Optical Spectra of Bi2Se3: The Effects of Electron-Hole Interactions

2019 ◽  
Vol 966 ◽  
pp. 489-493
Author(s):  
Desy Nicola Asturo ◽  
Ahmad Syahroni ◽  
Muhammad Aziz Majidi
Keyword(s):  
Density Functional ◽  
Computational Cost ◽  
Grid Method ◽  
Optical Spectra ◽  
Electron Interaction ◽  
Electron Hole ◽  
Many Body Perturbation Theory ◽  
Excitonic Effects ◽  
Double Grid ◽  
Quantum Espresso

Bi2Se3 has recently become the focus of research development due to its unique transport properties. It is a narrow band gap semiconductor with conducting states on its surface. A reliable and accurate calculation of the optical spectra including excitonic effects is very limited for this material. One of the reasons is that such calculations are computationally demanding since they require a very dense k-point sampling of the Brillouin zone. In this work, we use density functional theory as implemented in Quantum Espresso package to calculate the ground state properties of this material. Optical spectra are calculated within many-body perturbation theory by solving the Bethe-Salpeter equation in Yambo code to account for electron-hole interaction. A double-grid method implemented in Yambo helps us to do accurate calculations of the optical spectra with inexpensive computational cost. Furthermore, we expect that in bulk semiconductor with a narrow gap, electron-electron interaction is weak due to environmental screening. For this reason, to reduce the computational efforts, in this work we neglect the electron-electron interaction.

Pros and cons of time-dependent hybrid density functional approach to optical spectra of solids: a case study of CeO2

2021 ◽  
Author(s):  
Huai-Yang Sun ◽  
Shuo-Xue Li ◽  
Hong Jiang
Keyword(s):  
First Principles ◽  
Density Functional ◽  
Computational Cost ◽  
Optical Spectra ◽  
First Principles Calculation ◽  
Many Body ◽  
Many Body Perturbation Theory ◽  
Pros And Cons ◽  
Hybrid Density Functional

Prediction of optical spectra of complex solids remains a great challenge for first-principles calculation due to the huge computational cost of the state-of-the-art many-body perturbation theory based GW-Bethe Salpeter equation...

Ab-Initio Calculations for the Electronic Spectra of Cubic and Hexagonal Boron Nitride

2004 ◽  
Vol 829 ◽  
Author(s):  
Guido Satta ◽  
Giancarlo Cappellini ◽  
Valerio Olevano ◽  
Lucia Reining
Keyword(s):  
Boron Nitride ◽  
Random Phase Approximation ◽  
Density Functional ◽  
Hexagonal Boron Nitride ◽  
Random Phase ◽  
Optical Spectra ◽  
Many Body ◽  
Self Energy ◽  
Many Body Effects ◽  
Excitonic Effects

ABSTRACTWe present state of the art fist-principles calculations for the optical spectra and the loss functions of bulk boron nitride in the cubic (c-BN) and in the hexagonal (h-BN) phases. We start from a DFT-LDA density functional Khon-Sham bandstructure to investigate the influence of many-body effects beyond the Random Phase Approximation (RPA) on the optical spectra through the inclusion of self-energy and excitonic effects by a GW calculation and the solution of the Bethe-Salpeter equation. For the loss function we only perform RPA calculations. We show to which extent the description of many-body effects is important for a meaningiful comparison with experiment, and when they can be neglected.

