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Abstract Antiferromagnetic (AFM) materials are a pathway to spintronic memory and computing devices with unprecedented speed, energy efficiency, and bit density. Realizing this potential requires AFM devices with simultaneous electrical writing and reading of information, which are also compatible with established silicon‐based manufacturing. Recent experiments have shown tunneling magnetoresistance (TMR) readout in epitaxial AFM tunnel junctions. However, these TMR structures are not grown using a silicon‐compatible deposition process, and controlling their AFM order required external magnetic fields. Here are shown three‐terminal AFM tunnel junctions based on the noncollinear antiferromagnet PtMn₃, sputter‐deposited on silicon. The devices simultaneously exhibit electrical switching using electric currents, and electrical readout by a large room‐temperature TMR effect. First‐principles calculations explain the TMR in terms of the momentum‐resolved spin‐dependent tunneling conduction in tunnel junctions with noncollinear AFM electrodes. 

Abstract Objective.Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the periphery of a heterogeneous conductor are inverted to map its internal conductivity. The EIT method proposed here aims to improve computational speed and noise tolerance by introducing sensitivity volume as a figure-of-merit for comparing EIT measurement protocols.Approach.Each measurement is shown to correspond to a sensitivity vector in model space, such that the set of measurements, in turn, corresponds to a set of vectors that subtend a sensitivity volume in model space. A maximal sensitivity volume identifies the measurement protocol with the greatest sensitivity and greatest mutual orthogonality. A distinguishability criterion is generalized to quantify the increased noise tolerance of high sensitivity measurements.Main result.The sensitivity volume method allows the model space dimension to be minimized to match that of the data space, and the data importance to be increased within an expanded space of measurements defined by an increased number of contacts.Significance.The reduction in model space dimension is shown to increasecomputational efficiency, accelerating tomographic inversion by several orders of magnitude, while the enhanced sensitivitytolerates higher noiselevels up to several orders of magnitude larger than standard methods. 

One method to improve the properties of covalent adaptable networks (CANs) is to reinforce them with a fraction of permanent cross‐links without sacrificing their (re)processability. Here, a simple method to synthesize poly(n‐hexyl methacrylate) (PHMA) and poly(n‐lauryl methacrylate) (PLMA) networks containing static dialkyl disulfide cross‐links (utilizing bis(2‐methacryloyl)oxyethyl disulfide, or DSDMA, as a permanent cross‐linker) and dynamic dialkylamino sulfur‐sulfur cross‐links (utilizing BiTEMPS methacrylate as a dissociative dynamic covalent cross‐linker) is presented. The robustness and (re)processability of the CANs are demonstrated, including the full recovery of cross‐link density after recycling. The authors also investigate the effect of static cross‐link content on the stress relaxation responses of the CANs with and without percolated, static cross‐links. As PHMA and PLMA have very different activation energies of their respective cooperative segmental mobilities, it is shown that the dissociative CANs without percolated, static cross‐links have activation energies of stress relaxation that are dominated by the dissociation of BiTEMPS methacrylate cross‐links rather than by the cooperative relaxations of backbone segments, i.e., the alpha relaxation. In CANs with percolated, static cross‐links, the segmental relaxation of side chains, i.e., the beta relaxation, is critical in allowing for large‐scale stress relaxation and governs their activation energies of stress relaxation. 

A reaction limited by standard diffusion is simulated stochastically to illustrate how the continuous time random walk (CTRW) formalism can be implemented with minimum statistical error. A step-by-step simulation of the diffusive random walk in one dimension reveals the fraction of surviving reactants P(t) as a function of time, and the time-dependent unimolecular reaction rate coefficient K(t). Accuracy is confirmed by comparing the time-dependent simulation to results from the analytical master equation, and the asymptotic solution to that of Fickian diffusion. An early transient feature is shown to arise from higher spatial harmonics in the Fourier distribution of walkers between reaction sites. Statistical ‘shot’ noise in the simulation is quantified along with the offset error due to the discrete time derivative, and an optimal simulation time interval t0 is derived to achieve minimal error in the finite time-difference estimation of the reaction rate. The number of walkers necessary to achieve a given error tolerance is derived, and W = 10^7 walkers is shown to achieve an accuracy of ±0.2% when the survival probability reaches P(t) ∼ 1/3 . The stochastic method presented here serves as an intuitive basis for understanding the CTRW formalism, and can be generalized to model anomalous diffusion-limited reactions to prespecified precision in regimes where the governing wait-time distributions have no analytical solution.