SEARCH · Search NASA

Results for “Barrier properties”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Extracting Material Property Measurements from Scientific Literature with Limited Annotations

Extracting material property data from scientific text is pivotal for advancing data-driven research in chemistry and materials science; however, the extensive annotation effort required to produce training data for named entity recognition (NER) models for this task often makes it a barrier to extracting specialized data sets. Here, in this work, we present a comparative study of the conventional, supervised NER methodology to alternative few-shot learning architectures and large language model (LLM)-based approaches that mitigate the need to label large training data sets. We find that the best-performing LLM (GPT-4o) not only excels in directly extracting relevant material properties based on limited examples but also enhances supervised learning through data augmentation. We supplement our findings with error and data quality assessments to provide a nuanced understanding of factors that impact property measurement extraction.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Physics-informed machine-learning model of temperature evolution under solid phase processes

We model temperature dynamics during Shear Assisted Proccess Extrusion (ShAPE), a solid phase process that plasticizes feedstock with a rotating tool and subsequently extrudes it into a consolidated tube, rod, or wire. Control of temperature is critical during ShAPE processing to avoid liquefaction, ensure smooth extrusion, and develop desired material properties in the extruded products. Accurate modeling of the complicated thermo-mechanical feedbacks between process inputs, material temperature, and heat generation presents a significant barrier to predictive modeling and process design. In particular, connecting micro-structural scale mechanisms of heat generation to macro-scale predictions of temperature can become computationally intractable. In this work we use a neural network (NN) model of heat generation to bridge this gap, by combining it with a simplified model of the temperature dynamics due to conduction and convection to capture the macro scale evolution of temperature. We inform the construction of the NN heat generation model using crystal plasticity simulations at the micro-structural scale to model the effects of process inputs on generation of heat. We achieved close fits of the temperature dynamics model to a diverse experimental data-set. Further, the relationships learned by the NN model between process inputs and heat generation showed qualitative agreement with those predicted by crystal plasticity simulations.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Factors Defining the Intercalation Electrochemistry of CaFe 2 O 4 -Type Manganese Oxides

Oxides with the CaFe 2 O 4 -type structure have been predicted as being suitable hosts for reactions of intercalation of light cations such as Li and Mg because of their favorable cationic diffusion. Although Li has been shown to intercalate into the Mn 2 O 4 variant, the key structure property correlations determining function are not fully ascertained. This basic information is needed before attempting the intercalation of divalent cations, which face comparably higher migration barriers. For this purpose, here the electrode function of CaFe 2 O 4 -type Li 0.8 Mn 2 O 4 was compared for materials made by a direct high-pressure route or through cation exchange from NaMn 2 O 4 . X-ray diffraction and absorption spectroscopy revealed that, despite having largely the same bulk structure, the presence of surface defects blocked Li + transfer in Li 0.8 Mn 2 O 4 made at high pressure. These defects were not present in the cation-exchanged material, which resulted in highly reversible Li intercalation with very fast kinetics in micrometric crystals. Delithiated electrodes from the cation-exchange synthesis were subsequently reduced in an ionic liquid electrolyte containing Mg 2+ . The process induced topotactic changes in the bulk, strongly suggesting the existence of intercalation, but it is accompanied by severe reactivity with the electrolyte that impedes reversibility. This study uncovers that defects affect the fundamentals of cation intercalation in this novel class of materials. The ability of the cation-exchanged material to conduct fast reactions with Li is consistent with calculated activation energy barriers and creates promise for their use as Mg hosts, provided that novel electrolytes enhanced stability at high potential can be realized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Abnormally Low Activation Energy in Cubic Na3SbS4 Superionic Conductor

Inorganic Na-ion superionic conductors play a vital role in all-solid-state Na batteries that operate at room temperature. Sodium thioantimonate (Na3SbS4), a popular sulfide-based solid electrolyte, has attracted serious attention due to its advantages of high ionic conductivity at room temperature and impressive chemical stability under ambient conditions. Much research detailing Na3SbS4 focused on its synthetic approaches and interfacial stability against Na metal, yet, there is limited information elucidating a fundamental understanding of the Na- ion diffusion mechanisms in Na3SbS4 with different crystal structures (e.g., tetragonal and cubic). Herein, we combine real-time electrochemical impedance measurements with theoretical simulations based on density functional theory and in situ quasi-elastic neutron scattering to study the Na-ion conductive properties of Na3SbS4 during its phase transition from a tetragonal to cubic structure. Although there is a slight change in the lattice parameters, the energy barrier for Na-ion diffusion in the tetragonal structure was determined to be much larger (5-10 times) than that in the cubic structure from both theoretical and experimental perspectives. The high degree of symmetry in cubic Na3SbS4 leads to less interatomic correlations between Na and S(Sb) atoms, a shorter jump distance (2.85 angstrom), and a larger diffusion coefficient. This research provides insight into understanding the Na-ion diffusion in solid electrolytes with phase transitions and provides fundamental guidance for designing novel solid-state Na-ion conductors.

