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 397 records · Page 22

Solar PV on U.S. Houses of Worship: Overview of Market Activity and Trends [Slides]

Rooftop solar photovoltaic systems on houses of worship can provide unique community benefits and can raise local awareness and acceptance of solar energy. Recognizing that potential, a stakeholder team selected under DOE’s Solar Energy Innovation Network is working to develop a scalable model for recruiting and installing solar PV on houses of worship in underserved communities. Berkeley Lab is providing analytical support to this stakeholder team through several work products, including this report, which provides a data-oriented overview of market activity and trends related to solar PV installations on U.S. houses of worship (HoW). Drawing on Berkeley Lab’s project-level dataset of U.S. solar PV installations, the report describes: -market size and growth trends for PV on HoW -demographic characteristics of the communities in which HoW with PV are located, including income, race and ethnicity, and educational levels -key characteristics of the PV systems installed on HoW, including system size, installed costs, prevalence of third-party ownership, and pairing with storage -characteristics of the installer network servicing PV installations on HoW The purpose of the market overview is to inform business development and policy-making efforts aimed at supporting solar adoption by HoW.

14 SOLAR ENERGY↗

Enhanced convection for higher module and system efficiency (Final Technical Report)

The goal of this work is to develop new solar photovoltaic (PV) modules and solar system-scale designs that promote an increase of the convective heat transfer coefficient of at least 40%, reducing the operating temperature of the solar PV panels, and leading to a boost on the annual energy yield by at least 5%. By achieving this goal, we further foresee decreasing solar panel degradation by +0.3%/year, reducing the LCOE by 2.9-4.5¢/kWh. Currently, this question and/or approach is not considered though it is a relevant factor in performance/efficiency. The technology proposed will be at a mature stage by the end of the project and could be aligned to be proven on a full-field test. PV users, installers and manufacturers will be interested in the technology due to the aforementioned benefits. The work was conducted through a suite of wind tunnel experiments, numerical simulations and field experiments. These were then evaluated through a correlation encompassing the entire data set and implementing findings into NREL SAM. The work resulted in eight peer reviewed publications with three others in preparation. The key results of the project are 1.) Showing the capability of increasing the solar farm power production by increasing the heat transfer coefficient; 2.) Providing strategies for achieving this through large scale arrangement manipulation (heights, spacings, angles), flow deflectors and vortex generators; 3.) Demonstrating scalability of results by comparing numerical simulations, wind tunnel experiments and field experiments; 4.) Providing a correlation to be able to capture the various arrangements while exploiting the heat transfer coefficient; and 5.) Proving the feasibility of such strategies and their capacity through a comprehensive techno-economic analysis. For the heat transfer coefficients, gains of 40% were attained and increases in power in the excess of 5% were observed. For heat mitigation strategies, consideration at the PV array scale were inter-panel spacing, panel height and panel angles while at the module level, wind breaks such as solid walls and selected gaps were evaluated as well as vortex generators on the panel. All proposed strategies saw an increase in heat transfer coefficient. For scalability, results were compared against field experiments and a correlation for the heat transfer quantity was attained leading to a parametric understanding of the variations and impact in the heat transfer coefficient independent of tools implemented (wind tunnel/numerical simulations). The strategies were also further assessed by a technoeconomic analysis finding improvements based on LCOE with respect to location (several states with varies atmospheric conditions/geographic locations) yielded different results. Improvements on this end were also observed especially towards the colder climates and when considering bi-facial modules. The quantitative demonstrations of such conclusions are provided in the main portion of this document with complementary results and their narration. Milestones and go/no-go points were successfully met in the project.

14 SOLAR ENERGY↗

BETO 2021 Peer Review - FCIC Task 5 - Preprocessing

In the study of feedstock variability, this presentation specifically looks at preprocessing processes that will created well-defined and homogenous feedstock from variable biomass resources, in the quest to produce homogeneous intermediates that will be converted into market-ready products. The objective of this stage of the project is to develop science-based design and operation principles informed by TEA/LCA that result in predictable, reliable, and scalable performance of preprocessing unit operations (comminution, fractionation, deconstruction, and real-time imaging).

