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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Dielectric Resonator Design for Low Power and Low Temperature Microwave Plasma

Waveguide-based microwave plasmas generally operate at high temperatures (2000 - 6000K)[1], making it difficult to directly interface solid materials with the plasma without significant thermal damage. Dielectric microwave resonators (DMRs), long studied for wave-based manipulation of electromagnetic radiation for telecom and optics, can focus radiation to extremely small mode volumes, creating intense localized fields with low-power input.[2] This phenomenon can be used for applications ranging from efficient plasma electronics to near-ambient plasma-materials interactions. Such DMR-based plasmas have been demonstrated a handful of times in the literature, but the majority of research towards this utilize the lowest frequency resonance mode.[3], [4], [5] By carefully controlling the geometry of cylindrical resonators, a variety of electromagnetic modes can be excited. In this work, COMSOL Multiphysics simulations are used to study the electric field enhancement and absorption properties of CaTiO3 DMRs as a function of geometry and excitation frequency. Whereas previous studies have utilized the HEM111 resonance frequency to drive low power plasma excitation, we find that higher order resonance frequencies are more effective at field enhancement and result in less power loss within the dielectric material, hence less wasted heating. The effectiveness of these modes is also geometry dependent and can be computationally optimized for plasma generation. Complementing these computational efforts, we demonstrate a new closed-system reactor design built in a WR-650 waveguide and experimentally demonstrate the formation of atmospheric argon microwave plasma using < 30 W input power on DMR dimers. We observe a shifting resonance frequency as the DMRs heat in response to microwave excitation and develop a Python-based lock-in mechanism to effectively track the DMR resonance over time, leading to stable plasma operation. We use infrared thermal imaging to monitor the temperature of the DMR dimers and surrounding quartz chamber, demonstrating thermal temperatures < 60 degreesC. Finally, we utilize optical emission spectroscopy (OES) to probe the plasma properties as a function of the resonance mode.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

High-Fidelity Arc-Discharge Model for Hydrogen-Plasma-Smelting-Reduction of Iron Ore

Electrification and use of renewable hydrogen is currently a necessity for decarbonizing the iron-and-steel industry. In this regard, hydrogen plasma smelting reduction (HPSR) is a novel pathway that is being explored for reduction of iron ore. HPSR provides several decarbonization merits compared to conventional blast furnaces. Firstly, the use of renewable hydrogen drastically reduces the CO2 emissions compared to the use of coke. Secondly, renewable electricity in the form of a thermal plasma for making reactive hydrogen species (radicals, ions) are more efficient at reducing iron ore compared to neutral H2. Thirdly, a molten product compatible with downstream processes is obtained from the intense heat transfer from the plasma. However, the scale-up of this technology requires fundamental exploration of hydrogen plasma dynamics and its interaction with complex solid material that include phase changing iron-ore and slag. In this work, we present a first principles continuum scale model for thermal plasmas in Ar/H2 gas mixtures typically used for HPSR. The thermal plasma governing equations for mass, momentum and energy with Lorentz force and Joule heating source terms are solved along with electromagnetic equations for electrostatic and magnetic vector potential. Our solver will be based on Pele, a suite of reacting flow solvers designed for advanced scientific computing architectures (Henry De Frahan et al., Proceedings of SIAM Parallel Processing, 13-25, 2024), and will utilize adaptive mesh generation for enhanced resolutions at locations of intense physicochemical interactions. This study will present the impact of Ar to H2 ratios on excited/dissociated hydrogen species concentrations, plasma temperature and conductivity along with the impact of outgassed species (water, metal vapor, O, OH radicals) from ore surface on gas phase chemistry. Furthermore, the heat and species flux to the surface will be quantified as a function of applied voltages in a transferred arc configuration.

hydrogen plasma↗
DOE OSTI2025

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗
DOE OSTI2021

Phenol-containing polyester multiphase polymer blend materials

A solid multiphase polymer blend material comprising: (i) a polyphenolic substance having a molecular weight of at least 500 g/mol; and (ii) a polyester having a molecular weight of at least 500 g/mol; wherein at least a portion of the polyphenolic substance is covalently bonded directly or through a linking moiety to the polyester. Methods for producing the blend material are also described, e.g., homogeneously melt blending a mixture comprising components (i) and (ii) under conditions resulting in covalent attachment of at least a portion of the polyphenolic substance directly or through a linking moiety to the polyester. Methods for producing objects made of the blend material by melt extrusion are also described.

