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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Bayesian Optimization of Catalysis with In-Context Learning

Large language models (LLMs) can perform accurate classification with zero or few examples through in-context learning (ICL), allowing the model to observe query-relevant examples at inference time and eliminating the need for additional weight updates to generalize beyond its original training data. We extend this capability to regression with uncertainty estimation using frozen LLMs (e.g., GPT-4o, Gemini), enabling Bayesian optimization (BO) in natural language without explicit model training or feature engineering. We apply this to materials discovery by representing materials as synthesis and testing procedures for use in natural language prompts. This Bayesian, design-first approach prioritizes optimization toward target material properties before detailed characterization, in contrast to conventional experimental workflows that often emphasize characterization of suboptimal materials. On benchmarks like aqueous solubility and oxidative coupling of methane (OCM), BO-ICL matches or outperforms Gaussian processes. In live experiments on the reverse water–gas shift (RWGS) reaction, BO-ICL identifies multimetallic catalysts that approach equilibrium CO yield within 6 and 10 iterations from a pool of 3,700 and 360,000 candidates, respectively. Our method redefines materials representation and accelerates discovery, with broad applications across catalysis, materials science, and AI.

Calibration↗
DOE OSTI2025

AdditiveFOAM: A Continuum Multiphysics Code for Additive Manufacturing

AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM (Weller et al., 1998), the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing. Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.

Coleman, John [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2024

MxRAM (Final Report)

Sandia National Labs will provide Technical Assistance and consulting to Requester on a series of Requester’s test structures and devices to characterize and aid in the determination of optimal fabrication parameters via fabrication of functional test structures and cells. Working with previously established processes and test die modules, Sandia will construct a series of test chips with varying materials properties to allow the electrical characterization and component testing of Requester’s test structures and devices. Material variations will be selected for optimization of yield and desired target operation parameters. A deliverable in the form of a report will be written. Sandia intends to deliver testable die to the Requester.

36 MATERIALS SCIENCE↗
DOE OSTI2025

From Nonclassical to Classical: Crystallization Seeds Reshape Nucleation Mechanisms

Crystalline seeds are widely employed in crystallization to accelerate nucleation and control product polymorphs; yet, their impact on nucleation mechanisms remains poorly understood. While homogeneous nucleation of crystals from solution often proceeds through nonclassical pathways involving amorphous intermediates, it is unclear how seeds that promote heterogeneous nucleation reshape these mechanisms and govern polymorph selection. Here, in this study, we provide the first direct evidence that crystalline seeds can bypass the need for amorphous intermediates as nucleation sites, converting nonclassical nucleation mechanisms into classical, monomer-by-monomer crystallization pathways. Using molecular dynamics simulations of zeolite synthesis, we uncover a complex reaction network of competing nucleation processes mediated by intermediate interfacial polymorphs. The interplay between thermodynamic stability and kinetic favorability of these interfacial polymorphs dictates nucleation outcomes, creating a dynamic balance between the interfacial polymorph stability and crystallization rates. Furthermore, we show that the synthesis environment-whether monomers or aggregates serve as reactants-profoundly impacts these pathways. At moderate supersaturation, seeds eliminate amorphous intermediates and promote classical nucleation, whereas high supersaturation or aggregate-based reactants favor nonclassical pathways, even in the presence of seeds. These findings establish a general framework for understanding how seeds govern crystallization mechanisms, with broad implications for controlling nucleation kinetics, polymorph selection, and material properties. While focused on zeolites, this work reveals insights that may be applicable to biominerals, pharmaceuticals, functional materials, and catalysts, providing a basis for engineering crystallization pathways in diverse applications.

