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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dynamic entity formed by protein and its hydration water

The interaction between protein and water plays a pivotal role in shaping the structure, dynamics, and function of biomacromolecules. A comprehensive understanding of this intricate interplay necessitates a systematic evaluation of interaction strength and its consequential impact on the dynamics of proteins and water across diverse protein systems. Despite numerous works on understanding the dynamics of water and proteins and the coupling between them, there are still unanswered questions. Here, we combine neutron scattering and isotope labeling to probe the dynamics of proteins and their hydration water in a variety of protein systems. We consider proteins of different structures and varying thermostability as well as proteins within living cells with distinct growth temperatures. Simultaneous characterization of protein and hydration water dynamics across diverse systems was achieved. Moreover, we performed water sorption isothermal measurements on three representative proteins to correlate the observed dynamics with the strength of the interaction energies governing each system. The experimental results underscore that proteins manifesting stronger attractive interactions with water display diffusionlike dynamics with higher flexibility upon hydration, concomitant with a reduced mobility in hydration water. Significantly, our findings suggest that, in fact, it is the interaction between protein and its hydration water that facilitates the transfer of mobility from water to protein, with stronger interactions correlating to greater protein flexibility and slower hydration water diffusion. Published by the American Physical Society 2024

Ye, Yongfeng (ORCID:0009000792374198)↗
NASA NTRSDate not supplied

A Holistic Approach to Procedures

Aviation is a dynamic industry which is constantly changing. These changes require the continuous update of people’s knowledge and skills. A fundamental part of that knowledge and skill is procedures, because procedures form the backbone of aviation operations. On the flightdeck, on the ramp, and in the maintenance shop, procedures and checklists help support pilots, line crews, and mechanics in performing their work effectively, efficiently, and thus -- safely. To design effective and efficient procedures and checklists, one must take into account the full operational context within which these procedures are embedded. This context is defined by the requirements of the technology, the capabilities and limitations of the human operators, and the constraints and affordances of the operational environment. The complexity of this context arises from the interactions of the human, machine, and environment. Procedures are in place to govern those interactions. We present a model of that operational context, namely THE Model (Technology, Human, Environment in the context of a Mission), that lays a foundation for the analysis of each of these elements and their interactions. But procedures have their limitations, and there are risks involved in over-proceduralizing. To understand these limitations and risks, and to determine when to proceduralize and when not, we present the 4P Framework (Practice, Procedures, Policies, Philosophy) as a holistic approach to procedures. This approach brings together the understanding of human behavior, of organizational and operational factors, and of the technologies involved.

procedures↗
DOE OSTI2026

Characterization and automated optimization of laser-driven proton beams from converging liquid sheet jet targets

Compact, stable, and versatile laser-driven ion sources hold great promise for applications ranging from medicine to materials science and fundamental physics. While single-shot sources have demonstrated favorable beam properties, including the peak fluxes necessary for several applications, high-repetition-rate operation will be necessary to generate and sustain the high average flux needed for many of the most exciting applications of laser-driven ion sources. Further, to navigate through the high-dimensional space of laser and target parameters toward experimental optima, it is essential to develop ion acceleration platforms compatible with machine learning techniques and capable of autonomous real-time optimization. Here, we present a multi-Hz ion acceleration platform employing a liquid sheet jet target. We characterize the laser-plasma interaction and the laser-driven proton beam across a variety of key parameters governing the interaction using an extensive suite of online diagnostics. We also demonstrate real-time, closed-loop optimization of the ion beam maximum energy by tuning the laser wave front using a Bayesian optimization scheme. This approach increased the maximum proton energy by 11% compared to a manually optimized wave front by enhancing the energy concentration within the laser focal spot, demonstrating the potential for closed-loop optimization schemes to tune future ion accelerators for robust high-repetition-rate operation.

Glenn, G. D. [SLAC National Accelerator Laboratory↗
DOE OSTI2020

Grid-Interactive Efficient Buildings: An Introduction for State and Local Governments

This report describes grid-interactive efficient buildings in the context of state and local government interests; highlights trends, challenges and opportunities for demand flexibility; provides an overview of valuation and performance assessments for demand flexibility; and outlines actions that state and local governments can take, in concert with utilities, regional grid operators, and building owners, to advance demand flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

dynamics of organic-mineral interactions at the metal oxide-solution interface as studied via binding energetics (Final report)

