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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Krylov Subspace Methods for Quantum Dynamics with Time-Dependent Generators

Krylov subspace methods in quantum dynamics identify the minimal subspace in which a process unfolds. To date, their use is restricted to time evolutions governed by time-independent generators. Here, we introduce a generalization valid for driven quantum systems governed by a time-dependent Hamiltonian that maps the evolution to a diffusion problem in a one-dimensional lattice with nearest-neighbor hopping probabilities that are inhomogeneous and time dependent. This representation is used to establish a novel class of fundamental limits to the quantum speed of evolution and operator growth. We also discuss generalizations of the algorithm, adapted to discretized time evolutions and periodic Hamiltonians, with applications to many-body systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Understanding and Controlling the Formation of Nonradiative Defects in Blue Organic Triplet Emitters

Phosphorescent organic light-emitting devices (PHOLEDs) suffer from destructive molecular processes due to triplet-polaron and triplet-triplet annihilation. These processes are energetically driven and hence are particularly active in decreasing the lifetime of blue PHOLEDs. It has recently been shown that increasing triplet radiative rates via the Purcell effect effectively extends the device operational lifetime by reducing the triplet radiative lifetime, thus decreasing their density and the probability of triplet-annihilation reactions. We provide an analytical framework using Marcus theory to explain the observed, approximately exponential relationship between exciton energy and device lifetime. From transient drift-diffusion dynamics, we show that the Purcell effect reduces the exciton density in the steady state and increases the photoluminescent yield, thereby reducing defect generation rates and extending the device lifetime. We control the radiative rate of excitons in microcavities, thereby connecting the exciton energy and decay rates with the observed device lifetime. The device lifetime is shown to follow a power-law dependence on the Purcell factor ( PF m ) with m = 1.5 to 2.5, dependent on the TTA-to-TPA ratio and photoluminescence quantum yield. From our analysis, a fivefold increase in PF has the potential to extend the blue PHOLED lifetime by up to 2 orders of magnitude, making the blue PHOLED lifetime comparable to that of state-of-the-art green PHOLEDs. Published by the American Physical Society 2024

Zhao, Haonan (ORCID:0000000190584422)↗
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 OSTI2024

Designing Particle Morphologies for Materials with Solid Transport Limitations: A Case Study of Lithium and Manganese Rich Cathode Oxides

A lithium and manganese rich nickel-manganese-cobalt oxide (LMR-NMC) cathode is a promising candidate for next-generation batteries due to its high specific capacity, low cost, and low cobalt content. However, the material suffers from poor rate capability due to the diffusion limitations of lithium in the cathode particles. Understanding the material performance requires careful control of the morphology of the cathode particles, taking into account the primary and agglomerated diffusion pathways and the presence of pores, some of which could be closed from electrolyte infiltration. Here, in this study, we use a microstructure-based mathematical model combined with experimental data to understand the role of the complex cathode particle morphology in the rate performance of the material. Scanning electron microscopy images of cathodes made under different synthesis conditions, which results in different agglomerate morphologies, serve as the input into the mathematical model. The model is then compared to rate data to understand the controlling parameters. The presence of intra-agglomerate closed pores results in a large agglomerate diffusion length in comparison to the ideal condition, where the primary particles are agglomerated in an open and dispersed manner such that the entire interfacial area is available for electrochemical reaction. Smaller primary and agglomerate diffusion lengths result in better electrochemical performance. This points us toward designing the morphology of the cathode particles to compensate for the diffusion limitation of LMR-NMC while maximizing the density.