First-Principles Evaluation of the Potential of Borophene as a Monolayer Transparent Conductor

2017 ◽  
Author(s):  
Lyudmyla Adamska ◽  
Sridhar Sadasivam ◽  
Jonathan J. Foley ◽  
Pierre Darancet ◽  
Sahar Sharifzadeh
Keyword(s):  
First Principles ◽  
Density Functional ◽  
State Of The Art ◽  
Transparent Electrode ◽  
Visible Range ◽  
Two Dimensional ◽  
Transparent Conductor ◽  
Many Body ◽  
Functional Theory ◽  
Many Body Perturbation Theory

Two-dimensional boron is promising as a tunable monolayer metal for nano-optoelectronics. We study the optoelectronic properties of two likely allotropes of two-dimensional boron using first-principles density functional theory and many-body perturbation theory. We find that both systems are anisotropic metals, with strong energy- and thickness-dependent optical transparency and a weak (<1%) absorbance in the visible range. Additionally, using state-of-the-art methods for the description of the electron-phonon and electron-electron interactions, we show that the electrical conductivity is limited by electron-phonon interactions. Our results indicate that both structures are suitable as a transparent electrode.

Evaluating Transition Metal Barrier Heights with the Latest DFT Exchange–Correlation Functionals – the MOBH35 Benchmark Dataset

2019 ◽  
Author(s):  
Mark Iron ◽  
Trevor Janes
Keyword(s):  
Transition Metal ◽  
Density Functional ◽  
Computational Cost ◽  
Basis Set ◽  
Functional Theory ◽  
Exchange Correlation ◽  
Barrier Heights ◽  
Complete Basis Set ◽  
Complete Basis Set Limit ◽  
Hybrid Functionals

A new database of transition metal reaction barrier heights – MOBH35 – is presented. Benchmark energies (forward and reverse barriers and reaction energy) are calculated using DLPNO-CCSD(T) extrapolated to the complete basis set limit using a Weizmann1-like scheme. Using these benchmark energies, the performance of a wide selection of density functional theory (DFT) exchange–correlation functionals, including the latest from the Truhlar and Head-Gordon groups, is evaluated. It was found, using the def2-TZVPP basis set, that the ωB97M-V (MAD 1.8 kcal/mol), ωB97X-V (MAD 2.1 kcal/mol) and SCAN0 (MAD 2.1 kcal/mol) hybrid functionals are recommended. The double-hybrid functionals PWPB95 (MAD 1.6 kcal/mol) and B2K-PLYP (MAD 1.8 kcal/mol) did perform slightly better but this has to be balanced by their increased computational cost.

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

2019 ◽  
Author(s):  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
U. Deva Priyakumar
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Computational Cost ◽  
Geometry Optimization ◽  
Dft Methods ◽  
Energy Prediction ◽  
Machine Learning Model ◽  
Equilibrium Structures ◽  
High Level ◽  
Non Equilibrium

Recent advances in artificial intelligence along with development of large datasets of energies calculated using quantum mechanical (QM)/density functional theory (DFT) methods have enabled prediction of accurate molecular energies at reasonably low computational cost. However, machine learning models that have been reported so far requires the atomic positions obtained from geometry optimizations using high level QM/DFT methods as input in order to predict the energies, and do not allow for geometry optimization. In this paper, a transferable and molecule-size independent machine learning model (BAND NN) based on a chemically intuitive representation inspired by molecular mechanics force fields is presented. The model predicts the atomization energies of equilibrium and non-equilibrium structures as sum of energy contributions from bonds (B), angles (A), nonbonds (N) and dihedrals (D) at remarkable accuracy. The robustness of the proposed model is further validated by calculations that span over the conformational, configurational and reaction space. The transferability of this model on systems larger than the ones in the dataset is demonstrated by performing calculations on select large molecules. Importantly, employing the BAND NN model, it is possible to perform geometry optimizations starting from non-equilibrium structures along with predicting their energies.

scholarly journals A quantitative evaluation of computational methods to accelerate the study of alloxazine-derived electroactive compounds for energy storage

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi Zhang ◽  
Abhishek Khetan ◽  
Süleyman Er
Keyword(s):  
Energy Storage ◽  
Density Functional ◽  
Tight Binding ◽  
Computational Cost ◽  
Redox Potentials ◽  
Storage Compounds ◽  
Computational Screening ◽  
Chemical Descriptor ◽  
Lowest Unoccupied Molecular Orbital ◽  
Semi Empirical