Chu-Jon, Carlos [Univ. of Utah, Salt Lake City, UT↗
DOE OSTI2025

Extended Gutzwiller Approximation for Nonlocal Electron-Electron and Electron-Boson Correlations (I): The Theory

Understanding electron-electron and electron-photon correlations is central to uncovering the fundamental mechanisms governing material properties, particularly in systems where strong interactions give rise to emergent phenomena such as superconductivity, magnetism, and polaritonic effects. These correlations play a pivotal role in cavity quantum materials, where hybridized light-matter states enable quantum control over electronic properties. However, capturing both local and nonlocal correlations in these systems presents a significant theoretical challenge. In this work, we extend the Gutzwiller wavefunction method to include nonlocal electron-photon and electron-electron interactions, providing a unified framework to study the intricate interplay between these effects. Our approach accurately captures the long-range correlations induced by photon exchange, enabling the exploration of exotic quantum phases and the effects of cavity coupling on electronic structure. By benchmarking the method across coupling regimes, we reveal the critical role of nonlocal correlations in stabilizing phases, such as superconducting and insulating states, that are inaccessible through local interactions alone. This generalized Gutzwiller framework offers a versatile tool for understanding and designing materials that harness the transformative potential of strong light-matter coupling.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Silicon-On-Silicon Carbide Platform for Integrated Photonics

Silicon carbide (SiC)'s nonlinear optical properties and applications to quantum information have recently brought attention to its potential as an integrated photonics platform. However, despite its many excellent material properties, such as large thermal conductivity, wide transparency window, and strong optical nonlinearities, it is generally a difficult material for microfabrication. Here, it is shown that directly bonded silicon-on-silicon carbide can be a high-performing hybrid photonics platform that does not require the need to form SiC membranes or directly pattern in SiC. The optimized bonding method yields defect-free, uniform films with minimal oxide at the silicon–silicon–carbide interface. Ring resonators are patterned into the silicon layer with standard, complimentary metal–oxide–semiconductor (CMOS) compatible (Si) fabrication and measure room-temperature, near-infrared quality factors exceeding 10 5 . The corresponding propagation loss is 5.7 dB cm -1 . The process offers a wafer-scalable pathway to the integration of SiC photonics into CMOS devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. Built on top of the popular Deep Graph Library (DGL) and Python Materials Genomics (Pymatgen) packages, MatGL is designed to be an extensible “batteries-included” library for developing advanced model architectures for materials property predictions and interatomic potentials. At present, MatGL has efficient implementations for both invariant and equivariant graph deep learning models, including the Materials 3-body Graph Network (M3GNet), MatErials Graph Network (MEGNet), Crystal Hamiltonian Graph Network (CHGNet), TensorNet and SO3Net architectures. MatGL also provides several pre-trained foundation potentials (FPs) with coverage of the entire periodic table, and property prediction models for out-of-box usage, benchmarking and fine-tuning. Finally, MatGL integrates with PyTorch Lightning to enable efficient model training.

chemistry↗
DOE OSTI2025

Modeling Electrodeposition in 3D Porous Architectures for Solid-State Li-Metal Batteries

Li-metal storage in three-dimensional (3D) electrodes is considered a potential dendrite-mitigation strategy. The large surface area and high porosity of these electrodes result in reduced local Li-plating current densities. The porous topology provides a scaffold for Li-deposition and stripping, maintaining both mechanical integrity and Li accessibility. The goal of this study is to understand how characteristics, such as geometry and material properties, affect the current distribution and deposition pattern. To this end, we developed a computational method to track material growth driven by electrodeposition within a complex geometry. This method ensures that the finite-element discretization remains conforming to the moving boundary while preserving an adequate mesh quality, and thus maintains solution accuracy. Using this new computational tool, we analyze the conditions under which porous anode architectures effectively expand the surface area of the charge-transfer interface, and self-regulate current density and dendrite growth.

