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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 127 records · Page 7

Softening of dd excitation in the resonant inelastic x-ray scattering spectra as a signature of Hund's coupling in nickelates

We investigate the effects of Hund's coupling on the resonant x-ray absorption spectra of the recently discovered family of layered nickelate superconductors. We contrast two scenarios depending on the relative strength of the ratio of the effective Hund's coupling ( J H ) to the crystal fields ( Δ ) in these systems. We carry out the cluster and DFT + DMFT simulations of the RIXS signal at the Ni L edge for different values of Hund's coupling. We find the latter dominates for the parent compound while the former becomes important for sufficiently large doping. Our results are consistent with the observations of a softening of a RIXS peak as a function of doping by Rossi [], only when the Hund coupling is sizable. To interpret the results, we separate the theoretical RIXS signal into spin conserving and nonspin conserving channels and conclude that the infinite layer nickelates are in a regime where Δ and J compete effectively and suggest further experimental tests of the theory. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Generalized Hydrodynamics: A Perspective

Conventional hydrodynamics describes systems with few long-lived excitations. In one dimension, however, many experimentally relevant systems feature a large number of long-lived excitations and conserved quantities even at high temperature, because they are proximate to integrable limits. Such models cannot be treated using conventional hydrodynamics. The framework of generalized hydrodynamics (GHD) was recently developed to treat the dynamics of one-dimensional models: It combines ideas from integrability, hydrodynamics, and kinetic theory to come up with a quantitative theory of transport. GHD has successfully settled several long-standing questions about one-dimensional transport; it has also been leveraged to study dynamical questions beyond the transport of conserved quantities and to systems that are not integrable. In this article, we introduce the main ideas and predictions of GHD, survey some of the most recent theoretical extensions and experimental tests of the GHD framework, and discuss some open questions in transport that the GHD perspective might elucidate. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Acceptance dependence of factorial cumulants, long-range correlations, and the antiproton puzzle

We analyze joint factorial cumulants of protons and antiprotons in relativistic heavy-ion collisions and point out that they obey the scaling Ĉnmp,p¯∝〈Np〉n〈Np¯〉m as a function of acceptance when only long-range correlations are present in the system, such as global baryon conservation and volume fluctuations. This hypothesis can be directly tested experimentally without the need for corrections for volume fluctuations. We show that if correlations among protons and antiprotons are driven by global baryon conservation and volume fluctuations only, the equality Ĉ2p/〈Np〉2=Ĉ2p¯/〈Np¯〉2 holds for large systems created in central collisions. We point out that the experimental data of the STAR Collaboration from phase I of the Relativistic Heavy Ion Collider (RHIC) beam energy scan (BES) are approximately consistent with the scaling Ĉnmp,p¯∝〈Np〉n〈Np¯〉m, but the normalized antiproton correlations are stronger than those of protons, −Ĉ2p¯/〈Np¯〉2>−Ĉ2p/〈Np〉2. Existing theoretical baselines, based on global baryon conservation and volume fluctuations, cannot explain the data, which we refer to as the antiproton puzzle. We also discuss high-order factorial cumulants which can be measured with sufficient precision within phase II of RHIC-BES.

Bzdak, Adam↗

Optimal Litz Wire Design for High-Power Wireless Charging System

In this study, an optimized Litz wire and polyphase coil winding design is proposed for high-power wireless charging systems operating at 85 kHz frequency. Litz wire in a wireless charging system contributes to more than half of the losses of the system, making it a critical design component. Here, the Litz wire is optimized through Finite Element Analysis (FEA) considering electrical and mechanical design aspects and the design was validated through experimental tests on different Litz wires with various strand-diameters, twisting ratio, and number of strands. The proposed optimal Litz wire maximizes the system efficiency considering the tradeoff between coil resistance and mutual inductance. The optimal Litz wire shows that Litz wire constructed with the 63µm strands significantly outperform the traditionally used Litz wire with 100µm strand diameter. Additionally, the coil with optimal Litz wire design shows 60% reduction in the copper volume for the same loss, and at the same time increase the coil-to-coil efficiency by more than 2% by increasing the mutual inductance and reducing coil current. The optimized Litz wire was implemented in a 22-kW wireless charging system achieving 94.7% efficiency.

