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At least 775 records · Page 43

Advanced thermal/environmental barrier coatings of high-entropy rare earth disilicates tuned by strong anharmonicity of Eu 2 Si 2 O 7

Advancing thermal/environmental barrier coating (TEBC) materials with integrated thermal-mechanical functions is paramount for safeguarding SiC-based ceramic matrix composites (CMCs) in high-efficiency gas turbines. Herein, we employ a synergistic approach, combining density functional theory (DFT) methods and combinatorial chemistry techniques, to design high-performance and low-cost RE 2 Si 2 O 7 (RE = rare earth elements) TEBC materials tailored for enhanced compatibility with SiC-based CMCs. Expanding on phase stability of alloying pure RE 2 Si 2 O 7 , the investigation extends to the mechanical and thermal properties of solid solution systems, including Er 1/2 Y 3/4 Yb 3/4 Si 2 O 7 , Gd 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 , and Eu 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 . The solid solution systems exhibit a major reduction in lattice thermal conductivity relative to their pure counterparts, achieving ultralow values of 0.25 to 0.39 W m −1 K −1 at 1500 K. Furthermore, the coefficients of thermal expansion (CTE) of these solid solutions are precisely tuned within the desired range for SiC (4.4 to 5.5 × 10 −6 K −1 ), while maintaining good mechanical properties. Here, in particular, the addition of Eu 2 Si 2 O 7 demonstrates to be an important variable to the tuning of CTE and lattice thermal conductivity by leveraging its strong anharmonicity, presenting a pioneering avenue for fine-tuning material properties. In summary, this research not only identifies promising TEBC materials with superior thermal properties, but also introduces a valuable computational material design methodology for the rapid discovery of complex materials for harsh environments.

36 MATERIALS SCIENCE↗

The impact and mitigation of broad-absorption-line quasars in Lyman α forest correlations

ABSTRACT Correlations in and with the flux transmission of the Lyman α (Ly α) forest in the spectra of high-redshift quasars are powerful cosmological tools, yet these measurements can be compromised if the intrinsic quasar continuum is significantly uncertain. One particularly problematic case is broad-absorption-line (BAL) quasars, which exhibit blueshifted absorption associated with many spectral features that are consistent with outflows of up to ∼0.1c. As these absorption features can both fall in the forest region and be difficult to distinguish from Ly α absorption, cosmological analyses eliminate the ∼12–16 per cent of quasars that exhibit BALs. In this paper, we explore an alternate approach that includes BALs in the Ly α autocorrelation function, with the exception of the expected locations of the BAL absorption troughs. This procedure returns over 95 per cent of the path-length that is lost by the exclusion of BALs, as well as increasing the density of sightlines. We show that including BAL quasars reduces the fractional uncertainty in the covariance matrix and correlation function by 12 per cent and does not significantly change the shape of the correlation function relative to analyses that exclude BAL quasars. We also evaluate different definitions of BALs, masking strategies, and potential differences in the quasar continuum in the forest region for BALs with different amounts of absorption.

79 ASTRONOMY AND ASTROPHYSICS↗

Size-dependent attraction of Cu solutes to clusters formed at Ag grain boundaries

We report a size-dependent solute clustering mechanism at grain boundaries in a sputtered ultrafine-grained Ag-Cu alloy, where large Cu clusters form despite weak individual solute-solute interactions. X-ray diffraction confirms limited Cu solubility in the Ag matrix, while scanning transmission electron microscopy reveals Cu clustering at both ordinary GBs and GB junctions. Density functional theory calculations show that 12-atom Cu clusters are energetically preferred, while smaller three-atom clusters are significantly less stable. Additional calculations demonstrate a marked increase in solute-cluster attraction energy with cluster size. As a result, these findings point to a previously unrecognized pathway for grain-boundary solute clustering in immiscible systems, driven by collective solute-cluster interactions, with implications for segregation behavior and stability in nanocrystalline and ultrafine-grained alloys.

