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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Kilonovae Across the Nuclear Physics Landscape: The Impact of Nuclear Physics Uncertainties on r-process-powered Emission

Merging neutron stars produce “kilonovae”—electromagnetic transients powered by the decay of unstable nuclei synthesized via rapid neutron capture (the r-process) in material that is gravitationally unbound during inspiral and coalescence. Kilonova emission, if accurately interpreted, can be used to characterize the masses and compositions of merger-driven outflows, helping to resolve a long-standing debate about the origins of r-process material in the Universe. We explore how the uncertain properties of nuclei involved in the r-process complicate the inference of outflow properties from kilonova observations. Using r-process simulations, we show how nuclear physics uncertainties impact predictions of radioactive heating and element synthesis. For a set of models that span a large range in both predicted heating and final abundances, we carry out detailed numerical calculations of decay product thermalization and radiation transport in a kilonova ejecta with a fixed mass and density profile. The light curves associated with our models exhibit great diversity in their luminosities, with peak brightness varying by more than an order of magnitude. We also find variability in the shape of the kilonova light curves and their color, which in some cases runs counter to the expectation that increasing levels of lanthanide and/or actinide enrichment will be correlated with longer, dimmer, redder emission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1-x-yScxGdyN Heterostructural Alloys

Ternary nitride alloys based on wurtzite AlN are a promising platform to realize functional materials, particularly ferroelectrics and optical emitters, that can smoothly integrate with conventional microelectronics. Here, a strategic design is presented to enable multifunctional materials by substituting multiple elements into AlN to create quaternary nitride alloys. By combining computational predictions and combinatorial thin film synthesis, the phase diagram of these quaternary Al-Sc-Gd-N alloys (or pseudo-ternary heterostructural AlN-ScN-GdN alloys) is successfully predicted as a function of effective temperature, and we experimentally grow Al1-x-xScxGdyN thin films for the first time. It is revealed that Al1-x-xScxGdyN crystallizes in a wurtzite-derived structure for X + y <~ 0.35, consistent with the calculated phase diagram. The computational investigation explores whether co-substitution induces cooperative effects on these alloys' piezoelectric and ferroelectric properties, finding that it is beneficial for reducing the polarization switching barrier. We calculate that Al1-x-xScxGdyN thin films should display ferroelectric switching. This is supported by our experimental measurements of a high optical bandgap, enhanced piezoelectric coefficient, and a change in the calculated polarization switching mechanism, and we achieve preliminary ferroelectric switching that experimentally realizes the prediction. Overall, our work sets the foundation toward quaternary wurtzite-nitride-based multifunctional materials, including piezoelectrics, ferroelectrics, and possibly even multiferroics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Coupling High-Throughput Experiments and Regression Algorithms to Optimize PGM-Free ORR Electrocatalyst Synthesis

Over the past decades, significant improvement has been achieved in the performance of platinum group metal-free (PGM-free) materials as an alternative to Pt-based electrocatalysts for oxygen reduction reaction (ORR). However, further progress in ORR activity requires evaluation of precursors and synthesis approaches. In response to this challenge, we generated a first of its kind experimental data set of 36 samples using high-throughput synthesis and activity measurements. Several control parameters (e.g., Fe precursor identity, the precursor content, and pyrolysis temperature) were varied. We then developed several state-of-the-art machine learning (ML) based regression models to predict ORR activity, dependent on selected synthesis variables. Through an iterative algorithm, higher prediction accuracy (smaller root-mean-square error) was achieved. We identified that gradient boosting regression (GBR) and support vector regression (SVR), among several methods, work best for this data set. Aided by our ML-based surrogate models, we decided to alter catalyst synthesis conditions, which resulted in a 36% increase in measured ORR activity in comparison to the maximum ORR mass activity value of 21.9 A/g catalyst in the original data set. Overall, this combined experiment and machine learning approach represents a promising path forward toward developing highly efficient next-generation ORR electrocatalysts and, more generally, functional materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Homologous Alkali Metal Copper Rare-Earth Chalcogenides A 2 Cu 2 n Ln 4 Q 7+ n ( n = 1, 2, 3)

