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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Designed Iron Single Atom Catalysts for Highly Efficient Oxygen Reduction Reaction in Alkaline and Acid Media

Abstract Single atom catalysts (SACs) have attracted much attentions due to their advantages of high catalysis efficiency and excellent selectivity. However, for industrial applications, synthesis of SACs in large and practical quantities is very important. The challenge is to develop synthesis methods with controllability and scalability. Herein, a well‐characterized and scalable method is demonstrated to synthesize atomically dispersed iron atoms coordinated with nitrogen on graphene, SAFe @ NG, with high atomic loading (≈4.6 wt%) through a one‐pot pyrolysis process. The method is scalable for the fabrication of Fe SACs with high quantities. The Fe–N–G catalyst exhibits high intrinsic oxygen reduction reaction (ORR) performance, reaching half potential of 0.876 and 0.702 V in alkaline and acidic solutions, respectively, with excellent microstructure stability. Furthermore, the density functional theory (DFT) simulation confirms that the Fe atoms in coordination with four nitrogen atoms, FeN4, in graphene is the active center for the 4‐electron ORR process. This work demonstrates an efficient design pathway for single atom catalysts as highly active and stable electrocatalysts for high‐performance ORR applications.

Zhao, Shiyong↗
DOE OSTI2022

High Energy Systems for Transforming CO 2 to Valuable Products (Final Report)

The objective of this project is to develop the Direct E-Beam Synthesis (DEBS) process that uses high-energy electron beams (E-Beam) to break chemical bonds. This allows the production of valuable chemicals, such as acetic acid, methanol, and carbon monoxide, at relatively low severity (pressure near one atmosphere and temperatures <150°C) from near-pure CO 2 captured from a pulverized coal-fired power plant and methane, imported as natural gas. Creating such valuable products will offset the cost of carbon capture and storage. Through this project, we have designed, constructed, and operated an E-Beam reactor to examine the feasibility of performing dry reforming reaction without a catalyst using only DEBS. We have verified the production of syngas with 1:1 H2:CO ratio and calculated that the energy cost for conversion is about 5.2 eV/molecule of product for dry reforming reaction which is similar to the energy cost for conversion using conventional thermochemical conversion but under significantly milder conditions (room temperature and atmospheric pressure). We have performed a technoeconomic analysis (TEA) to estimate the total capital requirement and the cost of production for a 99.4 MMSCFD syngas production plant via non-catalytic Direct E-Beam Synthesis (DEBS) technology utilizing a high-energy electron beam (E-Beam) accelerator. No assumption is made for syngas utilization downstream, and the incoming reactants are pure CO 2 from carbon capture (assumed to be at zero cost) and natural gas. The Total As-Spent Cost (TASC) was calculated to be $\$242.5$ million, resulting in a levelized cost of syngas (LCOS) of $\$175.84$/tonne (metric) at a natural gas price of $\$6.24$/MMBTU1. The cost of syngas is primarily determined by the price of natural gas. If the cost of the CO 2 feedstock is assumed to be non-zero, then the price of the CO 2 feed also heavily influences the levelized cost of syngas. The potential impact on the cost of electricity from syngas revenue is significant. Following DOE NETL’s guidance, a lifecycle analysis (LCA) was conducted to compare the cradle-to-gate life cycle emissions of GTI Energy’s novel Direct E-Beam Synthesis (DEBS) process that produces syngas via the reaction of methane and carbon dioxide to the emissions of a state-of-the-art Steam Methane Reforming (SMR) process that also produces syngas via the reaction of methane and steam. The DEBS process results in less GHG emissions than SMR (with CO product as the basis of comparison). openLCA was used for the LCA and the results show that the total global warming potential (GWP) of DEBS is 0.981 kg CO 2 e per kg CO product, while the SMR process has a global warming potential of 2.573 kg CO 2 e per kg CO product. The ratio of the GWP of the proposed product system to the comparison product system is 0.381. This percent change is 61.9% lower GWP than SMR.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2002

Development of Advanced Life Cycle Costing Methods for Technology Benefit/Cost/Risk Assessment

