Unexpected solvent effects on the UV/Vis absorption spectra of o-cresol in toluene and benzene: in contrast with non-aromatic solvents

Benzophosphol-3-yl Triflates as Precursors of 1,3-Diarylbenzophosphole Oxides

A simple method for the synthesis of 3-arylbenzophosphole oxides under Suzuki-Miyaura coupling conditions has been presented. It employs benzophosphol-3-yl triflate starting materials which, prior to our work, had not been used for the synthesis of 3-arylbenzophosphole oxides. The reactions proceed over 24 h and provide a library of 3-arylbenzophosphole oxides. The synthetic access to the benzophosphol-3-yl triflates has been improved. The preliminary photophysical properties of some 3-arylbenzophosphole oxides have been investigated by absorption and emission measurements. The theoretical calculations were performed to establish structure-property relationships.

Treating Polarization Effects in Charged and Polar Bio-Molecules Through Variable Electrostatic Parameters

Polarization plays important roles in charged and hydrogen bonding containing systems. Much effort ranging from the construction of physics-based models to quantum mechanism (QM)-based and machine learning (ML)-assisted models have been devoted to incorporating the polarization effect into the conventional force fields at different levels, such as atomic and coarse grained (CG). The application of polarizable force fields or polarization models was limited by two aspects, namely, computational cost and transferability. Different from physics-based models, no predetermining parameters were required in the QM-based approaches. Taking advantage of both the accuracy of QM calculations and efficiency of molecular mechanism (MM) and ML, polarization effects could be treated more efficiently while maintaining the QM accuracy. The computational cost could be reduced with variable electrostatic parameters, such as the charge, dipole, and electronic dielectric constant with the help of linear scaling fragmentation-based QM calculations and ML models. Polarization and entropy effects on the prediction of partition coefficient of druglike molecules are demonstrated by using both explicit or implicit all-atom molecular dynamics simulations and machine learning-assisted models. Directions and challenges for future development are also envisioned.

UV-Visible Absorption Spectra of Solvated Molecules by Quantum Chemical Machine Learning

Predicting UV-visible absorption spectra is essential to understand photochemical processes and design energy materials. Quantum chemical methods can deliver accurate calculations of UV-visible absorption spectra, but they are computationally expensive, especially for large systems or when one computes line shapes from thermal averages. Here, we present an approach to predict UV-visible absorption spectra of solvated aromatic molecules by quantum chemistry (QC) and machine learning (ML). We show that a ML model, trained on the high-level QC calculation of the excitation energy of a set of aromatic molecules, can accurately predict the line shape of the lowest-energy UV-visible absorption band of several related molecules with less than 0.1 eV deviation with respect to reference experimental spectra. Applying linear decomposition analysis on the excitation energies, we unveil that our ML models probe vertical excitations of these aromatic molecules primarily by learning the atomic environment of their phenyl rings, which align with the physical origin of the π →π* electronic transition. Our study provides an effective workflow that combines ML with quantum chemical methods to accelerate the calculations of UV-visible absorption spectra for various molecular systems.

Solution and Solid-State Photophysical Properties of Positional Isomeric Acrylonitrile Derivatives with Core Pyridine and Phenyl Moieties: Experimental and DFT Studies

The compounds I (Z)-2-(phenyl)-3-(2,4,5-trimethoxyphenyl)acrylonitrile with one side (2,4,5-MeO-), one symmetrical (2Z,2'Z)-2,2'-(1,4-phenylene)bis(3-(2,4,5-trimethoxyphenyl)acrylonitrile), II (both sides with (2,4,5-MeO-), and three positional isomers with pyridine (Z)-2-(pyridin-2- 3, or 4-yl)-3-(2,4,5-trimethoxyphenyl)acrylonitrile, III-V were synthetized and characterized by UV-Vis, fluorescence, IR, H1-NMR, and EI mass spectrometry as well as single crystal X-ray diffraction (SCXRD). The optical properties were strongly influenced by the solvent (hyperchromic and hypochromic shift), which were compared with the solid state. According to the solvatochromism theory, the excited-state (μe) and ground-state (μg) dipole moments were calculated based on the variation of Stokes shift with the solvent's relative permittivity, refractive index, and polarity parameters. SCXRD analyses revealed that the compounds I and II crystallized in the monoclinic system with the space group, P21/n and P21/c, respectively, and with Z = 4 and 2. III, IV, and V crystallized in space groups: orthorhombic, Pbca; triclinic, P-1; and monoclinic, P21 with Z = 1, 2, and 2, respectively. The intermolecular interactions for compounds I-V were investigated using the CCDC Mercury software and their energies were quantified using PIXEL. The density of states (DOS), molecular electrostatic potential surfaces (MEPS), and natural bond orbitals (NBO) of the compounds were determined to evaluate the photophysical properties.

