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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

"PoliMOR: A Policy Engine \"Made-to-Order\" for Automated and Scalable Data Management in Lustre"

Modern supercomputing systems are increasingly reliant on hierarchical, multi-tiered file and storage system architectures due to cost-performance-capacity trade-offs. Within such multi-tiered systems, data management services are required to maintain healthy utilization, performance, and capacity levels. We present PoliMOR, a pragmatic and reliable policy-driven data management framework. PoliMOR is composed of modular, single-purpose agents that gather file system metadata and enforce policies on storage systems. PoliMOR facilitates automated and scalable data management with customizable agents tailored to HPC facility-specific storage systems and policies. Our evaluations demonstrate the scalability and performance of PoliMOR both by its individual agents and as a collective entity. We believe PoliMOR is widely applicable across HPC facilities with large-scale data management challenges and will garner interest from the HPC community, given its flexible and open-source nature.

George, Anjus↗

Highly Loaded Sulfur Cathode, Coated Separator and Gel Electrolyte for High Rate Li-Sulfur Batteries

As one of DOE Battery 500 Seedling projects, Cornell University and EIC Labs investigated and developed i) highly loaded sulfur cathodes (> 3 mg/cm 2 ), ii) hybrid separators, and iii) gel ceramic electrolytes (GCE) to mitigate the low rate capability, shuttling effect and limited cycle life in high performance Li-Sulfur batteries. Scalable nanomanufacturing processes such as air-controlled electrospray (ACES) and gas-assisted electrospinning (GAES) have been utilized to develop directly deposited electrodes and polymer/ceramic hybrid separators. First, in the development of highly loaded cathodes, alternating layers of sulfur impregnated mesoporous carbon and graphene were fabricated via ACES and the resulting layered cathodes and coated separators exhibit higher capacity and capacity retention (about 1,000 mAh/g capacity with less than 0.02% fade/cycles) than single layer cathode or cathode prepared by conventional slurry cast. Alternating layer approach via ACES has been applied to high loading systems (3 - 5 mg S/cm 2 ), demonstrating the potential to increase sulfur utilization and capacity retention. We have also incorporated iron oxides (Fe 3 O 4 ) into S/mesoporous carbon/graphene cathodes to enhance sulfur utilization and mitigation of polysulfide shuttling. and the effect of Fe 3 O 4 in mesoporous carbon and Gr is highly pronounced at high C rates of 1C and 2C cycling performance. To further improve the cathodes at high rates, graphene nanoribbons (GNR) which can promote ion transport were incorporated in the cathode, resulting in 550 mAh/g at 5C/5C rates. Hybrid Li-ion/Li-S cathodes has also been explored to better engage unreacted polysulfides during charge/discharge. S/LFP hybrid cathodes offer higher sulfur utilization and enhanced rate capability, as well as higher areal loading. This study suggests inclusion of iron phosphide (Fe2P) which can chemically interact with polysulfides can further enhance sulfur utilization and mitigation of soluble polysulfides at high rates. Secondly, in the development of hybrid separators, we first employed graphene coating on the commercial polyolefin separators, which exhibits higher capability, better capacity retention and enhanced rate capability. To improve the rate capability with enhanced safety features such as thermal stability and nonflammability, we developed polymer/ceramic hybrids based on thermally stable polyimide (PI) and room temperature curable ceramic precursors such as organopolysilazane (OPSZ) or polysilsesquioxanes (PSSQ), which exhibit no shrinkages up to 300 ºC and non-flammability. To improve mechanical properties and electrochemical stability, polybenzimidazole (PBI) and alumina have been incorporated in polymer/ceramic hybrid separator, replacing PI and OPSZ/PSSQ, respectively. Finally, the gel ceramic electrolyte (GCE) based on ceramic cross linkers have been applied to make Li-S cells even safer and also to mitigate the polysulfide shuttling further. The resulting gel ceramic electrolyte offers improved capacity retention and rate capability, and also effectively mitigates polysulfide shuttling which was also confirmed by modeling. Inclusion of high ion conducting additives into GCE together with polymer/ceramic hybrid separators exhibit the higher ionic conductivity than liquid electrolyte with commercial polyolefin separator. We demonstrated that the developed highly loaded sulfur cathodes, polymer/ceramic hybrid separators and gel ceramic electrolyte can effectively mitigate the low rate capability, shuttling effect and limited cycle life in high performance Li-Sulfur batteries with improved safety.