Zhang, Qian↗

DOE OSTI2020

Theoretical Design of Lithium Chloride Superionic Conductors for All-Solid-State High-Voltage Lithium-Ion Batteries

The development of solid electrolytes (SEs) is a promising pathway to improve the energy density and safety of conventional Li ion batteries. Several lithium chloride SEs, Li 3 MCl 6 (M = Y, Er, In, and Sc), have gained popularity due to their high ionic conductivity, wide electrochemical window, and good chemical stability. This study systematically investigated 17 Li 3 MCl 6 SEs to identify novel and promising lithium chloride SEs. Calculation results revealed that 12 Li 3 MCl 6 (M = Bi, Dy, Er, Ho, In, Lu, Sc, Sm, Tb, TI, Tm, and Y) were stable phase with a wide electrochemical stability window and excellent chemical stability against cathode materials and moisture. Li-ion transport properties were examined using bond valence site energy (BVSE) and ab initio molecular dynamics (AIMD) calculation. Li 3 MCl 6 showed the lower migration energy barrier in monoclinic structures, while orthorhombic and trigonal structures exhibited higher energy barriers due to the sluggish diffusion along the two-dimensional path based on the BVSE model. AIMD results confirmed the slower ion migration along the 2D path, exhibiting lower ionic diffusivity and higher activation energy in orthorhombic and trigonal structures. For the further increase of ionic conductivity in monoclinic structures, Li-ion vacancy was formed by the substitution of M 3+ with Zr 4+ . Zr-substituted phase (Li 2.5 M 0.5 Zr 0.5 Cl 6 , M = In, Sc) exhibited up to a fourfold increase in ionic conductivity. This finding suggested that the optimization of Li vacancy in the Li 3 MCl 6 SEs could lead to superionic Li 3 MCl 6 SEs.

25 ENERGY STORAGE↗

DOE OSTI2021

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs

We report that community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Negative components in the representation $\frac{𝑑^{2}⁡(𝜎⁢𝐸)}{𝑑⁡𝐸^2}$ of heavy-ion fusion cross sections

Negative components are observed in the representation $\frac{𝑑^{2}⁡(𝜎⁢𝐸)}{𝑑⁡𝐸^2}$ in heavy-ion fusions related to recent studies of noticeable oscillations in the high-energy region of the fusion excitation functions. A modified multiGaussian model has been developed, which includes contributions for both positive and negative components in the $\frac{𝑑^{2}⁡(𝜎⁢𝐸)}{𝑑⁡𝐸^2}$ representation. The model reproduces the heavy-ion fusion excitation functions very well, including oscillations. The property of these negative components in the $\frac{𝑑^{2}⁡(𝜎⁢𝐸)}{𝑑⁡𝐸^2}$ spectrum and the reaction mechanism of fusion at energies above the Coulomb barrier are investigated. Finally, the model also reproduces well light heavy-ion fusion reactions between 12 C and 16 O at high energy; results imply that the compound nucleus channel effect may have an important contribution at the high energy region for all fusion systems.

low & intermediate energy heavy-ion reactions↗

DOE OSTI2021

Corrosion of Steel During Long-Term Exposure to Evolving Cementitious Environments

