We demonstrate that the deviation in the reflectivity signal is reduced to ∼8 × 10-6 for a solution change from phosphate-buffered saline (PBS) (n = 1.335) to 1% dimethyl sulfoxide (DMSO) in PBS (n = 1.336). As a proof of concept, we applied the method to a biotin-streptavidin interaction, where biotin (MW = 244.3 Da) was dissolved at a final concentration of 1 μM in a 1% solution of DMSO in PBS and flowed over immobilized streptavidin. Clear binding results were obtained without a reference channel or any computational correction.NiCo2S4 nanoparticles (NPs) were dry coated on LiNi0.6Co0.2Mn0.2O2 (NCM622) cathode using a resonant acoustic coating technique to produce all-solid-state lithium batteries. The NiCo2S4 coating improved the electrochemical properties of the NCM622 cathode. In addition, NiCo2S4 eliminated the space-charge layer and the cathode showed an excellent affinity with the interface with a sulfide-based solid electrolyte as an inert material. X-ray diffraction patterns of NCM622 coated with NiCo2S4 showed the same peak separations and lattice parameters as those of bare NCM622. Field-emission scanning electron microscopy and electron dispersive spectroscopy mapping analyses showed that 0.3 wt% NiCo2S4-coated NCM622 had an evenly modified surface with NiCo2S4 NPs. X-ray photoelectron spectroscopy (XPS) revealed that the surface of 0.3 wt% NiCo2S4-coated NCM622 had two different S 2p peaks, a Co-S peak, and Ni and Co peaks, compared to those of bare NCM622. Electrochemical studies with electrochemical impedance spectroscopy and galvanostatic charge-discharge cycle performances showed that NiCo2S4-coated NCM622 retained a higher specific capacity over multiple cycles than bare NCM622. Especially, 0.3 wt% NiCo2S4-coated NCM622 exhibited a capacity retention of 60.6% at a current density of 15 mA/g for 20 cycles, compared to only 37.3% for bare NCM622. Finally, interfacial XPS and transmission electron microscopy-electron energy loss spectroscopy analyses confirmed the stable state of 0.3 wt% NiCo2S4-coated NCM622 with minimal side reactions.A D-A-π-A dye (PTZ-5) has been synthesized by introducing a benzothiadiazole (BTD) unit as an auxiliary acceptor in a phenothiazine-based D-π-A dye(PTZ-3) to broaden its spectral response range and improve the device performance. Photophysical properties indicate that the inclusion of BTD in the PTZ-5 effectively red-shifted the absorption spectra by reducing the E gap. However, the device measurements show that the open-circuit voltage (V oc) of PTZ-5 cell (640 mV) is obviously lower than that of the PTZ-3 cell (710 mV). This results in a poor photoelectric conversion efficiency (PCE) (4.43%) compared to that of PTZ-3 cell (5.53%). Through further comparative analysis, we found that the introduction of BTD increases the dihedral angle between the D and A unit, which can reduce the efficiency of intramolecular charge transfer (ICT), lead to a less q CT and lower molar extinction coefficient of PTZ-5. In addition, the ESI test found that the lifetime of the electrons in the PTZ-5 cell is shorter. These are the main factors for the above unexpected result of PCE. Our studies bring new insights into the development of phenothiazine-based highly efficient dye-sensitized solar cells (DSSCs).A novel Sm-metal-organic framework (MOF) sensor with the molecular formula Sm8(HDBA)6·H2O has been prepared based on a penta-carboxyl organic ligand (H5DBA = 3,5-di(2',4'-dicarboxylphenyl)benzoic acid) and samarium nitrate under solvothermal conditions. Sm-MOF is characterized by single-crystal X-ray diffraction analysis, elemental analysis, thermogravimetric analysis, and powder X-ray diffraction analysis. ARRY-382 chemical structure Structural analysis shows that the dimer metal units are alternately connected to form a one-dimensional chain, and this chain is connected by the bridging carboxyl oxygen of the ligand H5DBA to form a two-dimensional double-layer plane, which then expands into a three-dimensional microporous framework. Fluorescence detection studies show that Sm-MOF can detect Ag+ ions, MnO4 - anions, and cimetidine tablets with high sensitivity and selectivity and can also be used to electrochemically detect o-nitrophenol in water. High-sensitivity detection capability of the Sm-MOF can enrich the application of samarium complexes in multifunctional sensors.Biphasic systems have received increasing attention for acid-catalyzed dehydration of hexoses to 5-hydroxymethylfurfural (HMF) because of their high efficiency in in situ extraction and stabilization of HMF. Different organic solvents and acid catalysts were applied in these systems, but their effects on the dehydration activity and HMF yield, and the recycling of homogeneous acid catalysts remain largely unexplored. Here, we tested different solvent systems containing a wide range of organic solvents with low boiling points to study the effects of their chemical structures on fructose dehydration and provided stable H2O-dioxane and H2O-acetonitrile biphasic systems with high HMF yields of 76-79% using water-soluble sulfonic derivatives as homogeneous acid catalysts under mild conditions (383 K). By analyzing the partition coefficients of HMF and sulfonic derivatives, 94.3% of HMF and 87.1% of NH2SO3H were, respectively, restrained in the dioxane phase and aqueous phase in the H2O-dioxane biphasic system and easily divided by phase separation. The effects of the adjacent group in sulfonic derivatives and reaction temperature on fructose conversions and HMF yields suggest that in a specific biphasic system, the catalysts' acidity and reaction conditions significantly affect the fructose dehydration activity but hardly influence the optimal yield of HMF, and an almost constant amount of carbon loss was observed mainly due to the poor hydrothermal stability of fructose. Such developments offer a promising strategy to address the challenge in the separation and recycling of homogeneous acid catalysts in the practical HMF production.Predicting the fraction unbound of a drug in plasma plays a significant role in understanding its pharmacokinetic properties during in vitro studies of drug design and discovery. Owing to the gaining reliability of machine learning in biological predictive models and development of automated machine learning techniques for the ease of nonexperts of machine learning to optimize and maximize the reliability of the model, in this experiment, we built an in silico prediction model of a fraction unbound drug in human plasma using a chemical fingerprint and a freely available AutoML framework. The predictive model was trained on one of the largest data sets ever of 5471 experimental values using four different AutoML frameworks to compare their performance on this problem and to choose the most significant one. With a coefficient of determination of 0.85 on the test data set, our best prediction model showed better performance than other previously published models, giving our model significant importance in pharmacokinetic modeling.