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Predicting adsorption energies of small molecules (e.g., OH, OOH, CO) on electrocatalysts involved in electrochemical reactions aids in accelerating the design and screening of electrocatalysts. Avoiding computationally expensive electronic structure calculations increases the speed of such predictions. Geometric and electronic descriptors have been reported to characterize the environment around surface active sites and predict adsorption energies. However, these descriptors cannot be used to predict adsorption energies of small molecules on various substrates, e.g., metal-oxide and nonmetal electrocatalysts. We compare the performance of these descriptors in predicting adsorption energies of small molecules on various electrocatalysts with adsorption energies calculated from density functional theory. We show that two recently developed machine learning algorithms, Crystal Graph Convolutional Neural Network (CGCNN) and Atomistic Line Graph Neural Network (ALIGNN), outperform the reported descriptors based on geometric (coordination number of the active site and its nearest neighbors) and electronic (the bond-energy-integrated orbitalwise coordination number, the electronegativity, and the number of valence electrons of the active site) properties in predicting the adsorption energies. Our results suggest that ALIGNN is almost always more accurate than CGCNN in adsorption energy predictions. The improvement ranges from 0.02 to 1.0 eV in the mean absolute errors (MAEs). We also compare the performance of CGCNN and ALIGNN algorithms in predicting the overpotentials of the oxygen evolution reaction occurring on various electrocatalysts with MAEs of 0.06 and 0.05 V, respectively.

Molecular dynamics simulations were performed to study the hydration and ion association properties of a library of zwitterionic molecules with varying charged moieties and spacer chemistries in pure water and with Na + and Cl - ions. The structure and dynamics of associations were calculated using the radial distribution and residence time correlation function. Resulting association properties are used as target variables for a machine learning model, with cheminformatic descriptors of the molecule subunits used as descriptors. Prediction of hydration properties revealed that steric and hydrogen bonding descriptors were of greatest importance and there was influence from the cationic moiety on the anionic moiety hydration properties. Ion association properties prediction performed poorly, which is attributed to the role of hydration layers in ion association dynamics. This study is the first to quantitatively describe the influence of subunit chemistry on hydration and ion association properties of zwitterions. These quantitative descriptions supplement prior studies of zwitterion association and previously described design principles.

Shape control is of key importance in utilizing the structure-property relationship of nanocrystals. The high surface-to-volume ratio of nanocrystals induces dynamic surface reactions on exposed facets of nanocrystals, such as adsorption, desorption, and diffusion of surface atoms, all of which are important in overall shape transformation. However, it is difficult to track shape transformation of nanocrystals and understand the underlying mechanism at the level of distinguishing events on individual facets. Herein, we investigate changes of individual surface-exposed facets during diverse shape transformations of Au nanocrystals using liquid phase TEM in various chemical potentials and kinetic Monte Carlo simulations. The results reveal that the diffusion of surface atoms on nanocrystals is the governing factor in determining the final structure in shape transformation, causing the fast transformation of unstable facets to truncated morphology with minimized surface energy. The role of surface diffusion introduced here can be further applied to understanding the formation mechanism of variously shaped nanocrystals.

Colloidal nanoparticles are synthesized in a complex reaction mixture that has an inhomogeneous chemical environment induced by local phase separation of the medium. Nanoparticle syntheses based on micelles, emulsions, flow of different fluids, injection of ionic precursors in organic solvents, and mixing the metal organic phase of precursors with an aqueous phase of reducing agents are well established. However, the formation mechanism of nanoparticles in the phase-separated medium is not well understood because of the complexity originating from the presence of phase boundaries as well as nonuniform chemical species, concentrations, and viscosity in different phases. Herein, we investigate the formation mechanism and diffusion of silver nanoparticles in a phase-separated medium by using liquid phase transmission electron microscopy and many-body dissipative particle dynamics simulations. A quantitative analysis of the individual growth trajectories reveals that a large portion of silver nanoparticles nucleate and grow rapidly at the phase boundaries, where metal ion precursors and reducing agents from the two separated phases react to form monomers. The results suggest that the motion of the silver nanoparticles at the interfaces is highly affected by the interaction with polymers and exhibits superdiffusive dynamics because of the polymer relaxation.

