Simplified electrometer has excellent operating characteristics
Simplified and improved electrometer circuit provides high-input impedance, stability of gain and operating point, linear response, and low power requirements.
Brantner, R. E.↗
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Results for “operational excellence”
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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Center of Excellence for Operational Technology
The Center of Excellence for Operational Technology Traditional Presentation Abstract 2025 National Laboratories Information Technology Summit | Denver, CO Traditional Presentation Session Managing cybersecurity risk in Operational Technology (OT) presents a significant challenge across the Department, and critically, at many of the national laboratories. This includes IT-OT convergence, aging OT systems, cost of updating OT systems, and increased Advanced Persistent Threat efforts against OT including the 16 critical infrastructure sectors as listed in Presidential Policy Directive 21. DoE’s Office of Science and NNSA’s Office of the Chief Information Officer are taking the lead in addressing this challenge to include critical systems, by establishing the Center of Excellence (CoE) for Operational Technology. Championed by NNSA Deputy Chief Information Officer Steven McAndrews and the Office of Science Chief Information Officer Shila Cooch, the CoE for OT was chartered in February 2025 to address the challenges of OT cybersecurity and compliance. The CoE for OT will create partnerships and leverage expertise from across the NNSA National Security Enterprise and DOE Labs, Plants and Sites. The CoE will also collaborate with colleagues in other government agencies, industry partners and academia. The CoE for OT discussion at the National Laboratories Information Technology Summit ’25 will include the genesis of the CoE, stated goals, organizational structure, and the effort to attract OT subject matter experts to join the CoE effort to share knowledge and expertise. The discussion will include opportunities to get involved and contribute to this important effort. This session will be led by CoE for OT Co-Chairs Matt Kwiatkowski, Fermi National Laboratory Chief Information Security Officer, and Steven Weldon, Savannah River National Laboratory Cyber Program Director at the Georgia Cyber Center. The session will be of particular interest to CIOs, CTOs, CISOs, as well as IT and OT practitioners.
Kwiatkowski, Matt [Fermilab]↗
Research Reactors Division Infrastructure Investment Plan for the High Flux Isotope Reactor
The High Flux Isotope Reactor (HFIR) is a unique national asset. Operational for nearly 60 years, continued investment into the aging infrastructure is necessary to ensure operation for another 6 decades. Additionally, growing missions require HFIR as well as important upgrades. Consequently, carefully integrated planning is required to ensure that infrastructure investments are timely executed to ensure long-term, reliable operation of HFIR. Concerns about challenges to the operational reliability of HFIR resulted in a recommendation from the 2023 Operations Review by the US Department of Energy (DOE) Office of Basic Energy Sciences that a HFIR management strategy be developed to address the infrastructure needs. This report defines the investment needs, which are evolving as new upgrade efforts are better defined. HFIR is part of the three-source strategy within the Neutron Sciences Directorate (NScD) and contributes to the five strategic science areas outlined in the NScD 10 Year Strategic Science Plan: quantum materials, soft matter, materials and engineering, chemistry, and biosciences. Fundamental to this strategy are three core values: operational excellence, responsible stewardship, and servant leadership. These values guide our mission of safe and reliable operation of the reactor and require a strong and just nuclear safety culture, a solemn respect for responsible care of the facility, good workforce development, robust procedures and processes, an effective communication strategy, world-class asset management, a determined customer focus, and a commitment to protecting the environment, the safety and health of the public and our people, and the quality of work performed within our facility. These principles are all essential to operate HFIR at a world-class level. The Research Reactors Division (RRD) will lead a new era of neutron science and isotope production at HFIR through responsible and purposeful leadership and unwavering support of the science community. The approach outlined in this plan highlights the direction leadership is taking to ensure that HFIR is ready to support the science challenges and national needs of the future and that the United States maintains world leadership in neutron sciences. The plan is in alignment with the DOE’s desire to continue operating HFIR and with the NScD strategic science goals for the future. HFIR is an aging facility with numerous infrastructure challenges and needs. It has an aging workforce in relation to the general population of Oak Ridge National Laboratory (ORNL), with many expected retirements over the next 5–10 years. With an increase in work scope caused by changing national priorities and science goals, several critical hires have been identified. To manage HFIR’s infrastructure needs, a prioritized list of equipment upgrades has been identified along with an analysis of future staffing requirements. A desire to operate HFIR at eight cycles per year will necessarily require some significant changes to procedures and processes currently in place as well as targeted staffing additions. Many of the equipment upgrades identified in this plan will significantly increase the reliability of the plant, thus contributing to the effort to reach the goal of safely operating eight cycles per year. A plan to attain eight-cycle operation is being prepared in parallel with the activities identified in this plan, although the actions identified to satisfy both plans will overlap. This plan identifies new infrastructure needs—for both plant equipment and staffing—thus necessitating formulation of future budget requests to fund the increased work scope and improvement activities. Some activities are currently being scheduled with the expectation that funding will be received. Any delays to funding or reductions of funding from the identified cost estimations will directly and negatively affect the plan’s implementation.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Physics-Guided Deep Learning for Complex System Health Management and Decision Making
The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.
