Modeling of Dynamic Effects in a Laser-Driven Semiconductor Switch of High-Power Microwaves

Problems of high-power microwaves penetrating into and reflecting from a semiconductor (silicon) plate with non-stationary processes are investigated. The plate is the basis of switches activated by laser-driven photoconductivity which changes its properties when heated by the switched microwave power. Analytical criteria for the stationary solutions of the activated (quasi-metallic) and deactivated (dielectric) states of the switch under the conditions of high-power microwave heating and external cooling are found. Results of numerical simulations are also given for the problems of the switch activation by microwave heating initiated by pulsed laser radiation, which increases the carrier density rapidly. Numerical simulations are carried out using the finite-difference time-domain method with the unsplit perfectly matched layer absorbing boundary conditions. We demonstrate various types of solutions depending on the basic parameters of the problems - microwave field intensity, laser pulse energy and semiconductor doping.     

Simulation study on acoustic streaming and convective cooling in blood vessels during a high-intensity focused ultrasound thermal ablation

This study investigates the influence of blood vessels on temperature distribution during high-intensity focused ultrasound (HIFU) ablation of liver tumors. A three-dimensional acoustics-thermal-fluid coupling model is simulated to compute the temperature field in the hepatic cancerous region. The model is based on the linear Westervelt and bioheat equations as well as the non-linear Navier–Stokes equations for the liver parenchyma and blood vessels. The effect of acoustic streaming is also taken into account in the present HIFU simulation study. We found from this three-dimensional coupling study that in large blood vessel both the convective cooling and acoustic streaming can significantly change the temperature field and thermal lesion near blood vessels.     

Microscale geochemical gradients in Hanford 300 Area sediment biofilms and influence of uranium

The presence and importance of microenvironments in the subsurface at contaminated sites were suggested by previous geochemical studies. However, no direct quantitative characterization of the geochemical microenvironments had been reported. We quantitatively characterized microscale geochemical gradients (dissolved oxygen (DO), H₂, pH, and redox potential) in Hanford 300A subsurface sediment biofilms. Our results revealed significant differences in geochemical parameters across the sediment biofilm/water interface in the presence and absence of U(VI) under oxic and anoxic conditions. While the pH was relatively constant within the sediment biofilm, the redox potential and the DO and H₂ concentrations were heterogeneous at the microscale (<500-1000 μm). We found microenvironments with high DO levels (DO hotspots) when the sediment biofilm was exposed to U(VI). On the other hand, we found hotspots (high concentrations) of H₂ under anoxic conditions both in the presence and in the absence of U(VI). The presence of anoxic microenvironments inside the sediment biofilms suggests that U(VI) reduction proceeds under bulk oxic conditions. To test this, we operated our biofilm reactor under air-saturated conditions in the presence of U(VI) and characterized U speciation in the sediment biofilm. U L_III-edge X-ray absorption spectroscopy (XANES and EXAFS) showed that 80-85% of the U was in the U(IV) valence state.     

Ultra-Robust Flexible Electronics by Laser-Driven Polymer-Nanomaterials Integration

Polyethylene terephthalate (PET) is the most widely used polymer in the world. For the first time, the laser-driven integration of aluminum nanoparticles (Al NPs) into PET to realize a laser-induced graphene/Al NPs/polymer composite, which demonstrates excellent toughness and high electrical conductivity with the formation of aluminum carbide into the polymer is shown. The conductive structures show an impressive mechanical resistance against >10000 bending cycles, projectile impact, hammering, abrasion, and structural and chemical stability when in contact with different solvents (ethanol, water, and aqueous electrolytes). Devices including thermal heaters, carbon electrodes for energy storage, electrochemical and bending sensors show this technology's practical application for ultra-robust polymer electronics. This laser-based technology can be extended to integrating other nanomaterials and create hybrid graphene-based structures with excellent properties in a wide range of flexible electronics’ applications.     

Thermal stability of the nanolayered Fe2AlB2 in nitrogen and argon atmospheres

The thermal stability and decomposition mechanisms of Fe₂AlB₂ powders, synthesized by reactive powder metallurgy, were studied under nitrogen (N₂) or argon (Ar) atmospheres. The effects of using different FeB precursors to synthesize the Fe₂AlB₂ and hydrochloric acid (HCl) purification treatments on the thermal stability were also investigated. When as-synthesized Fe₂AlB₂ powders are treated in dilute HCl to dissolve impurity phases, decomposition in N₂ atmospheres occurs readily above 1200 K. The decomposition reaction involves β-FeB precipitation and the liberated Al atoms reacting with the ambient N₂ to form AlN. Under Ar environments, HCl-treated Fe₂AlB₂ powders decompose and precipitate β-FeB, by the out-diffusion of Al from the nanolaminated structure. Interestingly, isothermal annealing under N₂ atmospheres revealed that Fe₂AlB₂ was more thermally stable when synthesized from lab-synthesized, instead of commercially available, FeB precursors and when the HCl treatment was avoided. The effects of the various factors on the decomposition temperature and decomposition mechanisms are discussed herein.     

Quantifying adherence of oxide scales on steels exposed to high temperature and pressure steam

Oxide scale exfoliation is a major concern in fossil fuel power generation because it can cause tube blockages and erode valves and steam turbine components downstream. There is still considerable scientific and commercial interest to improve the mechanistic understanding of oxide failures by developing models to predict exfoliation and the extent of tube blockage as a function of operating conditions and component geometries. Tensile testing inside a scanning electron microscope was conducted on ferritic–martensitic and austenitic steel specimens with the steam side (Fe,Cr)-rich oxides grown after exposures for up to 1000 h in steam with ~100 ppb O₂ at 276 bar and 550°C. Multiple oxide layer cracks and delamination events were observed and analyzed in detail during the tests. Results from the testing agreed well with earlier observations that had identified the failure location at the outer–inner oxide layer for all tested materials. Calculated adhesion energies identified the outer–inner oxide interface of alloy 347HFG as the weakest interface.     