biomass↗

Towards Enhancing Coding Productivity for GPU Programming Using Static Graphs

The main contribution of this work is to increase the coding productivity of GPU programming by using the concept of Static Graphs. GPU capabilities have been increasing significantly in terms of performance and memory capacity. However, there are still some problems in terms of scalability and limitations to the amount of work that a GPU can perform at a time. To minimize the overhead associated with the launch of GPU kernels, as well as to maximize the use of GPU capacity, we have combined the new CUDA Graph API with the CUDA programming model (including CUDA math libraries) and the OpenACC programming model. We use as test cases two different, well-known and widely used problems in HPC and AI: the Conjugate Gradient method and the Particle Swarm Optimization. In the first test case (Conjugate Gradient) we focus on the integration of Static Graphs with CUDA. In this case, we are able to significantly outperform the NVIDIA reference code, reaching an acceleration of up to 11x thanks to a better implementation, which can benefit from the new CUDA Graph capabilities. In the second test case (Particle Swarm Optimization), we complement the OpenACC functionality with the use of CUDA Graph, achieving again accelerations of up to one order of magnitude, with average speedups ranging from 2x to 4x, and performance very close to a reference and optimized CUDA code. Our main target is to achieve a higher coding productivity model for GPU programming by using Static Graphs, which provides, in a very transparent way, a better exploitation of the GPU capacity. The combination of using Static Graphs with two of the current most important GPU programming models (CUDA and OpenACC) is able to reduce considerably the execution time w.r.t. the use of CUDA and OpenACC only, achieving accelerations of up to more than one order of magnitude. Finally, we propose an interface to incorporate the concept of Static Graphs into the OpenACC Specifications.

58 GEOSCIENCES↗

Magnesium‐Mediated Electrochemical Synthesis of Ammonia

Metal-mediated electrochemical synthesis of ammonia (NH3) is a promising method to activate N2 at room temperature. While a Li-mediated approach has been optimized to produce NH3 at high current density and selectivity, Li's scarcity and its highly negative plating potential limit scalability and energy efficiency. Alternative mediators have been proposed, but only Ca has shown some promise, achieving ≈50% Faradaic efficiency (FE), though requiring voltages beyond -3 V. Here, we report a Mg-mediated nitrogen reduction reaction (Mg-NRR), where N2 is activated on Mg to form Mg3N2, followed by protolysis to release NH3 and regenerate Mg. A notable NH3 FE of 25.28 ± 3.80% is achieved at a current density of -45 mA cm-2, corresponding to an NH3 partial current density of -11.30 ± 1.77 mA cm-2 under 6 bar N2. Isotope-labeled experiments confirm that NH3 originates from N2, with similar FE (25.15 ± 1.01%). Importantly, NH3 production is demonstrated at a total cell potential as low as -3 V. This Li-free Mg-NRR system offers key advantages, including lower energy input and use of earth-abundant materials, making it a scalable route for sustainable NH3 synthesis.

Goyal, Ishita↗

A scalable and autoclavable oxygen nanosensor platform for metabolic monitoring of Saccharomyces cerevisiae in a bioreactor and other in situ systems

Polymer-encapsulated dye nanoparticle sensors are a valuable approach to achieving in situ analyte measurements with luminescence; however, typical emulsion-based nanosensors are poorly suited for large-scale biological samples due to limitations of synthesis scalability and stability. Branched polyethylenimine (PEI) is a versatile polymer scaffold ideal for constructing nanoparticles with various covalently conjugated moieties due to their high density of reactive primary amines, high water solubility, and biological stability. In this work, we used branched polyethylenimine as a scaffold-based approach for making a stable and scalable ratiometric oxygen sensor. Pt (II) tetracarboxyporphine was used as an oxygen-sensing dye and coumarin 343 as a reference dye, all covalently linked to the PEI scaffold producing a product that could withstand sterilization procedures and easily be scaled. To minimize toxicity from the PEI scaffold, we conjugated it with 2000 MW PEG. The applicability of the sensors was demonstrated in a 200 mL Saccharomyces cerevisiae yeast culture, using orthogonal luminescent and electrochemical oxygen measurements to validate sensor response and measure the metabolic activity of the yeast in our culture. Further, this approach was able to match the sensitivity of our electrochemical measurements while improving upon drawbacks of other luminescent methods of oxygen detection, demonstrating effective monitoring for at least 20 h. Our scaffold-based approach is a modular and easily translatable technology that could be useful in various biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗

Near-Critical CO 2 -Assisted Liquefaction-Extraction of Biomass and Wastes to Fuels and Value-Added Products

