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The development of titanium matrix composites for elevated temperature applications was investigated. General solutions for treating diffusion in multiphase multicomponent systems were studied. Graphite polyimide composites were characterized with respect to mechanical property degradation by moisture.
XRD, Moessbauer spectroscopy, and EDXS have been used to characterize a rapidly-solidified (Co,Fe)3O4 spinel generated in a cobalt-iron-phosphate glass matrix by gas atomization of melts. Of the two compositions tested, that containing 20 mol pct P2O5 exhibited randomly-oriented ferrite crystallization whose growth appears to have been diffusion-controlled. Unlike the ferrite, in which the iron has both tetrahedral and octahedral coordination, the iron in the glassy matrix was primarily of distorted-octahedral coordination. Calculations indicate that the cooling rates obtained with oxide melts vary strongly with droplet size, but less strongly with melt temperature.
Significant efforts have been made to decompose polarimetric radar data into several simple scattering components. The components which are selected because of their physical significance can be used to classify SAR (Synthetic Aperture Radar) image data. If particular components can be related to forest parameters, inversion procedures may be developed to estimate these parameters from the scattering components. Several methods have been used to decompose an averaged Stoke's matrix or covariance matrix into three components representing odd (surface), even (double-bounce) and diffuse (volume) scatterings. With these decomposition techniques, phenomena, such as canopy-ground interactions, randomness of orientation, and size of scatters can be examined from SAR data. In this study we applied the method recently reported by van Zyl (1992) to decompose averaged backscattering covariance matrices extracted from JPL SAR images over forest stands in Maine, USA. These stands are mostly mixed stands of coniferous and deciduous trees. Biomass data have been derived from field measurements of DBH and tree density using allometric equations. The interpretation of the decompositions and relationships with measured stand biomass are presented in this paper.
Immunofluorescent localization of annexins using an anti-pea annexin polyclonal antibody (anti-p35) in pea (Pisum sativum) leaf and stem epidermal peels showed staining of the nuclei and the cell periphery. Nuclear staining was also seen in cell teases prepared from pea plumules. The amount of nuclear stain was reduced both by fixation time and by dehydration and organic solvent treatment. Observation with confocal microscopy demonstrated that the anti-p35 stain was diffusely distributed throughout the nuclear structure. Immunoblots of purified nuclei, nuclear envelope matrix, nucleolar, and chromatin fractions showed a cross-reactive protein band of 35 kDa. These data are the first to show annexins localized in plant cell nuclei where they may play a role in nuclear function.
Polymer mobility near nanoparticle surfaces has been extensively discussed; however, direct experimental observation in the nanocomposite melts has been a difficult task. Here, by taking advantage of large dynamical asymmetry between the miscible matrix and surface-bound polymers, we highlighted their interphases and studied the resulting effect on the nanoparticle relaxation using X-ray photon correlation spectroscopy. Here, the local mobility gradient is signified by an unprecedented increase in the relaxation time at length scales on the order of polymer radius of gyration. The effect is accompanied by a transition from simple diffusive to subdiffusive behavior in accord with viscous and entangled dynamics of polymers in the matrix and in the interphase, respectively. Our results demonstrate that the nanoparticle-induced polymer mobility changes in the interphases of nanocomposite melts can be extracted from the length-scale-dependent slow particle motion.
Multiplexed colorimetric solid-phase extraction (MC-SPE) is an extension of colorimetric solid-phase extraction (C-SPE) an analytical platform that combines colorimetric reagents, solid phase extraction, and diffuse reflectance spectroscopy to quantify trace analytes in water. In CSPE, analytes are extracted and complexed on the surface of an extraction membrane impregnated with a colorimetric reagent. The analytes are then quantified directly on the membrane surface using a handheld diffuse reflectance spectrophotometer. Importantly, the use of solid-phase extraction membranes as the matrix for impregnation of the colorimetric reagents creates a concentration factor that enables the detection of low concentrations of analytes in small sample volumes. In extending C-SPE to a multiplexed format, a filter holder that incorporates discrete analysis channels and a jig that facilitates the concurrent operation of multiple sample syringes have been designed, enabling the simultaneous determination of multiple analytes. Separate, single analyte membranes, placed in a readout cartridge create unique, analyte-specific addresses at the exit of each channel. Following sample exposure, the diffuse reflectance spectrum of each address is collected serially and the Kubelka-Munk function is used to quantify each water quality parameter via calibration curves. In a demonstration, MC-SPE was used to measure the pH of a sample and quantitate Ag(I) and Ni(II).
