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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Atmospheric Prebiotic Chemistry and Organic Hazes

Earth's atmospheric composition at the time of the origin of life is not known, but it has often been suggested that chemical transformation of reactive species in the atmosphere was a significant source of pre biotic organic molecules. Experimental and theoretical studies over the past half century have shown that atmospheric synthesis can yield molecules such as amino acids and nucleobases, but these processes are very sensitive to gas composition and energy source. Abiotic synthesis of organic molecules is more productive in reduced atmospheres, yet the primitive Earth may not have been as reducing as earlier workers assumed, and recent research has reflected this shift in thinking. This work provides a survey of the range of chemical products that can be produced given a set of atmospheric conditions, with a particular focus on recent reports. Intertwined with the discussion of atmospheric synthesis is the consideration of an organic haze layer, which has been suggested as a possible ultraviolet shield on the anoxic early Earth. Since such a haze layer - if formed - would serve as a reservoir for organic molecules, the chemical composition of the aerosol should be closely examined. The results highlighted here show that a variety of products can be formed in mildly reducing or even neutral atmospheres, demonstrating that contributions of atmospheric synthesis to the organic inventory on early Earth should not be discounted. This review intends to bridge current knowledge of the range of possible atmospheric conditions in the prebiotic environment and pathways for synthesis under such conditions by examining the possible products of organic chemistry in the early atmosphere.

Trainer, Melissa G.↗
NASA NTRS2017

Pathways to Meteoritic Glycine and Methylamine

Glycine and methylamine are meteoritic water-soluble organic compounds that provide insights into the processes that occurred before, during, and after the formation of the Solar System. Both glycine and methylamine and many of their potential synthetic precursors have been studied in astrophysical environments via observations, laboratory experiments, and modeling. Despite these studies, the synthetic mechanisms for their formation leading to their occurrence in meteorites remain poorly understood. Typical 13C-isotopic values ((delta)13C) of meteoritic glycine and methylamine are 13C-enriched relative to their terrestrial counterparts; thus, analyses of their stable carbon isotopic compositions (13C/12C) may be used not only to assess terrestrial contamination in meteorites but also to provide information about their synthetic routes inside the parent body. Here, we examine potential synthetic routes of glycine and methylamine from a common set of precursors present in carbonaceous chondrite meteorites, using data from laboratory analyses of the well-studied CM2 Murchison meteorite. Several synthetic mechanisms for the origins of glycine and methylamine found in carbonaceous chondrites may be possible, and the prevalence of these mechanisms will largely depend on (a) the molecular abundance of the precursor molecules and (b) the levels of processing (aqueous and thermal) that occurred inside the parent body. In this work, we also aim to contextualize the current knowledge about gas-phase reactions and irradiated ice grain chemistry for the synthesis of these species through parent body processes. Our evaluation of various mechanisms for the origins of meteoritic glycine and methylamine from simple species shows what work is still needed to evaluate both the abundances and isotopic compositions of simpler precursor molecules from carbonaceous chondrites as well as the effects of parent body processes on those abundances and isotopic compositions. The analyses presented here combined with the indicated measurements will aid a better interpretation of quantitative analysis of reaction rates, molecular stability, and distribution of organic products from laboratory simulations of interstellar ices, astronomical observations, and theoretical modeling.

interstellar ice↗
NASA NTRS2000

Gravity-Related Transport Process in Off-Axis Sputtering Deposition

In the synthesis of epitaxial oxide films, reactive off-axis sputtering deposition techniques have demonstrated the advantages of fabricating high quality epitaxial films. Due to the collisions between the sputtered species and the residue gases, the kinetic energy of species was reduced and the transport of depositing species changed from a ballistic movement to a diffusive drift in which the transport species were almost thermalized. A gravity effect could appear in the transport process. Three transport regimes were observed when the growth pressures vary from 5 mTorr to 150 mTorr. Film growth rate, depositing orientations, crystal structure, surface morphology, and compositions were characterized. A gravity related phenomenon was revealed in film growth at the relative low growth pressures.