SRS is proceeding with closure of the H-Area Tank Farm (HTF) and F-Area Tank Farm (FTF). Closure consists of removing the bulk waste, heel removal, and filling the tank with tailored grout formulations. The long-term performance of the concrete and steel materials of construction and the closure grout is an important consideration for Performance Assessment (PA) of closed tanks in FTF and HTF. Over PA timeframes of hundreds, thousands, to tens of thousands of years, the chemical and physical properties of the concrete and steel materials will slowly degrade due to environmental exposure and material aging. In the interim these materials will provide a barrier to the leaching of radionuclides into the soil. Savannah River Remediation (SRR) is updating relevant portions of these analysis inputs to support an imminent revision to the HTF PA and a future update to the FTF PA. This analysis provides an update to the previous PA inputs for steel corrosion. The Central Scenario for the PA analysis includes three postulated modeling cases: 1) Realistic Case, 2) Compliance Case, and 3) Pessimistic Case. This analysis also included a Fast Flow Path Case. This latter case considered the circumstance where the initial condition of the concrete was a completely degraded state and that grout shrinkage exposed the steel to the soil environment immediately. In effect, the steel was unprotected by the concrete and grout. The cases have various degrees of conservatism considered. Chemical, physical and tank configuration parameters were investigated to understand their effects on the predicted time to release of the contaminants. The assessment reviewed the initial tank and steel configuration, service life degradation of the steel, and potential corrosion mechanisms associated with degradation of the concrete materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Hexagonal Boron Nitride Reinforced Multifunctional Well Cement for Extreme Conditions

The overarching objective of this project was to provide a system approach for developing the next generation of well cementing with remarkable multifunctional, high performance characteristics including mechanical, thermal, rheological and durability properties to prevent offshore spill and leakage at extreme high temperature, high pressure (HTHP) and corrosive conditions. Building on our scientifically illustrated principles, the objective of Phase I was to develop and tune our current proof-of-concept hexagonal boron-nitride (hBN)/cement composite to offer the best hybrid nanostructure, and optimum slurry formulation and rheological properties in environments with a variety of extreme conditions including high temperature, high pressure, and high acidity. This phase also focused on testing the actual barrier efficiency and performance of our new cement formulation against gas/liquid leakage at HT, and/or corrosive conditions. The objective of Phase 2 was product validation (meeting API/EPA standards), cost/risk analysis, and scale-up to facilitate integration for primary well cementing with no/minimal modification.

02 PETROLEUM↗

DOE OSTI2021

BETO 2021 Peer Review - ChemCatBio Data Hub 2.6.2.500

The goal of the ChemCatBio DataHub project is to accelerate the catalyst and process development cycle by developing transformational tools for prediction and collaboration in catalyst R&D. The project is currently focused on the development of the Catalyst Property Database (CPD), a free and public resource released in September 2020. The CPD was designed in response to the observation that when data, such as computed reaction energetics, is used in catalyst design, it is almost always generated by the researchers seeking to use it, even if similar data has been published previously. One barrier to data reuse that results in this duplication of effort is the difficult process of finding and applying published data, which can be slow, error-prone, and manual. The CPD seeks to overcome these challenges by creating a centralized, searchable database of quality catalyst property data. At present, the CPD contains computed adsorption energies for intermediates along catalytic pathways. During FY21 and FY22, development of the CPD continues with a focus on external users and meeting their requirements. A batch upload capability, training and curation procedures, user interviews, and a demonstration of the CPD's utility in accelerating catalyst research are planned. Overall, the Data Hub project and CPD aim to reduce the time and cost of catalyst research by harnessing the power of data in catalyst discovery.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Non‐Equilibrium Synthesis Methods to Create Metastable and High‐Entropy Nanomaterials

Stabilizing multiple elements within a single phase enables the creation of advanced materials with exceptional properties arising from their complex composition. However, under equilibrium conditions, the Hume–Rothery rules impose strict limitations on solid-state miscibility, restricting combinations of elements with mismatched crystal structures, atomic radii, valence states, or electronegativities. This severely narrows the accessible compositional space for creating new inorganic materials. In this review, we highlight how non-equilibrium synthesis methods, featuring ultrafast heating and quenching, can overcome these thermodynamic barriers, enabling integration of immiscible elements into metastable and high-entropy nanostructures. The resulting materials benefit from both kinetic trapping and stabilization by high configurational entropy, leading to enhanced phase stability. These materials can exhibit unique structural and functional properties that are needed for advancing catalysis, energy storage, thermoelectrics, and sensing. Furthermore, the ability of non-equilibrium methods to generate unconventional compositions and structures expands the material design space dramatically, offering rich datasets for AI-guided materials discovery. When combined with their inherent high-throughput and scalable characteristics, these approaches enable rapid, iterative optimization and accelerate the development and industrial production of next-generation inorganic materials.