25 ENERGY STORAGE↗

Coupled Reactor Multiphysics and Mass Scalability Assessment for Crewed Megawatt-Class NEP System Architectures

Nuclear Electric Propulsion (NEP) is an in-space propulsion technology capable of enabling opposition and conjunction class crewed Mars missions. NEP subsystems include the reactor for heat generation, a power conversion system (PCS), power management and distribution (PMAD), electric propulsion subsystem (EPS), and a primary heat rejection system. Specific mass, or αe (kg / kWe), is a key performance parameter (KPP) of the propulsion system which is directly scalable with the performance and mass estimates for individual components. To inform technology maturation planning, full system and component level parametric modeling is ongoing to explore the design trade space and illustrate the effect of subsystem design choices on the system KPPs. In this study, scaling of high-assay, low-enriched uranium (HALEU) reactor designs is assessed through coupled reactor physics and thermal hydraulics analyses. Scaling analyses evaluate the impact of system performance parameters (power level, interface temperatures) on mass for direct gas cooled, pumped liquid metal, and passively cooled heat pipe reactor concepts. Each concept requires specific geometries and working fluids to reach the performance goals of PCS interface conditions (temperature, pressure, flow rate) and system mass. The reactor assembly includes the active core (fuel, moderator, cladding, working fluid), axial and radial neutron reflectors, control drums, structural support / pressure vessel, and external radiation shielding. Each of these components are parametrically sized based on performance parameters for a megawatt-class power cycle. Results of this scaling analysis increase NEP propulsion system modeling fidelity and ultimately aim to support technology down-selection along with related technology development planning. The reactor and shield αe are a function of several PCS design choices, and reactor scaling with these parameters must be considered to enable an informed decision on reactor geometry and working fluid combination.

Nuclear Electric Propulsion↗

Locality-Aware Scheduling for Scalable Heterogeneous Environments

Heterogeneous computing promise boost performance of scientific applications by allowing massively parallel execution of computational tasks. However, manually managing extremely heterogeneous, multi-device systems is complicated and may result in sub-optimal performance. Specifically, data management is an extremely challenging problem on multi-device systems. In this work, we introduce two locality-aware schedulers for the Minos Computing Library (MCL), an asynchronous, task-based programming model and runtime for extremely heterogeneous systems. The first scheduler implements a pure locality-aware algorithm to maximize data reuse, though it might incur in ”hot-spots” that limit system utilization. The second scheduler mitigates this drawback by dynamically targeting between locality-awareness and system utilization based on the current workload and available computing devices. Our results show that locality-awareness greatly benefit applications that exhibit data reuse, providing up to 6.9x and 7.9x over the original MCL scheduler and equivalent OpenCL implementations, respectively. Moreover, our schedulers introduce negligible overhead compared with the original MCL scheduler and achieve similar performance for applications that don’t benefit from data locality.

Architecture, co-design, Task-based programming mo↗

Performance evaluation of automated data-driven feature extraction and selection methods for practical and scalable building energy consumption prediction models

Here, this study quantifies the impact of automated feature engineering methods (feature extraction and selection) on the quality and accuracy of machine learning models that predict building energy consumption. The case study compares model performance for three main scenarios: baseline (no feature extraction and selection), feature extraction only, and feature extraction combined with feature selection (filter and/or wrapper methods) for fully trained machine learning models for 200 metered/sub-metered energy measurements across 118 real buildings. For consistency, the same machine learning model architecture (a black box deep learning neural network with probabilistic forecast output) was used for all scenarios. Based on results, all feature engineering methods provided noticeable prediction accuracy improvements (e.g., 29%-68% median prediction improvement) compared to baseline scenarios. However, in this application, feature selection methods provide little practical value due to their limited performance gains and high computational cost. Smarter algorithm development supported by better computational environments will be needed before feature selection methods can reliably and efficiently improve predictive model performance.

