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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 OSTI2025

Alloying multiple halide perovskites on the same sublattice in search of stability and target band gaps

Single-component halide perovskites (HPs) rarely satisfy all the necessary criteria for optoelectronic applications, such as achieving an optimal band gap while maintaining high chemical and structural stability. Alloying halide perovskites has emerged as a promising strategy, not only to enhance stability but also to fine-tune their electronic and optical properties. In this work, we explore multiple degrees of freedom in alloy design, considering different substitution sublattices sites (A, B, or X in ABX3 perovskites), various chemical species (isovalent and hetero-valent elements), and multi-component compositions on a given sublattice. Using first-principles calculations based on density functional theory (DFT), we investigate how compositional variations influence the electronic (band gap) and structural properties (mixing enthalpy) of HP alloys. Our approach employs the polymorphous cell model, allowing full local relaxation which breaks local symmetry while preserving global cubic symmetry—an essential framework for accurately modeling HPs. Our results reveal that X-site mixing (halogen substitution) primarily affects the valence band maximum, allowing target band gap engineering. Additionally, variations in halogen radii introduce internal strain through octahedral distortions, influencing the mixing enthalpy. A-site substitution, while not directly contributing to the band edge states, modifies structural stability via volume effects, indirectly impacting the band gap. B-site alloying plays a dominant role in band gap modulation, leading to either positive or negative band gap bowing. Specifically, isovalent B-site mixing (Sn–Pb) induces strong positive bowing, where the alloy band gap is smaller than the average gap of parent compounds, whereas hetero-valent mixing (Cd–Pb) results in pronounced negative bowing. As an aside, we investigate the competition between the excess energy of disordered alloys vs. that of long-range ordered double perovskites of the same compositions, seeking examples of ordered phases emerging from disordered alloys. Furthermore, our findings provide fundamental insights into the electronic and structural behavior of HP alloys, offering valuable design principles for the development of stable and efficient materials for next-generation photovoltaic and optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2020

Tuning martensitic transformations via coherent second phases in nanolaminates using free energy landscape engineering

In this work we explore the possibilities and limitations of using a coherent second phase to engineer the thermo-mechanical properties of a martensitic alloy by modifying the underlying free energy landscape that controls the transformation. We use molecular dynamics simulations of a model atomistic system where the properties of a coherent, nanoscale second phase can be varied systematically. With a base martensitic material that undergoes a temperature-induced transformation from a cubic austenite to a monoclinic martensite, simulations show significant ability to engineer the transformation temperatures, from a ~50% reduction to a ~200% increase, with 50 at.% of the cubic second phase. We establish correlations between the properties of the second phase, the transformation characteristics, and the microstructure via the free energy landscape of the twophase systems. Coherency stresses have a strong influence on the martensitic variants observed and can even cause the non-martensitic second phase to undergo a transformation. Reducing the stiffness of the second phase increases the transformation strain and modifies the martensitic microstructure, increasing the volume fraction of the transformed material. This increase in transformation strain is accompanied by a significant increase in Af and thermal hysteresis, while Ms remains unaltered. Our findings on the tunability of martensitic transformations can be used for informed searches of second phases to achieve desired material properties, such as achieving room temperature, lightweight shape memory alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Robustness of quasi-symmetry along parametric boundary variation

Quasi-symmetry is a guiding principle to modern stellarator optimization for improved plasma confinement. However, the robustness of optimized configurations, which can be crucial for maintaining performance under diverse engineering constraints and practical limitations, has received relatively little attention. Here, in this work, we present various case studies on this robustness, by investigating variations in 1/ v neoclassical transport when plasma configurations are smoothly altered across distinct optimized targets. These targets, optimized from different families—quasi-axisymmetric, quasi-helical, and quasi-isodynamic—are approximately matched in major radius as part of a flexible stellarator design. Our study shows that an optimized target does not always represent a local minimum in transport and that the robustness of a local minimum when present can vary significantly. Furthermore, there are configurations which belong to no established families but have transport levels as low as those of optimized targets. These results highlight the importance of conducting extended searches with key parametric variations around optimized configurations, to ensure its robustness as well as flexibility if desired.