Diagnostics↗
Thermally Evaporated Naphthalene Diimides as Electron Transport Layers for Perovskite Solar Cells
Thermally evaporated organic electron transport layers (ETLs) have the potential to enable high-performance and scalable perovskite solar cells (PSCs). Among these, naphthalene diimide (NDI)-based ETLs are a promising family of materials that exhibit the optoelectronic properties, ambient stability and versatility required of high-performance ETLs. Here, we synthesized five NDI derivatives with varying functional groups and identified the two most promising candidates for evaluating the impact of molecular structure on processability via thermal evaporation. While phosphonic acid functionalization was shown to introduce thermal instability, leading to chemical changes during evaporation, NDI-bis N-phenyl-bromide (NDI-(PhBr) 2 ) emerged as a promising ETL candidate. NDI-(PhBr) 2 demonstrated excellent compatibility with the thermal evaporation process and enabled PSCs with power conversion efficiencies (PCEs) of 15.6%, surpassing all previously reported PSCs containing thermally evaporated NDI ETLs. Furthermore, NDI-(PhBr) 2 exhibited excellent operational stability, retaining 75% of the initial PCE after 150 h of operation under continuous illumination at 65 °C. These results highlight the potential of NDI-based ETLs for advancing the scalability and performance of PSCs.
36 MATERIALS SCIENCE↗
Dual interfacial H-bonding-enhanced deep-blue hybrid copper–iodide LEDs
Solution-processed light-emitting diodes based on non-toxic copper–iodide hybrids are a compelling solution for efficient and stable deep-blue lighting, owing to their tunability, high photoluminescence efficiency and environmental sustainability. Here we present a hybrid copper–iodide that shows near-unity photoluminescence quantum yield (99.6%) with an emission wavelength of 449 nm and colour coordinates (0.147, 0.087), alongside its emission mechanism and charge transport characteristics. Here, we use the thin film of this hybrid as the sole active emissive layer to fabricate deep-blue light-emitting diodes and subsequently enhance the device performance through a dual interfacial hydrogen-bond passivation strategy. This synergetic surface modification approach, integrating a hydrogen-bond-acceptor self-assembled monolayer with an ultrathin polymethyl methacrylate capping layer, effectively passivates both heterojunctions of the copper–iodide hybrid emissive layer and optimizes charge injections. We achieve a maximum external quantum efficiency of 12.57%, a maximum luminance of 3,970.30 cd m −2 with colour coordinates (0.147, 0.091) and an excellent operational stability (half-lifetime) of 204 hours under ambient conditions. We further showcase a large-area device of 4 cm 2 that maintains high efficiency. Our findings reveal the potential of copper–iodide-based hybrid materials for applications in solid-state lighting and display technologies, offering a versatile strategy for enhancing device performances.
14 SOLAR ENERGY↗
JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits
The integration of Non-Energy Benefits (NEBs) into energy efficiency initiatives is essential for operational excellence in manufacturing. This presentation and software demonstration explore how quantifying NEBs such as improved safety, increased quality, and enhanced productivity, can strengthen business cases for energy investments, leading to better payback periods and alignment with organizational goals. We introduce JUSTIFI, a free, open-source software by the U.S. Department of Energy that aids in the measurement of NEBs and enhances understanding of their impact on Key Performance Indicators (KPIs) and return on investment (ROI). JUSTIFI features an intuitive interface for identifying NEBs, customizable reporting tools, and comprehensive system cataloging, empowering companies to effectively communicate the value of energy efficiency projects. By leveraging this innovative tool, organizations can better navigate energy efficiency assessments and drive support for their energy management initiatives.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Improving Performance via Energy Efficiency JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits
Energy efficiency is pivotal to achieving operational excellence, as it enhances value while reducing waste. This presentation explores the integration of non-energy benefits (NEBs) into energy efficiency projects, which can lead to risk reduction, value creation, and cost savings. By quantifying NEBs - such as improved safety, decreased pollution, and increased productivity - companies can strengthen their business cases for energy investments, ultimately improving payback periods and aligning with strategic goals. Designed for a diverse audience, from trained auditors to novices in energy assessments, we have developed open-source software called JUSTIFI, NEB finding methodology, and training materials which build on existing frameworks and leverages resources from the U.S. Department of Energy and Better Plants energy system analysis software suite such as MEASUR. This work aims to maximize ROI through NEB identification, utilizing tools like JUSTIFI and the NEBs Discovery Protocol.
