Objective: Accelerated magnetic resonance (MR) image acquisition with compressed sensing (CS) and parallel imaging is a powerful method to reduce MR imaging scan time. However, many reconstruction ...algorithms have high computational costs. To address this, we investigate deep residual learning networks to remove aliasing artifacts from artifact corrupted images. Methods: The deep residual learning networks are composed of magnitude and phase networks that are separately trained. If both phase and magnitude information are available, the proposed algorithm can work as an iterative k-space interpolation algorithm using framelet representation. When only magnitude data are available, the proposed approach works as an image domain postprocessing algorithm. Results: Even with strong coherent aliasing artifacts, the proposed network successfully learned and removed the aliasing artifacts, whereas current parallel and CS reconstruction methods were unable to remove these artifacts. Conclusion: Comparisons using single and multiple coil acquisition show that the proposed residual network provides good reconstruction results with orders of magnitude faster computational time than existing CS methods. Significance: The proposed deep learning framework may have a great potential for accelerated MR reconstruction by generating accurate results immediately.
Herein we report a rational design strategy for tailoring intermolecular interactions to enhance room‐temperature phosphorescence from purely organic materials in amorphous matrices at ambient ...conditions. The built‐in strong halogen and hydrogen bonding between the newly developed phosphor G1 and the poly(vinyl alcohol) (PVA) matrix efficiently suppresses vibrational dissipation and thus enables bright room‐temperature phosphorescence (RTP) with quantum yields reaching 24 %. Furthermore, we found that modulation of the strength of halogen and hydrogen bonding in the G1–PVA system by water molecules produced unique reversible phosphorescence‐to‐fluorescence switching behavior. This unique system can be utilized as a ratiometric water sensor.
A bright idea: Rationally designed strong intermolecular hydrogen and halogen bonds between a novel phosphor and a poly(vinyl alcohol) (PVA) matrix led to bright room‐temperature phosphorescence (RTP) with a quantum yield of 24 %. Modulation of the strength of halogen and hydrogen bonding in the purely organic phosphor–PVA system by water enabled reversible switching between phosphorescence (green) and fluorescence (blue).
Developing metal-free organic phosphorescent materials is promising but challenging because achieving emissive triplet relaxation that outcompetes the vibrational loss of triplets, a key process to ...achieving phosphorescence, is difficult without heavy metal atoms. While recent studies reveal that bright room temperature phosphorescence can be realized in purely organic crystalline materials through directed halogen bonding, these organic phosphors still have limitations to practical applications due to the stringent requirement of high quality crystal formation. Here we report bright room temperature phosphorescence by embedding a purely organic phosphor into an amorphous glassy polymer matrix. Our study implies that the reduced beta (β)-relaxation of isotactic PMMA most efficiently suppresses vibrational triplet decay and allows the embedded organic phosphors to achieve a bright 7.5% phosphorescence quantum yield. We also demonstrate a microfluidic device integrated with a novel temperature sensor based on the metal-free purely organic phosphors in the temperature-sensitive polymer matrix. This unique system has many advantages: (i) simple device structures without feeding additional temperature sensing agents, (ii) bright phosphorescence emission, (iii) a reversible thermal response, and (iv) tunable temperature sensing ranges by using different polymers.
We propose TiO x -based resistive switching device for neuromorphic synapse applications. This device is capable of 64-levels conductance states because of their optimized interface between the metal ...electrode and the TiOx film. To compensate the change in switching power with increasing pulse number, we propose the use of fixed voltage and current pulses in potentiation and depression conditions, respectively. By adopting a hybrid pulse scheme, the symmetry of conductance change under both potentiation and depression conditions is shown to be significantly improved. Both the improved conductance levels and the symmetry of conductance change are directly related with enhanced pattern recognition accuracy, which is confirmed by a neural network simulation.
Parallel MRI (pMRI) and compressed sensing MRI (CS-MRI) have been considered as two distinct reconstruction problems. Inspired by recent k-space interpolation methods, an annihilating filter-based ...low-rank Hankel matrix approach is proposed as a general framework for sparsity-driven k-space interpolation method which unifies pMRI and CS-MRI. Specifically, our framework is based on a novel observation that the transform domain sparsity in the primary space implies the low-rankness of weighted Hankel matrix in the reciprocal space. This converts pMRI and CS-MRI to a k-space interpolation problem using a structured matrix completion. Experimental results using in vivo data for single/multicoil imaging as well as dynamic imaging confirmed that the proposed method outperforms the state-of-the-art pMRI and CS-MRI.
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Complex oxides, such as ABO3 perovskites, are an important class of functional materials that exhibit a wide range of physical, chemical, and electrochemical properties, including ...high oxygen electrocatalytic activity, tunable electronic/ionic conductivity, and ferroelectricity. When complex oxides are engineered as thin films, their chemical and physical properties can be modified to be markedly different from their bulk form, providing additional degrees of freedom in materials design. In this review, we survey the landscape of strain-induced design of complex oxides in the context of oxygen electrocatalysis and ferroelectricity. First, we identify the role of strain in influencing oxide electronic properties, driven by the combination of modification of BO bond length and octahedral distortion in perovskites. We describe electronic structure parameters, such as the O 2p-band center, that quantitatively capture these electronic changes, highlighting the broad influence of the O 2p-band center on surface reactivity (oxygen adsorption and dissociation energy) and bulk defect energetics (oxygen vacancy formation and migration energy). Motivated by the promise of the influence of strain on material properties relevant for oxygen electrocatalysis and ferroelectricity, we describe the advances in state-of-the-art thin-film fabrication and characterization that have enabled a high degree of experimental control in realizing strain effects in oxide thin-film systems. In oxygen electrocatalysis, leveraging strain has not only resulted in activity enhancements relative to bulk unstrained material systems but also revealed mechanistic influences of oxide phenomena, such as bulk defect chemistry and transfer kinetics, on electrochemical processes. Similarly for ferroelectric properties, strain engineering can both enhance polarization in known ferroelectrics and induce ferroelectricity in material systems that would be otherwise non-ferroelectric in bulk. Based on understanding of a diverse range of perovskite functionalities, we offer perspectives on how further coupling of strain, oxygen electrocatalysis, and ferroelectricity opens up pathways toward the emergence of novel device design features with dynamic control of increasing complex chemical and high-performance electronic processes.
