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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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1,667 records · Page 19

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)

Lake sediment heatwaves under global warming

Lake sediment heatwaves, driven by rising global temperatures, pose emerging threats to freshwater ecosystems by altering sediment thermal regimes and intensifying sediment biogeochemical processes. Here we present a global-scale assessment of lake sediment heatwaves, examining their historical patterns and projecting future trends under various climate scenarios in 41,499 representative lakes worldwide. Using daily simulated lake sediment temperatures from 1981 to 2010 and future (2071-2100) projections under three Shared Socioeconomic Pathways (SSP126, SSP370, SSP585), we investigate lake sediment heatwave characteristics, including their duration, intensity, frequency, and seasonal timing, worldwide. Our results show that lake sediment heatwaves are generally more persistent and frequent than lake surface heatwaves, with sediment heatwaves in pelagic regions experiencing a significant lag relative to surface conditions. Under future climate scenarios, sediment heatwaves are projected to intensify, with their duration and frequency increasing substantially, particularly under SSP585. These shifts could exacerbate the production of greenhouse gases like methane and increase sediment respiration rates in lakes. This study highlights the need to account for sediment heatwaves in freshwater ecosystem management and climate adaptation strategies to mitigate future impacts.

Limnology

Fingerprinting Superconductors by Disentangling Andreev and Quasiparticle Currents Across Tunable Tunnel Junctions

Tunneling Andreev reflection (TAR) spectroscopy provides a new approach to identify superconducting pairing symmetry at the atomic scale. Using atomistic superconducting transport simulations, we reveal the mechanism by which TAR can distinguish between pairing symmetries, which is complementary to traditional conductance-based techniques. In particular, owing to the additivity of the excess tunneling decay rate, the TAR spectrum is a weighted average of the contributions from quasiparticle currents, Andreev reflection, and higher-order scattering processes, and their relative weights depend on both the superconducting order parameter and the coupling strength. Within the local tunneling model, TAR dominates mid-gap conductance for s-wave superconductors, is suppressed for d-wave, and coexists with quasiparticle tunneling in sign-changing symmetries if the expectation value for the superconducting gap remains finite. Meanwhile, higher-order processes generally enhance the TAR signal when GN exceeds approximately 0.1G0. As a result, TAR provides a rich spectral fingerprint of the underlying pairing symmetry and electronic structure, enabling atomically resolved identification of unconventional superconducting states.

Maksymovych, Petro [Clemson University]

Thermo-Mechanical Phase-Field Modeling of Fracture in High-Burnup UO2 Fuels Under Transient Conditions

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO2) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits.

Chemistry

A Novel Low-Profile High-Efficiency Three-Phase Matrix Transformer

High step-down isolated DC-DC conversion from an 800 V DC bus to low-voltage, high-current outputs is required in automotive auxiliary converters and data center power supplies. In such applications, conventional transformer-based converters require large turns ratios, which increase winding resistance, leakage inductance, and magnetic height. This paper proposes a novel low-profile three-phase matrix transformer that realizes a large effective voltage ratio through flux division among multiple secondary legs, without increasing the physical turns count of each winding. As a result, the proposed structure reduces copper usage and transformer height while preserving the voltage conversion capability of a conventional three-phase transformer. Finite element analysis shows that the proposed design reduces magnetic height by 27%, ferrite volume by 34%, and copper volume by 28%. Circuit-level simulations of an 800 V/12 V,3 kW CLLLC dual-active-bridge converter further show that the lower winding resistance reduces total system loss by 91% and increases DC-DC efficiency from 82.6% to 97.6% at 3 kW output.

Inoue, Shuntaro [ORNL] (ORCID:0000000262637627)

Reconfigurable structural color by reversible switching of colloidal discoid liquid crystal alignment

Combining the effects of alternating-current (AC) electric fields and sedimentation reconfigures colloidal discoids between planar and homeotropic orientational alignments, thereby controlling the material’s structural color. Here, we self-assemble micrometer-size polystyrene discoids in an isopropanol-water mixture. After sedimentation, the discoids adopt a homeotropic alignment, with the minor axis perpendicular to the substrate. Adding an AC electric field (1 kHz) of ≥0.50 V switches the discoids to planar alignment—with the minor axis parallel to the substrate—within ∼100 s. Removing the field switches them back to homeotropic alignment within ∼300 s. Kinetic modeling of the field-induced torques yields good agreement with these measurements. The peak wavelength and intensity of the crystal’s diffraction response shift significantly upon reconfiguration; scattering simulation predicts these shifts. The reconfiguration is maintained for at least 10 cycles. This method is a simple, scalable avenue to reconfigure the optical properties of colloidal crystals produced from simple dielectric spheroids.

