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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 289 records · Page 16

MatRIS: Multi-level Math Library Abstraction for Heterogeneity and Performance Portability using IRIS Runtime

Vendor libraries are tuned for a specific architecture and are not portable to others. Moreover, they lack support for heterogeneity and multi-device orchestration, which is required for efficient use of contemporary HPC and cloud resources. To address these challenges, we introduce MatRIS—a multilevel math library abstraction for scalable and performance-portable sparse/dense BLAS/LAPACK operations using IRIS runtime. The MatRIS-IRIS co-design introduces three levels of abstraction to make the implementation completely architecture agnostic and provide highly productive programming. We demonstrate that MatRIS is portable without any change in source code and can fully utilize multi-device heterogeneous systems by achieving high performance and scalability on Summit, Frontier, and a CADES cloud node equipped with four NVIDIA A100 GPUs and four AMD MI100 GPUs. A detailed performance study is presented in which MatRIS demonstrates multi-device scalability. When compared, MatRIS provides competitive and even better performance than libraries from vendors and other third parties.

Monil, M. A. H.↗

Comprehensive evaluation of commercially scalable atomic-layer-deposited alumina coating impact on full cell battery performance across varied test conditions

Atomic Layer Deposition (ALD) has emerged as a strategic enhancement method for lithium-ion battery (LIB) materials offering potential benefits and durability benefits for industrial battery production. However, the translation from laboratory achievements to commercial-scale applications has been limited. Here, this study aims to bridge this gap by comprehensively evaluating the effects of commercially scalable Al 2 O 3 ALD coatings using full pouch cell performance as a means to assess the ALD impact. We utilized large-scale slot-die coating techniques to ensure consistent electrode quality and tested four configurations of pouch cells to analyze the individual effects of ALD coating on anode and cathode electroactive materials. Our extensive testing matrix included long-term cycling, fast discharge, fast charge, leakage current, and high voltage tests. While at lower C-rates (<~1C), the influence of Al 2 O 3 coatings on cell performance is not significant. Fast charging conditions reveal that the anode ALD coating significantly enhances performance via a passivating effect, while on the cathode, it is detrimental, potentially due to increased resistance of the thin interfacial layer formed during the ALD processing. Leakage current and high-voltage tests show that the application of ALD coatings on either anode or cathode effectively minimizes side reactions at the electrode-electrolyte interface. Additionally, ALD coatings significantly mitigate concentrated and localized lithium plating on the anodes. These insights provide a valuable understanding of the potential of ALD technologies in LIB manufacturing to tailor cell performance, paving the way for safer, more efficient, and cost-effective battery solutions.

25 ENERGY STORAGE↗

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large-scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Autotuning↗

Cascade Dielectrophoretic Separation for Selective Enrichment of Polyhydroxybutyrate (PHB)-Producing Cyanobacterium Synechocystis sp. PCC 6803

Maintaining favorable biological productivities in photosynthetic biomanufacturing systems, especially when the risk of contamination with competing microbes is high, remains a challenge to achieve while maintaining economic feasibility. This study presents a dielectrophoresis (DEP)-based microfluidic approach for isolating a desired strain within a co-culture. The cyanobacterium Synechocystis sp. PCC 6803 (a strain capable of producing the bioplastic precursor polyhydroxybutyrate, or PHB) was enriched from mixed cultures containing the competing cyanobacterium Synechococcus elongatus PCC 7942 (which does not naturally produce PHB). A DEP cascade electrode system was established to increase purification efficiency through sequential enrichment, which leveraged inherent differences in cell morphology and dielectric properties, to achieve the selective separation of these strains under physiological conditions. A substantial increase in the relative abundance of PHB-producing cells was assessed by optical microscopy and flow cytometry characterization, confirming more than five-fold reduction of the Synechococcus fraction in the refined cell mix. The presented electrokinetic platform offers a scalable and effective approach for selectively enhancing desired microbial components within microbial biomanufacturing systems, leading towards improved product yields.