97 MATHEMATICS AND COMPUTING↗

The relation of scalability and execution time

Scalability has been used extensively as a de facto performance criterion for evaluating parallel algorithms and architectures. However, for many, scalability has theoretical interests only since it does not reveal execution time. In this paper, the relation between scalability and execution time is carefully studied. Results show that the isospeed scalability well characterizes the variation of execution time: smaller scalability leads to larger execution time, the same scalability leads to the same execution time, etc. Three algorithms from scientific computing are implemented on an Intel Paragon and an IBM SP2 parallel computer. Experimental and theoretical results show that scalability is an important, distinct metric for parallel and distributed systems, and may be as important as execution time in a scalable parallel and distributed environment.

Sun, Xian-He↗

Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel

GNU Parallel is a versatile and powerful tool for process parallelization widely used in scientific computing. This paper demonstrates its effective application in high-performance computing (HPC) environments, particularly focusing on its scalability and efficiency in executing large-scale high-throughput high-performance computing (HT-HPC) workflows. Through real-world examples, we highlight GNU Parallel’s performance across various HPC workloads, including GPU computing, container-based workloads, and node-local NVMe storage. Our results on two leading supercomputers, OLCF’s Frontier and NERSC’s Perlmutter, showcase GNU Parallel’s rapid process dispatching ability and its capacity to maintain low overhead even at extreme scales. We explore GNU Parallel’s application in massive parallel file transfers using a scheduled Data Transfer Node (DTN) cluster, emphasizing its broad utility in diverse scientific workflows. Beyond its direct application as a viable workflow manager, GNU Parallel can be employed in conjunction with other workflow systems as a "last-mile" parallelizing driver and as a quick prototyping tool to design and extract parallel profiles from application executions. We then argue that the potential for GNU Parallel to transform workflow management at extreme scales is substantial, paving the way for more efficient and effective scientific discoveries.

Maheshwari, Ketan↗

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗

Revealing Robust Room Temperature Ferromagnetism in Gd‐Doped Few‐Layered MoS 2 Thin Films

2D MoS 2 holds great promise for spintronics, yet is limited by intrinsic diamagnetism. This study demonstrates inducing ferromagnetic behavior in MoS 2 films doped with 0.47% Gd, achieving an ultrahigh saturation magnetization of 454 emu/cm 3 in a few‐layered film over 11‐times higher than bulk films (40 nm). Raman spectroscopy, X‐ray photoelectron spectroscopy, X‐ray magnetic circular dichroism, and density functional theory (DFT) calculations reveal an interplay between Gd dopants and Mo, S vacancies (V 1Mo+2S ), leading to the formation of bound magnetic polarons (BMPs) that drive ferromagnetic ordering. H 2 S annealing and DFT calculations reveal that defect healing reduces the saturation magnetization by 83%. High sulfur migration barrier in few‐layered films helps preserve BMPs, thereby sustaining ferromagnetism, whereas lower migration barriers in bulk films lead to suppression. These findings highlight the synergy between Gd doping and defect engineering in achieving ultrahigh room‐temperature ferromagnetism, offering a scalable strategy for developing high‐performance 2D magnetic materials for spintronic applications.

36 MATERIALS SCIENCE↗

Dual-function lignin monomers enable high-performance graphene electrodes via interface confinement and proton transfer enhancement

Graphene oxide (GO)-based energy storage faces dual bottlenecks: unsustainable reduction methods and sluggish proton transfer kinetics. Here, we introduce a groundbreaking green strategy using lignin-derived vanillyl alcohol (VA) as a dual-function monomer to simultaneously address these challenges. By thermally annealing GO/VA films at mild temperatures (<100 °C), VA triggers an interface-confined reduction of GO while self-polymerizing into redox-active oligomers (P-VA) that intercalate between graphene layers. This dual role-reducing agent and proton highway enables a 3D conductive network with minimized graphene restacking, abundant redox sites, and rapid H + transport pathways. Density Functional Theory (DFT) reveals how P-VA optimizes proton dynamics, while the resulting rGO-P-VA4-T90 electrode achieves a record volumetric capacitance of 311.1F/cm 3 (777.8F/cm 2 ) and retains 87.8 % capacity after 10,000 cycles. Flexible solid-state supercapacitors deliver 94.2 μWh/cm 2 energy density at 63.8 μW/cm 2 , rivaling state-of-the-art devices. Furthermore, this work redefines sustainable graphene engineering, merging biomass valorization with high-performance energy storage in a scalable, eco-friendly paradigm.

