9,647 research outputs found
Activating Methane and Other Small Molecules: Computational study of Zeolites and Actinides
Exploring the catalytic properties and reactivity of actinide complexes towards activation of small molecules is important as human activities have led to the increased distribution of these species in nature. Toward this end, it is important to have a computational protocol for studying these species, in this thesis we provide details on the performance of multiconfigurational pair-density functional theory (MC-PDFT) in actinide chemistry. MC-PDFT and Kohn-Sham Density Functional Theory (KS-DFT) perform well for these species with indications that the former can be used for species with even greater static electron correlation effect. In addition, we study the activity of organometallic trans-uranium complexes towards the electrocatalytic reduction of water. We conclude that, with a guided choice of ligand, neptunium complexes can provide similar reactivity when compared to organometallic uranium complexes.Conversion of methane to methanol has been a major focus of research interest over the years. This is largely due to the abundance of natural gas, of which methane is the major constituent. Copper-exchanged zeolites have been shown to be able to kinetically trap activated methane as strongly-bound methoxy groups, preventing over-oxidation to CO2, CO and HCOOH. In this stepwise process, there are three cycles; an initial activation step to form the copper oxo active site, methane C-H activation and lastly simultaneous desorption of methanol and re -activation of the active site.. We provide detailed description of the pathway for the formation of over oxidation products. It is observed that to ensure high selectivity to methanol and prevent further hydrogen atom abstraction by extra-framework species, the methyl group must be stabilized from the copper-oxo active sites. There is a temperature gradient between the steps in the methane-to-methanol conversion cycle which is an impediment to industrial adoption of this approach for methane-to-methanol conversion. To mitigate this, we have investigated the impact of heterometallic extra-framework motifs on the temperature gradients of each step. Using periodic DFT, we provide detailed descriptions of the mechanistic pathways for each of the three steps. We were subsequently able to design motif(s) with great methane C-H activities as well as the abilities to be formed and regenerated at nearly the same temperatures. We found [Cu-O-Ag] and [Cu-O-Pd] to be potential candidates for isothermal or near-isothermal operations of the methane-to-methanol conversion cycle.
Finally, we provide insights to the changes in optical spectra of activated copper-exchanged zeolites, gaining an understanding of the evolution of these systems on a molecular level will provide opportunities to achieve improved reactivity
Subgrid scale modeling for large eddy simulation of supercritical mixing and combustion
Large eddy simulation (LES) is a widely used modeling and simulation technique in turbulent flow research. While the LES methodology and accompanying subgrid scale (SGS) modeling have been developed and applied over decades, primarily in the context of ideal gas conditions, their extension to complex multi-physics flows encountered in aerospace propulsion requires further refinement. In particular, the application of LES to turbulent flows at supercritical conditions presents several new modeling challenges and uncertainties. The scope of this dissertation is to investigate the theoretical LES formalism and SGS modeling framework for multi-species turbulent mixing and combustion at supercritical pressures. The goal is to identify the deficiencies with the current methodology and to establish a refined and consistent framework that accurately accounts for all the necessary physics.
In this dissertation, a consistent theoretical formulation of the filtered governing equations for LES is derived. Direct numerical simulations (DNS) are performed for spatially evolving non-reacting and reacting mixing layers at supercritical pressures. The complete set of terms in the filtered equations are quantified and analyzed using the DNS datasets. Based on the analyses, two new groups of subgrid terms are identified as important quantities to account in the LES framework. Parametric analyses are performed as a function of the filter resolution to derive resolution considerations for practical LES applications.
