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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Viscoelastic Damping and Wave Cutoff of Titanium Alloy and Lattices

Here, the 3D-printed titanium alloy Ti5553 solid and octet truss lattice specimens are studied via resonant ultrasound spectroscopy, free decay of vibration and quasi-static methods to determine viscoelastic damping. Damping in solid alloy and a lattice is between 10 -4 and 10 -3 . Much of the damping at high sonic frequency is attributed to stress-induced heat flow between heterogeneities due to 3D printing. Pulsed wave ultrasound experiments disclose reverberation in the cell structure of the lattice. Continuous wave ultrasound experiments show that the transmissibility in the lattice rolls off beginning at about 50 kHz and becomes negligible above 110 kHz. By contrast, the polymer polymethyl methacrylate (PMMA), though it is viscoelastic, readily transmits waves up to 1 MHz. The cutoff frequency in the lattice is associated with the structure size, not intrinsic damping in the alloy. The octet truss lattice, in addition to providing good mechanical performance, is also an ultrasonic metamaterial.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Achieving the 1D Atomic Chain Limit in Van der Waals Crystals

Experiments with graphene have demonstrated that 2D van der Waals materials can be stable, robust, and efficiently manipulated at the level of individual atomic planes. However, the stability and manipulation of 1D van der Waals materials and individual atomic chains remains elusive. Here, in this work, the ability to exfoliate and process two representative van der Waals materials containing 1D motifs, namely MoI 3 and Ta 2 Se 8 I, at the scale of individual atomic chains is demonstrated. High‐resolution transmission electron microscopy and atomic force microscopy studies confirm the presence of stable individual atomic chains of MoI 3 at room temperature. It is further shown that 1D van der Waals materials with low exfoliation energy, such as Ta 2 Se 8 I, can be processed with electron beams to achieve suspended individual atomic chains. Ab initio calculations corroborate the findings regarding the cleavage energies and the thermodynamic stability of individual atomic chains in these 1D van der Waals materials. These results demonstrate that the top‐down approach in material processing can be extended to the scale of individual chains.

1D materials↗
DOE OSTI2024

Coherent-Precipitation-Stabilized Phase Formation in Over-Stoichiometric Rocksalt-Type Li Superionic Conductors

Rationalizing synthetic pathways is crucial for material design and property optimization, especially for polymorphic and metastable phases. Over-stoichiometric rocksalt (ORX) compounds, characterized by their face-sharing configurations, are a promising group of materials with unique properties; however, their development is significantly hindered by challenges in synthesizability. Here, taking the recently identified Li superionic conductor, over-stoichiometric rocksalt Li–In–Sn–O (o-LISO) material as a prototypical ORX compound, the mechanisms of phase formation are systematically investigated. It is revealed that the spinel-like phase with unconventional stoichiometry forms as coherent precipitate from the high-temperature-stabilized cation-disordered rocksalt phase upon fast cooling. This process prevents direct phase decomposition and kinetically locks the system in a metastable state with the desired face-sharing Li configurations. This insight enables us to enhance the ionic conductivity of o-LISO to be >1 mS cm -1 at room temperature through low-temperature post-annealing. This work offers insights into the synthesis of ORX materials and highlights important opportunities in this new class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Uranium Doped Gallium Nitride Epitaxial Thin Films

Gallium nitride (GaN) is near ubiquitous in modern day technologies, forming the backbone of solid-state lighting and high-power electronics. Engineering the physical properties of GaN has been investigated to some degree by the incorporation or doping of most of the elements of the periodic table, but the actinides remain unexplored. Molecular beam epitaxy is used to demonstrate uranium doping of GaN single crystals. High structural quality of the host matrix is maintained despite partial elemental segregation of the uranium dopant into 1D structures at the levels presented here. Electronic transport measurements reveal relatively high conductivity, which persists down to cryogenic temperature and is characterized by the formation of narrow gaps in the electronic band structures very close to the Fermi level. Photoluminescence measurements reveal that the U-doped GaN exhibits optical behavior similar to that of the GaN substrate. The addition of actinide materials to a non-centrosymmetric, optically active, radiation-hard, and electronically tunable host matrix opens a world of possibilities for investigating and leveraging elements with high electron correlations in the pursuit of novel devices.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

