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At least 109 records · Page 6

Progress towards a phenomenological picture and theoretical understanding of glassy dynamics and vitrification near interfaces and under nanoconfinement

The nature of alterations to dynamics and vitrification in the nanoscale vicinity of interfaces-commonly referred to as "nanoconfinement" effects on the glass transition-has been an open question for a quarter century. We first analyze experimental and simulation results over the last decade to construct an overall phenomenological picture. Key features include the following: after a metrology- and chemistry-dependent onset, near-interface relaxation times obey a fractional power law decoupling relation with bulk relaxation; relaxation times vary in a double-exponential manner with distance from the interface, with an intrinsic dynamical length scale appearing to saturate at low temperatures; the activation barrier and vitrification temperature T-g approach bulk behavior in a spatially exponential manner; and all these behaviors depend quantitatively on the nature of the interface. We demonstrate that the thickness dependence of film-averaged T-g for individual systems provides a poor basis for discrimination between different theories, and thus we assess their merits based on the above dynamical gradient properties. Entropy-based theories appear to exhibit significant inconsistencies with the phenomenology. Diverse free-volume-motivated theories vary in their agreement with observations, with approaches invoking cooperative motion exhibiting the most promise. The elastically cooperative nonlinear Langevin equation theory appears to capture the largest portion of the phenomenology, although important aspects remain to be addressed. A full theoretical understanding requires improved confrontation with simulations and experiments that probe spatially heterogeneous dynamics within the accessible 1-ps to 1-year time window, minimal use of adjustable parameters, and recognition of the rich quantitative dependence on chemistry and interface. Published under license by AIP Publishing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Competing magnetic interactions and emergent phase diagrams in double perovskite Y 2 Ni x Co 1–x MnO 6

We present a comparative study of double perovskites Y 2 Ni x Co 1–x MnO 6 for x = 1, 0.5, and 0. The polycrystalline samples of Y 2 Ni x Co 1–x MnO 6 with space group P2 1 /n were synthesized via sol-gel technique. X-ray photoelectron spectroscopy (XPS) confirms the presence of majority Ni 2+ /Mn 4+ in Y 2 NiMnO 6 (YNMO) and a mixed valence state Ni 2+/3+ /Co 2+/3+ /Mn 4+/3+ in co-doped Y 2 Ni 0.5 Co 0.5 MnO 6 (YNCMO). The temperature dependent magnetization results suggest homogeneous substitution of Ni ions with Co ions with minimal contribution of 3+ cationic magnetic interactions in YNCMO. The superexchange ferromagnetic (FM) interaction has a major contribution to the magnetism of YNMO. The strength of antiferromagnetic (AFM) coupling resulting from the antiphase boundaries in Y 2 Ni x Co 1–x MnO 6 increases with the increase in the Co concentration. The AC susceptibility (AC-χ) study further validates the presence of higher density of antiphase boundaries, which is reflected by the dynamics of domain walls in YNCMO. The isothermal magnetic entropy change (ΔS M ) as functions of temperature and magnetic field is exploited to assess the stabilization of different magnetic phases. Finally, the findings of ΔS M (T,µ 0 H) lead to the proposed new magnetic phase diagrams for Y 2 Ni x Co 1–x MnO 6 for x = 1 and 0.5, in comparison with the previously established phase diagram of Y 2 CoMnO 6 .

36 MATERIALS SCIENCE↗

Artificial intelligence based analysis of nanoindentation load–displacement data using a genetic algorithm

In this work, we developed an automated tool, Nanoindentation Neo package for the analysis of nanoindentation load–displacement curves using a Genetic Algorithm (GA) applied to the Oliver-Pharr method (Oliver et al.,1992). For some materials, such as polycrystalline isotropic graphites, Least Squares Fitting (LSF) of the unload curve can produce unrealistic fit parameters. These graphites exhibit sharply peaked unloading curves not easily fit using the LSF, which tends to overestimate the indenter tip geometry parameter. To tackle this problem, we extended our general materials characterization tool Neo for EXAFS analysis (Terry et al., 2021) to fit nanoindentation data. Nanoindentation Neo automatically processes and analyzes nanoindentation data with minimal user input while producing meaningful fit parameters. GA, a robust metaheuristic method, begins with a population of temporary solutions using model parameters called chromosomes; from these we evaluate a fitness value for each solution, and select the best solutions to mix with random solutions producing the next generation. A mutation operator then modifies existing solutions by random perturbations, and the optimal solution is selected. We tested the GA method using Silica and Al reference standards. We fit samples of graphite and a high entropy alloy (HEA) consisting of BCC and FCC phases.

