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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Autonomous Synthesis of Thin Film Materials with Pulsed Laser Deposition Enabled by In Situ Spectroscopy and Automation

Autonomous systems that combine synthesis, characterization, and artificial intelligence can greatly accelerate the discovery and optimization of materials, however platforms for growth of macroscale thin films by physical vapor deposition techniques have lagged far behind others. Here this study demonstrates autonomous synthesis by pulsed laser deposition (PLD), a highly versatile synthesis technique, in the growth of ultrathin WSe 2 films. Further, by combing the automation of PLD synthesis and in situ diagnostic feedback with a high-throughput methodology, this study demonstrates a workflow and platform which uses Gaussian process regression and Bayesian optimization to autonomously identify growth regimes for WSe 2 films based on Raman spectral criteria by efficiently sampling 0.25% of the chosen 4D parameter space. With throughputs at least 10x faster than traditional PLD workflows, this platform and workflow enables the accelerated discovery and autonomous optimization of the vast number of materials that can be synthesized by PLD.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Magnetic pair distribution function and half polarized neutron powder diffraction at the HB-2A powder diffractometer

Local magnetic order and anisotropy are often central for understanding fundamental behavior and emergent functional properties in quantum materials and beyond. Advances in neutron powder diffraction experiments and analysis tools now allow for quantitative determination. Here, we demonstrate this here with complementary total neutron scattering and polarized neutron measurements on the HB-2A neutron powder diffractometer at the High Flux Isotope Reactor (HFIR). In recent years, magnetic pair distribution function (mPDF) analysis has emerged as a powerful technique for probing local magnetic spin ordering of magnetic materials. This method can be broadly applied to any magnetic material but is particularly effective for studying systems with short-range magnetic order, such as materials with reduced dimensionality, geometrically frustrated magnets, thermoelectrics, multiferroics, and correlated paramagnets. Magnetic anisotropy often underpins the short-range order adopted. Half-polarized neutron powder diffraction (pNPD) can be used to determine the local susceptibility tensor on the magnetic sites to quantify the magnetic anisotropy. Combining the techniques of mPDF and pNPD can therefore provide valuable insights into local magnetic behavior. A series of measurements optimized for these techniques are presented as exemplar cases focused on frustrated materials where short-range order dominates, these include measurements to ultra-low temperature (<100 mK) not typically accessible for such experiments.

Half polarized neutron scattering↗
DOE OSTI2022

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Organoboron Based Antioxidants

Earth’s environment can be considered especially harsh due to the cyclic exposure of heat, moisture, oxygen, and ultraviolet (UV) and visible light. Polymer-derived materials subjected to these conditions over time often exhibit symptoms of degradation and deterioration, ultimately leading to accelerated material failure. To combat this, chemical additives known as antioxidants are often used to delay the onset of weathering and oxidative degradation. Phenol-derived antioxidants have been used for decades due to their excellent performance and stability; unfortunately, concerns regarding their toxicity and leaching susceptibility have driven researchers to identify novel solutions to replace phenolic antioxidants. Herein, we report on the antioxidant efficacy of organoborons, which have been known to exhibit antioxidant activity in plants and animals. Four different organoboron molecules were formulated into epoxy materials at various concentrations and subsequently cured into thermoset composites. Their antioxidant performance was subsequently analyzed via thermal, colorimetric, and spectroscopic techniques. Generally, thermal degradation and oxidation studies proved inconclusive and ambiguous. However, aging studies performed under thermal and UV-intensive conditions showed moderate to extreme color changes, suggesting poor antioxidant performance of all organoboron additives. Infrared spectroscopic analysis of the UV aged samples showed evidence of severe material oxidation, while the thermally aged samples showed only slight material oxidation. Solvent extraction experiments showed that even moderately high organoboron concentrations show negligible leaching susceptibility, confirming previously reported results. This finding may have benefits in applications where additive leaching may cause degradation to sensitive materials, such as microelectronics and other materials science related areas.