Alloys↗

Ab Initio Design of High-Entropy Thermal/ Environmental Barrier Coatings

Next generation thermal/environmental barrier coatings (TEBC) require carefully balancing various properties including phase stability, thermal conductivity, coefficient of thermal expansion (CTE), mechanical properties, and resistance against hot corrosion and water vapor recession. This work mainly focuses on rapid design of cost-effective high entropy rare-earth disilicates and aluminum garnets to protect SiC-based ceramic matrix composites and nickel-based superalloys in the hot section of gas turbine engines using density functional theory methods. Our calculations identify several low-cost high entropy TEBC exhibiting ultralow thermal conductivity at 1500 K and desirable CTE while maintaining good mechanical properties, including Er1/2Y3/4Yb3/4Si2O7, Gd1/4Er1/4Y3/4Yb3/4Si2O7, Eu1/4Er1/4Y3/4Yb3/4Si2O7, and (Y1/4Gd1/4Er1/4Yb1/4)3Al5O12. This work also aims to gain fundamental understanding of oxygen diffusion in model disilicates. Minimizing oxidizer (such as water vapor and oxygen) permeability through the EBC layer can significantly decrease the growth rate of thermally grown oxide and extend the service life of the coating system. Oxygen diffusion mechanisms including formation energy of defects under varying oxygen conditions and defect migration energy barriers will be presented.

coefficient of thermal expansion↗

Single-Molecule Kinetics of Styrene Hydrogenation on Silica-Supported Vanadium: The Role of Disorder for Single-Atom Catalysts

We report a theoretical approach for the study of supported atom catalysis is developed based on recent advances in the study of single-molecule kinetics. This view is particularly useful in exhibiting the role of disorder in single-atom and single-site catalysts on amorphous supports. The distribution of passage times (or waiting times) through a complex catalytic network originating from a set of coupled active sites is described by a probability distribution function (PDF), f(t), that reflects the local environment of the reaction center. An efficient algorithm is developed based on the linear algebra of the Markov transition matrix that produces f(t) or its moments. The kinetics of the hydrogenation reaction of styrene on an organovanadium(III) catalyst supported on amorphous silica is studied. A kinetic model consisting of three intertwined catalytic cycles emanating from three chemically distinct active sites is proposed to describe the chemistry. Density functional theory (DFT) calculations are employed to determine the free energy barriers of the reactions, which are used to construct the rate coefficient matrix. The disorder induced by the amorphous support material is divided into a low-dimensional short-range component reflecting the covalent structures near the reaction center and a weaker long-range component modeling the bulk randomness. The results are computed and analyzed for a wide range of concentration values and disorder scenarios. The unusual structure in the f(t) PDF is found to occur for certain cases that reveal the contribution of multiple catalytic pathways acting in concert.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flow Channeling in Fracture Networks: Characterizing the Effect of Density on Preferential Flow Path Formation

Flow channelization is a commonly observed phenomenon in fractured subsurface media where the flow of fluids is restricted primarily to highly transmissive fracture networks surrounded by a low-permeability rock matrix. The multiscale structural heterogeneity of these networks results in multiscale flow channelization where preferential flow paths form at length scales ranging from the entire system down to the subfracture size. We present an analysis of how one of the largest scales in fractured media, the network density, influences the degree of flow channeling that occurs using an ensemble of semigeneric three-dimensional discrete fracture network (DFN) simulations. We construct 10 DFNs, whose fracture lengths follow a power law distribution, at four densities for a total of 40 networks. We characterize their structure in terms of the network topology and geometry. Eulerian and Lagrangian observations of the steady-state flow fields obtained within the networks are used to quantify the degree of flow channelization at the network scale. We introduce a measure for the importance-ranking/hierarchy of different flow paths in the network using graph-based analysis of Lagrangian transport by which the degree of flow channeling between networks is compared. These flow observations are then linked to the structural properties of the networks. In general, network-scale flow channeling decreases as the network density increases. However, at low densities, there is more uniform flow within the entire connected network than in high-density networks. We also demonstrate how standard transport observables can be used to infer the degree of flow channelization occurring within a fracture network.

58 GEOSCIENCES↗

A Physically-Based Model for Thermo-Oxidative and Hydrolytic Aging of Elastomers

A computationally efficient model is proposed to capture the loss of mechanical performance due to chemical aging that are formed as the competition of chain scission and cross-link formation/dissolution, such as thermo-oxidative aging or hydrolytic aging. The model should be considered an extension of our recent models [1, 2, 3] which further simplifies the matrix behavior based on the assumption of independence of environmental and mechanical damage. The model uses this assumption to reduce the necessary material parameters needed to model constitutive and inelastic behavior of elastomers during aging. To this end, the model can provide accurate predictions of the material performance with the significantly fewer number of fitting parameters. The model is relevant for all decay mechanisms formed by the occurrence of two simultaneous micro-mechanisms; (i) formation/reduction of the cross-links, and (ii) chain scission, both of which are present in thermo-oxidation and hydrolytic aging. Assuming the alteration of the chain density along the aging trajectory is identical to the peroxide cross-link density for thermo-oxidation, and the change of the average molecular weight for hydrolysis, the strain energy of polymer matrix can be rewritten as a function of deformation, deformation history, storage time and aging temperature. Next, the modified network alteration model is formulated for implementation into Finite Element (FE) simulations. The model is built on the presumption of homogeneous and consistent oxygen/water absorption and thus is mainly relevant for relatively thin samples exposed to environmental loads for a long time. The proposed model includes only six physically inspired material parameters. Therefore, while it is computationally efficient, it shows good agreement with own experimental data, which performed on various range of accelerated aging temperatures and times. With respect to its computational efficiency, simplicity, accuracy, and interpret-ability, the model is the right choice for advanced implementations in FE programs.

