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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 145 records · Page 8

The impacts of horizontal resolution on the seasonally-dependent biases of the northeastern Pacific ITCZ in coupled climate models.

Double-ITCZ has puzzled climate model community for more than two decades. Here, we found that over the eastern Pacific, precipitation and sea surface temperature (SST) biases in the NCAR CESM1 are seasonally-dependent, with positive (negative) precipitation/SST biases during boreal summer/fall (winter/spring), although the easterly wind bias persists around the year. This seasonally-dependent bias of precipitation/SST is found to be caused by the failure of the model to reproduce the climatological seasonal wind reversal of North American monsoon. During winter/spring, the climatological easterly wind dominates, so the stronger wind speed in the model enhances the evaporation and lowers the SST. It is opposite when the climatological wind turns to westerly during summer/fall. The easterly wind bias also occurs in the atmospheric model when the observation SST is prescribed, suggesting it is of atmospheric origin. Further, the easterly wind bias is mainly evident in the lower troposphere and quite independent of time, implying the effect of complex and narrow-ranged Central American topography, which is not depicted well in the coarse model resolution. When the model resolution is doubled, both SST and precipitation are improved with the reduced easterly wind bias. During boreal spring, when ITCZ bias is most significant, the northern and southern ITCZ can be improved by 29% and 18.8% respectively in the higher resolution. Finally, we suggest that these seasonally-dependent biases over the eastern Pacific are quite universal among 37 CMIP5 coupled models, and the ongoing CMIP6 project will provide a valuable opportunity to examine whether the bias can be reduced by increasing model resolution.

Song, Fengfei↗

Predicting Compliance in an Epidemiological Model: Constructs from Psychological Theory and Research

Vaccination and the alternative behavior, vaccine refusal, are a classic example of manifesting behaviors driven by social norms and norm violations. Establishing how norms emerge, and under what circumstances people choose to violate them are key issues to understand in modeling epidemics. Interactions between individuals can lead to large-scale patterning of behavior (emergent phenomena). As norm violations are revealed through human behavior, drawing on psychological theory and principles to predict those violations is a viable approach for more human-constrained epidemiological models. As an example of the implications at scale, vaccine refusal is correlated with the spread of mis/disinformation about vaccine side-effects. Considering the complexities of network dynamics, the downstream effects means that if even a small group within a population are persuaded against vaccination, there is a reservoir from which disease and disease outbreaks can propagate. This work will attempt to identify those psychological indicators, to define circumstances that predict health behaviors, and identify potentially modifiable antecedents of health behavior, and factors that influence changes toward health protective behaviors.

59 BASIC BIOLOGICAL SCIENCES↗

Using AI to build a hydrobiogeochemical soil model

Soil water content is a function of inputs from precipitation and outputs via evaporation, transpiration, lateral flow, and vertical percolation, and is sensitive to biogeochemical processes. As such, soils serve as an ideal integrator of atmospheric, hydrological, and biogeochemical processes affecting the water cycle. In addition, soil water retention capacity, infiltration rates, and hydraulic conductivity can buffer or exacerbate the effects of extreme precipitation events (e.g., flooding, runoff, subsurface transport, erosion, greenhouse gas emissions) and mitigate the impact of droughts and heat waves on land systems (e.g., fire, crop failure). However, integrating water cycle measurements spanning different land atmosphere compartments across scales is a fundamental barrier for numerical model predictability. A significant challenge is that each domain (soil, hydrology, biology, and atmosphere) typically collects different sets of data at different temporal and spatial frequencies/scales, and even different dimensionalities (2D vs 3D). To implement soil as an integrator of the water cycle in land models, we suggest that novel machine learning (ML) tools can be developed to effectively simulate complex landscapes across various domains and scales, extended to regions with sparse or no data. The ultimate goals are to improve predictive understanding of land-atmosphere interactions and to extend the predictability of current Earth System Models (ESMs) through better integration of hydrological and biogeochemical data. We envision a framework in which: (1) ML-aided data reconstructions enable the merger of data sources into a unified geospatial product; (2) automated detection techniques are used to improve the knowledge of complex soil processes and interactions; and (3) this knowledge is leveraged and incorporated into models through AI-based emulators to distinctly connect the land and atmospheric compartments of the water cycle in models.