42 ENGINEERING↗

Operational Limits of Redox Metal Oxides Performing Thermochemical Water Splitting

Solar thermochemical hydrogen production is an attractive technology that stores intermittent solar energy in the form of chemical bonds. Efficient operation requires the identification of a redox-active metal oxide (MO x ) material that can achieve high conversion of water to hydrogen at minimal energy input. Water splitting occurs by consecutive reduction and reoxidation reactions of MO x . MO x is reduced to MO x-δ and, in the second step, is reoxidized by water recovering the initial MO x and generate H 2 . The material must reduce at temperatures achievable in concentrated solar receiver/reactors, while maintaining a thermodynamic driving force to split water. At equilibrium, extent of reduction depends on temperature and oxygen partial pressure, and in this analysis, a set of thermodynamic properties, namely, enthalpy and entropy of oxygen vacancy formation, is sufficient to represent MO x . Herein, a method to easily classify materials based on these thermodynamic properties under any condition of oxygen partial pressure and temperature is presented. This method is based on fundamental thermodynamic principles and is applicable for any redox material with known thermodynamic properties. Despite the simplicity of the method, it is believed that this analysis will support future research in targeting thermodynamic properties of redox-active metal oxides.

water splitting↗

Impact of Synthetic Parameters on Structure and Electrochemistry of High-Entropy Layered Oxide LiNi 0.2 Co 0.2 Mn 0.2 Al 0.2 Fe 0.2 O 2

Here, this study explored a high-entropy layered oxide (HELO), LiNi 0.2 Co 0.2 Mn 0.2 Al 0.2 Fe 0.2 O 2 , prepared by coprecipitation followed by heat treatment. Coprecipitation yielded a kinetically favored product, and the subsequent heat treatment under various temperatures and times allowed tuning the material toward more thermodynamically favored structures. Refinement of X-ray powder diffraction (XRD) revealed that after 450 °C treatment, ~12% of the Ni 2+ in the structure was located within the lithium cation layer. After heat treatment at 600, 700, and 800 °C, there was a continued decrease of Ni 2+ in the lithium cation layer to 9.3, 6.3, and 3.7%, respectively. Longer heat treatment times at 800 °C decreased the level to 2.5%. Electrochemical behavior was evaluated by cyclic voltammetry, galvanostatic cycling, rate capability testing, and electrochemical impedance spectroscopy, where increased loaded voltage, functional capacity, rate capability, and decreased impedance were observed for samples treated at higher temperatures with lower cation mixing. X-ray absorption near edge spectroscopy (XANES) data indicated that the redox activity of Ni and Co was dominant in the electrochemistry, while the participation of Mn or Fe was minimal. The level of Ni oxidation state change between charge and discharge related to the heat treatment temperature where the samples with high cation mixing showed lower capacity consistent with some Ni 3+ in the transition metal layer inaccessible for electron transfer. Longer heat treatment times at 800 °C did not continue to provide a benefit in electrochemical function even with some additional reduction in cation mixing.

25 ENERGY STORAGE↗

Dual heterogeneous structures lead to ultrahigh strength and uniform ductility in a Co-Cr-Ni medium-entropy alloy

Alloys with ultra-high strength and sufficient ductility are highly desired for modern engineering applications but difficult to develop. Here we report that, by a careful controlling alloy composition, thermomechanical process, and microstructural feature, a Co-Cr-Ni-based medium-entropy alloy (MEA) with a dual heterogeneous structure of both matrix and precipitates can be designed to provide an ultra-high tensile strength of 2.2 GPa and uniform elongation of 13% at ambient temperature, properties that are much improved over their counterparts without the heterogeneous structure. Electron microscopy characterizations reveal that the dual heterogeneous structures are composed of a heterogeneous matrix with both coarse grains (10~30 μm) and ultra-fine grains (0.5~2 μm), together with heterogeneous L1 2 -structured nanoprecipitates ranging from several to hundreds of nanometers. The heterogeneous L1 2 nanoprecipitates are fully coherent with the matrix, minimizing the elastic misfit strain of interfaces, relieving the stress concentration during deformation, and playing an active role in enhanced ductility.

