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Here’s a list of past and recent research projects

Learn electronic structures with Quantum Machine Learning

This project involves applying machine learning approaches to learn the most useful object: the electronic structure. Check out our latest paper on this, and our code QMLearn.

Ground State and Time-dependent Orbital-Free Density Functional Theory

This project involves the development of novel nonlocal noninteracting kinetic energy functionals for bulk, semi-infinite and finite systems (such as nanoparticles). Code development in DFTpy and eDFTpy (to be released).

Subsystem Time-Dependent Density Functional Theory

This project involves the development of a real-time TDDFT algorithm for treating molecules and materials interacting with metal and semiconducting surfaces. This project takes place in our own embedded Quantum-ESPRESSO and eDFTpy (to be released) softwares.

Non-Adiabatic Dynamics with Subsystem DFT and Mean Field Excited States Methods

This project involves the development of electronic structure methods to carry out non-adiabatic molecular dynamics simulations in the framework of subsystem DFT and eXcited Constrained DFT (XCDFT). The code development for this project takes place in ADF, embedded Quantum-ESPRESSO, QEpy and eDFTpy suites of software.

The new methods are being applied to a range of problems:

  1. Polaritonic chemistry
  2. Plasmonics
  3. Organic-Metal and Organic-Semiconductor interfaces

Many Body Effects on Optical Properties and Dispersion Interactions

This project involves the development of non-local orbital-free and orbital-dependent embedding potentials for the correct treatment of (many-body) interactions between subsystems.