PTC Seminar: Feb 8, 2022

Date: February 8, 2022 2:00 pm (ET)


  • Letitia Birnoschi
    University of Manchester
  • Irina Paci
    University of Victoria


Letita Birnoschi

Letitia Birnoschi
University of Manchester

HYPERION: a new computational tool for relativistic hyperfine coupling constants based on CASSCF-SO

Abstract: Magnetic resonance techniques are able to accurately probe the interactions between electron spins, nuclear spins and external magnetic fields; this information is encoded in a set of effective spin Hamiltonian parameters. Of particular interest are hyperfine coupling constants (HFCCs), which display a strong dependence on the unpaired electron (spin) density, thus providing important insight into chemical bonding.

Our aim is to devise a computational methodology for determining relativistic, picture-change-corrected HFCCs for chemical systems of arbitrary size and complexity. With this in mind, we developed HYPERION, a Python-based program that computes fully-decoupled magnetic resonance parameters from active space wavefunctions, with or without spin-orbit coupling (SOC) included variationally. Herein, we demonstrate the use of HYPERION to obtain HFCCs of selected atoms, based on electronic structure data from OpenMolcas. Our results are in excellent agreement with experimental data from atomic spectroscopy, as well as theoretical predictions from 4-component calculations.

Biography: Letitia completed her undergraduate studies (BA/MSc) at The University of Cambridge, where she studied Natural Sciences. For her MSc project, she worked on the development of stochastic electronic structure methods under the supervision of Dr Alex Thom. Letitia did her PhD in the group of Prof Nicholas Chilton at the University of Manchester. Her project involved the development of a computational toolbox for calculating magnetic resonance properties from ab initio electronic structure data


Irina Paci
University of Victoria

Theoretical Investigations of Nanocomposite Materials for Dielectric Applications

Abstract: Nanocomposite materials combine the versatility of a traditional matrix material (polymer, oxide, ceramic) with the adaptable field-response properties of metallic nanoparticles. New materials with distinct and sometimes highly tunable properties can be thus obtained. A small volume fraction of nanosized particles incorporated in a host material will significantly alter physical, chemical, and mechanical properties. Ag and Au nanoparticles are an effective way to enhance the complex permittivity of high-k oxides and polymers; however, the scale of many modern devices pushes inclusion dimensions below the metal–insulator transition at ~ 2 nm. In this talk, I describe how large-scale quantum mechanical methodologies can be used to obtain the dielectric and optical response in these molecular-scale nanocomposites. Our methodology also allows partitioning of the response into inclusion and matrix contributions. Our group’s efforts in this area and thoughts for efficiently improving computation times will be discussed.

Biography: Professor Paci has been doing research in Theoretical and Computational Chemistry over the past 20 years. She grew up and completed her BSc in Iasi, Romania. She then moved to Canada to do her PhD in the Cann group at Queen’s University, in Kingston, Ontario, Canada, developing Integral Equation Theories for liquids with low symmetries such as chiral liquids and nematic liquid crystals. In 2004, Dr. Paci moved to Northwestern University, where she worked with Mark Ratner on a number of projects including singlet fission processes for solar cells, self-assembled nanodielectric materials, and pattern assembly in dip-pen nanolithography.

In 2007, Dr. Paci started her independent career at the University of Victoria, where her research focuses on optimizing theoretical and computational methods for large complex systems. Her group investigates the behaviour of molecules physisorbed or chemisorbed on metallic substrates, combining quantum investigations of local binding and structures, to bulk simulations including Monte Carlo and mean field models, in order to capture the relevant length and interaction scales. A second research direction in the Paci group is dielectric nanocomposite simulation and design, with a focus on both determining appropriate theoretical methodologies for predicting the dielectric response of metal/metal oxide or metal/polymer nanocomposite materials and on optimizing the inclusion/matrix pair for charge storage, energy storage and other dielectric applications. In more recent years, the group has also been working on developing hybrid Monte Carlo / Molecular Dynamics methodologies for capturing the effect of induced fit on the selection of optimal ligand in protein/ligand docking simulations.