neoclassical transport↗
DOE OSTI2022

Vickers hardness prediction from machine learning methods

Abstract The search for new superhard materials is of great interest for extreme industrial applications. However, the theoretical prediction of hardness is still a challenge for the scientific community, given the difficulty of modeling plastic behavior of solids. Different hardness models have been proposed over the years. Still, they are either too complicated to use, inaccurate when extrapolating to a wide variety of solids or require coding knowledge. In this investigation, we built a successful machine learning model that implements Gradient Boosting Regressor (GBR) to predict hardness and uses the mechanical properties of a solid (bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio) as input variables. The model was trained with an experimental Vickers hardness database of 143 materials, assuring various kinds of compounds. The input properties were calculated from the theoretical elastic tensor. The Materials Project’s database was explored to search for new superhard materials, and our results are in good agreement with the experimental data available. Other alternative models to compute hardness from mechanical properties are also discussed in this work. Our results are available in a free-access easy to use online application to be further used in future studies of new materials at www.hardnesscalculator.com .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Genetic Algorithm-Based Commutation Angle Control for Torque Ripple Mitigation in Switched Reluctance Motor Drives

This work addresses the application of the Genetic Algorithm (GA) technique to optimize the commutation angles of a 2 kW 8/6 switched reluctance machine (SRM). The primary goal is to reduce the well-known drawback of SRMs: the torque ripple. Firstly, the machine was modeled in Matlab /Simulink ® using lookup tables obtained via finite element method (FEM) simulations. Subsequently, the model was used to perform the GA routine aiming to find the optimal phase commutation angles that minimize the torque ripple factor. Notably, the torque performance of the SRM was significantly affected by the commutation angles during the search for the optimal solution. Afterwards, the GA results for four different operation points were verified experimentally through a developed drive platform with digital signal processor-based (DSP) control and an asymmetric bridge converter. As showed by the experiments, the proposed approach was suitable to reduce the torque ripple by more than 50% for one of the evaluated operating points. Furthermore, it was confirmed that the torque ripple mitigation led to acoustic noise improvement.

42 ENGINEERING↗
DOE OSTI2020

Phase-Only Beam Broadening of Contiguous Uniform Subarrayed Arrays

In modern antenna systems, beam broadening of subarrayed arrays provides continuous coverage of a wide angular extent in a cost-effective manner. While many methods have been published that address beam broadening of traditional (non-subarrayed) arrays, there is a knowledge gap in the published literature with respect to efficient beam broadening of contiguous uniform subarrayed arrays. This article presents efficient methods for beam broadening of contiguous uniform subarrayed arrays where the excitation of each element is not individually controlled, but the elements of the array are grouped together as subarrays to have the same element excitations. Particularly, this article focuses on phase-only optimization to preserve maximum power output. Additionally, three modilied iterative Fourier transform (IFT) methods and one genetic algorithm (GA) are presented to efliciently search the vast solution space of possible phase settings for a solution that satislies the desired broadened pattern. These methods are evaluated on idealized 1 x 40 and 1 x 80 linear arrays with live element subarrays and 40 x 40 and 80 x 80 element rectangular arrays with 5 x 5 element subarrays. The proposed modilied IFT methods are found to be faster than the GA approach, while the GA approach only offers a few percentage points of better effectiveness.

42 ENGINEERING↗
DOE OSTI2020

Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

Existing generator parameterization methods, typically developed for large turbine generator units, are difficult to apply to small kW-level diesel generators in microgrid applications. Here, this article presents a model parameterization method that estimates a complete set of kW-level diesel generator parameters simultaneously using only load-step-change tests with limited measurement points. This method provides a more cost-efficient and robust approach to achieve high-fidelity modeling of diesel generators for microgrid dynamic simulation. A two-stage hybrid box-constrained Levenberg-Marquardt (H-BCLM) algorithm is developed to search the optimal parameter set given the parameter bounds. A heuristic algorithm, namely Generalized Opposition-based Learning Genetic Algorithm (GOL-GA), is applied to identify proper initial estimates at the first stage, followed by a modified Levenberg-Marquardt algorithm designed to fine tune the solution based on the first-stage result. The proposed method is validated against dynamic simulation of a diesel generator model and field measurements from a 16kW diesel generator unit.

