Structures, stabilities, and electronic properties of F-doped Sin （n=1～12） clusters：Density functional theory investigation

The geometries, stabilities, and electronic properties of FSin （n=1～12） clusters are systematically investigated by using first-principles calculations based on the hybrid density-functional theory at the B3LYP/6-311G level. The geometries are found to undergo a structural change from two-dimensional to three-dimensional structure when the cluster size n equals 3. On the basis of the obtained lowest-energy geometries, the size dependencies of cluster properties, such as averaged binding energy, fragmentation energy, second-order energy difference, HOMO–LUMO （highest occupied molecular orbital–lowest unoccupied molecular orbital） gap and chemical hardness, are discussed. In addition, natural population analysis indicates that the F atom in the most stable FSin cluster is recorded as being negative and the charges always transfer from Si atoms to the F atom in the FSin clusters.

Size Effect on the Raman Spectra and Electronic Structure of the Glycine-alanine Oligopeptide Chains

A theoretical study on oligopeptide chains of glycine-alanine by density functional theory（DFT） is given in this paper. Raman spectra of the oligopeptide chains are examined. The geometric structures, frontier orbital, energy gap, atomic charge distribution, density of states and chemical activity of the side chain are studied at the B3LYP/6-31G（d） level. Results show that, with the number of residues increasing, vibrations of typical functional groups present Raman frequency shift, and the energy gap is gradually reduced. The HOMO and LUMO focus on the amino and carboxyl at the ends of oligopeptides. It is helpful for oligopeptides to self-assemble into chains. In addition, different residues（glycine or alanine） at the ends of chains result in the even-odd effect of orbital energy in the growth process. The size effects of physical and chemical properties only exist when the oligopeptides are shorter, and the phenomenon disappeared as the chain continues to grow.

Structural, Electronic and Optical Properties of Te-Doped GaAs Nanowires： the First Principles Study

The first-principles calculations have been performed to determine the effects of Te doping to the structural, electronic, and optical properties of Ga As NWs. The calculated formation energies show that the single Te energetically prefers to substitute the core Ga（Ef = 0.4111 eV） under As-rich conditions of Ga As nanowires, while on surface, the single Te tends to substitute the surface As site. With increasing the Te concentration, the favorable substitution sites are 2Te–Ga–A and 3Te–Ga–D. Thus, the stability of the structure of the electronic structure and optical properties are discussed.

Theoretical calculations of structural, electronic, and elastic properties of CdSe_(1-x)Te_x:A first principles study

The plane wave pseudo-potential method was used to investigate the structural, electronic, and elastic properties of Cd Se_（1-x）Te_x in the zinc blende phase. It is observed that the electronic properties are improved considerably by using LDA ＋ U as compared to the LDA approach. The calculated lattice constants and bulk moduli are also comparable to the experimental results. The cohesive energies for pure Cd Se and Cd Te binary and their mixed alloys are calculated. The second-order elastic constants are also calculated by the Lagrangian theory of elasticity. The elastic properties show that the studied material has a ductile nature.

Graph representation-based machine learning framework for predicting electronic band structures of quantum-confined nanostructures

The application of machine learning(ML)to electronic structure theory enables electronic property prediction with ab initio accuracy.However,most previous ML models predict one or several properties of intrinsic materials.The prediction of electronic band structure,which embeds all the main electronic information,has yet to be deeply studied.This is a challenging task due to the highly variable inputs and outputs;the input materials may have different sizes and compositions,and the output band structures may have varying band numbers and k-point samplings.This task becomes even more difficult when quantum-confined nanostructures are considered,whose band structures are sensitive to the confinements applied.This paper presents an ML framework for predicting band structures of quantum-confined nanostructures from their geometries.Our framework introduces a graph convolutional network applicable to materials with varying compositions and geometries to extract their atoms’local environment information.A learnable real-space Hamiltonian construction process then enables the utilization of the information to predict the electronic structure at any arbitrary k-point;the theoretical foundations introduced in this process help to capture and incorporate minor changes in quantum confinements into band structures,and endow the framework with the ability of few-shot learning.Taking an example of graphene nanoribbons,typical quantum-confined nanostructures,we show how the framework is constructed and its excellent performance on band structure prediction with a tiny data set.Our framework may not only provide a rapid yet reliable method for electronic structure determination but also enlighten the applications of graph representation to ML in related fields.

QED-Like Simple High Order Perturbative Relation between the Gravitational Constant <i>G</i>and the Planck Constant <i>h</i>

We find a simple precise formula for the gravitational constant G relating it to the electron charge, electron mass, the vacuum dielectric constant and the speed of light (or magnetic permeability of the vacuum) in power of the fine structure constant i.e. relating the gravitational constant to the Planck constant through others which also well exist without the quantum mechanics therefore relating two fundamental constants as not independent through the parameters of the electron and the electromagnetic properties of the vacuum.

Comparative DFT Study of [Mg(CHZ)_3](ClO_4)_2 and [Mg(CHZ)_3](NO_3)_2(CHZ=Carbohydrazide)

The molecular geometry,electronic structure,thermochemistry and infrared spectra of [Mg（CHZ）3]（ClO4）2 and [Mg（CHZ）3]（NO3）2 were comparatively studied using the Heyd-Scuseria-Ernzerhof（HSE） screened hybrid density functional with 6-31G＊＊ basis set.The experimental results show that the complexes have six-coordinated octahedron feature,and the metal-ligand interactions are predominantly ionic in nature.The calculated heats of formation predict that [Mg（CHZ）3]（NO3）2 is more stable than [Mg（CHZ）3]（ClO4）2.Detailed NBO analyses indicate that the ligand-anion interaction plays an important role in the stability for these two energetic complexes.Moreover,the stretching vibration frequencies of N-H bonds shift to lower wave number compared to the free CHZ ligand,which are caused by the delocalizations from N-H bond orbital to lone-pair electron antibond orbital of magnesium.