36 MATERIALS SCIENCE↗
DOE OSTI2021

RapidEELS: machine learning for denoising and classification in rapid acquisition electron energy loss spectroscopy

Recent advances in detectors for imaging and spectroscopy have afforded in situ, rapid acquisition of hyperspectral data. While electron energy loss spectroscopy (EELS) data acquisition speeds with electron counting are regularly reaching 400 frames per second with near-zero read noise, signal to noise ratio (SNR) remains a challenge owing to fundamental counting statistics. In order to advance understanding of transient materials phenomena during rapid acquisition EELS, trustworthy analysis of noisy spectra must be demonstrated. In this study, we applied machine learning techniques to denoise high frame rate spectra, benchmarking with slower frame rate “ground truths”. The results provide a foundation for reliable use of low SNR data acquired in rapid, in-situ spectroscopy experiments. Such a tool-set is a first step toward both automation in microscopy as well as use of these methods to interrogate otherwise poorly understood transformations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Open-Cell Environmental Transmission Electron Microscopy Technique for In Situ Characterization of Samples in Aqueous Liquid Solutions

The desire to image specimens in liquids has led to the development of open-cell and closed-cell techniques in transmission electron microscopy (TEM). The closed-cell approach is currently more common in TEM and has yielded new insights into a number of biological and materials processes in liquid environments. The open-cell approach, which requires an environmental TEM (ETEM), is technically challenging but may be advantageous in certain circumstances due to fewer restrictions on specimen and detector geometry. Here, we demonstrate a novel approach to open-cell liquid TEM, in which we use salt particles to facilitate the in situ formation of droplets of aqueous solution that envelope specimen particles coloaded with the salt. This is achieved by controlling sample temperature between 1 and 10°C and introducing water vapor to the ETEM chamber above the critical pressure for the formation of liquid water on the salt particles. Our use of in situ hydration enables specimens to be loaded into a microscope in a dry state using standard 3 mm TEM grids, allowing specimens to be prepared using trivial sample preparation techniques. Furthermore, our future aim will be to combine this technique with an in situ light source to study photocorrosion in aqueous environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Current Status of Developing Ultrafast Mega-electron-volt Electron Microsope

Recent studies of ultrafast electron microscopy (UEM) techniques show the use of short bunches of relativistic electrons is promising for the development of a new instrument for imaging various materials. Compared to conventional electron microscopes, the main advantage of UEMs with the electron energy of a few MeV is the possibility to study thick samples. We will discuss the progress of UEM design to date, the principal challenges on the way to a high resolution, and possible methods for their mitigation including the design of low-aberration magnetic optics, RF and mechanical subsystems with high stability, and precise collimation of electrons scattered in the samples.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Simultaneous x-ray and neutron 4D tomographic study of drying-driven hydro-mechanical behavior of cement-based materials at moderate temperatures

The drying of cement-based materials is intimately related to their durability, which has significant economic, social and environmental repercussions. The evolution of the saturation of the pore network and the associated drying shrinkage are in fact leading causes of cracking and of the ensuing penetration of aggressive chemicals. This process is highly heterogeneous, due to the thermo-hydric spatial gradients developing in the material from the exposed surfaces to its core and because of local effects, driven by the intrinsically heterogeneous micro-structure (e.g., by the distribution of pores and aggregates). It follows that macroscopic, sample-scale measurements cannot fully disclose the complexity of the underlying processes. In the last few decades, significant advances in full-field techniques have allowed an unprecedented insight into these local processes. For cement-based materials, x-ray and neutron tomography lend themselves as ideal, and highly complementary, tools for the study of their thermo-hydro-mechanical behavior. Notably, the high sensitivity to density variations of x-ray imaging gives access to the developments of fractures, in 4D (3D + time). On the other hand, neutron tomography allows the study of the evolution of the moisture field in 4D, thanks to its high hydrogen sensitivity. The combination of these two techniques provides a unique insight in thermo-hydro-mechanical couplings, e.g., the effect of cracks on the water content field. This contribution presents novel 5D datasets (3D tomographies along time, plus truly simultaneous x-ray and Neutron rapid acquisitions) in-operando of a cement paste and of a concrete sample heated at moderate temperatures (up to 140{sup ∘}C). The analysis of this 5D data-set (once aligned in time and across modalities) allows for example a quantification of the 4D moisture profiles which were found to predict an overall water loss at hydric equilibrium coherent with the corresponding analytical analysis. In the cement paste sample, the x-ray dataset captures the evolution of an extensive cracking network, opening and propagation toward the core of the sample. A novel analysis procedure is here proposed which allows the extraction of these fractures and the analysis of their interplay with local drying as captured through neutron imaging. This for example reveals the depth of penetration of drying in the vicinity of the fractures along time, which is essential for the assessment and calibration of hydro-mechanical coupled models.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microstructure-Based Understanding of High-Temperature Deformation Behaviors in Laser Powder Bed Fusion (LPBF) 316H Stainless Steel