In‐Scribe Silane Bonding for Mechanical Reinforcement of Perovskite Photovoltaic Modules

Despite the extraordinary rise in power conversion efficiency over the last decade, metal halide perovskite (MHP) photovoltaics remain more mechanically fragile than other PV technologies. In this work, the scribe area, created by the monolithic interconnection of thin-film solar cells, is used to extrinsically reinforce the mechanical robustness of packaged MHP solar modules. In contrast to the epoxy-based chemistries often leveraged in the MHP literature, silane-grafted polyolefin encapsulants are designed to form strong covalent bonds to oxide surfaces, specifically to glass and the transparent conductive oxide at the base of the scribe line. Pseudo-modules encapsulated with silane-grafted polyolefin are measured with more than an order-of-magnitude enhancement infracture energy from 0.27 ± 0.01 J·m −2 (no scribes) to 5.97 ± 0.42 J·m −2 (scribes perpendicular to delamination directioncovering ≈2.2% of the module area). The silane-grafted polyolefin retains strong adhesion even after undergoing an accelerated IEC 61215 thermal cycling test consisting of 250 cycles. We find that the in-scribe bonding allows perovskite modules to have adhesion strength comparable to commercial c-Si and CdTe technologies with only 5% reduction in the active module area. This manufacturing-compatible approach offers a practical solution to address the mechanical integrity challenges in MHP solar modules, regardless of cell architecture.

14 SOLAR ENERGY↗
DOE OSTI2025

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Holistic Microstructure Control Strategies in Photopolymerization‐Induced Phase Separation of Acrylate Systems

Open porous materials, known for their large surface area and interconnected structures, are essential in various applications, including batteries, ion exchange, catalysis, filtration, and electronic waste recycling. A critical aspect of the functionality of porous membranes is the precise control of pore size and morphology. Photopolymerization-induced phase separation (photo-PIPS) offers a convenient and versatile methods for creating porous structures. However, controlling the porous morphology remains challenging due to the complex interplay between thermodynamics, polymerization kinetics, and monomer structures, which makes it difficult to establish the relationship between processing conditions and resulting morphology in photo-PIPS. Herein, a physics-based phase-field model capable of generating and characterizing the microstructures of porous materials based on both average and localized features is developed. Using the phase-field simulations as test bed, the effects of polarity, light intensity, and curing temperature, as well as the previously unexplored roles of chain transfer agents and substrates, on the morphology of the resulting porous microstructure are investigated. Experiments are performed to verify the results predicted by the simulations. This work lays out a comprehensive guide for designing PIPS-derived porous microstructures and offers practical engineering strategies for tailoring microstructure-level topology and size of pores for application-specific needs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Quantifying Uncertainties in Heat Capacity Measurements of Molten Salts Determined Using Differential Scanning Calorimetry

Uncertainty in specific heat capacity values of a molten salt determined by using differential scanning calorimetry (DSC) was assessed based on the precision of replicate measurements of heat flows used in the calculation and effects of corrections that are commonly made to heat flow measurements. The ratio method of determining heat capacity was applied using the results of replicate heat flow measurements made with two empty cells, a sapphire reference material, and three samples of a doped NaCl-UCl 3 salt mixture. Replicate measurements with empty cells were used to quantify the effects of system instabilities and sensitivities on the measured heat flows of sapphire and salt. The combined effects of uncertainties in individual heat flow measurements made with blank cells using this system were quantified to be 2.6 μV based on isothermal holds before and after the scan, with cell placement adding the greatest uncertainty. This value was used as the tolerance for accepting background-corrected heat flows measured with sapphire and salt to calculate the specific heat capacity. The acceptable heat flows measured for sapphire and salt over the temperature range of 540 to 725 °C resulted in calculated specific heat capacity values ranging from 0.53 to 0.91 J g −1 K −1 with an overall average value of 0.70 J g −1 K −1 and an uncertainty of 0.22 J g −1 K −1 at the 99 % confidence level. The combined uncertainty in the specific heat capacity masked detection of any effect of temperature or salt composition that occurred.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The SuperCam Instrument Suite on the NASA Mars 2020 Rover: Body Unit and Combined System Tests