The performance and accuracies of two state-of-the-art subgrid modeling approaches for the traditional subgrid fluxes are assessed. The study demonstrates the better performance of scale-similarity based models over the eddy-viscosity based approaches. The study also reveals the deficiencies of conventional subgrid modeling approaches for LES of supercritical combustion. To address the additional modeling requirement for the filtered equation of state, novel subgrid modeling approaches are proposed. The performance of these models are tested and good improvements are demonstrated.Ph.D
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Small-polaron mediated recombination in titanium dioxide from first principles
Nonradiative recombination leads to losses in efficiency in optoelectronic devices such as photovoltaic cells and light-emitting diodes. Charges trapped at point defects or self-trapped as a small polaron may act as recombination centers. Using various phases of titanium dioxide as an example, we provide first-principles predictions that small hole polarons in the bulk of the crystal would exhibit significant rates of recombination with electrons in the conduction band. However, small hole polarons trapped at a model grain boundary are predicted to have much higher nonradiative recombination rates, which can be attributed to softer phonon modes in the vicinity of the boundary as well as greater electron-phonon coupling. These findings have ramifications in materials other than titanium dioxide, and we propose strategies to reduce the degree of recombination that would occur at grain boundaries
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Collective variables between large-scale states in turbulent convection
The dynamics in a confined turbulent convection flow is dominated by multiple
long-lived macroscopic circulation states, which are visited subsequently by
the system in a Markov-type hopping process. In the present work, we analyze
the short transition paths between these subsequent macroscopic system states
by a data-driven learning algorithm that extracts the low-dimensional
transition manifold and the related new coordinates, which we term collective
variables, in the state space of the complex turbulent flow. We therefore
transfer and extend concepts for conformation transitions in stochastic
microscopic systems, such as in the dynamics of macromolecules, to a
deterministic macroscopic flow. Our analysis is based on long-term direct
numerical simulation trajectories of turbulent convection in a closed cubic
cell at a Prandtl number and Rayleigh numbers and
for a time lag of convective free-fall time units. The simulations
resolve vortices and plumes of all physically relevant scales resulting in a
state space spanned by more than 3.5 million degrees of freedom. The transition
dynamics between the large-scale circulation states can be captured by the
transition manifold analysis with only two collective variables which implies a
reduction of the data dimension by a factor of more than a million. Our method
demonstrates that cessations and subsequent reversals of the large-scale flow
are unlikely in the present setup and thus paves the way to the development of
efficient reduced-order models of the macroscopic complex nonlinear dynamical
system.Comment: 24 pages, 12 Figures, 1 tabl
Computing and Compressing Electron Repulsion Integrals on FPGAs
The computation of electron repulsion integrals (ERIs) over Gaussian-type
orbitals (GTOs) is a challenging problem in quantum-mechanics-based atomistic
simulations. In practical simulations, several trillions of ERIs may have to be
computed for every time step.
In this work, we investigate FPGAs as accelerators for the ERI computation.
We use template parameters, here within the Intel oneAPI tool flow, to create
customized designs for 256 different ERI quartet classes, based on their
orbitals. To maximize data reuse, all intermediates are buffered in FPGA
on-chip memory with customized layout. The pre-calculation of intermediates
also helps to overcome data dependencies caused by multi-dimensional recurrence
relations. The involved loop structures are partially or even fully unrolled
for high throughput of FPGA kernels. Furthermore, a lossy compression algorithm
utilizing arbitrary bitwidth integers is integrated in the FPGA kernels. To our
best knowledge, this is the first work on ERI computation on FPGAs that
supports more than just the single most basic quartet class. Also, the
integration of ERI computation and compression it a novelty that is not even
covered by CPU or GPU libraries so far.
