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Results for “Design, synthesis and processing”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design of refractory multi-principal-element alloys for high-temperature applications

Abstract Refractory multi-principal-element alloys (RMPEAs) exhibit high specific strength at elevated temperatures ( T ). However, current RMPEAs lack a balance of room-temperature (RT) ductility, high- T strength, and high- T creep resistance. Using density-functional theory methods, we scanned composition space using four criteria: (1) formation energies for operational stability: $$-150\le {E}_{{\rm {f}}}$$ − 150 ≤ E f ≤ +70 meV per atom; (2) higher strength found via interstitial electron density with Young’s moduli E > 250 GPa; (3) inverse Pugh ratio for ductility: G / B < 0.57; and (4) high melting points: T m > 2500 °C. Using rapid bulk alloy synthesis and characterization, we validated theory and down-selected promising alloy compositions and discovered Mo 72.3 W 12.8 Ta 10.0 Ti 2.5 Zr 2.5 having well-balanced RT and high- T mechanical properties. This alloy has comparable high- T compressive strength to well-known MoNbTaW but is more ductile and more creep resistant. It is also superior to a commercial Mo-based refractory alloy and a nickel-based superalloy (Haynes-282) with improved high- T tensile strength and creep resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition

Abstract Materials synthesis platforms that are designed for autonomous experimentation are capable of collecting multimodal diagnostic data that can be utilized for feedback to optimize material properties. Pulsed laser deposition (PLD) is emerging as a viable autonomous synthesis tool, and so the need arises to develop machine learning (ML) techniques that are capable of extracting information from in situ diagnostics. Here, we demonstrate that intensified-CCD image sequences of the plasma plume generated during PLD can be used for anomaly detection and the prediction of thin film growth kinetics. We develop multi-output (2 + 1)D convolutional neural network regression models that extract deep features from plume dynamics that not only correlate with the measured chamber pressure and incident laser energy, but more importantly, predict parameters of an auto-catalytic film growth model derived from in situ laser reflectivity experiments. Our results demonstrate how ML with in situ plume diagnostics data in PLD can be utilized to maintain deposition conditions in an optimal regime. Further, the predictive capabilities of plume dynamics on the kinetics of film growth or other film properties prior to deposition provides a means for rapid pre-screening of growth conditions for the non-expert, which promises to accelerate materials optimization with PLD.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Efficient Sn Recovery from SnO 2 by Alkane (C x H y=2x+2 , 0 ≤ x ≤ 4) Reduction

We study the mechanism of alkane reduction of SnO 2 for efficient low-temperature recovery of Sn from SnO 2 . Based on thermodynamic simulation results, we comparatively analyze the reduction behavior and the efficiency of SnO 2 reduction by H 2 and alkanes (C x H y=2x+2 , 0 ≤ x ≤ 4). We found that alkanes (n·C x H y ) with the higher nx generally complete the reduction of SnO 2 (T 100 ) at the lower temperature. Moreover, the T 100 of the SnO 2 reduction by alkanes (n·C x H y ) was decreased from the T 100 of pure hydrogen with the same amount of hydrogen atoms (n·H y ). We found that the concentration of a gas phase product mixture, the amount of the produced solid carbon, and the T 100 complementary vary as a function of the nx and ny, the total amount of carbon and hydrogen atoms in the reducing gas phase molecules. Our results demonstrate a viability of the low temperature reduction method of SnO 2 by alkanes for efficient recovery of Sn from SnO 2 , which can be applied for Sn recovery from Sn containing industrial wastes or Sn ores with economic value added that is held by the co-produced H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Combinatorial measurement of critical cooling rates in aluminum-base metallic glass forming alloys

