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At least 793 records · Page 44

Insights into Ti doping for stabilizing the Na 2/3 Fe 1/3 Mn 2/3 O 2 cathode in sodium ion battery

Iron- and manganese-based layered metal oxides, as cathodes for sodium ion batteries, have received widespread attention because of the low cost and high specific capacity. However, the Jahn-teller effect of Mn 3+ ions and the resulted unstable structure usually lead to continuously capacity decay. Herein, Titanium (Ti) has been successfully doped into Na 2/3 Fe 1/3 Mn 2/3 O 2 to suppress the Jahn-Teller distortion and improve both cycling and rate performance of sodium ion batteries. In situ high-energy synchrotron X-ray diffraction study shows that Ti-doped compound (Na 2/3 Fe 1/3 Mn 0.57 Ti 0.1 O 2 ) can maintain the single P2 phase without any phase transition during the whole charging/discharging process. Further, various electrochemical characterizations are also applied to explore the better kinetics of sodium ions transfer in the Na 2/3 Fe 1/3 Mn 0.57 Ti 0.1 O 2 . This work provides a comprehensive insight into the Ti-doping effects on the performance from both structural and electrokinetic perspectives.

25 ENERGY STORAGE↗

Defect Production and Microstructural Feature Impact for Radiation Damage in Additively Manufactured 316 Stainless Steel

This milestone presents multi-scale modeling research results for additively manufactured 316 stainless steel. A combination of phase field, cluster dynamics, molecular dynamics, and density functional theory with machine learning is used, allowing for predictions of radiation-driven microstructural evolution in additively manufactured 316 stainless steel over a range of temperatures, damage rates, neutron spectra, and microstructures, and supporting the development of combined ion and neutron irradiation for material qualification. Informed by ion irradiation and neutron irradiation results across the Advanced Materials and Manufacturing Technologies program, we investigate the unique aspects of radiation-driven microstructure evolution in additively manufactured 316 stainless steel. In particular, we focus on understanding the impact of carbon concentration (varying, for example, between the 316L and 316H standards) on void formation; radiation-induced segregation at dislocation cells and grain boundaries; and the evolution of dislocation loops and network dislocation populations. We find that the unique characteristics of the additively manufactured microstructures must be accounted for in understanding the evolution of dislocation populations under thermal and irradiation conditions, such as the variation in sink strengths arising due to the variation in dislocation density. We also find that the radiation-induced segregation of Cr and Ni to grain boundaries and cell walls differs due to the differences in their defect sink biases. We also find that increasing the Ni content can slow vacancy diffusion, which may provide a mechanism for the observed reduction in transient swelling rate for austenitic Fe-Cr-Ni alloys with increasing Ni content. In addition, ion irradiations have shown that increasing carbon content in 316 SS results in a larger population of smaller voids, suggesting reduced vacancy diffusion. Our results show that the carbon content of additively manufactured 316 SS has a significant impact on the migration rate of defect clusters. The presence of carbon atoms results in carbon-vacancy trapping, significantly reducing the diffusion rate of vacancies. Carbon atoms may also be trapped near the surface of a void, which may reduce void growth by trapping vacancies that diffuse toward the void.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling Heat Transfer and Reaction Kinetics of Biomass in Pyrolysis Feeding Systems

Biomass feedstocks can be used to produce low carbon-intensity chemicals and liquid fuels by displacing fossil-fuel sources. Pyrolysis is the thermal decomposition of biomass in the absence of oxygen and can be used to produce crude biofuels. A typical feeding mechanism for pyrolysis reactors is by lock hopper followed by a horizontal auger feeder. Particle agglomeration and plugging of the auger screw are regularly occurring phenomena that is detrimental to the process since it results in the need for periodic inspection and cleaning. The underlying mechanisms leading to agglomeration and plugging are unclear, but a working hypothesis is that heat from the reactor raises the temperature of the biomass in the feeder to the point at which preliminary decomposition reactions occur and produce "sticky" products. Using principles of heat and mass transfer, we derived one-dimensional differential equations for heat flow from the pyrolysis reactor through the auger feeder. Temperature profiles were solved from the system of one-dimensional differential equations using the shooting method. Subsequently, we used the temperature profiles as a one-way coupling to a reaction model for the biomass in the feeder. Kinetic models were adopted from the literature and used to predict the formation of intermediates, products, char, extractives, and metaplastics as well as phase changes along the auger feeder. Species were identified that correlated with softening of the biomass, causing it to become sticky and plug the feeder. We will discuss the details of this work, our findings, and the direction of future work that includes fully coupled transport and reaction-kinetics simulations.

