The ab initio potential energy curves of atom pairs and transport properties of high-temperature vapors of Cu and Si and their mixtures with He, Ar, and Xe gases.

The potential energy curves (PECs) for the homonuclear He-He, Ar-Ar, Cu-Cu, and Si-Si dimers, as well as heteronuclear Cu-He, Cu-Ar, Cu-Xe, Si-He, Si-Ar, and Si-Xe dimers, are obtained in quantum Monte Carlo (QMC) calculations. It is shown that the QMC method provides the PECs with an accuracy comparable with that of the state-of-the-art coupled cluster singles and doubles with perturbative triples corrections [CCSD(T)] calculations. The QMC data are approximated by the Morse long range (MLR) and (12-6) Lennard-Jones (LJ) potentials. The MLR and LJ potentials are used to calculate the deflection angles in binary collisions of corresponding atom pairs and transport coefficients of Cu and Si vapors and their mixtures with He, Ar, and Xe gases in the range of temperature from 100 K to 10 000 K. It is shown that the use of the LJ potentials introduces significant errors in the transport coefficients of high-temperature vapors and gas mixtures. The mixtures with heavy noble gases demonstrate anomalous behavior when the viscosity and thermal conductivity can be larger than that of the corresponding pure substances. In the mixtures with helium, the thermal diffusion factor is found to be unusually large. The calculated viscosity and diffusivity are used to determine parameters of the variable hard sphere and variable soft sphere molecular models as well as parameters of the power-law approximations for the transport coefficients. The results obtained in the present work include all information required for kinetic or continuum simulations of dilute Cu and Si vapors and their mixtures with He, Ar, and Xe gases.

Why Na+ has higher propensity than K+ to condense DNA in a crowded environment.

Experimentally, in the presence of the crowding agent polyethylene glycol (PEG), sodium ions compact double-stranded DNA more readily than potassium ions. Here, we have used molecular dynamics simulations and the "ion binding shells model" of DNA condensation to provide an explanation for the observed variations in condensation of short DNA duplexes in solutions containing different monovalent cations and PEG; several predictions are made. According to the model we use, externally bound ions contribute the most to the ion-induced aggregation of DNA duplexes. The simulations reveal that for two adjacent DNA duplexes, the number of externally bound Na+ ions is larger than the number of K+ ions over a wide range of chloride concentrations in the presence of PEG, providing a qualitative explanation for the higher propensity of sodium ions to compact DNA under crowded conditions. The qualitative picture is confirmed by an estimate of the corresponding free energy of DNA aggregation that is at least 0.2kBT per base pair more favorable in solution with NaCl than with KCl at the same ion concentration. The estimated attraction free energy of DNA duplexes in the presence of Na+ depends noticeably on the DNA sequence; we predict that AT-rich DNA duplexes are more readily condensed than GC-rich ones in the presence of Na+. Counter-intuitively, the addition of a small amount of a crowding agent with high affinity for the specific condensing ion may lead to the weakening of the ion-mediated DNA-DNA attraction, shifting the equilibrium away from the DNA condensed phase.

Comment on "Pushing the frontiers of density functionals by solving the fractional electron problem".

Kirkpatrick et al. (Reports, 9 December 2021, p. 1385) trained a neural network-based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. Here, we show that the ability of DM21 to generalize the behavior of such systems does not follow from the published results and requires revisiting.

Similarities and Differences between Na+ and K+ Distributions around DNA Obtained with Three Popular Water Models.

We have compared distributions of sodium and potassium ions around double-stranded DNA, simulated using fixed charge SPC/E, TIP3P, and OPC water models and the Joung/Cheatham (J/C) ion parameter set, as well as the Li/Merz HFE 6-12 (L/M HFE) ion parameters for OPC water. In all the simulations, the ion distributions are in qualitative agreement with Manning's condensation theory and the Debye-Hückel theory, where expected. In agreement with experiment, binding affinity of monovalent ions to DNA does not depend on ion type in every solvent model. However, behavior of deeply bound ions, including ions bound to specific sites, depends strongly on the solvent model. In particular, the number of potassium ions in the minor groove of AT-tracts differs at least 3-fold between the solvent models tested. The number of sodium ions associated with the DNA agrees quantitatively with the experiment for the OPC water model, followed closely by TIP3P+J/C; the largest deviation from the experiment, ∼10%, is seen for SPC/E+J/C. On the other hand, SPC/E+J/C model is most consistent (67%) with the experimental potassium binding sites, followed by OPC+J/C (60%), TIP3P+J/C (53%), and OPC+L/M HFE (27%). The use of NBFIX correction with TIP3P+J/C improves its consistency with the experiment. In summary, the choice of the solvent model matters little for simulating the diffuse atmosphere of sodium and potassium ions around DNA, but ion distributions become increasingly sensitive to the solvent model near the helical axis. We offer an explanation for these trends. There is no single gold standard solvent model, although OPC water with J/C ions or TIP3P with J/C + NBFIX may offer an imperfect compromise for practical simulations of ionic atmospheres around DNA.