The overall objective of this three-year grant is to provide NASA Langley's System Analysis Branch with improved affordability tools and methods based on probabilistic cost assessment techniques. In order to accomplish this objective, the Aerospace Systems Design Laboratory (ASDL) needs to pursue more detailed affordability, technology impact, and risk prediction methods and to demonstrate them on variety of advanced commercial transports. The affordability assessment, which is a cornerstone of ASDL methods, relies on the Aircraft Life Cycle Cost Analysis (ALCCA) program originally developed by NASA Ames Research Center and enhanced by ASDL. This grant proposed to improve ALCCA in support of the project objective by updating the research, design, test, and evaluation cost module, as well as the engine development cost module. Investigations into enhancements to ALCCA include improved engine development cost, process based costing, supportability cost, and system reliability with airline loss of revenue for system downtime. A probabilistic, stand-alone version of ALCCA/FLOPS will also be developed under this grant in order to capture the uncertainty involved in technology assessments. FLOPS (FLight Optimization System program) is an aircraft synthesis and sizing code developed by NASA Langley Research Center. This probabilistic version of the coupled program will be used within a Technology Impact Forecasting (TIF) method to determine what types of technologies would have to be infused in a system in order to meet customer requirements. A probabilistic analysis of the CER's (cost estimating relationships) within ALCCA will also be carried out under this contract in order to gain some insight as to the most influential costs and the impact that code fidelity could have on future RDS (Robust Design Simulation) studies.

Yackovetsky, Robert↗
NASA NTRS1990

Structure/control synthesis with nonnegligible actuator mass

The simultaneous design of a structure/active control system is addressed in which the mass of the actuators required to implement the active control is considered. An algorithm for estimating the required actuator mass given the control law and the desired maneuver is presented. A nonlinear optimization algorithm is used to direct the design process. Results are given for the design of a L shaped structure where it is desired to minimize the line of sight pointing error after a worst case slew maneuver.

Zimmerman, David C.↗
DOE OSTI2023

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗
DOE OSTI2026

Structural Design of Bismuth Telluride Nanoplates through Process Variables

Binary pnictogen chalcogen compounds, primarily bismuth tellurides and selenides, are of great interest due to their applications in emerging quantum devices, as well as thermoelectric generators. The performance of bismuth telluride in these roles depends on its structure at the nanoscale, particularly the size, shape, and crystallinity of its nanocrystalline forms. However, current methods for controlling these features are often slow, inconsistent, or difficult to scale. Here, we demonstrate that through a solvothermal synthesis and hot injection process, precise control over the morphology of bismuth telluride nanoplates is possible with independent tuning of process variables, such as temperature and reaction time. We find that the nanoplate shape and internal porosity vary systematically with synthesis temperature and that the same morphological outcomes can be rapidly achieved at a fixed temperature by adjusting reaction duration. These results reveal that both the temperature and time can independently direct bismuth telluride morphological features, allowing for rapid, tunable synthesis strategies. Our approach offers a scalable framework, not only for bismuth telluride but also for related layered chalcogenides used in energy harvesting and quantum technologies.

Ackley, Jordan [Boise State Univ., ID (United Stat↗
DOE OSTI2024

Novel Materials R&D for Next-Generation Accelerator Target Facilities

High-Entropy Alloys and Electrospun Nanofiber materials are two classes of novel materials that can offer improved resistance to beam-induced radiation damage and thermal shock. Research to develop these new materials specifically for multi-megawatt accelerator target applications, such as beam windows and particle-production targets, are ongoing at Fermilab within the scope of a DOE Early Career Research Program. The research program combines in-beam experiments with complementary simulations to tailor the microstructures of these novel materials for use in next-generation accelerator target facilities. Iterative simulations to optimize the material composition, physics performance, and beam-induced thermomechanical response will guide the material design and fabrication processes based on established figures of merit. This will be followed by material irradiation experiments using low-energy ions and prototypic high-energy protons with extensive post-irradiation material characterization to assess and qualify the selected novel materials. This talk will describe the alloy design and synthesis, microstructural pre-characterization of the alloys, and plans for the eventual down selection following low-energy ion irradiation studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Methods to Create Novel La 2- x Sr x CuO 4 Devices with Multiple Atomically Sharp Interfaces

We present methods to create devices that utilize the high-temperature superconductor La 2-x Sr x CuO 4 grown by atomic layer-by-layer molecular beam epitaxy (ALL-MBE). The ALL-MBE synthesis technique provides atomically precise interfaces necessary for the tunnel junctions, Josephson junctions, and dyon detection devices that will be considered. A series of microfabrication processing steps using established techniques are given for each device, and their details are discussed. These procedures are easily extended to generate more complex designs and could be suitable for a wider variety of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1976

