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.

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.

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.

The prediction of 13 C 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 13 C chemical shifts, whereas for the 1 H 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 13 C chemical shifts. On the other hand, for 1 H chemical shifts the opposite is true. Compared to calculations at the MP2 level none of the DFT functionals can compete with MP2 for the 13 C chemical shifts but for the 1 H chemical shifts the investigated DFT functionals are shown to give better agreement with experiment than MP2 calculations.

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.

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 POu N4-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.

Unveiling the details of the mechanisms of a chemical reaction is a difficult task as reaction mechanisms are strongly coupled with reaction conditions. Here, catalysts informatics combined with high-throughput experimental data is implemented to understand the oxidative coupling of methane (OCM) reaction. In particular, pairwise correlation and data visualization are performed to reveal the relation between reaction conditions and selectivity/conversion. In addition, machine learning is used to fill the gap between experimental data points; thus, a more detailed understanding of the OCM reaction against reaction conditions can be achieved. Therefore, catalysts informatics is proposed for understanding the details of the reaction mechanism, thereby aiding reaction design.

Excitonic coupling plays a key role for the understanding of excitonic energy transport (EET) in, for example, organic photovoltaics. However, the calculation of realistic systems is often beyond the applicability range of accurate wavefunction methods so that lower-scaling semi-empirical methods are used to model EET events. In the present work, the distance and angle dependence of excitonic couplings of dimers of selected organic molecules are evaluated for the semi-empirical long-range corrected density functional based tight binding (LC-DFTB) method and spin opposite scaled second order approximate coupled cluster singles and doubles (SOS-CC2). While semi-empirically scaled methods can lead to slightly increased deviations for excitation energies, the excitonic couplings and their dependence on the dimer geometry are reproduced. LC-DFTB yields a similar accuracy range as density-functional theory (DFT) employing the ωB97X functional while the computation time is reduced by several orders of magnitude. The dependence of the exchange contributions to the excitonic couplings on the dimer geometry is analyzed assessing the calculation of Coulombic excitonic couplings from monomer local excited states only, which reduces the computational effort significantly. The present work is a necessary first step toward the simulation of excitonic energy transport using semi-empirical methods.

The new software QSARINS-Chem standalone version is a multiplatform tool, freely downloadable, for the in silico profiling of multiple properties and activities of organic chemicals. This software, which is based on the concept of the QSARINS-chem module embedded in the QSARINS software, has been fully redesigned and redeveloped in the Java™ language. In addition to a selection of models included in the old module, the new software predicts biotransformation rates and aquatic toxicities of pharmaceuticals and personal care products in multiple organisms, and offers a suite of tools for the analysis of predictions. Furthermore, a comprehensive and transparent database of molecular structures is provided. The new QSARINS-Chem standalone version is an informative and solid tool, which is useful to support the assessment of the potential hazard and risks related to organic chemicals and is dedicated to users which are interested in the application of QSARs to generate reliable predictions.

Nowadays, the coupling of electronic structure and machine learning techniques serves as a powerful tool to predict chemical and physical properties of a broad range of systems. With the aim of improving the accuracy of predictions, a large number of representations for molecules and solids for machine learning applications has been developed. In this work we propose a novel descriptor based on the notion of molecular graph. While graphs are largely employed in classification problems in cheminformatics or bioinformatics, they are not often used in regression problem, especially of energy-related properties. Our method is based on a local decomposition of atomic environments and on the hybridization of two kernel functions: a graph kernel contribution that describes the chemical pattern and a Coulomb label contribution that encodes finer details of the local geometry. The accuracy of this new kernel method in energy predictions of molecular and condensed phase systems is demonstrated by considering the popular QM7 and BA10 datasets. These examples show that the hybrid localized graph kernel outperforms traditional approaches such as, for example, the smooth overlap of atomic positions and the Coulomb matrices.

In this article, we use two extensively studied systems, a retinal model system and azobenzene, to explore the use of coupled cluster models for describing ground and singlet excited state potential energy surfaces of photoswitchable systems. While not being suitable for describing nuclear dynamics of photoisomerization, coupled cluster models have useful attributes, such as the inclusion of dynamical correlation, their black box nature, and the systematic improvement offered by truncation level. Results for the studied systems show that when triple excitations (here through the CC3 model) are included, ground and excited state potential energy surfaces for isomerization paths may reliably be generated, also for states of doubly excited character. For ground state equilibrium cis- and trans-azobenzene, the molecular geometry and basis set is seen to significantly impact the vertical excitation energies for the two lowest excited states. Efficient implementations of coupled cluster models can therefore constitute valuable tools for investigating photoswitchable systems and can be used for preliminary black box studies to gather information before more complicated excited state dynamics approaches are pursued.