36 MATERIALS SCIENCE↗

Integrable model of topological SO(5) superfluidity

Assisted by general symmetry arguments and a many-body invariant, we introduce a phase of matter that constitutes a topological SO(5) superfluid. Key to this finding is the realization of an exactly solvable model that displays some similarities with a minimal model of superfluid 3 He. We study its quantum phase diagram and correlations, and find exotic superfluid as well as metallic phases in the repulsive sector. At the critical point separating trivial and nontrivial superfluid phases, our Hamiltonian reduces to the globally SO(5)-symmetric Gaudin model with a degenerate ground manifold that includes quartet states. Most importantly, the exact solution permits uncovering of an interesting non-pair-breaking mechanism for superfluids subject to external magnetic fields. Furthermore, nonintegrable modifications of our model lead to a strong-coupling limit of our metallic phase with a ground-state manifold that shows an extensive entropy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A simple introduction to the SiMPL method for density-based topology optimization

We introduce a novel method for solving density-based topology optimization problems: Sigmoidal Mirror descent with a Projected Latent variable (SiMPL). The SiMPL method (pronounced as “the simple method”) optimizes a design using only first-order derivative information of the objective function. The bound constraints on the density field are enforced with the help of the (negative) Fermi–Dirac entropy, which is also used to define a non-symmetric distance function called a Bregman divergence on the set of admissible designs. This Bregman divergence leads to a simple update rule that is further simplified with the help of a so-called latent variable. Because the SiMPL method involves discretizing the latent variable, it produces a sequence of pointwise-feasible iterates, even when high-order finite elements are used in the discretization. Numerical experiments demonstrate that the method outperforms other popular first-order optimization algorithms. In conclusion, to outline the general applicability of the technique, we include examples with (self-load) compliance minimization and compliant mechanism optimization problems.

Calculus of Variations and Optimization↗

Quantifying Quantum Chaos through Microcanonical Distributions of Entanglement

A characteristic feature of “quantum chaotic” systems is that their eigenspectra and eigenstates display universal statistical properties described by random matrix theory (RMT). However, eigenstates of local systems also encode structure beyond RMT. To capture this feature, we introduce a framework that allows us to compare the properties of eigenstates in local systems with those of pure random states. In particular, our framework defines a notion of distance between quantum state ensembles that utilizes the Kullback-Leibler divergence to compare the microcanonical distribution of entanglement entropy (EE) of eigenstates with a reference RMT distribution generated by pure random states (with appropriate constraints). This notion gives rise to a quantitative metric for quantum chaos that not only accounts for averages of the distributions but also higher moments. The differences in moments are compared on a highly resolved scale set by the standard deviation of the RMT distribution, which is exponentially small in system size. As a result, the metric can distinguish between chaotic and integrable behaviors and, in addition, quantify and compare the of chaos (in terms of proximity to RMT behavior) between two systems that are assumed to be chaotic. We implement our framework in local, minimally structured, Floquet random circuits, as well as a canonical family of many-body Hamiltonians, the mixed-field Ising model (MFIM). Importantly, for Hamiltonian systems, we find that the reference random distribution must be appropriately constrained to incorporate the effect of energy conservation in order to describe the ensemble properties of midspectrum eigenstates. The metric captures deviations from RMT across all models and parameters, including those that have been previously identified as strongly chaotic, and for which other diagnostics of chaos such as level spacing statistics look strongly thermal. In Floquet circuits, the dominant source of deviations is the second moment of the distribution, and this persists for all system sizes. For the MFIM, we find significant variation of the KL divergence in parameter space. Notably, we find a small region where deviations from RMT are minimized, suggesting that “maximally chaotic” Hamiltonians may exist in fine-tuned pockets of parameter space. Published by the American Physical Society 2024

Physics↗

Homogenization of Dendritic Structures and the High-Temperature Strength of the Refractory High-Entropy Alloy MoNbTaVW

MoNbTaVW, a pioneering refractory high-entropy alloy (RHEA), is renowned for its exceptional strength at elevated temperatures. Like most RHEAs, it solidifies into a dendritic microstructure with steep concentration gradients, necessitating heat treatment for equilibration. Steep concentration gradients typically complicate mechanical property analysis and modeling, key challenges for high-throughput alloy discovery. This study examines the effects of high-temperature homogenization (1800 °C for 8 hours) on the microstructure and mechanical properties of MoNbTaVW across temperatures up to 1200 °C. Postmortem microstructural analysis, coupled with chemical, crystallographic, and mechanical assessments, revealed that yield strength was surprisingly insensitive to homogenization, with less than a 3 pct difference between as-cast and heat-treated materials. Nanoindentation confirmed minimal nanohardness changes across the dendritic structure at room temperature. However, homogenization significantly enhanced high-temperature work hardening, producing higher peak compressive strength. Both as-cast and homogenized MoNbTaVW exhibited room-temperature strengths of 1400 MPa, exceeding previously reported values. These findings demonstrate that high-temperature treatment enables microstructural homogenization without compromising strength, a unique behavior among RHEAs. In conclusion, while not universally applicable, this insight highlights the importance of understanding microstructural development in experimental alloys and offers a pathway to design alloys that achieve homogeneous-like properties without heat treatment.