Shear viscosity prediction of alcohols, hydrocarbons, halogenated, carbonyl, nitrogen-containing, and sulfur compounds using the variable force fields

Viscosity of organic liquids is an important physical property in applications of printing, pharmaceuticals, oil extracting, engineering, and chemical processes. Experimental measurement is a direct but time-consuming process. Accurately predicting the viscosity with a broad range of chemical diversity is still a great challenge. In this work, a protocol named Variable Force Field (VaFF) was implemented to efficiently vary the force field parameters, especially λ_vdW, for the van der Waals term for the shear viscosity prediction of 75 organic liquid molecules with viscosity ranging from -9 to 0 in their nature logarithm and containing diverse chemical functional groups, such as alcoholic hydroxyl, carbonyl, and halogenated groups. Feature learning was applied for the viscosity prediction, and the selected features indicated that the hydrogen bonding interactions and the number of atoms and rings play important roles in the property of viscosity. The shear viscosity prediction of alcohols is very difficult owing to the existence of relative strong intermolecular hydrogen bonding interaction as reflected by density functional theory binding energies. From radial and spatial distribution functions of methanol, we found that the van der Waals related parameters λ_vdW are more crucial to the viscosity prediction than the rotation related parameters, λ_tor. With the variable λ_vdW-based all-atom optimized potentials for liquid simulations force field, a great improvement was observed in the viscosity prediction for alcohols. The simplicity and uniformity of VaFF make it an efficient tool for the prediction of viscosity and other related properties in the rational design of materials with the specific properties.

Quantification of Colorimetric Data for Paper-Based Analytical Devices

Colorimetric measurements by image analysis, giving RGB or HSV data, have become commonplace with optical indicator-based assays and as a readout for paper-based analytical devices (PADs). Yet, most works on PADs tend to ignore the quantitative relationship between color data and concentration, which may hamper their establishment as analytical devices and make it difficult to properly understand chemical or biological reactions on the paper substrate. This Perspective Article discusses how image color data are computed into colorimetric absorbance values that correlate linearly to dye concentration and compare well to traditional spectrophotometry. Thioflavin T (ThT), Neutral Red (NR), and Orange IV are used here as model systems. Absorbance measurements in solution correlate well to image data (and Beer's law) from the color channel of relevance if the gamma correction normally used to render the picture more natural to the human eye is removed. This approach also allows one to correct for color cast and variable background color, which may otherwise limit quantitation in field measurements. Reflectance measurements on paper color spots are equally found to correlate quantitatively between spectroscopy and imaging devices. In this way, deviations from Beer's law are identified that are explained with dye interactions on the paper substrate.

Acid selective pro-dye for cellular compartments

A novel pro-dye approach for the acid-selective staining of the subcellular compartments for better permeability and selectivity was applied. The designed sensor has suitable physicochemical properties such as a large Stokes shift and a long-lived intracellular fluorescence. The Schiff base fragment was used for the acid-sensitive release of a fluorophore without affecting the overall stability of the biological systems. Due to the presence of an imine bond in its structure and its unique fluorescent properties, it can be presented as a “pro-dye” for acidic structures such as lysosomes. As a result of an imine bond cleavage, a new fluorescent compound is released, whose substantially shifted excitation and emission wavelengths enable a more selective and effective imaging of lysosomes and endosomes. The presented report provides the chemical, physicochemical and optical profiles as well as biological assays and theoretical calculations.