Session GG01: V: Spectroscopy, Structure and Dynamics II

Defect and dopant ab-initio Simulation Package (DASP)

In order to perform automated calculations of defect and dopant properties in semiconductors and insulators, we developed a software package, Defect and Dopant ab-initio Simulation Package (DASP). DASP uses the materials genome database for quick determination of competing secondary phases and calculation of the energy above convex hull when calculating the elemental chemical potential that stabilizes compound semiconductors, so it can perform high-throughput prediction of thermodynamic stability of multinary compounds. DASP calls the ab-initio softwares to perform the total energy, structural relaxation and electronic structure calculations of the defect supercells with different structure configurations and charge states, based on which the defect formation energies and transition energy levels are calculated and the corrections for electrostatic potential alignment and image charge interaction can be included. Then DASP can calculate the equilibrium densities of defects and electron and hole carriers as well as the Fermi level in semiconductors under different chemical potential conditions and different growth/working temperature. For high-density defects, DASP can calculate the carrier dynamics properties such as the photoluminescence (PL) spectrum, defect-related radiative and non-radiative carrier capture cross sections, and recombination lifetime of non-equilibrium carriers. In the talk, I will demonstrate the applications of DASP in studying the undoped GaN, C-doped GaN, SbSeI, CdTe, ZnGeP2 and HfO2.   

Isotope Effects on the Electronic Spectra of Ammonia from Ab Initio Semiclassical Dynamics

Despite its simplicity, the single-trajectory thawed Gaussian approximation has proven useful for calculating the vibrationally resolved electronic spectra of molecules with weakly anharmonic potential energy surfaces. Here, we show that the thawed Gaussian approximation can capture surprisingly well even more subtle observables, such as the isotope effects in the absorption spectra, and we demonstrate it on the four isotopologues of ammonia (NH₃, NDH₂, ND₂H, and ND₃). The differences in their computed spectra are due to the differences in the semiclassical trajectories followed by the four isotopologues, and the isotope effects-narrowing of the transition band and reduction of the peak spacing-are accurately described by this semiclassical method. In contrast, the adiabatic harmonic model shows a double progression instead of the single progression seen in the experimental spectra. The vertical harmonic model correctly shows only a single progression but fails to describe the anharmonic peak spacing. Analysis of the normal-mode activation upon excitation provides insight into the elusiveness of the symmetric stretching progression in the spectra.   

High-order geometric integrators for the local cubic variational Gaussian wavepacket dynamics

Gaussian wavepacket dynamics has proven to be a useful semiclassical approximation for quantum simulations of high-dimensional systems with low anharmonicity. Compared to Heller's original local harmonic method, the variational Gaussian wavepacket dynamics is more accurate, but much more difficult to apply in practice because it requires evaluating the expectation values of the potential energy, gradient, and Hessian. If the variational approach is applied to the local cubic approximation of the potential, these expectation values can be evaluated analytically, but still require the costly third derivative of the potential. To reduce the cost of the resulting local cubic variational Gaussian wavepacket dynamics, we describe efficient high-order geometric integrators, which are symplectic, time-reversible, and norm-conserving. For small time steps, they also conserve the effective energy. We demonstrate the efficiency and geometric properties of these integrators numerically on a multi-dimensional, nonseparable coupled Morse potential.   

Machine learning predicted anharmonic frequencies and their effect in thermochemistry

Anharmonic effects play a crucial role in determining thermodynamic properties of liquids and gases. However, such data is computationally expensive and difficult to obtain. Machine learning (ML) methods are proving to be effective in making inexpensive computational approximations within theoretical chemistry and spectroscopy. In this work density functional theory (DFT) and vibrational self-consistent field (VSCF) are applied to obtain a vibrational dataset for HX, CH3X and C2H5X (X = F, Cl, Br) clusters of various sizes to train the gradient boosting ensemble model. It is shown that harmonic frequencies and reduced masses as descriptors are sufficient to train a ML model that significantly improves on harmonic frequencies and estimates anharmonic frequencies with negligible computational time. Anharmonic frequencies of the larger clusters (>10 atoms) of hydrogen fluoride were predicted using our ML model as a test case application. Quantum-mechanically calculated and ML-predicted harmonic/anharmonic frequencies were used as an input for quantum cluster equilibrium (QCE) method to generate thermodynamic data for the liquid and gas phases. QCE calculations show that anharmonic frequencies significantly affect and improve the final results, especially the populations of the clusters of liquid hydrogen fluoride. ML estimates provide an efficient way to include anharmonic contributions in the calculation of more accurate thermodynamic properties of condensed phases.

Keywords: machine learning, density functional theory, harmonic and anharmonic vibrational analysis, statistical thermodynamics, quantum cluster equilibrium, liquid hydrogen fluoride   

Dynamics of liquid bridges between patterned surfaces

We have simulated the motion of a single vertical, two-dimensional liquid bridge spanning the gap between two flat, horizontal solid substrates consisting of alternating hydrophilic and hydrophobic stripes, using a multicomponent pseudopotential lattice Boltzmann method. This extends our earlier work where the substrates were uniformly hydrophilic or hydrophobic. In steady-state conditions, we calculate the following, as functions of pattern wavelength and the liquid bridge contact angles at the hydrophilic and hydrophobic regions: (i) the velocity fields of moving bridges, in particular their (time-averaged) terminal velocities; (ii) the deformation of moving bridges, as measured by the deviation of bridge contact angles from their equilibrium values; (iii) the minimum applied force necessary to mobilise a bridge, and the minimum applied force that breaks a moving bridge. In addition, we found that a bridge moving between patterned substrates cannot be mapped onto a bridge moving between uniform substrates endowed with some effective contact angle, even in the limit of very small pattern wavelength compared to bridge width.   