colloidal crystals

Collective behavior of “flexicles”

In recent years the functionality of synthetic active microparticles has edged even closer to that of their biological counterparts. However, we still lack the understanding needed to recreate at the microscale key features of autonomous behavior exhibited by microorganisms or swarms of macroscopic robots. In this study, we propose a model for a three-dimensional deformable cellular composite particle consisting of self-propelled rod-shaped colloids confined within a flexible vesicle—representing a superstructure we call a “flexicle” that couples particle deformation to the internal dynamics of the internal active components. Using molecular dynamics simulations, we investigate the collective behavior of dense systems composed of many flexicles. We show that individual flexicles exhibit shape changes upon collisions with other flexicles that lead to rearrangements of the internal active rods, which slows flexicle motion. This shape deformability gives rise to a diverse set of motility-induced phase separation phenomena and the spontaneous flow of flexicles reminiscent of the migration of cells in dense tissues. Our findings establish a foundation for designing responsive, cell-like active particles and developing strategies for controlling swarm migration and other autonomous swarm behaviors at cellular and colloidal scales.

Science & Technology - Other Topics

Geometric Delocalization in Two Dimensions

We demonstrate the existence of transient two-dimensional surfaces where a random-walking particle escapes to infinity in contrast to localization in standard flat two-dimensional space. We first prove that any rotationally symmetric two-dimensional membrane embedded in flat three-dimensional space cannot be transient. Then we formulate a criterion for the transience of a general asymmetric two-dimensional membrane. We use it to explicitly construct a class of transient two-dimensional manifolds with a nontrivial metric and height function but “zero average curvature,” which we dub “tablecloth manifolds.” The absence of the logarithmic infrared divergence of the Laplace-Beltrami operator in turn implies the absence of weak localization, nonexistence of bound states in shallow potentials, and breakdown of the Mermin-Wagner theorem and Kosterlitz-Thouless transition on the tablecloth manifolds, which may be realizable in both quantum simulators and corrugated two-dimensional materials.

Anderson localization

Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials

Using knowledge from statistical thermodynamics and crystallography, we develop an image–image translation model, called SorbIIT, that uses three-dimensional grids of adsorbate–adsorbent interaction energies as input to predict the spatially resolved loading surface of nanoporous materials over a broad range of temperatures and pressures. SorbIIT consists of a closed-form differential model for loading-surface prediction and a U-Net to generate spatial differential distributions from the energy grids. SorbIIT is trained using the energy grids and adsorbate distributions (obtained from high-throughput simulations) of 50 synthesized and 70 hypothetical zeolites and applied for predicting the adsorption of carbon dioxide, hydrogen sulfide, n-butane, 2-methylpropane, krypton, and xenon in other zeolites from 256 to 400 K. In conclusion, employing a quadratic isotherm model for the local differentiation, SorbIIT yields mean R 2 values of 0.998 for total adsorption and 0.6904 for local adsorption with a resolution of 0.2 Å, and a value of 0.721 for the structural similarity of the local loading distribution.

Sun, Yangzesheng [Univ. of Minnesota, Minneapolis,

Predicting microstructurally sensitive fatigue‐crack path in WE43 magnesium using high‐fidelity numerical modeling and three‐dimensional experimental characterization

Abstract Microstructurally small fatigue‐crack growth in polycrystalline materials is highly three‐dimensional due to sensitivity to local microstructural features (e.g., grains). One requirement for modeling microstructurally sensitive crack propagation is establishing the criteria that govern crack evolution, including crack deflection. Here, a high‐fidelity finite‐element modeling framework is used to assess the performance and validity of various crack‐growth criteria, including slip‐based metrics (e.g., fatigue‐indicator parameters), as potential criteria for predicting three‐dimensional crack paths in polycrystalline materials. The modeling framework represents cracks as geometrically explicit discontinuities and involves voxel‐based remeshing, mesh‐gradation control, and a crystal‐plasticity constitutive model. The predictions are compared to experimental measurements of WE43 magnesium samples subject to fatigue loading, for which three‐dimensional grain structures and fatigue‐crack surfaces were measured post‐mortem using near‐field high‐energy x‐ray diffraction microscopy and x‐ray computed tomography. Findings from this work are expected to improve the predictive capabilities of simulations involving microstructurally small fatigue‐crack growth in polycrystalline materials.