Tewari, Deepti↗
DOE OSTI2024

Simulative Prediction of Solar Illuminance and Application of the Du-Sharples Model in Estimating Adapted Daylighting Metrics for an Urban Environment

The practice of daylighting in indoor spaces can significantly reduce electricity consumption and carbon emissions, improve human productivity, and enhance mood and cognitive perception. This work discussed the recent developments in daylighting science and practice, computed the periodic variations in average diurnal daylight levels for each month, quantified in terms of global horizontal illuminance and diffuse horizontal illuminance, for Kolkata, India, a city with tropical wet and dry climate, with two empirical luminous efficacy models of estimating solar illuminance, and assessed daylighting metrics with the Du-Sharples model. A program was formulated that could compute and generate daylight data with monthly-hourly solar irradiation data and the Du-Sharples model was utilized to predict dirt-corrected daylighting metrics for three glazing transmittance values and five elemental carbon deposition levels on glazing material. The highest monthly average global horizontal illuminance is recorded in April (64.05 klx for Littlefair model and 66.82 klx for Muneer-Kinghorn model) and the highest monthly average diffuse horizontal illuminance is recorded in July (33.23 klx for Littlefair model and 30.63 klx for Muneer-Kinghorn model). Further, the computed yearly average global and diffuse horizontal illuminance levels agree well with a previous study that applied the Perez model. Yearly average horizontal work surface illuminance level remained >1.5 klx for window-towall area ratio >30 %. The approach adopted in this work and the temporal variation charts of computed exterior daylight level data may assist building service engineers, architects, and indoor lighting practitioners in making informed policy decisions at different stages of building planning.

Engineering↗
DOE OSTI2024

In situ visualisation of zeolite anisotropic framework flexibility during catalysis

Zeolites exhibit framework flexibility driving their chemical and catalytic properties. Since the zeolitic pores are extremely small, a slight strain generated in the crystal induces compelling changes in shape, connectivity, accessibility, and the framework chemical properties. These modifications affected the adsorption and desorption of reactants/products and the diffusion within the channels during reaction. Using in situ 3D Bragg coherent X-ray diffraction imaging, we unveil the dynamics of the zeolite structure during catalysis, contraction and/or expansion of its framework also known as zeolite framework flexibility. Here, we imaged three-dimensionally a single faujasite zeolite crystal during the ethanol dehydration reaction revealing anisotropic lattice dynamics simultaneously to guest molecules formation. Understanding zeolite flexibility could permit to tune zeolites properties towards potentially higher adsorption and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Forced 3D Reconnection in an Exponentially Separating Magnetic Field

We present a solvable scenario for 3D reconnection in a sheared magnetic field. We consider a localized external force that is applied slowly to a flux tube and then maintained, generating an Alfvénic perturbation that spreads along the field lines. Separation of the sheared field lines reduces the scale of the perturbation across the field, enhancing magnetic diffusion. For a fusion-motivated equilibrium with exponential field-line separation, we find a reconnection timescale proportional to 𝒮/ ln⁡ 𝒮 under magnetohydrodynamics (MHD) and to 𝒮 1/3 for semicollisional electron-only reconnection, where 𝒮 is the Lundquist number of the perturbed flux tube. We generalize these results to arbitrary magnetic geometries, showing that the semicollisional case is geometry independent. Interestingly, we find that slower field-line separation yields an increased reconnection rate in MHD.

Magnetic confinement fusion↗
DOE OSTI2024

Exploring Li-Ion Transport Properties of Li 3 TiCl 6 : A Machine Learning Molecular Dynamics Study

We performed large-scale molecular dynamics simulations based on a machine-learning force field (MLFF) to investigate the Li-ion transport mechanism in cation-disordered Li 3 TiCl 6 cathode at six different temperatures, ranging from 25°C to 100°C. In this work, deep neural network method and data generated by ab − initio molecular dynamics (AIMD) simulations were deployed to build a high-fidelity MLFF. Radial distribution functions, Li-ion mean square displacements (MSD), diffusion coefficients, ionic conductivity, activation energy, and crystallographic direction-dependent migration barriers were calculated and compared with corresponding AIMD and experimental data to benchmark the accuracy of the MLFF. From MSD analysis, we captured both the self and distinct parts of Li-ion dynamics. The latter reveals that the Li-ions are involved in anti-correlation motion that was rarely reported for solid-state materials. Similarly, the self and distinct parts of Li-ion dynamics were used to determine Haven’s ratio to describe the Li-ion transport mechanism in Li 3 TiCl 6 . Obtained trajectory from molecular dynamics infers that the Li-ion transportation is mainly through interstitial hopping which was confirmed by intra- and inter-layer Li-ion displacement with respect to simulation time. Ionic conductivity (1.06 mS/cm) and activation energy (0.29eV) calculated by our simulation are highly comparable with that of experimental values. Overall, the combination of machine-learning methods and AIMD simulations explains the intricate electrochemical properties of the Li 3 TiCl 6 cathode with remarkably reduced computational time. Thus, our work strongly suggests that the deep neural network-based MLFF could be a promising method for large-scale complex materials.