54 ENVIRONMENTAL SCIENCES↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations.

97 MATHEMATICS AND COMPUTING↗

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗

A Community Guide to Regulatory Barriers Affecting Microgrids (Reports 1-3)

In response to growing risks of power outages from extreme weather and aging infrastructure, communities are increasingly exploring the potential of microgrids to provide reliable energy access. Microgrids offer promising solutions to meet this challenge but face a complex landscape of non-technical barriers, particularly regulations concerning the provision and distribution of energy. Most existing legal and regulatory frameworks were designed for a centralized, one-way power system, and are often poorly suited to handle systems that independently balance distributed energy resources with local load. This three-part report series provides a strategic analysis of existing regulatory and legal factors affecting microgrid deployments to help non-technical community leaders and decision-makers better understand the feasibility of a microgrid in their community. -Report No. 1: Foundational Issues Facing Microgrids details the universal policy barriers all microgrids face, including utility interconnection processes, rate structures, and local permitting. -Report No. 2: Single Property Microgrids outlines how direct asset ownership and operating behind-the-meter can bypass some regulatory oversight, using the Blue Lake Rancheria microgrid as a case study. -Report No. 3: Multi-Property Microgrids tackles the complex challenges of crossing public rights-of-way and navigating utility franchise rights, highlighting the Coventry microgrid project. The series equips decision-makers with phased frameworks to navigate financial and regulatory complexities, engage effectively with local utilities and Authorities Having Jurisdiction (AHJs), and structure successful microgrid projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗

HydroSource: A Platform for US Hydropower Data for Basin-Scale Applications

HydroSource: A Platform for US Hydropower Data for Basin-Scale Applications presents a high-level overview of ORNL’s HydroSource data products that can be used in various basin-scale applications across the United States to realistically conceptualize and quantitatively analyze the complex dynamics, effects, and implications of energy-water systems. This product is an ArcGIS Story Map that contains an array of interactive and static maps.

13 HYDRO ENERGY↗

Photon-In/Photon-Out X-ray Free-Electron Laser Studies of Radiolysis

Understanding the origin of reactive species following ionization in aqueous systems is an important aspect of radiation–matter interactions as the initial reactive species lead to production of radicals and subsequent long-term radiation damage. Tunable ultrafast X-ray free-electron pulses provide a new window to probe events occurring on the sub-picosecond timescale, supplementing other methodologies, such as pulse radiolysis, scavenger studies, and stop flow that capture longer timescale chemical phenomena. We review initial work capturing the fastest chemical processes in liquid water radiolysis using optical pump/X-ray probe spectroscopy in the water window and discuss how ultrafast X-ray pump/X-ray probe spectroscopies can examine ionization-induced processes more generally and with better time resolution. Ultimately, these methods will be applied to understanding radiation effects in complex aqueous solutions present in high-level nuclear waste.

47 OTHER INSTRUMENTATION↗

Identifying Characteristics of Wildfire Towers and Troughs

Wildfire behavior is dictated by the complex interaction of numerous physical phenomena including dynamic ambient and fire-induced winds, heat transfer, aerodynamic drag on the wind by the fuel and combustion. These phenomena create complex feedback effects between the fire and its surroundings. In this study, we aim to study the mechanisms by which buoyant flame dynamics along with vortical motions and instabilities control wildfire propagation. Specifically, this study employs a suite of simulations conducted with the physics-based coupled fire-atmosphere behavior model (FIRETEC). The simulations are initialized with a fire line and the fires are allowed to propagate on a grass bed, where the fuel heights and wind conditions are varied systematically. Flow variables are extracted to identify the characteristics of the alternating counter-rotational vortices, called towers and troughs, that drive convective heat transfer and fire spread. These vortices have previously been observed in wildfires and laboratory fires, and have also been observed to arise spontaneously in FIRETEC due to the fundamental physics incorporated in the model. However, these past observations have been qualitative in nature and no quantitative studies can be found in the literature which connected these coherent structures fundamental to fire behavior with the constitutive flow variables. To that end, a variety of state variables are examined in the context of these coherent structures under various wind profile and grass height conditions. Identification of various correlated signatures and fire-atmosphere feedbacks in simulations provides a hypothesis that can be tested in future observational or experimental efforts, potentially assisting experimental design, and can aid in the interpretation of data from in situ detectors.

