422 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Universal Pairwise Interatomic van der Waals Potentials Based on Quantum Drude Oscillators
Repulsive short-range and attractive long-range van der Waals (vdW) forces
have an appreciable role in the behavior of extended molecular systems. When
using empirical force fields - the most popular computational methods applied
to such systems - vdW forces are typically described by Lennard-Jones-like
potentials, which unfortunately have a limited predictive power. Here, we
present a universal parameterization of a quantum-mechanical vdW potential,
which requires only two free-atom properties - the static dipole polarizability
and the dipole-dipole dispersion coefficient. This is achieved
by deriving the functional form of the potential from the quantum Drude
oscillator (QDO) model, employing scaling laws for the equilibrium distance and
the binding energy as well as applying the microscopic law of corresponding
states. The vdW-QDO potential is shown to be accurate for vdW binding energy
curves, as demonstrated by comparing to ab initio binding curves of 21
noble-gas dimers. The functional form of the vdW-QDO potential has the correct
asymptotic behavior both at zero and infinite distances. In addition, it is
shown that the damped vdW-QDO potential can accurately describe vdW
interactions in dimers consisting of group II elements. Finally, we demonstrate
the applicability of the atom-in-molecule vdW-QDO model for predicting accurate
dispersion energies for molecular systems. The present work makes an important
step towards constructing universal vdW potentials, which could benefit
(bio)molecular computational studies
Understanding the role of Hubbard corrections in the rhombohedral phase of BaTiO
We present a first-principles study of the low-temperature rhombohedral phase
of BaTiO using Hubbard-corrected density-functional theory. By employing
density-functional perturbation theory, we compute the onsite Hubbard for
Ti() states and the intersite Hubbard between Ti() and O()
states. We show that applying the onsite Hubbard correction alone to
Ti() states proves detrimental, as it suppresses the Ti()-O()
hybridization and drives the system towards a cubic phase. Conversely, when
both onsite and intersite are considered, the localized character of
the Ti() states is maintained, while also preserving the Ti()-O()
hybridization, restoring the rhombohedral phase of BaTiO. The generalized
PBEsol++ functional yields remarkable agreement with experimental results
for the band gap and dielectric constant, while the optimized geometry is
slightly less accurate compared to PBEsol. Zone-center phonon frequencies and
Raman spectra, being significantly influenced by the underlying geometry,
demonstrate better agreement with experiments in the case of PBEsol, while
PBEsol++ exhibits reduced accuracy, and the PBEsol+ Raman spectrum
diverges remarkably from experimental data, highlighting the adverse impact of
the correction alone in BaTiO. Our findings underscore the promise of
the extended Hubbard PBEsol++ functional with first-principles and
for the investigation of other ferroelectric perovskites with mixed
ionic-covalent interactions
Electronic and Geometric Structure of Copper Single-Metal Sites in Zeolites by Hyperfine Spectroscopy and Quantum Chemical Modelling
A Thesis submitted to the Universities of Leipzig and Turin in candidature for a Joint PhD degree by Paolo Cleto Bruzzese
Abstract
Atomically dispersed transition metal ions in zeolites catalyse a wide range of
industrial reactions and are at the centre of intense research interest to design
new sustainable synthetic pathways for energy conversion and environment remediation.
One of the big challenges in this context is the characterization and
location of the active sites. Indeed, mapping their nature with atomic-scale
precision occupies a central place in the theory and practice of heterogeneous
catalysis.