With the growing need for sustainable carbon-neutral liquid fuels, low-grade feedstocks, such as lignocellulosic biomass, and municipal solid wastes offer sufficient potential via thermochemical conversion. But the existing thermochemical means are limited in feed flexibility and scalability and require significant processing (energy and costs) of the intermediates. Bio-oil/biocrude intermediate from fast pyrolysis and hydrothermal techniques is impeded by issues of stability and oxygen content, along with hydrotreating viability. To address these issues, we investigated a novel pathway of near-critical CO 2 -assisted integrated liquefaction-extraction (NILE) technology in conceptual aspects for conversion of various biomass and municipal solid wastes into high-quality biocrude with high compatibility for co-hydrotreating with traditional fossil crude for liquid fuel needs in power and transportation sectors. Using supercritical CO 2 for dewatering wet feedstocks, for liquefaction, and extraction for lighter biocrude has produced biocrude with lower oxygen content by 50%, lowered metal content by 90%, stable viscosity, low acidity, and good aging stability compared to that produced from hydrothermal liquefaction along with higher hydrotreating and co-hydrotreating compatibility. Hydrotreating of the biocrude extract from supercritical CO 2 extraction also was feasible with no detected coke deposition, an oxygen content of 1%, and catalyst deactivation. Here, the validation and capabilities of the NILE concept urge for its further development to obtain sustainable liquid fuels with lower greenhouse gas emissions and costs.

09 BIOMASS FUELS↗

Growth rate as a link between microbial diversity and soil biogeochemistry

The growth rate of a microorganism is a simple yet profound way to quantify its impact on the world. The absolute growth rate of a microbial population reflects rates of resource assimilation, biomass production, and element transformation, some of the many ways that organisms affect Earth’s ecosystems and climate. Microbial fitness in the environment depends on the ability to reproduce quickly when conditions are favorable and adopt a survival physiology when conditions worsen, which cells coordinate by adjusting their relative growth rate. At the population level, relative growth rate is a sensitive metric of fitness, linking survival and reproduction to the ecology and evolution of populations. Techniques combining ‘omics and stable isotope probing enable sensitive measurements of growth rates of microbial assemblages and individual taxa in soil. Microbial ecologists can explore how the growth rates of taxa with known traits and evolutionary histories respond to changes in resource availability, environmental conditions, and interactions with other organisms. We anticipate that quantitative and scalable data on the growth rates of soil microorganisms, coupled with measurements of biogeochemical fluxes, will allow scientists to test and refine ecological theory and advance process-based models of carbon flux, nutrient uptake, and ecosystem productivity. Finally, measurements of in situ microbial growth rates provide insights into the ecology of populations and can be used to quantitatively link microbial diversity to soil biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗

Landfilled coal ash for carbon dioxide capture and its potential as a geopolymer binder for hazardous waste remediation

In this report, the legacy of global fossil fuel usage is not just the increase in global warming due to CO 2 production, but also the billions of tons of toxic coal ash disposed in landfills. This investigation evaluates the merits of using high-calcium landfilled coal fly ash of different disposal durations and granulated blast furnace (GBF) slag as primary raw materials for production of a new class of geopolymer binder. Processing of landfilled coal fly ash, GBF slag and supplementary raw materials into a geopolymer binder was accomplished by a simple, scalable milling process in the absence of heating under a carbon dioxide environment. The resultant geopolymer cement binders were tested for carbon dioxide uptake, compressive strength, and heavy metal stabilization. The geopolymer binder demonstrated a desired balance of carbon dioxide uptake, strength and safety. These results also indicate that the performance of the geopolymer binder depends on the landfill disposal age of the coal fly ash.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Sustainable Seaweed Biotechnology Solutions for Carbon Capture, Composition, and Deconstruction

Seaweeds or macroalgae are attractive candidates for carbon capture, while also supplying a sustainable photosynthetic bioenergy feedstock, thanks to their cultivation potential in offshore marine farms. Seaweed cultivation requires minimal external nutrient requirements and allows for year-round production of biomass. Despite this potential, there remain significant challenges associated with realizing large-scale, sustainable agronomics, as well as in the development of an efficient biomass deconstruction and conversion platform to fuels and products. Recent biotechnology progress in the identification of enzymatic deconstruction pathways, tailored to complex polymers in seaweeds, opens up opportunities for more complete utilization of seaweed biomass components. Effective, scalable, and economically viable conversion processes tailored to seaweed are discussed and gaps are identified for yield and efficiency improvements.

59 BASIC BIOLOGICAL SCIENCES↗

Efficient Low-Temperature Direct Lithium Extraction from Chloride Brines Enabled by High-Capacity Sorbent

The demand for lithium, a key component in rechargeable batteries for electric vehicles and renewable energy storage systems, has surged in recent years. Meeting this demand requires efficient extraction methods that are both environmentally friendly and economically viable. This study investigates the utilization of the high-capacity sorbent amorphous aluminum hydroxide for enabling efficient direct lithium extraction at low temperatures. Traditional extraction methods often involve acid-leaching and energy-intensive processes that are not only expensive but also environmentally taxing. In contrast, our approach leverages the exceptional sorption properties of amorphous aluminum hydroxide to facilitate lithium extraction directly from brine, achieving extraction efficiencies of 94.4% in case 1 and 96.2% in case 2 at low temperatures. Kinetic modeling using the Avrami–Erofe’ev framework reveals a nucleation-growth mechanism ( n = 0.71, k = 0.131 h –1 ), providing quantitative insights into the solid-state phase transformation process. This method significantly reduces energy consumption and minimizes the environmental footprint. Through systematic experimentation and optimization, we demonstrate the effectiveness and scalability of our approach, highlighting its potential to revolutionize lithium extraction processes. Our findings highlight the potential of high-capacity sorbents, particularly amorphous aluminum hydroxide toward sustainable lithium production, contributing to the advancement of clean-energy technologies.

