Together with experimental data, theoretically predicted dipole moments represent a valuable tool for different branches in the chemical and physical sciences. With the diversity of levels of theory and basis sets available, a reliable combination must be carefully chosen in order to achieve accurate predictions. In a recent publication (J. Chem. Theory Comput. 2018Comput. , 14 (4), 1969Comput. −1981, Hait and Head-Gordon took a first step in this regard by providing recommendations on the best density functionals suitable for these purposes. However, no extensive study has been performed to provide recommendations on the basis set choice. Here, we shed some light into this matter by evaluating the performance of 38 general-purpose basis sets of single-up to triple-ζ-quality, when coupled with nine different levels of theory, in the computation of dipole moments. The calculations were performed on a data set with 114 small molecules containing second-and third-row elements. We based our analysis in regularized root-mean-square errors (regularized RMSE), in which the difference between the calculated μ calc and benchmark μ bmk dipole moment values is derived as (μ calc [D] − μ bmk [D])/ (max(μ bmk [D],1 [D])). This procedure ensures relative errors for ionic species and absolute errors for species with small dipole moment values. Our results indicate that the best compromise between accuracy and computational efficiency is achieved by performing the computations with an augmented double-ζ-quality basis set (i.e., aug-pc-1, aug-pcseg-1, aug-cc-pVDZ) together with a hybrid functional (e.g., ωB97X-V, SOGGA11-X). Augmented triple-ζ basis sets could enhance the accuracy of the computations, but the computational cost of introducing such a basis set is substantial compared with the small improvement provided. These findings also highlight the crucial role that augmentation of the basis set with diffuse functions on both hydrogen and non-hydrogen atoms plays in the computation of dipole moments.

in Wiley InterScience (www.interscience.wiley.com).Tactical management of development pipelines is concerned with the allocation of resources and scheduling of tasks. Though these decisions have to be made in the presence of uncertainty, to make the problem solvable it is customary to use deterministic MILP formulations of the multi-mode RCMPSP that are reevaluated after important uncertainties are realized. In spite of the major simplifications attained by down-playing the stochastic nature of the problem, the curse of dimensionality limits the exact solution of the formulations to very small systems. The curse is mainly caused by 3 factors: the indexing of the task execution modes the indexing of time periods, and the discrete character of the resources. Three models that attempt to overcome these limitations are proposed and compared. Results show that despite the theoretical advantages of the strategies used, the alternative formulations are limited to problems in the same range of applicability of the conventional multi-mode formulation.

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Peer-reviewed publication https://doi.org/10.1071/CH19466The traditional Gaussian basis sets used in modern quantum chemistry lack an electron-nuclear cusp, and hence struggle to accurately describe core electron properties. A recently introduced novel type of basis set, mixed ramp-Gaussians, introduce a new primitive function called a ramp function which addresses this issue.This paper introduces three new mixed ramp-Gaussian basis sets -STO-R, STO-RG and STO-R2G, made from a linear combination of ramp and Gaussian primitive functions -which are derived from the single-core-zeta Slater basis sets for the elements Li to Ne. This derivation is done in an analogous fashion to the famous STO-nG basis sets. The STO-RG basis functions are found to outperform the STO-3G basis functions and STO-R2G outperforms STO-6G, both in terms of wavefunction fit and other key quantities such as the one-electron energy and the electron-nuclear cusp.The second part of this paper performs preparatory investigations into how standard all-Gaussian basis sets can be converted to ramp-Gaussian basis sets through modifying the core basis functions. Using a test case of the 6-31G basis set for carbon, we determined that the second Gaussian primitive is less important when fitting a ramp-Gaussian core basis function directly to an all-Gaussian core basis function than when fitting to a Slater basis function. Further, we identified the basis sets that are single-core-zeta and thus should be most straightforward to convert to mixed ramp-Gaussian basis sets in the future.