In this thesis, the site-selectivity and sensitivity of Electron Paramagnetic
Resonance (EPR) with its pulsed variants are combined with quantum chemical
modelling to determine the microscopic structure of monomeric CuII species in
zeolites with Chabazite (CHA) topology as a function of the hydration conditions
and sample composition. By isotopic labelling of the zeolite framework
with 17O and employing 17O ENDOR spectroscopy, the degree of covalency in
the Cu-O bond is mapped and the evolution of CuII sites as a function of the
hydration conditions is followed. By combining 1H HYSCORE experiments with
state-of-the-art quantum chemical modelling, the EPR signature of the redox active
hydroxo-CuII species is univocally identified and a quantitative assessment
of its electronic and geometric structureis provided as a function of zeolite composition
Electronic structure of MoS revisited: a comprehensive assessment of calculations
Two-dimensional MoS combines many interesting properties that make the
material a top candidate for a variety of applications. It exhibits a high
electron mobility comparable to graphene, a direct fundamental band gap,
relatively strongly bound excitons, and moderate spin-orbit coupling. For a
thorough understanding of all these properties, an accurate description of the
electronic structure is mandatory. Surprisingly, published band gaps of MoS
obtained with , the state-of-the-art in electronic-structure calculations,
are quite scattered, ranging from 2.31 to 2.97 eV. The details of
calculations, such as the underlying geometry, the starting point, the
inclusion of spin-orbit coupling, and the treatment of the Coulomb potential
can critically determine how accurate the results are. In this manuscript, we
employ the linearized augmented planewave + local orbital method to
systematically investigate how all these aspects affect the quality of
calculations, and also provide a summary of literature data. We conclude that
the best overall agreement with experiments and coupled-cluster calculations is
found for results with HSE06 as a starting point including spin-orbit
coupling, a truncated Coulomb potential, and an analytical treatment of the
singularity at
Band structure renormalization at finite temperatures from first principles
In dieser Doktorarbeit untersuchen wir den Einfluss von Elektron-Phonon-Wechselwirkungen (EPW) auf die Bandlueckenrenormierung in kristallinen Festkoerpern bei endlichen Temperaturen. Das Hauptziel besteht darin, den Einfluss der Kernbewegung und der thermischen Ausdehnung des Gitters auf die Bandstruktur in einer Vielzahl von Materialien zu quantifizieren. Zu diesem Zweck wird der Temperatureinfluss auf das EPW in harmonischen Naeherungen unter Verwendung der stochastischen Abtastmethode und vollstaendig anharmonisch durch DurchfĂĽhrung von ab initio Molekulardynamiksimulationen (aiMD). Die Bandluecke bei endlichen Temperaturen wird aus der thermodynamisch gemittelten Spektralfunktion extrahiert, die unter Verwendung der Bandentfaltungstechnik berechnet wird. Waehrend die Verwendung von aiMD bereits fuer Berechnungen von EPW verwendet wurde, wurde die Kombination von aiMD und Bandentfaltung zur Behandlung der Bandluecken renormalisierung erst kuerzlich verwendet. In dieser Doktorarbeit haben wir eine verbesserte Bandentfaltungstechnik verwendet, um die Berechnung effektiv zu verwalten. Diese verbesserte Methode enthaelt mehrere methodische Neuerungen, die dazu dienen, den Rechenaufwand zu verringern und das statistische Rauschen in den Endergebnissen zu minimieren. Die aktualisierte Methode wurde gruendlich bewertet, dokumentiert und mit einer benutzerfreundlichen Oberflaeche gestaltet. Wir praesentieren eine umfassende Untersuchung der numerischen Aspekte der thermodynamischen Mittelung, der Schaetzung von Fehlerbalken und der Bewertung der Konvergenz in Bezug auf die Groesse der Simulationssuperzelle. Unser etabliertes Protokoll ermoeglicht die Berechnung der BandlĂĽckenrenormierung bei endlichen Temperaturen, was in guter Uebereinstimmung mit frueheren theoretischen Studien und experimentellen Daten steht.In this thesis, we investigate the influence of electron-phonon interactions (EPI) on the band gap renormalization in crystalline solids at finite temperatures. The main goal is to identify the impact of the nuclear motion and the lattice thermal expansion on the band structure in a wide range of materials. For this purpose, the temperature influence on the EPI is calculated in the harmonic approximations by utilizing the stochastic sampling methodology and fully anharmonically, by performing ab initio molecular dynamics simulations (aiMD). The band gap at finite temperatures is extracted from the thermodynamically averaged spectral function, which is calculated using band-unfolding technique. While utilization of aiMD was already used for calculations of EPI the combination of aiMD and band-unfolding to treat the band gap renormalization was used only recently. In this thesis, we employed an improved band unfolding technique in order to effectively manage the calculations. This improved method incorporates several methodological innovations that serve to mitigate computational cost and minimize statistical noise in the final results. The updated method was thoroughly benchmarked, documented, and designed with a user-friendly interface. We present a comprehensive examination of the numerical aspects of thermodynamic averaging, the estimation of error bars, and the evaluation of convergence with respect to the size of the simulation supercell. Our established protocol enables the calculation of band gap renormalization at finite temperatures, which is in good agreement with prior theoretical studies and experimental data
A Tale of Two Approaches: Comparing Top-Down and Bottom-Up Strategies for Analyzing and Visualizing High-Dimensional Data
The proliferation of high-throughput and sensory technologies in various fields has led to a considerable increase in data volume, complexity, and diversity. Traditional data storage, analysis, and visualization methods are struggling to keep pace with the growth of modern data sets, necessitating innovative approaches to overcome the challenges of managing, analyzing, and visualizing data across various disciplines.
