Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “scalable performance”

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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Restoring Escaped Zincate in Rechargeable Alkaline Zinc Batteries with a Seed-in-Nanoshell Design

Rechargeable alkaline zinc batteries are promising candidates for safe and low-cost energy storage, but suffer from ZnO dissolution that causes irreversible active material loss and rapid capacity decay. Here, we report a seed-in-nanoshell ZnO anode architecture that mitigates dissolution by combining physical confinement with electrochemical restoration of dissolved zincate species. ZnO particles are encapsulated within an ion-sieving carbon nanoshell that restricts zincate diffusion, maintains electrical conductivity, and stabilizes repeated solid–solution–solid transformations. Silver (Ag) nanoparticles incorporated into the nanoshell act as zincophilic nucleation seeds, lowering the Zn deposition barrier and directing the redeposition of dissolved zincate back to metallic Zn during charging. This confinement-enabled restoration mechanism converts zincate dissolution from an irreversible loss pathway into a recoverable process, enabling improved performance under harsh test conditions. The anode also delivers 227.9 mAh g −1 at −40 °C. Finally, a scalable tens-of-gram synthesis of ZnO@Ag is demonstrated, underscoring the practical potential of this strategy for advanced aqueous zinc batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

In operando cryo-STEM of pulse-induced charge density wave switching in TaS 2

The charge density wave material 1T-TaS 2 exhibits a pulse-induced insulator-to-metal transition, which shows promise for next-generation electronics such as memristive memory and neuromorphic hardware. However, the rational design of TaS 2 devices is hindered by a poor understanding of the switching mechanism, the pulse-induced phase, and the influence of material defects. Here, we operate a 2-terminal TaS 2 device within a scanning transmission electron microscope at cryogenic temperature, and directly visualize the changing charge density wave structure with nanoscale spatial resolution and down to 300 μs temporal resolution. We show that the pulse-induced transition is driven by Joule heating, and that the pulse-induced state corresponds to the nearly commensurate and incommensurate charge density wave phases, depending on the applied voltage amplitude. With our in operando cryogenic electron microscopy experiments, we directly correlate the charge density wave structure with the device resistance, and show that dislocations significantly impact device performance. This work resolves fundamental questions of resistive switching in TaS 2 devices, critical for engineering reliable and scalable TaS 2 electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A simulation framework for evaluating electronic order workflows in integrated health records

Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.

Engineering↗
DOE OSTI2025

Network Slicing for Federated Learning in Operational Technology Environment

Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) environments are essential to modern infrastructure, facing challenges in ensuring low-latency, high-throughput communication while mitigating cyber threats. This paper presents a framework integrating Federated Learning (FL) and network slicing with Quality of Service (QoS) to enable real-time monitoring without disrupting OT operations. Leveraging digital twin technology and Network Function Virtualization (NFV), the architecture supports predictive analytics and Industry 4.0 requirements. FL facilitates decentralized model training, preserving data privacy and scalability, though it introduces potential throughput constraints. Network slicing addresses this by creating dedicated virtualized segments optimized for performance and security. Advanced fault tolerance at the container and instance levels enhances system reliability. The proposed architecture ensures high throughput, low latency, and secure orchestration for real-time anomaly detection in OT networks. Performance evaluations validate its efficiency in throughput, deployment, and learning accuracy, providing a robust foundation for future ICS automation and data-driven decision-making.

Delgado, Brian G. Rodiles [University of Texas at ↗
DOE OSTI2026

Biomanufacturing and Scale-Up: Pathways to Biochemicals, Biofuels, and Biomaterials