Rietema, C. J. [Lawrence Livermore National Labora↗

Unified, Geometric Framework for Nonequilibrium Protocol Optimization

Controlling thermodynamic cycles to minimize the dissipated heat is a long-standing goal in thermodynamics, and more recently, a central challenge in stochastic thermodynamics for nanoscale systems. Here, we introduce a theoretical and computational framework for optimizing nonequilibrium control protocols that can transform a system between two distributions in a minimally dissipative fashion. These protocols optimally transport a system along paths through the space of probability distributions that minimize the dissipative cost of a transformation. Furthermore, we show that the thermodynamic metric—determined via a linear response approach—can be directly derived from the same objective function that is optimized in the optimal transport problem, thus providing a unified perspective on thermodynamic geometries. As a result, we investigate this unified geometric framework in two model systems and observe that our procedure for optimizing control protocols is robust beyond linear response.

36 MATERIALS SCIENCE↗

Slow thermalization and subdiffusion in $U$(1) conserving Floquet random circuits

Random quantum circuits are paradigmatic models of minimally structured and analytically tractable chaotic dynamics. We study a family of Floquet unitary circuits with Haar random U(1) charge conserving dynamics; the minimal such model has nearest-neighbor gates acting on spin-1/2 qubits, and a single layer of even/odd gates repeated periodically in time. We find that this minimal model is not robustly thermalizing at numerically accessible system sizes, and displays slow subdiffusive dynamics for long times. We map out the thermalization dynamics in a broader parameter space of charge conserving circuits, and understand the origin of the slow dynamics in terms of proximate localized and integrable regimes in parameter space. In contrast, we find that small extensions to the minimal model are sufficient to achieve robust thermalization; these include (i) increasing the interaction range to three-site gates, (ii) increasing the local Hilbert space dimension by appending an additional unconstrained qubit to the conserved charge on each site, or (iii) using a larger Floquet period comprised of two independent layers of gates. Furthermore, our results should inform future studies of charge conserving circuits, which are relevant for a wide range of topical theoretical questions.

1-dimensional spin chains↗

Differentiating Hund from Mott physics in a three-band Hubbard-Hund model: Temperature dependence of spectral, transport, and thermodynamic properties

We study the interplay between Mott physics, driven by Coulomb repulsion U, and Hund physics, driven by Hund's coupling J, for a minimal model for Hund metals, the orbital-symmetric three-band Hubbard-Hund model (3HHM) for a lattice filling of 1/3. Hund-correlated metals are characterized by spin-orbital separation (SOS), a Hund's-rule-induced two-stage Kondo-type screening process, in which spin screening occurs at much lower energy scales than orbital screening. By contrast, in Mott-correlated metals, lying close to the phase boundary of a metal-insulator transition, the SOS window becomes negligibly small and the Hubbard bands are well separated. Using dynamical mean-field theory and the numerical renormalization group as real-frequency impurity solver, we identify numerous fingerprints distinguishing Hundness from Mottness in the temperature dependence of various physical quantities. Furthermore, These include ARPES-type spectra, the local self-energy, static local orbital and spin susceptibilities, resistivity, thermopower, and lattice and impurity entropies. Our detailed description of the behavior of these quantities within the context of a simple model Hamiltonian will be helpful for distinguishing Hundness from Mottness in experimental and theoretical studies of real materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Elucidating Primary Degradation Mechanisms in High-Cycling-Capacity, Compositionally Tunable High-Entropy Hydrides

The hydrogen sorption properties of single-phase bcc (TiVNb) 100–x Cr x alloys (x = 0–35) are reported. All alloys absorb hydrogen quickly at 25 °C, forming fcc hydrides with storage capacity depending on the Cr content. Here, a thermodynamic destabilization of the fcc hydride is observed with increasing Cr concentration, which agrees well with previous compositional machine learning models for metal hydride thermodynamics. The steric effect or repulsive interactions between Cr–H might be responsible for this behavior. The cycling performances of the TiVNbCr alloy show an initial decrease in capacity, which cannot be explained by a structural change. Pair distribution function analysis of the total X-ray scattering on the first and last cycled hydrides demonstrated an average random fcc structure without lattice distortion at short-range order. If the as-cast alloy contains a very low density of defects, the first hydrogen absorption introduces dislocations and vacancies that cumulate into small vacancy clusters, as revealed by positron annihilation spectroscopy. Finally, the main reason for the capacity drop seems to be due to dislocations formed during cycling, while the presence of vacancy clusters might be related to the lattice relaxation. Having identified the major contribution to the capacity loss, compositional modifications to the TiVNbCr system can now be explored that minimize defect formation and maximize material cycling performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of lightweight BCC multi-principal element alloys with enhanced hydrogen storage using a machine learning-driven genetic algorithm

Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.