The SuperCam instrument suite provides the Mars 2020 rover, Perseverance, with a number of versatile remote-sensing techniques that can be used at long distance as well as within the robotic-arm workspace. These include laser-induced breakdown spectroscopy (LIBS), remote time-resolved Raman and luminescence spectroscopies, and visible and infrared (VISIR; separately referred to as VIS and IR) reflectance spectroscopy. A remote micro-imager (RMI) provides high-resolution color context imaging, and a microphone can be used as a stand-alone tool for environmental studies or to determine physical properties of rocks and soils from shock waves of laser-produced plasmas. SuperCam is built in three parts: The mast unit (MU), consisting of the laser, telescope, RMI, IR spectrometer, and associated electronics, is described in a companion paper. The on-board calibration targets are described in another companion paper. Here we describe SuperCam’s body unit (BU) and testing of the integrated instrument. The BU, mounted inside the rover body, receives light from the MU via a 5.8 m optical fiber. The light is split into three wavelength bands by a demultiplexer, and is routed via fiber bundles to three optical spectrometers, two of which (UV and violet; 245–340 and 385–465 nm) are crossed Czerny-Turner reflection spectrometers, nearly identical to their counterparts on ChemCam. The third is a high-efficiency transmission spectrometer containing an optical intensifier capable of gating exposures to 100 ns or longer, with variable delay times relative to the laser pulse. This spectrometer covers 535–853 nm ( $105\text{--}7070~\text{cm}^{-1}$ Raman shift relative to the 532 nm green laser beam) with $12~\text{cm}^{-1}$ full-width at half-maximum peak resolution in the Raman fingerprint region. The BU electronics boards interface with the rover and control the instrument, returning data to the rover. Thermal systems maintain a warm temperature during cruise to Mars to avoid contamination on the optics, and cool the detectors during operations on Mars.Results obtained with the integrated instrument demonstrate its capabilities for LIBS, for which a library of 332 standards was developed. Examples of Raman and VISIR spectroscopy are shown, demonstrating clear mineral identification with both techniques. Luminescence spectra demonstrate the utility of having both spectral and temporal dimensions. Finally, RMI and microphone tests on the rover demonstrate the capabilities of these subsystems as well.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Tensor network investigation of the double layer Kagome compound Ca 10 Cr 7 O 28

Quantum spin liquids are exotic quantum phases of matter that do not order even at zero temperature. While there are several toy models and simple Hamiltonians that could host a quantum spin liquid as their ground state, it is very rare to find actual, realistic materials that exhibit their properties. At the same time, the classical simulation of such instances of strongly correlated systems is intricate and reliable methods are scarce. Here, in this work, we investigate the quantum magnet Ca 10 Cr 7 O 28 that has recently been discovered to exhibit properties of a quantum spin liquid in inelastic neutron scattering experiments. This compound has a distorted bilayer Kagome lattice crystal structure consisting of Cr 5+ ions with spin- moments. Coincidentally, the lattice structure renders a tensor network algorithm in 2D applicable that can be seen as a new variant of a projected entangled simplex state algorithm in the thermodynamic limit. In this first numerical investigation of this material that takes into account genuine quantum correlations, good agreement with the experimental findings is found. Our study contributes to uplifting tensor networks from conceptual tools to methods to describe real two-dimensional quantum materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

An elastin-like polymer targeting vascular endothelial growth factor receptor-1 reduces survival in serum-starved endothelial cells