high-entropy materials↗

DOE OSTI2020

Barriers to carrier transport in multiple quantum well nitride-based c -plane green light emitting diodes

The presence of alloy disorder in III-nitride materials has been demonstrated to play a significant role in device performance through effects such as carrier localization and carrier transport. Relative to blue light emitting diodes (LEDs), these effects become more severe at green wavelengths. Because of the potential fluctuations that arise due to alloy disorder, full three-dimensional (3D) simulations are necessary to accurately relate materials properties to device performance. We demonstrate experimentally and through simulation that increased quantum well (QW) number in c-plane green LEDs contributes to excess driving voltage, and therefore reduced electrical efficiency. Experimentally, we grew an LED series with the number of QWs varying from one to seven and observed a systematic increase in voltage with the addition of each QW. Trends in LED electrical properties obtained from 3D simulations, which account for the effects of random alloy fluctuations, are in agreement with experimental data. Agreement is achieved without the need for adjusting polarization parameters from their known values. Finally, from these results, we propose that the polarization induced barriers at the GaN/InGaN (lower barrier/QW) interfaces and the sequential filling of QWs both contribute significantly to the excess forward voltage in multiple QW c-plane green LEDs.

42 ENGINEERING↗

DOE OSTI2024

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, the development of new coating systems is hindered by the large design space and difficulty in predicting the properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate the thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict the phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate the accurate prediction of the anisotropy of the CTE in good agreement with the diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Plant unusual fatty acids: learning from the less common

The plant kingdom contains an abundance of structurally diverse fatty acids referred to as unusual fatty acids. Unusual fatty acids on plant surfaces can form polyesters that contribute to the function of cutin as a barrier for water loss and pathogen protection. Unusual fatty acids are also found as abundant components of seed oils of selected species and often confer desirable properties for industrial and nutritional applications. Here in this paper, we review recent findings on the biosynthesis and metabolism of unusual fatty acids in cutin and seed oils and use of this information for enzyme structure-function studies and seed oil metabolic engineering. We also highlight the recent discovery of unusual fatty acids that are formed from a previously undescribed variation of fatty acid elongation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Proton Relay for the Rate Enhancement of Electrochemical Hydrogen Reactions at Heterogeneous Interfaces

Proton transfer is critically important to many electrocatalytic reactions, and directed proton delivery could open new avenues for the design of electrocatalysts. However, although this approach has been successful in molecular electrocatalysis, proton transfer has not received the same attention in heterogeneous electrocatalyst design. Here, in this work, we report that a metal oxide proton relay can be built within heterogeneous electrocatalyst architectures and improves the kinetics of electrochemical hydrogen evolution and oxidation reactions. The volcano-type relationship between activity enhancement and pK a of amine additives confirms this improvement; we observe maximum rate enhancement when the pK a of a proton relay matches the pH of the electrolyte solution. Density-functional-theory-based reactivity studies reveal a decreased proton transfer energy barrier with a metal oxide proton relay. These findings demonstrate the possibility of controlling the proton delivery and enhancing the reaction kinetics by tuning the chemical properties and structures at heterogeneous interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Growth–defense trade‐offs and yield loss in plants with engineered cell walls

Summary As a major component of plant secondary cell walls, lignin provides structural integrity and rigidity, and contributes to primary defense by providing a physical barrier to pathogen ingress. Genetic modification of lignin biosynthesis has been adopted to reduce the recalcitrance of lignified cell walls to improve biofuel production, tree pulping properties and forage digestibility. However, lignin‐modification is often, but unpredictably, associated with dwarf phenotypes. Hypotheses suggested to explain this include: collapsed vessels leading to defects in water and solute transport; accumulation of molecule(s) that are inhibitory to plant growth or deficiency of metabolites that are critical for plant growth; activation of defense pathways linked to cell wall integrity sensing. However, there is still no commonly accepted underlying mechanism for the growth defects. Here, we discuss recent data on transcriptional reprogramming in plants with modified lignin content and their corresponding suppressor mutants, and evaluate growth‐defense trade‐offs as a factor underlying the growth phenotypes. New approaches will be necessary to estimate how gross changes in transcriptional reprogramming may quantitatively affect growth. Better understanding of the basis for yield drag following cell wall engineering is important for the biotechnological exploitation of plants as factories for fuels and chemicals.