42 ENGINEERING↗

Investigation of 3D printed lightweight hybrid composites via theoretical modeling and machine learning

Hybrid composites combine two or more different fillers to achieve multifunctional or advanced material properties, such as lightweight and enhanced mechanical properties. The properties of the composites significantly depend on their microstructures, which can be tailored via advanced 3D printing processes. Understanding the process-structure-property relationships is critical to enable the design and engineering of novel hybrid composites for applications in aerospace, automotive, and protective coatings. Here, for this work, we develop 3D printable and lightweight hybrid composites and leverage the conventional design of experiments, a theoretical hybrid model, and an image-driven machine learning (ML) method to investigate their mechanical behaviors. The hybrid composites are formulated with elastomer matrix, microfillers, and thin-shell particles, enabling a significant degree of design freedom of microstructures with densities and mechanical properties varying up to 70% and 91%, respectively. Our statistical analysis indicates that the 3D printing path direction and the microfibers fraction are dominating process parameters with contribution percentages of 45.3% and 57.7% on the specific stiffness and strength, respectively. A hybrid mechanics model is developed based on a simple Weibull distribution function and classical single-filler models to effectively capture the variations in mechanical properties, however, it overestimates the values due to its statistical constraints and idealization of experimental uncertainty. The image-driven ML model leverages the microscale images directly without losing the structural details, shows more accurate predictions with experimental data, and has 48.6% lower root mean square error than the theoretical model.

3D printing↗

Investigation of crossed-twin structure formation in magnesium and magnesium alloys

In this work, the effect of alloying addition on the propensity for twin-twin interactions to transform into crossed-twin structures in magnesium alloys is investigated. A full-field elasto-viscoplastic fast Fourier transform (EVP-FFT) framework combined with a discrete twin model and dislocation density-based hardening law for slip strengths is used to calculate the micromechanical fields in the crystalline matrix around the interacting twins. AZ31 and MgLi alloys are selected along with pure Mg to study the influence of plastic anisotropy in connection with alloying elements. These alloys were selected since their plastic anisotropy measure, which is defined as the ratio between the critical resolved shear stress for pyramidal $\langle$c +a$\rangle$ and basal $\langle$a$\rangle$ slip modes, spanned a wide range. To quantify the role of twin thicknesses, we probe a range of impinging twin thicknesses while fixing the recipient twin thickness. The analysis reveals that: (i) the local driving stress for crossed twin structure formation generated from the interaction of the two twins is lower in a low plastically anisotropic material, like a MgLi alloy, than a high plastically anisotropic material like pure Mg and (ii) the critical impinging twin thickness needed to form the crossed twin structure in pure Mg, AZ31 and MgLi alloys is ~0.5, ~0.75 and ~1.5 times the recipient twin thickness. We propose a relationship between the tendency for crossed twin structure formation and the experimentally observed higher ductility in MgLi alloys compared to pure Mg. Finally, one key implication of the findings is that crossed- twin structure formation can be hindered and the ductility of magnesium alloy thereby improved by properly choosing alloying elements that lower the slip strength for pyramidal $\langle$c + a$\rangle$ slip.