Advancing the bioeconomy requires the development of large-scale microbial bioprocesses capable of converting waste carbon streams into biofuels, biochemicals, and biomaterials at industrially relevant scales. While biomanufacturing has been successfully demonstrated at the laboratory scale for a wide range of chemicals, only a few have reached industrial-scale production. This is partly due to the inherent complexity of microbial systems, which rely on living cells with intricate metabolic pathways that are highly sensitive to environmental changes, making large-scale production difficult to optimize and predict. As a result, scaling-up bioprocesses remains a high-stakes challenge that requires deeper exploration. This involves integrating feedstock and microbial selection, upstream and downstream processes, and computational modelling, among other research efforts. Bulk and specialty chemicals derived from biological processes also face competition from fossil-based production routes, which have been refined through decades of technological advancements. While biologically derived molecules may offer more environmentally friendly production pathways than traditional chemical manufacturing, their widespread adoption depends on achieving cost parity-or superiority-relative to fossil-based methods. This emphasizes the importance of holistic research, including techno-economic analyses and life cycle assessments, to ensure both economic viability and environmental sustainability. This editorial and special issue explores state-of-the-art strategies for converting waste carbon sources into valuable products. It discusses how enzymes, single microbes (e.g., extremophiles), and microbiomes (e.g., through division of labor) can be integrated with upstream and downstream process innovations-such as consolidated bioprocessing and in situ product recovery-to improve the efficiency and scalability of biomanufacturing. The editorial further highlights the role of computational modelling in understanding, predicting, and controlling bioprocess performance across scales, and concludes by emphasizing the importance of techno-economic modelling to identify technologies that can move to market.

09 BIOMASS FUELS↗
DOE OSTI2025

CUDO: closed-form universal dwell-time optimization for computer-controlled optical surfacing

Precision optical figuring demands fast and accurate dwell time optimization to reach nanometer- and sub-nanometer-level accuracy in next-generation optical systems. We introduce CUDO (closed-form universal dwell-time optimization), the first, to the best of our knowledge, unified closed-form analytical framework that supports both function-form and matrix-form dwell time models in computer-controlled optical surfacing (CCOS). In contrast to traditional methods, which rely on iterative optimization and hyperparameter tuning, our framework derives direct analytical solutions with no adjustable parameters. This approach unifies the solution principles of existing methods within a single mathematical model, delivering three key advantages: (1) accuracy on par with, or superior to, iterative solvers, (2) substantial reduction in computation time, and (3) numerical robustness. Comparative studies with prior art confirm that closed-form solutions achieve equivalent residual error while removing runtime bottlenecks. By simplifying the implementation and enabling real-time, scalable deployment, CUDO establishes a practical foundation for future deterministic fabrication of large-aperture and high-performance optics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Streaming Generalized Canonical Polyadic Tensor Decompositions

In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from traditional canonical polyadic (CP) tensor decompositions as it allows for arbitrary objective functions which the CP model attempts to minimize. This approach can provide better fits and more interpretable models when the observed tensor data is strongly non-Gaussian. In the streaming case, tensor data is gradually observed over time and the algorithm must incrementally update a GCP factorization with limited access to prior data. In this work, we extend the GCP formalism to the streaming context by deriving a GCP optimization problem to be solved as new tensor data is observed, formulate a tunable history term to balance reconstruction of recently observed data with data observed in the past, develop a scalable solution strategy based on segregated solves using stochastic gradient descent methods, describe a software implementation that provides performance and portability to contemporary CPU and GPU architectures and integrates with Matlab for enhanced usability, and demonstrate the utility and performance of the approach and software on several synthetic and real tensor data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

CO 2 to Fuels Through Novel Electrochemical Catalysis (Final Report)

Electrochemical upgrading of CO 2 into hydrocarbon fuels via CO 2 –H 2 O co-electrolysis using solid oxide electrolysis cells (SOECs) presents an encouraging approach to cost-effective storage of renewable power. In this study, we harness the unique property of protonic ceramic electrolysis cells (PCEC) and demonstrate direct electro-catalytic production of CH 4 from CO 2 –H 2 O in a unit-cell stack configuration. The unit-cell stack was developed to evaluate the scalability and the applicability of PCECs from a broader system-level viewpoint. Tradeoffs between operating conditions and performance metrics were explored and thoroughly characterized. An exceptional CH 4 -yield ratio of 34.6% from only CO 2 –H 2 O reactants was achieved under an electrolysis current of 1 A cm –2 at 450 °C. With exhaust-H 2 recycle, this value was boosted to greater than 70%. In addition, the electrochemical co-conversion of CO 2 –H 2 O offers a higher CH 4 -yield ratio compared to traditional thermo-catalytic conversion of CO 2 –H 2 under certain operating conditions, indicating possible electrochemical promotion of catalytic CO 2 methanation. The demonstrated good performance is a promising result for further scale-up and for the practical utilization of electrochemical CO 2 upgrade using PCECs. Techno-economic analyses reveal operating conditions that yield cost-competitive levelized cost of fuel production.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Upcycling Polyethylene Waste to Advanced Carbon Materials for Energy Storage Applications