97 MATHEMATICS AND COMPUTING↗
Low-background air-infrared telescope for balloon-borne infrared astronomy
The design and performance of a far-infrared telescope are discussed. The instrument is twenty centimeters in diameter and has excellent operating characteristics at 100 microns. The principal features of the telescope are summarized. A diagram of the system is provided. The telescope completed two sucessful balloon flights in which the planets Mars and Saturn were used as calibration sources. Observations were made of the H2 regions W 3, Orion A, NGC 2024, and the bright infrared galaxy M 82.
Low, F. J.↗
Interdisciplinary applications and interpretations of ERTS data within the Susquehanna River basin
The author has identified the following significant results. The full potential of high quality data is achieved only with the application of efficient and effective interpretation techniques. An excellent operating system for handling, processing, and interpreting ERTS-1 and other MSS data was achieved. Programs for processing digital data are implemented on a large nondedicated general purpose computer. Significant results were attained in mapping land use, agricultural croplands, forest resources, and vegetative cover. Categories of land use classified and mapped depend upon the geographic location, the detail required, and the types of lands use of interest. Physiographic and structural provinces are spectacularly displayed on ERTS-1 MSS image mosaics. Geologic bedrock structures show up well and formation contacts can sometimes be traced for hundreds of kilometers. Large circular structures and regional features, previously obscured by the detail of higher resolution data, can be seen. Environmental monitoring was performed in three areas: coal strip mining, coal refuse problems, and damage to vegetation caused by insects and pollution.
Mcmurtry, G. J.↗
Livewire: A Model Platform for Data Quality Assessment and AI Readiness Across DOE Missions
High-quality, well-governed data is essential for accelerating discovery and achieving operational excellence across DOE and national laboratory missions. The Livewire Data Platform is a DOE-supported platform that offers automated assessments of data quality, standardization, provenance, and Artificial Intelligence (AI) readiness. It allows researchers and data practitioners to systematically and easily evaluate datasets against established governance criteria and prepare them for advanced analytics. Livewire addresses critical challenges in DOE's data ecosystem with integrated capabilities for metadata validation, provenance tracking, and schema alignment. This platform's automated workflows assist users in identifying data quality gaps, enhancing interoperability between datasets collected from various stakeholders, and ensuring compliance with DOE data standards, all while reducing manual curation efforts. Additionally, we will discuss its AI readiness framework, which is being developed to prepare datasets for training models, developing advanced analytic tools, and machine learning applications. Using some of the more than one hundred tabular datasets on Livewire, processed with this open-source methodology, we will demonstrate how Livewire can serve as a model for scalable, standards-driven data management. This approach provides a pathway to leverage existing and future datasets within the DOE, boosting innovation and efficiency across national laboratories.
33 - ADVANCED PROPULSION SYSTEMS↗
Analysis and Experimental Tests of a High-Performance Evacuated Tubular Collector
A high-performance collector based on the use of all-glass, evacuated tubular collector elements is described and analyzed, and supporting experimental data presented. The collector operated with excellent efficiency at temperatures high enough to drive existing air conditioning units, and showed good performance under diffuse light and low insolation conditions. Collector efficiency was insensitive to operating temperature, ambient temperature, and wind speed. In addition, air, as well as liquid, can be used as the heat transfer fluid, with no significant performance penalty. While the equations governing the useful energy produced can be cast in a form similar to that for flat plate collectors, several important parameters were unique in a number of respects. The loss coefficient was unusually low, while the flow factor and effective insolation were unusually high.