This project focused on addressing longstanding fundamental and experimental uncertainties on how dissolved organic substances (DOS) interact with metal oxide surface under environmentally relevant conditions. By leveraging a custom-built real-time, in-tandem flow adsorption microcalorimetry-UV-Vis/fluorescence spectroscopy platform, we characterized the binding energetics, kinetics and mechanistic pathways driving DOS-metal oxide interactions at temporal resolution on the order of 1-5 seconds. We studied a diverse suite of model organic compounds/substances – including monocarboxylates (e.g. acetate and benzoate), di-carboxylates (oxalate and succinate), amino acids, amino-based nanparticles and natural organic matter – interacting at the mineral-water interface of structurally- and/or chemically distinct metal oxides (including SiO2, boehmite, ferrihydrite, and γ-Al2O3). Our results indicated that DOS-metal oxide interactions are governed by multi-step reaction pathways, often switching between distinct, resolvable enthalpy- and entropy-driven non-electrostatic or electrostatic configurations. To quantify these interactions, we developed and implemented an analytical workflow that integrates peak deconvolution and Monte-Carlo based error propagation to determine site-specific thermodynamic and kinetic parameters for individual binding/debinding events. In addition to resolving apparent first-order rate constants of each event, we were able to quantify associated apparent equilibrium constants as well as free energy, enthalpy and entropy contribution to the activation and subsequent progression of the binding/debinding process across compounds, compound class and metal oxide surfaces. The kinetic-thermodynamic data produced in this study captured how the interplay between oxide surface reactivity and DOS molecular structure jointly drives binding-debinding dynamics. Notably, that at pH below PZC of the oxide surface, neutral species were heavily involved in monocarboxylate binding, while anionic species drove dicarboxylate binding. Also, that among amino acids 1) positional isomers show distinctive binding characteristics to each other while enantiomers show no significant differences in binding characteristics, 2) molecules that bind via outer-sphere complexation show a larger entropic shift between binding and debinding with no impact on oxide surface while 3) inner-sphere interactions increased anion exchange capacity of the oxide surface. The new insights and data from this work has great potential for improving predictive modeling of carbon dynamics and specifically organic-mineral interactions in environmental and industrial systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

U-net architected deep material network training with microstructure local field information

The Deep Material Network (DMN) has recently emerged as a powerful reduced-order modeling framework for simulating the mechanical response of heterogeneous materials such as composites. Unlike most data-driven approaches that directly learn a material’s response under prescribed loading, the DMN acts as a homogenization operator, learning the kinematic constraints and mechanical interactions of the underlying microstructure. However, traditional DMN training relies exclusively on homogenized effective properties derived from Direct Numerical Simulations (DNS), discarding the rich local field data that govern microstructural interactions. In this work, we extend the DMN framework to incorporate such local field information into the offline training process. Utilizing a U-Net architecture, we augment the DMN training objective to include the first and second statistical moments of the local stress fields obtained from linear DNS. This ensures that the learned network topology not only fits the effective stiffness but also accurately reflects the internal local stress and strain partitioning of the microstructure. The results confirm that supervising the localization process during training yields a superior surrogate model, reducing local prediction errors by an order of magnitude and significantly improving generalization to unseen nonlinear constitutive behaviors compared to traditional DMNs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ansatz-Free Hamiltonian Learning with Heisenberg-Limited Scaling

Learning the unknown interactions that govern a quantum system is crucial for quantum information processing, device benchmarking, and quantum sensing. The problem, known as Hamiltonian learning, is well understood under the assumption that interactions are local, but this assumption may not hold for arbitrary Hamiltonians. Previous methods all require high-order inverse polynomial dependency with precision, unable to surpass the standard quantum limit and reach the gold-standard Heisenberg-limited scaling. Whether Heisenberg-limited Hamiltonian learning is possible without prior assumptions about the interaction structures, a challenge we term ansatz-free Hamiltonian learning , remains an open question. In this work, we present a quantum algorithm to learn arbitrary sparse Hamiltonians without any structure constraints using only black-box queries of the system’s real-time evolution and minimal digital controls to attain Heisenberg-limited scaling in estimation error. Our method is also resilient to state-preparation-and-measurement errors, enhancing its practical feasibility. We numerically demonstrate our ansatz-free protocol for learning physical Hamiltonians and validating analog quantum simulations, benchmarking our performance against the state-of-the-art Heisenberg-limited learning approach. Moreover, we establish a fundamental trade-off between total evolution time and quantum control on learning arbitrary interactions, revealing the intrinsic interplay between controllability and total evolution-time complexity for any learning algorithm. These results pave the way for further exploration into Heisenberg-limited Hamiltonian learning in complex quantum systems under minimal assumptions, potentially enabling new benchmarking and verification protocols.

machine learning↗
DOE OSTI2020

Review of corrosion interactions between different materials relevant to disposal of high-level nuclear waste

Abstract This review covers the corrosion interactions between different materials that are relevant to the disposal of high-level nuclear waste, in particular the waste forms and containers. The materials of interest are borosilicate glass, crystalline ceramics, metal alloys, and any corrosion products that might form. The available data show that these interactions depend on the structure, chemistry, thermodynamic history, and proximity of the materials in contact, as well as the environmental attributes, such as temperature, solution chemistry, and radiation. Several key mechanisms that govern these interactions are highlighted. Scientific gaps and open questions are summarized and discussed.