One such approach is utilizing novel storage media, such as deoxyribonucleic acid~(DNA), which presents efficient, stable, compact, and energy-saving storage option. Researchers are exploring the potential use of DNA as a storage medium for long-term storage of significant cultural and scientific materials.
In addition to novel storage media, scientists are also focussing on developing new techniques that can integrate multiple data modalities and leverage machine learning algorithms to identify complex relationships and patterns in vast data sets. These newly-developed data management and analysis approaches have the potential to unlock previously unknown insights into various phenomena and to facilitate more effective translation of basic research findings to practical and clinical applications.
Addressing these challenges necessitates different problem-solving approaches. Researchers are developing novel tools and techniques that require different viewpoints. Top-down and bottom-up approaches are essential techniques that offer valuable perspectives for managing, analyzing, and visualizing complex high-dimensional multi-modal data sets. This cumulative dissertation explores the challenges associated with handling such data and highlights top-down, bottom-up, and integrated approaches that are being developed to manage, analyze, and visualize this data. The work is conceptualized in two parts, each reflecting the two problem-solving approaches and their uses in published studies. The proposed work showcases the importance of understanding both approaches, the steps of reasoning about the problem within them, and their concretization and application in various domains
A 'moment-conserving' reformulation of GW theory
We show how to construct an effective Hamiltonian whose dimension scales
linearly with system size, and whose eigenvalues systematically approximate the
excitation energies of theory. This is achieved by rigorously expanding
the self-energy in order to exactly conserve a desired number of
frequency-independent moments of the self-energy dynamics. Recasting in
this way admits a low-scaling approach to build this
Hamiltonian, with a proposal to reduce this further to . This
relies on exposing a novel recursive framework for the density response moments
of the random phase approximation (RPA), where the efficient calculation of its
starting point mirrors the low-scaling approaches to compute RPA correlation
energies. The frequency integration of which distinguishes so many
different variants can be performed directly and cheaply in this moment
representation. Furthermore, the solution to the Dyson equation can be
performed exactly, avoiding analytic continuation, diagonal approximations or
iterative solutions to the quasiparticle equation, with the full-frequency
spectrum of all solutions obtained in a complete diagonalization of this
effective static Hamiltonian. We show how this approach converges rapidly with
respect to the order of the conserved self-energy moments, and is applied
across the benchmark dataset to obtain accurate spectra in
comparison to traditional implementations. We also show the ability to
systematically converge all-electron full-frequency spectra and high-energy
features beyond frontier excitations, as well as avoiding discontinuities in
the spectrum which afflict many other approaches
Metal Cations in Protein Force Fields: From Data Set Creation and Benchmarks to Polarizable Force Field Implementation and Adjustment
Metal cations are essential to life. About one-third of all proteins require metal cofactors to accurately fold or to function. Computer simulations using empirical parameters and classical molecular mechanics models (force fields) are the standard tool to investigate proteins’ structural dynamics and functions in silico. Despite many successes, the accuracy of force fields is limited when cations are involved. The focus of this thesis is the development of tools and strategies to create system-specific force field parameters to accurately describe cation-protein interactions. The accuracy of a force field mainly relies on (i) the parameters derived from increasingly large quantum chemistry or experimental data and (ii) the physics behind the energy formula.
The first part of this thesis presents a large and comprehensive quantum chemistry data set on a consistent computational footing that can be used for force field parameterization and benchmarking. The data set covers dipeptides of the 20 proteinogenic amino acids with different possible side chain protonation states, 3 divalent cations (Ca2+, Mg2+, and Ba2+), and a wide relative energy range. Crucial properties related to force field development, such as partial charges, interaction energies, etc., are also provided. To make the data available, the data set was uploaded to the NOMAD repository and its data structure was formalized in an ontology.