Beekley, D. C.↗
Feasibility model of a high reliability five-year tape transport, volume 2
Analysis of the design features of the modularized tape transport renders a life expectancy in excess of five years. Tests performed on the tape transport were directed toward determining its performance capability. These tests revealed that the tape jitter and skew are in the range achieved by high quality digital tape transports. Guidance of the tape in the lateral sense by the use of the two hybrid crowned rollers proved to be excellent. Tracking was maintained within less than one thousandth inch (approximately 2 micrometers). The guidance capability demonstrated makes possible the achievement of the performance objective of 7.2 x 10 to the 9th power storage capability employing 1500 ft. of one inch wide tape with a packing density of 5,000 bits per inch per track on 80 tracks. Also, the machine showed excellent characteristics operating over a wide range of tape speeds. The basic design concept lends itself to growth and adaptation to a wide range of recorder requirements.
Eshleman, R. L.↗
Viscous flow analysis in mixed flow rotors
A method for analyzing the viscous flow through turbomachine rotors is presented. The field analysis is based upon the solution of the full Navier-Stokes equations over the rotor blade-to-blade stream channels. An Alternating-Direction-Implicit method is employed to carry out the necessary numerical integration of the elliptic governing equations. The flow analysis may be applied to various types of turbomachine rotors. Preliminarily, only the case of laminar flows are considered in this paper. The flow characteristics within the rotors of a mixed flow turbine and a radial bladed compressor are investigated over a wide range of operating conditions. Excellent results are obtained when compared with existing experimental data. The method of this analysis is quite general and can deal with a wide range of applications. Possible modification of the present study to deal with turbulent flow cases are also identified.
Khalil, I.↗
Building the Business Case with JUSTIFI: Quantifying Multiple Benefits in the Automotive Industry
The Michigan State University Industrial Training and Assessment Center (MSU ITAC) conducted a pilot study at an automotive parts manufacturer in Michigan. The study identified energy-productivity enhancements through the application of the JUSTIFI software. Key recommendations included replacing six inefficient rooftop units (RTUs) with a new air rotational unit. By quantifying operational savings for this project, the expected payback period went from 6.6 years to 1.4 years. Additionally, the installation of variable frequency drives (VFDs) on condenser tower motors was suggested. By including all operational benefits, the payback period was reduced from 8.2 years to 1.3 years. This comprehensive analysis aims to bolster the manufacturer's goals of reducing energy while enhancing overall operational efficiency.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Surrogate Modeling of Landau Damping with Deep Operator Networks
Kinetic simulations excel at capturing microscale plasma physics phenomena with high accuracy, but their computational demands make them impractical for modeling large-scale space and astrophysical systems. In this context, we build a surrogate model, using Deep Operator Networks (DeepONets), based upon the Vlasov–Poisson simulation data to model the dynamical evolution of plasmas, focusing on the Landau damping process—a fundamental kinetic phenomenon in space and astrophysical plasmas. The trained DeepONets are able to capture the evolution of electric field energy in both linear and nonlinear regimes under various conditions. Extensive validation highlights DeepONets’ robust performance in reproducing complex plasma behaviors with high accuracy, paving the way for large-scale modeling of space and astrophysical plasmas.
plasma astrophysics↗
Remote control flare stack igniter for combustible gases
Device has been designed and developed for igniting nonrecoverable combustible gases and sustaining combustion of gases evolving from various gas vent stacks. Igniter is superior to existing systems because of simplicity of operation, low cost fabrication, installation, operational and maintainability features, and excellent reliability in all phases of required operations.
Ray, W. L.↗
Calcium-Doped High-Voltage Spinel Cathode for Long Cycle Life Lithium-Ion Batteries
With the promises of low cost, high operating voltage, and excellent rate capability, the high-voltage spinel material with the formula of LiNi 0.5 Mn 1.5 O 4 (LNMO) has been considered as one of the most promising cathode materials for nextgeneration lithium-ion batteries (LIBs). However, the adoption of LNMO into practical LIBs is greatly hindered due to its rapid capacity decay associated with its bulk structural instability and interfacial side reactions. To address these issues, we proposed to use the cost-effective calcium (Ca) element as a dopant to stabilize the oxygen framework and surface of the LNMO crystal. The experimental results showed that, with moderate Ca doping, the obtained cathode (Ca 0.05 LNMO) retained a specific capacity of ∼121 mAh/g (∼94.4% capacity retention) after 500 cycles at 0.5 C, compared to ∼73% for the baseline bare sample. Furthermore, the Ca 0.05 LNMO cathode retained ∼84% of its initial capacity, vs the baseline with ∼69%, after 150 cycles at the high temperature of 55 °C. The excellent battery performance of the moderately Ca-doped LNMO cathode is ascribed to its structural and kinetic advantages.
25 ENERGY STORAGE↗