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At least 613 records · Page 34

A conserved chaperone protein is required for the formation of a noncanonical type VI secretion system spike tip complex

Type VI secretion systems (T6SSs) are dynamic protein nanomachines found in Gram-negative bacteria that deliver toxic effector proteins into target cells in a contact-dependent manner. Prior to secretion, many T6SS effector proteins require chaperones and/or accessory proteins for proper loading onto the structural components of the T6SS apparatus. However, despite their established importance, the precise molecular function of several T6SS accessory protein families remains unclear. In this study, we set out to characterize the DUF2169 family of T6SS accessory proteins. Using gene co-occurrence analyses, we find that DUF2169-encoding genes strictly co-occur with genes encoding T6SS spike complexes formed by valine-glycine repeat protein G (VgrG) and DUF4150 domains. Although structurally similar to Pro-Ala-Ala-Arg (PAAR) domains, “PAAR-like” DUF4150 domains lack PAAR motifs and instead contain a conserved PIPY motif, leading us to designate them PIPY domains. Next, we present both genetic and biochemical evidence that PIPY domains require a cognate DUF2169 protein to form a functional T6SS spike complex with VgrG. This contrasts with canonical PAAR proteins, which bind VgrG on their own to form functional spike complexes. By solving the first crystal structure of a DUF2169 protein, we show that this T6SS accessory protein adopts a novel protein fold. Furthermore, biophysical and structural modeling data suggest that DUF2169 contains a dynamic loop that physically interacts with a hydrophobic patch on the surface of its cognate PIPY domain. Based on these findings, we propose a model whereby DUF2169 proteins function as molecular chaperones that maintain VgrG–PIPY spike complexes in a secretion-competent state prior to their export by the T6SS apparatus.

DUF2169↗

Evidence for redispersion of Ni on LaMnO 3 films following high-temperature oxidation

LaMnO 3 films, 0.5-nm thick, were deposited by atomic layer deposition (ALD) onto γ-Al 2 O 3 that had been modified with 15-wt% CaO. The CaO was shown to be effective in preventing formation of LaAlO 3 that formed when La 2 O 3 was deposited directly onto γ-Al 2 O 3 . Lattice fringes on the resulting CaAl 2 O 4 /γ-Al 2 O 3 substrate were weakly resolved, allowing a detailed characterization of the LaMnO 3 films. High-resolution transmission electron microscopy (HR-TEM) images showed that the LaMnO 3 formed two-dimensional crystallites, ~10 to 15 nm wide, that covered most of the surface. Crystallites with (001) and (111) orientation were clearly identified. High-temperature oxidation caused Ni to spread over the LaMnO 3 film, suggesting there is a reaction of the Ni 2+ cations with the perovskite lattice. Ni formed by high-temperature reduction on these films remained well dispersed and significantly more active for CO 2 reforming of CH 4 compared to Ni on MgAl 2 O 4 , even after repeated oxidation and reduction cycles at 1073 K. Finally, the implications of these results for understanding metal-support interactions between Ni and LaMnO 3 are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analyzing the co-evolution of green technology diffusion and consumers’ pro-environmental attitudes: An agent-based model

Massive diffusion of green technologies is significant for building a cleaner world. However, the process of technology diffusion is usually slow and complex. An in-depth understanding of the mechanism regarding green technology diffusion is an essential precondition for effectively stimulating this process. Green technology diffusion heavily involves both social and technological changes. Although existing studies have provided rich knowledge about identifying critical drivers and barriers affecting green technology diffusion, research that considers consumers’ pro-environmental attitudes and green technology diffusion as an evolving system is still sparse. Aiming at exploring the co-evolution of consumers’ pro-environmental attitudes and green technology diffusion, this paper builds an agent-based model that integrates the relative agreement model with technology diffusion theories to conduct a sequence of controlled numerical experiments, which progressively unveil how attitudinal and technological factors impact green technology diffusion. The main findings include that (1) improving consumers’ pro-environmental attitudes is prominently beneficial to green technology diffusion and maturation; (2) technology maturity has very limited impact on consumers’ first-time purchases but significantly affects consumers’ satisfaction, which would further impact consumers’ repeat purchases; (3) consumers that do not support green technologies frequently emerge during the evolution of attitudes (despite the high technology maturity), which corresponds to the emergence of the anti-environmental groups observed in the real world; (4) active interactions between non-adopters enable their attitudes to converge, which results in the polarization of consumers’ attitudes.

