Neurodegenerative diseases represent some of the greatest challenges for both basic science and clinical medicine. Due to their prevalence and the lack of known biochemical-based treatments, these complex pathologies result in an increasing societal cost. Increasing genetic and neuropathological evidence indicates that lysosomal impairment may be a common factor linking these diseases, demanding the development of therapeutic strategies aimed at restoring the lysosomal function. Here, we propose the design and synthesis of a nucleolipid conjugate as a nonviral chemical nanovector to specifically target neuronal cells and intracellular organelles. Herein, thymidine, appropriately substituted to increase its lipophilicity, was used as a model nucleoside and a fluorophore moiety, covalently bound to the nucleoside, allowed the monitoring of nucleolipid internalization in vitro. To improve nucleolipid protection and cellular uptake, these conjugates were formulated in nanoemulsions. In vitro biological assays demonstrated cell uptake- and internalization-associated colocalization with lysosomal markers. Overall, this nucleolipid-nanoemulsion-based formulation represents a promising drug-delivery tool to target the central nervous system, able to deliver drugs to restore the impaired lysosomal function. Copyright © 2020 American Chemical Society.Functionalized mesoporous silicas are an emerging kind of adsorbents for the removal of volatile organic compounds (VOCs). Breaking the limitations of traditional mesoporous silica, in this study, porous silica nanocapsules (PSNs) functionalized with phenyl and n-octyl groups (named as p-PSN and n-PSN, respectively) were developed for the first time. Under dry conditions, the PSNs exhibited highest dynamic adsorption capacity and desorption efficiency among the ever-reported typical adsorbents (i.e., SBA-15, KIT-6, silicalite-1, and activated carbon). Under wet conditions, the functionalized PSNs made up the defects of pure PSNs, displaying excellent hydrophobicity. The Q WET for n-PSN and p-PSN increased by 44 and 76%, respectively, as compared with that of pure PSNs in 50% relative humidity. The Henry constant of static adsorption demonstrated that p-PSN had a better capture ability for toluene, which was owing to the π-interaction between the phenyl groups and the toluene molecules. In addition, p-PSN showed considerable stability after six consecutive dynamic adsorption-desorption cycles in 50% relative humidity. Copyright © 2020 American Chemical Society.Using first-principles calculation and Boltzmann electron/phonon transport theory, we present an accurate theoretical prediction of thermoelectric properties of the α-Ag2S crystal, a ductile inorganic semiconductor reported experimentally [Nat. Mater. 2018, 17, 421]. The semiconductor α-Ag2S has ultralow thermal conductivity associated with high anisotropy, which can be attributed to the complex crystalline structure and weak bonding. The optimal values of the Seebeck coefficient are 0.27 × 10-3 V/K for n-type and 0.21 × 10-3 V/K for p-type α-Ag2S, respectively, which are comparable to those of many promising thermoelectric materials. As a consequence, a maximum ZT value of 0.97/1.12 can be realized for p-type/n-type α-Ag2S at room temperature. More interestingly, the value of ZT can be further enhanced to 1.65 at room temperature by applying 5% compressive strain. Moreover, we find that the electronic thermal conductivity is a major factor limiting the ZT, which is several times the lattice thermal conductivity for n-type α-Ag2S. Our work demonstrates the great advantage of the α-Ag2S crystal as a ductile thermoelectric material and sparks new routes to improve its figure of merit. Copyright © 2020 American Chemical Society.In this work, numerical simulation is carried out in a three-dimensional full-loop pilot-scale circulating fluidized bed to explore the shape effect of the riser cross section on the typical flow characteristics of the bed via the multiphase particle-in-cell (MP-PIC) method. The gas and solid phases are modeled with the large eddy simulation and Newton's law of motion in the Eulerian and Lagrangian frameworks, respectively. The proposed model has been well validated with experimental data, followed by evaluating the typical core-annulus structure and the nonuniformity of the solid phase distributed along the radial and axial directions of the riser. Then, the particle-scale information of the solid phase distributed in different parts of the system is explored. The results demonstrate that (i) the square riser gives rise to a higher solid inventory in the standpipe owing to the stronger circulation intensity; (ii) the thickness of the solid back-mixing layer reduces along the riser height; the solid back-mixing tends to concentrate in the four corners, while it is not obvious near the sidewalls of the square riser; and (iii) nonuniform distribution of the particle-scale information of the solid phase (e.g., mass, flux, drag force, and slip velocity) can be observed. The square riser gives rise to comparatively more uniform axial mass distribution, a larger rising solid flux, larger horizontal transportation velocity between the core and annulus regions, and a larger horizontal dispersion coefficient in the riser, as compared with the corresponding ones in the circular riser. Copyright © 2020 American Chemical Society.Peptides are used as reagents both for basic research and diagnostic purposes.  https://www.selleckchem.com/products/pds-0330.html  Therefore, there is a need for novel methods for the design of peptide molecules with a particular specific physiochemical profile. The properties of the peptides are governed by the nature of amino acids constituting the peptide. There is a lack of a web server or tools which could predict all the possible combinations of the peptides generated because of the combinations of amino acids based on the physiochemical properties. We have developed a peptide combination generator (PepCoGen), a web server for generating all the possible combinations of peptides by varying the amino acids having similar physiochemical properties at a particular position. It also predicts other properties of the peptides including molecular weight, charge, solubility, hydrophobic plot, and isoelectric point, and random three-dimensional models for each generated combination. Copyright © 2020 American Chemical Society.