Aydin, Emrullah [ORNL]↗

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗

A Compact, Single Stage, >1 kV Medium-Voltage Line Impedance Stabilization Network

This paper presents the design of a single-phase, single-stage line impedance stabilization network (LISN) for medium-voltage (MV) applications. More than 1 kV rated widebandgap (WBG) power semiconductor switches are increasingly utilized in new, emerging power electronics energy systems to improve power density and efficiency. However, due to inherently fast-switching speeds, WBG switch modules emit considerable electromagnetic interference (EMI) (e.g., common mode (CM) or differential mode (DM)). State-of-the-art offers standardized LISN solutions to validate and certify the new energy system for electromagnetic compatibility (EMC). However, most are for low voltage applications (i.e., < 1 kV). MV LISNs (i.e., > 1 kV) are rare until recently and literature does not provide sufficient guidelines for designing and characterizing such devices. It has been a critical challenge for many scientists and engineers to reliably certify the emerging MV energy systems (e.g., electric ships and aircraft). This paper addresses such a technology gap. Specifically, a CISPR 16-1-2 compliant 50Ω/50μH LISN with 1.5kV, 75A and 30MHz measurement capability has been proposed. Detailed performance study versus non-linear parasitic parameters variations in MV inductors and capacitors have been done. Based on new understandings, novel techniques to intuitively mitigate unwanted parasitic have been proposed to develop the proposed LISN successfully. Thorough characterization of important LISN parameters are presented and factors influencing them are analyzed. A rigorous analysis, experimental tests, and in-depth comparisons over state-of-the-art have been made to validate the effectiveness. This is done through the state-of-the-art 300kVA MV EMI testbed.

42 ENGINEERING↗

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.

Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗

Computational Study of Additively Manufactured Internally Cooled Airfoils for Industrial Gas Turbine Applications

Internal cooling features such as pin-fins, impingement jets, and rib-turbulators are necessary to keep turbine components cool, but if sufficiently advanced can potentially also eliminate the need for film cooling on turbine blades particularly in industrial gas turbines where temperatures are not extreme. Furthermore, by leveraging additive manufacturing, other advanced designs such as lattice and incremental impingement configurations are possible and have recently been experimentally tested. While the performance of such configurations has been quantified through means of overall cooling effectiveness, it is not as clear why certain designs were better than others, or what the mechanisms were behind the observed external cooling patterns. The purpose of this study was to computationally analyze different advanced turbine blade internal cooling designs previously tested by the National Energy Technology Laboratory.

CFD↗

Design of intrinsically disordered protein variants with diverse structural properties

Intrinsically disordered proteins (IDPs) perform a broad range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Computational design of IDPs with specific conformational properties has, however, been difficult because of their substantial dynamics and structural complexity. We describe a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs that differ in compaction, long-range contacts, and propensity to phase separate. We experimentally tested and validated our designs and analyzed the sequence features that determine conformations. We show how our results are captured by a machine learning model, enabling us to speed up the algorithm. Our work expands the toolbox for computational protein design and will facilitate the design of proteins whose functions exploit the many properties afforded by protein disorder.

Science & Technology - Other Topics↗

Adaptive Stiffness Power Take-Off System for a Hydraulic Hose-Pump Point Absorber Wave Energy Converter

Two crucial challenges faced in the design of ocean wave energy converters (WECs) are maintaining high capacity factors and remaining robust in everchanging, harsh ocean environments. This study introduces a novel mechanism for achieving reactive WEC control with a soft hydraulic power take-off, thereby addressing both challenges. The device of interest involves a hydraulic pump, constructed from a fluidic flexible matrix composite (F2MC), which is cyclically stretched by driving waves and pressurizes working fluid through a turbine-generator. This class of fiber-reinforced stretch hoses is established for ocean use as robust moorings and shock absorbers. The dynamic properties of the F2MC pump depend on internal pressure, which can be controlled by a continuously variable transmission between the turbine and generator, allowing the system to be adapted for better performance over a wide range of wave conditions. This work presents a dynamic model for operation and adaptive behavior of this power take-off system, experimentally validates components of the model, and performs dynamic simulations of the system that show increases in power production and capacity factor compared to non-adaptive operation for a variety of driving wave conditions. This work develops the basis for future large-scale experimental testing and controller design of this system.

Wave energy conversion, fluidic flexible matrix co↗

Reconfigurable unitary transformations of optical beam arrays

Spatial transformations of light are ubiquitous in optics, with examples ranging from simple imaging with a lens to quantum and classical information processing in waveguide meshes. Multi-plane light converter (MPLC) systems have emerged as a platform that promises completely general spatial transformations, i.e., a universal unitary. However, until now, MPLC systems have demonstrated transformations that are far from general, e.g., converting from a Gaussian to Laguerre-Gauss mode. Here, we demonstrate the promise of an MLPC, the ability to impose an arbitrary unitary transformation that can be reconfigured dynamically. Specifically, we consider transformations on superpositions of parallel free-space beams arranged in an array, which is a common information encoding in photonics. We experimentally test the full gamut of unitary transformations for a system of two parallel beams and make a map of their fidelity. We obtain an average transformation fidelity of 0.85 ± 0.03. This high-fidelity suggests that MPLCs are a useful tool for implementing the unitary transformations that comprise quantum and classical information processing.

