اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدTracing potential energy surfaces of electronic excitations via their transition origins: application to Oxirane
206
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We show that the transition origins of electronic excitations identified by quantified natural transition orbital (QNTO) analysis can be employed to connect potential energy surfaces (PESs) according to their character across a widerange of molecular geometries. This is achieved by locating the switching of transition origins of adiabatic potential surfaces as the geometry changes. The transition vectors for analysing transition origins are provided by linear response time-dependent density functional theory (TDDFT) calculations under the Tamm-Dancoff approximation. We study the photochemical CO ring opening of oxirane as an example and show that the results corroborate the traditional Gomer-Noyes mechanism derived experimentally. The knowledge of specific states for the reaction also agrees well with that given by previous theoretical work using TDDFT surface-hopping dynamics that was validated by high-quality quantum Monte Carlo calculations. We also show that QNTO can be useful for considerably larger and more complex systems: by projecting the excitations to those of a reference oxirane molecule, the approach is able to identify and analyse specific excitations of a trans-2,3-diphenyloxirane molecule.
قيم البحث
اقرأ أيضاً
The time-dependent, mean-field Newns-Anderson model for a spin-polarised adsorbate approaching a metallic surface is solved in the wide-band limit. Equations for the time-evolution of the electronic structure of the adsorbate-metal system are derived
and the spectrum of electronic excitations is found. The behaviour of the model is demonstrated for a set of physically reasonable parameters.
We propose a method to decompose the total energy of a supercell containing defects into contributions of individual atoms, using the energy density formalism within density functional theory. The spatial energy density is unique up to a gauge transf
ormation, and we show that unique atomic energies can be calculated by integrating over Bader and charge-neutral volumes for each atom. Numerically, we implement the energy density method in the framework of the Vienna ab initio simulation package (VASP) for both norm-conserving and ultrasoft pseudopotentials and the projector augmented wave method, and use a weighted integration algorithm to integrate the volumes. The surface energies and point defect energies can be calculated by integrating the energy density over the surface region and the defect region, respectively. We compute energies for several surfaces and defects: the (110) surface energy of GaAs, the mono-vacancy formation energies of Si, the (100) surface energy of Au, and the interstitial formation energy of O in the hexagonal close-packed Ti crystal. The surface and defect energies calculated using our method agree with size-converged calculations of the difference between the total energies of the system with and without the defect. Moreover, the convergence of the defect energies with size can be found from a single calculation.
Modifying the optoelectronic properties of nanostructured materials through introduction of dopant atoms has attracted intense interest. Nevertheless, the approaches employed are often trial and error, preventing rational design. We demonstrate the p
ower of large-scale electronic structure calculations with density functional theory (DFT) to build an atlas of preferential dopant sites for a range of M(II) and M(III) dopants in the representative III-V InP magic sized cluster (MSC). We quantify the thermodynamic favorability of dopants, which we identify to be both specific to the sites within the MSC (i.e., interior vs surface) and to the nature of the dopant atom (i.e., smaller Ga(III) vs larger Y(III) or Sc(III)). These observations motivate development of maps of the most and least favorable doping sites, which are consistent with some known experimental expectations but also yield unexpected observations. For isovalent doping (i.e., Y(III)/Sc(III) or Ga(III), we observed stronger sensitivity of the predicted energetics to the type of ligand orientation on the surface than to the dopant type, but divergent behavior is observed for whether interior doping is favorable. For charge balancing with M(II) (i.e., Zn or Cd) dopants, we show that the type of ligand removed during the doping reaction is critical. We show that limited cooperativity with dopants up to moderate concentrations occurs, indicating rapid single-dopant estimations of favorability from DFT can efficiently guide rational design. Our work emphasizes the strong importance of ligand chemistry and surface heterogeneity in determining paths to favorable doping in quantum dots, an observation that will be general to other III-V and II-VI quantum dot systems generally synthesized with carboxylate ligands.
Interatomic potential models based on machine learning (ML) are rapidly developing as tools for materials simulations. However, because of their flexibility, they require large fitting databases that are normally created with substantial manual selec
tion and tuning of reference configurations. Here, we show that ML potentials can be built in a largely automated fashion, exploring and fitting potential-energy surfaces from the beginning (de novo) within one and the same protocol. The key enabling step is the use of a configuration-averaged kernel metric that allows one to select the few most relevant structures at each step. The resulting potentials are accurate and robust for the wide range of configurations that occur during structure searching, despite only requiring a relatively small number of single-point DFT calculations on small unit cells. We apply the method to materials with diverse chemical nature and coordination environments, marking a milestone toward the more routine application of ML potentials in physics, chemistry, and materials science.
Accurately describing excited states within Kohn-Sham (KS) density functional theory (DFT), particularly those which induce ionization and charge transfer, remains a great challenge. Common exchange-correlation (xc) approximations are unreliable for
excited states owing, in part, to the absence of a derivative discontinuity in the xc energy ($Delta$), which relates a many-electron energy difference to the corresponding KS energy difference. We demonstrate, analytically and numerically, how the relationship between KS and many-electron energies leads to the step structures observed in the exact xc potential, in four scenarios: electron addition, molecular dissociation, excitation of a finite system, and charge transfer. We further show that steps in the potential can be obtained also with common xc approximations, as simple as the LDA, when addressed from the ensemble perspective. The article therefore highlights how capturing the relationship between KS and many-electron energies with advanced xc approximations is crucial for accurately calculating excitations, as well as the ground-state density and energy of systems which consist of distinct subsystems.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