BIOMASS FUELS↗

Operando real-space imaging of a structural phase transformation in the high-voltage electrode LixNi0.5Mn1.5O4

Abstract Discontinuous solid-solid phase transformations play a pivotal role in determining the properties of rechargeable battery electrodes. By leveraging operando Bragg Coherent Diffractive Imaging (BCDI), we investigate the discontinuous phase transformation in Li x Ni 0.5 Mn 1.5 O 4 within an operational Li metal coin cell. Throughout Li-intercalation, we directly observe the nucleation and growth of the Li-rich phase within the initially charged Li-poor phase in a 500 nm particle. Supported by the microelasticity model, the operando imaging unveils an evolution from a curved coherent to a planar semi-coherent interface driven by dislocation dynamics. Our data indicates negligible kinetic limitations from interface propagation impacting the transformation kinetics, even at a discharge rate of C/2 (80 mA/g). This study highlights BCDI’s capability to decode complex operando diffraction data, offering exciting opportunities to study nanoscale phase transformations with various stimuli.

Sun, Yifei (ORCID:0000000295625120)↗

Competition Between Growth and Removal in Zirconia Nanocrystal-Derived Tribofilms: The Role of Co-additives

Antiwear additives permit energy-efficient lubrication of gearboxes, bearings, and other tribological interfaces. We study zirconia (ZrO 2 ) nanocrystal additives, which readily form protective tribofilms in tribological contacts. Our prior work demonstrated cooperative antiwear performance between ZrO 2 and the S- and P-based co-additives in fully formulated hydrocarbon gear oils. Here, we extend that work by examining the growth kinetics of the ZrO 2 tribofilms, including the influence of the co-additives. In the boundary lubrication regime for mixed rolling-sliding contacts, the initial phase of ZrO 2 tribofilm growth is soon overtaken by removal processes, phenomena whose importance has gone unnoticed in prior work. Tribofilm removal affects the steady-state thickness and morphology of the tribofilm as well as its growth kinetics. The S- and P-based co-additives are incorporated into the ZrO 2 tribofilm, and alter the competition between the growth and removal processes, increasing initial net growth rates per contact cycle and contributing to a more polished final interface. This work highlights the significance of removal processes in determining tribofilm antiwear performance, and suggests several routes for improving tribofilm growth kinetics using co-additives.

Coadditives↗

Kinetic-controlled transformations of group-III arsenide nanocubes

Tracking the structural evolution of colloidal nanocrystals (NCs) facilitates the mechanistic studies of their materials chemistry. NC engineering via phase transformation reveals the chemical and physical determinants that drive lattice-scale dynamic processes such as cation exchange. Here, in this study, we employed NCs to demonstrate the cation exchange process from Cu 3 As to InAs and GaAs within nanocubes. The symmetry conversion in unit cells from cubic Cu 3 As to hexagonal InAs and GaAs can be described using a schematic cellular automaton model, which suggests a simplified cube-to-sphere transition. The strong covalent characteristics of III–V materials highlight the kinetic control that navigates the tailorable transformation through either an isotropic trajectory, leading to hollow structures, or a topotaxial trajectory, with abundant stacking faults. The reconstruction of complex covalent bonds is envisioned as the foundation for the synthesis of NCs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A predictive mirror twin Higgs with small Z2 breaking

