Sharp Phase Boundary Research Articles

Sharp quantum phase transition in the frustrated spin-1/2 Ising chain antiferromagnet CaCoV2O7

We report on a quantum critical behavior in the quasi-1D spin-1/2 zigzag frustrated chain antiferromagnet CaCoV2O7, induced by an applied magnetic field. Below TN=3.3 K our zero-field neutron diffraction studies revealed the up-up-down-down spin structure, stabilized by an order-by-disorder phenomenon. At base temperature, the magnetic order is suppressed by an applied magnetic field (B), inducing a transition into a quantum paramagnetic state at Bc=3 T, as revealed by both neutron diffraction and ESR data. The transition exhibits an unusually sharp phase boundary with the critical exponent ϕ=0.164(3)≈1/6, in contrast to the earlier experimental observations for uniform spin-1/2 chain systems. Such a sharp QPT is anticipated due to a rare combination of spin-orbit coupling and competing NN and NNN exchange interactions J1 and J2 of the zigzag spin chain. Published by the American Physical Society 2024

Disorder-Broadened Phase Boundary with Enhanced Amorphous Superconductivity in Pressurized In2Te5.

As an empirical tool in materials science and engineering, the iconic phase diagram owes its robustness and practicality to the topological characteristics rooted in the celebrated Gibbs phase law free variables (F) = components (C) - phases (P) + 2. When crossing the phase diagram boundary, the structure transition occurs abruptly, bringing about an instantaneous change in physical properties and limited controllability on the boundaries (F = 1). Here, the sharp phase boundary is expanded to an amorphous transition region (F = 2) by partially disrupting the long-range translational symmetry, leading to a sequential crystalline-amorphous-crystalline (CAC) transition in a pressurized In2Te5 single crystal. Through detailed in situ synchrotron diffraction, it is elucidated that the phase transition stems from the rotation of immobile blocks [In2Te2]2+, linked by hinge-like [Te3]2- trimers. Remarkably, within the amorphous region, the amorphous phase demonstrates a notable 25% increase of the superconducting transition temperature (Tc), while the carrier concentration remains relatively constant. Furthermore, a theoretical framework is proposed revealing that the unconventional boost in amorphous superconductivity might be attributed to an intensified electron correlation, triggered by a disorder-augmented multifractal behavior. These findings underscore the potential of disorder and prompt further exploration of unforeseen phenomena on the phase boundaries.

Exploring solute-defect interactions in nanosized palladium hydrides across multiple time scales

We employ two different atomistic methods to investigate solute-defect interactions in nanosized palladium–hydrogen (Pd–H) systems across multiple time scales. The first method, referred to as Diffusive Molecular Dynamics (DMD), focuses on capturing hydride phase transformation and the evolution of solute-induced lattice defects over a diffusive time scale. The second method, Molecular Dynamics (MD), provides more detailed insights into atomic movements and lattice relaxation over the time scale of thermal vibrations. These two methods are connected with MD simulations initialized using statistical measures of microscopic variables obtained from DMD at different H/Pd ratios. Our study demonstrates that DMD effectively captures the propagation of an atomistically sharp hydride phase boundary as well as the dynamics of solute-induced misfit dislocations and stacking faults. While the H-concentrated phase leads to a reduction in the vibrational energy, the presence of stacking faults locally increases the vibrational energy of both Pd and H atoms. Furthermore, the MD simulation results align with DMD in terms of equilibrium potential energy, the preservation of hydride phase boundary, and the spatial distribution of stacking faults. We thoroughly characterize the lattice crystalline structures in four key regions of the particle. We observe a preference for H atoms to occupy tetrahedral interstitial sites near stacking faults due to the lower stacking fault energies provided by these sites within the H-concentrated phase.

Shattering versus metastability in spin glasses

AbstractOur goal in this work is to better understand the relationship between replica symmetry breaking, shattering, and metastability. To this end, we study the static and dynamic behaviour of spherical pure p‐spin glasses above the replica symmetry breaking temperature . In this regime, we find that there are at least two distinct temperatures related to non‐trivial behaviour. First we prove that there is a regime of temperatures in which the spherical p‐spin model exhibits a shattering phase. Our results holds in a regime above but near . We then find that metastable states exist up to an even higher temperature as predicted by Barrat–Burioni–Mézard which is expected to be higher than the phase boundary for the shattering phase . We develop this work by first developing a Thouless–Anderson–Palmer decomposition which builds on the work of Subag. We then present a series of questions and conjectures regarding the sharp phase boundaries for shattering and slow mixing.