3D electrode architectures↗
DOE OSTI2024

Nanoscale Imaging and Measurements of Grain Boundary Thermal Resistance in Ceramics with Scanning Thermal Wave Microscopy

Material thermal conductivity is a key factor in various applications, from thermal management to energy harvesting. With microstructure engineering being a widely used method for customizing material properties, including thermal properties, understanding and controlling the role of extended phonon-scattering defects, like grain boundaries, is crucial for efficient material design. However, systematic studies are still lacking primarily due to limited tools. In this study, we demonstrate an approach for measuring grain boundary thermal resistance by probing the propagation of thermal waves across grain boundaries with a temperature-sensitive scanning probe. The method, implemented with a spatial resolution of about 100 nm on finely grained Nb-substituted SrTiO 3 ceramics, achieves a detectability of about 2 × 10 –8 K m 2 W –1 , suitable for chalcogenide-based thermoelectrics. The measurements indicated that the thermal resistance of the majority of grain boundaries in the STiO 3 ceramics is below this value. While there are challenges in improving sensitivity, considering spatial resolution and the amount of material involved in the detection, the sensitivity of the scanning probe method is comparable to that of optical thermoreflectance techniques, and the method opens up an avenue to characterize thermal resistance at the level of single grain boundaries and domain walls in a spectrum of microstructured materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design of a first-of-A-kind instrumented advanced test reactor irradiation Capsule experiment for In situ thermal conductivity measurements of metallic fuel

Metallic fuel undergoes dramatic microstructural changes early in life due to fission gas swelling until ~2–3 at% burnup which affects the conductivity of the material, however the evolution of metallic fuel thermal conductivity during this early phase burnup has never been successfully measured in situ. The Irradiated Material Properties Accelerated Characterization Test (IMPACT) experiment will be the first in a series of experiments to irradiate advanced nuclear metallic fuel specimens with novel embedded thermal conductivity probes in ATR. In the current work the IMPACT experiment final design and supporting analysis is reported in detail. Results are evaluated for various reactor operational conditions to meet the functional requirements of the experiment. Finally, the first iteration of this IMPACT experiment will provide data regarding thermal properties evolution in uranium-zirconium (U10Zr) fuel, but this experiment vehicle is envisioned for future advanced fuels and structural materials irradiations in ATR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Heterogeneous field response of hierarchical polar laminates in relaxor ferroelectrics

Understanding the microscopic origin of the superior electromechanical response in relaxor ferroelectrics requires knowledge not only of the atomic-scale formation of polar nanodomains (PNDs) but also the rules governing the arrangements and stimulated response of PNDs over longer distances. Using x-ray coherent nanodiffraction, we show the staggered self-assembly of PNDs into unidirectional mesostructures that we refer to as polar laminates in the relaxor ferroelectric 0.68PbMg 1/3 Nb 2/3 O 3 -0.32PbTiO 3 (PMN-0.32PT). Here, we reveal the highly heterogeneous electric-field–driven responses of intra- and interlaminate PNDs and establish their correlation with the local strain and the nature of the PND walls. Our observations highlight the critical role of hierarchical lattice organizations on macroscopic material properties and provide guiding principles for the understanding and design of relaxors and a wide range of quantum and functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Test capsules for measuring a change in at least one property of a material, and related methods

A test capsule for measuring at least one property of a material exposed to nuclear radiation comprises a lattice structure configured to exhibit a change in at least one property responsive to exposure to nuclear radiation. The lattice structure comprises a first strut and a second strut connected to the first strut at a node. Related test capsules and methods are also described.

Roach, Robert A.↗
DOE OSTI2026

Ultrafast Formation of Jahn–Teller Polarons Revealed by State-Selective Excitation in Correlated Spinel Co 3 O 4

Jahn–Teller polarons are quasiparticles that stem from symmetry breaking and strong local electron–phonon coupling. They originate from an excess charge carrier being dressed by a local lattice distortion, caused by the Jahn–Teller effect, and they critically impact electrical, structural, and magnetic properties in transition metal oxides. The observation of the microscopic steps involved in their formation is essential for enabling control over material properties through the targeted activation of local, site-specific modifications with light pulses. While Jahn–Teller distortion associated with polaron formation was predicted to contribute significantly to changes in electronic band gap and optical properties in Co 3 O 4 , its experimental observation remains elusive, requiring signatures of local symmetry reduction. In this work, we demonstrate Jahn–Teller polaron formation in spinel Co 3 O 4 . By exciting electronic transitions at 3.10 eV and 1.55 eV, we target either the Oh Cobalt(III) or the Td Cobalt(II) ions, and drive the subsequent coherent responses of the system through two different pathways. For the former, we demonstrate that ligand-to-metal charge transfer leads to Jahn–Teller polaron formation, which is linked to the deformation potential and magnetoelastic coupling. For the latter, we identify the coherent excitation of a T 2g phonon mode launched by on-site d-d electronic transitions. Key to our observations is the ability to target site-specific electronic excitations in spinel Co 3 O 4 using ultrafast optical pulses, while monitoring the ensuing low-energy collective modes through the coherent time-domain response of the material. Our approach, which combines the comparative analysis of experimental fingerprints with the support from density functional theory calculations, is broadly applicable to systems in which Jahn–Teller polaron physics has been theoretically predicted but remains experimentally unverified, and it underscores the potential of electronic-state targeting as a route to selectively excite and probe quasiparticle dynamics in solids.