Graphene oxide reduction↗

Fabrication of flexible perovskite solar cells via rapid thermal annealing

Adaptability, lightweight, and low cost of materials make flexible perovskite solar cells essential for the perovskite technology to breach commercial photovoltaic markets. Roll-to-roll manufacturing has great potential for high-throughput perovskite manufacturing; however, conventional annealing methods are not capable of producing flexible perovskite solar cells at scale. Conventional methods are time consuming and may compromise functionality of flexible substrates under tension. Here, we introduce a bladecoated perovskite thin film on flexible ITO-coated PET annealed via rapid thermal annealing (RTA) that reduces post-deposition processing time from ~150 s to ~14 s. As a result, performance was not sacrificed for scalability as a perovskite solar cell was produced with a power conversion efficiency (PCE) of 14.58%.

14 SOLAR ENERGY↗

Practical implications of SFQ-based two-qubit gates

Scalability of today’s superconducting quantum computers is limited due to the huge costs of generating/routing microwave control pulses per qubit from room temperature. One active research area in both industry and academia is to push the classical controllers to the dilution refrigerator in order to increase the scalability of quantum computers. Superconducting Single Flux Quantum (SFQ) is a classical logic technology with low power consumption and ultra-high speed, and thus is a promising candidate for in-fridge classical controllers with maximized scalability. Prior work has demonstrated high-fidelity SFQ-based single-qubit gates. However, little research has been done on SFQ-based multi-qubit gates, which are necessary to realize SFQ-based universal quantum computing.In this paper, we present the first thorough analysis of SFQ-based two-qubit gates. Our observations show that SFQ-based two-qubit gates tend to have high leakage to qubit non-computational subspace, which presents severe design challenges. We show that despite these challenges, we can realize gates with high fidelity by carefully designing optimal control methods and qubit architectures. We develop optimal control methods that suppress leakage, and also investigate various qubit architectures that reduce the leakage. After carefully engineering our SFQ-friendly quantum system, we show that it can achieve similar gate fidelity and gate time to microwave-based quantum systems. Furthermore, the promising results of this paper show that (1) SFQ-based universal quantum computation is both feasible and effective; and (2) SFQ is a promising approach in designing classical controller for quantum machines because it can increase the scalability while preserving gate fidelity and performance.

42 ENGINEERING↗

Simulation-Based Inference for Neutrino Interaction Model Tuning

This project demonstrates, for the first time, the application of simulation-based inference (SBI) techniques to tune neutrino–nucleus interaction models. Using a mock dataset based on the MicroBooNE tuning of the GENIE event generator, our approach employs a Neural Posterior Estimator (NPE) with Masked Autoregressive Flows (MAF) to infer the posterior distributions of key GENIE parameters directly from simulated histograms. The workflow provides a scalable and amortized framework for performing likelihood-free inference in high-dimensional parameter spaces, offering a pathway to more efficient and uncertainty-aware model tuning for next-generation neutrino experiments such as DUNE and SBND.

Tame-Narvaez, KarlaMaria [Fermi National Accelerat↗

A New State of the Art: Zero Energy Modular Multifamily Construction

In 2020, the U.S. Department of Energy's Building Technologies Office (BTO) launched the Advanced Building Construction (ABC) Initiative. This initiative aimed to integrate energy efficiency into high-production construction practices. One focus area of the initiative is off-site construction, an approach that may achieve scalable, efficient, and high-performing construction buildings through process standardization. This report presents the findings and recommendations from our ABC Initiative project: A New State of the Art: Zero-Energy Modular Multifamily Construction System. The objectives of the BTO-funded project are to: 1) Achieve energy performance 50% better than the 2018 International Energy Conservation Code (IECC). 2) Achieve this level of energy performance at no additional cost VEIC worked with Louisiana State University (LSU), National Renewal Energy Lab (NREL), [the project team], and industry partners at the Mod Coach, KBS, and Solar Home Factory to identify and analyze multifamily business designs and modular construction practices. These designs and processes hold the promise of achieving the goals set out by the DOE.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Extending SST vanadis to Add SIMT Functional Units