Low cost silicon solar array project. Task 1: Establishment of the feasibility of a process capable of low cost, high volume production of silane, SiH4

The kinetics of the redistribution of dichlorosilane and trichlorosilane vapor over a tertiary amine ion exchange resin catalyst were investigated. The hydrogenation of SiCl4 to form HSiCl3 and the direct synthesis of H2SiCl2 from HCl gas and metallurgical silicon metal were also studied. The purification of SiH4 using activated carbon adsorbent was studied along with a process for storing SiH4 absorbed on carbon. The latter makes possible a higher volumetric efficiency than compressed gas storage. A mini-plant designed to produce ten pounds per day of SiH4 is described.

Breneman, W. C.↗
DOE OSTI2024

Multivariate Bayesian Optimization of CoO Nanoparticles for CO 2 Hydrogenation Catalysis

The hydrogenation of CO 2 holds promise for transforming the production of renewable fuels and chemicals. However, the challenge lies in developing robust and selective catalysts for this process. Transition metal oxide catalysts, particularly cobalt oxide, have shown potential for CO 2 hydrogenation, with performance heavily reliant on crystal phase and morphology. Achieving precise control over these catalyst attributes through colloidal nanoparticle synthesis could pave the way for catalyst and process advancement. Yet, navigating the complexities of colloidal nanoparticle syntheses, governed by numerous input variables, poses a significant challenge in systematically controlling resultant catalyst features. We present a multivariate Bayesian optimization, coupled with a data-driven classifier, to map the synthetic design space for colloidal CoO nanoparticles and simultaneously optimize them for multiple catalytically relevant features within a target crystalline phase. The optimized experimental conditions yielded small, phase-pure rock salt CoO nanoparticles of uniform size and shape. These optimized nanoparticles were then supported on SiO 2 and assessed for thermocatalytic CO 2 hydrogenation against larger, polydisperse CoO nanoparticles on SiO 2 and a conventionally prepared catalyst. The optimized CoO/SiO 2 catalyst consistently exhibited higher activity and CH 4 selectivity (ca. 98%) across various pretreatment reduction temperatures as compared to the other catalysts. This remarkable performance was attributed to particle stability and consistent H* surface coverage, even after undergoing the highest temperature reduction, achieving a more stable catalytic species that resists sintering and carbon occlusion.

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

Kinetic modelling of an environmentally friendly carbamazepine synthesis via urea and iminostilbene in batch and continuous processes

Accurate kinetic models for reaction systems allow for improved process understanding and greater quality control, which is particularly beneficial as the pharmaceutical industry shifts from batch to continuous manufacturing (CM). In this work, a first principles kinetic model has been developed for the synthesis of carbamazepine (CBZ) from iminostilbene and urea, starting in a batch reactor and subsequently in a continuous flow reactor. An eco-friendly reaction pathway using urea was selected to avoid the toxic reagents that are typically used for synthesis of CBZ. The kinetic parameters determined from batch reactions were utilized in a MATLAB based kinetic model to simulate the yield for the continuous process. Overall, good agreement between the model prediction and corresponding experimental values was observed for the batch and continuous reaction systems within the full factorial design space. However, the model slightly overpredicted the yield of the continuous reaction system for higher conversion values (>60%) since it did not account for the reverse reaction that can occur at the studied reaction conditions. Here, the use of broken order kinetics was compared with whole number orders, and it was determined that the whole number orders resulted in better agreement at all conversion values for the continuous system.

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

SPERLU Selective Process for Efficient Removal of Lignin and Upgrading (Final Technical Report)

