular systems 


Data-driven many-body energy (MB-nrg) potential energy functions (PEFs) provide predictive molecular models for large systems with quantum mechanical accuracy, positioning them as a powerful tool in investigating structural, thermodynamic, dynamical, and spectroscopical properties of generic molecular systems from the gas to the condensed phase.

Alongside my mentor Ruihan Zhou, I am developing the first MB-nrg PEF for a ring-molecule, phloroglucinol, a highly effective organic ice nucleator. A thorough understanding of phloroglucinol’s ice-binding mechanism would allow us to harness its natural properties to promote ice crystallization through applications like weather engineering, and more efficient thermal storage techniques.


Many-Body Potential Energy Function

The many-body expansion (MBE) decomposes the energy of a system of N monomers into a summation over n-body contributions:

MBE converges quickly for nonmetallic systems, so we can approximate the two body PEFs as:

                       are 2-body electrostatics and dispersion describing the classical 2B effects with simple functional forms.

          accounts for the classical many-body polarization.

            is machined learned with permutationally invariant polynomials (PIPs) (MB-nrg) trained from ab-initio data to characterize the short-range quantum mechanical many-body effects. A generalized expression for n-Body PIP adopts the following functional form:

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The 1-body PHG PEF is developed with machine learned degree-2 MB-nrg PIP with 219 terms and describes the energetics of an isolated phloroglucinol molecule with high accuracy

For 2-body PHG-H2O interactions, a machine learned degree-3 MB-nrg PIP with 2,164 terms shows the best agreement with reference method

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Our MB-nrg model accurately reproduces the binding energy curve of DF-MP2/AVQZ for PHG

Future Directions

In our study of ice-nucleating organic crystals, this PEF will be used to develop a comprehensive description of ice-binding molecules’ interaction with water, their ice-binding sites, and the kinetics of ice nucleation and antifreeze behavior via simulations that model the behavior of a monolayer of phloroglucinol molecules at the interface between water and ice

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