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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. [ABSTRACT FROM AUTHOR]

Density functional theory (DFT) has become ubiquitous for chemical applications in research and in education. The exact functional at the foundation of DFT is unfortunately unknown, and issues arise when choosing an approximation for a specific application. With this tutorial review, we tackle the selection problem and many related ones, such as the choices of a basis set and of an integration grid, that are often overlooked by occasional practitioners and by more experienced users as well. We offer a practical approach in the form of a commented notebook containing 12 experiences that can be run on a simple computer in just a few hours. We propose this review as a primary source for those who are willing to include DFT in their everyday research or teaching activities in a way that reflects the research advances of the field in the last couple of decades. [ABSTRACT FROM AUTHOR]

The importance of databases of reliable and accurate data in chemistry has substantially increased in the past two decades. Their main usage is to parametrize electronic structure theory methods, and to assess their capabilities and accuracy for a broad set of chemical problems. The collection we present here—ACCDB—includes data from 16 different research groups, for a total of 44,931 unique reference data points, all at a level of theory significantly higher than density functional theory, and covering most of the periodic table. It is composed of five databases taken from literature (GMTKN, MGCDB84, Minnesota2015, DP284, and W4‐17), two newly developed reaction energy databases (W4‐17‐RE and MN‐RE), and a new collection of databases containing transition metals. A set of expandable software tools for its manipulation is also presented here for the first time, as well as a case study where ACCDB is used for benchmarking commercial CPUs for chemistry calculations. © 2018 Wiley Periodicals, Inc. ACCDB—A Collection of Chemistry DataBases—includes five previously published databases from different sources (GMTKN, MGCDB84, DP284, Minnesota2015B, and W4‐17), and three new one (W4‐17‐RE, MN‐RE, and Metals&EE), and it includes 44,931 unique reference data (all at a level significantly higher than DFT), and 10,049 structures. Software tools for manipulation of ACCDB are also presented, as well as a case study for the performance of commercial CPUs for quantum chemistry calculations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• New database for assessing and developing functionals and semi-empirical methods. • Benchmarking of several popular methods for geometry optimization. • Comparison between the long bonds in CLB18 with bond lengths in transition structures. • Inclusion of effects beyond dispersion not commonly found in other structural database in the literature. We introduce a new database called Carbon Long Bond 18 (CLB18), composed of 18 structures with one long C–C bond. We use this new database to evaluate the performance of several low-cost methods commonly used for geometry optimization of medium and large molecules. We found that the long bonds in CLB18 are electronically different from those found in barrier heights databases. We also report the unexpected correlation between the results of CLB18 and those of the energetics of spin states in transition-metal complexes. Given this unique property, CLB18 can be a useful tool for assessing existing electronic structure calculation methods and developing new ones. [ABSTRACT FROM AUTHOR]