The activity of water is important in many natural systems and directed processes. To better understand water activity, the hydration of individual ions is approximated for a recently developed speciation-based solution model. Here a matrix of values for hydration of complete salts (anion and cation) was used as source data to calculate individual ion hydration values. Some electrolytes were excluded from calculations of individual ion hydration due to the prevalence of ion pairing and resulting liberation of water upon ion pairing. Evaluation of the periodic trends emerging from individual ion hydration values suggests that ionic volume, relative to the volume of molecular water, dictates both modeled hydration requirements (related to vapor-liquid-equilibrium-derived activity) as well as properties historically described by hydrodynamic radius (ion diffusion and solution viscosity). When water is conceptualized as a granular three-dimensional matrix, solutes may function as substitutional defects (dilation or constriction) inducing local compressive or tensile stress. These results have implications on the mechanism of the Hofmeister series and series reversals.
This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.
A mathematical model is presented for the transport and precipitation of mineral in refilling osteons. One goal of this model was to explain calcification 'halos,' in which the bone near the haversian canal is more highly mineralized than the more peripheral lamellae, which have been mineralizing longer. It was assumed that the precipitation rate of mineral is proportional to the difference between the local concentration of calcium ions and an equilibrium concentration and that the transport of ions is by either diffusion or some other concentration gradient-dependent process. Transport of ions was assumed to be slowed by the accumulation of mineral in the matrix along the transport path. The model also mimics bone apposition, slowing of apposition during refilling, and mineralization lag time. It was found that simple diffusion cannot account for the transport of calcium ions into mineralizing bone, because the diffusion coefficient is two orders of magnitude too low. If a more rapid concentration gradient-driven means of transport exists, the model demonstrates that osteonal geometry and variable rate of refilling work together to produce calcification halos, as well as the primary and secondary calcification effect reported in the literature.
A mathematical model is presented for the transport and precipitation of mineral in refilling osteons. One goal of this model was to explain calcification 'halos,' in which the bone near the haversian canal is more highly mineralized than the more peripheral lamellae, which have been mineralizing longer. It was assumed that the precipitation rate of mineral is proportional to the difference between the local concentration of calcium ions and an equilibrium concentration and that the transport of ions is by either diffusion or some other concentration gradient-dependent process. Transport of ions was assumed to be slowed by the accumulation of mineral in the matrix along the transport path. ne model also mimics bone apposition, slowing of apposition during refilling, and mineralization lag time. It was found that simple diffusion cannot account for the transport of calcium ions into mineralizing bone, because the diffusion coefficient is two orders of magnitude too low. If a more rapid concentration gradient-driven means of transport exists, the model demonstrates that osteonal geometry and variable rate of refilling work together to produce calcification halos, as well as the primary and secondary calcification effect reported in the literature.
In the present study, we selected solutes to be added to the CrCoNi medium-entropy alloy (MEA) based on the mismatch of self-diffusion activation energy (SDQ) between the alloying elements and constituent elements of the matrix, and then investigated their grain growth behavior and mechanical properties. Mo and Al were selected as the solutes for investigation primarily because they have higher and lower SDQ, respectively, than those of the matrix elements; a secondary factor was their higher and lower shear modulus. Their concentrations were fixed at 3 at.% each because previous work had shown these compositions to be single-phase solid solutions with the face-centered cubic structure. Three alloys were produced by arc melting, casting, homogenizing, cold rolling and annealing at various temperatures and times to produce samples with different grain sizes. They were (a) the base alloy CrCoNi, (b) the base alloy plus 3 at.% Mo, and (c) the base alloy plus 3 at.% Al. The activation energies for grain growth of the CrCoNi, CrCoNi-3Mo and CrCoNi-3Al MEAs were found to be ~251, ~368 and ~219 kJ/mol, respectively, consistent with the notion that elements with higher SDQ (in this study Mo) retard grain growth (likely by a solute-drag effect), whereas those with lower values (Al) accelerate grain growth. The room-temperature tensile properties show that Mo increases the yield strength by ~40% but Al addition has a smaller strengthening effect consistent with their relative shear moduli. The yield strength as a function of grain size for the three singlephase MEAs follows the classical Hall-Petch relationship with much higher slopes (> 600 MPa μm -0.5 ) than traditional solid solutions. Furthermore, this work shows that the grain growth kinetics and solid solution strengthening of the CrCoNi MEA can be tuned by selecting solute elements that have appropriate diffusion and physical properties.