36 MATERIALS SCIENCE↗

Designing high-performance superconductors with nanoparticle inclusions: Comparisons to strong pinning theory

One of the most promising routes for achieving high critical currents in superconductors is to incorporate dispersed, non-superconducting nanoparticles to control the dissipative motion of vortices. However, these inclusions reduce the overall superconducting volume and can strain the interlaying superconducting matrix, which can detrimentally reduce T c . Consequently, an optimal balance must be achieved between the nanoparticle density n p and size d. Determining this balance requires garnering a better understanding of vortex–nanoparticle interactions, described by strong pinning theory. Here, we map the dependence of the critical current on nanoparticle size and density in (Y 0.77 , Gd 0.23 )Ba 2 Cu 3 O 7-δ films in magnetic fields of up to 35 T and compare the trends to recent results from time-dependent Ginzburg–Landau simulations. We identify consistency between the field-dependent critical current J c (B) and expectations from strong pinning theory. Specifically, we find that J c ∝ B -α , where α decreases from 0.66 to 0.2 with increasing density of nanoparticles and increases roughly linearly with nanoparticle size d/ξ (normalized to the coherence length). At high fields, the critical current decays faster (~B -1 ), suggesting that each nanoparticle has captured a vortex. When nanoparticles capture more than one vortex, a small, high-field peak is expected in J c (B). Due to a spread in defect sizes, this novel peak effect remains unresolved here. Finally, we reveal that the dependence of the vortex creep rate S on nanoparticle size and density roughly mirrors that of α, and we compare our results to low-T nonlinearities in S(T) that are predicted by strong pinning theory.

36 MATERIALS SCIENCE↗

A Review of the Influence of Processing Parameters on ODS Steels Produced via Additive Manufacturing Techniques

Abstract This paper reviews current observations regarding processing conditions for oxide dispersion-strengthened steels consolidated through additive manufacturing techniques. Variations in ODS steels observed across process parameters include changes in grain size, grain texture, oxide size, density of oxides, porosity, melt pool characteristics, and mechanical properties. These properties were then compared across techniques to understand which techniques and processing conditions lead to the highest strength, ductility, and oxide density. Current literature suggests that a mix of grain types, in the form of either morphology or phase, can significantly increase the strength of printed ODS steels. Meanwhile, the most ductile samples, regardless of consolidation technique or matrix material, were made from feedstock with oxide additions located on the powder surface. Reported grain and oxide sizes were plotted against the ratio of laser power to scan speed, volumetric energy density, and normalized enthalpy. No strong correlation between these values and microstructural features was observed. The plots that were made suggest that a larger data set, more in-depth representative equations, and more defined material properties as a function of specific feedstock used are necessary to determine a value that can be correlated to the printed ODS steel microstructure.

deJong, Matthew↗

A Novel NASICON‐Type Na 4 MnCr(PO 4 ) 3 Demonstrating the Energy Density Record of Phosphate Cathodes for Sodium‐Ion Batteries

Abstract Sodium‐ion batteries (SIBs) have attracted incremental attention as a promising candidate for grid‐scale energy‐storage applications. To meet practical requirements, searching for new cathode materials with high energy density is of great importance. Herein, a novel Na superionic conductor (NASICON)‐type Na 4 MnCr(PO 4 ) 3 is developed as a high‐energy cathode for SIBs. The Na 4 MnCr(PO 4 ) 3 nanoparticles homogeneously embedded in a carbon matrix can present an extraordinary reversible capacity of 160.5 mA h g −1 with three‐electron reaction at ≈3.53 V during the Na + extraction/insertion process, realizing an unprecedentedly high energy density of 566.5 Wh kg −1 in the phosphate cathodes for SIBs. It is intriguing to reveal the underlying mechanism of the unique Mn 2+ /Mn 3+ , Mn 3+ /Mn 4+ , and Cr 3+ /Cr 4+ redox couples via X‐ray absorption near‐edge structure spectroscopy. The whole electrochemical reaction undergoes highly reversible single‐phase and biphasic transitions with a moderate volume change of 7.7% through in situ X‐ray diffraction and ex situ high‐energy synchrotron X‐ray diffraction. Combining density functional theory (DFT) calculations with the galvanostatic intermittent titration technique, the superior performance is ascribed to the low ionic‐migration energy barrier and desirable Na‐ion diffusion kinetics. The present work can offer a new insight into the design of multielectron‐reaction cathode materials for SIBs.