Dimethyl phosphate (DMP- ) is a model for the phosphodiester backbone of DNA, RNA, and phospholipids. It is central for the binding of divalent cations and water along the backbone of nucleic acids. Significant polarization and charge-transfer contributions and nonadditivity come into play in the multimolecular complexes organized around phosphate. Prior to large-scale molecular dynamics (MD) with advanced polarizable potentials, it is essential to evaluate how well the values and trends of intermolecular interaction energies (ΔE) from ab initio quantum chemistry (QC) and their individual contributions are reproduced in a diversity of such complexes. These differ by the starting binding modes of a divalent cation, Zn(II), namely direct, bi- or mono-dentate to anionic and/or ester oxygens, versus through-water binding. We present first the results from automated refinements of the individual contributions of the SIBFA potential with respect to their QC counterparts using a Zn(II) or a water probe. This is followed by validations on eight relaxed multimolecular complexes of DMP- with Zn(II) or Mg(II) and seven waters, then on sixteen complexes of DMP- with Zn(II) and eight waters in arrangements extracted from MD or energy-minimization on a droplet of sixty-four waters. This monitors the compared evolutions of SIBFA and QC ΔE and their individual contributions in the competing arrangements. Some waters, bridging Zn(II) and DMP- , were found to have exceptionally large dipole moments, of up to 3.8 Debye. The perspectives of extension to a flexible phosphodiester backbone are discussed in the context of the SIBFA potential for DNA and RNA.

Comment on J Comput Chem. 2021 Mar 5;42(6):412-417.

I reply to the comment by Weinhold and Glendening on the article (J. Comput. Chem. 2021, 42, 412). I provide further explanation and an additional numerical example to support my previous assertion that the present form of natural resonance theory is fundamentally flawed, at least within the DFT framework.

The Eighth-Shell method for parallelization of molecular dynamics simulations has previously been shown to be the most optimal for efficiency at large process counts. However, in its current formulation only the P1 space group is supported for periodic boundary conditions (PBC) and thus reflection and/or rotational crystal symmetries are not supported. In this work, we outline the development and implementation of the Extended Eighth-Shell (EES) method that allows rotational symmetry by using an extended import region compared to the ES method. It simulates only the asymmetric unit and communicates coordinates and forces with images that correspond to P21 PBC. The P21 PBC has application in lipid bilayer simulations as it can be used to allow lipids to switch leaftlets, thus rapidly balancing the chemical potential difference between the two layers. Our results show that the EES method scales efficiently over large number of processes and can be used for simulations with P21 symmetry in an orthorhombic crystal.

The two dissociation channels of HOOH, namely, HOOH and HOOH, in water and methanol are investigated using umbrella-sampling ab initio molecular dynamics. Our potential of mean force calculations reveals the HOOH dissociation to be more favorable in methanol with a free energy barrier of 7.56 kcal/mol, while the HOOH dissociation possesses a free energy barrier of 11.46 kcal/mol. In water, the HOOH dissociation channel is more favorable (8.25 kcal/mol), while the HOOH dissociation process requires a higher free energy (11.28 kcal/mol). Such reaction favorability can be explained by inspecting the formation of secondary radical species during the course of multiple hydrogen donating-accepting processes in each reaction channel. The radical species, that is, H3 O• (observed in water) and CH3 OH2• (observed in methanol), are the first subordinate species upon the HOOH dissociation. For the HOOH dissociation channel in methanol, the secondary species such as water and formaldehyde can be observed, while the re-generation of HOOH in water can be spotted.

The present work reports the computational study of the major Diels-Alder reaction between 2-bromocycloalkenone and a variety of mono- and di-substituted dienes. Through density functional theory (DFT) calculations and subsequent activation strain model/energy decomposition analysis/conceptual DFT (C-DFT) analyses, the key factors governing the activation barriers heights, and thus reactivity, are characterized. In contrast with a previous study, steric effects do not appear to control reactivity. Conversely, in all presented cases, a subtle interplay between deformation and interaction energies is evidenced at transition states. In the end, neither term alone is enough to explain or predict reactivity. Yet a simple C-DFT descriptor allows to predict with a reasonable efficiency the activation barriers: the excitation energy needed to observe a charge transfer from the diene to the dienophile. Theoretical elements are provided to support the use of this descriptor.

In this paper, metallocene-fullerene hybrid complexes, [M(η5 -Cp)(η5 -C60 Me5 )] (M = Fe2+ , Ru2+ , Os2+ ), as well as corresponding classical metallocenes have been studied theoretically at BP86/def2-SVP and M06L/def2-SVP levels of theory. With considering these metal complexes as an ABA' system (B is the central metal ion and A and A' are related η5 -ligands), the total interaction energies were calculated using common methods, as well as by calculating the interaction energies between the four defined pairs of fragments including A-B, B-A', A-BA', and AB-A'. The resulting data clearly showed that in all complexes there is a strong anticoopertivity between two metal-(η5 -ligand) bonds. In order to understand the origin of difference in values of various calculated interactions in above two types of complexes, the nature of metal-ligand bonds was also studied using energy decomposition analysis-natural orbital for chemical valence calculations. The results showed that in hybrid complexes, in contrast to metallocenes, the orbital interactions are considerably larger than electrostatic interactions.