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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Weak-Bonding Elements Lead to High Thermoelectric Performance in BaSnS 3 and SrSnS 3 : A First-Principles Study

SnS2, an earth-abundant and ecofriendly material, is limited as a thermoelectric material because of the high lattice thermal conductivity κ L and low carrier mobility μ. By introducing weak-bonding elements Ba or Sr into the SnS 2 framework, we discovered two SnS 2 -based materials BaSnS3 and SrSnS3 with the calculated low κL values of 0.15 and 0.17 W m -1 K -1 , respectively, along the a-axis. The low group velocity and high lattice anharmonicity originating from the weakened and distorted Sn–S bonding network are found in both systems. Moreover, the vibrations of Ba and Sr induce low-lying optical phonons, which strongly couple with the acoustic phonons and strengthen the phonon scattering rates. Compared to SnS 2 , both compounds present lower single-band effective masses, smaller deformation potential constants, and better band convergence, which enhance μ with an insignificantly reduced effective mass. By solving the linearized Boltzmann transport equation with a nonempirical carrier lifetime, we predict excellent ZT values of 2.89 and 2.77 along the a-axis at 900 K in BaSnS 3 and SrSnS 3 , respectively. Further phase diagram calculations of Ba 1–x Sr x SnS 3 solid solutions propose a new compound, Ba 0.5 Sr 0.5 SnS 3 , with an even higher ZT of 3.0. Our work analyzes explicitly how weak-bonding elements enhance μ and suppress κL simultaneously in SnS 2 -analogous systems with a series of compounds nominated as potential high-performance thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗
DOE OSTI2025

Nonsingular black holes as dark matter

It is commonly assumed that low-mass primordial black holes cannot constitute a significant fraction of the dark matter in our universe due to their predicted short lifetimes from the conventional Hawking radiation and evaporation process. Assuming physical black holes are nonsingular—likely due to quantum gravity or other high-energy physics—we demonstrate that a large class of nonsingular black holes have finite evaporation temperatures. This can lead to slowly evaporating low-mass black holes or to remnant mass states that circumvent traditional evaporation constraints. As a proof of concept, we explore the limiting curvature hypothesis and the evaporation process of a nonsingular black hole solution in two-dimensional dilaton gravity. We identify generic features of the radiation profile and compare them with known regular black holes, such as the Bardeen solution in four dimensions. Remnant masses are proportional to the fundamental length scale, and we argue that slowly evaporating low-mass nonsingular black holes, or remnants, are viable dark matter candidates. Published by the American Physical Society 2025

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Detailed Design and Cost Estimation of a 300 MWe Oxy-Fuel sCO2 Turbine

The detailed design of a 300 MWe, utility scale oxy-fuel turbine has been completed for purposed operation in the sCO2 direct fired Allam-Fetvedt cycle, targeting near-zero emissions and a 50% LHV system efficiency. The turbine and its supporting plant aim to offer a lower levelized cost of energy than a natural gas combined cycle plant employing carbon capture. The oxy-fuel turbine conditions include an inlet temperature of 1150°C and inlet pressure of 305 bar, representing temperatures near that of a gas turbine simultaneously with pressures near an ultra-supercritical steam turbine. The combustor housing and turbine designs were completed according to the ASME BPVC; the turbine case specifically incorporates a multi-body design with inner high-pressure barrel case and low-pressure (30 bar) horizontally split outer case of low-chromium steel material. Lateral rotordynamic evaluation demonstrated acceptable vibration response for a range of imbalance conditions per API standards. The cooling flow required in the six-stage turbine flowpath for 30,000 hr. blade and stator lifetime is predicted through thermal and structural modeling of the first stage. The provided cost estimate of the turbine is formed through a combination of scaled up-costs from procured 10 MWe scale sCO2 turbomachinery hardware, and vendor provided budgetary quotes of larger components including the turbine case requiring casting, welding, and final machining processes. The performance and cost estimation of the oxy-fuel turbine predicted for the completed detailed design provides important information towards future development needs for market penetration of utility scale direct fired sCO2 power cycles.

Marshall, Michael [Southwest Research Institute, S↗
DOE OSTI2023

Post Irradiation Examination of Pressurized Water Reactor Stainless Steel Internal Components

Internal structural components of pressurized water reactors (PWR), such as baffle former bolts, are subjected to significant neutron irradiation and mechanical stresses at elevated temperatures during plant operation. Over the long operation of the power plant, these conditions lead to potential degradation and reduced load-carrying capacity of these bolts. To understand property degradation more fully, to confirm the results of experimental irradiation programs, and to predict operational lifetime performance of structural materials in internal components, post irradiation examination of harvested materials from operating nuclear reactors is required. In this work, two high fluence 316 stainless steel baffle former bolts were retrieved from a commercial Westinghouse two-loop downflow type PWR and then sectioned for analysis via mechanical testing and microstructural characterization. The irradiation damage fluctuated along the bolt length with damage levels from 15 to 41 displacements per atom with the bolt head receiving approximately twice the neutron damage levels as that of the bolt thread section. Mechanical testing evaluations showed extensive irradiation hardening and a sharp decrease in fracture toughness in all parts of the bolt, though with limited variation along the bolt length. Microstructural characterization using analytical scanning transmission electron microscopy and atom probe tomography showed significant radiation induced precipitation, segregation, and dislocation loop and cavity formation. However, unlike the mechanical behavior, there was considerable variation along the bolt length but opposite of what may be expected, with more precipitation and cavity formation in the bolt thread where the neutron radiation dose is less than in the bolt head where the neutron radiation dose is higher. The cause of this variation is likely due to gradients in temperature, neutron energy spectra, and gamma irradiation.

