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We use a variety of computational chemistry tools based on quantum mechanics and statistical mechanics in our research. These tools give us:

  • Qualitative frameworks for thinking about molecular processes and mechanisms
  • Quantitative understanding of different molecular driving forces
  • Prediction of properties or molecular architectures for engineering design

Often, we will want to know as precisely as possible the structure of a few atoms in a small molecule. It is hard to visualize small systems at the nanoscale, especially when they are still conceptual and/or yet to be synthesized. Quantum mechanics allows us to calculate electronic energy levels (e.g., recall the particle in a box) of many-body systems, with Schrödinger's equation as the basis for these calculations. An exciting and current application is understanding how molecules absorb photons and excite electrons to higher energy states and predicting which structural changes can enhance these processes, which opens up many possibilities for photochemical energy production.

However, we also want to know how these systems behave over length and time scales that are not always accessible with quantum mechanics. For example, even though we can calculate electrical properties of materials, we have not yet discussed how to effectively calculate thermal properties of materials. This is because we need a tool to link calculated energies at the atomic or molecular scale with temperatures at the macroscopic scale. (Similarly, we need to link atomic or molecular scale forces with macroscopic pressures.) Statistical mechanics enables us to perform temporal or spatial averages over a large number of simulations to obtain these macroscopic observables. Ultimately, we aim to predict multi-scale properties that may be used to guide materials design for efficient and/or high-yield energy conversion.

Our current projects include:

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