Besides a proper data basis for parameterization, the physics covered by the terms of the additive force field formulation model impacts its applicability. The second part of this thesis
benchmarks three popular non-polarizable force fields and the polarizable Drude model against a quantum chemistry data set. After some adjustments, the Drude model was found to reproduce the reference interaction energy substantially better than the non-polarizable force fields, which showed the importance of explicitly addressing polarization effects. Tweaking of the Drude model involved Boltzmann-weighted fitting to optimize Thole factors and Lennard-Jones parameters. The obtained parameters were validated by (i) their ability to reproduce reference interaction energies and (ii) molecular dynamics simulations of the N-lobe of calmodulin. This work facilitates the improvement of polarizable force fields for cation-protein interactions by quantum chemistry-driven parameterization combined with molecular dynamics simulations in the condensed phase.
While the Drude model exhibits its potential simulating cation-protein interactions, it lacks description of charge transfer effects, which are significant between cation and protein. The CTPOL model extends the classical force field formulation by charge transfer (CT) and polarization (POL). Since the CTPOL model is not readily available in any of the popular molecular-dynamics packages, it was implemented in OpenMM. Furthermore, an open-source parameterization tool, called FFAFFURR, was implemented that enables the (system specific) parameterization of OPLS-AA and CTPOL models. Following the method established in the previous part, the performance of FFAFFURR was evaluated by its ability to reproduce quantum chemistry energies and molecular dynamics simulations of the zinc finger protein.
In conclusion, this thesis steps towards the development of next-generation force fields to accurately describe cation-protein interactions by providing (i) reference data, (ii) a force field model that includes charge transfer and polarization, and (iii) a freely-available parameterization tool.Metallkationen sind für das Leben unerlässlich. Etwa ein Drittel aller Proteine benötigen Metall-Cofaktoren, um sich korrekt zu falten oder zu funktionieren. Computersimulationen unter Verwendung empirischer Parameter und klassischer Molekülmechanik-Modelle (Kraftfelder) sind ein Standardwerkzeug zur Untersuchung der strukturellen Dynamik und Funktionen von Proteinen in silico. Trotz vieler Erfolge ist die Genauigkeit der Kraftfelder begrenzt, wenn Kationen beteiligt sind. Der Schwerpunkt dieser Arbeit liegt auf der Entwicklung von Werkzeugen und Strategien zur Erstellung systemspezifischer Kraftfeldparameter zur genaueren Beschreibung von Kationen-Protein-Wechselwirkungen. Die Genauigkeit eines Kraftfelds hängt hauptsächlich von (i) den Parametern ab, die aus immer größeren quantenchemischen oder experimentellen Daten abgeleitet werden, und (ii) der Physik hinter der Kraftfeld-Formel.
Im ersten Teil dieser Arbeit wird ein großer und umfassender quantenchemischer Datensatz auf einer konsistenten rechnerischen Grundlage vorgestellt, der für die Parametrisierung und das Benchmarking von Kraftfeldern verwendet werden kann. Der Datensatz umfasst Dipeptide der 20 proteinogenen Aminosäuren mit verschiedenen möglichen Seitenketten-Protonierungszuständen, 3 zweiwertige Kationen (Ca2+, Mg2+ und Ba2+) und einen breiten relativen Energiebereich. Wichtige Eigenschaften für die Entwicklung von Kraftfeldern, wie Wechselwirkungsenergien, Partialladungen usw., werden ebenfalls bereitgestellt. Um die Daten verfügbar zu machen, wurde der Datensatz in das NOMAD-Repository hochgeladen und seine Datenstruktur wurde in einer Ontologie formalisiert.
