Heterobimetallic Gold/Ruthenium Complexes Synthesized via Post‐functionalization and Applied in Dual Photoredox Gold Catalysis

The synthesis of heterobimetallic AuI/RuII complexes of the general formula syn- and anti-[{AuCl}(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$ is reported. The ditopic bridging ligand L1∩L2 refers to a P,N hybrid ligand composed of phosphine and bipyridine substructures, which was obtained via a post-functionalization strategy based on Diels-Alder reaction between a phosphole and a maleimide moiety. It was found that the stereochemistry at the phosphorus atom of the resulting 7-phosphanorbornene backbone can be controlled by executing the metal coordination and the cycloaddition reaction in a different order. All precursors, as well as the mono- and multimetallic complexes, were isolated and fully characterized by various spectroscopic methods such as NMR, IR, and UV-vis spectroscopy as well as cyclic voltammetry. Photophysical measurements show efficient phosphorescence for the investigated monometallic complex anti-[(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$ and the bimetallic analogue syn-[{AuCl}(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$, thus indicating a small influence of the {AuCl} fragment on the photoluminescence properties. The heterobimetallic Au$^{I}$/Ru$^{II}$ complexes syn- and anti-[{AuCl}(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$ are both active catalysts in the P-arylation of aryldiazonium salts promoted by visible light with H-phosphonate affording arylphosphonates in yields of up to 91 %. Both dinuclear complexes outperform their monometallic counterparts

Dependence of exciton transition energy of single-walled carbon nanotubes on surrounding dielectric materials

We theoretically investigate the dependence of exciton transition energies on dielectric constant of surrounding materials. We make a simple model for the relation between dielectric constant of environment and a static dielectric constant describing the effects of electrons in core states, $\sigma$ bonds and surrounding materials. Although the model is very simple, calculated results well reproduce experimental transition energy dependence on dielectric constant of various surrounding materials.Comment: 5pages, 4 figure

Intersubband decay of 1-D exciton resonances in carbon nanotubes

We have studied intersubband decay of E22 excitons in semiconducting carbon nanotubes experimentally and theoretically. Photoluminescence excitation line widths of semiconducting nanotubes with chiral indicess (n, m) can be mapped onto a connectivity grid with curves of constant (n-m) and (2n+m). Moreover, the global behavior of E22 linewidths is best characterized by a strong increase with energy irrespective of their (n-m) mod(3)= \pm 1 family affiliation. Solution of the Bethe-Salpeter equations shows that the E22 linewidths are dominated by phonon assisted coupling to higher momentum states of the E11 and E12 exciton bands. The calculations also suggest that the branching ratio for decay into exciton bands vs free carrier bands, respectively is about 10:1.Comment: 4 pages, 4 figure

Vibrational spectra of C60C8H8 and C70C8H8 in the rotor-stator and polymer phases

C60-C8H8 and C70-C8H8 are prototypes of rotor-stator cocrystals. We present infrared and Raman spectra of these materials and show how the rotor-stator nature is reflected in their vibrational properties. We measured the vibrational spectra of the polymer phases poly(C60C8H8) and poly(C70C8H8) resulting from a solid state reaction occurring on heating. Based on the spectra we propose a connection pattern for the fullerene in poly(C60C8H8), where the symmetry of the C60 is D2h. On illuminating the C60-C8H8 cocrystal with green or blue light a photochemical reaction was observed leading to a similar product to that of the thermal polymerization.Comment: 26 pages, 8 figures, to appear in Journal of Physical Chemistry B 2nd version: minor changes in wording, accepted version by journa

Opening "Olive branch" as a method of settlement of the Kurdish question in Syria

The work is devoted to the analysis of the influence of the operation of the Turkish government "Olive branch" against Kurdish political formations on the relations of the latter with the official government of the Syrian Arab Republic.Работа посвящена анализу влияния операции турецкого правительства «Оливковая ветвь» против курдских политических формирований на взаимоотношения последних с официальным правительством Сирийской Арабской республике

Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm

These days, the ability to predict the result of the development of the system is the guarantee of the successful functioning of the system. Improving the quality and volume of information, complicating its presentation, the need to detect hidden connections makes it ineffective, and most often impossible, to use classical statistical forecasting methods. Among the various forecasting methods, methods based on the use of artificial neural networks occupy a special place. The main objective of our work is to create a neural network that predicts the risk of depression in a person using data obtained using a motor control performance testing system. The stop-signal paradigm (SSP) is an experimental technique to assess a person’s ability to activate deliberate movements or inhibit movements that have become inadequate to external conditions. In modern medicine, the SSP is most commonly used to diagnose movement disorders such as Parkinson’s disease or the effects of stroke. We hypothesized that SSP could serve as a basis for detecting the risk of affective diseases, including depression. The neural network we are developing is supposed to combine such behavioral indicators as: the amount of missed responses, amount of correct responses, average time, the amount of correct inhibition of movements after stopsignal onset. Such a combination of indicators will provide increased accuracy in predicting the presence of depression in a person. The artificial neural network implemented in the work allows diagnosing the risk of depression on the basis of the data obtained in the stop-signal task. An architecture was developed and a system was implemented for testing motor control indicators in humans, then it was tested in real experiments. A comparison of neural network technologies and methods of mathematical statistics was carried out. A neural network was implemented to diagnose the risk of depression using stop-signal paradigm data. The efficiency of the neural network (in terms of accuracy) was demonstrated on data with an expert assessment for the presence of depression and data from the motor control testing system