60 APPLIED LIFE SCIENCES↗

A Co-Simulation Framework for Steady-State Analyses of Multiple Droop-based MTdc Grids in Continental-Scale Systems

The growing scale and complexity of planning continental hybrid ac and multi-terminal dc (MTdc) systems require scalable steady-state modeling and analysis approaches not currently available in commercial tools. This paper presents a comprehensive multi-fidelity model-conversion framework that enables the efficient transition of MTdc grid models from production cost modeling (PCM) and approximated ac power flow to detailed ac–MTdc power flow for large-scale planning studies. The core of this framework is a scalable co-simulation approach that, for the first time, enables power flow analysis in continental-scale ac–MTdc systems. It seamlessly couples commercial ac solvers with a detailed MTdc grid model that incorporates droop-based control and current-limiting strategies of multiple meshed MTdc grids. Leveraging this capability, an evaluation framework to systematically assess and compare different MTdc power redispatch strategies under ac and dc contingencies is introduced. The proposed framework and algorithm are evaluated using a combined Western and Eastern Interconnection system with 11 MTdc grids of various sizes, showing a coherent transition from PCM to detailed ac–MTdc power flow and improved system performance in voltage regulation and line overload mitigation following typical contingencies.

Nguyen, Quan H.↗

Electroslag additive manufacturing: A pathway for high throughput near net shape production

Electroslag Additive Manufacturing (ESAM), a new high-throughput additive manufacturing (AM) method that combines Electroslag Strip Cladding (ESC) and wire arc AM (WAAM) is introduced. This combination enables the high deposition rate of ESC (more than 20 kg/h with a 60 mm strip electrode) to benefit from the precise geometric control of WAAM. As a precursor to ESAM, the ESC process is investigated in an AM context independently by evaluating both direct and staggered bead-stacking strategies and analyzing the microstructural and mechanical properties of each. This is followed by an ESAM demonstration producing an annular geometry by pairing ESC with gas tungsten arc welding (GTAW), wherein GTAW is utilized to construct annular walls that are subsequently infilled via ESC. The microstructure and mechanical properties of ESC-only AM are compared with that of the ESAM method and it is shown that printed integral retaining walls do not impact the resulting mechanical properties of ESAM. Furthermore, results indicate that ESAM-produced Alloy 625 parts exhibit tensile properties on par with cast counterparts, supporting the method’s scalability to components exceeding one metric ton, and possibly making ESAM a viable future manufacturing approach for competitive production of large-scale components currently manufactured by casting and forging.

Additive manufacturing↗

Coupling Waste Feedstocks to Microbial Protein Production in a Circular Food System

Global food production is a major contributor to greenhouse gas emissions, water consumption, and land use. As an alternative to conventional agriculture, the production of waste-derived microbial protein (MP) holds promise for reducing environmental impacts. MP can be mass-produced in volumetrically scalable fermentation processes on short time scales, enabling facile scale-up with lower greenhouse gas emissions, land use, and water impacts than animal and, in some cases, plant protein. MP can also be produced from waste feedstocks, diverting waste from landfills or the natural environment. This Perspective explores the availability and suitability of waste feedstocks for MP production, suggesting that MP generated from waste feedstocks in the United States could fulfill twice the current national protein demand. Here, we also discuss the biotechnological and separations processes required to produce food-grade MP for human consumption from waste. Key challenges include MP consistency, consumer and regulatory acceptance, and the process utilities (electricity, heat, and nutrients) that account for up to 85% of MP costs and most environmental impacts, all of which present opportunities for innovation in the microbiology and process design spaces. Overall, this work highlights the potential of MP to contribute to a more circular, resilient, and sustainable food system.

09 BIOMASS FUELS↗

Characterization of a selective, zero power sensor for distributed sensing of hydrogen in energy applications

The use of hydrogen as a clean and renewable energy source is increasing rapidly for both vehicle and stationary applications. There are safety concerns for the locations in which hydrogen is made, used, and transported (i.e., pipelines and tanker trucks). Sensors are needed to comply with safety regulations and to enable a smooth and safe rollout of hydrogen as an alternative energy. However, hydrogen sensors do not yet exist that have the combined features of small size and low power for easy deployment coupled with high-volume manufacturability and low cost. This is necessary to accommodate the emerging fixed and mobile markets while retaining critical metrological metrics, including measurement range, detection limits, selectivity, fast response, stability, and long lifetime. An amperometric gas sensor for hydrogen (AGS) has been developed using an innovative manufacturing method. The sensor was designed using scalable fabrication strategies based on “Printed Electronics” (PE) methodology which are compatible with large-scale production. Prototype sensors were batch fabricated with multiple individual elements on a substrate compatible in size with a standard 8-inch wafer to enable high-volume, low-cost manufacturing, thereby leveraging PE and semiconductor fabrication infrastructure. This novel AGS was instrumented with control circuitry and evaluated for hydrogen detection in the range of 0–5000 ppmv H2 in air. Specific performance evaluations included assessment of the sensor measurement range, repeatability, and selectivity.