DFT↗

High-Temperature Oxidation Behavior of FeCoCrNi+(Cu/Al)-Based High-Entropy Alloys in Humid Air

Previous studies showed some transition metal high-entropy alloy (HEA) compositions can have good oxidation resistance in air up to 800 °C. Four equiatomic HEAs have been developed based on FeCoCrNi with additions of Mn, Cu, Al or Al+Cu. The oxidation behavior of these HEAs was compared in humid (10 vol.% H2O) air at 800 °C for 100–500 h to investigate the influence of water vapor on the oxidation mechanisms. The Cu- and Al-containing alloys exhibited improved oxidation resistance over the Mn composition. For the Cu-containing alloy, a local attack of the Cu-rich phase was observed, which formed an Fe/Ni/Co/Cr spinel that was surrounded by Cr2O3. This oxide was thicker for the humid air atmosphere when compared to dry air, and the transition of the Cu oxide to the spinel was accelerated. The Al-containing HEA formed a thin Al2O3 scale with humidity suppressing AlN formation and forming a smoother oxide layer. The Al+Cu composition had the highest overall oxidation resistance (minimal local attack, no nitridation) and also showed a smooth oxide scale topography under humid air oxidation as opposed to a plate-like, rougher scale under dry air.

Crystallography↗

Dual Passivation of Cathode and Anode through Electrode–Electrolyte Interface Engineering Enables Long-Lifespan Li Metal–SPAN Batteries

The reliability and durability of lithium metal (Li 0 )–sulfur batteries are largely limited by the undesired Li 0 plating-stripping irreversibility and the detrimental polysulfide dissolution, yet approaches that can simultaneously address the above anodic and cathodic problems are scarce. In this study, we report the stable operation of a Li 0 -SPAN (sulfurized polyacrylonitrile) battery via an anode–cathode dual-passivation approach. By combination of a fluorinated localized high concentration electrolyte (LHCE) and a Li 3 N-forming additive (TMS-N 3 ), robust and highly conductive electrode passivation layers are formed in situ on the surface of both the Li 0 anode and the SPAN cathode. The resulting highly reversible, dendrite-free, and high-density Li 0 plating morphology enables a high Coulombic efficiency of 99.4%. Advanced tender energy X-ray spectroscopy also reveals the eliminated Li 2 S formation and minimized polysulfide dissolution in SPAN cathodes, leading to a high capacity of 580 mAh/g SPAN and stable cycling with negligible capacity decay (0.7%) for 800 cycles. This electrode–electrolyte interphase engineering strategy has tackled the major limitations of Li–S batteries in both ether- and carbonate-based electrolyte systems and under a wide temperature range from –10 to +50 °C, thus providing insightful guidelines for the rational design of highly durable and high-energy-density Li 0 -S batteries.

25 ENERGY STORAGE↗

A multistage distributionally robust optimization approach to water allocation under climate uncertainty

This paper investigates a Multistage Distributionally Robust Optimization (MDRO) approach to water allocation under climate uncertainty. The MDRO is formed by creating sets of conditional distributions (called conditional ambiguity sets) on a finite scenario tree. The distributions in the conditional ambiguity sets remain close to a nominal conditional distribution according a ø-divergence (e.g., Kullback-Leibler divergence, Hellinger distance, Burg entropy, etc.). Here, the paper discusses a decomposition algorithm to solve the resulting MDRO with ø-divergences, which uses the dual formulation and solves only linear subproblems instead of convex ones. Some properties of the algorithm such as generating feasible policies and valid upper/lower bounds are established. The paper then applies the modeling and solution techniques to allocate water in a rapidly-developing area of Tucson, Arizona. Tucson, like many arid and semi-arid regions around the world, faces considerable uncertainty in its ability to provide water for its citizens in the future. The primary sources of uncertainty in the Tucson region include (1) unpredictable population growth, (2) the availability of water from the Colorado River, and (3) the effects of climate variability on water consumption. This paper integrates forecasts for all these sources of uncertainty into a single optimization model for robust and sustainable water allocation. Then, it uses this model to analyze the value of constructing additional treatment facilities to reduce future water shortages. The results indicate that the MDRO approach can be very valuable for water managers by providing insights to minimize their risks and help them plan for the future.

54 ENVIRONMENTAL SCIENCES↗