47 OTHER INSTRUMENTATION↗

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗

What are the Principles Controlling Biomimetic Heteropolymer Secondary Structure? (Final Technical Report)

The goal of the project was to develop improved theories to understand how nonbiological oligomers could be designed to cooperatively fold into 3D structures. These studies would lay the groundwork for materials made of such molecules, making it possible to create controlled and ordered materials for electron transport, efficient protein-like catalysts that work under extreme conditions, and sensors with highly-specific chemical responsiveness. Two different simulation thrusts were investigated, one focused on programs to identify stable low energy folded structures at a coarse-level of description of oligomers, and another to calculate thermodynamics of such oligomers. We used these theories to answer several specific questions about what properties of oligomers lead to cooperative transitions, and to identify how oligomer knots could serve as secondary structure elements. We also carried out significant collaborative investigation with Dr. Samuel Gellman (UW-Madison, National Academy of Sciences member) on stability for foldamers of interest to them. Only one of the experimentally tested foldamers stably folded, which was indicated by simulations as being the most likely to fold. Finally, we developed new theoretical descriptions of foldamers, showing how cooperativity was determined primarily by the entropy difference between the folded and unfolded state. The research did not answer all questions laid out in the original proposal but laid the groundwork for later efforts to design folded oligomers materials with high switchability.

36 MATERIALS SCIENCE↗

Bioblendstocks to Optimize Mixing Controlled Compression Ignition (MCCI) Engines

In this project, a team of researchers from the University of Massachusetts Lowell, the University of Maine, and Mainstream Engineering developed an integrated process for the product of bioblendstocks to optimize mixing controlled compression ignition (MCCI) engines. The objective was to improve the energy density, sooting propensity, and cetane number of base diesel fuel while maintaining cold weather behavior. The process converts woody biomass (e.g. sawmill residues) into bio-oil through selective fast pyrolysis; the bio-oil is then selectively upgraded to form selectively oxygenated, minimally-branched hydrocarbons using non-noble metal catalysts in combination with metal-catalyzed hydrogenation. Advanced predictive models, in conjunction with existing property databases, and experimental testing are used to evaluate overall bioblendstock properties and their impact on base diesel fuel. An iterative, targeted upgrading approach was implemented to optimize the proposed bioblendstock’s properties. Assessment methodologies included techno-economic analysis, life-cycle assessment, property testing, and engine testing. Ultimately, the project team successfully produced a viable bioblendstock while identifying critical process points related to scale-up efforts. It was found that producing pyrolysis oils at 500 degrees C and with pine particle sizes of 1-2 mm led to bio-oil with a higher yield (of approximately 45 wt%) and rich amounts of aromatic alcohols. The resultant pyrolysis oil was then upgraded using a sequence of mild hydrotreating, followed by catalytic etherification and esterification, followed by another final mild hydrotreating to produce a blendstock containing saturated species with a limited, but non-zero, amount of oxygen. The aromatic alcohols produced by pyrolysis were especially helpful in this regard, as the resulting bicycloethers and derivatives exhibited high cetane numbers. While most bulk properties of the bioblendstock met or exceeded targeted thresholds, viscosity and cloud point notably fell outside the expected range; this could be addressed by blending limits and/or through the use of additives that are commonplace in current refinding practices. Identification of a bioblendstock that can be produced economically at scale while improving the performance and emissions characteristics of internal combustion engines positively affects the economy by boosting domestic fuel production and the environment by decreasing harmful emissions and increasing efficiency.

09 BIOMASS FUELS↗

A Methodology for Simulating Supercritical CO2 Heat Transfer Experiments Using Machine Learning Models

In an effort to support the growth of supercritical carbon dioxide (sCO2) power cycles in the energy industry, this study seeks to train a machine learning model to mirror experimental data to inform future efforts and design features for both sCO2 heat exchangers and sCO2 turbine thermal management. There is a need for large amounts of experimental testing as there is less established literature about sCO2 used as a working medium in these cycles, as well as due to the influx of novel heat transfer designs presented by the advent of additive manufacturing.