08 HYDROGEN↗

Enhancing water and oxygen transport through electrode engineering for AEM water electrolyzers

Anion-exchange membrane water electrolyzers (AEMWEs) can accelerate the deployment of more efficient and affordable hydrogen production solutions. Here, electrode structure is shown to affect water back-diffusion and oxygen transport, which, in return, governs overpotential behaviors in AEMWEs. Measurements indicate that electrode with copious catalytic sites produces water close to the AEM, creating a higher water gradient and driving water back-diffusion, which improves membrane hydration and mass transport. In situ measurement reveals a high pH gradient near the anode surface, which affects anode kinetics. Operando measurement shows reduced oxygen accumulation when decoupling oxygen production and transport on anode. Catalyst ink rheology and stability are tuned with additives to realize scalable fabrication of electrodes with enhanced transport features, allowing AEMWE to operate at 2 A cm−2 for over 1,000+ h at a 2.3 μV h−1 degradation rate. Analysis during and post-durability provides insights into degradation mechanisms. This work demonstrates an electrode design strategy for efficient and durable AEMWEs.

AEM↗

Randomized Algorithms for Symmetric Nonnegative Matrix Factorization

Symmetric Nonnegative Matrix Factorization (SymNMF) is a technique in data analysis and machine learning that approximates a matrix with a product of a nonnegative, low-rank matrix and it transpose. To design faster and more scalable algorithms for SymNMF we develop two randomized algorithms for its computation. The first method uses randomized matrix sketching to compute an initial low-rank approximation to the input matrix and proceeds to uses this as a low-rank input to rapidly compute a SymNMF. The second methods uses randomized leverage score sampling to approximately solve constrained least squares problems. Many successful methods for SymNMF rely on (approximately) solving sequences of constrained least squares problems. Here, we prove theoretically that leverage score sampling can approximately solve constrained least squares problems to e-accuracy. Finally we demonstrate both methods work in practice by applying them to graph clustering tasks on large real world data sets. These experiments show that our methods approximately maintain solution quality and achieve significant speed ups for both large dense and large sparse problems.

97 MATHEMATICS AND COMPUTING↗

otsdaq

otsdaq is a Ready-to-Use data-acquisition (DAQ) solution aimed at scaling down to test-beam, detector development, and other rapid-deployment scenarios; and scaling up through the development cycle to fullscale production and operation. otsdaq uses the artdaq DAQ framework under-the-hood, providing flexibility and scalability to meet evolving DAQ needs. otsdaq provides a library of supported front-end boards and firmware modules which implement a custom UDP protocol. Additionally, an integrated Run Control GUI and readout software are provided, preconfigured to communicate with otsdaq firmware.

Rivera, Ryan [Fermi National Accelerator Laborator↗

Scalable neutral H 2 O 2 electrosynthesis by platinum diphosphide nanocrystals by regulating oxygen reduction reaction pathways

Despite progress in small scale electrocatalytic production of hydrogen peroxide (H 2 O 2 ) using a rotating ring-disk electrode, further work is needed to develop a non-toxic, selective, and stable O 2 -to-H 2 O 2 electrocatalyst for realizing continuous on-site production of neutral hydrogen peroxide. We report ultrasmall and monodisperse colloidal PtP 2 nanocrystals that achieve H 2 O 2 production at near zero-overpotential with near unity H 2 O 2 selectivity at 0.27 V vs. RHE. Density functional theory calculations indicate that P promotes hydrogenation of OOH* to H 2 O 2 by weakening the Pt-OOH* bond and suppressing the dissociative OOH* to O* pathway. Atomic layer deposition of Al 2 O 3 prevents NC aggregation and enables application in a polymer electrolyte membrane fuel cell (PEMFC) with a maximum r(H 2 O 2 ) of 2.26 mmol h -1 cm -2 and a current efficiency of 78.8% even at a high current density of 150 mA cm -2 . Catalyst stability enables an accumulated neutral H 2 O 2 concentration in 600 mL of 3.0 wt% (pH = 6.6).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Industrial Scalable Additives for Enhanced Decomposition of Plastic Waste Through Photocatalysis