Selvaraj, Selva Chandrasekaran (ORCID:000000029023↗
DOE OSTI2025

A cost-effective all-in-one halide material for all-solid-state batteries

All-solid-state batteries require advanced cathode designs to realize their potential for high energy density and economic viability. Integrated all-in-one cathodes, which eliminate inactive conductive additives and heterogeneous interfaces, hold promise for substantial energy and stability gains but are hindered by materials lacking sufficient Li + /e − conductivity, mechanical robustness and structural stability. Here, in this work, we present Li 1.3 Fe 1.2 Cl 4 , a cost-effective halide material that overcomes these challenges. Leveraging reversible Fe 2+ /Fe 3+ redox and rapid Li + /e − transport within its framework, Li 1.3 Fe 1.2 Cl 4 achieves an electrode energy density of 529.3 Wh kg −1 versus Li + /Li. Critically, Li 1.3 Fe 1.2 Cl 4 shows unique dynamic properties during cycling, including reversible local Fe migration and a brittle-to-ductile transition that confers self-healing behaviour. This enables exceptional cycling stability, maintaining 90% capacity retention for 3,000 cycles at a rate of 5 C. Integration of Li 1.3 Fe 1.2 Cl 4 with a nickel-rich layered oxide further increases the energy density to 725.6 Wh kg −1 . By harnessing the advantageous dynamic mechanical and diffusion properties of all-in-one halides, this work establishes all-in-one halides as an avenue for energy-dense, durable cathodes in next-generation all-solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Time-Domain Extreme-Ultraviolet Diffuse Scattering Spectroscopy of Nanoscale Surface Phonons

Here, we report the observation of dynamic fringe patterns in the diffuse scattering of extreme ultraviolet light from surfaces, following femtosecond optical excitation. At each point on the detector, the diffuse scattering intensity exhibits oscillations at well-defined frequencies that correspond to surface phonons with wave vectors determined by the scattering geometry, indicating that the optical excitation generates coherent surface phonons propagating in all directions and spanning a wavelength range from 60 to 300 nm. This phenomenon is observed on a variety of samples, including single-layer and multilayer metal films, as well as bulk semiconductors. The measured surface phonon dispersions show good agreement with theoretical calculations. By comparing signal amplitudes from samples with different surface morphologies, we find that the excitation mechanism is linked to the natural surface roughness of the samples. However, the signal is still detectable on extremely smooth surfaces with subnanometer roughness. Our findings demonstrate a simple and effective method for optically exciting coherent surface phonons with nanoscale wavelengths on a wide range of solid samples and establish a foundation for surface phonon spectroscopy in a wave vector range well beyond the limit of conventional surface Brillouin scattering.

Capotondi, F. [Elettra-Sincrotrone Trieste (Italy)↗
DOE OSTI2024

Nanometer-Scale Acoustic Wave Packets Generated by Stochastic Core-Level Photoionization Events

We demonstrate that the absorption of femtosecond hard x-ray pulses excites quasispherical, high-amplitude, and high-wave-vector coherent acoustic phonon wave packets using an all hard-x-ray pump-probe scattering experiment. The time- and momentum-resolved diffuse scattering signal is consistent with an ensemble of 3D strain wave packets induced by the rapid electron cascade dynamics following photoionization at uncorrelated excitation centers. We quantify key parameters of this process, including the localization size of the stress field and the photon energy conversion efficiency into elastic energy. The parameters are determined by the photoelectron and Auger electron cascade dynamics, as well as the electron-phonon interaction. In particular, we obtain the localization size of the observed strain wave packet to be 1.5 and 2.5 nm for bulk SrTiO 3 and KTaO 3 single crystals, respectively. The results provide crucial information on the mechanism of x-ray energy deposition into matter and shed light on the shortest collective length scales accessible to coherent acoustic phonon generation using x-ray excitation. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2024

