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Results for “out-of-equilibrium dynamics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Transport-based initial conditions for heavy-ion collisions at finite densities

Here, we employ the SMASH transport model to provide event-by-event initial conditions for the energy-momentum tensor and conserved charge currents in hydrodynamic simulations of relativistic heavy-ion collisions. We study the fluctuations and dynamical evolution of three conserved charge currents (net baryon, net electric charges, and net strangeness) with a four-dimensional lattice-QCD-based equation of state, NEOS-4D, in the hydrodynamic phase. Out-of-equilibrium corrections at the particlization are generalized to finite densities to ensure the conservation of energy, momentum, and the three types of charges. These theoretical developments are integrated within the X-SCAPE code as a unified framework for studying the nuclear matter properties in the Beam Energy Scan program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A brief review of spin glass magnetometry techniques

Spin glasses are inherently dynamical. Taken properly, measurements of these materials can capture their dynamics and provide a wealth of insight into the physics of the spin glass state. In this methods review, two magnetometry methods are directly compared–ac and dc. Because these measurements are taken differently, the resulting data of each method will contain different information about spin glass behavior. This review will specifically focus on how the out-of-equilibrium effects of aging, rejuvenation, and memory manifest in each of these techniques, and how to construct protocols to measure these effects. We then describe the physical significance of each type of measurement and how to interpret their results. Finally, we explicitly detail which applications are most appropriate for which method. This will help the reader select the most helpful technique to carry out their own future experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accuracy Guarantees and Quantum Advantage in Analog Open Quantum Simulation with and without Noise

Many-body open quantum systems, described by Lindbladian master equations, are a rich class of physical models that display complex equilibrium and out-of-equilibrium phenomena which remain to be understood. In this paper, we theoretically analyze noisy analog quantum simulation of geometrically local open quantum systems and provide evidence that this problem both is hard to simulate on classical computers and could be approximately solved on near-term quantum devices. First, given a noiseless quantum simulator, we show that the dynamics of local observables and the fixed-point expectation values of rapidly mixing local observables in geometrically local Lindbladians can be obtained to a precision of ϵ in time that is poly ( ϵ − 1 ) and uniform in system size. Furthermore, we establish that the quantum simulator would provide a superpolynomial advantage, in run-time scaling with respect to the target precision and either the evolution time (when simulating dynamics) or the Lindbladian’s decay rate (when simulating fixed points), over any classical algorithm for these problems, assuming BQP ≠ BPP . We then consider the presence of noise in the quantum simulator in the form of additional geometrically local Lindbladian terms. We show that the simulation tasks considered in this paper are stable to errors; i.e., they can be solved to a noise-limited, but system-size independent, precision. Finally, we establish that, assuming BQP ≠ BPP , there are stable geometrically local Lindbladian simulation problems such that, as the noise rate on the simulator is reduced, classical algorithms must take time superpolynomially longer in the inverse noise rate to attain the same precision as the analog quantum simulator. Published by the American Physical Society 2025

Kashyap, Vikram (ORCID:0000000208195207)↗
DOE OSTI2024

The ab initio amorphous materials database: Empowering machine learning to decode diffusivity

Amorphous materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven ex- ploration and design of amorphous materials is hampered by the absence of a com- prehensive database covering a broad chemical space. In this work, we present the largest computed amorphous materials database to date, generated from sys- tematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductiv- ity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching amorphous materials provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in uni- versal machine learning potentials, impacting design beyond that of non-crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The ab initio non-crystalline structure database: empowering machine learning to decode diffusivity

Non-crystalline materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven exploration and design of non-crystalline materials is hampered by the absence of a comprehensive database covering a broad chemical space. In this work, we present the largest computed non-crystalline structure database to date, generated from systematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductivity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching non-crystalline structures provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in universal machine learning potentials, impacting design beyond that of non-crystalline materials. In addition, combining diffusion trajectories from our dataset with models that predict liquidus viscosity and melting temperature could be utilized to develop models for predicting glass-forming ability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