Zhang, Jian↗

Quantum chaos on edge

Recently, the physics of many-body quantum chaotic systems close to their ground states has come under intensified scrutiny. Such studies are motivated by the emergence of model systems exhibiting chaotic fluctuations throughout the entire spectrum [the Sachdev-Ye-Kitaev (SYK) model being a renowned representative] as well as by the physics of holographic principles, which likewise unfold close to ground states. Interpreting the edge of the spectrum as a quantum critical point, here we combine a wide range of analytical and numerical methods to the identification and comprehensive description of two different universality classes: the near edge physics of “sparse” and the near edge of “dense” chaotic systems. The distinction lies in the ratio between the number of a system's random parameters and its Hilbert space dimension, which is exponentially small or algebraically small in the sparse and dense case, respectively. Notable representatives of the two classes are generic chaotic many-body models (sparse) and invariant random matrix ensembles or chaotic gravitational systems (dense). While the two families share identical spectral correlations at energy scales comparable to the level spacing, the density of states and its fluctuations near the edge are different. Considering the SYK model as a representative of the sparse class, we apply a combination of field theory and exact diagonalization to a detailed discussion of its edge spectrum. Conversely, Jackiw-Teitelboim gravity is our reference model for the dense class, where an analysis of the gravitational path integral and random matrix theory reveal universal differences to the sparse class, whose implications for the construction of holographic principles we discuss. Published by the American Physical Society 2024

Altland, Alexander (ORCID:0000000229914805)↗

Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning

The deep operator network (DeepONet) has shown remarkable potential in solving partial differential equations (PDEs) by mapping between infinite-dimensional function spaces using labeled datasets. However, in scenarios lacking labeled data, the physics-informed DeepONet (PI-DeepONet) approach, which utilizes the residual loss of the governing PDE to optimize the network parameters, faces significant computational challenges, particularly due to the curse of dimensionality. This limitation has hindered its application to high-dimensional problems, making even standard 3D spatial with 1D temporal problems computationally prohibitive. Additionally, the computational requirement increases exponentially with the discretization density of the domain. Here, to address these challenges and enhance scalability for high-dimensional PDEs, we introduce the Separable physics-informed DeepONet (Sep-PI-DeepONet). This framework employs a factorization technique, utilizing sub-networks for individual one-dimensional coordinates, thereby reducing the number of forward passes and the size of the Jacobian matrix required for gradient computations. By incorporating forward-mode automatic differentiation (AD), we further optimize computational efficiency, achieving linear scaling of computational cost with discretization density and dimensionality, making our approach highly suitable for high-dimensional PDEs. We demonstrate the effectiveness of Sep-PI-DeepONet through three benchmark PDE models: the viscous Burgers’ equation, Biot’s consolidation theory, and a parameterized heat equation. Our framework maintains accuracy comparable to the conventional PI-DeepONet while reducing training time by two orders of magnitude. Notably, for the heat equation solved as a 4D problem, the conventional PI-DeepONet was computationally infeasible (estimated 289.35 h), while the Sep-PI-DeepONet completed training in just 2.5 h. These results underscore the potential of Sep-PI-DeepONet in efficiently solving complex, high-dimensional PDEs, marking a significant advancement in physics-informed machine learning.

Neural operator↗

Enhanced magnetic and optical properties of Y 3 Fe 5 O 12 (YIG) films with Au nanoinclusions

Y 3 Fe 5 O 12 (YIG) thin films are well known for their ferrimagnetic insulating property and low Gilbert damping coefficient (α), allowing them to be used for various spintronic applications and as magneto-optical isolators for photonic devices. Instead of doping, incorporation of plasmonic metals as nanoinclusions could be a promising route for improved magneto-optical coupling properties. In this work, YIG–Au nanocomposites have been deposited with ferrimagnetic insulating YIG as the matrix and Au nanoinclusions which introduce plasmonic absorption, optical anisotropy, and hyperbolic properties. Films with varying Au nanoinclusion densities have been processed and annealed to compare with the as-deposited ones. The films that had low Au nanoinclusion density and were annealed presented a lower magnetic damping coefficient of 2.84 × 10 −4 than the pure YIG film (9.66 × 10 −4 ). The as-deposited film with the highest Au density shows the strongest hyperbolic properties among all samples. These results demonstrate that both magnetic damping and optical properties can be tuned through deposition conditions in YIG–Au nanocomposite thin films, allowing for a balance of both properties. This YIG–Au nanocomposite system presents promising potential in next-generation opto-spintronic devices.

