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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Disk Density Tuning of a Maximal Random Packing

We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Community size-spectra applied to recreational freshwater fisheries in Puerto Rican reservoirs

We developed a management framework based on community size-spectra (CSS) to establish targets to maximize desirable gamefish. We evaluated the influence of relative abundance of fish functional groups and watershed characteristics on the slope of the CSS or ecological efficiency. Both ecological efficiency and capacity were strongly influenced by relative abundance of fish functional groups and the degree of water level variation. Steeper slopes indicated overfished gamefish populations, whereas flatter slopes indicated systems dominated by undesirable invasive large-bodied low trophic position fish. We hypothesize that a desirable fishery would have a target range of CSS slopes that provides a deterministic community-based framework of predictable responses to environmental and food web changes that can be used to evaluate outcomes of management actions and a means to assess annual progress toward desirable conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Historical Trends in PM 2.5 -Related Premature Mortality during 1990$-$2010 across the Northern Hemisphere

Air quality across the northern hemisphere over the past two decades has witnessed dramatic changes, with continuous improvement in developed countries in North America and Europe, but a contrasting sharp deterioration in developing regions of Asia. Objective: This study investigates the historical trend in the long-term exposure to PM 2.5 and PM 2.5 -related premature mortality (PM 2.5 -mortality) and its response to changes in emission that occurred during 1990-2010 across the northern hemisphere. Implications for future trends in human exposure to air pollution in both developed and developing regions of the world are discussed. Methods: We employed the integrated exposure-response model developed by Health Effects Institute to estimate the PM 2.5 -mortality. The 1990-2010 annual-average PM 2.5 concentrations were obtained from the simulations using WRF-CMAQ model. Emission mitigation efficiencies of SO 2 , NO x , NH 3 and primary PM are estimated from the PM 2.5 -mortality responses to the emission variations. Results: Estimated PM 2.5 -mortalities in East Asia and South Asia increased by 21% and 85% respectively, from 866,000 and 578,000 in 1990, to 1,048,000 and 1,068,000 in 2010. PM2.5-mortalities in developed regions, i.e., Europe and high-income North America decreased substantially by 67% and 58% respectively. Conclusions: Over the past two decades, correlations between population and PM 2.5 have become weaker in Europe and North America due to air pollution controls but stronger in East Asia due to deteriorating air quality. Mitigation of primary PM appears to be the most efficient way for increasing health benefits, i.e., providing the largest mortality reduction per unit emissions. However, reductions in emissions of NH 3 are needed to maximize the effectiveness of NO x emission controls.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Dissolution Flowsheet for High Flux Isotope Reactor Fuel