Twenty-seven new members of the A 2 Cu 2n Ln 4 Q 7+n (A = Cs, Rb; Ln = La-Nd, Sm, Gd-Yb; Q = S, Se) homologous series were synthesized in one of three structural types (indicated by n = 1, 2, 3). All the compounds contained 3D frameworks with alkali-metal-containing tunnels. For each increment in n, one Cu 2 Q was added, which was incorporated into the framework as an edge-sharing tetrahedron by replacing a square planar chalcogenide site. High-throughput DFT calculations predicted many of the phases to be thermodynamically stable. These predictions were compared with the synthesis results for the phases formed in each composition space. In the syntheses, heavier lanthanides showed a preference to start forming the n = 3 ACu 3 Ln 2 Q 5 , which is consistent with the predictions. RbCuNd 2 Se 4 and RbCuTb 2 Se 4 were found to be thermally stable under vacuum at temperatures up to 1000 °C. Optical measurements revealed band gaps of 1.55(5) and 1.62(5) eV for CsCuCe 2 Se 4 and RbCuTb 2 Se 4 , respectively, and a work function of 4.83(5) eV for CsCuPr 2 Se 4 . Additionally, some n = 3 ACu 3 Ln 2 Qs compounds exhibit a negative phonon mode because of a copper atom coordination, which may distort to a trigonal planar geometry at sufficiently low temperatures. The dynamic instabilities and the predicted distortion in the copper tetrahedra for the n = 3 ACu 3 Ln 2 Q 5 compounds were found to have a linear relationship with the atomic number of the lanthanides and the electronegativity of the lanthanides. In conclusion, the A 2 Cu 2 n Ln 4 Q 7+n compounds can potentially find application as high-temperature thermoelectric materials and other semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Discovery and Synthesis of a Family of Boride Altermagnets

Borides are a rich material family. To push the boundaries of borides’ properties and applications into broader fields, we have conducted systematic theoretical and experimental searches for synthesizable phases in ternary borides TM 2 B 2 (T = 3d, M = 4d/5d transition metals). We find that TM 2 B 2 in the FeMo 2 B 2 -type and CoW 2 B 2 -type structures form a large family of stable/metastable materials of 120 members. Among them, we identify 40 materials with stable magnetic solutions. Further, we discover 11 altermagnets in the FeMo 2 B 2 -type structure. So far, boride altermagnets are rare. In these altermagnets, T = Fe or Mn atoms are arranged in parallel T-chains with strong ferromagnetic intrachain couplings and antiferromagnetic interchain couplings. They simultaneously exhibit electronic band spin splitting, typical of ferromagnetism, and zero net magnetization, typical of antiferromagnetism. They also exhibit magnonic band chiral splitting. Both effects originate from the unique altermagnetic symmetries crucially constrained by the nonmagnetic atoms in the structure. Transport properties of relevance to spintronic applications, including the strain-induced spin-splitter effect and anomalous Hall effect, are predicted. An iodine-assisted synthesis method for TM 2 B 2 is developed, using which 7 of the predicted low-energy phases are experimentally synthesized and characterized, including 4 altermagnets. This work expands the realm of borides by offering new opportunities for studying altermagnetism and altermagnons in borides. It also provides valuable insights into the discovery and design of altermagnets. Here, by demonstrating that altermagnets can exist as families sharing a common motif, this work paves a feasible route for discovering altermagnets by elemental substitutions and high-throughput computations.

Chemical structure↗
DOE OSTI2025

Synthesis challenges, thermodynamic stability, and growth kinetics of La–Si–P ternary compounds