54 ENVIRONMENTAL SCIENCES↗

Effective Polarizability in Near-Field Microscopy of Phonon-Polariton Resonances

We investigate the resonant characteristics of planar surfaces and distinct edges of structures with the excitation of phonon-polaritons. We analyze two materials supporting phonon-polariton excitations in the mid-infrared spectrum: silicon carbide, characterized by an almost isotropic dielectric constant, and hexagonal boron nitride, notable for its pronounced anisotropy in a spectral region exhibiting hyperbolic dispersion. We formulate a theoretical framework that accurately captures the excitations of the structure involving phonon-polaritons, predicts the response in scattering-type near-field optical microscopy, and is effective for complex resonant geometries where the locations of hot spots are uncertain. We account for the tapping motion of the probe, perform analysis for different heights of the probe, and demodulate the signal using a fast Fourier transform. Using this Fourier demodulation analysis, we show that light enhancement across the entire apex is the most accurate characteristic for describing the response of all resonant excitations and hot spots. We demonstrate that computing the demodulation orders of light enhancement in the microscope probe accurately predicts its imaging.

Chemistry↗

Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition

Multi-fidelity Bayesian optimization (MFBO) is a powerful approach that utilizes lowfidelity, cost-effective sources to expedite the exploration and exploitation of a high-fidelity objective function. Existing MFBO methods with theoretical foundations either lack justification for performance improvements over single-fidelity optimization or rely on strong assumptions about the relationships between fidelity sources to construct surrogate models and direct queries to low-fidelity sources. To mitigate the dependency on cross-fidelity assumptions while maintaining the advantages of low-fidelity queries, we introduce a random sampling and partition-based MFBO framework with deep kernel learning. This framework is robust to cross-fidelity model misspecification and explicitly illustrates the benefits of low-fidelity queries. Our results demonstrate that the proposed algorithm effectively manages complex cross-fidelity relationships and efficiently optimizes the target fidelity function.

Zhang, Fengxue [University of Chicago, Illinois, U↗

RE-INTEGRATE EMT Simulation Tool: Input Data Processing Layer for Bulk Power System

This paper introduces an advanced input data processing layer for EMT simulations of large-scale bulk power systems. The paper proposes two versions of the RE-INTEGRATE EMT simulation tool, RE-INTEGRATE Gen-0 and RE-INTEGRATE Gen-1, which are developed to enhance simulation generalizability, scalability, and accuracy. The framework leverages a generic class design for components to incorporate linear equations, which are generated by discretizing the Differential-Algebraic Equations (DAEs) that represent the dynamics of the components. In addition, the framework employs a parsing algorithm that parses a power system’s raw and dyr files to generate a connectivity graph which is then traversed to form the overall system’s dynamics. The proposed input data processing layer is used to simulate the IEEE 39-bus test system. The obtained results demonstrate the framework’s capability to achieve simulation scalability and accuracy. Further, the results indicate that EMT simulations performed using the proposed automations can effectively handle complex grid configurations.

Mishra, Rahul [ORNL] (ORCID:0000000328205932)↗

Fundamental Effects of Al and Ta on Microstructure and Phase Transformations in the Al–Cr–Mo–Ta–Ti Refractory Complex Concentrated Alloy System

The effect of aluminum and tantalum concentrations on a refractory metal complex concentrated alloy is reported, particularly with respect to their effect on microstructure and phase composition of the alloy in cast and annealed form. Alloys with an equiatomic composition, (AlCrMoTaTi), an aluminum-lean composition (Al 0.75 CrMoTaTi), and a tantalum-lean composition (AlCrMoTa 0.75 Ti) are produced via arc melting. The alloys exhibit multiphase structures, confirmed by X-ray diffraction, microstructural characterization, and thermal analysis. The minor off-equiatomic adjustments of aluminum and tantalum in this alloy system did not drastically alter the prevalence of the Cr–Ta-based Laves phase. Correlations between thermodynamic predictions and observed phase transformations via thermal analysis are improved upon refinement of calculations removing impractical intermediate phases. As a result, experimental findings provide information for the refinement of thermodynamic modeling and deliver additional insight into the optimization of alloy compositions within this five-component system.