Learning two-phase microstructure evolution using neural operators and autoencoder architectures

Phase-field modeling is an effective but computationally expensive method for capturing the mesoscale morphological and microstructure evolution in materials. Hence, fast and generalizable surrogate models are needed to alleviate the cost of computationally taxing processes such as in optimization and design of materials. The intrinsic discontinuous nature of the physical phenomena incurred by the presence of sharp phase boundaries makes the training of the surrogate model cumbersome. We develop a framework that integrates a convolutional autoencoder architecture with a deep neural operator (DeepONet) to learn the dynamic evolution of a two-phase mixture and accelerate time-to-solution in predicting the microstructure evolution. We utilize the convolutional autoencoder to provide a compact representation of the microstructure data in a low-dimensional latent space. After DeepONet is trained in the latent space, it can be used to replace the high-fidelity phase-field numerical solver in interpolation tasks or to accelerate the numerical solver in extrapolation tasks.

Comparison of preparation techniques used for the identification of microstructural constituents in the microcrystalline structure of the eutectoid cold-work steel 80CrV2 (1.2235) after austempering

Abstract Strip material made of 80CrV2 was bainitized for a further development of the master blade steels for thin-cutting circular and band saw blades. Severe distortion after tempering of the material led to the search for a metallographic preparation method to identify the microstructural constituents retained austenite and martensite. Mechanical preparation followed by chemical etching was unsuccessful because the surface was too rough to identify the targeted phases under SEM. Performing an electrolytic preparation produced a less rough surface with sharp phase boundaries, which allowed identification at high magnifications under the SEM. Microhardness testing was used to distinguish between the microstructural constituents of retained austenite and martensite.

Structure of stellar remnants with coupling to a light scalar

In this paper, we study how a Yukawa coupling of the Standard Model fermions to a light scalar field affects the stellar structure of cold stellar remnants such as neutron stars. We elucidate the stellar structure phenomenology using a simple model of a massive scalar coupled to a single dominant fermion with no other interactions. For a broad scalar mass range (10-10 eV ≪ mϕ ≪ 103 eV for neutron stars) we show that the equation-of-state and stellar structure depends on the effective coupling ℊ = gf mf /mϕ , where gf is the Yukawa coupling, mf is the fermion mass, and mϕ is the scalar kinematic mass at nuclear densities. If ℊ > \U0001d4aa(1) the Yukawa coupled matter exhibits various anomalous behaviors including hydrodynamic instability, negative pressure, distinct phases (soft and hard) of matter with sharp phase boundaries between them and with the vacuum. These anomalies can lead to stars consisting of only soft, only hard, or a hybrid of soft and hard matter. These stars can have either sign for the slope of the mass-radius relation, anomalously large and small masses, gaps in allowed radii, multiple radii for the same mass, thin crusts and radiate anomalously large amounts of energy when they form (in the form of neutrinos for neutron stars). To the extent that these anomalies have not and/or will not be observed limits the effective coupling to ℊ < \U0001d4aa(1). We argue this phenomenology is generic to stars with Yukawa coupled matter.

Deep learning of topological phase transitions from entanglement aspects: An unsupervised way

Machine learning techniques have been shown to be effective to recognize different phases of matter and produce phase diagrams in the parameter space interested, while they usually require prior labeled data to perform well. Here, we propose a machine learning procedure, mainly in an unsupervised manner, which can first identify topological/non-topological phases and then refine the locations of phase boundaries. By following this proposed procedure, we expand our previous work on the one-dimensional $p$-wave superconductor [Phys. Rev. B 102, 054512 (2020)] and further on the Su-Schrieffer-Heeger model, with an emphasis on using the quantum entanglement-based quantities as the input features. We find that our method not only reproduces similar results to the previous work with sharp phase boundaries but importantly it also does not rely on prior knowledge of the phase space, e.g., the number of phases present. We conclude with a few remarks about its potential, limitations, and explainabilities.

Mesophasic organization of GABAA receptors in hippocampal inhibitory synapses.