Although many new compounds have been recently predicted with the help of machine learning, the successful experimental synthesis of these compounds remains challenging. Computational insights about the thermodynamic stability and phase formation kinetics among the ground state and competing metastable phases are highly desirable to rationalize and attempt to overcome synthesis challenges experimentally. In this work, we explore synthetic challenges within ternary La–Si–P compounds through feedback between experimental and computational studies. We discuss the experimental challenges in forming three computationally predicted ternary phases (La 2 SiP, La 5 SiP 3 , and La 2 SiP 3 ). To understand the synthetic challenges, we performed molecular dynamics (MD) simulations using an accurate and efficient artificial neural network machine learning (ANN-ML) interatomic potential. We study the phase stability and formation kinetics of these ternary phases in relation to the reported and synthesized La 2 SiP 4 phase. While the growth of the La 2 SiP 4 phase can be reproduced by our MD simulation, our results indicate that the rapid formation of a Si-substituted LaP crystalline phase is a major barrier to the synthesis of the predicted La 2 SiP, La 5 SiP 3 , and La 2 SiP 3 ternary compounds, agreeing well with experimental observations. Our simulations also suggest that there is a narrow temperature window in which the La 2 SiP 3 phase can be grown from the solid–liquid interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Recent advances in rational design of defect-engineered photocatalysts toward sustainable NH 3 synthesis as H 2 carrier: From fundamental and development to machine-learning

In this study, we provide a detailed overview of the fundamental mechanisms underpinning photocatalytic N 2 reduction. We also discuss advances in catalyst design for the synthesis of NH 3 . Particular emphasis is placed on the role of surface defect engineering, which includes the creation of surface defects to enhance the performance of semiconducting photocatalysts for efficient N 2 reduction. In addition, the application of a machine learning-based computational modeling approach is discussed as an important driving force for predicting and regulating NH 3 synthesis efficiency based on catalyst features and reaction conditions. Finally, existing challenges and future perspectives for improving the performance of defect-engineered photocatalysts are outlined to contribute to the ongoing discourse on sustainable ammonia generation. This review aims to clarify recent progress in the rational design of defect-containing photocatalysts for the synthesis of NH 3 and encourages innovative approaches to catalyst optimization rather than solely focusing on new materials.

08 HYDROGEN↗
DOE OSTI2025

Stability, growth, and doping of In 2 (Si, Ge) 2 O 7 : Promising n -type wide-bandgap semiconductors

In this paper, we investigate, computationally and experimentally, the phase stability, electronic structure properties, and the propensity for n-type doping of In 2 X 2 O 7 (X = Si, Ge) ternary oxides. This family of materials contains promising novel wide-gap semiconductors based on their estimated high n-type Baliga figures of merit and acceptable thermal conductivity for power electronics applications. Here, we predict that both In 2 Si 2 O 7 and In 2 Ge 2 O 7 are n-type dopable, with Zr providing between 10 16 and above 10 21 cm −3 net donor concentrations under O-poor conditions, depending on the chemistry, structure (ground-state thortveitite or high-pressure pyrochlore), and synthesis temperature. To verify our predictions, we synthesize Zr-doped In 2 Ge 2 O 7 in the thortveitite structure and measure its electrical properties. Initial thin-film growth and annealing lead to polycrystalline thin films with bandgaps over 4 eV and confirm Zr doping predictions by achieving electron concentrations at 10 14 –10 16 cm −3 even under O-rich conditions. While future epitaxial growth development is still needed, this study establishes In 2 X 2 O 7 as promising n-type wide-gap semiconductors for power electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Navigating phase diagram complexity to guide robotic inorganic materials synthesis

Abstract Efficient synthesis recipes are needed to streamline the manufacturing of complex materials and to accelerate the realization of theoretically predicted materials. Often, the solid-state synthesis of multicomponent oxides is impeded by undesired by-product phases, which can kinetically trap reactions in an incomplete non-equilibrium state. Here we report a thermodynamic strategy to navigate high-dimensional phase diagrams in search of precursors that circumvent low-energy, competing by-products, while maximizing the reaction energy to drive fast phase transformation kinetics. Using a robotic inorganic materials synthesis laboratory, we perform a large-scale experimental validation of our precursor selection principles. For a set of 35 target quaternary oxides, with chemistries representative of intercalation battery cathodes and solid-state electrolytes, our robot performs 224 reactions spanning 27 elements with 28 unique precursors, operated by 1 human experimentalist. Our predicted precursors frequently yield target materials with higher phase purity than traditional precursors. Robotic laboratories offer an exciting platform for data-driven experimental synthesis science, from which we can develop fundamental insights to guide both human and robotic chemists.