This brief presents a new method of analyzing stability and design of a controller for an electric power steering (EPS) system. The most important task when designing a steering system is ensuring ...that the driver is pleased with how the steering feels. The way that the steering feels is dependent upon the assist torque map. The assist torque map is a one-to-one map between sensed driver torque and assist motor torque that varies with the cars speed. However, an assist torque map cannot be applied alone as an EPS controller because of high level of steering assist gain and nonlinearity of the torque map. Both elements of torque map can result in instability, which leads to vibration or divergence of the steering system. Therefore, an EPS system always needs to be designed with a stabilizing compensator and an assist torque map. The objective of designing a compensator is to stabilize the system with robustness and attenuate any unpleasant vibration. This brief presents a mechanical model of the EPS system and demonstrates a method to identify the model parameter. Based on the EPS model, stability of the system with an approximate linear torque map and nonlinear torque map is analyzed. Furthermore, criteria for designing the stabilizing compensator are suggested. Lead-lag compensators with different parameters are applied with the torque map in simulations, and vehicle experiments are performed to verify the theoretical analysis.
Thermal conductivity is an important property for polymers, as it often affects product reliability (for example, electronics packaging), functionality (for example, thermal interface materials) ...and/or manufacturing cost. However, polymer thermal conductivities primarily fall within a relatively narrow range (0.1-0.5 W m(-1) K(-1)) and are largely unexplored. Here, we show that a blend of two polymers with high miscibility and appropriately chosen linker structure can yield a dense and homogeneously distributed thermal network. A sharp increase in cross-plane thermal conductivity is observed under these conditions, reaching over 1.5 W m(-1) K(-1) in typical spin-cast polymer blend films of nanoscale thickness, which is approximately an order of magnitude larger than that of other amorphous polymers.
In this paper, we extend the unsplit staggered mesh scheme (USM) for 2D magnetohydrodynamics (MHD) D. Lee, A.E. Deane, An unsplit staggered mesh scheme for multidimensional magnetohydrodynamics, J. ...Comput. Phys. 228 (2009) 952–975 to a full 3D MHD scheme. The scheme is a finite-volume Godunov method consisting of a constrained transport (CT) method and an efficient and accurate single-step, directionally unsplit multidimensional data reconstruction-evolution algorithm, which extends Colella’s original 2D corner transport upwind (CTU) method P. Colella, Multidimensional upwind methods for hyperbolic conservation laws, J. Comput. Phys. 87 (1990) 446–466. We present two types of data reconstruction-evolution algorithms for 3D: (1) a reduced CTU scheme and (2) a full CTU scheme. The reduced 3D CTU scheme is a variant of a simple 3D extension of Collela’s 2D CTU method and is considered as a direct extension from the 2D USM scheme. The full 3D CTU scheme is our primary 3D solver which includes all multidimensional cross-derivative terms for stability. The latter method is logically analogous to the 3D unsplit CTU method by Saltzman J. Saltzman, An unsplit 3D upwind method for hyperbolic conservation laws, J. Comput. Phys. 115 (1994) 153–168. The major novelties in our algorithms are twofold. First, we extend the reduced CTU scheme to the full CTU scheme which is able to run with CFL numbers close to unity. Both methods utilize the transverse update technique developed in the 2D USM algorithm to account for transverse fluxes without solving intermediate Riemann problems, which in turn gives cost-effective 3D methods by reducing the total number of Riemann solves. The proposed algorithms are simple and efficient especially when including multidimensional MHD terms that maintain in-plane magnetic field dynamics. Second, we introduce a new CT scheme that makes use of proper upwind information in taking averages of electric fields. Our 3D USM schemes can be easily combined with various reconstruction methods (e.g., first-order Godunov, second-order MUSCL-Hancock, third-order PPM and fifth-order WENO), and a wide choice of 1D based Riemann solvers (e.g., local Lax–Friedrichs, HLLE, HLLC, HLLD, and Roe). The 3D USM-MHD solver is available in the University of Chicago Flash Center’s official FLASH release.
Abstract This paper presents a fully multidimensional kernel-based reconstruction scheme for finite volume methods applied to systems of hyperbolic conservation laws, with a particular emphasis on ...the compressible Euler equations. Nonoscillatory reconstruction is achieved through an adaptive-order weighted essentially nonoscillatory (WENO) method cast into a form suited to multidimensional reconstruction. A kernel-based approach inspired by radial basis functions and Gaussian process modeling, which we call kernel-based finite volume method with WENO, is presented here. This approach allows the creation of a scheme of arbitrary order of accuracy with simply defined multidimensional stencils and substencils. Furthermore, the fully multidimensional nature of the reconstruction allows for a more straightforward extension to higher spatial dimensions and removes the need for complicated boundary conditions on intermediate quantities in modified dimension-by-dimension methods. In addition, a new simple yet effective set of reconstruction variables is introduced, which could be useful in existing schemes with little modification. The proposed scheme is applied to a suite of stringent and informative benchmark problems to demonstrate its efficacy and utility. A highly parallel multi-GPU implementation using Kokkos and the message-passing interface is also provided.
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