Lattices↗
DOE OSTI2024

Effect of Heat Treatment on Microstructure and Mechanical Property of 316L Stainless Steel Produced by Laser Powder Bed Fusion

The advanced non-light water reactor designs (Gen IV reactors), including molten salt/ very high temperature/ sodium-cooled and lead-cooled fast reactors, typically operate at higher temperatures and more extreme radiation conditions than light water reactors. An intrinsic part of the deployment and progress of Gen IV reactor designs is selecting the most suitable structural material for a specific application. Additive manufacturing (AM), a fairly new process of making physical, three-dimensional objects from a computer design file, is going to completely change the way of design, build and certify nuclear systems. It offers a range of opportunities to produce complex geometries from existing materials, offers new routes for processing of previously difficult to process materials, allows for design of new high-performance materials, and finally facilitates hybridization of dissimilar materials. This emerging technology has successfully produced cars, wind turbine blade molds and even live cells. It could also open up big opportunities for the nuclear industry to quickly deploy technologies at a fraction of the cost. So far, AM techniques have been preliminarily applied in the field of nuclear reactors, including the classical parts such as the pressure vessel of a small reactor with 508-III steel, the bottom nozzle of a fuel assembly with 304L steel, the fuel cladding with zirconium alloy and the integrated impeller of a pump and the multi-channel valve body with 316L steel [6,7]. The AM applications for operating nuclear reactors started in auxiliary plant components and have slowly migrated to metallic reactors and core components, but many of these are not safety critical components. Although many parts used for nuclear reactors have been fabricated by AM techniques, practical applications in engineering are still a long way off due to the uncertainty factors focused on the processing, material properties, analysis methods and application standards, which feeds the safety and life-cycle of the nuclear reactor. Due to rapid, repeated heating and cooling during production, a high dislocation density was present in the AM material. This microstructure feature is unstable at elevated temperature while high temperature is one of the typical operation environments for nuclear reactors. Thus, it is important to understand the thermal effect on the microstructure of AM material. The objectives of this study are to investigate the effect of heat treatment on the microstructure and mechanical properties of 316L stainless steel produced by laser powder bed fusion additive manufacturing, and to determine an appropriate heat treatment practice that will be applied to the lightweight AM lattice-structured material with the same chemistry. The heat treatment study consisted of annealing the samples at a temperature range of 800 to 1200 oC with a 50 oC increment for different times (1-24 hours), followed by vacuum or air cooling. Microstructural characterization was carried out by Scanning Electron Microscope (SEM). Grain size and crystallographic orientation were investigated by Electron Backscatter Diffraction (EBSD). Vickers hardness tests with a 0.5 kg load were employed to determine the hardness of samples after different heat treatments. After heat treatment, the random crystallographic orientation was preserved, and the volume fraction of high-angle grain boundaries (grain boundary misorientation =15 oC) remained the same. The dislocation density decreased with annealing temperature due to recovery. The fine subgrain structures in the as-printed specimen were quite stable up to 1200 oC. Minimal recrystallization was observed up to 1200 oC. Recrystallization initiated only after 8.5 hours at 1200 oC. The SEM images did not show obvious dependence of microstructure on cooling rate. The hardness of the specimens decreased with increasing annealing temperature as a result of the decrease in dislocation density. It is interesting to note that the AM material showed very similar hardness to the wrought material when annealing at similar temperature, although the microstructures are very different. Annealing at 1050 oC for 1 hour followed by air cooling was selected as the heat treatment procedure for the lattice designed lightweight AM 316L material.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗
DOE OSTI2024