Our evaluation shows that using 16-bit integer for the ERI compression, the
fastest FPGA kernels exceed the performance of 10 GERIS ( ERIs
per second) on one Intel Stratix 10 GX 2800 FPGA, with maximum absolute errors
around - Hartree. The measured throughput can be accurately
explained by a performance model. The FPGA kernels deployed on 2 FPGAs
outperform similar computations using the widely used libint reference on a
two-socket server with 40 Xeon Gold 6148 CPU cores of the same process
technology by factors up to 6.0x and on a new two-socket server with 128 EPYC
7713 CPU cores by up to 1.9x
Leading-order QED effects in the ground electronic state of molecular hydrogen
We perform highly accurate calculations of the leading order QED correction
to the ground electronic state of molecular hydrogen. Numerical results are
obtained for a grid of the internuclear distances au with the relative
precision of about . The major numerical uncertainty of previous QED
results [K. Piszczatowski et al., JCTC , 3039 (2009)] has been
eliminated. Nevertheless, the discrepancy with measurements in HD at the level
of 1.9 persists.Comment: 9 pages, 2 figures, 2 table
GNN-Assisted Phase Space Integration with Application to Atomistics
Overcoming the time scale limitations of atomistics can be achieved by
switching from the state-space representation of Molecular Dynamics (MD) to a
statistical-mechanics-based representation in phase space, where approximations
such as maximum-entropy or Gaussian phase packets (GPP) evolve the atomistic
ensemble in a time-coarsened fashion. In practice, this requires the
computation of expensive high-dimensional integrals over all of phase space of
an atomistic ensemble. This, in turn, is commonly accomplished efficiently by
low-order numerical quadrature. We show that numerical quadrature in this
context, unfortunately, comes with a set of inherent problems, which corrupt
the accuracy of simulations -- especially when dealing with crystal lattices
with imperfections. As a remedy, we demonstrate that Graph Neural Networks,
trained on Monte-Carlo data, can serve as a replacement for commonly used
numerical quadrature rules, overcoming their deficiencies and significantly
improving the accuracy. This is showcased by three benchmarks: the thermal
expansion of copper, the martensitic phase transition of iron, and the energy
of grain boundaries. We illustrate the benefits of the proposed technique over
classically used third- and fifth-order Gaussian quadrature, we highlight the
impact on time-coarsened atomistic predictions, and we discuss the
computational efficiency. The latter is of general importance when performing
frequent evaluation of phase space or other high-dimensional integrals, which
is why the proposed framework promises applications beyond the scope of
atomistics
Exact two-component TDDFT with simple two-electron picture-change corrections: X-ray absorption spectra near L- and M-edges of four-component quality at two-component cost
X-ray absorption spectroscopy (XAS) has gained popularity in recent years as it probes matter with high spatial and elemental sensitivities. However, the theoretical modeling of XAS is a challenging task since XAS spectra feature a fine structure due to scalar (SC) and spin-orbit (SO) relativistic effects, in particular near L and M absorption edges. While full four-component (4c) calculations of XAS are nowadays feasible, there is still interest in developing approximate relativistic methods that enable XAS calculations at the two-component (2c) level while maintaining the accuracy of the parent 4c approach. In this article we present theoretical and numerical insights into two simple yet accurate 2c approaches based on an (extended) atomic mean-field exact two-component Hamiltonian framework, (e)amfX2C, for the calculation of XAS using linear eigenvalue and damped response time-dependent density functional theory (TDDFT). In contrast to the commonly used one-electron X2C (1eX2C) Hamiltonian, both amfX2C and eamfX2C account for the SC and SO two-electron and exchange-correlation picture-change (PC) effects that arise from the X2C transformation. As we demonstrate on L- and M-edge XAS spectra of transition metal and actinide compounds, the absence of PC corrections in the 1eX2C approximation results in a substantial overestimation of SO splittings, whereas (e)amfX2C Hamiltonians reproduce all essential spectral features such as shape, position, and SO splitting of the 4c references in excellent agreement, while offering significant computational savings. Therefore, the (e)amfX2C PC correction models presented here constitute reliable relativistic 2c quantum-chemical approaches for modeling XAS. © 2023 The Authors. Published by American Chemical Society.2/0135/21; NN4654K; Ministerstvo Å kolstvÃ, Mládeže a TÄ›lovýchovy, MÅ MT: RP/CPS/2022/007; Agentúra na Podporu Výskumu a Vývoja, APVV: APVV-19-0516, APVV-21-0497; Norges ForskningsrÃ¥d: 262695, 314814, 315822; Horizon 2020: 945478, SASPRO
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