Direct measurement of critical cooling rates has been challenging and only determined for a minute fraction of the reported metallic glass forming alloys. Here, we report a method that directly measures critical cooling rate of thin film metallic glass forming alloys in a combinatorial fashion. Based on a universal heating architecture using indirect laser heating and a microstructure analysis this method offers itself as a rapid screening technique to quantify glass forming ability. We use this method to identify glass forming alloys and study the composition effect on the critical cooling rate in the Al–Ni–Ge system where we identified Al 51 Ge 35 Ni 14 as the best glass forming composition with a critical cooling rate of 10 4 K/s.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Twin-pulse seeding enables pump-probe capabilities in the EUV to soft X-ray spectrum at synchrotron light sources

Having previously reported that separating the two stages of echo-enabled harmonic generation (EEHG) with one or more bending magnet (BM) sections allows the BMs to serve as the desired source of momentum compaction, here we demonstrate that this arrangement can greatly reduce the total energy modulation required by any 4th generation synchrotron light source, leading to higher repetition rates as well as stronger coherent radiation output power, with significant benefits. Since the EEHG beamline performance is mainly determined by the momentum compaction, beam emittances and beta functions of a storage ring lattice, allowing for different separations between the two stages is a straightforward way to increase the momentum compaction of chicane 1. This also enables pump-probe capabilities in a novel context, where twin-pulse seeding on the same electron bunch would allow two distinct radiation pulses with an adjustable delay in the range of 0.1 to 10 ps. In the twin-pulse seeding scheme, the same electron bunch could undergo modulation from two distinct laser pulses. Later stages would produce independent harmonics in subsequent straight sections. There are two variations of this twin-pulse seeding scheme, supporting different scientific applications. With a common modulation in stage 1, the first option allows simultaneously two independent radiation sources, with a full coverage of the EUV (2.5 to 50 nm) to soft X-ray (1.25 to 2.5 nm) spectrum; for the second option, the same stage 2 undulator could generate two coherent pulses both fitting within the FEL bandwidth, or at distinct harmonics. We present particle tracking simulation studies based on the APS-U lattice, including quantum excitation and radiation damping. These simulations indicate that there is no degradation of the modulated longitudinal phase space even when the two stages are separated by as many as 10 BM sections.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hybrid molecular beam epitaxy of germanium-based oxides

Abstract Germanium-based oxides such as rutile GeO 2 are garnering attention owing to their wide band gaps and the prospects of ambipolar doping for application in high-power devices. Here, we present the use of germanium tetraisopropoxide (GTIP), a metal-organic chemical precursor, as a source of germanium for the demonstration of hybrid molecular beam epitaxy for germanium-containing compounds. We use Sn 1- x Ge x O 2 and SrSn 1- x Ge x O 3 as model systems to demonstrate our synthesis method. A combination of high-resolution X-ray diffraction, scanning transmission electron microscopy, and X-ray photoelectron spectroscopy confirms the successful growth of epitaxial rutile Sn 1- x Ge x O 2 on TiO 2 (001) substrates up to x = 0.54 and coherent perovskite SrSn 1- x Ge x O 3 on GdScO 3 (110) substrates up to x = 0.16. Characterization and first-principles calculations corroborate that germanium occupies the tin site, as opposed to the strontium site. These findings confirm the viability of the GTIP precursor for the growth of germanium-containing oxides by hybrid molecular beam epitaxy, thus providing a promising route to high-quality perovskite germanate films.

36 MATERIALS SCIENCE↗
NASA NTRS1991

A new variable testability measure

In this paper, we propose a new Variable Testability Measure (VTM) for implementing testability at the high-level synthesis stage of the design process of integrated circuits. This new approach, based on binary decision diagrams, representing fully functional blocks of a circuit, and on their cyclomatic testability measures. It manipulates dataflow blocks to predict whether the circuit is testable and the vector set required to test it.