Ha, Chan Man↗

DOE OSTI2023

Evaluation of Desiccation Behavior in Basalt Microfiber–Reinforced Bentonite Clay for Geological Repositories of Nuclear Spent Fuel Using Digital Image Correlation

ABSTRACT Secure storage of nuclear spent fuel (NSF) is of great concern for protecting public health and safety. The preferred long-term solution is underground containment in geological repositories, where one or more engineered barrier materials (EBM) encapsulate the NSF and separate it from the natural rock. Bentonite clay is commonly used as an EBM due to its many advantageous properties including low hydraulic conductivity, which ensures limitation of water infiltration to the system and the subsequent risk of corrosion in NSF canisters. However, bentonite clay subjected to heating from nuclear decay may form desiccation cracking. This study conducted disk-shaped free shrinkage tests and ring-shaped restrained shrinkage tests of bentonite clay samples reinforced with basalt microfibers. Digital image correlation was used as a noncontact full-field displacement measurement to track the time-evolving shrinkage and desiccation cracking phenomena and make quantified comparisons between plain bentonite and bentonite with varying contents of basalt microfibers (i.e., 0.0, 0.5, 1.0, and 1.5 % wt.). Results indicate that plain bentonite and basalt microfiber-reinforced samples showed similar free shrinkage behavior, while desiccation cracking behavior was significantly altered by adding basalt microfibers. Microfiber reinforcement effectively reduced major cracks through a “crack-bridging” effect while causing minor cracks to initiate earlier and at higher moisture contents than plain bentonite. Results infer that reinforcing plain bentonite with inorganic microfibers can potentially control desiccation cracking, leading to safer and improved nuclear waste management.

Materials Science↗

DOE OSTI2021

Bio-project “derisking” through development of systematic methodologies and frameworks for risk assessment

One of the primary hindrances to producing a viable, sustainable domestic biomass industry for renewable biofuels, bio-products and bio-power is the lack of understanding and quantification of the risks associated with both the biomass supply chain and preprocessing and conversion technologies. Currently a consistent method for assessing, comparing, and quantifying risks in biomass supply chains does not exist, creating a major investment barrier to bioenergy projects in the U.S. The lack of a standardized approach has resulted in bioenergy stakeholders independently using inconsistent approaches and evaluation criteria, leading to unreliable and incomparable assessments of risks and financing barriers to bio-project development. Along with the challenges of inconsistent risk assessment for supply chain risk, technology specific risks based on variability in biomass properties are not fully understood and can pose significant unforeseen challenges for bioenergy projects. In many cases these properties have not yet been identified and the impacts on the proposed technology and products unquantified. This is particularly challenging for emerging preprocessing and conversion technologies. Without a firm understanding of the preprocessing/conversion technology-specific critical properties, the risk of a proposed bio-project cannot be fully evaluated. To address inconsistent risk evaluation in the biomass supply chain supporting project financing, a Biomass Supply Chain Risk Standards (BSCRS) framework was developed. The BSCRS framework includes a comprehensive list of known and perceived risks (Risk Indicators) to the supply chain developed through 100’s of interviews with bioenergy industry experts spanning from feedstock growers and suppliers to representatives from the financial sector. These risks have been organized into a manageable hierarchy of Risk Categories and Risk Factors that can be practically assessed. This BSCRS framework also provides mitigation strategies for multiple Risk Indicators from best available industry practices and research findings. Additionally, a risk quantification methodology for each Risk Factor, Risk Category, and the bio-project as a whole was developed to enable capital markets to assess feedstock risk more efficiently and more accurately. Multiple case studies representing existing bio-projects have been used to evaluate and verify the BSCRS framework and scoring methodology. To address technological risk along with the supply chain risk captured in the developed BSCRS framework, this work also focuses on development of a systematic criticality assessment tool using well-accepted, quantitative risk analysis methods to evaluate bioenergy feedstock critical properties impacting system unit operations. The proposed Failure Mode and Effect Analysis (FMEA) approach uses a team of subject area experts (SAEs) for each targeted unit operation within a system. Collectively, the team will develop and use a quantitative scoring system to assess the material attributes, process parameters, and quality attributes for key unit operations that have already been identified. The FMEA process generates Risk Priority Numbers (RPNs) for the various failures and predominant causes for each material/process unit/product combination resulting in a semi-quantitative, standardized methodology for assessing technological risk and biomass properties contributing to that risk.

09 BIOMASS FUELS↗