Elevated Temperature Graphite Mechanical Testing

High purity graphite will be used for core components within most High Temperature Reactor (HTR) designs. Several "high tech” industries currently utilize synthetic, high-purity, commercially available graphite components to fabricate photovoltaic cells, semi-conductors, optical fibers, and other high value electronic industry products. New advanced HTR designs are also interested in using these graphite grades for long-term, internal core component applications. Consequently, the US Department of Energy, Advanced Reactor Technologies (DOE-ART) program has spent several years testing different high purity graphite grades for potential use within these new nuclear reactor designs. A significant part of that effort has been in the development and improvement of American Society for Testing and Materials (ASTM) test standards specifically for nuclear graphite grades. Nearly all ASTM test standards have either been developed or improved by the DOE-ART program over the past 25 years. The ART program continues to assist in the development of new ASTM test standards in support of the future commercial HTR fleet currently being designed and built in the USA. The newest effort undertaken by ART is the development of high temperature mechanical testing practices that may be acceptable for a future ASTM test standard (or guide) for this critical material property measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Synthesizing, Compounding, and Characterizing a Heat Labile Polyurethane Foam

ABSTRACT A need exists for a packaging foam material that can be converted from solid to gaseous degradation products at reasonably low energy levels or temperatures, such as 100O C. This paper will primarily discuss the approaches currently being used to synthesize and characterize such a material. These approaches include the incorporation of novel polyols such as azo containing diols, polycarbonate diols, and polypropylene carbonate polyols into polyurethane foams. Characterization methods include NMR, FTIR, TGA, finite element analysis, impact strength, and others. This project will be funded for a duration of three years. Year 1 focused on developing the proposed test methods and producing an initial rigid polyurethane foam. Year 2 focuses on refining the materials and test methods. If appropriate, design of experiment (doe) techniques will be used to optimize components, component levels, density and other variables to attain required final material properties (TGA weight loss, impact strength, etc.). Year 3 focuses on scaling up to larger engineering quantities. The application for this material is in load securement for transportation of low level radioactive waste materials within the US Department of Energy (DOE) complex. Foam in place process equipment and operators will be shielded using this novel method over current practice. Current practice can involve time consuming methods of load securement in low level radiation environments. This new technique would eliminate exposure time securing the load and greatly improve the As Low As Reasonably Attainable (ALARA) conditions. The objective is to progress to higher Technical Readiness Levels (TRL) and larger pilot scale quantities. This paper discusses methodologies and presents current results to date.

Kranjc, Mark D.↗
DOE OSTI2025

Enhancing Post-Irradiation Examination (PIE) Efficiency with High-Throughput Experiments

Nuclear materials testing is essential for understanding changes in reactor environments, but traditional methods are costly and time-consuming. High-Throughput Experimentation (HTE) enables rapid screening and optimization of material properties by significantly increasing the number of specimens in the experiment. In this work, HTE methods were employed to irradiate novel materials at the Advanced Test Reactor (ATR) at Idaho National Laboratory. A total of 367 sub-sized tensile specimens were irradiated using the standard capsule design. To facilitate HTE, automated systems such as the Automated Mechanical Testing System were implemented for mechanical testing within hot cell environments, thereby reducing the need for manual interaction with hot cell manipulators and significantly lowering both the cost and duration of experiments. Digital image correlation (DIC) was used to measure displacement during mechanical testing, providing precise, non-contact measurement capabilities. The methodologies developed in this research will support the advancement of HTE techniques for future nuclear materials testing experiments at ATR. This approach allows for more efficient and cost-effective evaluation of new materials, ultimately leading to improved reactor performance, enhanced safety, and extended longevity within the nuclear industry.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