42 ENGINEERING↗
DOE OSTI2026

Requirements Description of DASSH-F

This report reviews the modeling and simulation capabilities of Argonne National Laboratory’s DASSH code that is used in present reactor analysis activities. These capabilities will be used to establish the set of verification tasks necessary to verify DASSH for use on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The DASSH program is a thermal analysis code designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. DASSH is a follow-on development to the SE2-ANL software and SUPERENERGY-2 software that it is based upon. DASSH was designed to account for both neutron and gamma heating and is inherently connected to the GAMSOR part of the ARC suite of fast reactor analysis software. SE2-ANL is a developed piece of software from the 1980s while DASSH is a modern implementation with notable improvements in geometry handling. The most important upgrade of DASSH relative to SE2-ANL is that it can analyze multiple time points in a single run where SE2-ANL can only treat a single time point. This allows the user to understand the impact of and search the flow distribution for the entire operational period of a reactor design considering pressure drop, peak coolant and fuel temperatures, and thermal striping. DASSH has three input paths that have to be verified. The first input path builds the geometry and power distribution based upon the DIF3D model but ignores the gamma heating aspects of the problem. The second input path also builds the geometry from the DIF3D model but it takes the neutron and gamma heating distributions from GAMSOR. The third input path is to take the geometry and power distribution directly from user input (i.e. not coupled to DIF3D or GAMSOR). DASSH also has many built in correlations for material properties along with a user defined specification of the fuel, structure, and coolant properties. There are correlations for flow split, mixing, pressure drop, and heat transfer coefficients (subchannel rather than a direct methodology). In total, verification of DASSH will require an extensive testing to cover all possible user features of the software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Hard and semi-hard Fe-based magnetic materials

Iron (Fe) is the most important ferromagnetic element, not only for its high magnetic moment and high Curie temperature but for its abundance as well. Fe-based magnetic materials are therefore widely applied in technologies and industries, with most of the applications for soft magnetic materials, because of the low magnetocrystalline anisotropy (MCA) of Fe. However, it is possible to realize magnetic hardening in Fe-based materials as we have learned from the early carbon steel permanent magnets although their coercivity was modest. Recent efforts to search for rare-earth-free hard magnetic materials have shown more promising evidences for achieving high MCA in Fe-based materials. In this paper, we review the history and the recent developments of Fe-based hard and semi-hard magnetic materials with a focus on mechanisms of high MCA in Fe-based phases and the related crystal and electronic structures. Here, we have tabulated and discussed the structures and the magnetic properties of the Fe-based binary or ternary systems containing p-block and d-block elements, with many of them showing considerable MCA. Furthermore, it is important to know and to understand that the MCA in Fe-based magnetic materials can be tailored/enhanced through chemical and/or structural modifications that will lead to “artificially engineered” hard and semi-hard magnetic materials for advanced permanent magnets in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reflector coatings development (FY2020 End of Year Report)

X-ray detection instrumentation has been developed and manufactured at LANL for various DOE programs. One way to improve light collection efficiency, for a scintillator type detector, is to apply suitable reflectors. The coating capability and fabrication procedure for Al reflective coatings was established in FY19 at MST-7. Al reflective coatings with good stability, good adhesion to LSO, and reflectivity (R) up to 78% were fabricated. Materials with higher diffuse reflectivity (such as Teflon tape R=99%) are desirable. A literature search revealed a number of materials in the form of paint or free standing tape with diffuse R = 98- 99%. However, for the intended application such reflectors have to be applied in the form of a coating with strong adhesion to LSO crystals. The purpose of the FY20 project was to develop thin film coating techniques for PTFE (known as Teflon) reflectors and fabricate reflective coatings on provided LSO crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Atacama Cosmology Telescope: Systematic Transient Search of 3 Day Maps

