Targeted ferromagnetic coupling in a trinuclear copperII complex: analysis of the St = 3/2 spin ground state

The trinuclear Cu(II) complex [(talen)Cu(II)(3)] (1) using the new triplesalen ligand H(6)talen has been synthesized and structurally characterized. The three Cu(II) ions are bridged in a m-phenylene linkage by the phloroglucinol backbone of the ligand. This m-phenylene bridging mode results in ferromagnetic couplings with an S(t) = (3)/(2) spin ground state, which has been analyzed by means of EPR spectroscopy and DFT calculations. The EPR spectrum exhibits an unprecedented pattern of 10 hyperfine lines due to the coupling of three Cu(II) ions (I = (3)/(2)). Resonances around g = 4 in both perpendicular and parallel mode EPR spectra demonstrate a zero-field splitting of D approximately 74 x 10(-4) cm(-1) arising from anisotropic/antisymmetric exchange interactions. The DFT calculations show an alteration in the sign of the spin densities of the central benzene ring corroborating the spin-polarization mechanism as origin for the ferromagnetic coupling.     

Comparison of Force Fields on the Basis of Various Model Approaches—How To Design the Best Model for the [CnMIM][NTf2] Family of Ionic Liquids

In this contribution, we present two new united‐atom force fields (UA‐FFs) for 1‐alkyl‐3‐methylimidazolium bis(trifluoromethylsulfonyl)imide [C_nMIM][NTf₂] (n=1, 2, 4, 6, 8) ionic liquids (ILs). One is parametrized manually, and the other is developed with the gradient‐based optimization workflow (GROW). By doing so, we wanted to perform a hard test to determine how researchers could benefit from semiautomated optimization procedures. As with our already published all‐atom force field (AA‐FF) for [C_nMIM][NTf₂] (T. Köddermann, D. Paschek, R. Ludwig, ChemPhysChem­ 2007, 8, 2464 ), the new force fields were derived to fit experimental densities, self‐diffusion coefficients, and NMR rotational correlation times for the IL cation and for water molecules dissolved in [C₂MIM][NTf₂]. In the manual force field, the alkyl chains of the cation and the CF₃ groups of the anion were treated as united atoms. In the GROW force field, only the alkyl chains of the cation were united. All other parts of the structures of the ions remained unchanged to prevent any loss of physical information. Structural, dynamic, and thermodynamic properties such as viscosity, cation rotational correlation times, and heats of vaporization calculated with the new force fields were compared with values simulated with the previous AA‐FF and the experimental data. All simulated properties were in excellent agreement with the experimental values. Altogether, the UA‐FFs are slightly superior for speed‐up reasons. The UA‐FF speeds up the simulation by about 100 % and reduces the demanded disk space by about 78 %. More importantly, real time and efforts to generate force fields could be significantly reduced by utilizing GROW. The real time for the GROW parametrization in this work was 2 months. Manual parametrization, in contrast, may take up to 12 months, and this is, therefore, a significant increase in speed, though it is difficult to estimate the duration of manual parametrization.     

Tuning Ruthenium Carbene Complexes for Selective P−H Activation through Metal-Ligand Cooperation

The use of iminophosphoryl-tethered ruthenium carbene complexes to activate secondary phosphine P−H bonds is reported. Complexes of type [(p-cymene)-RuC(SO₂Ph)(PPh₂NR)] (with R = SiMe₃ or 4-C₆H₄−NO₂) were found to exhibit different reactivities depending on the electronics of the applied phosphine and the substituent at the iminophosphoryl moiety. Hence, the electron-rich silyl-substituted complex undergoes cyclometallation or shift of the imine moiety after cooperative activation of the P−H bond across the M=C linkage, depending on the electronics of the applied phosphine. Deuteration experiments and computational studies proved that cyclometallation is initiated by the activation process at the M=C bond and triggered by the high electron density at the metal in the phosphido intermediates. Consistently, replacement of the trimethylsilyl (TMS) group by the electron-withdrawing 4-nitrophenyl substituent allowed the selective cooperative P−H activation to form stable activation products.     

Reactions with Oleum under Harsh Conditions: Characterization of the Unique [M(S2O7)3]2− Ions (M=Si,Ge, Sn) in A2[M(S2O7)3] (A=NH4, Ag)

The reactions of group 14 tetrachlorides MCl₄ (M=Si, Ge, Sn) with oleum (65 % SO₃) at elevated temperatures lead to the unique complex ions [M(S₂O₇)₃]^2?, which show the central M atoms in coordination with three chelating S₂O₇^2? groups. The mean distances M? O within the anions increase from 175.6(2)–177.5(2) pm (M=Si) to 186.4(4)–187.7(4) pm (M=Ge) to 201.9(2)–203.5(2) pm (M=Sn). These distances are reproduced well by DFT calculations. The same calculations show an increasing positive charge for the central M atom in the row Si, Ge, Sn, which can be interpreted as the decreasing covalency of the M? O bonds. For the silicon compound (NH₄)₂[Si(S₂O₇)₃], ²⁹Si solid‐state NMR measurements have been performed, with the results showing a signal at ?215.5 ppm for (NH₄)₂[Si(S₂O₇)₃], which is in very good agreement with theoretical estimations. In addition, the vibrational modes within the [MO₆] skeleton have been monitored by Raman spectroscopy for selected examples, and are well reproduced by theory. The charge balance for the [M(S₂O₇)₃]^2? ions is achieved by monovalent A⁺ counter ions (A=NH₄, Ag), which are implemented in the syntheses in the form of their sulfates. The sizes of the A⁺ ions, that is, their coordination requirements, cause the crystallographic differences in the crystal structures, although the complex [M(S₂O₇)₃]^2? ions remain essentially unaffected with the different A⁺ ions. Furthermore, the nature of the A⁺ ions influences the thermal behavior of the compounds, which has been monitored for selected examples by thermogravimetric differential thermal analysis (DTA/TG) and XRD measurements.     

Could we use a million cores to solve an integer program?

Given the steady increase in cores per CPU, it is only a matter of time before supercomputers will have a million or more cores. In this article, we investigate the opportunities and challenges that will arise when trying to utilize this vast computing power to solve a single integer linear optimization problem. We also raise the question of whether best practices in sequential solution of ILPs will be effective in massively parallel environments.