Zhu, Shen↗
DOE OSTI2025

Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts

Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study presents a multistage machine learning (ML) approach to streamline the discovery and optimization of complex multimetallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain knowledge with minimized reliance on subjective intuition. Then, the active learning module efficiently refines element composition and synthesis conditions through iterative experimental feedback. The process culminated in the discovery of a promising Ru-Mn-Ca-Pr oxide catalyst. Our workflow also enhances theoretical simulations with domain adaptation strategy, providing deeper mechanistic insights aligned with experimental findings. By leveraging diverse data sources and multiple ML strategies, we demonstrate an efficient pathway for electrocatalyst discovery and optimization. This comprehensive, data-driven approach represents a paradigm shift and potentially benchmark in electrocatalysts research.

Science & Technology - Other Topics↗
DOE OSTI2024

Crystallization and assembly at interfaces: Celebrating the achievements of a vibrant research community

Crystallization is one of the cornerstones of modern materials science and engineering and plays a critical role in industries ranging from petroleum derivative manufacturing to microstructural engineering of structural materials and the defect-free growth of silicon single crystals for integrated chip technology. Also, in the realm of environmental and biological processes, the mineralization of diverse compounds has shaped the vast array of ecosystems we observe today. Conversely, understanding the crystallization and assembly of building blocks of various sizes at interfaces has broader impacts on materials synthesis, performance of energy storage devices, optimized processing conditions, and more.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ultra-fast non-equilibrium synthesis of cathode materials for Li-ion batteries

Synthesis of cathode materials plays an important role in determining the production efficiency, cost and performance of lithium-ion batteries. However, the conventional synthesis methods always experience a slow heating rate and involve a complicated multi-step reaction process and sluggish reaction dynamics, leading to high energy and long time consuming. Herein, we report a high-temperature shock (HTS) strategy for the ultra-fast synthesis of cathode materials in seconds. The HTS process experiences an ultra-high heating rate, leading to a non-equilibrium reaction and fast reaction kinetics and avoiding high energy and long time consuming. Mainstream cathode materials (such as LiMn 2 O 4 , LiCoO 2 , LiFePO 4 , and Li-rich layered oxide/NiO heterostructured material) are successfully synthesized with pure phases, oxygen vacancies, ultra-small particle sizes and good electrochemical performance. In conclusion, the HTS process not only provides an efficient synthesis approach for cathode materials but also can be extended beyond lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Single Crystalline Na 0.67 Ni 0.33 Mn 0.67 O 2 Positive Electrode Material via Molten Salt Synthesis for Sodium Ion Batteries

P2-layered Na 0.67 Ni 0.33 Mn 0.67 O 2 (NNMO) has emerged as a promising positive electrode material for sodium ion batteries due to its appealing electrochemical properties. Synthesis of polycrystalline NNMO (PC-NNMO) materials through conventional calcination of solid precursors remains the prevailing method, where heating occurs in a dry environment with air or O 2 . On the other hand, the molten salt method, where precursors are submerged in molten salt medium during calcination, emerged in recent years to be a scalable technique for more controlled crystal growth and uniform morphology in a variety of materials. Here, we utilize the molten salt method to synthesize single crystalline NNMO (SC-NNMO) materials with enhanced electrochemical properties. The SC-NNMO material exhibits an initial specific discharge capacity of 95 mAh g –1 at a 0.1C rate, retaining approximately 88.5% of its capacity after 100 cycles over a wide voltage range of 2.0–4.2 V. Furthermore, SC-NNMO maintains a capacity retention of 83.9% after 300 cycles at a 1C rate compared to 66.6% for PC-NNMO, indicating excellent long-term cycling stability. This stability is further confirmed by the performance of an SC-NNMO//hard carbon full cell, which retains 90.3% of its capacity after 200 cycles at 1C within a voltage window of 1.9–4.1 V. The enhancement in stability of the SC-NNMO sample is attributed to the single crystalline structure suppressing the undesired P2–O2 phase transition at high voltage. This study also presents an easy, efficient, and straightforward molten salt process for SC-NNMO material synthesis, offering valuable insights into the potential application of such methodology for the large-scale, cost-effective production of various sodium-layered transition metal oxide positive electrode materials for SIBs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