Chen, Jiadong (ORCID:0009000476038838)↗
DOE OSTI2021

The Creation of True Two-Dimensional Silicon Carbide

This paper reports the successful synthesis of true two-dimensional silicon carbide using a top-down synthesis approach. Theoretical studies have predicted that 2D SiC has a stable planar structure and is a direct band gap semiconducting material. Experimentally, however, the growth of 2D SiC has challenged scientists for decades because bulk silicon carbide is not a van der Waals layered material. Adjacent atoms of SiC bond together via covalent sp3 hybridization, which is much stronger than van der Waals bonding in layered materials. Additionally, bulk SiC exists in more than 250 polytypes, further complicating the synthesis process, and making the selection of the SiC precursor polytype extremely important. This work demonstrates, for the first time, the successful isolation of 2D SiC from hexagonal SiC via a wet exfoliation method. Unlike many other 2D materials such as silicene that suffer from environmental instability, the created 2D SiC nanosheets are environmentally stable, and show no sign of degradation. 2D SiC also shows interesting Raman behavior, different from that of the bulk SiC. Our results suggest a strong correlation between the thickness of the nanosheets and the intensity of the longitudinal optical (LO) Raman mode. Furthermore, the created 2D SiC shows visible-light emission, indicating its potential applications for light-emitting devices and integrated microelectronics circuits. We anticipate that this work will cause disruptive impact across various technological fields, ranging from optoelectronics and spintronics to electronics and energy applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Insights into the Biomimetic Synthesis of 2D ZnO Nanomaterials through Peptoid Engineering

Achieving predictable biomimetic crystallization using sequence-defined synthetic molecules in mild conditions represents a long-standing challenge in materials synthesis. Herein we report a peptoid-based approach for biomimetic control over the formation of nanostructured ZnO materials in ambient aqueous conditions. A series of two-dimensional (2D) ZnO nanomaterials have been successfully obtained using amphiphilic peptoids with different numbers, ratios, and patterns of various hydrophilic and hydrophobic side chains. By investigating the relationship between peptoid hydrophobicity and the thickness of the resultant ZnO nanomaterials, we found the critical role of peptoid hydrophobicity in the peptoid-controlled ZnO formation. Our results suggest that tuning the hydrophobicity of peptoids can be used to moderate peptoid–ZnO surface interactions, thus controlling the formation of ultrathin (<2.5 nm) 2D ZnO nanomaterials. Here, the peptoid-controlled formation of ZnO nanomaterials was further investigated using ultrasmall-angle X-ray scattering (USAXS). Our work suggests a new approach to synthesizing 2D metal oxide nanomaterials using sequence-defined synthetic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Prediction and Control of Atomic Ordering in Electrodeposited Binary Alloy Films: Direct Synthesis of L10 Magnetic Phases

Permanent magnet materials are essential components in renewable energy technology, underlying, electric vehicles, hybrids, wind turbines and more. Today commercial permanent magnets based on Nd-Fe-B exhibit an energy product of ~ 400 kJ/m 3 , capable to run wind turbines efficiently. Unfortunately, the supplies of rare-earth elements are centralized, and their availability may see volatility over time. This state of affairs stimulates the search for the search for rare-earth-free permanent magnetic materials. The L1 0 crystal structure underlines an important class of chemical ordered alloys that exhibit uniaxial magnetocrystalline anisotropy. This material has been considered an excellent candidate for rare-earth-free permanent magnets. In this program, a series of systematic experiments were performed and analysed in order to understand the effect of each. In order to synthesize L 10-Fe-Ni, one has to circumvent the sluggish kinetic and the limited driving force resulted from the low order-disorder temperature (~320°C) of the system. A strategy was found to trigger a martensitic transformation from the FCC phase to one of the non-cubic phases by high-strain methods. The body-centered tetragonal Fe-Ni obtained by this strategy was considered as a precursor of L10 Fe-Ni. The formation of BCT Fe-Ni via a displacive process was also implemented at the nanoscale by using tailored AuNi@FeNi core@shell.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Computational evolution of high-performing unfused non-fullerene acceptors for organic solar cells