The twin Higgs mechanism is a solution to the little hierarchy problem in which the top partner is neutral under the Standard Model (SM) gauge group. The simplest mirror twin Higgs (MTH) model — where a Z 2 symmetry copies each SM particle — has too many relativistic degrees of freedom to be consistent with cosmological observations. We demonstrate that MTH models can have an observationally viable cosmology if the twin mass spectrum leads to twin neutrino decoupling before the SM and twin QCD phase transitions. Our solution requires the twin photon to have a mass of ~20 MeV and kinetically mix with the SM photon to mediate entropy transfer from the twin sector to the SM. This twin photon can be robustly discovered or excluded by future experiments. Additionally, the residual twin degrees of freedom present in the early Universe in this scenario would be detectable by future observations of the cosmic microwave background.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Conservative velocity mappings for discontinuous Galerkin kinetics

Continuum computational kinetic plasma models evolve the distribution function of a plasma species f s on a phase-space grid over time. In many problems of interest the distribution function has limited extent in velocity space; hence, using a uniform, highly refined mesh would be costly and slow. Nonuniform velocity grids can reduce the computational cost by placing more degrees of freedom where f s is appreciable and fewer where it is not. In this work we introduce a first-of-its kind discontinuous Galerkin approach to nonuniform velocity-space discretization using mapped velocity coordinates. This new method is presented in the context of a gyrokinetic model used to study magnetized plasmas. We create discretizations of collisionless and collisional terms using mappings in a way that exactly conserves particles and energy. Numerical tests of such properties are presented, and we show that this new discretization can reproduce earlier gyrokinetic simulations using grids with up to 6–60 times fewer cells and 22X-60X speed-ups depending on dimensionality, geometry and plasma parameters.

Discontinuous Galerkin↗

Promotional Effect of ZnO and ZrO 2 in K-Doped Fe Catalysts for CO 2 Hydrogenation to Light Olefins

Promoters play a critical role in tuning the activity and selectivity of Fe catalysts in CO 2 hydrogenation to produce light olefins, which are key building blocks in the petrochemical industry. Herein, by a combined experimental and theoretical approach, we show that high and stable performance of Fe catalysts could be achieved by taking advantage of the promotional effect of both Zn and Zr. Structural characterization indicates that ZnO could improve the dispersion and reducibility of Fe oxides and facilitate the formation of active Fe carbide species, whereas ZrO 2 could stabilize the structure and catalytic performance, especially the selectivity of hydrocarbon products. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments suggest that carbonate, bicarbonate, formate, and methoxy are essential intermediates in the CO 2 hydrogenation to hydrocarbon products, including paraffins and olefins. The conversion kinetics of each intermediate species are dependent on the type of promoters as well as the phase structure of the active Fe species. DFT calculations revealed a strong correlation between the formation energy of surface oxygen vacancies and that of Fe carbide species in promoted Fe oxides, in accordance with experimental results. Moreover, the calculated energy profiles of CO 2 hydrogenation over different catalysts indicate that Zn could promote the activation of CO 2 and its transformation to the oxygenate intermediates, while Zr could facilitate the conversion of oxygenates to hydrocarbon precursors. Finally, the discrepancies in the evolution trend of various intermediate species on promoted Fe catalysts in the transient DRIFTS experiments can be rationalized by the differences in energy barriers of elementary or rate limiting steps.