N2-to-NH3 conversion by excess electrons trapped in point vacancies on 5f-element dioxide surfaces

Ammonia (NH 3 ) is one of the basic chemicals in artificial fertilizers and a promising carbon-free energy storage carrier. Its industrial synthesis is typically realized via the Haber−Bosch process using traditional iron-based catalysts. Developing advanced catalysts that can reduce the N 2 activation barrier and make NH 3 synthesis more efficient is a long-term goal in the field. Most heterogeneous catalysts for N 2 -to-NH 3 conversion are multicomponent systems with singly dispersed metal clusters on supporting materials to activate N 2 and H 2 molecules. Herein, we report single-component heterogeneous catalysts based on 5 f actinide dioxide surfaces (ThO 2 and UO 2 ) with oxygen vacancies for N 2 -to-NH 3 conversion. The reaction cycle we propose is enabled by a dual-site mechanism, where N 2 and H 2 can be activated at different vacancy sites on the same surface; NH 3 is subsequently formed by H − migration on the surface via associative pathways. Oxygen vacancies recover to their initial states after the release of two molecules of NH 3 , making it possible for the catalytic cycle to continue. Our work demonstrates the catalytic activities of oxygen vacancies on 5 f actinide dioxide surfaces for N 2 activation, which may inspire the search for highly efficient, single-component catalysts that are easy to synthesize and control for NH 3 conversion.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Modifying Silicates for Better Dispersion in Nanocomposites

An improved chemical modification has been developed to enhance the dispersion of layered silicate particles in the formulation of a polymer/silicate nanocomposite material. The modification involves, among other things, the co-exchange of an alkyl ammonium ion and a monoprotonated diamine with interlayer cations of the silicate. The net overall effects of the improved chemical modification are to improve processability of the nanocomposite and maximize the benefits of dispersing the silicate particles into the polymer. Some background discussion is necessary to give meaning to a description of this development. Polymer/silicate nanocomposites are also denoted polymer/clay composites because the silicate particles in them are typically derived from clay particles. Particles of clay comprise layers of silicate platelets separated by gaps called "galleries." The platelet thickness is 1 nm. The length varies from 30 nm to 1 m, depending on the silicate. In order to fully realize the benefits of polymer/silicate nanocomposites, it is necessary to ensure that the platelets become dispersed in the polymer matrices. Proper dispersion can impart physical and chemical properties that make nanocomposites attractive for a variety of applications. In order to achieve nanometer-level dispersion of a layered silicate into a polymer matrix, it is typically necessary to modify the interlayer silicate surfaces by attaching organic functional groups. This modification can be achieved easily by ion exchange between the interlayer metal cations found naturally in the silicate and protonated organic cations - typically protonated amines. Long-chain alkyl ammonium ions are commonly chosen as the ion-exchange materials because they effectively lower the surface energies of the silicates and ease the incorporation of organic monomers or polymers into the silicate galleries. This completes the background discussion. In the present improved modification of the interlayer silicate surfaces, the co-ion exchange strengthens the polymer/silicate interface and ensures irreversible separation of the silicate layers. One way in which it does this is to essentially tether one amine of each diamine molecule to a silicate surface, leaving the second amine free for reaction with monomers during the synthesis of a polymer. In addition, the incorporation of alkyl ammonium ions into the galleries at low concentration helps to keep low the melt viscosity of the oligomer formed during synthesis of the polymer and associated processing - a consideration that is particularly important in the case of a highly cross-linked, thermosetting polymer. Because of the chemical bonding between the surface-modifying amines and the monomers, even when the alkyl ammonium ions become degraded at high processing temperature, the silicate layers do not aggregate and, hence, nanometer-level dispersion is maintained.