Materials optimization for organic solar cells (OSCs) is a highly active field, with many approaches using empirical experimental synthesis, computational brute force to screen a subset of chemical space, or generative machine learning methods that often require significant training sets. While these methods may find high-performing materials, they can be inefficient and time-consuming. Genetic algorithms (GAs) are an alternative approach, allowing for the “virtual synthesis” of molecules and a prediction of their “fitness” for some property, with new candidates suggested based on good characteristics of previously generated molecules. In this work, a GA is used to discover high-performing unfused non-fullerene acceptors (NFAs) based on an empirical prediction of power conversion efficiency (PCE) and provides design rules for future work. The electron-withdrawing/donating strength, as well as the sequence and symmetry, of those units are examined. The utilization of a GA over a brute-force approach resulted in speedups up to 1.8 × 10 12 . New types of units, not frequently seen in OSCs, are suggested, and in total 5426 NFAs are discovered with the GA. Of these, 1087 NFAs are predicted to have a PCE greater than 18%, which is roughly the current record efficiency. While the symmetry of the sequence showed no correlation with PCE, analysis of the sequence arrangement revealed that higher performance can be achieved with a donor core and acceptor end groups. Future NFA designs should consider this strategy as an alternative to the current A-D-A'-D-A architecture.

14 SOLAR ENERGY↗
DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗
NASA NTRS1978

Relationships between digital signal processing and control and estimation theory

Research directions in the fields of digital signal processing and modern control and estimation theory are discussed. Stability theory, linear prediction and parameter identification, system synthesis and implementation, two-dimensional filtering, decentralized control and estimation, and image processing are considered in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the disciplines.

Willsky, A. S.↗
NASA NTRS1984

The calculation of theoretical chromospheric models and the interpretation of solar spectra from rockets and spacecraft

Models and spectra of sunspots were studied, because they are important to energy balance and variability discussions. Sunspot observations in the ultraviolet region 140 to 168 nn was obtained by the NRL High Resolution Telescope and Spectrograph. Extensive photometric observations of sunspot umbrae and prenumbrae in 10 chanels covering the wavelength region 387 to 3800 nm were made. Cool star opacities and model atmospheres were computed. The Sun is the first testcase, both to check the opacity calculations against the observed solar spectrum, and to check the purely theoretical model calculation against the observed solar energy distribution. Line lists were finally completed for all the molecules that are important in computing statistical opacities for energy balance and for radiative rate calculations in the Sun (except perhaps for sunspots). Because many of these bands are incompletely analyzed in the laboratory, the energy levels are not well enough known to predict wavelengths accurately for spectrum synthesis and for detailed comparison with the observations.

Avrett, E. H.↗
NASA NTRSDate not supplied

Operational Evaluation of NASA SPoRT Lightning Safety Applications for Impact Based Decision Support Services

The NWS Office in Huntsville is tasked with monitoring and predicting the threat for lightning within its County Warning Area. These impact-based decision support services (IDSS) are provided routinely for aviation operations, irregularly for large-scale, outdoor events, and can have varying safety requirements, such as proximity to location and duration. Lightning monitoring and prediction can require the rapid synthesis of a plethora of data, so products that make this process more efficient and effective are sought by the operational community. The Huntsville NWS Office benefits from close collaboration with the NASA SPoRT Center, which is developing several products to address these operational challenges in concentrated R2O/O2R efforts. One example of this is the StopLight product, which uses Geostationary Lightning Mapper (GLM) flash extent density (FED) to provide an easy-to-interpret visual aid of lightning occurring within the last 30 minutes. The StopLight product shows both the age and location of the last lightning flash within each GLM pixel, which can be particularly useful for IDSS with determining when to resume activities or operations that have been shut down due to lightning. This presentation highlights results of collaboration between NASA SPoRT and NWS Huntsville, including testing of the Stoplight product, and additional experimental products in development. A brief summary of the lightning products are provided while the main focus will discuss product evaluation and forecaster perspective during real-time weather watch activities to support aviation operations and events where IDSS was necessary.

Kristopher White↗