Radiance matrix algebraic methods enable efficient annual daylight simulation while preserving accuracy. The five sub-methods, 2 to 6 phase methods, enable scene components parameterization and separation of direct and diffuse flux transfer based on the user's need. However, the burden is on the user to figure out the which method, matrix basis, matrix resolution, simulation parameters to use to achieve the desired efficiency and accuracy to the end application. Several utility programs and an executive program (in-progress) were created to lower the entry barrier and to reduce human error when executing the simulation. This suite of programs should also reduce the burden of adopting Radiance matrix methods for third party software.
Internal structure study at an atomic level is a challenging task with far reaching consequences to its material properties, specifically in the field of transition metal doping in quantum dots. Diffusion of transition metal ions in and out of quantum dots forming magnetic clusters has been a major bottleneck in this class of materials. Diffusion of the magnetic ions from the core into the nonmagnetic shell in a core/shell heterostructure architecture to attain uniform doping has been recently introduced and yet to be understood. In this work, we have studied the local structure variation of Fe as a function of CdS matrix thickness and annealing time during the overcoating of Fe 3 O 4 core with CdS using X-ray absorption spectroscopy. The data reveals that Fe 3 O 4 core initially forms a core/shell structure with CdS followed by alloying at the interface eventually completely diffusing all the way through the CdS matrix to form homogeneously Fe-doped CdS QDs with excellent control over size and size distribution. Study of Fe K-edge shows a complete change of Fe local environment from Fe–O to FeS.
Out-of-time ordered (OTO) correlation functions describe scrambling of information in correlated quantum matter. They are of particular interest in incoherent quantum systems lacking well defined quasi-particles. Thus far, it is largely elusive how OTO correlators spread in incoherent systems with diffusive transport governed by a few globally conserved quantities. Here, we study the dynamical response of such a system using high-performance matrix-product-operator techniques. Specifically, we consider the non-integrable, one-dimensional Bose–Hubbard model in the incoherent high-temperature regime. Our system exhibits diffusive dynamics in time-ordered correlators of globally conserved quantities, whereas OTO correlators display a ballistic, light-cone spreading of quantum information. The slowest process in the global thermalization of the system is thus diffusive, yet information spreading is not inhibited by such slow dynamics. We furthermore develop an experimentally feasible protocol to overcome some challenges faced by existing proposals and to probe time-ordered and OTO correlation functions. As a result, our study opens new avenues for both the theoretical and experimental exploration of thermalization and information scrambling dynamics.
The kinetics of octahedral tilt transitions in the lead-free relaxor material sodium bismuth titanate Na{sub 1/2}Bi{sub 1/2}TiO{sub 3} (NBT) is investigated by electronic structure calculations within density functional theory. Energy barriers for transitions between tetragonal, rhombohedral and orthorhombic tilts in cation configurations with [001]- and [111]-order on the A-sites are determined by nudged elastic band calculations. By tilting entire layers of octahedra simultaneously we find that the activation energy is lower for structures with 001-order compared to such with 111-order. The energetic coupling between differently tilted layers is, however, negligibly small. By introducing a single octahedral defect we create local tilt disorder and find that the deformation energy of the neighboring octahedra is less in a rhombohedral than in a tetragonal structure. By successively increasing the size of clusters of orthorhombic defects in a rhombohedral matrix with 001-order, we determine a critical cluster size of about 40 Å . Thus groups of about ten octahedra can be considered as nuclei for polar nanoregions, which are the cause of the experimentally observed relaxor behavior of NBT. - Graphical abstract: Nine orthorhombic oxygen octahedral tilt defects in a rhombohedral tilt configuration. - Highlights: • Chemical order influences energy barriers of octahedral tilt transitions. • The octahedral deformation energy is lower in rhombohedral phases. • Tilt defect clusters are more likely in rhombohedral structures. • Tilt defect clusters can act as nuclei for polar nanoregions.