3D pattern formation of a protein–membrane suspension

Many essential cellular processes, including cell division and the establishment of cell polarity during embryogenesis, are regulated by pattern-forming proteins. These proteins often need to bind to a substrate, such as the cell membrane, onto which they interact and form two-dimensional (2D) patterns. It is unclear how the membrane’s continuity and dimensionality impact pattern formation. Here, we address this gap using the MinDE system, a prototypical example of pattern-forming membrane proteins. We show that when the lipid substrate is fragmented into submicrometer-sized diffusive liposomes, adenosine triphosphate-driven protein–protein interactions generate three-dimensional (3D) spatially extended patterns, despite the complete loss of membrane continuity. Remarkably, these 3D patterns emerge at scales four orders of magnitude larger than the individual liposomes. By systematically varying protein concentration, liposome size, and density, we observed and characterized a variety of 3D dynamical patterns not seen on continuous 2D membranes, including traveling waves, dynamical spirals, and a coexistence phase. Simulations and linear stability analysis of a coarse-grained model revealed that the physical properties of the dispersed membrane effectively rescale both the protein–membrane binding rates and diffusion, two key parameters governing pattern formation and wavelength selection. These findings highlight the robustness of Min’s pattern-forming ability, suggesting that protein–membrane suspensions could serve as an adaptable template for studying out-of-equilibrium self-organization in 3D, beyond in vivo contexts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Interplay of quantum information, thermodynamics, and gravity in the early Universe

Our interdisciplinary proposal brought together a unique team of researchers to tackle foundational questions on the quantum origins of the Universe and out-of-equilibrium quantum systems in general. The specific goals of our proposal were as follows. First, to develop a self-consistent quantum mechanical framework for the early Universe using an open system approach, with focus on non-Markovian vs. Markovian evolution of system modes and signatures in late-time observables. Second, to explore the use of quantum resource theory and thermodynamics techniques to understand the initial conditions of the Universe. Third, to in vestigate open quantum system dynamics in strongly-coupled qubit and oscillator systems, with focus on non-Markovian evolution, entanglement dynamics, and quantum backaction, including experimental real izations and implications for gravity. And fourth, to establish thermodynamics for chaotic quantum systems, with emphasis on dynamics of information scrambling and implications for black hole solutions in AdS/CFT and quantum gravity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Kinetic Monte Carlo Framework for Coupled Degradation and Dehydration of Anion Exchange Membranes

Kinetic Monte Carlo (kMC) simulations, augmented with temporal-acceleration schemes, can efficiently handle stiff reaction-transport networks when fast processes rapidly relax to quasi-equilibrium on a fixed lattice. However, in glassy anion-exchange membranes (AEM), rare and irreversible chemical degradation events continuously reshape the nanoscale morphology, and the associated hydration and transport degrees of freedom remain far from a well-defined local equilibrium. This combination of evolving state space and nonequilibrated fast dynamics lies outside the scope of existing kMC acceleration frameworks. Here, to address this challenge, we introduce an auxiliary-particle kinetic Monte Carlo (AP-kMC) scheme. In AP-kMC, short-lived mobile particles spawned at degradation sites execute hop, water-elimination, and decay moves, enforcing rapid local relaxation of the hydration structure while preserving the stochastic rules of kMC. Parameterized with molecular-dynamics morphologies and experimental solution degradation kinetics, AP-kMC reproduces the evolution of ion-exchange capacity, water uptake, and conductivity, and reveals a feedback loop in which poorly hydrated sites degrade first and each degradation event induces further local dehydration. The resulting thinning and fragmentation of water channels cause loss of hydrophilic percolation and abrupt conductivity collapse well before complete charge loss. AP-kMC thus reframes AEM durability as a coupled degradation–drying–percolation problem and provides a transferable strategy to simulate reactive, out-of-equilibrium polymer electrolytes where local solvation controls reactivity.

organic↗
DOE OSTI2023

Photoinduced enhancement of superconductivity in the plaquette Hubbard model

Real-time dynamics techniques have proven increasingly useful in theoretically and experimentally understanding strongly correlated systems. By employing unbiased time-resolved exact diagonalization, we study pump dynamics in the two-dimensional plaquette Hubbard model, where distinct hopping integrals t h and t' h are present within and between plaquettes. In the intermediate coupling regime, a significant enhancement of d-wave superconductivity is observed and compared with that obtained by simply examining expectation values with the eigenstates of the Hamiltonian. Furthermore, our work provides a further understanding of superconductivity in the Hubbard model, extends the description of the pairing amplitude to the frequency-anisotropy plane, and offers a promising approach for experimentally engineering emergent out-of-equilibrium states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Precise Control of Dissipative Self-assembly by Light and Electricity