Polyethylene is notoriously difficult to upcycle because it decomposes into light gases at approximately 350-400 °C which prevents processing it at higher temperatures to convert it into high-value carbon materials, such as graphene or graphite. We address this challenge by using an air-based, thermo-oxidation process, which heats polyethylene (PE) just below the decomposition point to initiate oxidation and cross-linking of PE alkyl chains. These molecular transformations allow PE to be further graphenized or graphitized at higher temperatures without decomposing. The PE-derived graphene has a specific surface area up to 1,800 m 2/g and Raman ID/IG ratio of 0.85, which enables it to be used as an electrode material for a symmetric supercapacitor with the 1 M H2SO4 electrolyte. The PE-derived graphene material has a comparable electrochemical capacitive performance, such as power density, specific capacitance, and long cycle stability, to the commercial state of art porous carbon electrode. The stabilized PE could also be converted into highly crystalline flake graphite via low-temperature catalytic graphitization. The PE-derived graphite is used for the lithium-ion battery anode, which showed comparable electrochemical battery performance, such as reversible rate performance and long-term cyclic stability, to the current use battery-grade graphite, thus providing a scalable method to upcycle PE plastic waste into high-value carbon material.

Gao, Yuan↗
DOE OSTI2025

Environmental Evaluation of Gas Switching Reforming for Low Carbon Hydrogen: A Power-to-X Study

Gas Switching Reforming for hydrogen production (GSR-H2) offers a promising pathway for producing low-carbon hydrogen at scale, with significant implications for Power-to-X (PtX) systems that rely on clean hydrogen as a feedstock for synthetic fuels and chemicals. GSR-H2 integrates inherent carbon capture and thermal self-sufficiency, positioning it as an efficient alternative to conventional steam methane reforming (SMR), proton exchange membrane (PEM) electrolysis, and chemical looping reforming (CLR). Unlike SMR, GSR-H2 avoids external natural gas combustion by leveraging exothermic redox cycles to generate process steam and recover electricity internally. Its innovative reactor design consolidates all reforming stages within a single reactor cluster, eliminating the need for solid circulation found in CLR, thereby reducing capital costs and improving system reliability and scalability. This presentation describes the first environmental life cycle assessment (LCA) of GSR-H2, evaluating its environmental performance across U.S. grid and renewable energy scenarios. In a renewables-powered configuration, GSR-H2 achieves a global warming potential (GWP) of 2.77 kg CO2 equivalent per kg H2, substantially lower than SMR (10.4 kg) and competitive with PEM electrolysis (1.85 kg) and CLR (1.84 kg). Results across additional impact categories, including air quality and water use, support GSR-H2’s role as a complementary hydrogen source in PtX applications. Its reduced environmental burden, thermal integration, and simplified scale-up potential make GSR-H2 a viable contributor to net-zero PtX systems, particularly where renewable energy is abundant and electricity-intensive hydrogen production faces economic or infrastructure constraints.

03 NATURAL GAS↗
DOE OSTI2023

An Overview of Challenges and Strategies for Stabilizing Zinc Anodes in Aqueous Rechargeable Zn-Ion Batteries

Aqueous rechargeable zinc ion batteries (ZIBs) have been revived and are considered a promising candidate for scalable electrochemical energy storage systems due to their intrinsic safety, low cost, large abundance, mature recyclability, competitive electrochemical performance, and sustainability. However, the deployment of aqueous rechargeable ZIBs is still hampered by the poor electrochemical stability and reversibility of Zn anodes, which is a common, inherent issue for most metal-based anodes. This review presents a comprehensive and timely overview of the challenges and strategies of Zn anodes toward durable ZIBs. First, several challenges that significantly reduce the Coulombic efficiency and cycling stability of Zn anodes are briefly discussed including dendrite formation, hydrogen evolution, and corrosion. Then, the mitigation strategies are summarized in terms of modifying the electrode/electrolyte interfaces, designing electrode structures, and optimizing electrolytes and separators. Further, we comprehensively discuss the mechanisms behind these issues and improvement strategies with respect to the anodes, electrolytes, and separators. Lastly, we provide perspectives and critical analyses of remaining challenges, outlook, and future direction for accelerating the practical application of aqueous rechargeable ZIBs.