Campbell, Sandi↗
DOE OSTI2022

Generalized optimization-based synthesis of membrane systems for multicomponent gas mixture separation

Synthesizing a membrane system to separate multicomponent gas mixture is challenging due to the combinatorial number of feasible configurations and the difficulties in describing the multicomponent permeators. Here we present a mixed-integer nonlinear programming (MINLP) model for synthesizing membrane systems for multicomponent gas mixture separation. The approach employs a richly connected superstructure to represent numerous potential system configurations, and different physics-based surrogate permeator models, such as countercurrent flow or crossflow, to be used in each stage. Moreover, to describe realistic systems, pressure drop equations can be included. We also present solution methods to accelerate the solution process. Through a case study of natural gas sweetening, we demonstrate that the proposed approach is able to obtain good solutions using an off-the-shelf global optimization solver. Finally, we expand the conventional membrane system synthesis problem by introducing feed variability in our model through a case study of an integrated reactor-separation system.

42 ENGINEERING↗
DOE OSTI2026

Absorption dissymmetry factor enhancement: A data-driven approach to unravel the synthesis knobs of chiral 2D perovskites

Chiral 2D metal halide perovskites (MHPs) are promising for spin-optoelectronic applications, yet their absorption dissymmetry factor (g abs ) exhibits significant variability due to complex, co-dependent structural and experimental factors. Here, we established a data-driven framework using Pearson’s correlation, ANOVA, and Gaussian process regression to identify and model key synthesis “knobs” governing these properties. The analysis revealed that solvent choice is the primary factor driving variability. For acetonitrile-based films, g abs was maximized by optimizing annealing temperature and film thickness. Conversely, films from higher boiling point solvents showed complex dependencies on annealing temperature, excitonic integral intensity, and film texture. These statistical correlations provide a roadmap for the rational design of high-performance chiral MHPs and establish a foundation for future machine learning-driven material exploration.

ANOVA↗
DOE OSTI2022

Optimizing thermal stability and mechanical behavior in segregation-engineered nanocrystalline Al–Ni–Ce alloys: A combinatorial study

The deliberate use of solute enrichment at grain boundaries, otherwise known as segregation engineering, is a promising approach to tailor the properties of interface-dominated materials such as nanocrystalline alloys. Here, the ensuing chemical and structural evolution at grain boundaries can give rise to thermal stability and excellent mechanical properties, but the interplay between enrichment, phase decomposition, grain growth, and mechanical behavior exists in a vast composition and processing space. In this study, a combinatorial synthesis and rapid characterization approach was applied to segregation-engineered nanocrystalline Al–Ni–Ce alloys to assess the evolution of microstructure and resulting mechanical behavior as functions of alloying content and annealing conditions. In addition to the identification of alloys and processing conditions that give rise to exceptional thermal stability, strength retention, and homogeneous plastic flow, we construct combined thermal stability and deformation mechanism maps that demarcate several important regimes of behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Site-specific surface reactivity on SnO 2 : Evaluating selective atomic layer deposition processes

Area selective atomic layer deposition (AS-ALD) is a bottom-up synthesis approach with potential for deposition with molecular level precision. Here, the site-specific hydration of metal oxide substrates, combined with surface H 2 O-selective ALD processes, provides a potentially powerful path to targeted synthesis. Density functional theory (DFT) calculations are used to predict the thermodynamics of ALD precursor reactivity and hydration for (001), (101), (110), and (100) rutile SnO 2 facets as a function of temperature. Trimethylaluminum (TMA) and dimethyl aluminum isopropoxide (DMAI) dimers are predicted to react with both dehydrated and hydrated SnO 2 (001), (101), and (110) facets at ALD-relevant temperatures, while the SnO 2 (100) facet is predicted to be uniquely unreactive with TMA and DMAI monomers as well as dehydrate near 177 °C making this facet more amenable to targeted ALD. In situ ellipsometric studies of Al 2 O 3 ALD on polycrystalline SnO 2 at 150 °C are consistent with the computational predictions of rapid and unselective nucleation, in stark contrast to inhibited and selective ALD on isostructural rutile TiO 2 .

