Analytical methods for superresolution dislocation identification in dark-field X-ray microscopy

Journal of Materials Science - We develop several inference methods to estimate the position of dislocations from images generated using dark-field X-ray microscopy (DFXM)—achieving...     

Photoactive Earth‐Abundant Iron Pyrite Catalysts for Electrocatalytic Nitrogen Reduction Reaction

The generation of ammonia, hydrogen production, and nitrogen purification are considered as energy intensive processes accompanied with large amounts of CO₂ emission. An electrochemical method assisted by photoenergy is widely utilized for the chemical energy conversion. In this work, earth‐abundant iron pyrite (FeS₂) nanocrystals grown on carbon fiber paper (FeS₂/CFP) are found to be an electrochemical and photoactive catalyst for nitrogen reduction reaction under ambient temperature and pressure. The electrochemical results reveal that FeS₂/CFP achieves a high Faradaic efficiency (FE) of ≈14.14% and NH₃ yield rate of ≈0.096 µg min^?1 at ?0.6 V versus RHE electrode in 0.25 m LiClO₄. During the electrochemical catalytic reaction, the crystal structure of FeS₂/CFP remains in the cubic pyrite phase, as analyzed by in situ X‐ray diffraction measurements. With near‐infrared laser irradiation (808 nm), the NH₃ yield rate of the FeS₂/CFP catalyst can be slightly improved to 0.1 µg min^?1 with high FE of 14.57%. Furthermore, density functional theory calculations demonstrate that the N₂ molecule has strong chemical adsorption energy on the iron atom of FeS₂. Overall, iron pyrite‐based materials have proven to be a potential electrocatalyst with photoactive behavior for ammonia production in practical applications.     

Design of Trehalose-Based Amide/Sulfonamide C-type Lectin Receptor Signaling Compounds

Mincle agonists have been shown to induce inflammatory cytokine production, such as tumor necrosis factor-alpha (TNF) and promote the development of a Th1/Th17 immune response that might be crucial to development of effective vaccination against pathogens such as Mycobacterium tuberculosis. As an expansion of our previous work, a library of 6,6′-amide and sulfonamide α,α-d -trehalose compounds with various substituents on the aromatic ring was synthesized efficiently in good to excellent yields. These compounds were evaluated for their ability to activate the human C-type lectin receptor Mincle by the induction of cytokines from human peripheral blood mononuclear cells. A preliminary structure–activity relationship (SAR) of these novel trehalose diamides and sulfonamides revealed that aryl amide-linked trehalose compounds demonstrated improved activity and relatively high potency cytokine production compared to the Mincle ligand trehalose dibehenate adjuvant (TDB) and the natural ligand trehalose dimycolate (TDM) inducing dose-dependent and human-Mincle-specific stimulation in a HEK reporter cell line.     

Using deep learning to combine static and dynamic power analyses of cryptographic circuits

Side-channel attacks have shown to be efficient tools in breaking cryptographic hardware. Many conventional algorithms have been proposed to perform side-channel attacks exploiting the dynamic power leakage. In recent years, with the development of processing technology, static power has emerged as a new potential source for side-channel leakage. Both types of power leakage have their advantages and disadvantages. In this work, we propose to use the deep neural network technique to combine the benefits of both static and dynamic power. This approach replaces the classifier in template attacks with our proposed long short-term memory network schemes. Hence, instead of deriving a specific probability density model for one particular type of power leakage, we gain the ability of combining different leakage sources using a structural algorithm. In this paper, we propose three schemes to combine the static and dynamic power leakage. The performance of these schemes is compared using simulated test circuits designed with a 45-nm library.     

Advanced Postirradiation Characterization of Nuclear Fuels Using Pulsed Neutrons

Methods for postirradiation characterization of bulk (cm³) irradiated materials or even spent nuclear fuels are sparse due to their extremely radioactive nature. While several methods exist to characterize smaller volumes (<?1 mm³) of such samples, selecting these volumes from larger samples is challenging. X-ray-based methods are prohibitive due to the strong γ-radiation from the sample flooding the detectors. Neutron-based methods available in the proximity of irradiation reactors allow for thermal neutron radiography or computed tomography using a small reactor source, but one cannot assess isotope distributions or microstructural features such as phases, texture, or strain from diffraction measurements due to flux limitations. We present herein a pathway to provide pulsed neutron characterization of bulk irradiated samples using time-of-flight neutron diffraction for microstructural characterization and energy-resolved neutron imaging for assessment of isotopic densities and distributions. Ultimately, laser-driven pulsed neutron sources may allow deployment of these techniques pool-side at irradiation reactors.

     

Photophoretic Levitation of Macroscopic Nanocardboard Plates

Scaling down miniature rotorcraft and flapping-wing flyers to sub-centimeter dimensions is challenging due to complex electronics requirements, manufacturing limitations, and the increase in viscous damping at low Reynolds numbers. Photophoresis, or light-driven fluid flow, was previously used to levitate solid particles without any moving parts, but only with sizes of 1–20 µm. Here, architected metamaterial plates with 50 nm thickness are leveraged to realize photophoretic levitation at the millimeter to centimeter scales. Instead of creating lift through conventional rotors or wings, the nanocardboard plates levitate due to light-induced thermal transpiration through microchannels within the plates, enabled by their extremely low mass and thermal conductivity. At atmospheric pressure, the plates hover above a solid substrate at heights of ≈0.5 mm by creating an air cushion beneath the plate. Moreover, at reduced pressures (10–200 Pa), the increased speed of thermal transpiration through the plate's channels creates an air jet that enables mid-air levitation and allows the plates to carry small payloads heavier than the plates themselves. The macroscopic metamaterial structures demonstrate the potential of this new mechanism of flight to realize nanotechnology-enabled flying vehicles without any moving parts in the Earth's upper atmosphere and at the surface of other planets.     

Outlier accommodation in moving-horizon state estimation: A risk-averse performance-specified approach

This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation.     

Optimization of Pathogen Capture in Flowing Fluids with Magnetic Nanoparticles

Magnetic nanoparticles have been employed to capture pathogens for many biological applications; however, optimal particle sizes have been determined empirically in specific capturing protocols. Here, a theoretical model that simulates capture of bacteria is described and used to calculate bacterial collision frequencies and magnetophoretic properties for a range of particle sizes. The model predicts that particles with a diameter of 460 nm should produce optimal separation of bacteria in buffer flowing at 1 L h⁻¹. Validating the predictive power of the model, Staphylococcus aureus is separated from buffer and blood flowing through magnetic capture devices using six different sizes of magnetic particles. Experimental magnetic separation in buffer conditions confirms that particles with a diameter closest to the predicted optimal particle size provide the most effective capture. Modeling the capturing process in plasma and blood by introducing empirical constants (c_e), which integrate the interfering effects of biological components on the binding kinetics of magnetic beads to bacteria, smaller beads with 50 nm diameters are predicted that exhibit maximum magnetic separation of bacteria from blood and experimentally validated this trend. The predictive power of the model suggests its utility for the future design of magnetic separation for diagnostic and therapeutic applications.