Grabowski, Owen↗

Cool GTL for the Conversion of Biogas to Jet Fuel

Cool GTL is a new process under development for conversion of biogas from digestors or CO2 +H2 to high quality drop in jet fuel. Cool GTL is designed to be a streamlined simplified low cost process which can be cost effective for small scale biogas applications. Cool GTL has the advantage that it uses a high activity bi-reforming catalyst, in a streamlined electric reformer design, to make the synthesis gas for a high conversion slurry fischer Tropsch process followed by a trailing wax cracking reactor. In this way high quality jet fuel can be directly produced. Recent experimental test data will be presented showing product quality. The life cycle analysis LCA will also be presented as well.

09 BIOMASS FUELS↗

Design of Novel Hot Gas Component for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

This CRADA project was the result of a project award under FOA-DOE-0001980. The overarching FOA project team consisted of researchers from Carpenter Technology Corporation (CTC), Solar Turbines Incorporated (Solar), Pennsylvania State University (PSU), University of California-Santa Barbara (UCSB), and Oak Ridge National Laboratory (ORNL). Evaluations were conducted on two high-γ’ superalloys that were designed by CTC and the UCSB. One alloy named GammaPrint-700 (GP-700) is a cobalt-base superalloy. The other alloy named GammaPrint-1100 (GP-1100) is a nickel-base (Ni-base) superalloy. PSU provided expertise and experimental testing of the thermal performance of AM micro-cooling architectures. ORNL provided expertise with the AM superalloy materials characterization and AM processing science. Solar provided turbine component design expertise. The focus of this CRADA report is to document the efforts between ORNL and CTC towards the development of superalloys designed for AM. The project goal was to use an AM processable high-temperature superalloy and design for Additive Manufacturing (DfAM) techniques to design an efficient turbine component (i.e. a turbine tip shoe) with enhanced cooling features that can only be fabricated through additive manufacturing (AM). The efficiencies of existing combined heat and power (CHP) engines are capped by both component design and materials limitations. However, AM of a tip shoe component from a γ’strengthened superalloy offers the design flexibility to increase the efficiency and power of an industrial gas turbine. This project brought about advancements in the DfAM tip shoe design space and in the area of high temperature superalloys processable through laser powder bed fusion (LPBF) AM. State of art computation design tools were utilized to optimize unique cooling features into a tip shoe component design. A two-prong materials development approach was taken to support development of the AM tip shoe geometry. The first approach centered on investigating the processability and the appropriate process science for the industry standard high-γ’ nickel-base (Ni-base) superalloy Mar-M247. This superalloy is typically cast and considered non-weldable by traditional welding standards. In the course of this work, the alloy was not deemed feasible for process scale-up due to significant cracking issues during printing. The second approach focused on the development and evaluation of a novel cobalt-base superalloy, GammaPrint™-700 (GP-700 and a Ni-base superalloy, GammaPrint™-1100 (GP-1100) designed to mitigate the significant AM processing issues with Mar-M247. The processability of these two alloys were investigated through electron beam melting (EBM) binder-jet AM (BJAM), and LPBF as a risk mitigation for manufacturability. To be considered a candidate material for down-selection to proceed to full-scale AM tip shoe engine testing trials, the high temperature creep rupture strength was required to achieve at a minimum, a Larsen Miller Parameter (LMP) increase of 10.9% over the baseline material LPBF AM Hastelloy X.

99 GENERAL AND MISCELLANEOUS↗

Environmental Compatibility Issues for Ni-Based Alloys in Direct-Fired Supercritical CO2 Power Cycles

Direct-fired supercritical CO2 (sCO2) power cycles offer potential for high-efficiency power generation from natural gas and other fossil fuels with built-in carbon capture. Ni-based superalloys are the leading candidates for the hottest portions of these systems, where they must endure long-term exposure to high-temperature, high-pressure, high-velocity, impure CO2-rich environments. Herein we describe results of various experimental testing campaigns conduced at NETL showing that under such conditions, several simultaneously occurring degradation modes may be active including surface oxidation, alloy carburization, and oxide volatilization. It will be shown that the rates of degradation can be strongly affected by the alloy composition, impurities in the CO2, manufacturing method (wrought vs additive), and other factors. The influence of these factors in controlling alloy degradation are discussed in the context of potential compatibility issues for components in real sCO2 systems, such as compact heat exchangers. Finally, as a potential remedial measure, ongoing work involving protective coatings suitable for complex geometries is presented.

alloy oxidation↗