Information processing in the brain depends on specialized organization of neurotransmitter receptors and scaffolding proteins within the postsynaptic density. However, how these molecules are organized in situ remains largely unknown. In this study, template-free classification of oversampled sub-tomograms was used to analyze cryo-electron tomograms of hippocampal synapses. We identified type-A GABA receptors (GABAARs) in inhibitory synapses and determined their in situ structure at 19-Å resolution. These receptors are organized hierarchically: from GABAAR super-complexes with a preferred inter-receptor distance of 11 nm but variable relative angles, through semi-ordered, two-dimensional receptor networks with reduced Voronoi entropy, to mesophasic assembly with a sharp phase boundary. These assemblies likely form via interactions among postsynaptic scaffolding proteins and receptors and align with putative presynaptic vesicle release sites. Such mesophasic self-organization might allow synapses to achieve a 'Goldilocks' state, striking a balance between stability and flexibility and enabling plasticity in information processing.

Atom Probe Tomography Analysis of Exsolved Mineral Phases.

Element diffusion rates and temperature/pressure control a range of fundamental volcanic and metamorphic processes. Such processes are often recorded in lamellae exsolved from host mineral phases. Thus, the analysis of the orientation, size, morphology, composition and spacing of exsolution lamellae is an area of active research in the geosciences. The conventional study of these lamellae has been conducted by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and more recently with focused ion beam (FIB)-based nanotomography, yet with limited chemical information. Here, we explore the use of atom probe tomography (APT) for the nanoscale analysis of ilmenite exsolution lamellae in igneous titanomagnetite from ash deposits erupted from the active Soufrière Hills Volcano (Montserrat, British West Indies). APT allows the precise calculation of interlamellar spacings (14-29 ± 2 nm) and reveals smooth diffusion profiles with no sharp phase boundaries during the exchange of Fe and Ti/O between the exsolved lamellae and the host crystal. Our results suggest that this novel approach permits nanoscale measurements of lamellae composition and interlamellar spacing that may provide a means to estimate the lava dome temperatures necessary to model extrusion rates and lava dome failure, both of which play a key role in volcanic hazard mitigation efforts.

On the derivation of an admissibility condition for phase boundary propagation in an SMA bar based on a 3-D formulation

There is some considerable difficulty in determining the solution uniquely for a propagating phase boundary in shape memory alloy (SMA) bar. In this paper, we establish an admissibility condition starting from a three-dimensional (3-D) internal-variable formulation to resolve this issue. We adopt a 3-D formulation in literature which is based on a constitutive model with specific forms of the Helmholtz free energy and dissipation rate. Then the 3-D dynamical equations are reduced to the 1-D rod equations for three phase regions (coupled with the radial effect and surface condition) by using two small parameters. Connection conditions at the phase interfaces are determined. By considering the traveling-wave solution for the rod system, we eventually derive three conditions across a sharp phase boundary corresponding to the 1-D sharp-interface model, including the two usual jump conditions and an additional condition. The third condition is then used to supplement the 1-D sharp-interface model to study an impact problem. The unique solution is constructed analytically for all possible impact velocity, including three kinds of wave patterns according to different levels of the impact velocity. The results are compared with those obtained by the maximal dissipation rate criterion.

Elasticity of akimotoite under the mantle conditions: Implications for multiple discontinuities and seismic anisotropies at the depth of ∼600–750 km in subduction zones

The equation of state and elastic properties of akimotoite at simultaneously high pressures and high temperatures are obtained using first-principles calculations based on the density functional theory (DFT). The calculated results agree with the available experimental data. Combining our results with the elastic data of other minerals, we estimated the VP, VS, and density contrasts caused by the akimotoite-related transitions. The velocity contrasts between akimotoite and bridgmanite are 4.6% and 8.3% for VP and VS, respectively, which are only about half of those between majorite and akimotoite. Moreover, because both the akimotoite-bridgmanite and majorite-akimotoite transitions have broad phase boundaries, these two phase transitions may not contribute to multiple discontinuities around ∼660 km depth in subduction zones as detected by seismic studies. Instead, the decomposition of pyrope into bridgmanite and corundum, which would occur in cold subduction zones with a sharp phase boundary and a large impedance contrast due to the inhibition of the pyroxene-garnet transformation at relatively low temperatures, could be a more reasonable explanation for the discontinuity at ∼700–750 km in subduction zones. Furthermore, the transformation from high-pressure clinopyroxene to akimotoite at the depth of ∼600 km can increase the VP, VS, and density by 10.1%, 14.8%, and 9.9%, respectively, indicating that the phase transition may account for the local discontinuity at ∼600 km in some subduction zones. In addition, the anisotropies of akimotoite are significantly higher than those of other major minerals at the base of the mantle transition zone and could be the origin of the seismic anisotropies detected in some subduction zones.