Bova, Anthony S.↗
DOE OSTI2022

Phenol-containing polyester multiphase polymer blend materials

A solid multiphase polymer blend material comprising: (i) a polyphenolic substance having a molecular weight of at least 500 g/mol; and (ii) a polyester having a molecular weight of at least 500 g/mol; wherein at least a portion of the polyphenolic substance is covalently bonded directly or through a linking moiety to the polyester. Methods for producing the blend material are also described, e.g., homogeneously melt blending a mixture comprising components (i) and (ii) under conditions resulting in covalent attachment of at least a portion of the polyphenolic substance directly or through a linking moiety to the polyester. Methods for producing objects made of the blend material by melt extrusion are also described.

Bova, Anthony S.↗
DOE OSTI2026

A bioinspired approach for adaptive solid-solid phase change material coatings with optimized surface features for passive thermal regulation

The necessity to reduce global energy consumption calls for innovative strategies in building thermal management. Passive thermal regulation, particularly through bio-inspired designs, offers a promising avenue by mimicking nature's efficient control of optical properties. This research introduces a novel, climate-responsive coating that integrates optimized bio-inspired surface features with a solid-solid phase change material (SS-PCM) to dynamically manage solar absorptivity without adding additional thickness, enabling both heating and cooling as needed. Drawing on the photonic architectures of the Saharan silver ant and Morpho Didius butterfly, we employed a modeling and multi-objective optimization framework to tailor these surface features. Simulations reveal that surface texture, rather than the intrinsic phase transition of the SS PCM, dominates optical control. Relative to a flat SS PCM coating, optimized isotropic random roughness and broader range features yielded the highest passive heating power increase of about 144 % and 319 % respectively suitable for cold climates. Saharan ant-inspired features enhanced passive cooling for hot climates, achieving a 21.8 % improvement. For moderate climates, Butterfly-wing-inspired surface features provided a balanced enhancement of 19 % for heating and 7 % for cooling. Across all cases, the optimized surface features reduced combined heating and cooling energy demand more effectively than the baseline coating, while preserving material thickness. These findings demonstrate that climate-adaptive, optimized bio-inspired surface features can unlock the full potential of SS PCM coatings, providing a versatile pathway to significant energy savings in buildings and other applications. The methodology establishes a framework for designing next-generation adaptive envelopes that leverage natural photonic principles for high-impact, low-cost thermal regulation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synchrotron based transient x-ray absorption spectroscopy for emerging solid-state energy materials

The rational design of cutting-edge materials for an efficient solar energy conversion process is a challenging task, which demands a fundamental understanding of the mechanisms operative during the photoinduced physical and chemical reactions. In response to these issues, progress in the field has steered attention toward the use of time-resolved spectroscopic techniques to resolve the multiple intermediate species involved in these photoinduced reactions. Thanks to the advent of pump–probe technique, which leads to the development of various time-resolved spectroscopic methods, significant progress has been made in understanding the photophysical and photochemical properties (e.g., excited state dynamics, charge transfer mechanism, charge separation dynamics, etc.) of energy materials. Synchrotron-based x-ray transient absorption (XTA) spectroscopy is one of the most important time-resolved techniques to unravel the direct correlation of the material structure with their photophysical properties owing to its unique capability in directly observing electronic and structural evolution simultaneously. As a result, the aim of this work is to provide a systematic overview of the recent progress in using XTA for capturing the structural dynamics associated with excited state and charge separation dynamics in emerging solid-state energy materials.

14 SOLAR ENERGY↗
DOE OSTI2022

Conductivity and Transference Number Determination Protocols for Solid Oxide Cell Materials

To standardize materials and component characterization for next generation hydrogen production and energy generation solid oxide cell (SOC) technologies, test protocols are being established to facilitate comparison across the numerous laboratories and research institutions where SOC development for application in solid oxide fuel cells (SOFCs) and solid oxide electrolyzes cells (SOEC) is conducted. This paper proposes guiding protocols for fundamental electrical properties characterization of SOC materials, including temperature- and oxygen partial pressure (pO 2 )-dependent conductivity measurements, and use of the electromotive force for determining the transference numbers, or contributions of each charge carrier (i.e., ions and electrons), to the total conductivity. The protocol for Archimedes density measurements is also provided as an integral technique to both of these methods.