Nature-inspired synthetic dissipative self-assemblies have attracted much attention recently. However, it remains a major challenge to achieve precise control over dissipative supramolecular assembly structures and functions of self-contained systems. Here we combine light and electricity as two clean, and spatiotemporally addressable fuels to provide precise control over the morphology for dissipative self-assembly of a perylene bisimide glycine (PBIg) building block in a self-contained solution. In this design, electrochemical oxidation provides the positive fuel to activate PBIg self-assembly while photoreduction supplies the negative fuel to deactivate the system for disassembly. Further, through programming the two counteracting fuels, we demonstrated the control of PBIg self-assembly into a variety of assembly morphologies in a self-contained system. In addition, by exerting light and electrical dual fuels simultaneously, we could create an active homeostasis exhibiting dynamic instability, leading to morphological change to asymmetric assemblies with curvatures. Such precise control over self-assembly of self-contained systems may find future applications in programming complex active materials as well as formulating pharmaceutical reagents with desired morphologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Dynamic Transformation of High-Architectural Nanocrystal Superlattices upon Solvent Molecule Exposure

The cluster-based body-centered-cubic superlattice (cBCC SL) represents one of the most complicated structures among reported nanocrystal assemblies, comprised of 72 truncated tetrahedral quantum dots per unit cell. Our previous report revealed that truncated tetrahedral quantum dots within cBCC SLs possessed highly controlled translational and orientational order owing to an unusual energetic landscape based on the balancing of entropic and enthalpic contributions during the assembly process. However, the cBCC SL’s structural transformability and mechanical properties, uniquely originating from such complicated nanostructures, have yet to be investigated. Herein, we report that cBCC SLs can undergo dynamic transformation to face-centered-cubic SLs in response to post-assembly molecular exposure. We monitored the dynamic transformation process using in situ synchrotron-based small-angle X-ray scattering, revealing a dynamic transformation involving multiple steps underpinned by interactions between incoming molecules and TTQDs’ surface ligands. Furthermore, our mechanistic study demonstrated that the precise configuration of TTQDs’ ligand molecules in cBCC SLs was key to their high structural transformability and unique jelly-like soft mechanical properties. While ligand molecular configurations in nanocrystal SLs are often considered minor features, our findings emphasize their significance in controlling weak van der Waals interactions between nanocrystals within assembled SLs, leading to previously unremarked superstructural transformability and unique mechanical properties. Finally, our findings promote a facile route toward further creation of soft materials, nanorobotics, and out-of-equilibrium assemblies based on nanocrystal building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Investigating Fundamental Principles of Nonequilibrium Assembly Using Temperature-Sensitive Copolymers

Both natural biomaterials and synthetic materials benefit from complex energy landscapes that provide the foundation for structure–function relationships and environmental sensitivity. Understanding these nonequilibrium dynamics is important for the development of design principles to harness this behavior. Using a model system of poly(ethylene glycol) methacrylate-based thermoresponsive lower critical solution temperature (LCST) copolymers, we explored the impact of composition and stimulus path on nonequilibrium thermal hysteretic behavior. Through turbidimetry analysis of nonsuperimposable heat–cool cycles, we observe that LCST copolymers show clear hysteresis that varies as a function of pendent side chain length and hydrophobicity. Hysteresis is further impacted by the temperature ramp rate, as insoluble states can be kinetically trapped under optimized temperature protocols. As a result, this systematic study brings to light fundamental principles that can enable the harnessing of out-of-equilibrium effects in synthetic soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Information loss, mixing and emergent type III 1 factors