36 MATERIALS SCIENCE↗

Origin of spin-driven ferroelectricity and effect of external pressure on the complex magnetism of the 6⁢ H perovskite Ba 3 ⁢Ho⁢Ru 2⁢ O 9

The compound Ba 3 HoRu 2 O 9 magnetically orders at 50 K (T N1 ), followed by another complex magnetic ordering at 10.2 K (T N2 ). The second magnetic phase transition was characterized by the coexistence of two competing magnetic ground states associated with two different magnetic wave vectors (K 1 = 0.5 0 0 and K 2 = 0.25 0.25 0). The multiferroicity and magnetoelectric coupling were predicted below T N2 in these 4d-based materials. Here, in this work, we have discussed the origin of spin-driven ferroelectricity, which is not known yet, and the nature of magnetoelectric domains. We have investigated the compound through time-of-flight neutron diffraction, synchrotron x-ray diffraction (XRD), ac susceptibility, frequency-dependent complex dielectric spectroscopy, and dc magnetization under external pressure. We have demonstrated that the noncollinear structure involving two different magnetic ions, Ru (4d) and Ho (4f), breaks the spatial inversion symmetry via inverse Dzyaloshinskii-Moriya (DM) interaction through strong 4d-4f magnetic correlation, which shifts the oxygen atoms and results in nonzero polarization. Such an observation of inverse DM interaction from two different magnetic ions which cause ferroelectricity is rarely observed. The stronger spin-orbit coupling of 4d orbital might play a major role in creating DM interaction of noncollinear spins. We have systematically studied the spin and dipolar dynamics, which exhibit intriguing behavior with shorter coherence lengths of second magnetic phase associated with the k 2 wave vector. The results manifest the development of finite-size magnetoelectric domains instead of true long-range ordering, which justifies the experimentally obtained low value of ferroelectric polarization. The lattice parameters and volume show a sharp anomaly at T N2 obtained by analyzing the temperature-dependence XRD, which is consistent with the ferroelectric transition, predicting a noncentrosymmetric space group, $P\bar{6}2c$, for this compound. Furthermore, we have investigated the effect of external pressure on this complex magnetism. The result reveals an enhancement of ordering temperature by the application of external pressure (~1.6 K/GPa). The external pressure might favor stabilizing the magnetic ground state associated with second magnetic phase. Our study shows an unconventional mechanism of spin-driven ferroelectricity involving inverse DM interaction between Ru (4d) and Ho (4f) magnetic ions due to strong 4d-4f cross coupling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhancing durability of polymer electrolyte membrane using cation size selective agents

Radical species generated during proton exchange membrane fuel cell operation considerably limit the achievable durability, particularly for heavy-duty vehicle applications. A promising solution to the problem is the incorporation of radical scavenger additives such as cerium which mitigates chemical attacks on the membrane. However, these additives migrate during fuel cell operation causing a loss in durability and performance due to detrimental interaction with various components of the fuel cell. Here, we study cation size selective agents as a means to immobilize cerium within perfluorosulfonic acid (PFSA) membranes. We synthesized an organometallic complex of cerium with 15-Crown-5 and investigated the effectiveness of this complex to immobilize cerium. Over 300% increase in cerium retention and an 80% increase in chemical durability were observed owing to the stabilization effect of crown ethers on cerium. Migration under a potential gradient can be eliminated while the complex also contributes to the enhancement in cerium radical scavenging activity. In conclusion, current challenges with the proposed solution are highlighted and future work is discussed.

25 ENERGY STORAGE↗

Effects of Structural Constraints on Excited-State Properties in Dimeric Cu(I) Diimine Complexes