In this study, a novel mesoporous nanocomposite was fabricated in several steps. In this regard, SBA-15 was prepared by the hydrothermal method, next it was magnetized by in-situ preparation of Fe 3 O 4 MNPs. After that, the as-prepared SBA-15/Fe 3 O 4 functionalized with 3-minopropyltriethoxysilane (APTES) via post-synthesis approach. Then, the guanidinylated SBA-15/Fe 3 O 4 was obtained by nucleophilic addition of APTES@SBA-15/Fe 3 O 4 to cyanimide. The prepared nanocomposite exhibited excellent catalytic activity in the synthesis of dihydropyrano[2,3-c]pyrazole derivatives which can be related to its physicochemical features such as strong basic sites (presented in guanidine group), Lewis acid site (presented in Fe 3 O 4 ), high porous structure, and high surface area. The characterization of the prepared mesoporous nanocomposite was well accomplished by different techniques such as FT-IR, EDX, FESEM, TEM, VSM, TGA, XRD and BET. Furthermore, the magnetic catalyst was reused at least six consequent runs without considerable reduction in its catalytic activity., (© 2021. The Author(s).)

We present a molecular view using many-body dissipative particle dynamics simulations to unravel the pinning phenomenon of a liquid film receding over a solid substrate with a nanocavity. We find that the pinning force and distortion of the pinned contact line vary across different nanocavity shapes. We show that the mechanism of a caterpillar motion, which has previously been proposed for advancing precursor films, persists in a partially pinned receding contact line. Our results also demonstrate a localized clamping effect, which is originated from the variation of the dynamic contact angle along the pinned contact line. The simulation results suggest that the clamping effect can be controlled by the geometry of the nanocavity and hydrophilicity of the underlying substrate.

Cell replacement therapy using mesenchymal (MSC) and other stem cells has been evaluated for diabetic retinopathy and glaucoma. This approach has significant limitations, including few cells integrated, aberrant growth, and surgical complications. Mesenchymal Stem Cell Exosomes/Extracellular Vesicles (MSC EVs), which include exosomes and microvesicles, are an emerging alternative, promoting immunomodulation, repair, and regeneration by mediating MSC's paracrine effects. For the clinical translation of EV therapy, it is important to determine the cellular destination and time course of EV uptake in the retina following administration. Here, we tested the cellular fate of EVs using in vivo rat retinas, ex vivo retinal explant, and primary retinal cells. Intravitreally administered fluorescent EVs were rapidly cleared from the vitreous. Retinal ganglion cells (RGCs) had maximal EV fluorescence at 14 days post administration, and microglia at 7 days. Both in vivo and in the explant model, most EVs were no deeper than the inner nuclear layer. Retinal astrocytes, microglia, and mixed neurons in vitro endocytosed EVs in a dose-dependent manner. Thus, our results indicate that intravitreal EVs are suited for the treatment of retinal diseases affecting the inner retina. Modification of the EV surface should be considered for maintaining EVs in the vitreous for prolonged delivery.

Bioresorbable polymers, including polyesters and polypeptides, are being widely used in the medical field. However, these materials still suffer from some long-standing challenges, such as material-induced blood coagulation, foreign body response, non-adjustable degradation rate, and absence of elastic properties. In this work, we explored a new approach to address these challenges by incorporating critical anti-fouling, improved mechanical and controllable degradation properties into the existing bioresorbable polymers. We synthesized a set of zwitterionic thermoplastic polyurethanes, which consist of degradable polycaprolactone diols as soft segments and faster hydrolyzable carboxybetaine (CB) diols as chain extenders. Differential scanning calorimetry and temperature sweep rheology revealed thermal transition performance and thermoplastic behavior of the polymers. The calorimetric study observed that CB-based chain extender played a critical role in the crystallization process by affecting the structure and crystallization temperature. Cell attachment study demonstrated that the degradable zwitterionic polyurethane surfaces highly resist cell attachment even after being submerged in 100% fetal bovine serum for two weeks. The gold standard PEG-based degradable polyurethane showed the initial resistance to the cell attachment for one day and then failed after three days. This work clearly shows that the adaption of existing materials with slightly better anti-fouling properties is unlikely to solve these long-lasting challenges. Our design approach and the material platform with critical anti-fouling properties and other desired tunable properties show the potential to address these complications associated with existing bioresorbable polymers. This method can be adapted to design customized bioresorbable polymers for a wide range of applications, including implantable biomedical devices and drug delivery.