CO2 conversion↗

Three-dimensional flat bands in pyrochlore metal CaNi 2

Electronic flat-band materials host quantum states characterized by a quenched kinetic energy. These flat bands are often conducive to enhanced electron correlation effects and emergent quantum phases of matter. Long studied in theoretical models, these systems have received renewed interest after their experimental realization in van der Waals heterostructures and quasi-two-dimensional (2D) crystalline materials. An outstanding experimental question is if such flat bands can be realized in three-dimensional (3D) networks, potentially enabling new materials platforms and phenomena. Here we investigate the C15 Laves phase metal CaNi 2 , which contains a nickel pyrochlore lattice predicted at a model network level to host a doubly-degenerate, topological flat band arising from 3D destructive interference of electronic hopping. Using angle-resolved photoemission spectroscopy, we observe a band with vanishing dispersion across the full 3D Brillouin zone that we identify with the pyrochlore flat band as well as two additional flat bands that we show arise from multi-orbital interference of Ni d -electrons. Furthermore, we demonstrate chemical tuning of the flat-band manifold to the Fermi level that coincides with enhanced electronic correlations and the appearance of superconductivity. Extending the notion of intrinsic band flatness from 2D to 3D, this provides a potential pathway to correlated behaviour predicted for higher-dimensional flat-band systems ranging from tunable topological to fractionalized phases.

36 MATERIALS SCIENCE↗

Chemomechanical effect of reduced graphene oxide encapsulation on hydrogen storage performance of Pd nanoparticles

Primary chemomechanical impacts of confinement on hydrogen storage performance are studied using a nanolaminate structure where reduced graphene oxide (rGO) encapsulates palladium (Pd) nanoparticles. Three contributing factors are identified that can alter the reaction enthalpy: nanosizing, chemical interaction with the encapsulant, and mechanical stress induced strain from a combination of clamping force and lateral pulling force exerted on the Pd nanoparticles. The mechanical contributions are quantified by combining transmission electron microscopy, ab initio computation, and continuum elasticity theory, from which the encapsulation is found to exert an additional strain of 4.96% and 2.99% before and after hydrogen absorption, respectively, increasing the Pd and Pd hydride (PdH x ) reaction enthalpy by 1.3–2.8 kJ (mol H 2 ) -1 . The effect of the chemical interaction with rGO also raises the reaction enthalpy by up to 1.6 kJ (mol H 2 ) -1 , while the nanosizing effect decreases the reaction enthalpy. The three contributing factors to the reaction enthalpy are found to be similar in magnitude, where the net effect is in agreement with the measured enthalpy increase of 3.7 kJ (mol H 2 ) -1 from the bulk value. Hydrogen absorption kinetics and capacity also improved, which is attributed to facile nucleation of the hydrogen-rich phase enabled by the inhomogeneous strain distribution over the encapsulated PdHx nanoparticles. These results demonstrate that the chemomechanical effect can be controlled in the nanolaminate structure, providing an ideal template for tuning hydrogen storage performance.

08 HYDROGEN↗

Reconnection from a turbulence perspective

The spectral properties associated with laminar, anti-parallel reconnection are examined using a 2.5D kinetic particle in cell simulation. Both the reconnection rate and the energy spectrum exhibit three distinct phases: an initiation phase where the reconnection rate grows, a quasi-steady phase, and a declining phase where both the reconnection rate and the energy spectrum decrease. During the steady phase, the energy spectrum exhibits approximately a double power law behavior, with a slope near −5/3 at wave numbers smaller than the inverse ion inertial length and a slope steeper than −8/3 for larger wave numbers up to the inverse electron inertial length. This behavior is consistent with a Kolmogorov energy cascade and implies that laminar reconnection may fundamentally be an energy cascade process. Consistent with this idea is the fact that the reconnection rate exhibits a rough correlation with the energy spectrum at wave numbers near the inverse ion inertial length. The 2D spectrum is strongly anisotropic with most energy associated with the wave vector direction normal to the current sheet. Reconnection acts to isotropize the energy spectrum, reducing the Shebalin angle from an initial value of 70° to about 48° (nearly isotropic) by the end of the simulation. The distribution of energy over length scales is further analyzed by dividing the domain into spatial subregions and employing structure functions.