25 ENERGY STORAGE↗
DOE OSTI2021

Random copolymer of poly(polyethylene glycol methyl ether)methacrylate as tunable transition temperature solid-solid phase change material for thermal energy storage

Polymer based phase change materials (PCM) for thermal energy storage (TES) applications have gained some attention recently due to their high stability and potential solid to solid phase transition. In this work, we are the first to utilize a simple copolymerization strategy for static tunability transition temperature (T t ) of polymeric PCM. The copolymerization between short and long side chain polyethylene glycol based methacrylate polymers was designed to tune T t with minimum impact on their energy density. Polarized optical microscope and x-ray techniques were also used to understand the relationship between crystal structure and T t of different copolymer composition which was discussed in the context. The solid to solid transition polymeric PCM were successfully developed with tunable T t ranged from 18 °C to 35 °C which is suitable toward building envelop applications.

14 SOLAR ENERGY↗
DOE OSTI2020

Development of Low Cost, Robust and Durable Cathode Materials to Support Solid Oxide Fuel Cell Commercialization (Final Technical Report)

The project is aimed at addressing critical issues related to chromia-poisoning in the cathode of solid oxide fuel cells. A technical hurdle to the commercialization of solid oxide fuel cells is that chromia sources from the metallic interconnect and the balance of plant (BoP) components will cause chromia-poisoning to the cathode performance. This presents a significant challenge since it is very difficult to eliminate chromia sources in the cathode environment. One aspect of the current project is to evaluate whether SFM (Sr 2 Fe 1.5 Mo 0.5 O 6-δ ) that we have recently developed as redox-stable mixed conducting oxide possesses tolerance to chromia-poisoning. The second focus of this project is to evaluate coating on the cathode materials to mitigate chromia poisoning effect. Both thermodynamic evaluation and experimental approaches have been applied to enhance the knowledge base and fundamental understanding of chromia-tolerance of cathode for solid oxide fuel cells. low cost, robust and durable cathode material to support SOFC commercialization.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Conduction Heat Transfer through Solid in Porous Materials: A Comparative Study by Finite-Element Simulations and Effective Medium Approximations

The development of insulation materials with low effective thermal conductivity is essential for energy savings in various applications, including buildings, food services, pipe insulation, and refrigeration. Such materials can be developed by using micro- or nanoporous structures, as well as low-thermal conductivity gases and/or reduced pressure. A variety of effective medium approximation (EMA) models have been developed to study thermal transport through solid in porous structures. However, in many cases, the impacts of porosity on solid conduction are not well predicted by EMA models because of the assumptions made for simplification. Furthermore, the results can vary by a factor of up to 1.5, depending on the morphology of the pores. Hence, proper guidance is needed to choose the appropriate EMA model for a given morphology. This work presents a finite element method study using COMSOL Multiphysics software for various geometries, including hollow cubes, overlapping hollow spheres (normally stacked and tightly packed), and Voronoi structures, and compares the results to those obtained from various EMA models. Simulation results for the hollow cubes and Voronoi structures matched well with the Maxwell-Eucken and Russell model. The results for hollow spheres closely matched the Bauer model and the Glicksman model with fitting parameters. This work provides guidance on analyzing and designing insulation materials for energy savings in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evolution of solid electrolyte interphase and active material in the silicon wafer model system

Alloying anode materials for lithium-ion batteries, such as silicon (Si), are an important focus of materials research due to the demand for increased energy density for electric vehicles and stationary grid storage. However, progress towards next generation anode materials has been hindered by poor capacity retention due to the instability of the Si active material and the solid electrolyte interphase (SEI). Herein, the evolution of the active Si material and the SEI are simultaneously investigated from the perspective of chemical, structural, morphological, and electronic evolution in the Si wafer model system through its cycling life, using time-of-flight secondary ion mass spectrometry (TOF-SIMS), scanning transmission electron microscopy (STEM), atomic force microscopy (AFM), and scanning spreading resistance microscopy (SSRM). The results illustrate a dynamic evolution of the SEI and active Si material through cycling. Through an improved understanding of evolution of SEI and Si active material within the Si wafer model system, mitigation strategies may be designed to extend the lifetime of Si anodes.

25 ENERGY STORAGE↗
DOE OSTI2020

Sound Speed as a Candidate for Internal Temperature Monitoring During Solid Phase Processing of Materials

Internal temperature is an important parameter for understanding the solid phase processing (SPP) of materials and improving feedback control of these processes. Friction stir processes, shear assisted processing and extrusion (ShAPE ™ ), and ultrahigh velocity (UHV) cold spray are examples of such processes. Simple thermal models based on temperatures measured at the boundary of the deforming body cannot capture the dynamic nature of temperature generation within the deforming solid. One possibly way of understanding internal temperature is by measuring sound speed, which varies as a function of temperature for materials and directing ultrasonic wave propagation through selected material volumes of interest. In this project, longitudinal wave speed is estimated for aluminum 6061. Piezoelectric materials bonded to a specimen provided data from which longitudinal wave speed was estimated. A discussion evaluated the linear relationship of wave speed versus temperature and postulated how wave speed measurements could be used to estimate the internal temperature of selected material volumes for feedback during SPP of materials. Instrumentation, data and analysis, and a discussion are reviewed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fast and stable deep-learning predictions of material properties for solid solution alloys