25 ENERGY STORAGE↗
NASA NTRS1996

Novel Composites for Wing and Fuselage Applications

Design development was successfully completed for textile preforms with continuous cross-stiffened epoxy panels with cut-outs. The preforms developed included 3-D angle interlock weaving of graphite structural fibers impregnated by resin film infiltration (RFI) and shown to be structurally suitable under conditions requiring minimum acquisition costs. Design guidelines/analysis methodology for such textile structures are given. The development was expanded to a fuselage side-panel component of a subsonic commercial airframe and found to be readily scalable. The successfully manufactured panel was delivered to NASA Langley for biaxial testing. This report covers the work performed under Task 3 -- Cross-Stiffened Subcomponent; Task 4 -- Design Guidelines/Analysis of Textile-Reinforced Composites; and Task 5 -- Integrally Woven Fuselage Panel.

Suarez, J. A.↗
NASA NTRSDate not supplied

The Solar Neutron TRACking (SONTRAC) Instrument for the Detection of Fast Neutrons

Fast neutrons (energies >0.5 MeV) contribute to the radiation exposure of space hardware and astronaut crew, enable greater understanding of planetary atmospheric and surface compositions and allow unique measurements of solar particle acceleration. Neutrons are challenging to detect and measurements of them typically suffer from high background rates. High energy neutrons (>50 MeV) pose even more challenges, because the traditional double-scatter technique based on a time-of-flight (ToF) measurement. These measurements are challenging due to size constraints on satellites, particularly newer small satellites. The SOlar Neutron TRACking instrument (SONTRAC) is a small satellite neutron detector that utilizes fine-grained scintillating fiber bundles with 1-mm pitch silicon photomultiplier (SiPM) array readout. Signal processing is accomplished with multichannel ASICs. SONTRAC is able to image fast neutron (between 20-200 MeV) scatters in a compact scalable package. We discuss below the numerous applications of this technology and recent progress on the development and performance characteristics of the prototype instrument.

Georgia A de Nolfo↗
DOE OSTI2024

Cold Climate Degradation: An Analysis of Double-Axis Tracked, E-W Vertical, and Fixed-Tilt Photovoltaic Deployments in Alaska

As countries around the world transition towards renewable energy, there is increasing interest in using photovoltaic (PV) technologies to help decarbonize remote northern communities due to their scalability and affordability. However, a major barrier towards large-scale adoption of PV in cold climates is performance uncertainty under extreme environmental conditions including snowfall, freeze-thaw cycles, and high wind loads. Existing literature on PV degradation rates in the North is relatively limited, with published degradation rates varying between -0.2%/year (Sweden) to -1.3%/year (Scotland). At this workshop, we will present preliminary results on the long-term performance of two diverse photovoltaic sites located in Fairbanks, Alaska at 64.8 degrees N: a monofacial Al-BSF double-axis tracking site maintained by the Cold Climate Housing Research Center (CCHRC), and a bifacial PERC/SHJ E-W vertical and south-facing fixed-tilt site maintained by the Alaska Center Energy and Power (ACEP). CCHRC data has been collected over a period of 15 years, while ACEP site data has been collected over 4 years. Using the degradation analysis tool, RdTools, we will present annual system degradation rates, seasonal performance ratio, and identify potential cold climate failure mechanisms for commercially available PV technologies. This analysis will add to existing literature by directly comparing the performance of multiple PV configurations in Alaska.

bifacial↗
DOE OSTI2025

Redis-Based Streaming Architecture for Accelerator Beam Instrumentation DAQ Systems