Highlights: • Cu- and Zn-doped Fe{sub 2}O{sub 3} nanoparticles were successfully obtained by a simple solvothermal method. • The sizes and morphologies of the doped Fe{sub 2}O{sub 3} nanoparticles could be regulated by doping with divalent cations. • The doped Fe{sub 2}O{sub 3} nanoparticles showed enhanced remanent magnetization and coercivity. • The doped Fe{sub 2}O{sub 3} nanoparticles showed excellent catalytic activity toward thermal decomposition of ammonium perchlorate. • The enhanced catalytic activity could be attributed to the defect structure induced by doping with divalent cations. - Abstract: To assess the relationship between metal ion-mediated microstructures and the macro-performance, Cu- and Zn-doped α-Fe{sub 2}O{sub 3} nanoparticles were prepared via a solvothermal method. The morphologies of the as-synthesized nanoparticles were investigated by scanning electron microscopy and transmission electron microscopy. The results revealed that the sizes and morphologies could be regulated by doping with divalent cations. The structures of the as-synthesized nanoparticles were characterized by X-ray diffraction and Raman spectroscopy, indicating that Cu{sup 2+} and Zn{sup 2+} ions had diffused into the lattice of α-Fe{sub 2}O{sub 3} matrix. The magnetization behaviors of these nanoparticles were measured to analyze the effect of doping on α-Fe{sub 2}O{sub 3}. Furthermore, the catalytic activities of Cu- and Zn-doped α-Fe{sub 2}O{sub 3} nanoparticles demonstrated that the high-temperature decomposition temperature of ammonium perchlorate could be lowered by 115 °C and 107 °C, respectively, compared to that of ammonium perchlorate without catalyst. The enhanced catalytic activity could be attributed to the defect structure induced by doping with divalent cations.
Abstract Understanding the underlying processes of biomineralization is crucial to a range of disciplines allowing us to quantify the effects of climate change on marine organisms, decipher the details of paleoclimate records and advance the development of biomimetic materials. Many biological minerals form via intermediate amorphous phases, which are hard to characterize due to their transient nature and a lack of long-range order. Here, using Monte Carlo simulations constrained by X-ray and neutron scattering data together with model building, we demonstrate a method for determining the structure of these intermediates with a study of amorphous calcium carbonate (ACC) which is a precursor in the bio-formation of crystalline calcium carbonates. We find that ACC consists of highly ordered anhydrous nano-domains of approx. 2 nm that can be described as nanocrystalline. These nano-domains are held together by an interstitial net-like matrix of water molecules which generate, on the mesoscale, a heterogeneous and gel-like structure of ACC. We probed the structural stability and dynamics of our model on the nanosecond timescale by molecular dynamics simulations. These simulations revealed a gel-like and glassy nature of ACC due to the water molecules and carbonate ions in the interstitial matrix featuring pronounced orientational and translational flexibility. This allows for viscous mobility with diffusion constants four to five orders of magnitude lower than those observed in solutions. Small and ultra-small angle neutron scattering indicates a hierarchically-ordered organization of ACC across length scales that allow us, based on our nano-domain model, to build a comprehensive picture of ACC formation by cluster assembly from solution. This contribution provides a new atomic-scale understanding of ACC and provides a framework for the general exploration of biomineralization and biomimetic processes.
Superdiffusive transport with dynamical exponent z=3/2 has been firmly established at finite temperature for a class of integrable systems with a non-Abelian global symmetry G. On the inclusion of integrability-breaking perturbations, diffusive transport with z=2 is generically expected to hold in the limit of late time. Recent studies of the classical Haldane-Ishimori-Skylanin model have found that perturbations that preserve the global symmetry lead to a much slower time scale for the onset of diffusion, albeit with uncertainty over the exact scaling exponent. That is, for perturbations of strength λ, the characteristic timescale for diffusion goes as t*∼λ−α for some α. Using large-scale matrix product state simulations, we investigate this behavior for perturbations to the canonical quantum model showing superdiffusion: the S=1/2 quantum Heisenberg chain. We consider a ladder configuration and look at various perturbations that either break or preserve the SU(2) symmetry, leading to scaling exponents consistent with those observed in one classical study [McCarthy , Phys. Rev. B 110, L180301 (2024)2469-995010.1103/PhysRevB.110.L180301]: α=2 for symmetry-breaking terms and α=6 for symmetry-preserving terms. We also consider perturbations from another integrable point of the ladder model with G=SU(4) and find consistent results. Finally, we consider a generalization to an SU(3) ladder and find that the α=6 scaling appears to be universal across superdiffusive systems when the perturbations preserve the non-Abelian symmetry G.