Peptides often exhibit biological activity that depends on the context in which they are displayed and delivered. Understanding and controlling these contextual effects on peptide function is critical for designing targeted and responsive peptide-based biomaterials and therapeutics. Genetically engineered protein polymers such as elastin-like polypeptides (ELPs) can incorporate bioactive peptide motifs and are attractive candidates for biomaterials used in tissue engineering and targeted drug delivery. They also present an opportunity for investigating and modulating cell signaling pathways by presenting a peptide ligand in various defined chemical and physical environments. Vascular endothelial growth factor receptor-1 (VEGFR1) signaling plays important and complex roles in cell survival and angiogenesis, but polymeric materials that interact with this signaling axis are scarce. In this study, a novel genetically engineered elastin-like polymer that targets VEGFR1 is characterized. This polymer, termed R1B-ELP, binds to human endothelial cells in a manner dependent on its VEGFR1-targeting motif and, based on cell proliferation and cytotoxicity assays, demonstrates activity consistent with disrupting pro-survival signaling necessary for endothelial cell function under conditions of environmental stress. Notably, these findings indicate that ELP fusion alters the functional behavior of the targeting peptide. Modulators of VEGFR1 signaling have potential applications in basic studies of angiogenesis as well as in therapeutic applications targeting vascular or inflammatory diseases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dynamic genetic adaptation of Bacteroides thetaiotaomicron during murine gut colonization

To understand how a bacterium ultimately succeeds or fails in adapting to a new host, it is essential to assess the temporal dynamics of its fitness over the course of colonization. Here, we introduce a human-derived commensal organism, Bacteroides thetaiotaomicron (Bt), into the guts of germ-free mice to determine whether and how the genetic requirements for colonization shift over time. Combining a high-throughput functional genetics assay and transcriptomics, we find that gene usage changes drastically during the first days of colonization, shifting from high expression of amino acid biosynthesis genes to broad upregulation of diverse polysaccharide utilization loci. Within the first week, metabolism becomes centered around utilization of a predominant dietary oligosaccharide, and these changes are largely sustained through 6 weeks of colonization. Spontaneous mutations in wild-type Bt also evolve around this locus. These findings highlight the importance of considering temporal colonization dynamics in developing more effective micro biome-based therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Improving microstructures segmentation via pretraining with synthetic data

Image analysis of material microstructures through microscopy is an integral capability in the field of materials science. The topological and chemical information obtained through microscopy allow us to draw vital connections between material microstructures, properties, and processing. While scanning electron microscopy (SEM) is able to yield a considerable wealth of information interpretable by the intuition of experts, there has been considerable interest in using machine learning, convolutional neural networks (CNNs) in particular, for such image analysis task. Training CNNs for an image analysis task requires a large annotated dataset. However, in many materials science applications, obtaining a large annotated dataset is cost and labor intensive. In this work, we study the use of synthetic data to enlarge the available annotated experimental data of uranium oxide. We utilize a modified Potts model to simulate uranium oxide particles with morphologies similar to those observed experimentally. We then leverage an image-to-image translation model to synthesize the simulated particles as if they are acquired with SEM. Through this process, we obtain pairs of particle images and their corresponding SEM representations, which corresponds to pairs of annotations and images. Unlike previous works, we leverage synthetic data for pretraining a CNN model prior, and finetune that model further with experimental data. We experimentally demonstrate that using synthetic data as incremental learning process benefits the overall performance compared to training a model on combined synthetic and experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Automatic building energy model development and debugging using large language models agentic workflow

Building energy modeling (BEM) is a complex process that demands significant time and expertise, limiting its broader application in building design and operations. While Large Language Models (LLMs) agentic workflow have facilitated complex engineering processes, their application in BEM has not been specifically explored. This paper investigates the feasibility of automating BEM using LLM agentic workflow. Here, we developed a generic LLM-planning-based workflow that takes a building description as input and generates an error-free EnergyPlus building energy model. Our robust workflow includes four core agents: 1) Building Description Pre-Processing, 2) IDF Object Information Extraction, 3) Single IDF Object Generator Suite, and 4) IDF Debugging Agent. These agents divide the complex tasks into manageable sub-steps, enabling LLMs to generate accurate and reliable results at each stage. The case study demonstrates the successful translation of a building description into an error-free EnergyPlus model for the iUnit modular building at the National Renewable Energy Laboratory. The effectiveness of our workflow surpasses: 1) naive prompt engineering, 2) other LLM-based workflows, and 3) manual modeling, in terms of accuracy, reliability, and time efficiency. The paper concludes with a discussion on the interplay between foundational models and LLM agent planning design, advocating for the use of fine-tuned, specialized models to advance this field.

97 MATHEMATICS AND COMPUTING↗