Improved pseudobonds for combined ab initio quantum mechanical/molecular mechanical methods

2005 ◽  
Vol 122 (2) ◽  
pp. 024114 ◽  
Author(s):  
Yingkai Zhang
2021 ◽  
Vol 22 (9) ◽  
pp. 4378
Author(s):  
Anna Helena Mazurek ◽  
Łukasz Szeleszczuk ◽  
Dariusz Maciej Pisklak

This review focuses on a combination of ab initio molecular dynamics (aiMD) and NMR parameters calculations using quantum mechanical methods. The advantages of such an approach in comparison to the commonly applied computations for the structures optimized at 0 K are presented. This article was designed as a convenient overview of the applied parameters such as the aiMD type, DFT functional, time step, or total simulation time, as well as examples of previously studied systems. From the analysis of the published works describing the applications of such combinations, it was concluded that including fast, small-amplitude motions through aiMD has a noticeable effect on the accuracy of NMR parameters calculations.


Micromachines ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1002
Author(s):  
Caterina Cocchi ◽  
Holger-Dietrich Saßnick

Ab initio quantum–mechanical methods are well-established tools for material characterization and discovery in many technological areas. Recently, state-of-the-art approaches based on density-functional theory and many-body perturbation theory were successfully applied to semiconducting alkali antimonides and tellurides, which are currently employed as photocathodes in particle accelerator facilities. The results of these studies have unveiled the potential of ab initio methods to complement experimental and technical efforts for the development of new, more efficient materials for vacuum electron sources. Concomitantly, these findings have revealed the need for theory to go beyond the status quo in order to face the challenges of modeling such complex systems and their properties in operando conditions. In this review, we summarize recent progress in the application of ab initio many-body methods to investigate photocathode materials, analyzing the merits and the limitations of the standard approaches with respect to the confronted scientific questions. In particular, we emphasize the necessary trade-off between computational accuracy and feasibility that is intrinsic to these studies, and propose possible routes to optimize it. We finally discuss novel schemes for computationally-aided material discovery that are suitable for the development of ultra-bright electron sources toward the incoming era of artificial intelligence.


2015 ◽  
Vol 17 (17) ◽  
pp. 11670-11677 ◽  
Author(s):  
Alessandro Erba ◽  
Jefferson Maul ◽  
Raffaella Demichelis ◽  
Roberto Dovesi

Accurate ab initio calculations of thermodynamic and structural thermal properties of corundum demonstrate its quasi-harmonic nature up to the melting temperature.


Author(s):  
Nigel G. J. Richards

Computational methods that can be employed to investigate fundamental questions concerning the complex chemical and structural behavior of biological molecules such as proteins, carbohydrates, and nucleic acids have been traditionally limited by the large number of atoms that comprise even the simplest system of biochemical interest. As a consequence, highly parameterized, empirical force field methods have been developed that describe the energy of macromolecular structures as a function of the spatial locations of the atomic nuclei. In combination with algorithms for simulating molecular dynamics, these classical models allow relatively accurate calculations of the structural and thermodynamic properties associated with proteins and nucleic acids. On the other hand, empirical approaches cannot be used to model molecular behavior that is directly dependent on electrons and their energies. For example, no information can be obtained concerning the electronic spectra of macromolecule/ligand complexes, electron transfer reactions such as those that occur within the photosynthetic reaction center, nitrogenase, an enzyme involved in nitrogen fixation, or cytochrome c oxidase which catalyzes the reduction of oxygen in the last step of aerobic respiration. Accurate modeling of transition states, excited states, and intermediates in biological catalysis requires application of quantummechanical (QM) representations since all of these phenomena depend on the distribution and/or excitation of electrons. At present, the most accurate ab initio algorithms for calculating electronic structure cannot be applied to systems comprised of hundreds of atoms, as such calculations scale as N4–N7 on most workstations, where N is the number of functions used in constructing the many-electron, molecular wavefunction. Even with the implementation of ab initio codes optimized for use on parallel computing engines, and density functional approaches, it is likely that high-accuracy QM calculations in the near future will remain limited to systems that comprise tens, rather than hundreds, of nonhydrogen atoms. Semi-empirical quantum-mechanical methods combine fundamental theoretical treatments of electronic behavior with parameters obtained from experiment to obtain approximate wavefunctions for molecules composed of hundreds of atoms.


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