Adhikari, S. (ORCID:0000000321607066)↗

Nonlinear dynamics of multiple Alfvén modes driven by trapped energetic ions in tokamaks: A triplet paradigm

Non-linear dynamics of multiple infernal Alfvén eigenmodes—a subset of global Alfvén eigenmodes in tokamak plasmas with extended low-shear central core [Marchenko et al., Phys. Plasmas 16, 092502 (2009)]—is studied. The analysis is carried out for a mode triplet with toroidal mode-numbers n=1, 2, 3. It was assumed that the n = 1 mode was linearly unstable due to precession resonance with trapped fast ions, whereas the other modes were linearly damped. The modes were coupled due to a non-linearity in a bounce-averaged drift kinetic equation for the distribution function of fast ions. Nonlinear equations for the mode amplitudes and phases are derived and solved numerically. It is found that the temporal evolution of the amplitudes and the phase (responsible for the frequency chirping) of the modes exhibit Hopf bifurcations to stable limit cycles. This can explain a synchronous cyclic destabilization of multiple modes in Alfvén avalanches (sudden growth of amplitudes of the mode cluster with different n and approximately equal frequency spacing) in NSTX and bursting modes in MAST—events, which resulted in enhanced loss of fast ions.

Marchenko, V. S. (ORCID:0000000261480533)↗

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Profusion of symmetry-protected qubits from stable ergodicity breaking

We show how combining a discrete symmetry with topological Hilbert space fragmentation can give rise to exponentially many topologically stable qubits protected by a single discrete symmetry. We illustrate this explicitly with the example of the CZ𝑝 model, where the encoded qubits are prethermally stable to arbitrary symmetry-respecting perturbations for parametrically long times, substantially enhancing the robustness of a recently proposed construction based on nontopological fragmentation. In this model, the encoded qubits naturally come in pairs for which a universal set of transversal logical gates can be performed, ruling out (by the Eastin-Knill theorem) the possibility of using them for quantum error correction. We also comment on the combination of symmetry enrichment and topological fragmentation more generally, and the implications for use of systems exhibiting Hilbert space fragmentation as quantum memories.

kinetically constrained models↗

Quantifying the regime of thermodynamic control for solid-state reactions during ternary metal oxide synthesis

The success of solid-state synthesis often hinges on the first intermediate phase that forms, which determines the remaining driving force to produce the desired target material. Recent work suggests that when reaction energies are large, thermodynamics primarily dictates the initial product formed, regardless of reactant stoichiometry. Here, we validate this principle and quantify its constraints by performing in situ characterization on 37 pairs of reactants. These experiments reveal a threshold for thermodynamic control in solid-state reactions, whereby initial product formation can be predicted when its driving force exceeds that of all other competing phases by ≥60 milli–electron volt per atom. In contrast, when multiple phases have a comparable driving force to form, the initial product is more often determined by kinetic factors. Analysis of the Materials Project data shows that 15% of possible reactions fall within the regime of thermodynamic control, highlighting the opportunity to predict synthesis pathways from first principles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-scale transport in the DIII-D ITER baseline scenario with direct electron heating and projection to ITER

Multi-scale fluctuations measured by turbulence diagnostics spanning long and short wavelength spatial scales impact energy confinement and the scale-lengths of plasma kinetic profiles in the DIII-D ITER baseline scenario with direct electron heating. Contrasting discharge phases with ECH + neutral beam injection (NBI) and NBI only at similar rotation reveal higher energy confinement and lower fluctuations when only NBI heating is used. Modeling of the core transport with TGYRO using the TGLF turbulent transport model and NEO neoclassical transport reproduces the experimental profile changes upon application of direct electron heating and indicates that multi-scale transport mechanisms are responsible for changes in the temperature and density profiles. Intermediate and high-k fluctuations appear responsible for the enhanced electron thermal flux, and intermediate-k electron modes produce an inward particle pinch that increases the inverse density scale length. Projection to ITER is performed with TGLF and indicates a density profile that has a finite scale length due to intermediate-k electron modes at low collisionality and increases the fusion gain. For a range of E×B shear, the dominant mechanism that increases fusion performance is suppression of outward low-k particle flux and increased density peaking.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