The Fermilab Acceleraor Division, Beam Instrumentation Department, is always adopting modern and current software methodologies for complex DAQ architectures. This paper highlights the Redis Adapter (RA) as the key software component enabling high performance, modular communication between digitizers and distributed control systems by leveraging Redis and containerization. The RA provides a unified, efficient interface between Redis based data streams and consumer systems. In the legacy architecture, digitized data flowed through the custom, UDP based Distributed Data Communication Protocol in the middle layer. In the current system, DDCP remains the ingestion path, while the RA serves as the decoupling layer. The proposed system replaces old VME digitizers with a SOM-based digitizer that communicates with Redis using the RA. The RA acts as both a performance-critical bridge and a protocol-agnostic adapter, ensuring compatibility with legacy control frameworks while enabling future scalability and modularity. This restructuring of the middle layer also helps the system achieve high throughput, reduce latency, and simplify the data path. Finally, we will demonstrate how RA is utilized in our two core products to deliver both legacy compatibility and future flexibility.

Joshi, S. [Fermilab]↗
DOE OSTI2026

Deploying MARTe2 and MDSplus for Scalable Real-Time Control Systems: A Proof-of-Concept for the SMART Tokamak

The SMART tokamak is a spherical tokamak with flexible shaping that will need a modular and high-performance real-time control system. This work presents the implementation and validation of the MARTe2 framework at the Princeton Plasma Physics Laboratory (PPPL) as a testbed for supporting SMART (University of Seville, Spain). The system integrates MARTe2, MDSplus for data archiving, and user datagram protocol (UDP)-based communication with both synthetic and physical devices. A deterministic control loop was developed using custom control algorithms, showing the system’s ability to operate under strict real-time constraints. The resulting framework is scalable, maintainable, and adaptable to experimental tokamaks like SMART.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2013

Development and Testing of a Variable Conductance Thermal Acquisition, Transport, and Switching System

This paper describes the development and testing of a scalable thermal management architecture for instruments, subsystems, or systems that must operate in severe space environments with wide variations in sink temperature. The architecture involves a serial linkage of one or more hot-side variable conductance heat pipes (VCHPs) to one or more cold-side loop heat pipes (LHPs). The VCHPs provide wide area heat acquisition, limited distance thermal transport, modest against gravity pumping, concentrated LHP startup heating, and high switching ratio variable conductance operation. The LHPs provide localized heat acquisition, long distance thermal transport, significant against gravity pumping, and high switching ratio variable conductance operation. The single-VCHP, single-LHP system described herein was developed to maintain thermal control of a small robotic lunar lander throughout the lunar day-night thermal cycle. It is also applicable to other variable heat rejection space missions in severe environments. Operationally, despite a 60-70% gas blocked VCHP condenser during ON testing, the system was still able to provide 2-4 W/K ON conductance, 0.01 W/K OFF conductance, and an end-to-end switching ratio of 200-400. The paper provides a detailed analysis of VCHP condenser performance, which quantified the gas blockage situation. Future multi-VCHP/multi-LHP thermal management system concepts that provide power/transport length scalability are also discussed.

Bugby, David C.↗
DOE OSTI2023

Distributed-Memory Parallel JointNMF

Joint Nonnegative Matrix Factorization (JointNMF) is a hybrid method for mining information from datasets that contain both feature and connection information. We propose distributed-memory parallelizations of three algorithms for solving the JointNMF problem based on Alternating Nonnegative Least Squares, Projected Gradient Descent, and Projected Gauss-Newton. We extend well-known communication-avoiding algorithms using a single processor grid case to our coupled case on two processor grids. We demonstrate the scalability of the algorithms on up to 960 cores (40 nodes) with 60% parallel efficiency. The more sophisticated Alternating Nonnegative Least Squares (ANLS) and Gauss-Newton variants outperform the first-order gradient descent method in reducing the objective on large-scale problems. We perform a topic modelling task on a large corpus of academic papers that consists of over 37 million paper abstracts and nearly a billion citation relationships, demonstrating the utility and scalability of the methods.

Eswar, Srinivas↗