The role of Hydrogen Bonding in sunscreen performance

Intramolecular H-bonding facilitates processes such as tautomerization and has significant impact on molecular spectroscopic behaviors and macroscopic properties. We explore how changes in H-bonding between two categories of ultraviolet (UV) filters impact their spectroscopic behaviors and their performance in commercial sunscreen formulations.

We explore first the case of methyl anthranilate (MA), a precursor to the now discontinued UV filter meradimate, which contains a N–H intramolecular H-bond. Using laser and static spectroscopy techniques, as well as computational studies, we created a detailed account of how the intramolecular H-bond influences MA’s spectroscopic behavior, including its performance within a commercial sunscreen formulation. In addition, we compare these results to equivalent ones for homosalate, a salicylate approved for use in commercial sunscreen formulations worldwide. Instead of the N–H bond in anthranilates, salicylates contain a O–H intramolecular H-bond.

Our work reveals key differences in the spectroscopy and chemical dynamics of anthranilates vs salicylates, with important implications for sunscreen performance. This work further highlights how fundamental science can inform product development in real-life applications.   

On the Temporal Response of Instantaneous Two-Photon Processes

With the advent of shorter and shorter laser pulse resolution, the significance of two-photon transitions without an intermediate-state that shows all two-photon characteristics have grown in importance. We explore such systems in a theoretical context with experimental validation. We show that the case of a temporal scan between two laser pulses gives rise to the two-photon signal. Two-photon processes progress via intermediate virtual states and we have earlier shown that the virtual state model of multiphoton absorption is mathematically equivalent to the single-photon absorption model of an appropriate wavelength and phase. We probe the nature of the intermediate physical state of two-photon absorption by performing a temporal scan of the delay between two pulses generating two-photon process. We demonstrate the possibility of two-photon non-resolvable virtual state transitions when the two-photons are simultaneously incident on a two-level system with only two-photon transitions possible. These transitions continue to show the well-known characteristics of two-photon processes in terms of the control parameters of phase, polarization, and intensity. We note that, the significance of such transitions is that if a temporal scan is done on the two laser pulses causing the transition, there is no intermediate state whose signatures can be observed.   

Photocatalytic Degradation of Microplastics over Ilmenite-Graphene Oxide Nanohybrid

Microplastics (MPs) pose a significant environmental threat, as they can accumulate in ecosystems, harming aquatic life and disrupting food chains. Additionally, their small size allows them to be ingested by marine organisms, potentially leading to harmful health effects in humans when consuming contaminated seafood. There is a growing global demand for a durable and ecologically sustainable solution to this issue. In this study, complete photocatalytic removal of MPs is achieved using a nanohybrid of natural ilmenite (FeTiO₃) and graphene oxide (GO) synthesized via a microwave-assisted route. Powdered polyethylene terephthalate (PET) with a maximum particle size of 50 μm was employed as the model MP. PET was dispersed in a water-ethanol 1:1 mixture to increase the solubility. The adsorption characteristics and photocatalytic activity of the nanohybrid against PET were studied by varying the PET concentration and photocatalyst dosage. UV-Vis spectroscopic results suggest that the system with optimized parameters can completely degrade PET. SEM, FT-IR, and TGA results are in accordance with the findings. The methodical investigations conclude that MPs can be removed effectively and permanently, using the ilmenite-GO nanohybrid as a sustainable photocatalyst.   

Efficient Removal of Microplastics Using Magnetic-Reduced Graphene Oxide (MrGO) as an Adsorbent Material

Microplastics (MPs) are prominent environmental pollutants, that exert adverse impacts on natural ecosystems and organisms, which consequently pose direct threats to both food security and human health. Magnetic-reduced graphene oxide (MRGO) has demonstrated exceptional potential as an adsorbent material. It could be easily separated from water using an external magnetic field. In this study, the utility of MRGO as an efficient adsorbent material for MPs was explored. Graphene oxide (GO) and Fe₃O₄ nanoparticles (NPs) were synthesized using an improved Hummer's method and the chemical coprecipitation method, respectively. MRGO was prepared as a composite material incorporating GO and Fe₃O₄ NPs. Polyethylene terephthalate (PET) MPs were employed as the model MP.  PET powder with a maximum particle size of 50 μm was dispersed in an ethanol-water 1:1 mixture. Subsequently, the adsorption process was conducted under different PET concentrations and MRGO dosages. UV-Vis spectroscopic results show that MRGO exhibits remarkable adsorption capabilities, achieving a maximum MPs removal efficiency of 73.49% in two hours. FTIR, SEM and TGA analyses were also carried out to confirm the findings. The combined results suggest that MRGO makes an efficient adsorbent for the removal of MPs.