Stress generation during anisotropic lithiation in silicon nanopillar electrodes: A reactive force field study

Models that are developed to investigate lithiation-induced stress in high-volume-change electrodes are often based on continuum approaches with simplifying assumptions. In this work, we investigate stress generation during the first lithiation of crystalline silicon electrodes solely using atomistic simulations with chemo-mechanical fidelity. We use a 〈100〉-oriented silicon nanopillar as a model system and perform molecular statics simulations with a reactive force field. The simulation approach incorporates the key physical feature of the lithiation – anisotropic formation and migration of an atomistically-sharp phase boundary. The resulting stress fields show the development of hoop tension near the nanopillar surface, which drives surface fracture at angular sites between two adjacent {110} facets. This work links the atomic-level physics of the lithiation directly with the stress generation and accounts for the geometric effect of the sharp phase boundary.

Atomistic modeling and analysis of hydride phase transformation in palladium nanoparticles

Palladium-hydrogen (Pd-H) is a prototypical system for studying solute-induced phase transformation in various energy conversion and storage applications. While the behaviors of bulk Pd-H have been studied extensively, the detailed atomic picture of hydride phase transformation within individual Pd nanoparticles is still unclear. In this work, we employ a novel atomistic computational model, referred to as Diffusive Molecular Dynamics (DMD), to characterize the H absorption dynamics in Pd nanoparticles of spherical, octahedral and cubic shapes. The DMD model couples a non-equilibrium thermodynamic model with a discrete diffusion law, which allows it to reach diffusive time scales with atomic resolution. The model is capable of capturing the propagation of an atomistically sharp hydride phase boundary. A remarkable feature of the phase boundary structure that is predicted by the calculations is the emergence of misfit dislocations distributed over the interface. These dislocations relieve the elastic residual stresses induced by the change of volume that accompanies the phase transformation. Shape effects are also investigated in this work. More specifically, in both spherical and octahedral nanoparticles, we observe stacking faults during the H absorption process while the phase boundary in the cubic nanoparticle remains coherent. The spatial distribution of the stacking faults in the spherical sample is investigated in detail using an elastic core-shell model. We also identify the mechanisms that enable the movement of the stacking faults as they track the propagation of the phase boundary. Finally, we find that the rate of H absorption is reduced by the formation and movement of the stacking faults.

Dynamical localization-delocalization crossover in the Aubry-André-Harper model

Examining the Aubry-Andr\'e-Harper (AAH) model driven by periodic fields, we find a crossover between the localization and delocalization phases. This is different from the sharp phase boundary in the AAH model without drives. On the contrary, the phase boundary in the present model depends on the frequency and amplitude of the driving field. We show numerically the dependence of the phase boundary on the frequency and amplitude and reveal the physics behind the relationship. The effect of aperiodicity of the drive on the localization-delocalization crossover is also investigated by numerical simulations. The results may be useful for engineering novel phases in periodically driven systems.

An atomistic perspective on lithiation-induced stress in silicon nanopillars

We present reactive force field simulations that provide an atomistic understanding of lithiation-induced stress generation in silicon nanopillars. We investigate two-phase lithiation by developing a new protocol for simulation of formation and movement of an atomically sharp phase boundary. This protocol involves the layer-by-layer insertion of lithium atoms in the silicon lattice. The simulation results show the development of compressive stresses at the phase boundary and hoop tension near the surface of a Si nanopillar, thereby highlighting the atomistic underpinning of lithiation-induced stress. The work enables a direct mapping between atomistic and continuum modeling of lithiation-induced stress in large-volume-change electrodes.

Modeling diffusion–induced stress on two-phase lithiation in lithium-ion batteries

Abstract Capacity fade induced by chemo-mechanical degradation during charge-discharge cycles is the bottleneck in the design of high-performance batteries, especially high-capacity electrode materials. In this paper, a flexible sigmoid function is used to create the two-phase electrochemical lithiation profile, describing a sharp phase boundary that separates the pristine core from the lithiated shell of an electrode particle. According to such a phase transition, an analytical solution of the stress evolution is obtained by introducing an electrochemical reaction layer into the plastic model. Finally, based on the theory of diffusion-induced stress and the energy principle, we determine the critical thickness of radius of a lithiated layer, at which fracture occurs.

