Electrochemically Triggered Chain Reactions for the Conversion of Furan Derivatives
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We report on the assembly of gold nanoparticle (AuNPs) superlattices at the liquid/vapor interface and in the bulk of their suspensions. Interparticle distances in the assemblies are achieved on multiple length scales by varying chain lengths of surface grafted AuNPs by polyethylene glycol (PEG) with molecular weights in the range 2000–40,000 Da. Crystal structures and lattice constants in both 2D and 3D assemblies are determined by synchrotron-based surface-sensitive and small-angle X-ray scattering. Here, assuming knowledge of grafting density, we show that experimentally determined interparticle distances are adequately modeled by spherical brushes close to the θ point (Flory–Huggins parameter, x ≈ 1/2) for 2D superlattices at a liquid interface and a nonsolvent (χ = ∞) for the 3D dry superlattices.
Poly(4–4′-oxydiphenylene-pyromellitimide)-based polyimides─trade name Kapton─have wide-ranging engineering applications owing to their thermal and mechanical stability, but little is known about underlying chain-level characteristics. While theoretical models have conceptualized Kapton as inflexible polycyclic rods separated by freely rotating diphenyl ether hinge groups, the model’s core predictions remain untested and subtleties of the relaxation behavior are missed, which atomistic modeling can resolve. To these ends, we examine all-atom Kapton structures in crystalline and glassy amorphous configurations using a DFT-validated class II force field. Constructing amorphous configurations is challenging, as the fused-ring-containing backbone has slow relaxation dynamics and scaling suggestive of entanglements even in oligomers. In conclusion, we find larger backbone rearrangements of the linear polycyclic segments about ether groups that are consistent with the rod-hinge picture on the monomer scale, whereas a ring rotation analysis suggests partially flexible rod-like segments and involves multiple facile rotational relaxation modes.
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Polymers are widely implemented materials often used for safety and security in our daily lives. However, we do not have a thorough understanding of the phase transformations of these materials when exposed to extreme condition, high strain rate, events. To study polymers in these severe environments, we performed plate impact experiments that impart a one-dimensional shock wave, at high pressures and temperatures, to observe the materials response. Generally, velocimetry is the experimental diagnostic used to capture the movement of high velocity interfaces to then calculate the mechanical variables associated with shock compression. However, when a material undergoes a phase transition, such as between two crystalline phases or melting to decomposition during shock compression, velocimetry does not explicitly indicate what structural change occurred. At the Dynamic Compression Sector at the Advanced Photon Source gas gun driven compression has been paired with x-ray diffraction, providing the ability to study both the shock parameters and structural changes concurrently. We explored high density polyethylene (HDPE) both on its reactants Hugoniot (<10.12 GPa) and within its transition region (24.3 GPa) where HDPE is hypothesized to decompose from reactants to products. With x-ray diffraction we observed both polymer chain compression and crystal structure reorientation from orthorhombic to monoclinic above 6 GPa, as well as either a possible phase change or chemical decomposition at 24.3 GPa. With these experiments we were able to determine the crystalline and amorphous Hugoniot loci at pressures below the polymer transition region.
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As an important Markov chain Monte Carlo (MCMC) method, the stochastic gradient Langevin dynamics (SGLD) algorithm has achieved great success in Bayesian learning and posterior sampling. Furthermore, SGLD typically suffers from a slow convergence rate due to its large variance caused by the stochastic gradient. In order to alleviate these drawbacks, we leverage the recently developed Laplacian smoothing technique and propose a Laplacian smoothing stochastic gradient Langevin dynamics (LS-SGLD) algorithm. We prove that for sampling from both log-concave and non-log-concave densities, LS-SGLD achieves strictly smaller discretization error in 2-Wasserstein distance, although its mixing rate can be slightly slower. Experiments on both synthetic and real datasets verify our theoretical results and demonstrate the superior performance of LS-SGLD on different machine learning tasks including posterior sampling, Bayesian logistic regression, and training Bayesian convolutional neural networks.
Previous work has identified the importance of the lipophilic-fluorophilic block length ratio R l in predicting the morphology of linear lipophilic-hydrophilic-fluorophilic (hereafter referred to as BAC) micelle systems. Here, a generalized form R of this structural parameter is developed that makes no assumption of BAC triblock copolymer linearity, while still providing accurate predictions of micelle morphology. Here, the morphologies of BAC micelles formed by triblock copolymers with R <<1 or R >>1 have similar features, with the only notable difference being an inversion of the lipophilic and fluorophilic regions. A destabilization of the single-core micelle structure occurs as R approaches unity from either direction. Finally, the extent to which micelle morphology depends on polymer architecture instead of composition alone is examined, with decreased patchiness observed in BAC systems with very long block lengths. Through modification of both the R-value and the polymer architecture, the micelle morphology can be effectively tuned for use in immobilized catalysis and nanoreactor applications.
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To investigate whether the vascular collapse in tumors by conventional dose rate (CONV) irradiation (IR) would also occur by the ultra-high dose rate FLASH IR.
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