We conduct a systematic search for transients in 3 yr of data (2017–2019) from the Atacama Cosmology Telescope (ACT). ACT covers 40% of the sky at three bands spanning from 77–277 GHz. Analysis of 3 day mean-subtracted sky maps, which were match filtered for point sources, yielded 29 transient detections. Eight of these transients are due to known asteroids, and three others were previously published. Four of these events occur in areas with poor noise models and thus we cannot be confident they are real transients. We are left with 14 new transient events occurring at 11 unique locations. All of these events are associated with either rotationally variable stars or cool stars. Ten events have flat or falling spectra indicating radiation from synchrotron emission. One event has a rising spectrum indicating a different engine for the flare.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Symmetrically tuned large-volume conic shell-cavities for axion searches

In an earlier paper [1], a new class of thin-shell cavities were proposed to evade the steep frequency scaling of conventional axion haloscopes. In this follow-up work, we see that a generalized conic geometry enables robust frequency-tuning for these large-volume cm-wave cavities. The frequency-defining dimension of a conic shell-cavity changes symmetrically and uniformly during tuning, maintaining a high axion coupling efficiency (the "form factor") to an external solenoid field. It is further shown that such tunable geometry is not restricted to circular cones. A general prescription for arbitrary volume-filling conic shell-cavities is developed and direct solutions are obtained for the created numerical models. Additionally, the largest of the realized designs is a meandering "brain" cavity that is tunable over a frequency range of 20%. The scan rate of this cavity is three orders of magnitude larger than that of a scaled cylindrical cavity used in the current generation experiments. The prospects for such a large improvement in the scan rate should motivate R& D efforts in fabrication and other implementation techniques. If these engineering challenges can be met, cavity-based axion haloscopes can stay competitive at frequencies higher than a few GHz. We propose an experimental configuration at 20 GHz (~80 μeV) using an array of brain cavities and compare it with other proposals for similar frequencies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Efficiency droop contributors in InGaN green light emitting diodes

Here, efficiency droop contributors (i.e., inherent Auger–Meitner recombination, polarization-induced effects, thermal effects, and light extraction) in InGaN green light emitting diodes (LEDs) are decoupled and quantified. First, a modified ABC model is developed, and external quantum efficiency measurements are taken under constant and pulsed currents (⁠ EQE Constant and EQE Pulsed ⁠, respectively). The LED internal quantum efficiency with and without thermal effects (⁠ IQE$^{ABC}_{Constant}$ and IQE$^{ABC}_{Pulsed}$⁠, respectively) is extracted using the modified model. Then, using Raman spectroscopy, the LED junction temperature is extracted. Finally, using the optical-electrical model (OEM), the polarization- and temperature-independent LED internal quantum efficiency (⁠ IQE OEM ) is calculated from the modified ABC model and the extracted junction temperature. By comparing external (⁠ EQE Constant ⁠) and the three internal quantum efficiencies (⁠ IQE$^{ABC}_{Constant}$, IQE$^{ABC}_{Pulsed}$⁠, and IQE OEM ), the impacts of inherent Auger–Meitner recombination, polarization-induced effects, thermal effects, and light extraction on the efficiency droop are decoupled and quantified. It is found that inherent Auger–Meitner recombination-induced droop is approximately 49% of the total efficiency droop in commercial green LEDs, while polarization-induced effects contribute about 35%, and thermal droop accounts for nearly 16%. Lastly, these findings suggest, to quash the green gap, it is critical to search for materials and device designs with low inherent Auger–Meitner coefficients and polarization fields, respectively.

42 ENGINEERING↗
DOE OSTI2024

Refinement and Modeling of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing collaboration searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, an experiment of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD reflector setup allows for the focusing of converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within $\SI{50}{\micro\metre}$ in the $z$ dimension.