anions↗

A microbial supply chain for production of the anti-cancer drug vinblastine

Monoterpene indole alkaloids (MIAs) are a diverse family of complex plant secondary metabolites with many medicinal properties, including the essential anti-cancer therapeutics vinblastine and vincristine. As MIAs are difficult to chemically synthesize, the world’s supply chain for vinblastine relies on low-yielding extraction and purification of the precursors vindoline and catharanthine from the plant Catharanthus roseus, which is then followed by simple in vitro chemical coupling and reduction to form vinblastine at an industrial scale. Here, we demonstrate the de novo microbial biosynthesis of vindoline and catharanthine using a highly engineered yeast, and in vitro chemical coupling to vinblastine. The study showcases a very long biosynthetic pathway refactored into a microbial cell factory, including 30 enzymatic steps beyond the yeast native metabolites geranyl pyrophosphate and tryptophan to catharanthine and vindoline. In total, 56 genetic edits were performed, including expression of 34 heterologous genes from plants, as well as deletions, knock-downs and overexpression of ten yeast genes to improve precursor supplies towards de novo production of catharanthine and vindoline, from which semisynthesis to vinblastine occurs. As the vinblastine pathway is one of the longest MIA biosynthetic pathways, this study positions yeast as a scalable platform to produce more than 3,000 natural MIAs and a virtually infinite number of new-to-nature analogues.

60 APPLIED LIFE SCIENCES↗

Cyclic olefin copolymer-based reinforced anion exchange membranes for water electrolyzers

Anion exchange membranes (AEMs) have emerged as a promising technology for water electrolysis in hydrogen production since they offer significant cost reduction in choices of electrocatalysts and bipolar plates. However, AEMs satisfying multiple requirements of high ionic conductivity, good chemical stability, robust mechanical properties, scalable synthesis, and low manufacturing costs are rare. Herein, we introduce quaternary ammonium functionalized cyclic olefin copolymers (COCs) as a new class of chemically stable and low-cost AEM materials. To further enhance the mechanical robustness, we prepared reinforced composite AEMs by impregnating the ionically functionalized COC into a mechanically robust matrix. The resulting reinforced composite membrane exhibits a high hydroxide conductivity of 127 mS cm −1 and excellent mechanical strength. In water electrolyzers, the MEA demonstrated outstanding performance, achieving a current density of 2.24 A cm −2 at 1.8 V, attributable to high conductivity, enhanced mechanical properties, and good alkaline stability of the composite membrane. These results indicate that the COC-based AEMs demonstrate good potential for application in AEM electrolyzers.

08 HYDROGEN↗

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

99 GENERAL AND MISCELLANEOUS↗

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $\$$200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

17 WIND ENERGY↗

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗

GR-Athena++: Puncture Evolutions on Vertex-centered Oct-tree Adaptive Mesh Refinement

Numerical relativity is central to the investigation of astrophysical sources in the dynamical and strong-field gravity regime, such as binary black hole and neutron star coalescences. Current challenges set by gravitational-wave and multimessenger astronomy call for highly performant and scalable codes on modern massively parallel architectures. We present GR-Athena++, a general-relativistic, high-order, vertex-centered solver that extends the oct-tree, adaptive mesh refinement capabilities of the astrophysical (radiation) magnetohydrodynamics code Athena++. To simulate dynamical spacetimes, GR-Athena++ uses the Z4c evolution scheme of numerical relativity coupled to the moving puncture gauge. We demonstrate stable and accurate binary black hole merger evolutions via extensive convergence testing, cross-code validation, and verification against state-of-the-art effective-one-body waveforms. GR-Athena++ leverages the task-based parallelism paradigm of Athena++ to achieve excellent scalability. We measure strong-scaling efficiencies above 95% for up to ~1.2 × 10 4 CPUs and excellent weak scaling is shown up to ~10 5 CPUs in a production binary black hole setup with adaptive mesh refinement. GR-Athena++ thus allows for the robust simulation of compact binary coalescences and offers a viable path toward numerical relativity at exascale.

79 ASTRONOMY AND ASTROPHYSICS↗