اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدAdsorption and dissociation of O$_{2}$ at Be(0001): First-principles prediction of an energy barrier on the adiabatic potential energy surface
278
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The adsorption and dissociation of O$_{2}$ molecules at the Be(0001) surface is studied by using density-functional theory within the generalized gradient approximation and a supercell approach. The physi- and chemisorbed molecular precursor states are identified to be along the parallel and vertical channels, respectively. It is shown that the HH-Z (see the text for definition) channel is the most stable channel for the molecular chemisorption of O$_{2}$. The electronic and magnetic properties of this most stable chemisorbed molecular state are studied, which shows that the electrons transfer forth and back between the spin-resolved antibonding $pi^{ast}$ molecular orbitals and the surface Be $sp$ states. A distinct covalent weight in the molecule-metal bond is also shown. The dissociation of O$_{2}$ is determined by calculating the adiabatic potential energy surfaces, wherein the T-Y channel is found to be the most stable and favorable for the dissociative adsorption of O$_{2}$. Remarkably, we predict that unlike the other simple $sp$ metal surfaces such as Al(111) and Mg(0001), the textit{adiabatic} dissociation process of O$_{2}$ at Be(0001) is an activated type with a sizeable energy barrier.
قيم البحث
اقرأ أيضاً
We report first-principles calculations of acoustic surface plasmons on the (0001) surface of Be, as obtained in the random-phase approximation of many-body theory. The energy dispersion of these collective excitations has been obtained along two sym
metry directions. Our results show a considerable anisotropy of acoustic surface plasmons, and underline the capability of experimental measurements of these plasmons to {it map} the electron-hole excitation spectrum of the quasi two-dimensional Shockley surface state band that is present on the Be(0001) surface.
The structural, elastic and electronic properties of ReN are investigated by first-principles calculations based on density functional theory. Two competing structures, i.e., CsCl-like and NiAs-like structures, are found and the most stable structure
, NiAs-like, has a hexagonal symmetry which belongs to space group P63/mmc with a=2.7472 and c=5.8180 AA. ReN with hexagonal symmetry is a metal ultra-incompressible solid and has less elastic anisotropy. The ultra-incompressibility of ReN is attributed to its high valence electron density and strong covalence bondings. Calculations of density of states and charge density distribution, together with Mulliken atomic population analysis, show that the bondings of ReN should be a mixture of metallic, covalent, and ionic bondings. Our results indicate that ReN can be used as a potential ultra-incompressible conductor. In particular, we obtain a superconducting transition temperature T$_c$=4.8 K for ReN.
Ab initio structure prediction methods have been nowadays widely used as powerful tools for structure searches and material discovery. However, they are generally restricted to small systems owing to the heavy computational cost of underlying density
functional theory (DFT) calculations. In this work, by combining state-of-art machine learning (ML) potential with our in-house developed CALYPSO structure prediction method, we developed two acceleration schemes for structure prediction toward large systems, in which ML potential is pre-constructed to fully replace DFT calculations or trained in an on-the-fly manner from scratch during the structure searches. The developed schemes have been applied to medium- and large-sized boron clusters, which are challenging cases for both construction of ML potentials and extensive structure searches. Experimental structures of B36 and B40 clusters can be readily reproduced, and the putative global minimum structure for B84 cluster is proposed, where substantially less computational cost by several orders of magnitude is evident if compared with full DFT-based structure searches. Our results demonstrate a viable route for structure prediction toward large systems via the combination of state-of-art structure prediction methods and ML techniques.
We have used diffusion Monte Carlo (DMC) simulations to calculate the energy barrier for H$_2$ dissociation on the Mg(0001) surface. The calculations employ pseudopotentials and systematically improvable B-spline basis sets to expand the single parti
cle orbitals used to construct the trial wavefunctions. Extensive tests on system size, time step, and other sources of errors, performed on periodically repeated systems of up to 550 atoms, show that all these errors together can be reduced to $sim 0.03$ eV. The DMC dissociation barrier is calculated to be $1.18 pm 0.03$ eV, and is compared to those obtained with density functional theory using various exchange-correlation functionals, with values ranging between 0.44 and 1.07 eV.
Alanates and boranates are studied intensively because of their potential use as hydrogen storage materials. In this paper we present a first-principles study of the electronic structure and the energetics of beryllium boranate, Be(BH4)2. From total
energy calculations we show that - in contrast to the other boranates and alanates - hydrogen desorption directly to the elements is likely, and is at least competitive with desorption to the elemental hydride (BeH2). The formation enthalpy of Be(BH4)2 is only -0.12 eV/H2 (at T=0K). This low value can be rationalized by the participation of all atoms in the covalent bonding, in contrast to the ionic bonding observed in other boranates. From calculations of thermodynamic properties at finite temperature we estimate a decomposition temperature of 162 K at a pressure of 1 bar.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