This report presents the results of high-temperature mechanical property testing and microstructural analysis of laser powder bed fusion (LPBF) 316H stainless steel (SS) conducted during Fiscal Year 2025 (FY25) under the U.S. Department of Energy, Office of Nuclear Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program. The study builds upon prior work by expanding the mechanical property test matrix and advancing a microstructure-based mechanistic understanding of LPBF 316H SS performance, with a focus on the solution annealed (SA, 1100°C for 1 hour) materials. High-temperature tension, creep, fatigue, and creep-fatigue tests were performed. Thermal aging studies were conducted. Advanced characterization techniques, including scanning electron microscopy (SEM), scanning transmission electron microscopy (STEM), and high-energy synchrotron X-ray diffraction, were employed to investigate the microstructural evolution during thermal aging and mechanical testing. It was discovered that the as-built (AB) LPBF 316H SS exhibited precipitation kinetics during thermal aging that are 10–100 times faster than its wrought counterpart due to the presence of high densities of preferred nucleation sites, while the precipitation kinetics in SA LPBF 316H was under investigation. The accelerated precipitation of embrittling phases such as sigma phase in LPBF 316H SS compared to its wrought counterpart led to significant impacts on creep ductility. The influence of laser printing parameters and build orientations on fatigue and creep-fatigue performance was observed. In assessing the creep-fatigue performance, it was discovered that the SA LPBF 316H samples failed in less than 200 cycles under 595°C, 0.5% (strain amplitude) with a 60-minute hold time. This work establishes a mechanistic framework for predicting the long-term behavior of LPBF 316H SS, supporting its rapid qualification under the ASME BPVC. The findings contribute to the broader goal of enabling the deployment of advanced materials in next-generation nuclear energy systems. An outlook for FY26 work, including continued aging studies, mechanical testing, and microstructural characterization, is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Infrared nanospectroscopy characterization of metal oxide photoresists

Implementation of extreme ultraviolet (EUV) lithography in high-volume semiconductor manufacturing requires a reliable and scalable EUV resist platform. A mechanistic understanding of the pros and cons of different EUV resist materials is critically important. However, most material characterization methods with nanometer resolution use an x-ray photon or electron beam as the probe, which often cause damage to the photoresist film during measurement. Here, we illustrated the use of non-destructive infrared nanospectroscopy [or nano-Fourier-Transform infrared spectroscopy (nano-FTIR)] to obtain spatially resolved composition information in patterned photoresist films. Further, clear evidence of exposure-induced chemical modification was observed at a spatial resolution down to 40 nm, well below the diffraction limit of infrared light. With improvements, such a nano-FTIR technique with nanoscale spatial resolution, chemical sensitivity, and minimal radiation damage can be a promising candidate for the fundamental study of material properties relevant to EUV lithography.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigation and Suppression of Oxygen Release by LiNi 0.8 Co 0.1 Mn 0.1 O 2 Cathode under Overcharge Conditions

The safety issue of lithium-ion batteries is a crucial factor limiting their large-scale application. Therefore, it is of practical significance to evaluate the impact of their overcharge behavior because of the severe levels of oxygen release of cathode materials during this process. Here, by combining a variety of in situ techniques of spectroscopy and electron microscopy, this work studies the structural degradation of LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811) accompanying the oxygen release in the overcharge process. It is observed that a small amount of O 2 evolves from the initial surface at ≈4.7V. When charging to a higher voltage (≈5.5V), a large amount of O 2 evolves on the newly formed surface due to the occurrence of microcracks. Based on experimental results and theoretical calculations, it is determined that the oxygen release mainly occurs in the near-surface regions, where the remaining oxygen vacancies accumulate to create voids. To suppress the oxygen release, single-crystalline NCM811 with integrated structure is introduced and serves as a cathode, which can effectively inhibit morphology destruction and reduce the activation of lattice oxygen in the surface region. These findings provide a theoretical basis and effective strategy for improving the safety performance of Ni-rich cathode materials in practical applications.