Quigley, Lizabeth [Purdue Univ., West Lafayette, I↗

Gamow-Teller Strength in Ca 48 and Ni 78 with the Charge-Exchange Subtracted Second Random-Phase Approximation

Here, we develop a fully self-consistent subtracted second random-phase approximation for charge-exchange processes with Skyrme energy-density functionals. As a first application, we study Gamow-Teller excitations in the doubly magic nucleus 48 Ca, the lightest double-β emitter that could be used in an experiment, and in 78 Ni, the single-beta-decay rate of which is known. The amount of Gamow-Teller strength below 20 or 30 MeV is considerably smaller than in other energy-density-functional calculations and agrees better with experiment in 48 Ca, as does the beta-decay rate in 78 Ni. These important results, obtained without ad hoc quenching factors, are due to the presence of two-particle–two-hole configurations. Their density progressively increases with excitation energy, leading to a long high-energy tail in the spectrum, a fact that may have implications for the computation of nuclear matrix elements for neutrinoless double-β decay in the same framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Developing Platinum-Group-Metal-Free Catalysts for Oxygen Reduction Reaction in Acid: Beyond the Single Metal Site

This project is to develop M (x) -N-C catalysts with dense multiple metal center (MMC) sites to meet the DOE 2025 activity target of 0.044 mA/cm 2 at 0.9 V IR-free ., as well as other goals such as durability. We have made important contributions to both catalyst development and fundamental understandings of the active sites in M-N-C catalysts in this project. We successfully made M (x) -N-C catalysts with some multiple metal center (MMC) sites by combining ionothermal carbonization with chemical vapor deposition (CVD). These catalysts, however, are not as active as the most active single-atom Fe-N-C catalysts made by the similar CVD process, owing likely to the low site density and the presence of inorganic Fe species such as iron carbides and nanoparticles. The most significant accomplishments we achieved in this project are: (1) we unraveled the formation pathway of Fe-N 4 sites during pyrolysis step-by-step and identified the trans-metalation mechanism, in collaboration with Deborah Myers and her colleagues at Argonne National Laboratory (ANL); (2) inspired by this finding, we pioneered the CVD synthesis of M-N-C catalysts (M = Mn, Fe, and Co), in which the Fe-N-C catalyst by CVD demonstrated an ORR activity of 33 mA/cm 2 at 0.9 V in H 2 -O 2 proton exchange membrane fuel cells (PEMFCs), very close to the ultimate goal of 35 mA/cm 2 of our project. This catalyst is the first Fe-N-C catalyst that contains only D1 sites without the D2 sites; whereas D1 and D2 sites have been always identified by Mossbauer in previous Fe-N-C catalysts. This finding helps to understand what the D1 and D2 sites are and their roles in catalyzing the ORR. (3) by improving the mass transport of the carbon matrix prior to the CVD process, the revised Fe-N-C catalyst made by CVD delivered a maximum power density of 0.53 W/cm 2 in H 2 -air PEMFCs. The improvement strategy was partly inspired by the computational modeling work by Adam Weber from LBNL, the Co-PI of this project, by developing, coding, and exercising a continuum level model of transport phenomena within a PGM-free catalyst layer. The model demonstrated that local resistances combined with limited site density of the PGM-free catalyst can result in limiting currents and poor polarization performance. The model also gave design guidance for impact of ECSA and overall catalyst-layer thickness. However, both Fe-N-C and Co-N-C catalysts developed by CVD showed poor durability in PEMFCS, in comparison with the traditional M-N-C catalysts synthesized via regular pyrolysis process. Consequently, we did not achieve the proposed durability targets. Despite so, we believe the FeNC-CVD catalysts with the poor durability and D1 sites only provides an excellent platform to understand the degradation mechanism of Fe-N-C in PEMFCs, the most important challenge in the development of M-N-C catalysts.

08 HYDROGEN↗

Fluid-like shock compression of dilute polymer nanocomposites

The shock Hugoniot of heterogenous mixtures of discrete particles has been experimentally investigated for porous agglomerates and fluids, while the study of full-density solids has been primarily limited to compressed powders and high-dimensional composites. By dispersing ceria nanoparticles in a polyethylene matrix, we are able to examine the hydrodynamic behavior of a nonporous, heterogenous solid in thermal equilibrium during weak shock compression. Phase-driven discontinuities in the Hugoniot particle velocity–shock velocity (u−D) relationship of pure polyethylene are replicated in the nanocomposites but are shifted to lower velocity and to higher pressure with higher particle concentration. The results are explained using an isothermal, two-velocity fluid model under the hydrodynamic approximation. The model, which assumes a theoretical equation-of-state for ceria and either a low-order or high-order fit to the measured polyethylene Hugoniot, reasonably predicts the Hugoniot for two different polyethylene/ceria nanocomposites. Using the model, the mixture Hugoniot is shown to be insensitive to the Hugoniot of the stiffer constituent when the moduli are sufficiently disparate, while dependence on particle density and volume fraction is preserved through fluid-like motion.

Moore, Nathan W. [Sandia National Laboratories (SN↗