Polymer pollution is a dangerous environmental problem that can lead to the spread of toxic chemicals and microplastics throughout aquatic biomes. Commonly littered plastic from consumer goods and products with a limited or single use can be embedded with photocatalysts to avoid an increase in the amount of plastic present in Earth’s bodies of water. In this work, the photocatalyst nanoparticles, less than 100 nm particle size, were integrated into polyethylene terephthalate, high-density polyethylene, low-density polyethylene, and polystyrene and exposed under ultraviolet light over two independent experimental trials examining both the environmental factors impacting decay and the physical parameters required to implement this solution on a large scale. The plastics were chosen due to their prolific use in items such as grocery bags, bottles, and packaging. The first half of the project examined the effects of water and light frequency on polymer decay, and the second half of the project examined photodecomposition of polymer films. We report that low-density and high-density polyethylene films with titanium dioxide decayed approximately 11.7 and 9.6 faster than control samples, respectively. With an estimated price of less than half the cost of a shopping bag for titanium catalyst integration and a retention of the polymer’s tensile strength with a 2 wt% catalyst concentration, photocatalytic decomposition is a feasible, scalable method for the prevention and future reduction of polymer waste from realistic products littered in the environment.

36 MATERIALS SCIENCE↗

Aerogel with Unparalleled Performance and Cost-Effectiveness for All Insulation Needs (CRADA Final Report)

Westwood Aerogel investigated the reproducible production of an ambiently or electromagnetic spectrum assisted drying of extremely porous aerogel materials. Traditional aerogel processing is limited by low throughput and scalability due to supercritical drying. Westwood Aerogel’s advanced manufacturing process enables commercialization and deployment at scale, making aerogel materials more accessible to a range of industries and applications. We focused on shifting from the lab scale environment to manufacturing prototypes. The initial manufacturing model is based on the float glass process, which is the industry standard for glass window production, and the paper drying process. By incorporating an ambient drying process a continuous line model can be used from start to finish. The project team worked to develop a continuous manufacturing system to scale-up and reduce costs while maintaining the lightweight and insulative properties of aerospace-grade aerogel. While aerogels are extremely insulative, lightweight, and thin materials (making them ideal insulators across application spaces), high costs and stagnant innovation have hampered their wider adoption. Traditional manufacturing of aerogel requires supercritical extraction of pore fluid to obtain highly insulating materials, which is an energy intensive batch process and limits aerogel production output. Westwood Aerogel’s proprietary ambient drying process enables the continuous production of highly insulative aerogel materials without the use of supercritical extraction.

36 MATERIALS SCIENCE↗

Development of a scalable, robust electrocatalytic technology for conversion of CO 2 to formic acid via microstructured materials

This project was funded by the Bioenergy Engineering for Product Synthesis (BEEPS) program under the Funding Opportunity Announcement (FOA) DE-FOA-0001916 Topic Area 5 “Rewiring Carbon Utilization”. This FOA sought projects that would electrocatalytically reduce CO 2 to a carbon intermediate and then upconvert to a multi-carbon product or fuel via non-photosynthetic biological system engineering. The project sought to combine the expertise of OCO Chem, whose chief scientist had previously developed an efficient electrocatalytic reactor for conversion of CO 2 to formate with potential to scale, Montana State University investigators who had recently patented a method for laterally grading membranes with the potential of improving reactant distribution and more uniform efficiency across membrane-based reactors, and University of South Florida which had recently discovered a novel C-C bond forming reaction not known to naturally occur in biological systems and which uses C1 substrates and circumvents the central microbial metabolism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shower Reconstruction for Cross-Section Measurements with Photon(s) in the Final State at SBND

The Short-Baseline Near Detector (SBND) is a 112-ton liquid argon time projection chamber operating in the Booster Neutrino Beam at Fermilab as part of the Short-Baseline Neutrino Program. Precise reconstruction of electromagnetic showers from photons and electrons is essential for searches for neutrino oscillations, cross-section measurements, and rare-process studies in liquid argon. In this poster, we present a unified set of SBND analyses enabled by the SPINE (Scalable Particle Imaging with Neural Embeddings) end-to-end machine-learning–based reconstruction framework, highlighting charged-current neutral pion (CC π⁰) production and neutral-current (NC) Δ radiative decay as complementary physics cases. Charged-current π⁰ interactions provide a high-statistics benchmark for validating photon reconstruction, constraining the electromagnetic energy scale, and modeling backgrounds to other cross-section measurements and BSM searches with one or more photons in the final state. We summarize progress toward the ongoing development of a CC π⁰ selection in SBND and, report on the current status of a search for NC resonant Δ production followed by radiative decay (Δ→Nγ) in SBND. This rare process, previously investigated in MicroBooNE, provides a stringent test of photon-only final-state reconstruction and is of interest in the context of the MiniBooNE low-energy excess. Together, these analyses demonstrate how modern machine-learning–based shower reconstruction enables a diverse and scalable physics program at SBND.

Chung, Seokju [Nevis Labs, Columbia U.]↗