Engineering

Uncovering obscured phonon dynamics from powder inelastic neutron scattering using machine learning

The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional analysis methods. In this study, we present a machine learning framework designed to reveal obscured phonon dynamics from powder spectra. Using a variational autoencoder, we obtain a disentangled latent representation of spectra and successfully extract force constants for reconstructing phonon dispersions. Notably, our model demonstrates effective applicability to experimental data even when trained exclusively on physics-based simulations. The fine-tuning with experimental spectra further mitigates issues arising from domain shift. Analysis of latent space underscores the model’s versatility and generalizability, affirming its suitability for complex system applications. Furthermore, our framework’s two-stage design is promising for developing a universal pre-trained feature extractor. This approach has the potential to revolutionize neutron measurements of phonon dynamics, offering researchers a potent tool to decipher intricate spectra and gain valuable insights into the intrinsic physics of materials.

domain adaptation

Biochemical properties of glycerol kinase from the hypersaline-adapted archaeon Haloferax volcanii

ABSTRACT Extremophilic microorganisms are promising candidates for industrial and analytical biocatalysis.Haloferax volcanii, a halophilic archaeon that prefers glycerol over glucose, channels this substrate into central metabolism through glycerol kinase (GK). Here, we report the biochemical properties ofH. volcaniiGK and its potential for biotechnological applications. An N-terminal His-tagged GK was functionalin vivoand yielded 3 mg/L culture—4.5 times more enzyme than a C-terminal StrepII-tagged version. Size exclusion chromatography revealed a glycerol-induced oligomeric shift from homodimer to a dimer-dominant state with detectable tetramer. The purified enzyme showed robust activity across broad pH and salinity ranges, with optimal activity at 100 mM NaCl and 50°C–60°C. It retained catalytic activity in 5%–10% dimethyl sulfoxide (DMSO) and crude glycerol containing methanol. His-GK was freeze-thaw stable and thermotolerant in 2 M NaCl buffers. In the absence of ligands, the enzyme’s melting temperature (T m ) was 80°C. Glycerol increased the T m to 85°C, and combinations with MgCl₂ (84°C) or ATP (88°C) provided further stabilization. The highest T m (89°C) occurred with all three ligands, suggesting a cumulative stabilizing effect. Kinetic analyses revealed positive cooperativity for glycerol, ATP, and Mg² + ; Mn² + and Co² + also supported the activity.H. volcaniiGK is the first known GK to exhibit positive cooperativity with glycerol and ATP. Its high stability and substrate flexibility support its use in biodiesel waste valorization,in vitrobiocatalysis, and biosensor development—applications demanding robust, specific, and stable enzymes. IMPORTANCE This study reveals thatH. volcaniiGK exhibits positive cooperativity for glycerol, ATP, and Mg² + , a kinetic feature not previously reported for glycerol kinases. This behavior enables steep, switch-like responses to small substrate changes, offering unique advantages for biosensor design. Importantly,H. volcaniiGK also maintains high activity under extreme salinity, temperature, broad pH, and solvent conditions that typically limit enzyme use in industrial and environmental applications. These traits make this GK an ideal candidate for enzyme-based biosensors, which often suffer from poor tolerance to pH, solvent, and thermal stress. Its robustness supports its use in cross-linked enzyme crystals, an immobilization method that enhances enzyme stability and reusability under harsh conditions. Moreover, GKs are already employed in Mg² + detection kits; however,H. volcaniiGK’s ability to tolerate and respond to diverse divalent cations (e.g., Co² + , Mn² + ) broadens their potential for pollutant detection and environmental monitoring. These features collectively positionH. volcaniiGK as a valuable biocatalyst for biosensing,in vitrodiagnostics, and biotechnological applications requiring both precision and durability.

Biotechnology & Applied Microbiology

Elimination of detrimental grain boundary segregation in garnets

Garnet Li 7 La 3 Zr 2 O 12 electrolyte is considered a key enabler of solid-state batteries with Li metal electrodes, but the grain boundaries impair its performance. To date, the understanding of grain boundary structures and its impact on performance remains elusive. Here, we show that element segregation at Li 7 La 3 Zr 2 O 12 grain boundaries critically governs Li transport and nucleation. During conventional sintering, Al, Ta, and La segregate at grain boundaries, locally depleting Li and creating space-charge layers that lower total ionic conductivity. Simultaneously, this segregation leads to higher electronic conductivity along grain boundaries, which promotes Li nucleation at grain boundary edges with increased risk of dendrite formation. The underlying mechanism of segregation is governed by both thermodynamic driving forces and diffusion kinetics. Building on this understanding, we develop a strategy to achieve segregation-free grain boundaries through a rapid sintering protocol that utilizes the onset of solid-state softening. This approach yields transparent, polycrystalline Li 7 La 3 Zr 2 O 12 with negligible grain boundary impedance and enhanced dendrite tolerance. By elucidating the structural origins and electrochemical consequences of grain boundary segregation, this work provides a guidance for the rational optimization of solid electrolytes.

