RESUMEN
Carbonate esters are utilized as solvents and reagents for C1 building blocks in organic synthesis. This study reports a novel photo-on-demand in situ synthesis of carbonate esters with CHCl3 solutions containing a mixture of an aromatic or haloalkyl alcohol having relatively high acidity, and an organic base. We found that the acid-base interaction of the alcohol and base in the CHCl3 solution plays a key role in enabling the photochemical reaction. This reaction allows practical syntheses of diphenyl carbonate derivatives, haloalkyl carbonates, and polycarbonates, which are important chemicals and materials in industry.
RESUMEN
RATIONALE: Electrospray ionization (ESI) favors the multiple charging of high molecular weight polymer samples and allows their high-resolution mass analysis in the low-mass range. It also induces the detection of numerous ion series at different charge states with different adducts complicating the interpretation of the mass spectrum which should be facilitated by an appropriate data processing. METHODS: An arsenal of tools based on the Kendrick mass defect (KMD) is proposed to process congested ESI high-resolution mass spectra of poly(propylene oxide) (PPO) samples. The combination of regular, charge-dependent, and resolution-enhanced KMD plots in addition to a "remainders" plot and a new three-dimensional plot offers unrivaled capabilities of filtering for any minor series among thousands of points. The sequential data processing is conducted using Kendo, a spreadsheet developed in-house for an advanced KMD analysis. RESULTS: The charge-state distribution is easily evaluated by counting the parallel lines in a regular KMD plot. A charge-dependent resolution-enhanced KMD plot instantly reveals the variation of adducted ions at a given charge state, helping the user to choose the best analytical conditions. Ion series at different charge states from PPO oligomers carrying different end-groups are also efficiently extracted using several combinations of KMD and remainders plots and assigned using a new simulator tool. CONCLUSIONS: The innovative combination of existing and new KMD-related plots, selection tools, and simulator all combined in a single spreadsheet dramatically facilitates the processing and interpretation of complex ESI mass spectral data. The presented tools may be extended to any other class of homo-, co- and terpolymers.
RESUMEN
Materials informatics is an emerging field that allows us to predict the properties of materials and has been applied in various research and development fields, such as materials science. In particular, solubility factors such as the Hansen and Hildebrand solubility parameters (HSPs and SP, respectively) and Log P are important values for understanding the physical properties of various substances. In this study, we succeeded at establishing a solubility prediction tool using a unique machine learning method called the in-phase deep neural network (ip-DNN), which starts exclusively from the analytical input data (e.g., NMR information, refractive index, and density) to predict solubility by predicting intermediate elements, such as molecular components and molecular descriptors, in the multiple-step method. For improving the level of accuracy of the prediction, intermediate regression models were employed when performing in-phase machine learning. In addition, we developed a website dedicated to the established solubility prediction method, which is freely available at "http://dmar.riken.jp/matsolca/".
RESUMEN
We investigated the fluorescence properties of dye aggregates formed in a poly(vinylalcohol) (PVA) matrix by phase separation. Trimethyl-(2-oxo-2-pyrene-1-yl-ethyl)-ammonium bromide (PyAm) was used as a fluorescent dye molecule. The size of PyAm aggregates in the PVA thin films were increased with increasing dye concentration, which was confirmed by atomic force microscope (AFM) measurements. The fluorescence spectra of PyAm in the PVA film at a lower concentration of 0.001 mol% only showed the monomer emission. The fluorescence peak shifted to the red with increasing dye concentration, which was assigned to a dimer or excimer-like emission. Changes in the fluorescence spectra relate to the formation of aggregates in the films. The fluorescence anisotropy decay time constant increases with increasing PyAm concentration up to the order of 100 ps. It is suggested that the exciton efficiently diffuses within the aggregates, and then was trapped at the dimer sites. We also demonstrated the application for gas sensing of nitroaromatics: 2,4-dinitrotoulene (DNT) based on the fluorescence quenching by the photoinduced electron transfer. The quenching efficiency of PyAm fluorescence reached about 43% under concentration of 2.0 mol%. The fluorescence intensity efficiently quenched at the dimer or excimer-like band. These results indicated that the efficient fluorescence quenching increases the reaction probability between PyAm and DNT by the exciton diffusion in the aggregates, called "amplified quenching". The nano-sized aggregates of PyAm formed in the PVA films are responsible for high sensitivity as an artificial fluorescent chemosensor for vapors of the nitroaromatics.
RESUMEN
The excitation energy transfer from meso-tetrakis(N-methylpyridinium-4-yl)porphyrin (TMPyP) to 3,3'-diethyl-2,2'-thiatricarbocyanine iodide (DTTCI) along the deoxyribonucleic acid (DNA) double strand was investigated by the steady-state absorption and fluorescence measurements and time-resolved fluorescence measurements. The steady-state fluorescence spectra showed that the near-infrared fluorescence of DTTCI was strongly enhanced up to 86 times due to the energy transfer from the excited TMPyP molecule in DNA buffer solution. Furthermore, we elucidated the mechanism of fluorescence quenching and enhancement by the direct observation of energy transfer using the time-resolved measurements. The fluorescence quenching of TMPyP chiefly consists of a static component due to the formation of complex and dynamic components due to the excitation energy transfer. In a heterogeneous one-dimensional system such as a DNA chain, it was proved that the energy transfer process only carries out within the critical distance based on the Förster theory and within a threshold value estimated from the modified Stern-Volmer equation. The present results showed that DNA chain is one of the most powerful tools for nanoassemblies and will give a novel concepts of material design.