Copper(I) bis-diimine complexes have played important roles in light-activated processes that can lead to their potential applications in photocatalysis and chemical sensing. Their metal-to-ligand charge-transfer (MLCT) excited-state properties are tunable by various structural factors. Dimeric Cu(I) complexes with connecting diimine derivative ligands offer another structural tuning platform for the excited-state properties. Here, we investigate excited-state properties in two covalently connected dimeric Cu(I)'s with varying structural constraints exerted by the number of carbons in the polyethylene bridge (C0 and C4) connecting the two copper(I) diimine moieties. An interesting feature of Cu(I) diimine complexes is their ability to flatten following a photoinduced structural change. Herein, we observe larger structural constraints and more structural rearrangement required upon excitation of the longer bridged complex C4 to achieve a conformation toward a more flattened tetrahedral coordination geometry compared to the shorter bridged C0. Vibrational wavepacket analysis of these complexes further supports the effect of these structural constraints where we observe a more rapid dephasing of the C0 complex, as opposed to the C4 complex, despite similar normal mode vibrations. The experimental results were supplemented by TDDFT calculations. In conclusion, the studies provide insight into using metal-metal interactions through constraints to tune excited-state dynamics and pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dimensionality effects on multicomponent ionic transport and surface complexation in porous media

Coulombic interactions between charged species in pore water and at surface/solution interfaces are of pivotal importance for multicomponent reactive transport in porous media. In this study, we investigate the impact of domain dimensionality on electrostatically coupled dispersion and surface-solution reactions during transport of acidic plumes and major ions in porous media. Column and quasi two-dimensional flow-through experiments were performed, with identical silica porous media and under the same advection-dominated conditions. Equal mass fluxes of different electrolyte solutions (i.e., HCl - pH ~ 2.8, NaBr - 100 mM, HCl - pH ~ 2.8 plus NaBr - 100 mM) were continuously injected in the 1-D and 2-D experiments and breakthrough curves of pH and major ions were measured at the outlet of the domains. The presence of pronounced ionic strength gradients in the transverse direction in the 2-D setup caused distinct retardation and transport behaviors of protons and major ions which were not observed in the one-dimensional column experiments. Furthermore, in the cases of salt electrolytes injection, considerably enhanced release of H + (>61%) from the quartz surface was observed in the multidimensional system compared to the one-dimensional setup. Reactive transport modeling was performed to reproduce the experimental outcomes and to analyse the coupling between transport processes, based on the Nernst-Planck formulation of diffusive/dispersive fluxes and on surface complexation reactions at the solid-solution interface. Electrostatic interactions between Na + , B – , and H + , and deprotonation of the quartz surface upon the formation of sodium outer-sphere complexes, are the primary controllers of the spatial and temporal features displayed by the pH and major ions measurements. The reactive transport simulations allowed us to interpret the experimental observations, to visualize the distribution and spatio-temporal evolution of dissolved and solid species, to identify a spatially heterogeneous zonation of Coulombic interactions with distinct behavior at the fringe and core of the injected plumes in the multidimensional setup, and to quantify the different components of the Nerst-Planck fluxes of the charged solutes. This study demonstrates that the domain dimensionality directly affects electrostatic interactions between charged aqueous species in the pore water and surface complexation reactions at the solid-solution interface. The non-trivial effects of dimensionality on multicomponent ionic transport result in a significantly different behavior in 1-D and 2-D systems.

58 GEOSCIENCES↗

CaMn 3 IV O 4 Cubane Models of the Oxygen‐Evolving Complex: Spin Ground States S <9/2 and the Effect of Oxo Protonation

Abstract We report the single crystal XRD and MicroED structure, magnetic susceptibility, and EPR data of a series of CaMn 3 IV O 4 and YMn 3 IV O 4 complexes as structural and spectroscopic models of the cuboidal subunit of the oxygen‐evolving complex (OEC). The effect of changes in heterometal identity, cluster geometry, and bridging oxo protonation on the spin‐state structure was investigated. In contrast to previous computational models, we show that the spin ground state of CaMn 3 IV O 4 complexes and variants with protonated oxo moieties need not be S =9/2. Desymmetrization of the pseudo ‐ C 3 ‐symmetric Ca(Y)Mn 3 IV O 4 core leads to a lower S =5/2 spin ground state. The magnitude of the magnetic exchange coupling is attenuated upon oxo protonation, and an S =3/2 spin ground state is observed in CaMn 3 IV O 3 (OH). Our studies complement the observation that the interconversion between the low‐spin and high‐spin forms of the S 2 state is pH‐dependent, suggesting that the (de)protonation of bridging or terminal oxygen atoms in the OEC may be connected to spin‐state changes.

Lee, Heui Beom↗