Energy - Storage

Three-chamber electrochemical reactor for selective lithium extraction from brine

Efficient lithium recovery from geothermal brines is crucial for the battery industry. Current electrochemical separation methods struggle with the simultaneous presence of Na + , K + , Mg 2+ , and Ca 2+ because these cations are similar to Li + , making it challenging to separate effectively. We address these challenges with a three-chamber reactor featuring a polymer porous solid electrolyte in the middle layer. This design improves the transference number of Li + (t Li+ ) by 2.1 times compared to the two-chamber reactor and also reduces the chlorine evolution reaction, a common side reaction in electrochemical lithium extraction, to only 6.4% in Faradaic Efficiency. Employing a lithium-ion conductive glass ceramic (LICGC) membrane, the reactor achieved high t Li+ of 97.5% in LiOH production from simulated brine, while the concentrations of Na + K + , Mg 2+ , and Ca 2+ are below the detection limit. Electrochemical experiments and surface analysis elucidated the cation transport mechanism, highlighting the impact of Na + on Li + migration at the LICGC interface.

Science & Technology - Other Topics

Phosphorylation toggles the SARS-CoV-2 nucleocapsid protein between two membrane-associated condensate states

Abstract The Nucleocapsid protein (N) of SARS-CoV-2 plays a critical role in the viral lifecycle by regulating RNA replication and by packaging the viral genome. N and RNA phase separate to form condensates that may be important for these functions. Both functions occur at membrane surfaces, but how N toggles between these two membrane-associated functional states is unclear. Here, we reveal that phosphorylation switches how N condensates interact with membranes, in part by modulating condensate material properties. Our studies also show that phosphorylation alters N’s interaction with viral membrane proteins. We gain mechanistic insight through structural analysis and molecular simulations, which suggest phosphorylation induces a conformational change in N that softens condensate material properties. Together, our findings identify membrane association as a key feature of N condensates and provide mechanistic insights into the regulatory role of phosphorylation. Understanding this mechanism suggests potential therapeutic targets for COVID infection.

Science & Technology - Other Topics

Improved constraints on hematite refractive index for estimating climatic effects of dust aerosols

Abstract Uncertainty in desert dust composition poses a big challenge to understanding Earth’s climate across different epochs. Of particular concern is hematite, an iron-oxide mineral dominating the solar absorption by dust particles, for which current estimates of absorption capacity vary by over two orders of magnitude. Here, we show that laboratory measurements of dust composition, absorption, and scattering provide valuable constraints on the absorption potential of hematite, substantially narrowing its range of plausible values. The success of this constraint is supported by results from an atmospheric transport model compared with station-based measurements. Additionally, we identify substantial bias in simulating hematite abundance in dust aerosols with current soil mineralogy descriptions, underscoring the necessity for improved data sources. Encouragingly, the next-generation imaging spectroscopy remote sensing data hold promise for capturing the spatial variability of hematite. These insights have implications for enhancing dust modeling, thus contributing to efforts in climate change mitigation and adaptation.

Environmental Sciences & Ecology

The CP-PAW Code Package for First-Principles Calculations from a User’s Perspective

CP-PAW is a combined electronic structure and ab initio molecular dynamics code to perform mixed quantum and classical simulations of atomistic condensed phase systems, such as solids, liquids, and molecular systems. As the name suggests, the CP-PAW code unifies the all-electron projector augmented-wave (PAW) method with the Car–Parrinello (CP) approach to determine not only the electronic and nuclear ground states of condensed matter but also to study their properties and dynamics. In addition to briefly outlining the underlying theory, the focus will be on the unique aspects of CP-PAW and how to correctly employ them as a user. How to install CP-PAW using the new build system will also be briefly mentioned.

Blöchl, Peter E [Institute for Theoretical Physic

Entanglement Structure of Non-Gaussian States and How to Measure It

Rapidly growing capabilities of quantum simulators to probe quantum many-body phenomena require new methods to characterize increasingly complex states. Here, we present a protocol that constrains quantum states using experimentally measured correlation functions. This method enables measurement of a quantum state’s entanglement structure, opening a new route to study entanglement-related phenomena. Our approach extends Gaussian state parameterizations by systematically incorporating higher-order correlations. We show the protocol’s usefulness in conjunction with current and forthcoming experimental capabilities, focusing on weakly interacting fermions as a proof of concept. Here, the lowest nontrivial expansion quantitatively predicts early time thermalization dynamics, including signaling the onset of quantum chaos indicated by the entanglement Hamiltonian.

Fermi gases