Jamoussi, M.↗
DOE OSTI2021

Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis

Abstract Solid‐state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing reaction conditions and precursors for ceramic synthesis can be a laborious, trial‐and‐error process, as heterogeneous mixtures of precursors often evolve through a complicated series of reaction intermediates. Here, ab initio thermodynamics is used to model which pair of precursors has the most reactive interface, enabling the understanding and anticipation of which non‐equilibrium intermediates form in the early stages of a solid‐state reaction. In situ X‐ray diffraction and in situ electron microscopy are then used to observe how these initial intermediates influence phase evolution in the synthesis of the classic high‐temperature superconductor YBa 2 Cu 3 O 6+ x (YBCO). The model developed herein rationalizes how the replacement of the traditional BaCO 3 precursor with BaO 2 redirects phase evolution through a low‐temperature eutectic melt, facilitating the formation of YBCO in 30 min instead of 12+ h. Precursor selection plays an important role in tuning the thermodynamics of interfacial reactions and emerges as an important design parameter in planning kinetically favorable synthesis pathways to complex ceramic materials.

36 MATERIALS SCIENCE↗
NASA NTRS1993

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design.

Source record↗
NASA NTRS1991

Decomposing Systems Into Subsystems For Design

Interactions among systems displayed in concise format. DeMAID (Design Manager's Aide for Intelligent Decomposition) is knowledge based software system for automating sequencing of subprocesses in design process and identifying possible multilevel structure for synthesis problem. Reorders and groups modules of equipment being designed on basis of links among modules, helping design manager make design decisions early in design cycle. Written in FORTRAN 77.

Rogers, James L., Jr.↗
DOE OSTI2020

NMR-Guided High-Temperature Electrolyte Design Using a Novel PF 5 Marker

The thermal degradation of electrolytes containing lithium hexafluorophosphate (LiPF 6 ) is a well-studied subject. However, practical application of the knowledge is difficult since the effects of the degradation process on battery performance are not well known. In this work, we propose a novel NMR experimental setup allowing direct observation of the effects of various perturbations on the electrolyte thermal degradation process, which guides the design and synthesis of new additives that improve lithium-ion battery performance at elevated temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Morphological Tuning of Nanoporous Metals Prepared with Conversion Reaction Synthesis via Thermal Annealing

We report that conversion reaction synthesis, namely, reacting an organolithium reducing agent with a metal chloride to produce a metal/LiCl nanocomposite and then removing lithium chloride with a polar organic solvent, is an efficient and scalable way to fabricate a variety of three-dimensional, bicontinuous nanoporous transition metals. Thermal annealing was investigated as a means to tune the morphology of these nanoporous metals. X-ray diffraction studies were used to investigate the effect of thermal annealing on the size and strain of phases in Cu/ LiCl, Co/LiCl, and Fe/LiCl nanocomposites, while electron microscopy and nitrogen adsorption studies were used to study the porosity and surface properties of the resulting nanoporous metals after LiCl was removed from the annealed nanocomposites. Annealing metal/LiCl nanocomposites resulted in the controlled growth of the metal nanoparticles, the rate of which depended on the diffusivity of the metal. It was observed that annealing nanocomposites produced more robust nanoporous metals with increased porosity under certain conditions. In conclusion, it was found that annealing the as-formed nanocomposites rather than the isolated nanoporous metals provides finer control of the conversion synthesis process and allows for the design of more optimized pore structures and thus enhanced suitability for catalytic and electrochemical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Optimized Photoemission from Organic Molecules in 2D Layered Halide Perovskites