Neben einer geeigneten Datenbasis für die Parametrisierung beeinflusst die Physik, die von den Termen des additiven Kraftfeld-Modells abgedeckt wird, dessen Anwendbarkeit. Der zweite Teil dieser Arbeit vergleicht drei populäre nichtpolarisierbare Kraftfelder und das polarisierbare Drude-Modell mit einem Datensatz aus der Quantenchemie. Nach einigen Anpassungen stellte sich heraus, dass das Drude-Modell die Referenzwechselwirkungsenergie wesentlich besser reproduziert als die nichtpolarisierbaren Kraftfelder, was zeigt, wie wichtig es ist, Polarisationseffekte explizit zu berücksichtigen. Die Anpassung des Drude-Modells umfasste eine Boltzmann-gewichtete Optimierung der Thole-Faktoren und Lennard-Jones-Parameter. Die erhaltenen Parameter wurden validiert durch (i) ihre Fähigkeit, Referenzwechselwirkungsenergien zu reproduzieren und (ii) Molekulardynamik-Simulationen des Calmodulin-N-Lobe. Diese Arbeit demonstriert die Verbesserung polarisierbarer Kraftfelder für Kationen-Protein-Wechselwirkungen durch quantenchemisch gesteuerte Parametrisierung in Kombination mit Molekulardynamiksimulationen in der kondensierten Phase.
Während das Drude-Modell sein Potenzial bei der Simulation von Kation - Protein - Wechselwirkungen zeigt, fehlt ihm die Beschreibung von Ladungstransfereffekten, die zwischen Kation und Protein von Bedeutung sind. Das CTPOL-Modell erweitert die klassische Kraftfeldformulierung um den Ladungstransfer (CT) und die Polarisation (POL). Da das CTPOL-Modell in keinem der gängigen Molekulardynamik-Pakete verfügbar ist, wurde es in OpenMM implementiert. Außerdem wurde ein Open-Source-Parametrisierungswerkzeug namens FFAFFURR implementiert, welches die (systemspezifische) Parametrisierung von OPLS-AA und CTPOL-Modellen ermöglicht. In Anlehnung an die im vorangegangenen Teil etablierte Methode wurde die Leistung von FFAFFURR anhand seiner Fähigkeit, quantenchemische Energien und Molekulardynamiksimulationen des Zinkfingerproteins zu reproduzieren, bewertet.
Zusammenfassend lässt sich sagen, dass diese Arbeit einen Schritt in Richtung der Entwicklung von Kraftfeldern der nächsten Generation zur genauen Beschreibung von Kationen-Protein-Wechselwirkungen darstellt, indem sie (i) Referenzdaten, (ii) ein Kraftfeldmodell, das Ladungstransfer und Polarisation einschließt, und (iii) ein frei verfügbares Parametrisierungswerkzeug bereitstellt
Halide Perovskite and Perovskite-Inspired Nanocrystals for Optoelectronic Applications
Optoelectronic applications, such as photovoltaics (PVs) and light-emitting diodes (LEDs), play a key role in addressing the global energy crisis. Yet, they demand new semiconductors with high stability, low environmental impact, and low cost. One of the attractive ways of synthesizing semiconductor materials is their colloidal synthesis at the nanoscale, leading to nanocrystals (NCs). This thesis focuses on a promising family of NCs extensively investigated during the last decade, namely NCs based on halide perovskites and their derivatives.
Halide perovskite nanocrystals (PNCs) display appealing optoelectronic properties due to high defect tolerance, tunable crystal structures and dimensions, and versatile synthesis. However, a comprehensive optimization of these PNCs synthesis to enhance their stability and optical properties is lacking. Furthermore, the understanding of the fundamental structure-property relationships in emerging PNCs is still very limited. At the same time, the toxicity of lead (Pb) present in the most efficient PNC compositions demands the development of eco-friendly lead-free PNCs for optoelectronic applications.
In this dissertation, we have identified the relationships between the synthesis and the key properties of emerging or novel PNCs, starting from the popular CsPbI3 and then moving towards Pb-free compositions. In particular, we have (i) enhanced the phase stability of CsPbI3 PNCs by tailoring the reaction temperature, (ii) achieved highly luminescent CsMnCl3 PNCs by tailoring the synthesis of the emissive crystalline phase, and (iii) proposed the first-ever syntheses of Cs2TiX6 (X = Br and Cl) PNCs and phase-pure AgBiI4 perovskite-inspired NCs with enhanced stabilities for potential nonlinear optical applications.
We believe that the results of this thesis will encourage other researchers and practitioners in the field to further investigate the promising perovskites and perovskite-inspired NCs that we have identified and eventually enable their usage in real-life optoelectronics applications
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