Search NASA⌕ Search

SEARCH · Search NASA

Results for “scalable production”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Scalable, Infiltration-Free Ceramic Matrix Composite (SIF-CMC) manufacturing for Molten Salt Receiver: Investigation of particle-loaded preceramic resin

Due to their unique combination of high temperature, corrosion resistance, and toughness, Ceramic Matrix Composites (CMC) are the optimal materials to be used in the next generation of Concentrated Solar Power (CSP), which will operate at working temperatures up to 800 °C. However, today, CMC is too costly to be used in CSP applications due to its complex manufacturing process based on repeated infiltration-pyrolysis cycles. To solve this issue, PARC is developing a scalable, infiltration-free method (SIF) to manufacture CMC, which can reduce the production cost, increase batch consistency, and leverage all of the intrinsic advantages of current CMCs. The key to the SIF method is using a flowable preceramic resin with high loading of functional components. The formulation impregnates the fiber during curing and leads to high-density, low-shrinkage parts upon pyrolysis. In this paper, we demonstrate a proof-of-concept of the SIF process and report the relationships between key process parameters in the manufacturing process: functional material loading in the resin vs. resin’s flowability and morphology changes upon pyrolysis.

ceramic matrix composite, concentrated solar power↗
DOE OSTI2020

Potential for Applying Continuous Directed Evolution to Plant Enzymes: An Exploratory Study

Plant evolution has produced enzymes that may not be optimal for maximizing yield and quality in today’s agricultural environments and plant biotechnology applications. By improving enzyme performance, it should be possible to alleviate constraints on yield and quality currently imposed by kinetic properties or enzyme instability. Enzymes can be optimized more quickly than naturally possible by applying directed evolution, which entails mutating a target gene in vitro and screening or selecting the mutated gene products for the desired characteristics. Continuous directed evolution is a more efficient and scalable version that accomplishes the mutagenesis and selection steps simultaneously in vivo via error-prone replication of the target gene and coupling of the host cell’s growth rate to the target gene’s function. However, published continuous systems require custom plasmid assembly, and convenient multipurpose platforms are not available. We discuss two systems suitable for continuous directed evolution of enzymes, OrthoRep in Saccharomyces cerevisiae and EvolvR in Escherichia coli, and our pilot efforts to adapt each system for high-throughput plant enzyme engineering. To test our modified systems, we used the thiamin synthesis enzyme THI4, previously identified as a prime candidate for improvement. Our adapted OrthoRep system shows promise for efficient plant enzyme engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Electrodeposited Sn–Cu@Sn dendrites for selective electrochemical CO 2 reduction to formic acid

Large-scale CO 2 electrolysis can be applied to store renewable energy in chemicals. Recent developments in gas diffusion electrodes now enable a commercially relevant current density. However, the low selectivity of the CO 2 reduction reaction (CO 2 RR) still hinders practical applications. The selectivity of the CO 2 RR highly depends on the electrocatalyst. Sn catalysts are considered promising cathode materials for the production of formic acid. The selectivity of Sn catalysts can be regulated by controlling their morphology or alloying them with secondary metals. In this work, we enhanced the selectivity of CO 2 reduction to formic acid by synthesizing Sn–Cu@Sn dendrites that have a core@shell architecture. The Sn–Cu@Sn dendrites were prepared by a scalable electro-deposition method. The electronic structure was modified to suppress a reaction pathway for CO production on the Sn surface. Notably, the Sn shell inhibited the cathodic corrosion of Cu during the CO 2 RR. On a gas diffusion electrode, the Sn–Cu@Sn dendrites exhibited 84.2% faraday efficiency to formic acid for 120 h with high stability.

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

Synthesis of platinum nanoparticles on strontium titanate nanocuboids via surface organometallic grafting for the catalytic hydrogenolysis of plastic waste

Pt/SrTiO 3 (Pt/STO), prepared on small scale by atomic layer deposition (ALD), is a capable heterogeneous catalyst for the selective hydrogenolysis of polyolefins to hydrocarbon oils, providing a promising approach for upcycling plastic waste. However, because deposition by ALD is costly and resource-intensive, a new synthesis of Pt/STO is needed to effectively scale catalyst production and pursue the commercialization of upcycling processes. To that effect, this work details a scalable deposition method for Pt/STO made by surface organometallic chemistry (SOMC) techniques using Pt(II) acetylacetonate or and trimethyl(methylcyclopentadienyl)platinum. The STO support was calcined (550 °C), treated with ozone (200 °C), and finally steamed (200 °C) to afford a clean STO surface populated with only hydroxyl groups. Pt precursors were dissolved in toluene and deposited onto STO. After reduction at 300 °C, the STO support was decorated with 1.0–1.5 nm Pt nanoparticles. The size and loading of these nanoparticles were varied by employing a multi-cycle deposition and oxidation and/or reduction process designed to ALD techniques. In conclusion, these Pt/STO catalysts hydrogenolyzed isotactic polypropylene into liquid products (>95% yield) with average molecular weights of 200–300 Da (~25 carbon atoms) and narrow size distributions at 300 °C and 180 psi H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An Integrated Indexing and Search Service for Distributed File Systems

Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases and indexing services. However, modern data production rates, looming data movement costs, and the lack of metadata, entail revisiting the decoupled file system-data services design philosophy. In this article, we present TagIt, a scalable data management service framework aimed at scientific datasets, which can be integrated into prevalent distributed file system architectures. A key feature of TagIt is a scalable, distributed metadata indexing framework, which facilitates a flexible tagging capability to support data discovery. Furthermore, the tags can also be associated with an active operator, for pre-processing, filtering, or automatic metadata extraction, which we seamlessly offload to file servers in a load-aware fashion. We have integrated TagIt into two popular distributed file systems, i.e., GlusterFS and CephFS. Our evaluation demonstrates that TagIt can expedite data search operation by up to 10× over the extant decoupled approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Scalable Gas Diffusion Electrode Fabrication for Electrochemical CO 2 Reduction Using Physical Vapor Deposition Methods

Electrochemical CO 2 reduction (ECR) promises the replacement of fossil fuels as the source of feedstock chemicals and seasonal storage of renewable energy. While much progress has been made in catalyst development and electrochemical reactor design, few studies have addressed the effect of catalyst integration on device performance. Using a microfluidic gas diffusion electrolyzer, we systematically studied the effect of thickness and the morphology of electron beam (EB) and magnetron-sputtered (MS) Cu catalyst coatings on ECR performance. We observed that EB-Cu outperforms MS-Cu in current density, selectivity, and energy efficiency, with 400 nm thick catalyst coatings performing the best. Additionally, the superior performance of EB-Cu catalysts is assigned to their faceted surface morphology and sharper Cu/gas diffusion layer interface, which increases their hydrophobicity. Tests in a large-scale zero-gap electrolyzer yielded similar product selectivity distributions with an ethylene Faradaic efficiency of 39% at 200 mA/cm 2 , demonstrating the scalability for industrial ECR applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Non‐Equilibrium Synthesis Methods to Create Metastable and High‐Entropy Nanomaterials

Stabilizing multiple elements within a single phase enables the creation of advanced materials with exceptional properties arising from their complex composition. However, under equilibrium conditions, the Hume–Rothery rules impose strict limitations on solid-state miscibility, restricting combinations of elements with mismatched crystal structures, atomic radii, valence states, or electronegativities. This severely narrows the accessible compositional space for creating new inorganic materials. In this review, we highlight how non-equilibrium synthesis methods, featuring ultrafast heating and quenching, can overcome these thermodynamic barriers, enabling integration of immiscible elements into metastable and high-entropy nanostructures. The resulting materials benefit from both kinetic trapping and stabilization by high configurational entropy, leading to enhanced phase stability. These materials can exhibit unique structural and functional properties that are needed for advancing catalysis, energy storage, thermoelectrics, and sensing. Furthermore, the ability of non-equilibrium methods to generate unconventional compositions and structures expands the material design space dramatically, offering rich datasets for AI-guided materials discovery. When combined with their inherent high-throughput and scalable characteristics, these approaches enable rapid, iterative optimization and accelerate the development and industrial production of next-generation inorganic materials.

high-entropy materials↗
DOE OSTI2020

Facile and scalable dry surface doping technique to enhance the electrochemical performance of LiNi 0.64 Mn 0.2 Co 0.16 O 2 cathode materials

Lithium nickel manganese cobalt oxide (NMC) is one of the dominant cathode materials in lithium-ion batteries. In this study a simple, efficient and scalable surface doping technique is successfully demonstrated, which can be readily used in mass production of cathode materials. For the first time neodymium oxide (Nd 2 O 3 ) has been employed as the surface doping agent. The Nd-doped NMC shows greatly improved cycling and rate performance, and the enhanced cycling stability has been demonstrated in full pouch cells, with a 17.5% increase in capacity retention after 300 cycles. Fewer cracks have been observed in the doped NMC after cycling, and in situ X-ray diffraction reveals the suppressed lattice collapse by Nd doping. Greatly suppressed surface phase change has been confirmed by HR-TEM and EELS. The result suggests great promise in using this dry doping technique to enhance the electrochemical performance of NMC cathodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Particle Mass Flow Control and Measurement for High-Temperature Particle Receivers

This work is developing particle flow control and measurement methods for next-generation concentrating solar power systems employing particle-based technologies. Particle receivers are being pursued to provide substantial performance improvements through higher temperatures (>700 °C) for more efficient and cost-effective CSP systems with direct storage for electricity generation, process heating, thermochemistry, and solar fuels production. This specific work will develop technologies that enable more efficient particle receivers and scalable methods to accommodate variable irradiances during commercial on-sun operation. The development of next-generation particle-receiver systems and methods with potentially high consequences for improved performance and cost savings for CSP applications is an appropriate role for the government.

