arXiv subjects

Tim Duong

Publications and source records attributed to Tim Duong.

5 recordsLinked to original sources

arXiv2026

Nuclear-Electronic Quantum Dynamics in a Plasmonic Nanocavity

Plasmonic nanocavities are a promising platform for strong light-matter coupling and enhanced spectroscopies at the single-molecule level. These nanoscale environments are challenging to model due to their strongly multimodal character and short cavity lifetimes. Herein, we study the effects of these environments using real-time nuclear-electronic orbital time-dependent density functional theory (RT-NEO-TDDFT) coupled to multiple classical cavity modes in a manner that includes cavity loss. In RT-NEO-TDDFT, the quantum mechanical densities of all electrons and specified nuclei, typically protons, are propagated in real time. We show that a cavity with many modes at different frequencies can be used to probe and modify the nuclear-electronic quantum dynamics of chemical systems. Ultrafast excited-state proton transfer reactions can be probed through the time- and energy-resolved cavity emission of a multimode cavity. Under strong coupling conditions, the cavity can modify the dynamics, in some cases suppressing proton transfer and exhibiting Rabi-like oscillations of the cavity emission due to polariton formation. Utilizing the spectral density for an experimentally relevant nanoparticle-on-mirror single-molecule cavity, we show that an excited-state proton transfer system can evolve into resonance with the cavity even when initially out of resonance with the dominant cavity peak. In this case, tuning the dominant cavity peak to be resonant with the electronic transition leads to polariton formation for a small collection of molecules. The RT-NEO framework with multimode cavities enables the efficient simulation of chemical reactions in physically realistic electromagnetic environments, providing fundamental insights into the dynamics and associated spectroscopic signatures.

physics.chem-ph↗

arXiv2025

Parameterized Attenuated Exchange for Generalized TDHF@$v_W$ Applications

Building upon our previously developed time-dependent Hartree-Fock (TDHF)@$v_W$ method, based on many-body perturbation theory and specifically the Bethe-Salpeter Equation (BSE), we introduce a parameterization scheme for the attenuated exchange kernel, $v_W(|r - r'|)$. In the original method, $v_W$ was determined individually for each system via an efficient stochastic short-time TD Hartree propagation for the screened Coulomb interaction, $W(r,r')$. The new parameterization leverages photochemical similarities in exciton binding energies (or exchange interaction attenuation) among molecules with comparable static dielectric responses. We parameterize the inverse dielectric function using a low-order polynomial with error function apodization, calibrated on a few representative molecules, each with its own $v_W$. Using only 7 parameters, the parameterized $v_W$ is fully grid-independent and broadly applicable within a family of molecules. This enables TDHF@$v_W$ that retains BSE-level accuracy, achieving a mean absolute error of $\sim0.1$ eV compared to experimental optical gaps and representing a five- to ten-fold improvement over conventional TD density functional theory or TDHF while reducing the cost to that of standard TDHF.

physics.chem-ph↗

arXiv2025

Efficient plane-wave approach to generalized Kohn-Sham density-functional theory of solids with mixed deterministic/stochastic exchange

An efficient mixed deterministic/sparse-stochastic plane-wave approach is developed for bandstructure calculations of large supercell periodic generalized-Kohn-Sham density functional theory, for any hybrid-exchange density functional. The method works for very large elementary cells and supercells, and we benchmark it on covalently bonded solids and molecular crystals with nonbonded interactions, for supercells of up to 33,000 atoms. Memory and CPU requirements scale with supercell size quasi-linearly.

cond-mat.mtrl-sci↗

arXiv2023

Time-Dependent Density Functional Theory with the Orthogonal Projector Augmented Wave Method

The projector augmented wave (PAW) method of Bl\"ochl linearly maps smooth pseudo wavefunctions to the highly oscillatory all-electron DFT orbitals. Compared to norm-conserving pseudopotentials (NCPP), PAW has the advantage of lower kinetic energy cutoffs and larger grid spacings at the cost of having to solve for non-orthogonal wavefunctions. We earlier developed orthogonal PAW (OPAW) to allow the use of PAW when orthogonal wavefunctions are required. In OPAW, the pseudo wavefunctions are transformed through the efficient application of powers of the PAW overlap operator with essentially no extra cost compared to NCPP methods. Previously, we applied OPAW to DFT. Here, we take the first step to make OPAW viable for post-DFT methods by implementing it in real-time time-dependent (TD) DFT. Using fourth-order Runge-Kutta for the time-propagation, we compare calculations of absorption spectra for various organic and biological molecules and show that very large grid spacings are sufficient, 0.6-0.8 Bohr in OPAW-TDDFT rather than the 0.4-0.5 Bohr used in traditional NCPP-TDDFT calculations. This reduces the memory and propagation costs by up to a factor of 5. Our method would be directly applicable to any post-DFT methods that require time-dependent propagations such as GW and BSE.

physics.chem-ph↗

arXiv2021

An Open Natural Language Processing Development Framework for EHR-based Clinical Research: A case demonstration using the National COVID Cohort Collaborative (N3C)

While we pay attention to the latest advances in clinical natural language processing (NLP), we can notice some resistance in the clinical and translational research community to adopt NLP models due to limited transparency, interpretability, and usability. In this study, we proposed an open natural language processing development framework. We evaluated it through the implementation of NLP algorithms for the National COVID Cohort Collaborative (N3C). Based on the interests in information extraction from COVID-19 related clinical notes, our work includes 1) an open data annotation process using COVID-19 signs and symptoms as the use case, 2) a community-driven ruleset composing platform, and 3) a synthetic text data generation workflow to generate texts for information extraction tasks without involving human subjects. The corpora were derived from texts from three different institutions (Mayo Clinic, University of Kentucky, University of Minnesota). The gold standard annotations were tested with a single institution's (Mayo) ruleset. This resulted in performances of 0.876, 0.706, and 0.694 in F-scores for Mayo, Minnesota, and Kentucky test datasets, respectively. The study as a consortium effort of the N3C NLP subgroup demonstrates the feasibility of creating a federated NLP algorithm development and benchmarking platform to enhance multi-institution clinical NLP study and adoption. Although we use COVID-19 as a use case in this effort, our framework is general enough to be applied to other domains of interest in clinical NLP.

cs.CL↗