25 ENERGY STORAGE↗
DOE OSTI2022

Electrical Manipulation of Topological Phases in a Quantum Anomalous Hall Insulator

Quantum anomalous Hall phases arising from the inverted band topology in magnetically doped topological insulators have emerged as an important subject of research for quantization at zero magnetic fields. Though necessary for practical implementation, sophisticated electrical control of molecular beam epitaxy (MBE)-grown quantum anomalous Hall matter have been stymied by growth and fabrication challenges. Here, in this study, a novel procedure is demonstrated, employing a combination of thin-film deposition and 2D material stacking techniques, to create dual-gated devices of the MBE-grown quantum anomalous Hall insulator, Cr-doped (Bi,Sb) 2 Te 3 . In these devices, orthogonal control over the field-induced charge density and the electric displacement field is demonstrated. A thorough examination of material responses to tuning along each control axis is presented, realizing magnetic property control along the former and a novel capability to manipulate the surface exchange gap along the latter. Through electrically addressing the exchange gap, the capabilities to either strengthen the quantum anomalous Hall state or suppress it entirely and drive a topological phase transition to a trivial state are demonstrated. The experimental result is explained using first principle theoretical calculations, and establishes a practical route for in situ control of quantum anomalous Hall states and topology.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-performance molded composites using additively manufactured preforms with controlled fiber and pore morphology

Here, large-scale multimaterial preforms produced by additive manufacturing (AM) underwent compression molding (CM) to produce high-performance thermoplastic composites reinforced with short carbon fibers. AM and CM techniques were integrated to control the fiber orientation (microstructure) and to reduce void content for the improved mechanical performance of the composite. The new integrated manufacturing technique is termed “additive manufacturing-compression molding” (AM-CM). For the present study, the most common materials were used for large-scale printing, i.e., acrylonitrile butadiene styrene (ABS), carbon fiber (CF)–filled ABS (CF/ABS) and glass fiber (GF)–filled ABS (GF/ABS). Three different manufacturing processes; (a) AM (b) extrusion compression molding (ECM), and (c) AM-CM were used to prepare four different panel configurations: (1) neat ABS, (2) CF/ABS, (3) overmold (CF/ABS over neat ABS), and (4) sandwich (neat ABS between two CF/ABS layers). The mechanical properties (tensile and flexural strength and modulus, and Izod impact energy) of samples prepared via all three manufacturing processes were compared. X-ray microcomputer tomography was employed to evaluate the fiber orientation distribution and the volumetric porosity content. The preform maintained high fiber alignment (≈ 82% of fibers within the range of 0–20° in the deposition direction), and the volumetric porosity was reduced by 50% from 3.79% to 1.91% after compression. The alignment of long pores along the deposition direction was also observed. The mechanical properties are discussed with correlation to the fiber alignment and void content in the samples. CF/ABS samples prepared by AM-CM showed significant improvement of 11.15%, 35.27%, 28.6%, and 74.3% in the tensile strength, tensile modulus, flexural strength, and flexural modulus, respectively, when compared with samples prepared by ECM. Unique aspects of this study are the demonstration of large-scale multimaterial AM and the use of multimaterials as preforms to make high-performance composites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Insights into the Li Diffusion Mechanism in Si/C Composite Anodes for Lithium-Ion Batteries

Recently, Si/C composite materials have attracted enormous research interest as the most promising candidates for the anodes of next-generation lithium-ion batteries, owing to their high energy density and mechanical buffering property. However, the fundamental mechanism of Li diffusion behavior in various Si/C composite materials remains unclear, with our understanding limited by experimental techniques and continuum modeling methodologies. Herein, the atomic behavior of Li diffusion in the Si/C composite material is studied within the framework of density functional theory. Two representative structural mixing formats, that is, simple mixture mode and core-shell mode, are modeled and compared. We discover that the carbon material increases Li diffusion in silicon from 7.75 x 10 -5 to 2.097 x 10 -4 cm 2 /s. The boost is about 50% more obvious in the mixture mode, while the core-shell structure shows more dependence on the atomic structures of the carbon layer. These results offer new insights into Li diffusion behavior in Si/C composites and unlock the enhancing mechanism for Li diffusion in Si/C. Furthermore, this understanding facilitates the modeling of batteries with composite anodes and will guide the corresponding structure designs for robust and high-energy-density batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Ordered porous RGO/SnO 2 thin films for ultrasensitive humidity detection