ABM↗

Identifying and tracking bubbles and drops in simulations: A toolbox for obtaining sizes, lineages, and breakup and coalescence statistics

Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the background flow also drive the time evolution of these distributions. Accurate and robust identification and tracking algorithms for the dispersed phase are necessary to reliably measure this evolution and thereby quantify the underlying mechanisms in interface-resolving flow simulations. The identification of individual bubbles and drops traditionally relies on an algorithm used to identify connected regions. This traditional algorithm can be sensitive to the presence of spurious structures. A cost-effective refinement is proposed to maximize volume accuracy while minimizing the identification of spurious bubbles and drops. An accurate identification scheme is crucial for distinguishing bubble and drop pairs with large size ratios. The identified bubbles and drops need to be tracked in time to obtain breakup and coalescence statistics that characterize the evolution of the size distribution, including breakup and coalescence frequencies, and the probability distributions of parent and child bubble and drop sizes. An algorithm based on mass conservation is proposed to construct bubble and drop lineages using simulation snapshots that are not necessarily from consecutive time steps. These lineages are then used to detect breakup and coalescence events, and obtain the desired statistics. Accurate identification of large-size-ratio bubble and drop pairs enables accurate detection of breakup and coalescence events over a large size range. Accurate detection of successive breakup and coalescence events requires that the snapshot interval be an order of magnitude smaller than the characteristic breakup and coalescence times to capture these successive events while minimizing the identification of repeated confounding events. Together, these algorithms serve as a toolbox for detailed analysis of two-phase simulations, and enable insights into the mechanisms behind bubble and drop formation and evolution in flows of practical importance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Noise and error analysis and optimization in particle-based kinetic plasma simulations

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix C(x,y) is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy = 0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, p(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. Next, we repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. Furthermore, we show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation of crumpled sheets via alternating quasistatic and dynamic representations

In this work, we present a method for simulating the large-scale deformation and crumpling of thin, elastoplastic sheets. Motivated by the physical behavior of thin sheets during crumpling, two different formulations of the governing equations of motion are used: (1) a quasistatic formulation that effectively describes smooth deformations, and (2) a fully dynamic formulation that captures large changes in the sheet's velocity. The former is a differential-algebraic system of equations integrated implicitly in time, while the latter is a set of ordinary differential equations (ODEs) integrated explicitly. We adopt a hybrid integration scheme to adaptively alternate between the quasistatic and dynamic representations as appropriate. Further, we demonstrate the capacity of this method to effectively simulate a variety of crumpling phenomena. Finally, we show that statistical properties, notably the accumulation of creases under repeated loading, as well as the area distribution of facets, are consistent with experimental observations.

97 MATHEMATICS AND COMPUTING↗

DRIPS: A framework for dimension reduction and interpolation in parameter space

Reduced-order models are often used to describe the behavior of complex systems, whose simulation with a full model is too expensive, or to extract salient features from the full model’s output. We introduce a new model-reduction framework DRIPS (dimension reduction and interpolation in parameter space) that combines the offline local model reduction with the online parameter interpolation of reduced-order bases (ROBs). The offline step of this framework relies on dynamic mode decomposition (DMD) to build a low-rank linear surrogate model, equipped with a local ROB, for quantities of interest derived from the training data generated by repeatedly solving the (nonlinear) high-fidelity model for multiple parameter points. The online step consists of the construction of a parametric reduced-order model for each target/test point in the parameter space, with the interpolation of ROBs done on a Grassman manifold and the interpolation of reduced-order operators done on a matrix manifold. The DMD component enables DRIPS to model (typically low-dimensional) quantities of interest directly, without having to access the (typically high-dimensional and possibly nonlinear) operators in a high-fidelity model that governs the dynamics of the underlying high-dimensional state variables, as required in projection-based reduced-order modeling. A series of numerical experiments suggests that DRIPS yields a model reduction, which is computationally more efficient than the commonly used projection-based proper orthogonal decomposition; it does so without requiring a prior knowledge of the governing equation for quantities of interest. Furthermore, for the nonlinear systems considered, DRIPS is more accurate than Gaussian-process interpolation (Kriging).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bimetallic NiCo boride nanoparticles confined in a MXene network enable efficient ambient ammonia electrosynthesis