In recent years, hybrid organic−inorganic metal halides have been at the forefront of materials research. Typically, the functional (e.g., optoelectronic) properties of hybrid halides are derived from the inorganic structural part, whereas the organic structural units can add extra advantages in terms of stability, rigidity, and processability. Here, we report the design, synthesis, and characterization of two new hybrid materials in which the outstanding photophysical properties originate from the organic structural part. The new compounds, (C 15 H 16 N) 2 CdCl 4 and ((Br)C 15 H 15 N) 2 CdCl 4 , have 2D layered Ruddlesden−Poppertype perovskite structures. These hybrids are blue-white light emitters just like their corresponding pure organic salts, but with much improved emission efficiencies. Optical spectroscopy and density functional theory (DFT) studies confirm that photoemission comes from the trans-stilbene organic cations. The photoluminescence quantum yield (PLQY) values of these new materials are among the highest known, 50.83% and 26.60% for (C 15 H 16 N) 2 CdCl 4 and ((Br)C 15 H 15 N) 2 CdCl 4 , respectively. This is up to a 5-fold increase as compared to the light emission efficiency of the precursor salt C 15 H 16 NCl (PLQY of 10.33%). Alongside their outstanding optical properties, their environmental and thermal stability allow their consideration for potential practical applications such as radiation detection. This work shows that hybrid metal halides can be compositionally and structurally engineered to have highly efficient photoemission originating from the organic components for fast scintillation applications.

Halogens↗
DOE OSTI2025

Extending High-Level Synthesis with AI/ML Methods

Artificial Intelligence (AI) and Machine Learning (ML) methods provide significant opportunities of improving quality of results when performing high-level synthesis (HLS). For example, they can be used to model and predict metrics of the final design (e.g., area, considering aspects such as interconnect overhead for different device technologies), facilitating exploration when searching for the best design trade-offs. They can also enable identifying hidden correlations across the various phases of the synthesis and the various optimizations performed, identifying the most effective pipelines. Finally, in more general terms, bio-inspired heuristic algorithms can improve the design space exploration for the synthesis process in terms of time and quality of the result. This paper discusses opportunities and challenges to augment HLS with AI/ML using as example flow the SODA Synthesizer, an open-source hardware generation toolchain which includes SODA-OPT, a hardware/software partitioning and pre-optimization tool developed with the MLIR framework, and PandA-Bambu, a state-of-the art HLS tool. SODA interfaces with OpenROAD to provide a complete end-to-end toolchain.

artificial intelligence↗
DOE OSTI2024

gcamfaostat: An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling

The gcamfaostat R package is designed for the preparation, processing, and synthesis of the Food and Agriculture Organization (FAO) Statistics (FAOSTAT) agroeconomic data. The primary purpose is to facilitate FAOSTAT data use in global economic and multisector dynamic models while ensuring transparency, traceability, and reproducibility. Here, we provide an overview of the development of gcamfaostat (v1.0) and demonstrate its capabilities in generating and maintaining agroeconomic data required for the Global Change Analysis Model (GCAM). Our initiative seeks to enhance the quality and accessibility of data for the global agroeconomic modeling community, with the aim of fostering more robust and harmonized outcomes in a collaborative, efficient, and open-source framework. One of the important features of the package is the possibility to construct the FAO Food Balance Sheets at the disaggregated commodity level (with over 500 commodities), which provides a comprehensive and detailed data input for a variety of analytical and modeling applications. The processed data and visualizations offered by gcamfaostat can also be valuable to a broader audience interested in gaining insights into the intricacies of global agriculture.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Performance of Integrated Fiber Optic, Piezoelectric, and Shape Memory Alloy Actuators/Sensors in Thermoset Composites

Recently, scientists and engineers have investigated the advantages of smart materials and structures by including actuators in material systems for controlling and altering the response of structural environments. Applications of these materials systems include vibration suppression/isolation, precision positioning, damage detection and tunable devices. Some of the embedded materials being investigated for accomplishing these tasks include piezoelectric ceramics, shape memory alloys, and fiber optics. These materials have some benefits and some shortcomings; each is being studied for use in active material design in the SPICES (Synthesis and Processing of Intelligent Cost Effective Structures) Consortium. The focus of this paper concerns the manufacturing aspects of smart structures by incorporating piezoelectric ceramics, shape memory alloys and fiber optics in a reinforced thermoset matrix via resin transfer molding (RTM).

Trottier, C. Michael↗