Rao, Shardul↗
DOE OSTI2023

Search for High-Pressure Silicon Phases: Reaching the Extreme Conditions with High-Intensity Laser Irradiation

Controlling electronic and optical properties of semiconducting materials could substantially expand their functionality and enable new pathways for the formation of ‘smart’ materials for emerging innovative applications. An emerging new path for the synthesis of exotic silicon (Si) polymorphs is irradiation of bulk diamond-cubic Si by ultrashort laser pulses at relativistic intensity above 1019 W/cm2. Exotic polymorphs are formed due to interaction with MeV-energy electrons generated in laser-produced high-temperature plasma state. The unusual Si structures are found in the form of 5–10 nm nanoparticles confined deep in the bulk of 500-μm-thick Si samples. Raman spectroscopy, electron microscopy and X-ray diffraction studies provide an unequivocal evidence of exotic Si phase formation. A key advantage of such relativistic irradiation lies thereby in the fact that large quantities of such exotic Si is synthesised embedded within the bulk diamond-cubic Si and that further the formed Si polymorphs are stable at ambient temperature and pressure. They are thus available for further studies for electronic applications in selective band gap engineering.

Rapp, Ludovic↗
DOE OSTI2025

Liquid Metals for Advanced Batteries: Recent Progress and Future Perspective

ABSTRACT The shift toward sustainable energy has increased the demand for efficient energy storage systems to complement renewable sources like solar and wind. While lithium‐ion batteries dominate the market, challenges such as safety concerns and limited energy density drive the search for new solutions. Liquid metals (LMs) have emerged as promising materials for advanced batteries due to their unique properties, including low melting points, high electrical conductivity, tunable surface tension, and strong alloying tendency. Enabled by the unique properties of LMs, four key scientific functions of LMs in batteries are highlighted: active materials, self‐healing, interface stabilization, and conductivity enhancement. These applications can improve battery performance, safety, and lifespan. This review also discusses current challenges and future opportunities for using LMs in next‐generation energy storage systems. image

Zheng, Tianrui [Materials Science and Engineering ↗
DOE OSTI2025

Workforce planning: a review of methodologies

Workforce planning deals with determining the number of employees and associated skills necessary to meet the future operational needs of an organization. A workforce system consists of six elements: recruitment, attrition, promotion, training, retention, and scheduling. Historically, several workforce modeling and analysis methodologies have been developed to capture these elements. This paper reviews the results of workforce and manpower models published within peer-reviewed literature between 1959 and 2021 to provide an in-depth analysis of current models. The focus of this review is on analytical, simulation, and empirical models found in literature that were collected based on a citation requirement and keyword search criteria. Results demonstrate the trends in workforce modeling research and discuss the common uses of each model type and the advantages/disadvantages related to each model. Based on the common attributes of workforce systems, the discussion focuses on the most frequently used model type for each element and the best use for each model. Lastly, recommendations are made for the development of workforce models that allow the most comprehensive view of the workforce systems of the future.

42 ENGINEERING↗
DOE OSTI2020

A non-cooperative meta-modeling game for automated third-party calibrating, validating and falsifying constitutive laws with parallelized adversarial attacks

The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and falsification. While there are numerous efforts to develop paradigms and standard procedures to validate models, difficulties may arise due to the sequential, manual, and often biased nature of the commonly adopted calibration and validation processes, thus slowing down data collections, hampering the progress towards discovering new physics, increasing expenses and possibly leading to misinterpretations of the credibility and application ranges of proposed models. This work attempts to introduce concepts from game theory and machine learning techniques to overcome many of these existing difficulties. Here, we introduce an automated meta-modeling game where two competing AI agents systematically generate experimental data to calibrate a given constitutive model and to explore its weakness such that the experiment design and model robustness can be improved through competitions. The two agents automatically search for the Nash equilibrium of the meta-modeling game in an adversarial reinforcement learning framework without human intervention. In particular, a protagonist agent seeks to find the more effective ways to generate data for model calibrations, while an adversary agent tries to find the most devastating test scenarios that expose the weaknesses of the constitutive model calibrated by the protagonist. By capturing all possible design options of the laboratory experiments into a single decision tree, we recast the design of experiments as a game of combinatorial moves that can be resolved through deep reinforcement learning by the two competing players. Our adversarial framework emulates idealized scientific collaborations and competitions among researchers to achieve a better understanding of the application range of the learned material laws and prevent misinterpretations caused by conventional AI-based third-party validation. Numerical examples are given to demonstrate the wide applicability of the proposed meta-modeling game with adversarial attacks on both human-crafted constitutive models and machine learning models.

97 MATHEMATICS AND COMPUTING↗