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between different physical properties in alloy systems to improve the prediction accuracy of neural network (NN) models. We use multitasking NN models to simultaneously predict the total energy, charge density and magnetic moment. These physical properties mutually serve as constraints during the training of the multitasking NN, resulting in more reliable DL models because multiple physics properties are correctly learned by a single model. Two binary alloys, copper–gold (CuAu) and iron–platinum (FePt), were studied. Our results show that once the multitasking NN's are trained, they can estimate the material properties for a specific configuration hundreds of times faster than first-principles density functional theory calculations while retaining comparable accuracy. We used a simple measure based on the root-mean-squared errors to quantify the quality of the NN models, and found that the inclusion of charge density and magnetic moment as physical constraints leads to more stable models that exhibit improved accuracy and reduced uncertainty for the energy predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Defect Thermodynamics and Transport Properties of Perovskite and Fluorite Materials for Solid-Oxide and Proton Conducting Oxide Cells Evaluated Based on Density Functional Theory Modeling

Density functional theory based defect thermodynamic modeling was performed to determine the effect of humidity and H2/O2 gas pressure on various defect chemistry and transport properties of perovskite and fluorite oxides for solid-oxide and proton-conducting-oxide cell applications, with inclusion of the electronic-conducting oxides (as electrodes) and insulating oxides (as electrolytes). Automatic defect generation workflow and first-principles charged defect analysis were implemented on NETL Joule supercomputer for modeling defect equilibria and transport properties of insulating oxides as electrolytes in SOCs and proton-conducting ceramic cells. A GNU Octave defect model subroutines were developed to facilitate defect modeling of electronic conducting oxides in a wide range of operating conditions guided by modeling and experiments. The model includes the hydride defect formation reaction under reducing conditions and allows to incorporate nonstoichiometry effects on the defect thermodynamic parameters. The developed model serves as a platform to facilitate fundamental understanding of the defect thermodynamics in SOC oxide materials and can be used as a novel tool in computational materials screening for SOC and other energy applications.

Lee, Yueh-Lin↗
DOE OSTI2025

Development of chemometric models to classify solid-state U materials by micro-Raman spectroscopy

Discerning uranium (U) particles found in environmental sampling is of interest for monitoring the peaceful use of nuclear material. In this study, a soft independent modeling of class analogy (SIMCA) library was successfully developed for the classification of a four-class system consisting of α-U 3 O 8 , UO 2 , UO 2 (NO 3 ) 2 ·6H 2 O (UNH), and UO 2 O 2 ·4H 2 O (studtite) by Raman spectroscopy in the presence of matrix particulates and additional outliers. Spectral variability between numerous particles of each type revealed appreciable differences as a function of particle size with respect to hydration state and potential oxide phase within each class. Interclass variability was accounted for using both unsupervised and supervised chemometric models. The supervised SIMCA model displayed reasonable sensitivity for each U class and a high degree of specificity by returning whether a spectrum belonged to one class or not. This work demonstrates how Raman spectral features and chemometrics can be used to distinguish U materials from one another and from matrix materials such as flint clay. Combining the outlined chemometric approach with Raman mapping sequences could provide a rapid, nondestructive technique to characterize the chemical composition of a diverse collection of U compounds amid background samples for environmental sampling, nuclear forensics, and industrial applications.

Actinide↗
DOE OSTI2023

Chemically Fueled Reinforcement of Polymer Hydrogels

Carbodiimide-fueled anhydride bond formation has been used to enhance the mechanical properties of permanently crosslinked polymer networks, giving materials that exhibit transitions from soft gels to covalently reinforced gels, eventually returning to the original soft gels. Temporary changes in mechanical properties result from a transient network of anhydride crosslinks, which eventually dissipate by hydrolysis. Over an order of magnitude increase in the storage modulus is possible through carbodiimide fueling. Here, the time-dependent mechanical properties can be modulated by the concentration of carbodiimide, temperature, and primary chain architecture. Because the materials remain rheological solids, new material functions such as temporally controlled adhesion and rewritable spatial patterns of mechanical properties have been realized.

36 MATERIALS SCIENCE↗