Atomic Layer Deposition↗
DOE OSTI2025

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Speaker-targeted Synthetic Speech Detection

Text-to-speech technologies are evolving quickly towards realistic-sounding human-like voices. As this technology improves, so does the opportunity for malpractice in speaker identification (SID) via spoofing, the process of impersonating a voice biometric via synthesis. More data typically equates to a more realistic voice model, which poses an issue for well-known subjects, such as politicians and celebrities, who have vast amounts of multimedia available online. Detection of synthetic speech has relied on signal processing techniques that focus on the generation of new acoustic features and train deep learning models to detect when an audio file has been manipulated through the characterization of unnatural changes or artifacts. However, these techniques do not use any information from the speaker they are evaluating. This paper proposes to incorporate information from the speaker-of-interest (SoI) into the models to avoid specific spoofing attacks for certain vulnerable people. The wealth of data for well-known people can also be used to train a speaker-specific spoofing detector with a higher level of accuracy than a speaker-independent model. The paper proposes a new xResNet-PLDA system and compares it to three different baseline systems: a state-of-the-art speaker identification system, an xResNet system trained to discriminate between bona fide and fake speech, and a speaker identification system in which the PLDA and calibration models were trained with bona fide and fake speech. We evaluated the systems in two different scenarios — a cross-validation scenario and a hold-out scenario — with three different databases. We show how the proposed system outperforms dramatically the baseline systems in each scenario and for each database. Finally, we show how using a small amount of the SoI’s speech to adapt global calibration parameters improves the performance of the system, especially in unseen conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2003

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

Blonski, Slawomir↗
DOE OSTI2020

Improving the picture of atomic structure in nonoriented polymer domains using the pair distribution function: A study of polyamide 6

Abstract Investigations of the atomic structures within polyamides started over 80 years ago and continue today. These weakly ordered materials diffract X‐rays poorly and typically require postprocessing to obtain idealized samples for structural studies. An important goal remains to develop techniques to study the local structure in its natural state, with atomic resolution, and with sensitivity to subtle changes due to synthesis conditions or other technologically relevant processing procedures. Here, we compare the structures of as‐produced, nonoriented polyamide 6 ([C 6 H 11 NO] n ) from both hydrolytic and anionic processes. A total scattering pair distribution function approach is used to elucidate information about the atomic bonding, molecular conformation, chain packing, crystallite size, and ratio of ordered to disordered domain content. The results are compared with those from standard analytical methods.

Terban, Maxwell W.↗
DOE OSTI2024

Computationally guided synthesis of carbon coated mesoporous silica materials

Mesoporous silica materials (MSMs) are well-suited for biomedical applications due to their unique features, including a large surface area and tunable pore size. To enhance their durability, the small pores in MSMs are filled with carbon precursors and then carbonized to prevent them from interacting with unreacted silicic acid. Here, in this study, we synthesized and healed MSMs using a combination of non-reactive and reactive molecular dynamics (MD) simulations. The non-reactive MD simulation revealed that the self-assembly of Pluronic® L64 polymers in water resulted in nearly 80 % hydrogen bonds between the hydrophilic sections of the micelle and water. In the bond-boosted ReaxFF MD simulations, silicic acid precursors were condensed on the micelle surface, with over 60 % of them leading to the creation of periodic mesoporous silica within the system. Condensation of silicic acid precursors at 300 K with bond-boosting and at 1500 K without it both significantly promoted the polymerization of Si(OH) 4 , with the latter doubling the rate compared to the former. Subsequently, we healed the MSM surface by carbonizing carbon precursors inside an MSM pore. Polyethylene (PE) and high-rank lignite were identified as the most suitable precursors due to their ability to form turbostratic graphene structures. High-rank lignite exhibited the highest carbon conversion ratio to 6-membered rings, closely followed by PE, in the carbon ring formation analysis. Additionally, the production of gases, such as H 2 , increased significantly for PE at both 2200 K and 2600 K, indicating the conversion of a considerable portion of carbon into graphitic or turbostratic structures. The carbonization of PE primarily led to the formation of planar (sp 2 ) structures, while sucrose yielded the least planar structures. Finally, we studied the protective blocking of unreacted silicic acid precursor by considering a PET turbostratic graphene structure in a silica mesopore formed at 2600 K. The trajectory analysis showed that the surface of the silica was effectively coated with PET tar, preventing unreacted silicic acid from interacting with the inner silica pore surface. These findings offer valuable insights into the synthesis and carbonization-based healing processes of MSMs, enhancing their potential for various biomedical applications.

36 MATERIALS SCIENCE↗