Compressive Strain Reduces the Hydrogen Evolution and Oxidation Reaction Activity of Platinum in Alkaline Solution
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Abstract The compression behavior of osmium metal was investigated up to 280 GPa (volume compression V/V o = 0.725) under nonhydrostatic conditions at ambient temperature using angle dispersive axial x-ray diffraction (A-XRD) with a diamond anvil cell (DAC). In addition, shear strength of osmium was measured to 170 GPa using radial x-ray diffraction (R-XRD) technique in DAC. Both diffraction techniques in DAC employed platinum as an internal pressure standard. Density functional theory (DFT) calculations were also performed, and the computed lattice parameters and volumes under compression are in good agreement with the experiments. DFT predicts a monotonous increase in axial ratio ( c/a ) with pressure and the structural anomalies of less than 1% in ( c/a ) ratio reported below 150 GPa were not reproduced in theoretical calculations and hydrostatic measurements. The measured value of shear strength of osmium ( τ ) approaches a limiting value of 6 GPa above a pressure of 50 GPa in contrast to theoretical predictions of 24 GPa and is likely due to imperfections in polycrystalline samples. DFT calculations also enable the studies of shear and tensile deformations. The theoretical ideal shear stress is found along the (001)[1–10] shear direction with the maximal shear stress ∼24 GPa at critical strain ∼0.13.
Recent advances in nanotechnology have enabled researchers to manipulate small collections of quantum-mechanical objects with unprecedented accuracy. In semiconductor quantum-dot qubits, this manipulation requires controlling the dot orbital energies, the tunnel couplings, and the electron occupations. These properties all depend on the voltages placed on the metallic electrodes that define the device, the positions of which are fixed once the device is fabricated. While there has been much success with small numbers of dots, as the number of dots grows, it will be increasingly useful to control these systems with as few electrode voltage changes as possible. Here, we introduce a protocol, which we call the "compressed optimization of device architectures" (CODA), in order both to efficiently identify sparse sets of voltage changes that control quantum systems and to introduce a metric that can be used to compare device designs. As an example of the former, we apply this method to simulated devices with up to 100 quantum dots and show that CODA automatically tunes devices more efficiently than other common nonlinear optimizers. To demonstrate the latter, we determine the optimal lateral scale for a triple quantum dot, yielding a simulated device that can be tuned with small voltage changes on a limited number of electrodes.
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Room temperature compression of graphitic materials leads to interesting superhard sp 3 rich phases which are sometimes transparent. In the case of graphite itself, the sp 3 rich phase is proposed to be monoclinic M-carbon; however, for disordered materials such as glassy carbon the nature of the transformation is unknown. We compress glassy carbon at room temperature in a diamond anvil cell, examine the structure in situ using x-ray diffraction, and interpret the findings with molecular dynamics modeling. Experiment and modeling both predict a two-stage transformation. First, the isotropic glassy carbon undergoes a reversible transformation to an oriented compressed graphitic structure. This is followed by a phase transformation at ~35 GPa to an unstable, disordered sp 3 rich structure that reverts on decompression to an oriented graphitic structure. Analysis of the simulated sp 3 rich material formed at high pressure reveals a noncrystalline structure with two different sp 3 bond lengths.
Here, compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quantification analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several compressive sensing solvers that target the unconstrained LASSO formulation, with a focus on linear systems that arise in the construction of polynomial chaos expansions. With core solvers l1_ls, SpaRSA, CGIST, FPC_AS, and ADMM, we develop techniques to mitigate overfitting through an automated selection of regularization constant based on cross-validation, and a heuristic strategy to guide the stop-sampling decision. Practical recommendations on parameter settings for these techniques are provided and discussed. The overall method is applied to a series of numerical examples of increasing complexity, including large eddy simulations of supersonic turbulent jet-in-crossflow involving a 24-dimensional input. Through empirical phase-transition diagrams and convergence plots, we illustrate sparse recovery performance under structures induced by polynomial chaos, accuracy, and computational trade-offs between polynomial bases of different degrees, and practicability of conducting compressive sensing for a realistic, high-dimensional physical application. Across test cases studied in this paper, we find ADMM to have demonstrated empirical advantages through consistent lower errors and faster computational times.
We experimentally demonstrate how divided-pulse nonlinear compression can be used to improve the temporal contrast of a laser pulse train while simultaneously temporally compressing the pulses. We measure a contrast improvement of almost four orders of magnitude on a nanosecond time scale and temporally compress the pulses from 1.2 ps to 187 fs. The efficiency of our method is also competitive with other contrast improvement methods, with 72% efficiency measured for the main pulse. We expect the method will be useful in the continuing development of high-power, Yb regenerative amplifiers, which suffer from both significant prepulses and relatively long pulse durations.