AbstractAlloxazines are a promising class of organic electroactive compounds for application in aqueous redox flow batteries (ARFBs), whose redox properties need to be tuned further for higher performance. High-throughput computational screening (HTCS) enables rational and time-efficient study of energy storage compounds. We compared the performance of computational chemistry methods, including the force field based molecular mechanics, semi-empirical quantum mechanics, density functional tight binding, and density functional theory, on the basis of their accuracy and computational cost in predicting the redox potentials of alloxazines. Various energy-based descriptors, including the redox reaction energies and the frontier orbital energies of the reactant and product molecules, were considered. We found that the lowest unoccupied molecular orbital (LUMO) energy of the reactant molecules is the best performing chemical descriptor for alloxazines, which is in contrast to other classes of energy storage compounds, such as quinones that we reported earlier. Notably, we present a flexible in silico approach to accelerate both the singly and the HTCS studies, therewithal considering the level of accuracy versus measured electrochemical data, which is readily applicable for the discovery of alloxazine-derived organic compounds for energy storage in ARFBs.

scholarly journals A machine learning platform for the discovery of materials

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Carl E. Belle ◽  
Vural Aksakalli ◽  
Salvy P. Russo
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Gw Approximation ◽  
Dft Methods ◽  
Functional Theory ◽  
Unit Cell Size ◽  
Learning Platform ◽  
Photovoltaic Materials ◽  
Wide Range ◽  
Quantum Espresso

AbstractFor photovoltaic materials, properties such as band gap $$E_{g}$$ E g are critical indicators of the material’s suitability to perform a desired function. Calculating $$E_{g}$$ E g is often performed using Density Functional Theory (DFT) methods, although more accurate calculation are performed using methods such as the GW approximation. DFT software often used to compute electronic properties includes applications such as VASP, CRYSTAL, CASTEP or Quantum Espresso. Depending on the unit cell size and symmetry of the material, these calculations can be computationally expensive. In this study, we present a new machine learning platform for the accurate prediction of properties such as $$E_{g}$$ E g of a wide range of materials.

Study of thermo-elastic and lattice dynamics properties of half-Heusler compounds XMgAl (X = Li, Na) by computational investigations

2019 ◽  
Vol 33 (08) ◽  
pp. 1950093 ◽  
Author(s):  
A. Afaq ◽  
Abu Bakar ◽  
M. Rizwan ◽  
M. Aftab Fareed ◽  
H. Bushra Munir ◽  
...  
Keyword(s):  
Debye Temperature ◽  
Elastic Constants ◽  
Density Functional ◽  
Phonon Dispersion ◽  
Dynamic Properties ◽  
Mechanical Parameters ◽  
Heusler Compounds ◽  
Generalized Gradient ◽  
Text Type ◽  
Quantum Espresso

In this study, thermo-elastic and lattice dynamic properties of XMgAl (X = Li, Na) half-Heusler compounds are investigated using density functional theory implemented in WIEN2k and Quantum ESPRESSO codes. Generalized gradient approximation (GGA) as an exchange correlation function has been used in Kohn–Sham equations. Firstly, the structure of these Heusler compounds is optimized and then these optimized parameters are used to find three elastic constants [Formula: see text], [Formula: see text] and [Formula: see text] for [Formula: see text] type structures. Three elastic constants are then used to determine different elastic moduli like bulk modulus, shear modulus, Young’s modulus and other mechanical parameters like Pugh’s ratio, Poisson’s ratio, anisotropic ratio, sound velocities, Debye temperature and melting temperature. On behalf of these mechanical parameters, the brittle/ductile nature and isotropic/anisotropic behavior of the materials has been studied. Different regions of vibrational modes in the materials are also discussed on behalf of Debye temperature calculations. The vibrational properties of the half-Heusler compounds are computed using Martins–Troullier pseudo potentials implemented in Quantum ESPRESSO. The phonon dispersion curves and phonon density of states in first Brillion zone are obtained and discussed. Reststrahlen band of LiMgAl is found greater than NaMgAl.

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