Impact induced depolarization of ferroelectric materials

We study the large deformation dynamic behavior and the associated nonlinear electro-thermo-mechanical coupling exhibited by ferroelectric materials in adiabatic environments. This is motivated by a ferroelectric generator which involves pulsed power generation by loading the ferroelectric material with a shock, either by impact or a blast. Upon impact, a shock wave travels through the material inducing a ferroelectric to nonpolar phase transition giving rise to a large voltage difference in an open circuit situation or a large current in a closed circuit situation. In the first part of this paper, we provide a general continuum mechanical treatment of the situation assuming a sharp phase boundary that is possibly charged. We derive the governing laws, as well as the driving force acting on the phase boundary. In the second part, we use the derived equations and a particular constitutive relation that describes the ferroelectric to nonpolar phase transition to study a uniaxial plate impact problem. We develop a numerical method where the phase boundary is tracked but other discontinuities are captured using a finite volume method. We compare our results with experimental observations to find good agreement. Specifically, our model reproduces the observed exponential rise of charge as well as the resistance dependent Hugoniot. We conclude with a parameter study that provides detailed insight into various aspects of the problem.

Silicate liquid immiscibility in impact melts

AbstractWe have investigated silicate emulsions in impact glasses and impact melt rocks from the Wabar (Saudi Arabia), Kamil (Egypt), Barringer (USA), and Tenoumer (Mauritania) impact structures, and in experimentally generated impact glasses and laser‐generated glasses (MEMIN research unit) by scanning electron microscopy, electron microprobe analysis, and transmission electron microscopy. Textural evidence of silicate liquid immiscibility includes droplets of one glass disseminated in a chemically distinct glassy matrix; sharp phase boundaries (menisci) between the two glasses; deformation and coalescence of droplets; and occurrence of secondary, nanometer‐sized quench droplets in Si‐rich glasses. The compositions of the conjugate immiscible liquids (Si‐rich and Fe‐rich) are consistent with phase separation in two‐liquid fields in the general system Fe2SiO4–KAlSi3O8–SiO2–CaO–MgO–TiO2–P2O5. Major‐element partition coefficients are well correlated with the degree of polymerization (NBO/T) of the Si‐rich melt: Fe, Ca, Mg, and Ti are concentrated in the poorly polymerized, Fe‐rich melt, whereas K, Na, and Si prefer the highly polymerized, Si‐rich melt. Partitioning of Al is less pronounced and depends on bulk melt composition. Thus, major element partitioning between the conjugate liquids closely follows trends known from tholeiitic basalts, lunar basalts, and experimental analogs. The characteristics of impact melt inhomogeneity produced by melt unmixing in a miscibility gap are then compared to impact melt inhomogeneity caused by incomplete homogenization of different (miscible or immiscible) impact melts that result from shock melting of different target lithologies from the crater's melt zone, which do not fully homogenize and equilibrate due to rapid quenching. By taking previous reports on silicate emulsions in impact glasses into account, it follows that silicate impact melts of variable composition, cooling rate, and crystallization history might readily unmix during cooling, thereby rendering silicate liquid immiscibility a much more common process in the evolution of impact melts than previously recognized.

Acceleration of diffusive molecular dynamics simulations through mean field approximation and subcycling time integration

Diffusive Molecular Dynamics (DMD) is a class of recently developed computational models for the simulation of long-term diffusive mass transport at atomistic length scales. Compared to previous atomistic models, e.g., transition state theory based accelerated molecular dynamics, DMD allows the use of larger time-step sizes, but has a higher computational complexity at each time-step due to the need to solve a nonlinear optimization problem at every time-step. This paper presents two numerical methods to accelerate DMD based simulations. First, we show that when a many-body potential function, e.g., embedded atom method (EAM), is employed, the cost of DMD is dominated by the computation of the mean of the potential function and its derivatives, which are high-dimensional random variables. To reduce the cost, we explore both first- and second-order mean field approximations. Specifically, we show that the first-order approximation, which uses a point estimate to calculate the mean, can reduce the cost by two to three orders of magnitude, but may introduce relatively large error in the solution. We show that adding an approximate second-order correction term can significantly reduce the error without much increase in computational cost. Second, we show that DMD can be significantly accelerated through subcycling time integration, as the cost of integrating the empirical diffusion equation is much lower than that of the optimization solver. To assess the DMD model and the numerical approximation methods, we present two groups of numerical experiments that simulate the diffusion of hydrogen in palladium nanoparticles. In particular, we show that the computational framework is capable of capturing the propagation of an atomically sharp phase boundary over a time window of more than 30 seconds. The effects of the proposed numerical methods on solution accuracy and computation time are also assessed quantitatively.