To meet the growing demand for bio-based chemicals and improve the profitability and efficiency of the emerging biorefinery industry, lignin is an abundant and attractive feedstock. Spero Renewables has developed a proprietary and patent-pending technology, the Selective Process for Efficient Removal of Lignin and Upgrading (SPERLU). The technology is a catalytic deconstruction and upgrading of lignin in lignocellulosic biomass or commercially available technical lignin to produce multi-functional phenol (MFP) products. The SPERLU process has been demonstrated and vetted on a lab scale to convert commercially available technical lignin to MFPs in yields of 60-90% (based on lignin). The MFP products can be separated and further upgraded through catalytic or biological means. Spero performed a detailed kinetic study of the SPERLU process and used the resulting kinetic data to design and construct a mini-pilot-scale reactor for routine production of hundreds of grams of MFP products. Spero’s lignin-based MFPs have been demonstrated for use as a drop-in replacement for bisphenol A (BPA) in the synthesis of thermoset polymers. Spero’s lignin-based thermoset polymers exhibit excellent mechanical properties and can be used in many applications. Additionally, a collaboration with the National Renewable Energy Lab (NREL) was used to evaluate the feasibility of upgrading SPERLU products through biological means into valuable chemicals. A comprehensive technoeconomic analysis (TEA) and Life-cycle analysis (LCA) have been completed and support the case for commercialization of the SPERLU technology. Through this project Spero has significantly de-risked the SPERLU technology and is actively planning larger scale pilot projects.

09 BIOMASS FUELS↗
NASA NTRS1998

Synthesis and Characterization of Modified Phenylethynyl Terminated Polyimides

As an ongoing effort to develop structural adhesives for high performance aerospace applications, recent work has focused on phenylethynyl terminated imide (PETI) oligomers. The work reported herein involves the synthesis and characterization of a series of phenylethynyl containing oligomers designated LARC (TM) MPEI (Modified Phenylethynyl Terminated Polyimide). These oligomers contain mixtures of linear, branched and star-shaped molecules. The fully imidized polymers exhibited minimum melt viscosity as low as 600 poise at 335 C. Ti/Ti lap shear specimens processed at 288 C under 15 psi showed tensile shear strength of approx. 6000 psi and 5200 psi at ambient and 350 F temperatures, respectively. The chemistry and properties of these new MPEIs are presented and compared to an optimized linear PETI, LaRC(Tm) -PETI-5.

Chang, Alice C.↗
NASA NTRS2000

The Instrument Synthesis for Analysis Laboratory at the Goddard Space Flight Center

The objectives of the Instrument Synthesis and Analysis laboratory (ISAL) are to: 1) Provide a rapid and sustainable instrument development environment with clear efficient processes and tools, re-usable models and skilled engineers. 2) Provide a capability for quick and efficient trade studies of instrument architectures and concepts. 3) Streamline and optimize instrument systems design for the entire life cycle, including cost and technology assessment. 4) Provide detailed multi-disciplinary modeling and analysis for phase C/D design validation and for operational investigations.

Wood, H. John↗
DOE OSTI2025

Multimetallic Metal-Organic Frameworks as Heterogeneous Catalysts for Gas Phase Hydroformylation and Hydrogenation Reactions

This project focused on the development bimetallic metal-organic frameworks (MOFs) as gas phase heterogeneous catalysts for hydrogenation and hydroformylation reactions. MOFs are a new class of hybrid inorganic/organic materials that are highly crystalline, with structures consisting of metal nodes of specific geometries connected by organic linkers. Although there have been a number of studies of catalysis at MOF nodes in solution, there is little experimental data in the literature for gas phase reactions despite the fact that industrial heterogeneous catalysis on MOFs is more economically viable than homogeneous catalysis. The use of MOFs as heterogeneous catalysts presents the unique opportunity to carefully control the composition, geometry and ensemble sizes of the active sites, which are all critical factors for the rational design of new catalysts. Specific objectives of the project are as follows: (1) to tailor the geometry, composition and ensemble size of the active sites; (2) to understand how the adsorption of molecules at metal sites can be modified by interactions with a neighboring metal site; (3) to determine how oxidation states of the metal change during reaction and how these states can be modified by metal-metal electronic interactions; and (4) to elucidate reaction mechanisms and intermediates. For these studies, we have chosen to investigate selective hydrogenation of hydrocarbons and hydroformylation, which are industrially relevant reactions. Our interdisciplinary team of Chen, Shustova and Vogiatzis/Henkelman provides critical expertise in novel MOF synthesis (Shustova), atomic-scale surface science and catalysis (Chen) and computational studies of reaction mechanisms (Vogiatzis/Henkelman) that are necessary for the development of these catalysts. We believe that this work will lead directly to the rational design of new catalysts that are versatile, highly active/selective and suitable for industrial processes.