Materials Science↗
NASA NTRS2013

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.

Clouds↗
DOE OSTI2020

Layer size polydispersity in hydrated montmorillonite creates multiscale porosity networks

The aluminosilicate layers of the swelling clay mineral montmorillonite, and the saturated pores they delineate, control the mechanical properties and the transport of solutes in many natural and engineered environments. However, the structural basis of montmorillonite porosity remains poorly characterized due to the difficulty in visualizing hydrated samples in their native state. Here in this paper, we used cryogenic transmission electron microscopy (cryo-TEM) and cryo electron tomography (cryo-ET) to show that stacking defects within minimally altered, fully hydrated montmorillonite particles define multiscale porosity networks. Variations in layer lateral dimensions over tens to thousands of nanometers cause a range of topological and dynamic defects that generate pervasive curvature and introduce previously uncharacterized solute transport pathways. Observations of long-range rotational order between neighboring layers indicate that the layer-layer interactions that govern clay swelling involve three dimensional orienting forces that operate across nanoscale pores. These direct observations of the hierarchical structure of hydrated montmorillonite pore networks with nanoscale resolution reveal potentially general aspects of colloidal interactions in fluid-saturated clay minerals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improving nanoparticle superlattice stability with deformable polymer gels

The self-assembly of colloidal nanoparticles into ordered superlattices typically uses dynamic interactions to govern particle crystallization, as these non-permanent bonds prevent the formation of kinetically trapped, disordered aggregates. However, while the use of reversible bonding is critical in the formation of highly ordered particle arrangements, dynamic interactions also inherently make the structures more prone to disassembly or disruption when subjected to different environmental stimuli. Thus, there is typically a trade-off between the ability to initially form an ordered colloidal material and the ability of that material to retain its order under different conditions. Here, we present a method for embedding colloidal nanoparticle superlattices into a polymer gel matrix. This encapsulation strategy physically prevents the nanoparticles from dissociating upon heating, drying, or the introduction of chemicals that would normally disrupt the lattice. However, the use of a gel as the embedding medium still permits further modification of the colloidal nanoparticle lattice by introducing stimuli that deform the gel network (as this deformation in turn alters the nanoparticle lattice structure in a predictable manner). Moreover, encapsulation of the lattice within a gel permits further stabilization into fully solid materials by removing the solvent from the gel or by replacing the solvent with a liquid monomer that can be photopolymerized. This embedding method therefore makes it possible to incorporate ordered colloidal arrays into a polymer matrix as either dynamic or static structures, expanding their potential for use in responsive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

All-Order Full-Coulomb Quantum Spectral Line-Shape Calculations

Understanding how atoms interact with hot dense matter is essential for astrophysical and laboratory plasmas. Interactions in high-density plasmas broaden spectral lines, providing a rare window into interactions that govern, for example, radiation transport in stars. However, up to now, spectral line-shape theories employed at least one of three common approximations: second-order Taylor treatment of broadening operator, dipole-only interactions between atom and plasma, and classical treatment of perturbing electrons. In this Letter, we remove all three approximations simultaneously for the first time and test the importance for two applications: neutral hydrogen and highly ionized magnesium and oxygen. Finally, we found 15%–50% change in the spectral line widths, which are sufficient to impact applications including white-dwarf mass determination, stellar-opacity research, and laboratory plasma diagnostics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

Nonlinear Tollmien-Schlichting/vortex interaction in boundary layers

The nonlinear reaction between two oblique 3-D Tollmein-Schlichting (TS) waves and their induced streamwise-vortex flow is considered theoretically for an imcompressible boundary layer. The same theory applies to the destabilization of an incident vortex motion by subharmonic TS waves, followed by interaction. The scales and flow structure involved are addressed for high Reynolds numbers. The nonlionear interaction is powerful, starting at quite low amplitudes with a triple-deck structure for the TS waves but a large-scale structure for the induced vortex, after which strong nonlinear amplification occurs. This includes nonparallel-flow effects. The nonlinear interaction is governed by a partial differential system for the vortex flow coupled with an ordinary-differential one for the TS pressure. The solution properties found sometimes produce a breakup within a finite distance and sometimes further downstream, depending on the input amplitudes upstream and on the wave angles, and that then leads to the second stages of interaction associated with higher amplitudes, the main second stages giving either long-scale phenomena significantly affected by nonparallelism or shorter quasi-parallel ones governed by the full nonlinear triple-deck response.