Lach, Tim↗
DOE OSTI2022

Accelerated aging of all-inorganic, interface-stabilized perovskite solar cells

To understand degradation routes and improve the stability of perovskite solar cells (PSCs), accelerated aging tests are needed. Here, we use elevated temperatures (up to 110°C) to quantify the accelerated degradation of encapsulated CsPbI 3 PSCs under constant illumination. Incorporating a two-dimensional (2D) Cs 2 PbI 2 Cl 2 capping layer between the perovskite active layer and hole-transport layer stabilizes the interface while increasing power conversion efficiency of the all-inorganic PSCs from 14.9 to 17.4%. Devices with this 2D capping layer did not degrade at 35°C and required >2100 hours at 110°C under constant illumination to degrade by 20% of their initial efficiency. Degradation acceleration factors based on the observed Arrhenius temperature dependence predict intrinsic lifetimes of 51,000 ± 7000 hours (>5 years) operating continuously at 35°C.

Science & Technology - Other Topics↗
DOE OSTI2023

Final Report

This project focused on investigating the prospects of two-dimensional (2D) materials, transition metal dichalcogenides (TMDs) and graphene, for developing nanostructures that are potentially useful for quantum science. These materials class exhibit a range of fascinating electronic and optical properties and, due to their sub-nanometer thickness, are particularly well suited for confining electronic quantum states in atomic-size structures. The project involved developing first-principles calculations that can predict coherent lifetimes of defects; theoretical schemes for identifying new platforms suitable for studying the dynamics of driven quantum systems; and optical and electronic spectroscopy characterization of novel defects and heterostructures with the aim of creating the next generation of materials for quantum science. This report provides a brief background into the project, highlights some of the major achievements accomplished within the projects and lists the supported publications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Accelerated Beta Radiation Aging of Interlayer Titanium Nitride in Gallium Nitride Contacts

Research conducted under the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory, a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy. An NNSS author co-authored this paper, and portions of this work were supported by the Mission Support and Test Services, LLC, under Contract No. DE-NA0003624 with the U.S. Department of Energy, National Nuclear Security Administration, NA-10 USDOE NA Office of Defense Programs (NA-10). PNNL-SA-163618 Currently, there is no good way to determine the influence of radiation on the aging of betavoltaic electrical contacts. This work tested a method to accelerate the aging of the contacts inside a betavoltaic by enhancing energy deposition within the interfacial region of interest. An electrical contact of gold-titanium on gallium nitride was aged by exposure to tritium betas and electrons in a beamline. The interface stoichiometry was compared to the electrical performance of the contact. The method to age the betavoltaic component could help predict the lifetime performance of the internal electrical contacts and provide assurance of deployment reliability.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A reactive tracer method for predicting EGS reservoir geometry and thermal lifetime: development and field validation

The project summarized here (DOE Award No. DE-EE0006764) was intended to develop a methodology for predicting advective heat transfer in fracture-dominated crystalline rock. Our goal was to determine if a combination of inert and reactive tracers could adequately constrain the effective heat transfer surface area between an injection-production well pair. Our approach consisted of: 1. developing a novel computational framework; 2. Performing heat and tracer experiments at meso-scale; and 3. Comparing predictions of advective heat transfer to the “true” thermal breakthrough measured at the Altona site. Below is a summary of project activities/findings, a summary of project tasks, and a conclusion

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Auto-BLAST (AutoBLAST) [SWR-20-93]

Battery life modeling often involves a lot of manual parameter fitting and is not easy for users to adopt the model and use it. To reduce the difficulties for users to adopt battery lifetime models, an automatic battery lifetime modeling analysis and simulation tool suite, Auto-BLAST, has been developed. Auto-BLAST includes a lithium-loss-base life model, a battery electric model, and an algorithm which automatically fits all key parameters in the electric and life models using user provided data. The models and algorithm are packaged into two user-friendly GUIs, Auto-LifeMod, for easy battery life prognostic model fitting and Auto-LifeSim, for easy battery lifetime simulation. The lithium-loss-based life model adopts a similar model framework that models degradations using aging rate models, using battery cycling data to predict battery degradation and expected lifetime. The electric model is an equivalent circuit model which simulates battery voltage responses based on current/power demand profiles. The auto-fitting algorithm uses the user-input data to generate custom battery life model(s). Two GUIs, wrapping around the life model and the auto-fitting algorithm, provide friendly interfaces for users to generate a life model and use it for case study. One GUI requires summary data from accelerated battery life degradation tests as an input and produces battery life models predicting (a) capacity degradation, and (b) resistance growth of the battery. The GUI displays the electrical model response and the input experimental data against the life model predictions with fitted model parameters and fitting error. The GUI also generates an output file to save the fitted model parameters. The second GUI uses the life model from the first GUI and a user-defined battery cycling profile to predict battery lifetime degradation and expected lifetime. Predicted capacity and resistance vs. time are plotted in the GUI and saved to output file. There is a user guide for both GUIs