Sandia National Laboratories is currently investigating scalable architectural simulation capabilities, with a focus on simulating and evaluating highly scalable supercomputers for high-performance computing applications. This exploration is driven by the shift toward more specialized forms of compute and the need for a more diverse set of accurate models. This project will explore the use of General-Purpose Graphical Processing Units (GPGPUs) in high-performance computing using both physical systems and new simulator models – traditional GPUs as well as tightly-coupled SIMT accelerators.

97 MATHEMATICS AND COMPUTING↗

CRADA Number NFE-22-09375 with Vitriform3D, Inc. (CRADA Final Report)

Each year, roughly 8 million tons of glass are landfilled in the United States. Vitriform3D, in collaboration with Oak Ridge National Laboratory through the Innovation Crossroads program, is developing an additive manufacturing approach to transform post-consumer glass into engineered stone building materials. A custom UV-curable binder jetting system was commissioned to enable recycled glass printing without energy-intensive oven curing. While this printer is still under development, the team pursued a parallel research track using ORNL equipment and a polyethyleneimine (PEI) binder. Printed parts were thermally post-cured and infiltrated with epoxy, with the resulting material exceeding fiber cement board performance. Silane treatment of the glass particles further improved glass–epoxy adhesion, yielding an additional 24% strength gain over the epoxy-glass composite, achieving nearly 3x the fiber cement benchmark. Ongoing research is focused on reducing epoxy content to improve cost and recycled content while retaining mechanical performance. This work demonstrates a scalable, low-carbon pathway to convert glass waste into high-value, locally produced construction materials.

36 MATERIALS SCIENCE↗

Epitaxial Growth of Ga2O3: A Review

Beta-phase gallium oxide (β-Ga2O3) is a cutting-edge ultrawide bandgap (UWBG) semiconductor, featuring a bandgap energy of around 4.8 eV and a highly critical electric field strength of about 8 MV/cm. These properties make it highly suitable for next-generation power electronics and deep ultraviolet optoelectronics. Key advantages of β-Ga2O3 include the availability of large-size single-crystal bulk native substrates produced from melt and the precise control of n-type doping during both bulk growth and thin-film epitaxy. A comprehensive understanding of the fundamental growth processes, control parameters, and underlying mechanisms is essential to enable scalable manufacturing of high-performance epitaxial structures. This review highlights recent advancements in the epitaxial growth of β-Ga2O3 through various techniques, including Molecular Beam Epitaxy (MBE), Metal-Organic Chemical Vapor Deposition (MOCVD), Hydride Vapor Phase Epitaxy (HVPE), Mist Chemical Vapor Deposition (Mist CVD), Pulsed Laser Deposition (PLD), and Low-Pressure Chemical Vapor Deposition (LPCVD). This review concentrates on the progress of Ga2O3 growth in achieving high growth rates, low defect densities, excellent crystalline quality, and high carrier mobilities through different approaches. It aims to advance the development of device-grade epitaxial Ga2O3 thin films and serves as a crucial resource for researchers and engineers focused on UWBG semiconductors and the future of power electronics.

Chemistry↗

A case for Redundant Arrays of Inexpensive Disks (RAID)

Increasing performance of CPUs and memories will be squandered if not matched by a similar performance increase in I/O. While the capacity of Single Large Expensive Disks (SLED) has grown rapidly, the performance improvement of SLED has been modest. Redundant Arrays of Inexpensive Disks (RAID), based on the magnetic disk technology developed for personal computers, offers an attractive alternative to SLED, promising improvements of an order of magnitude in performance, reliability, power consumption, and scalability. This paper introduces five levels of RAIDs, giving their relative cost/performance, and compares RAID to an IBM 3380 and a Fujitsu Super Eagle.

Patterson, David A.↗