14 SOLAR ENERGY↗
DOE OSTI2023

CO 2 electroreduction favors carbon isotope 12 C over 13 C and facilitates isotope separation

We discovered that CO 2 electroreduction strongly favors the conversion of the dominant isotope of carbon ( 12 C) and discriminates against the less abundant, stable carbon 13 C isotope. Both absorption of CO 2 in the alkaline electrolyte and CO 2 electrochemical reduction favor the lighter isotopologue. As a result, the stream of unreacted CO 2 leaving the electrolyzer has an increased 13 C content, and the depletion of 13 C in the product is several times greater than that of photosynthesis. Using a natural abundance feed, we demonstrate enriching of the 13 C fraction to ~1.3% (i.e., +18%) in a single-pass reactor and propose a scalable and economically attractive process to yield isotopes of a commercial purity. Our finding opens pathways to both cheaper and less energy-intensive production of stable isotopes ( 13 C, 15 N) essential to the healthcare and chemistry research, and to an economically viable, disruptive application of electrolysis technologies developed in the context of sustainability transition.

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

Separations Consortium: Counter Current Chromatography

In support of the Bioenergy Technologies Office in recovering coproducts in biorefineries this project evaluates the use of Counter Current Chromatography (CCC) in recovering co-products from Reductive Catalytic Fractionation (RCF) oil, Alkaline Pretreatment Liquor (APL), aqueous phase Hydrothermal Liquefaction (HTL) oil, and Catalytic Fast Pyrolysis (CFP) oil. The project addresses three technology barriers in developing the bioeconomy; (1) Cost of production (2) Selective separation of organic acid species, and (3) Advanced bioprocess development. CCC is a unique, scalable, chromatographic technology that operates with two immiscible liquid phases moving counter current to one another. Unlike Simulated Moving Bed (SMB) technology, CCC is a true moving bed and because it uses liquids as both the stationary and mobile phase it can handle solids directly in the feed. This aspect of CCC allows it to skip the expensive filtration step needed prior to traditional SMB, furthermore the liquid phases are composed on relatively inexpensive organics (e.g. hexane and ethyl acetate). This project develops CCC methods for direct isolation of co-products from RCF oil, APL, HTL aqueous, and CFP oil. TechnoEconomic Analysis and process modeling is presented to compare CCC to SMB and assess its applicability in a holistic biorefinery. Initial results indicate approximately 4x reductions in solvent demand and 2x reduction in energy consumption compared to SMB.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1- 13 C]Pyruvate

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1- 13 C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker’s yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1- 13 C]pyruvate into oxidative decarboxylation products CO 2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO 2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1- 13 C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.

fungi↗
DOE OSTI2020

Stabilization of Uranium Metal by Chloride Conversion-Economical, Safe, Scalable [Factsheet]

Researchers at Los Alamos National Laboratory have developed SUCCESS, a process to convert uranium metal to uranium tetrachloride enabling production of these valuable compounds for actinide science, molten salt nuclear reactors, and energy research. Conventional methods are problematic due to the oxide reduction processes use rare reagents and generate significant amounts of waste and hydride conversion process using chlorine at high temperature is hazardous. This new method using inexpensive reagents chemically transform uranium metal into uranium halide compounds under mild conditions. The facile conversion to stable uranium tetrachloride could reduce the need to mine uranium for uses other than nuclear, by recycling the uranium without oxidation. The Laboratory is interested in supporting further scale-up efforts using a Cooperative Research and Development Agreement (CRADA) or by granting a license to a qualified entity

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Two-dimensional forms of robust CO 2 reduction photocatalysts