Hall, P.↗
NASA NTRS1989

Nonlinear a Tollmien-Schlichting/vortex interaction in boundary layers

The nonlinear reaction between two oblique three-dimensional Tollmien-Schlichting (TS) waves and their induced streamwise-vortex flow is considered theoretically for an incompressible boundary layer. The same theory applies to the destabilization of an incident vortex motion by subharmonic TS waves, followed by interaction. The scales and flow structure involved are addressed for high Reynolds numbers. The nonlinear interaction is powerful, starting at quite low amplitudes with a triple-deck structure for the TS waves but a large-scale structure for the induced vortex, after which strong nonlinear amplification occurs. This includes nonparallel-flow effects. The nonlinear interaction is governed by a partial differential system for the vortex flow coupled with an ordinary-differential one for the TS pressure. The solution properties found sometimes produce a breakup within a finite distance and sometimes further downstream, depending on the input amplitudes upstream and on the wave angles, and that then leads to the second stages of interaction associated with higher amplitudes, the main second stages giving either long-scale phenomena significantly affected by nonparallelism or shorter quasi-parallel ones governed by the full nonlinear triple-deck response.

Hall, P.↗
DOE OSTI2022

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

New Perspectives on Vibrational Energy Transfer in Energetic Materials: Insights from Pressure-Tuned Ultrafast Spectroscopy

Understanding the manner in which vibrational energy flows between molecular and lattice vibrations is of great interest in physical chemistry due to its central role in reactivity and energy dissipation in molecular materials. Here, in this feature article, we highlight our recent efforts employing ultrafast broadband infrared spectroscopy toward understanding the interplay between molecular and lattice vibrations in energetic materials, motivated by the open questions surrounding the role of vibrational energy transfer (VET) in reaction initiation in these materials. Our work addresses the ongoing debate on the participation of doorway modes in VET. We further present new results from high-pressure ultrafast experiments on RDX, a hydrogen-bonded material, and BNFF, a hydrogen-free material, to explore how intermolecular interaction strength governs VET pathways and time scales. Collectively, our findings reveal that vibrational dynamics in these systems occurs across three distinct time regimes, with VET being incomplete out to hundreds of picoseconds, suggesting the importance of considering nonstatistical reactions in the modeling of these materials. These time scales vary as intermolecular interaction strength is indirectly modified by application of static pressure, indicating dramatic changes to the vibrational structure of these materials under shock-relevant conditions. Our results thus shed light on how intermolecular interactions shape vibrational energy redistribution in molecular materials, and highlight the need for further theoretical and experimental investigation.

Carlson, Daniel Ryan [Sandia National Laboratories↗
DOE OSTI2020

Correlating dynamic microstructure to observed color in electrophoretic displays via in situ small-angle x-ray scattering

Electrophoretic deposition (EPD) is an industrially relevant and scalable technique used to form particle deposits from colloidal suspensions. Highly concentrated particle suspensions generally prevent real-time in situ microscopy observations which limit the characterization of EPD films to ex situ, or postprocessed, laboratory techniques. For dynamic systems, such as tunable amorphous photonic crystals (APCs), only reversible deposits are formed during the EPD process. Since reversible deposits cannot be characterized with standard ex situ methods, the particle-particle and particle-field interactions that govern the displayed color and crystallinity of these systems are not well understood. In this paper, we present in situ small-angle x-ray scattering and UV-Vis techniques for measuring both the structural and optical response of an APC under applied electric fields. Furthermore, we also develop a computational model based on colloidal interactions to explain the observed change in the interparticle spacing of APCs due to the applied electric field which correlates to displayed color. Ultimately, this work provides a new in situ characterization method that could be expanded for other dynamic, tunable colloidal systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phonons in complex twisted crystals: Angular momenta, interactions, and topology

We report phonons and their interactions are critically important for a variety of energy-relevant applications ranging from low thermal resistance substrates to thermal barrier coatings. Fundamental insights into the nature of phonons and allowed interactions are governed by the underlying symmetries of the crystal lattice. In this paper, we provide a comprehensive and detailed description of lattice dynamics derived from twist symmetries of chiral and achiral crystals—twist dynamics. Phonon bands naturally carry quantized crystal angular momentum derived from rotational phases, which give insights into the nature of band crossings and avoided crossings, selection rules for phonon interactions, and topological band crossing behaviors. Twist dynamics is demonstrated for a variety of materials covering a range of space groups, symmetry operations, twist axis orientations, and constituent elements. Furthermore, twist symmetry offers insights into peculiar features observed in scattering measurements. In this context, we present inelastic neutron scattering measurements for rutile TiO 2 and explain them using twist dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