Multistep energy and electron transfer processes in novel rotaxane donor–acceptor hybrids generating microsecond-lived charge separated states

A new set of [Cu(phen)₂]⁺ based rotaxanes, featuring [60]-fullerene as an electron acceptor and a variety of electron donating moieties, namely zinc porphyrin (ZnP), zinc phthalocyanine (ZnPc) and ferrocene (Fc), has been synthesized and fully characterized with respect to electrochemical and photophysical properties. The assembly of the rotaxanes has been achieved using a slight variation of our previously reported synthetic strategy that combines the Cu(i)-catalyzed azide–alkyne cycloaddition reaction (the “click” or CuAAC reaction) with Sauvage''s metal-template protocol. To underline our results, complementary model rotaxanes and catenanes have been prepared using the same strategy and their electrochemistry and photo-induced processes have been investigated. Insights into excited state interactions have been afforded from steady state and time resolved emission spectroscopy as well as transient absorption spectroscopy. It has been found that photo-excitation of the present rotaxanes triggers a cascade of multi-step energy and electron transfer events that ultimately leads to remarkably long-lived charge separated states featuring one-electron reduced C₆₀ radical anion (C₆₀˙^–) and either one-electron oxidized porphyrin (ZnP˙⁺) or one-electron oxidized ferrocene (Fc˙⁺) with lifetimes up to 61 microseconds. In addition, shorter-lived charge separated states involving one-electron oxidized copper complexes ([Cu(phen)₂]²⁺ (τ < 100 ns)), one-electron oxidized zinc phthalocyanine (ZnPc˙⁺; τ = 380–560 ns), or ZnP˙⁺ (τ = 2.3–8.4 μs), and C₆₀˙^– have been identified as intermediates during the sequence. Detailed energy diagrams illustrate the sequence and rate constants of the photophysical events occurring with the mechanically-linked chromophores. This work pioneers the exploration of mechanically-linked systems as platforms to position three distinct chromophores, which are able to absorb light over a very wide range of the visible region, triggering a cascade of short-range energy and electron transfer processes to afford long-lived charge separated states.     

Vibration Spectroscopy Stability Investigation of 12-Tungstosilicic Acid Solution

Heteropoly acids (HPA) attract the attention of large variety of scientists, due to HPA’s extraordinary interesting properties and possible application fields. 12-tungstosilicic acid (WSiA), the Keggin type HPA, has some promising characteristic to be used in catalytic processes, but with not well-defined stability. Raman spectroscopy was used for in situ analysis of WSiA hydrolysis in detail in a wide pH range of 1–12. Raman spectroscopy is able to give an almost immediate response/spectrum as a representation of the exact profile/composition of the solution. This method and FTIR spectroscopy, as a complementary technique, enabled recording of the solid and liquid phases of the same sample under different conditions. Our results confirm that the decomposition pathways of WSiA in solution proceed via the formation of the lacunary monovacant anion at pH > 6.4. This anion is a major constituent in pH range up to 9.5. With further increases in pH this species convert to the trivacant lacunary anion. The total decomposition of the Keggin anion to silicate and tungstate occurs at pH > 11.0. The results of the performed study contribute to understand the behavior of WSiA in the water–methanol solution, as the model system of aqueous-organic system. It is concluded that addition of methanol in aqueous solution of WSiA leads to expansion of the pH region where Keggin anion is stable up to 8.1 and above this pH value, precipitation occurs. The obtained data clarify the stability range of WSiA in both water and water–methanol solutions, as well.     

Mechanistic investigations reveal that dibromobimane extrudes sulfur from biological sulfhydryl sources other than hydrogen sulfide

Hydrogen sulfide (H₂S) has emerged as an important biological signaling molecule in the last decade. During the growth of this field, significant controversy has arisen centered on the physiological concentrations of H₂S. Recently, a monobromobimane (mBB) method has been developed for the quantification of different biologically-relevant sulfide pools. Based on the prevalence of the mBB method for sulfide quantification, we expand on this method to report the use of dibromobimane (dBB) for sulfide quantification. Reaction of H₂S with dBB results in formation of highly-fluorescent bimane thioether (BTE), which is readily quantifiable by HPLC. Additionally, the reaction of sulfide with dBB to form BTE is significantly faster than the reaction of sulfide with mBB to form sulfide dibimane. Using the dBB method, BTE levels as low as 0.6 pM can be detected. Upon use of the dBB method in wild-type and CSE^–/– mice, however, dBB reports significantly higher sulfide levels than those measured using mBB. Further investigation revealed that dBB is able to extract sulfur from other sulfhydryl sources including thiols. Based on mechanistic studies, we demonstrate that dBB extracts sulfur from thiols with α- or β-hydrogens, thus leading to higher BTE formation than from sulfide alone. Taken together, the dBB method is a highly sensitive method for H₂S but is not compatible for use in studies in which other thiols are present.     

Wavelength selection framework for classifying food and pharmaceutical samples into multiple classes

Near infrared (NIR) spectroscopy is an efficient, low‐cost analytical technique widely applied to identify the origin of food and pharmaceutical products. NIR spectra‐based classification strategies typically use thousands of equally spaced wavelengths as input information, some of which may not carry relevant information for product classification. When that is the case, the performance of predictive and exploratory multivariate techniques may be undermined by such noisy information. In this paper, we propose an iterative framework for selecting subsets of NIR wavelengths aimed at classifying samples into categories. For that matter, we integrate Principal Components Analysis (PCA) and three classification techniques: k‐Nearest Neighbor (KNN), Probabilistic Neural Network (PNN) and Linear Discriminant Analysis (LDA). PCA is first applied to NIR data, and a wavelength importance index is derived based on the PCA loadings. Samples are then categorized using the wavelength with the highest index and the classification accuracy is calculated; next, the wavelength with the second highest index is inserted into the dataset and a new classification is performed. This forward‐based iterative procedure is carried out until all original wavelengths are inserted into the dataset used for classification. The subset of wavelengths leading to the maximum accuracy is chosen as the recommended subset. Our propositions performed remarkably well when applied to four datasets related to food and pharmaceutical products. Copyright © 2016 John Wiley & Sons, Ltd.     

Physical Chemistry of the Interaction of Cellulose with Lignin during Wood Surface Treatment with a Phosphate Flame Retardant

Russian Journal of General Chemistry - A phosphate flame-retardant hardener (PFH) produced on the basis of industrial orthophosphoric acid and acetic anhydride was proposed for reducing the...     

Convenient Microwave-Assisted Chlorosulfonic Acid-Catalyzed Synthesis of Some Quinazolinones from 2-Phenylindole

Russian Journal of Organic Chemistry - A new convenient method has been developed for the synthesis of quinazolinones from 2-phenyl-1H-indole and substituted amines under catalysis by...