A manifestation of the black hole information loss problem is that the two-point function of probe operators in a large Anti-de Sitter black hole decays in time, whereas, on the boundary CFT, it is expected to be an almost periodic function of time. We point out that the decay of the two-point function (clustering in time) holds important clues to the nature of observable algebras, states, and dynamics in quantum gravity. We call operators that cluster in time “mixing” and explore the necessary and sufficient conditions for mixing. The information loss problem is a special case of the statement that in type I algebras, there exists no mixing operators. We prove that, in a thermofield double state (KMS state), if mixing operators form an algebra (close under multiplication), the resulting algebra must be a von Neumann type III 1 factor. In other words, the physically intuitive requirement that all nonconserved operators should exponentially mix is so strong that it fixes the observable algebra to be an exotic algebra called a type III1 factor. More generally, for an arbitrary out-of-equilibrium state of a general quantum system (von Neumann algebra), we show that if the set of operators that mix under modular flow forms an algebra, it is a type III1 von Neumann factor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Positional ordering induced by dynamic steric interactions in superparamagnetic rods

The dynamic motion produced by precessing magnetic fields can drive matter into far-from-equilibrium states. We predict 1D periodic ordering in systems of precessing rods when magnetic interactions between rods remain insignificant. The precession angle of the rods is completely determined by the field's precession angle and the ratio of the field's precession frequency and the characteristic response frequency of the rods. Here, we develop a molecular dynamics model that explicitly calculates magnetic interactions between particles, and we also simulate rods in the limit of a strong and fast precessing magnetic field where inter-rod magnetic interactions are negligible, using a purely steric model. Our simulations show how steric interactions drive the rods from a positionally disordered phase (nematic) to a layered (smectic) phase. As the rod precession angle increases, the nematic–smectic transition density significantly decreases. The minimization of unfavorable steric interactions also induces phase separation in binary mixtures of rods of different lengths. This effect is general to any force that produces precession in elongated particles. This work will advance the understanding and control of out-of-equilibrium soft matter systems.

42 ENGINEERING↗
DOE OSTI2024

Oversaturating Liquid Interfaces with Nanoparticle-Surfactants

Assemblies of nanoparticles at liquid interfaces hold promise as dynamic “active” systems when there are convenient methods to drive the system out of equilibrium via crowding. To this end, we show that oversaturated assemblies of charged nanoparticles can be realized and held in that state with an external electric field. Upon removal of the field, strong interparticle repulsive forces cause a high in-plane electrostatic pressure that is released in an explosive emulsification. We quantify the packing of the assembly as it is driven into the oversaturated state under an applied electric field. Finally, physiochemical conditions substantially affect the intensity of the induced explosive emulsification, underscoring the crucial role of interparticle electrostatic repulsion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Electron and muon dynamics in neutron stars beyond chemical equilibrium

A neutron star harbors $\mathcal{O}$(10 56 ) electrons in its core, and almost the same number of muons, with muon decay prohibited by Pauli blocking. However, as macroscopic properties of the star such as its mass, rotational velocity, or magnetic field evolve over time, the equilibrium lepton abundances (dictated by the weak interactions) change as well. Scenarios where this can happen include spin-down, accretion, magnetic field decay, and tidal deformation. Here, we discuss the mechanisms by which a star disrupted in one of these ways re-establishes lepton chemical equilibrium. In most cases, the dominant processes are out-of-equilibrium Urca reactions, the rates of which we compute for the first time. If, however, the equilibrium muon abundance decreases, while the equilibrium electron abundance increases (or decreases less than the equilibrium muon abundance), outward diffusion of muons plays a crucial role as well. This is true in particular for stars older than about 10 4 yrs whose core has cooled to ≲ 20 keV. The muons decay in a region where Pauli blocking is lifted, and we argue that these decays lead to a flux of Script $\mathcal{O}$(10 MeV) neutrinos. Realistically, however, this flux will remain undetectable for the foreseeable future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Neutrino Trapping and Out-of-Equilibrium Effects in Binary Neutron-Star Merger Remnants

We study out-of-thermodynamic-equilibrium effects in neutron-star mergers with 3D general-relativistic neutrino-radiation large-eddy simulations. During mergers, the cores of the neutron stars remain cold (T ~ a few MeV) and out of thermodynamic equilibrium with trapped neutrinos originating from the hot collisional interface between the stars. However, within ~2 to 3 ms matter and neutrinos reach equilibrium everywhere in the remnant massive neutron star. Furthermore, our results show that dissipative effects, such as bulk viscosity, if present, are only active for a short window of time after the merger.

79 ASTRONOMY AND ASTROPHYSICS↗