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Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller-Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube.

This work analyzes the performance of 250 electronic structure theory methods (including 240 density functional approximations) for the description of spin states and the binding properties of iron, manganese, and cobalt porphyrins. The assessment employs the Por21 database of high-level computational data (CASPT2 reference energies taken from the literature). Results show that current approximations fail to achieve the "chemical accuracy" target of 1.0 kcal/mol by a long margin. The best-performing methods achieve a mean unsigned error (MUE) <15.0 kcal/mol, but the errors are at least twice as large for most methods. Semilocal functionals and global hybrid functionals with a low percentage of exact exchange are found to be the least problematic for spin states and binding energies, in agreement with the general knowledge in transition metal computational chemistry. Approximations with high percentages of exact exchange (including range-separated and double-hybrid functionals) can lead to catastrophic failures. More modern approximations usually perform better than older functionals. An accurate statistical analysis of the results also casts doubts on some of the reference energies calculated using multireference methods. Suggestions and general guidelines for users are provided in the conclusions. These results hopefully stimulate advances for both the wave function and the density functional side of electronic structure calculations.

Allylation reactions of aldehydes are chemical transformations of fundamental interest, as they give direct access to chiral homoallylic alcohols. In this work, we focus on the full computational characterization of the catalytic activity of substituted biisoquinoline-N,N'-dioxides for the allylation of 2-naphthaldehyde. We characterized the structure of all transition states as well as identified the π stacking interactions that are responsible for their relative energies. Motivated by disagreement with the experimental results, we also performed an assessment of 34 different density functional methods, with the goal of assessing DFT as a general tool for understanding this chemistry. We found that the DFT results are generally consistent as long as functionals that correctly account for dispersion interactions are used. However, agreement with the experimental results is not always guaranteed. We suggest the need for a careful synergy between computations and experiments to correctly interpret the data and use them as a design tool for new and improved asymmetric catalysts., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest.

A new class of axial-chiral biisoquinoline N , N '-dioxides was evaluated as catalysts for the enantioselective hydrosilylation of acyl hydrazones with trichlorosilane. While these catalysts provided poor to moderate reactivity and enantioselectivity, this study represents the first example of the organocatalytic asymmetric reduction of acyl hydrazones. In addition, the structures and energies of two possible diastereomeric catalyst-trichlorosilane complexes ( 2a -HSiCl 3 ) were analyzed using density functional theory calculations., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest.

The 7-nitroindolinyl family of caging chromophores has received much attention in the past two decades. However, its uncaging mechanism is still not clearly understood. In this study, we performed state-of-the-art density functional theory calculations to unravel the photo-uncaging mechanism in its entirety, and we compared the probabilities of all plausible pathways. We found competition between a classical cyclization and an acyl migration pathway, and here we explain the electronic and steric reasons behind such competition. The migration mechanism possesses the characteristics of a combined Norrish type I and a 1,6-nitro-acyl variation of a Norrish type II mechanism, which is reported here for the first time. We also found negligible energetic differences in the uncaging mechanisms of the 4-methoxy-5,7-dinitroindolinyl (MDNI) cages and their mononitro analogues (MNI). We traced the experimentally observed improved quantum yields of MDNI to a higher population of the reactants in the triplet surface. This fact is supported by a more favorable intersystem crossing due to the availability of a higher number of triplet excited states with the correct symmetry in MDNI than in MNI. Our findings may pave the way for improved cage designs that possess higher quantum yields and a more efficient agonist release.

The stability of the five main isomers of C6H3(+) was investigated using quantum chemical calculations. The cyclic isomers are stabilized by two complementary aromatic effects, first 6-electron π aromaticity, and second a more unusual three-center two-electron σ aromaticity. Two cyclic isomers sit at the bottom of the potential energy surface with energies very close to each other, with a third cyclic isomer slightly higher. The reaction barriers for the interconversion of these isomers, as well as to convert to low-energy linear isomers, are found to be very high with transition states that break both the π and the σ aromaticities. Finally, possibilities for forming the cyclic isomers via association reactions are discussed.

Using quantum chemical approximations to understand and predict complex transition metal chemistry, such as catalytic processes and materials properties, is an important activity in modern computational chemistry. High-level theory can sometimes provide high-precision benchmarks for systems containing transition metals, and these benchmarks can be used to understand the reliability of less expensive quantum chemical approximations that are applicable to complex systems. Here, we studied the ionization potential energy of Fe and FeC and the bond dissociation energies of FeC and FeC(+) by 15 density functional approximations: M05, M06, M06-L, ωB97, ωB97X, ωB97X-D, τ-HCTHhyb, BLYP, B3LYP, M08-HX, M08-SO, SOGGA11, SOGGA11-X, M11, and M11-L. All of the functionals predict the correct spin state as the ground state of neutral iron atom, but five of them predict the wrong spin state for Fe(+). In the final analysis, four functionals, namely M11-L, τ-HCTHhyb, SOGGA11, and M06-L, have small mean unsigned errors when averaged over two bond dissociation energies and two ionization potentials. In fact, the results show that M11-L gives the smallest averaged mean unsigned error, i.e., M11-L is the most reliable density functional for these iron carbide systems among those studied.