Mishra, Partha↗
DOE OSTI2021

Twist Angle-Dependent Interlayer Exciton Lifetimes in van der Waals Heterostructures

In van der Waals (vdW) heterostructures formed by stacking two monolayers of transition metal dichalcogenides, multiple exciton resonances with highly tunable properties are formed and subject to both vertical and lateral confinement. We investigate how a unique control knob, the twist angle between the two monolayers, can be used to control the exciton dynamics. We observe that the interlayer exciton lifetimes in MoSe 2 /WSe 2 twisted bilayers (TBLs) change by one order of magnitude when the twist angle is varied from 1° to 3.5°. Additionally, using a low-energy continuum model, we theoretically separate two leading mechanisms that influence interlayer exciton radiative lifetimes. The shift to indirect transitions in the momentum space with an increasing twist angle and the energy modulation from the moiré potential both have a significant impact on interlayer exciton lifetimes. We further predict distinct temperature dependence of interlayer exciton lifetimes in TBLs with different twist angles, which is partially validated by experiments. While many recent studies have highlighted how the twist angle in a vdW TBL can be used to engineer the ground states and quantum phases due to many-body interaction, our studies explore its role in controlling the dynamics of optically excited states, thus, expanding the conceptual applications of “twistronics”.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Early calendar life and health prediction of silicon batteries via machine learning with uncertainty quantification

Lithium-ion batteries with silicon anodes promise high energy density but are limited by calendar lifetime. Reducing the long iteration time to obtain experimental results requires predicting calendar lifetime early in a cell's life. In this study, we demonstrate that lightweight machine learning models with feature engineering can provide calendar lifetime estimates from early electrochemical signals. After 1 month of electrochemical aging, the best models achieve 10% error in calendar-life prediction and can separate "bad" from "good" lifetime cells with a mean F1 score of 0.857. As battery systems exhibit inherent variability, four methods for uncertainty quantification are compared, and confidence intervals are demonstrated with an uncertainty of +-3.6 months in lifetime prediction. A feature importance analysis indicates that early patterns in voltage decay are the strongest indicators of calendar lifetime. Finally, this modeling approach has high error when generalizing to new electrode chemistries or testing conditions but with appropriately low confidence.

25 ENERGY STORAGE↗
DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Transverse Beam Tails and Beam Lifetime in the EIC Electron Storage Ring

For most storage ring design purposes it is sufficient to assume a Gaussian distribution of the electrons in a bunch. However, a more detailed knowledge of the population in the transverse tails beyond a few sigma is necessary to predict the beam lifetime and the synchrotron radiation load in the interaction region due to beam-gas scattering and the beam-beam interaction. This report presents simulations to determine the required vacuum level as well as to serve as input data for detailed synchrotron radiation simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py

Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.

Smith, Kandler↗
DOE OSTI2021

Reduction of bright exciton lifetimes by radiation-induced disorder

Quantum-radiative decay is a fundamental process in many optoelectronic systems such as laser diodes and solar cells. The bright exciton lifetime is a critical factor in determining the performance of these systems. Motivated by the ever-increasing need for laser systems in space and nuclear applications, we develop a many-particle approach to predict the radiative lifetime under harsh radiation environments. Here, using GaAs as a model system, we find that radiation-induced band tailing reduces the bright exciton lifetime. This result shows that the efficiency of radiative recombination, in addition to nonradiative recombination, can be affected by ionization radiation. Our approach enables a detailed understanding of the interplay between correlation, localization, and radiation that affect the performance of gain media.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multivariable degradation modeling and life prediction using multivariate fractional Brownian motion

In system prognostics and health management, multivariable degradation models have been widely developed to predict the life of complex systems using degradation data of multiple Performance Characteristics (PCs). Recent studies have detected a Long-Term Memory (LTM) effect among the degradation process of various PCs, implying a strong coupling phenomenon between the future degradation behavior and historical degradation trajectory. Although the LTM has been widely integrated into single-PC-based degradation modeling, it has not been considered in multi-PC-based scenarios. To capture LTM among multiple PCs, this article proposes a novel LTM-integrated Multivariate Degradation Model (MDM) for system life prediction based on multivariate fractional Brownian motion, which simultaneously incorporates the cross-correlation among different PCs. To estimate parameters of the LTM-integrated MDM, a maximum likelihood method is developed. Here, two likelihood-ratio hypothesis tests are developed to test the existence of the overall and individual LTM effect among multiple PCs. Both simulation studies and physical experiments on the performance degradation of solar energy conversion and storage devices are conducted to validate the proposed model. Results reveal that the proposed LTM-integrated MDM significantly outperforms existing MDMs in life prediction, while the lifetime uncertainty is heavily underestimated by those traditional approaches that neglect the LTM.

42 ENGINEERING↗