Phase-Selective Synthesis of Rhombohedral WS 2 Multilayers by Confined-Space Hybrid Metal–Organic Chemical Vapor Deposition

Rhombohedral polytype transition metal dichalcogenide (TMDC) multilayers exhibit non-centrosymmetric interlayer stacking, which yields intriguing properties such as ferroelectricity, a large second-order susceptibility coefficient χ (2) , giant valley coherence, and a bulk photovoltaic effect. These properties have spurred significant interest in developing phase-selective growth methods for multilayer rhombohedral TMDC films. Here, in this study, we report a confined-space, hybrid metal–organic chemical vapor deposition method that preferentially grows 3R-WS 2 multilayer films with thickness up to 130 nm. We confirm the 3R stacking structure via polarization-resolved second-harmonic generation characterization and the 3-fold symmetry revealed by anisotropic H 2 O 2 etching. The multilayer 3R WS 2 shows a dendritic morphology, which is indicative of diffusion-limited growth. Multilayer regions with large, stepped terraces enable layer-resolved evaluation of the optical properties of 3R-WS 2 via Raman, photoluminescence, and differential reflectance spectroscopy. These measurements confirm the interfacial quality and suggest ferroelectric modification of the exciton energies.

3R-WS2↗
DOE OSTI2025

Cation selectivities in zwitterion grafted nanopores: effect of zwitterion architecture

Selective separation of monovalent cations is a critical challenge in applications such as water purification and lithium recovery from salt brines. Cross-linked zwitterionic amphiphilic copolymer (ZAC-X) membranes have gained attention for their exceptional anion permselectivity, attributed to self-assembled zwitterion-lined nanodomains that interact preferentially with anions according to their hydrated radii r hyd . However, these membranes show minimal selectivity among monovalent cations, despite significant differences in their hydration structures, motivating studies on the underlying mechanisms of cation transport and selectivity in this family of materials. In this study, we conducted molecular dynamics simulations of aqueous salt solutions within zwitterion-functionalized nanopores to elucidate the influence of dipole orientation of the zwitterionic (ZI) ligands on cation diffusivities, partitioning, and permeabilities. To this end, we examined two contrasting ZI ligand architectures: Motif A (surface–cation–anion, S–ZI + –ZI − ) and Motif B (surface–anion–cation, S–ZI − –ZI + ). Our results show that in Motif A, the sulfonate groups of the ZI ligands are localized near the pore center radially, leading to strong electrostatic interactions with small bare cations (Mg 2+ and Li + ). This configuration results in high cation partitioning but low cation diffusion, maintaining solution-diffusion tradeoff typical of functionalized membranes. In contrast, Motif B show that sulfonate groups shift radially toward the mid-region of the pore. This shift, especially for small bare cations, introduces steric constraints that weaken their interactions with the sulfonate groups, thereby enhancing hydration and lowering partitioning, while still maintaining their low self-diffusivity. These findings establish zwitterion dipole orientation as a powerful design lever for tuning cation selectivity in membrane systems and offer molecular-level insights for engineering next-generation ion separation materials.

Morishita, Kazuya [Univ. of Texas, Austin, TX (Uni↗
DOE OSTI2024

Accelerated Irradiation and Qualification of Ceramic Nuclear Fuels

Accelerated irradiation efforts are an important topic in accelerated qualification of new nuclear fuel concepts for light water reactor (LWRs), microreactors, and other special purpose reactors. Accelerated fuel qualification combines both experimental and modeling work to expedite the total qualification time from approximately 20-25 years to 5-10 years timeframe. The scope covered under the current work package focuses on the experimental contributions for the neutron irradiations. Accelerated irradiation aims to reduce the total time needed for neutron irradiation to achieve targeted burnup, which is timely using conventional irradiation profiles. The purpose of this report is to detail the samples preparation for such irradiations, which contain standard, medium, and large grain undoped UO 2 , as well as large grain, Cr 2 O 3 -doped UO 2 . The data that will be generated from the irradiation of these samples will yield important information regarding fission gas retention as a function of grain size and the effect that Cr dopants have on diffusivity of fission gases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Automated shaker placement and regularized input estimation for MIMO testing.