Ambient electrocatalytic nitrogen fixation is an emerging technology for green ammonia synthesis, but the absence of optimized, stable and performant catalysts can render its practical application challenging. Herein, bimetallic NiCo boride nanoparticles confined in MXene are shown to accomplish high-performance nitrogen reduction electrolysis. Taking advantage of the synergistic effect in specific compositions with unique electronic d and p orbits and typical architecture of rich nanosized particles embedded in the interconnected conductive network, the synthesized MXene@NiCoB composite demonstrates extensive improvements in nitrogen molecule chemisorption, active area exposure and charge transport. As a result, optimal NH 3 yield rate of 38.7 μg h -1 mgcat. -1 and Faradaic efficiency of 6.92% are acquired in 0.1 M Na 2 SO 4 electrolyte. Moreover, the great catalytic performance can be almost entirely maintained in the cases of repeatedly-cycled and long-term electrolysis. Theoretical investigations reveal that the nitrogen reduction reaction on MXene@NiCoB catalyst proceeds according to the distal pathway, with a distinctly-reduced energy barrier relative to the Co 2 B counterpart. In conclusion, this work may inspire a new route towards the rational catalyst design for the nitrogen reduction reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical properties of Gd(III) ions in LiCl-KCl-GdCl 3 at 723–1023 K

Electrochemical behavior of Gd(III) ions in molten LiCl-KCl-GdCl 3 was investigated at 723–1023 K via cyclic voltammetry using tungsten as a working electrode, Gd-Bi (mole fraction, x Gd = 0.16) as a reference electrode, and Gd-Bi (x Gd = 0.02) as a counter electrode. A single reduction–oxidation wave was observed, confirming a single-step, 3-electron transfer Gd(III)/Gd transition. The cathodic peak potential exhibited minimal change (<13 mV) over a wide range of scan rates (0.05–0.30 V s –1 ), indicating facile charge transfer kinetics (i.e., a reversible electrode process). A nucleation overpotential associated with solid Gd deposition was observable at low temperatures (T < 823 K). The mass transport properties of Gd(III) ions were estimated using the Berzins and Delahay relation based on diffusion-limiting peak current. The diffusivity values were determined to be D Gd(III) = 0.5–2.7 × 10 –5 cm 2 s –1 at 723–1023 K with an associated activation energy of E a = 33.9 (±1.0) kJ mol –1 . Finally, the two-phase [liquid + GdBi] Gd-Bi alloy reference electrode experienced less than 0.5 mV of drift over 5 days of repeated electrochemical measurements, indicating high stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thin film growth effects on electrical conductivity in entropy stabilized oxides

Entropy stabilization has garnered significant attention as a new approach to designing novel materials. Much of the work in this area has focused on bulk ceramic processing, leaving entropy-stabilized thin films relatively under-explored. Following an extensive multi-variable investigation of polycrystalline (Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )O thin films deposited via pulsed laser deposition (PLD), it is shown here that substrate temperature and deposition pressure have strong and repeatable effects on film texture and lattice parameter. Further analysis shows that films deposited at lower temperatures and under lower oxygen chamber pressure are 40x less electrically resistive than otherwise identical films grown at higher temperature and pressure. Annealing these films in an oxygen-rich environment increases their electrical resistivity to match that of the films grown at higher temperatures and pressures. Because of this, the electric conductivity is hypothesized to be the result of polaron hopping mediated by transition metal valence changes which compensate for oxygen off-stoichiometry.

36 MATERIALS SCIENCE↗

The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data

The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

59 BASIC BIOLOGICAL SCIENCES↗

Determining processing behaviour of pure Cu in laser powder bed fusion using direct micro-calorimetry

We report copper is challenging to process by laser powder bed fusion (LPBF) given its high reflectivity at common infrared laser diode wavelengths and high thermal conductivity. Successful deposition of copper in a predictable and repeatable fashion relies on understanding the development of the keyhole melting regime, as well as heating, melting, boiling and vapour formation behaviour when interacting with a laser beam within an LPBF environment. In this study, in situ optical absorptivity measurements are used to clarify the complex physics of the laser material interaction. Absorptivity of laser energy is measured using direct micro-calorimetry and compared to melt pool depth in correlation to processing parameters. The measured absorptivity for a 100 μm layer thickness of powder was found to be approximately four times higher than that of the bare polished discs. It was also shown that high laser power above 500 W and scan speed up to 150 mm/s are appropriate for effective melting of the powder layer, with these parameters overcoming the threshold required to achieve keyhole melting. This is explained by multiple reflections withing the powder particles and the lower thermal conductivity of packed powder in comparison to bare discs. Melt pool formation was found to be highly unstable and an explosive behavior was observed when in the keyhole regime, caused by high fluctuations in absorptivity values. This work demonstrates calorimetry can be used to monitor melting behaviour in a real-time fashion during processing for this challenging to process material, thereby avoiding unnecessary parametric optimisation. In addition, the parametric window for optimum processing revealed here can inform future work.

