Journal of Computational Chemistry

doi: 10.1002/jcc.26295pmid: N/A

Zahn, Sarah L. V.; Hammerich, Ole; Hansen, Poul Erik; Sauer, Stephan P. A.

doi: 10.1002/jcc.26540pmid: 33931893

The prediction of 13C chemical shifts can be challenging with density functional theory (DFT). In this study 39 different functionals and three different basis sets were tested on three neutral alkylpyrroles and their corresponding protonated species. The calculated shielding constants were compared to experimental data and results from previous calculations at the MP2. We find that the meta‐hybrid functional TPSSh with either the Pople style basis set 6‐311++G(2d,p) or the polarization consistent basis set pcSseg‐1 gives the best results for the 13C chemical shifts, whereas for the 1H chemical shifts it is the TPSSh functional with either the 6‐311++G(2d,p) or pcSseg‐2 basis set. Including an explicit solvent molecule hydrogen bonded to NH in the alkylpyrroles improves the results slightly for the 13C chemical shifts. On the other hand, for 1H chemical shifts the opposite is true. Compared to calculations at the MP2 level none of the DFT functionals can compete with MP2 for the 13C chemical shifts but for the 1H chemical shifts the investigated DFT functionals are shown to give better agreement with experiment than MP2 calculations.

Pechlaner, Maria; Oostenbrink, Chris; Gunsteren, Wilfred F.

doi: 10.1002/jcc.26541pmid: 33951201

Computer simulation of proteins in aqueous solution at the atomic level of resolution is still limited in time span and system size due to limited computing power available and thus employs a variety of time‐saving techniques that trade some accuracy against computational effort. Examples of such time‐saving techniques are the application of constraints to particular degrees of freedom or the use of a multiple‐time‐step (MTS) algorithm distinguishing between particular forces when integrating Newton's equations of motion. The application of two types of MTS algorithms to bond‐stretching forces versus the remaining forces in molecular dynamics (MD) simulations of a protein in aqueous solution or of liquid water is investigated and the results in terms of total energy conservation and the influence on various other properties are compared to those of MD simulations of the same systems using bond‐length, and for water bond‐angle, constraints. At comparable computational effort, the use of bond‐length constraints in proteins leads to better energy conservation and less distorted properties than the two MTS algorithms investigated.

Henkel, Pascal; Mollenhauer, Doreen

doi: 10.1002/jcc.26546pmid: 33949700

Amorphous lithium phosphorus oxynitride (LIPON) has emerged as a promising solid electrolyte for all‐solid‐state thin‐film lithium batteries. In this context, the use of theoretical modeling to characterize, understand, or screen material properties is becoming increasingly important to complement experimental analysis or elucidate features at atomistic level that are difficult to obtain through experimental studies. Density functional theory (DFT) is the method of choice for quantum mechanical material modeling at the atomistic scale. The current state of the art represents DFT values, such as the formation or migration energies relevant for bulk phase of materials, as absolute numbers. Estimating the accuracy or fluctuation range of the different density functionals is challenging. In order to investigate the thermodynamic and kinetic properties of LIPON by DFT, an approach to describe the fluctuation range caused by the choice of the exchange‐correlation (XC) functional is developed. Three different model systems were chosen to characterize various structural features of amorphous LIPON, which are distinguished by the cross‐linking of the POuN4‐u‐structural units. The uncertainty Ũ is introduced as a parameter describing the fluctuation range of energy values. The uncertainty approach does not determine the accuracy of DFT results, but rather a fluctuation range in the DFT results without the need for a reference value from a higher level of theory or experiment. The uncertainty was determined for both the thermodynamic Li‐vacancy formation energies and the kinetic Li‐vacancy migration energies in LIPON. We assume that the uncertainty approach can be applied to different material systems with different density functionals.

Khorief Nacereddine, Abdelmalek; Merzoud, Lynda; Morell, Christophe; Chermette, Henry

doi: 10.1002/jcc.26547pmid: 33931864

The selectivity and the mechanism of the uncatalyzed and AlCl3 catalyzed hetero‐Diels–Alder reaction (HDR) between ([E]‐4‐methylpenta‐2,4‐dienyloxy)(tert‐butyl)dimethylsilane 1 and benzaldehyde 2 have been studied using density functional theory at the MPWB1K/6‐31G(d) level of theory. The uncatalyzed HDR between diene 1 and alkene 2 is characterized by a polar character and proceeds via an asynchronous one‐step mechanism for the meta paths and synchronous for the ortho ones. In the presence of AlCl3 catalyst, the mechanism changes to be stepwise, while the first step is the rate‐determining step. The activation energies widely decrease, and the polar character increases dramatically. A large analysis of the mechanism is performed using the activation strain model/energy decomposition analysis (ASM/EDA) model, the natural bond orbital (NBO) and state specific dual descriptors (SSDDs). The obtained results indicate that the combined interaction energy associated with the distortion of the reactants in these HDR are at the origin of the observed kinetics. NBO analyses were applied to estimate the Lewis‐acid catalyst donor‐acceptor interaction with the molecular system. The SSDD analysis shed light into the orientation effects on the reaction kinetics by providing important information about charge transfer interactions during the chemical reaction. It indicates that the more favorable HDR pathway have the lowest excitation energies, facilitating the interaction between diene 1 and benzaldehyde 2 moieties. Non‐covalent interaction (NCI) and QTAIM analyses of the meta‐endo structure indicate that the presence of several weak NCIs formed at this approach is at the origin of the meta‐endo selectivity.

Eidi, Mohammadreza; Vafaee, Mohsen; Koochaki Kelardeh, Hamed; Landsman, Alexandra

doi: 10.1002/jcc.26549pmid: 33960416

We solve the time‐dependent Schrodinger equation using the coherent states as basis sets for computing high harmonic generation (HHG) in a full‐dimensional single‐electron “realistic” system. We apply the static coherent states (SCS) method to investigate HHG in the hydrogen molecular ion induced by a linearly polarized laser field. We show that SCS gives reasonable agreement compared to the three dimensional unitary split‐operator approach. Next, we study isolated attosecond pulse generation in H2+. To do so, we employ the well‐known polarization gating technique, which combines two delayed counter‐rotating circular laser pulses, and opens up a gate at the central portion of the superposed pulse. Our results suggest that the SCS method can be used for full‐dimensional quantum simulation of higher dimensional systems such as the hydrogen molecule in the presence of an external laser field.

DeFever, Ryan S.; Matsumoto, Ray A.; Dowling, Alexander W.; Cummings, Peter T.; Maginn, Edward J.

doi: 10.1002/jcc.26544pmid: 33931885

We introduce a new Python interface for the Cassandra Monte Carlo software, molecular simulation design framework (MoSDeF) Cassandra. MoSDeF Cassandra provides a simplified user interface, offers broader interoperability with other molecular simulation codes, enables the construction of programmatic and reproducible molecular simulation workflows, and builds the infrastructure necessary for high‐throughput Monte Carlo studies. Many of the capabilities of MoSDeF Cassandra are enabled via tight integration with MoSDeF. We discuss the motivation and design of MoSDeF Cassandra and proceed to demonstrate both simple use‐cases and more complex workflows, including adsorption in porous media and a combined molecular dynamics – Monte Carlo workflow for computing lateral diffusivity in graphene slit pores. The examples presented herein demonstrate how even relatively complex simulation workflows can be reduced to, at most, a few files of Python code that can be version‐controlled and shared with other researchers. We believe this paradigm will enable more rapid research advances and represents the future of molecular simulations.