Photoelectrocatalysts that use sunlight to power the CO 2 reduction reaction will be crucial for carbon-neutral power and energy-efficient industrial processes. Scalable photoelectrocatalysts must satisfy a stringent set of criteria, such as stability under operating conditions, product selectivity, and efficient light absorption. Two-dimensional materials can offer high specific surface area, tunability, and potential for heterostructuring, providing a fresh landscape of candidate catalysts. From a set of promising bulk CO 2 reduction photoelectrocatalysts, we screen for candidate monolayers of these materials, then study their catalytic feasibility and suitability. For stable monolayer candidates, we verify the presence of visible-light band gaps, check that band edges can support CO 2 reduction, determine exciton binding energies, and compute surface reactivity. We find visible light absorption for SiAs, ZnTe, and ZnSe monolayers, and that due to a lack of binding, CO selectivity is possible. We thus identify SiAs, ZnTe, and ZnSe monolayers as targets for further investigation, expanding the chemical space for CO 2 photoreduction candidates.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-Current Light-Ion Cyclotron for Applications in Nuclear Security and Radioisotope Production

In this article, we propose the conceptual design, with supporting beam dynamics results, of a normal conducting, separated-sector cyclotron with a strong-focusing field gradient designed to accelerate light ions with a charge-to-mass ratio of 1/2 up to 15–20 MeV/u. The design can support a host of applications for therapy, radiobiology, material science, and instrumentation development. The light-ion species, which can include a mixed ion beam, can be dynamically chosen to provide a range of characteristic signals appropriate for specific material identification such as special nuclear materials. A conservative baseline concept is presented which has been optimized for radioisotope production of alpha emitters and theranostic radiopharmaceuticals. The modular design is also demonstrated to be scalable in gross physical parameters by a factor of 2–3, thereby reducing the size, weight, and power requirements (SWaP) and enabling near-term security applications.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Towards Superior Software Portability with SHAD and HPX C++ Libraries

As hardware architectures and software stacks complexity grows, development productivity, performance and software portability, quickly evolve from desirable features to actual needs. SHAD, the Scalable High-performance Algorithms and Data-structures C++ library is designed to mitigate these issues: it provides general purpose building blocks as well as high-level custom utilities, and offers a shared-memory programming abstraction which facilitates the programming of complex systems, scaling up to High Performance Computing clusters. SHAD’s portability is achieved through an abstract runtime interface, which decouples the upper layers of the library and hides the low level details of the underlying architecture. This layer enables SHAD to interface with different runtime/threading systems, e.g. Intel TBB and Global Memory and Threading (GMT). However, current backends targeting distributed systems, rely on a centralized controller which may possibly limit scalability up to hundreds of nodes and creates a network hot spot due to all to one communication for synchronization, and possibly resulting in degraded performance at high process counts. In this research, we explore HPX, the C++ standard library for parallelism and concurrency, as an additional backend in support of the SHAD library, and present the methodologies in support of local and remote task executions in SHAD with respect to HPX. Finally, we evaluate the proposed system by comparing against existing backends of SHAD and analyzing their performance on C++ Standard Template Library algorithms.

Wu, Nanmiao↗
DOE OSTI2020

Functional Lithography for Advanced Additive Manufacturing

The viability of 3D printing as a manufacturing technology is limited by the material properties of the printed parts. polySpectra successfully developed a scalable, efficient, and economic print process using commercially available hardware in order to 3D print production parts using novel functional lithography resins. The printed parts exhibited unmatched physical and chemical properties. The combination of the novel resin with unique properties and a facile, economic print process will help elevate additive manufacturing from a prototyping tool to a viable manufacturing technology.

42 ENGINEERING↗
DOE OSTI2026

Satellite Embedding-Based Population Imputation for Areas with Missing Building Footprint Data: A Computer Vision-Based Approach

High-resolution population modeling is important for supporting effective decision-making across diverse sectors. LandScan Mosaic generates population estimates at the level of individual buildings and aggregates them to 3 arc-second grids, and this approach performs well in regions where building footprint data are comprehensive and reliable. However, large portions of the globe still suffer from incomplete, sparse, or entirely missing building stock datasets, creating a structural limitation for strictly building-based population models. To address this research gap, this study proposes a computer vision-based framework that employs Google Earth Engine satellite embeddings and UNet, which allows us to directly impute grid-level population estimates in building-data-deficient areas. Applied to Taiwan as a case study, the framework achieved strong predictive performance with R$^{2}$ of 0.89, RMSE of 18.70, and MAE of 8.41, outperforming traditional machine learning approaches. Notably, the proposed framework effectively addressed building false-positive errors inherent in Global Human Settlement Layer (GHSL) data, correctly identifying uninhabited areas that were erroneously classified as populated. The framework also offers significant advantages for global population mapping, particularly in terms of scalability and temporal consistency, thereby extending the coverage and accuracy of high-resolution population products in data-scarce regions worldwide. Urban planners, decision makers, and related stakeholders can obtain granular population distributions to support more accurate and targeted infrastructure investment, service delivery, resource allocation, and risk assessment decisions.

97 MATHEMATICS AND COMPUTING↗