36 MATERIALS SCIENCE↗

Enhanced biomechanical performance of additively manufactured Ti-6Al-4V bone plates

As the global trauma fixation devices market expands rapidly, it is imperative to improve the production of fixation devices through enhanced design accuracy and fit for best performance and maximum patient comfort. Selective laser melting (SLM) is one of the mature additive manufacturing methods, which provides a viable route for the rapid production of such devices. In this work, the ability of SLM to produce near-net-shape parts, as desired for medical implants, was utilized for the fabrication of bone plates from Ti-6Al-4V alloy powder. Martensitic microstructure obtained after the printing of alloy resulted in poor ductility, limiting its application in the field of orthopedics. A specially designed repeated cyclic heating and cooling close to but below the β-transus was used to transform from acicular to a bimodal microstructure without the need for plastic deformation prior to heat treatment for improving the ductility. Bone plates subjected to this heat treatment were mechanically tested by means of tensile and 3-point bend tests and demonstrated large improvement in ductility, and the values were comparable to those similar plates prepared from wrought alloy. Other important properties required for implants were assessed, such as corrosion resistance in simulated body fluid and cytocompatibility in vitro using MC3T3-E1 cells. These results for the bone plate after heat treatment were excellent and similar to those of the additively manufactured and wrought plates. Taken together, the performance of the additively manufactured bone plates after subjecting to heat treatment was similar to those of bone plate manufactured using wrought alloy. These results have important implications for the fabrication of patient-specific metallic orthopedic devices using SLM without compromising their biomechanical performance by subjecting them to a tailored heat treatment.

36 MATERIALS SCIENCE↗

Disorder-induced time effect in the antiferromagnetic domain state of Fe 1+ y Te

Herein we report on temperature-dependent soft X-ray absorption spectroscopy (XAS) measurements utilizing linearly polarized synchrotron radiation to probe magnetic phase transitions in iron-rich Fe 1+y Te (y ≈ 0.12). X-ray magnetic linear dichroism (XMLD) signals, which sense magnetic ordering processes at surfaces, start to increase monotonically below the Néel temperature T N = 57 K. This increase is due to a progressive bicollinear antiferromagnetic (AFM) alignment of Fe spins of the monoclinic Fe 1+y Te parent phase. This AFM alignment was achieved by a [1 0 0]-oriented biasing field favoring a single-domain state during cooling across T N . Our specific heat and magnetization measurements confirm the bulk character of this AFM phase transition. On longer time scales, however, we observe that the field-biased AFM state is highly unstable even at the lowest temperature of T = 3 K. After switching off the biasing field, the XMLD signal decays exponentially with a time constant τ = 1506 s. The initial XMLD signal is restored only upon repeating a cycle consisting of heating and field-cooling through T N . We explain the time effect by a gradual formation of a multi-domain state with 90° rotated AFM domains, promoted by structural disorder, facilitating the motion of twin-domains. Significant disorder in our Fe 1+y Te sample is evident from our X-ray diffraction and specific heat data. The stability of magnetic phases in Fe-chalcogenides is an important material property, since the Fe(Te 1-x Se x ) phase diagram shows magnetism intimately connected with superconductivity.

36 MATERIALS SCIENCE↗

Observation of skyrmion bubbles in multilayer [Pt/Co/Cu] n using spin-polarized STM

Magnetic multilayers are a promising platform for storage and logic devices based on skyrmion spin textures, due to the large materials phase space for tuning properties. Epitaxial superlattice structures of [Pt/Co/Cu]n thin films were grown by molecular beam epitaxy at room temperature. Spin-polarized scanning tunneling microscopy (SP-STM) of these samples was used to probe the connection between surface structure and skyrmion morphology with nanoscale spatial resolution. Irregular-shaped skyrmion bubbles were observed, with effective diameters from 20 to 200 nm that are much larger than the nanoscale grain structure of the surface topography. Nucleation, annihilation, and motion of skyrmion bubbles could be driven using the stray field of the ferromagnetic tip in repeated imaging, and spin-polarized current/voltage pulses. Furthermore, our detailed comparison of STM topography and differential conductance images shows that there are no surface defects or inhomogeneities at length scales that could account for the range in skyrmion bubble size or shape observed in the measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Learning macroscopic internal variables and history dependence from microscopic models