As the pioneer semiconductor in transistor, germanium (Ge) has been widely applied in information technology for over half a century. Although many phase transitions in Ge have been reported, the complicated phenomena of the phase structures in amorphous Ge under extreme conditions are still not fully investigated. Here, we report the different routes of phase transition in amorphous Ge under different compression conditions utilizing diamond anvil cell (DAC) combined with synchrotron-based X-ray diffraction (XRD) and Raman spectroscopy techniques. Upon non-hydrostatic compression of amorphous Ge, we observed that shear stress facilitates a reversible pressure-induced phase transformation, in contrast to the pressure-quenchable structure under a hydrostatic compression. These findings afford better understanding of the structural behaviors of Ge under extreme conditions, which contributes to more potential applications in the semiconductor field.
A method of bunch length compression method for a free electron laser (FEL) that avoids parasitic compressions by 1) applying acceleration on the falling portion of the RF waveform, 2) compressing using a positive momentum compaction (R.sub.56>0), and 3) compensating for aberration by using nonlinear magnets in the compressor beam line.
Methanol is a potentially attractive fuel for marine and off−road engines owing to its availability at bunkering and global distribution locations. Although methanol is well−distributed worldwide, its fuel chemistry and ignition properties make it poorly suited as a direct drop−in replacement for diesel fuel in compression−ignition engines. However, industrial processes are regularly used to convert methanol, via catalytic dehydration, to dimethyl ether (DME) over nonprecious metal catalysts. This chemical conversion can occur at relatively low pressures, temperatures, and catalyst space velocities, highlighting a potential opportunity to generate DME via onboard catalytic dehydration of methanol. DME’s fuel kinetic and ignition properties for compression ignition are much more favorable than those of methanol or even diesel fuel, but DME is more challenging than diesel fuel or methanol to pump, store, and deliver through conventional diesel fueling injection hardware. Thus, a potential opportunity exists to use the ignition and kinetic properties of DME, with the transportation and delivery advantages of methanol, in a methanol−fueled mixing−controlled compression−ignition engine. The present work explores performance, combustion behavior, and emissions reduction opportunities for methanol mixing−controlled combustion, enabled by a HCCI of DME that represents a small fraction of the total fuel energy that can be generated onboard via catalytic dehydration of methanol.
A computational technique has been developed to perform compressible flow simulations involving moving boundaries using an embedded boundary approach within the block-structured adaptive mesh refinement (SAMR) framework of AMReX [1], [91], [92]. We leverage the SAMR capability to obtain quantitatively accurate results whilst using robust, second-order finite volume schemes. A conservative, unsplit, cut-cell approach is utilized and a ghost-cell approach is developed for computing the flux on the moving, embedded boundary faces. A third-order least-squares formulation has been developed to compute the wall velocity gradients, and was found to significantly improve the performance of the solver in terms of the quantitative comparison of surface quantities such as the skin friction coefficient. Various test cases are performed to validate the method, and compared with analytical, experimental, and other numerical results in literature. Inviscid and viscous test cases are performed that span a wide regime of flow speeds - acoustic (harmonically pulsating sphere), smooth flows (expansion fan created by a receding piston) and flows with shocks (shock-cylinder interaction, shock-wedge interaction, pitching NACA 0012 airfoil and shock-cone interaction). A closed system with moving boundaries - an oscillating piston in a cylinder, showed that the percentage error in mass within the system decreases with refinement, demonstrating that the numerical scheme is conservative with grid refinement, but is not discretely conservative. Viscous test cases involve that of a horizontally moving cylinder at Re = 40, an inline oscillating cylinder at Re = 100, and a transversely oscillating cylinder at Re = 185. The judicious use of adaptive mesh refinement with appropriate refinement criteria to capture the regions of interest leads to well-resolved flow features, and good quantitative comparison is observed with the results available in literature.
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A rapid compression machine is an experimental apparatus used to study ignition chemistry at conditions that are relevant to internal combustion engines and gas turbines. However, due to the operating characteristics of these devices, heat transfer effects and inhomogeneous ignition events can be encountered. Hence, this paper develops a combustion regime diagram, which incorporates these effects in order to better understand physical in uences on the measurements. This diagram employs familiar Damkohler number and Reynolds number scaling, and seeks to provide an operational guide for rapid compression machine experiments. This diagram is compared to experimental data and good agreement is found.
Abstract not provided
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