Identification of the Primary Factors Determining the Specificity of Human VKORC1 Recognition by Thioredoxin-Fold Proteins

Redox (reduction–oxidation) reactions control many important biological processes in all organisms, both prokaryotes and eukaryotes. This reaction is usually accomplished by canonical disulphide-based pathways involving a donor enzyme that reduces the oxidised cysteine residues of a target protein, resulting in the cleavage of its disulphide bonds. Focusing on human vitamin K epoxide reductase (hVKORC1) as a target and on four redoxins (protein disulphide isomerase (PDI), endoplasmic reticulum oxidoreductase (ERp18), thioredoxin-related transmembrane protein 1 (Tmx1) and thioredoxin-related transmembrane protein 4 (Tmx4)) as the most probable reducers of VKORC1, a comparative in-silico analysis that concentrates on the similarity and divergence of redoxins in their sequence, secondary and tertiary structure, dynamics, intraprotein interactions and composition of the surface exposed to the target is provided. Similarly, hVKORC1 is analysed in its native state, where two pairs of cysteine residues are covalently linked, forming two disulphide bridges, as a target for Trx-fold proteins. Such analysis is used to derive the putative recognition/binding sites on each isolated protein, and PDI is suggested as the most probable hVKORC1 partner. By probing the alternative orientation of PDI with respect to hVKORC1, the functionally related noncovalent complex formed by hVKORC1 and PDI was found, which is proposed to be a first precursor to probe thiol–disulphide exchange reactions between PDI and hVKORC1.     

Forging furnace with thermochemical waste-heat recuperation by natural gas reforming: Fuel saving and heat balance

This paper considers thermochemical recuperation (TCR) of waste-heat using natural gas reforming by steam and combustion products. Combustion products contain steam (H₂O), carbon dioxide (CO₂), and ballast nitrogen (N₂). Because endothermic chemical reactions take place, methane steam-dry reforming creates new synthetic fuel that contains valuable combustion components: hydrogen (H₂), carbon monoxide (CO), and unreformed methane (CH₄). There are several advantages to performing TCR in the industrial furnaces: high energy efficiency, high regeneration rate (rate of waste-heat recovery), and low emission of greenhouse gases (CO₂, NO_x). As will be shown, the use of TCR is significantly increasing the efficiency of industrial furnaces – it has been observed that TCR is capable of reducing fuel consumption by nearly 25%. Additionally, increased energy efficiency has a beneficial effect on the environment as it leads to a reduction in greenhouse gas emissions.     

Learning and Predicting Photonic Responses of Plasmonic Nanoparticle Assemblies via Dual Variational Autoencoders

The application of machine learning is demonstrated for rapid and accurate extraction of plasmonic particles cluster geometries from hyperspectral image data via a dual variational autoencoder (dual-VAE). In this approach, the information is shared between the latent spaces of two VAEs acting on the particle shape data and spectral data, respectively, but enforcing a common encoding on the shape-spectra pairs. It is shown that this approach can establish the relationship between the geometric characteristics of nanoparticles and their far-field photonic responses, demonstrating that hyperspectral darkfield microscopy can be used to accurately predict the geometry (number of particles, arrangement) of a multiparticle assemblies below the diffraction limit in an automated fashion with high fidelity (for monomers (0.96), dimers (0.86), and trimers (0.58). This approach of building structure-property relationships via shared encoding is universal and should have applications to a broader range of materials science and physics problems in imaging of both molecular and nanomaterial systems.     

MidDRIFTS-PLSR-based quantification of physico-chemical soil properties across two agroecological zones in Southwest Germany: generic independent validation surpasses region specific cross-validation

Development of spectroscopic prediction models via partial least squares regression (PLSR) suggests that model performance is highly affected by means of calibration and nature of the dataset. This study compares the predictive performance of PLSR models obtained by cross-validation and independent validation to quantify physico-chemical soil properties from their mid-infrared diffuse reflectance Fourier transform spectra (midDRIFTS) across two contrasting regions, Kraichgau (K) and Swabian Alb (SA), in Southwest Germany. We evaluated the capability of midDRIFTS-PLSR models for predicting total carbon (TC), organic carbon (TOC), inorganic carbon (TIC), nitrogen (TN), mineral N (N_min), C:N ratio, hot water extractable C and N (C_HWE, N_HWE), microbial biomass C and N (C_mic, N_mic), pH, bulk density, and clay, silt and sand contents of 126 soil samples. Based on calibrated models, most soil properties were predicted successfully using either calibration approach with residual prediction deviations ≥3 and R² > 0.9, except for N_min, C/N ratio, pH, bulk density and sand. However, predictive performance of generic independent validation derived models (GIC) of test set was considerably higher than generic cross-validation models. Validation using GIC models gave relatively the same predictive performance with those obtained in calibration except for N_min. Validation of region specific cross-validated models, however, resulted in successful predictions only for TC, TIC, TOC and TN in SA and TC and TIC and TOC in K. Our results show the superiority of independent validation over both generic and region specific cross-validation as a robust tool for predicting soil properties without further laboratory measurements.