This paper concerns the study of history dependent phenomena in heterogeneous materials in a two-scale setting where the material is specified at a fine microscopic scale of heterogeneities that is much smaller than the coarse macroscopic scale of application. Here, we specifically study a polycrystalline medium where each grain is governed by crystal plasticity while the solid is subjected to macroscopic dynamic loads. The theory of homogenization allows us to solve the macroscale problem directly with a constitutive relation that is defined implicitly by the solution of the microscale problem. However, the homogenization leads to a highly complex history dependence at the macroscale, one that can be quite different from that at the microscale. In this paper, we examine the use of machine-learning, and especially deep neural networks, to harness data generated by repeatedly solving the finer scale model to: (i) gain insights into the history dependence and the macroscopic internal variables that govern the overall response; and (ii) to create a computationally efficient surrogate of its solution operator, that can directly be used at the coarser scale with no further modeling. We do so by introducing a recurrent neural operator (RNO), and show that: (i) the architecture and the learned internal variables can provide insight into the physics of the macroscopic problem; and (ii) that the RNO can provide multiscale, specifically FE 2 , accuracy at a cost comparable to a conventional empirical constitutive relation.

36 MATERIALS SCIENCE↗

Crystal plasticity modeling for the strengthening effect of multilayered copper–graphene nanocomposites

The paper explores plastic deformation mechanisms in metal–graphene nanocomposites, illustrating their material strengthening effects through a crystal plasticity finite element (CPFE) model. This model is compared with published experimental results, which have previously shown that the two-dimensional shape of graphene effectively controls dislocation motion and significantly enhances the strength of metals. Simulated nanopillar compression tests, using a physics-based CP model that incorporates surface nucleation and single-arm source dislocation mechanisms, help us understand dislocation motions at submicron length scales. The crystal plasticity models are applied to nanolayered composites with copper grain layers and monolayer graphene, featuring repeat layer spacings of 200 nm, 125 nm, and 70 nm, respectively. This study quantifies the accumulation of dislocations at the graphene interfaces, contributing to the ultra-high strength of copper–graphene composites. Furthermore, a Hall–Petch-like correlation is established between yield strength and the number of embedded graphene layers.

36 MATERIALS SCIENCE↗

Evolution of {delta}ferrite in a CF3 cast stainless steel upon neutron irradiation to 3, 5, 10, 20, and 40 dpa

The microstructural evolution of delta ferrite in a CF3 cast stainless steel irradiated to 3, 5, 10, 20, and 40 dpa with two dose rates was studied with atom probe tomography (APT) and transmission electron mi-croscopy. Spinodal decomposition and G-phase precipitates induced by neutron irradiation and thermal aging were quantified systematically. The neutron irradiation significantly enhances the spinodal decom-position in delta ferrite as both the spinodal wavelength (i.e. a characteristic repeat distance) and am-plitude (i.e. magnitude of elemental concentration fluctuation) increase after irradiation. The wavelength only varies slightly when the dose increases from 5 to 40 dpa, while the amplitude increases dramatically from 10 to 20 dpa and starts to saturate before 20 dpa. The dose rate and irradiation temperature also have a notable effect on the spinodal wavelength and amplitude. The study shows that higher dose rate promotes a larger wavelength at given irradiation doses. Regarding the G-phase precipitates, a slightly lower irradiation temperature would result in a smaller mean size of G-phase precipitates, while a lower irradiation dose rate would lead to a larger G-phase precipitates at a given temperature and dose. Over-all, the spinodal decomposition and G-phase precipitates in the delta ferrite continue to evolve with the increasing dose beyond 10 dpa. This study confirms that the formation of G-phase precipitates at the in-terdomain region between alpha and alpha-prime is facilitated by the Si and Mo atoms rejected from Fe rich alpha phase and the Ni and Mn atoms rejected from Cr rich alpha-prime phase. Neutron irradiation plays a dominant role in the ferrite instability, and the effect of prior thermal aging at 400 degrees C for 10,000 hours is negligible as the dose is 3 dpa and above.

duplex stainless steel↗