In this work, ordered porous thin films of reduced graphene oxide and tin oxide (rGO/SnO 2 ) were synthesized by a polystyrene sphere monolayer colloidal crystal template method, and their gas-sensing properties were systematically studied. The formed amorphous SnO 2 and partially reduced graphene oxide were analyzed using several complementary material characterization techniques. Further, the results show that the incorporation of rGO significantly improved the humidity sensitivity and the electrical conductivity of the sensor relative to the pristine SnO 2 thin film. Fast response time and excellent selectivity towards humidity were also achieved for the rGO/SnO 2 composite film. The long-term stability of the rGO/SnO 2 sensor was confirmed by comparing its performance to a commercial humidity sensor. The enhanced sensor performance is attributed to the synergistic effects of the incorporation of rGO and the ordered porous structure of the composite film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

ASCENDS: Advanced data SCiENce toolkit for Non-Data Scientists

Recently, advances in machine learning and artificial intelligence have been playing more and more critical roles in a wide range of areas. For the last several years, industries have shown that how learning from data, identifying patterns and making decisions with minimal human intervention can be extremely useful to their business (e.g., image classification, recommending a product to a customer, finding friends in a social network, predicting customers actions, etc.). These success stories have been motivating scientists who study physics, chemistry, materials, medicine, and many other subjects, to explore a new pathway of utilizing machine learning techniques like regression and classification for their scientific activities. However, most existing machine learning tools, systems, and methodologies have been developed for programming experts but not for scientists (or any users) who have no or little knowledge of programming. ASCENDS is a toolkit that is developed to assist scientists (or any persons) who want to use their data for machine learning tasks, more specifically, correlation analysis, regression, and classification. ASCENDS does not require programming skills. Instead, it provides a set of simple but powerful CLI (Command Line Interface) and GUI (Graphic User Interface) tools for non-data scientists to be able to intuitively perform advanced data analysis and machine learning techniques. ASCENDS has been implemented by wrapping around opensource software including Keras, TensorFlow, and scikit-learn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Single Crystals of Vanadium Oxides as a Lens for Understanding Structural and Electronic Phase Transformations, Ion Transport, Chemo-Mechanical Coupling, and Electrothermal Neuronal Emulation

Vanadium oxides cystallize in a diverse array of structures and compositions arising from the redox versatility of vanadium, variable covalency of V−O bonds, and myriad coordination geometries. Their open frameworks present abundant interstitial sites that enable insertion of guest-ions. In such compounds, V3d electron and spin localization and disorder couple strongly to structural preferences. The rich structural diversity manifests as a “rugged” free energy landscape with multiple interconvertible polymorphs. Such a landscape sets up structural, electronic, and magnetic transitions that underpin the promise of these materials as ion-insertion battery electrodes; compact primitives for brain-inspired computing, and heterogeneous catalysts. Here, we examine the structural and compositional diversity, electronic instabilities, defect dynamics, structure transformations, mechanical properties, and surface structure of vanadium oxides using single crystals as a distinctive lens. Single crystals enable the measurement of structure−function correlations without the ensemble and orientational averaging inevitable in polycrystalline materials. Their well-defined surfaces further enable examination of facet-dependent reactivity toward molecular adsorbates, ion fluxes, and lattice (mis)matched solids. We provide a comprehensive account of vanadium-oxide single-crystal studies, from delineation of common structural motifs to single-crystal growth techniques, topochemical modification strategies, mechanisms underpinning electronic instabilities, and implementation as electrothermal neurons and battery electrode materials.

Ponis, John [Texas A&M University, College Station↗
DOE OSTI2021

Thermal conductivity of cement paste: Influence of macro-porosity

Thermal conductivity of cement paste is significantly influenced by the presence of macro-pores within it. These pores (pores with size greater than 6 μm, measured using microCT) which may be filled with air and/or water significantly alters the thermal conductivity of the resulting material. A combination of experiments, molecular dynamic investigations of major constituents of the cement paste, multiscale homogenization techniques, and inclusion of thermal conductivity of the pores containing either air or water has been utilized in this study to reveal the influence of pores in the calculation of thermal conductivity of the composite material.

36 MATERIALS SCIENCE↗