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

Colloidal quantum dots for optoelectronics

Colloidal quantum dots (QDs) are semiconductor nanocrystals that have unique size-tunable optoelectronic properties and are suitable for wet processing. QD research aims to answer fundamental questions about the chemical and physical properties of nanoscale materials and use these tools for technological applications ranging from bio-imaging to quantum optics. At the core of this field is a set of synthetic, processing and analytical methods designed to produce QDs in uniform ensembles that meet the highest performance standards. Here, this Primer reviews QD fabrication methods with a focus on the applications of QDs in printed optoelectronics and quantum optics. After outlining the current state-of-the-art QD syntheses, the experimental and computational analysis of QDs is discussed. These topics are then connected to the methodologies, processes and concepts required for developing QD-based photodetectors, light-emitting devices and quantum optics applications. Special attention is paid to challenges in reproducibility and current limitations of the field, such as the need to balance non-restricted material composition with high performing technology while achieving long-term stability in QD devices under operating conditions. Finally, the ongoing advancement in QD synthesis, precise atomic-level analysis and computational methodologies are highlighted as key drivers towards rational QD design, particularly in understanding how structural changes under loading impact QD properties.

optical materials↗
DOE OSTI2022

Dilute Alloys Based on Au, Ag, or Cu for Efficient Catalysis: From Synthesis to Active Sites

The development of new catalyst materials for energy-efficient chemical synthesis is critical as over 80% of industrial processes rely on catalysts, with many of the most energy-intensive processes specifically using heterogeneous catalysis. Catalytic performance is a complex interplay of phenomena involving temperature, pressure, gas composition, surface composition and structure over multiple length and time scales. In response to this complexity, the integrated approach to heterogeneous dilute-alloy catalysis reviewed here brings together materials synthesis, mechanistic surface chemistry, reaction kinetics, in-situ and operando characterization, and theoretical calculations in a coordinated effort to develop design principles to predict and improve catalytic selectivity. Dilute alloy catalysts—in which isolated atoms or small ensembles of the minority metal on the host metal lead to enhanced reactivity while retaining selectivity—are particularly promising as selective catalysts. Several dilute alloy materials using Au, Ag and Cu as the majority host element, including more recently introduced support-free nanoporous metals and oxide-supported nanoparticle "raspberry colloid templated (RCT)" materials, are reviewed for selective oxidation and hydrogenation reactions. Progress in understanding how such dilute alloy catalysts can be used to enhance selectivity of key synthetic reactions is reviewed, including quantitative scaling from model studies to catalytic conditions. The dynamic evolution of catalyst structure and composition studied in surface science and catalytic conditions and their relationship to catalytic function are also discussed, followed by advanced characterization and theoretical modeling that have been developed to determine the distribution of minority metal atoms at or near the surface. Furthermore, the integrated approach demonstrates the success of bridging the divide between fundamental knowledge and design of catalytic processes in complex catalytic systems, which can accelerate the development of new and efficient catalytic processes.

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

Intrinsically Conductive {pi}‑d Conjugated Layers with Co–N4 Active Sites for Efficient Nitrate Electrocatalysis and Zinc-Nitrate Batteries

Electrochemical synthesis of ammonia from nitrate has been extensively investigated as a potential alternative to the energy-intensive Haber-Bosch process. This approach not only operates under ambient conditions but also simultaneously removes nitrate contaminants while producing ammonia as a value-added product. However, the ongoing quest lies in designing an efficient electrocatalyst that achieves a high ammonia yield rate, high selectivity, and long-term stability. Herein, we report the outstanding performance of a Co–N4 coordinated π-d layered Co3(HITP)2 (HITP = 2,3,6,7,10,11-hexaiminotriphenylene) in nitrate electrocatalysis. The unique combination of abundant Co–N4 active sites and superior electrical conductivity enables significant electrocatalytic activity, delivering a maximum ammonia yield rate of 56.8 mg cm–2 h–1 at −0.8 V vs RHE and a Faradaic efficiency of ∼91% at −0.4 V vs RHE. Mechanistic analysis reveals that alkaline conditions accelerate water dissociation to generate adsorbed hydrogen intermediates (H*), which are utilized by Co–N4 sites to drive the stepwise hydrogenation of nitrate to ammonia while suppressing competing hydrogen evolution reaction (HER) pathways. Furthermore, integration of this catalyst into a zinc-nitrate battery resulted in a maximum power density of 5.3 mW cm–2 and an open-circuit potential of ∼1.45 V. These results highlight the potential of π-d conjugated Co–N4 materials as an efficient catalyst for both environmental remediation and energy conversion.

Namvar, shahrirar↗