Multi-input, multi-output (MIMO) testing is used in component qualification to reproduce operational responses in the laboratory. It is often preferred to single-input and base-shake testing because of the potential for equivalent or better tests using smaller actuators and shorter test suites. Given a target response, two key steps in MIMO test design are selecting actuator locations and solving for input loads. Actuator locations are often manually selected using expert judgment. If an automatic method is used, locations are usually determined by simulating the vibration control problem and minimizing a combination of the input energy and control residuals. To select a configuration, the relative importance of input energy and residuals must be specified. Specifying relative weights is, in general, a manual and subjective process. This paper develops an objective function that compares actuator configurations based on control accuracy and required input energy without any manual parameter tuning. The objective function uses an optimally selected tradeoff parameter for each candidate configuration. To choose actuator locations using the new objective function, a pivoting algorithm for integer programming problems is developed. Starting with an initial configuration (such as the one generated by a greedy algorithm), the pivoting algorithm guarantees an objective function decrease in each iteration until convergence is reached. In a simulation featuring a structure excited by a diffuse acoustic field, electrodynamic shaker locations and regularized inputs are solved for without any analyst-specified parameters. Simulations are performed in MIMO configurations where the number of target responses is less than, equal to, and greater than the number of actuators.

Multi-input multi-output↗
DOE OSTI2026

Full-stack Quantification of Variability in Predicting Ion Transport Properties using Machine-learned Interatomic Potentials

Machine-learned interatomic potentials (MLIPs) have become the state-of-the-art for performing accurate, scalable molecular dynamics (MD) simulations. It is therefore crucial to understand and quantify the reliability of MLIPs for downstream property predictions. Uncertainty in predicted properties can arise from limitations in first-principles training data, intrinsic MLIP model errors in representing the data, and the statistical noise introduced during subsequent MD simulations. Using ion transport in Li7P3S11 as a case study, we systematically assess the impact of training set size and selection, neural network stochasticity, and MD sampling statistics on predicted diffusivity and activation energy. We find that when using equivariant MLIP architectures with standard MD protocols, uncertainty arising from MD sampling dominates over model-induced errors. In contrast, MLIP errors relative to the underlying first-principles data are consistently minor. Given this, there are two main routes to improving the accuracy of predictions based on MLIP potentials: adopting higher accuracy reference data generation methods, and improving the MD sampling statistics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Self-generated electrokinetic flows from active-charged boundary patterns

We develop a hydrodynamic description of self-generated electrolyte flow in capillaries whose bounding walls feature nonuniform distributions of charge nonuniform active ionic fluxes. The hydrodynamic velocity arising in such a system has components that are forbidden by symmetry in the absence of charge and fluxes. However, when these two boundary mechanisms are simultaneously present, they can lead to a symmetry broken state where steady flows with both unidirectional and circulatory components emerge. We show that these flow states arise when modulated boundary patterns of charge and fluxes are offset by a flux-charge phase difference, which is associated with the separation between sites of their peak densities on the wall. Mismatch in diffusivity of cationic and anionic species can modify the flow states and becomes an enhancing factor when fluxes of both ion species are being produced together at the same site. We demonstrate that this mechanism can be realized with a microfluidic generator that is powered by enzyme-coated patches that catalyze reactants in the solution to produce fluxes of ions. The local ionic elevation or depletion, which disrupts a nonuniform double layer, promotes self-induced gradients yielding persistent body forces to generate bulk fluid motion. Our work quantifies a boundary-driven mechanism behind self-sustained electrolyte flow in confined environments that exists without any external bulk-imposed fields or gradients. It provides a theoretical framework for understanding the combined effect of active and charged boundaries that are relevant in biological or soft matter systems, and can be utilized in electrofluidic and iontronic applications.

active matter↗