As part of the Spent Nuclear Fuel (SNF) processing campaign, H-Canyon is planning to begin dissolving High Flux Isotope Reactor (HFIR) fuel in late FY17 or early FY18. Each HFIR fuel core contains inner and outer fuel elements which were fabricated from uranium oxide (U 3 O 8 ) dispersed in a continuous Al phase using traditional powder metallurgy techniques. Fuels fabricated in this manner, like other SNF’s processed in H-Canyon, dissolve by the same general mechanisms with similar gas generation rates and the production of H 2 . The HFIR fuel cores will be dissolved and the recovered U will be down-blended into low-enriched U. HFIR fuel was previously processed in H-Canyon using a unique insert in both the 6.1D and 6.4D dissolvers. Multiple cores will be charged to the same dissolver solution maximizing the concentration of dissolved Al. The objective of this study was to identify flowsheet conditions through literature review and laboratory experimentation to safely and efficiently dissolve the HFIR fuel in H-Canyon. Laboratory-scale experiments were performed to evaluate the dissolution of HFIR fuel using both Al 1100 and Al 6061 T6 alloy coupons. The Al 1100 alloy was considered a representative surrogate which provided an upper bound on the generation of flammable (i.e., H 2 ) gas during the dissolution process. The dissolution of the Al 6061 T6 alloy proceeded at a slower rate than the Al 1100 alloy, and was used to verify that the target Al concentration in solution could be achieved for the selected Hg concentration. Mass spectrometry and Raman spectroscopy were used to provide continuous monitoring of the concentration of H 2 and other permanent gases in the dissolution offgas, allowing the development of H 2 generation rate profiles. The H 2 generation rates were subsequently used to evaluate if a full HFIR core could be dissolved in an H-Canyon dissolver without exceeding 60% of the calculated lower flammability limit (LFL) for H 2 at a given Hg concentration. Complete dissolution of the Al 1100 and Al 6061 T6 alloys up to a final Al concentration of 2 M was obtained using a 7 M HNO 3 solution containing a 0.002 M Hg catalyst. However, following the dissolutions, solids were observed in the solution. The solids were amorphous, but likely originated from the Si present in the alloys. No crystalline materials, such as Al(NO 3 ) 3 were observed. During the course of the dissolution experiments, it was determined that delaying the addition of Hg once the HNO 3 solution reached the boiling point can reduce the total offgas and H 2 generation rates. The delay in starting the Hg addition is not necessary for HFIR fuel dissolution, but could be useful in other research reactor dissolution campaigns. The potential to generate flammable concentrations of H 2 in the offgas during a HFIR fuel dissolution was evaluated using the experimental data. The predicted H 2 concentration in the dissolver offgas stream was compared with 60% of the calculated H 2 LFL at 200 °C using several prototypical experiments. The calculations showed that a full HFIR core can be dissolved using nominally 0.002 M Hg to catalyze the dissolution. The margin between the predicted H 2 concentration and the calculated LFL was greater when the solution was allowed to boil for 45 min prior to initiating the Hg addition. When the Hg was increased to 0.004 M, the predicted H 2 concentration exceeded the calculated LFL early in the dissolution. The dissolution experiments also demonstrated that additional Hg (beyond the initial 0.002 M) could be added as the Al concentration increases. The ability to add more Hg during a HFIR fuel dissolution could be beneficial if slow dissolution rates are observed at high Al concentrations. Experimental data were used to demonstrate that the predicted H 2 concentration in a dissolver was below 60% of the calculated LFL at 200 °C when 0.004 M Hg was used to catalyze the dissolution if the Al concentration is conservatively greater than 0.5 M. Data also show that the Hg concentration during a HFIR fuel dissolution can be increased from 0.002 to 0.008 M at an Al concentration of 1.3 M.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Dissolution flowsheet for high flux isotope reactor fuel

As part of the Spent Nuclear Fuel (SNF) processing campaign, H-Canyon is planning to begin dissolving High Flux Isotope Reactor (HFIR) fuel in late FY17 or early FY18. Each HFIR fuel core contains inner and outer fuel elements which were fabricated from uranium oxide (U 3 O 8 ) dispersed in a continuous Al phase using traditional powder metallurgy techniques. Fuels fabricated in this manner, like other SNF’s processed in H-Canyon, dissolve by the same general mechanisms with similar gas generation rates and the production of H 2 . The HFIR fuel cores will be dissolved and the recovered U will be down-blended into low-enriched U. HFIR fuel was previously processed in H-Canyon using a unique insert in both the 6.1D and 6.4D dissolvers. Multiple cores will be charged to the same dissolver solution maximizing the concentration of dissolved Al. The objective of this study was to identify flowsheet conditions through literature review and laboratory experimentation to safely and efficiently dissolve the HFIR fuel in H-Canyon. Laboratory-scale experiments were performed to evaluate the dissolution of HFIR fuel using both Al 1100 and Al 6061 T6 alloy coupons. The Al 1100 alloy was considered a representative surrogate which provided an upper bound on the generation of flammable (i.e., H 2 ) gas during the dissolution process. The dissolution of the Al 6061 T6 alloy proceeded at a slower rate than the Al 1100 alloy and was used to verify that the target Al concentration in solution could be achieved for the selected Hg concentration. Mass spectrometry and Raman spectroscopy were used to provide continuous monitoring of the concentration of H 2 and other permanent gases in the dissolution offgas allowing the development of H 2 generation rate profiles. The H 2 generation rates were subsequently used to evaluate if a full HFIR core could be dissolved in an H-Canyon dissolver without exceeding 60% of the calculated lower flammability limit (LFL) for H 2 at a given Hg concentration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Real-Time Sea State Estimation for Wave Energy Converter Control via Machine Learning

Wave energy converters (WECs) harness the untapped power of ocean waves to generate renewable energy, offering a promising solution to sustainable energy. An optimal WEC control strategy is essential to maximize power capture that dynamically adjusts system parameters in response to rapidly changing sea states. This study presents a novel control approach that leverages neural networks to estimate sea states from onboard WEC measurements such as position, velocity, and force. Using a point absorber WEC device as a test platform, our proposed approach estimates sea states in real-time and subsequently adjusts PID controller gains to maximize energy extraction. Simulation results across diverse sea conditions demonstrate that our strategy eliminates the need for external wave monitoring equipment while maintaining power capture efficiency. The results show that our neural network-based control technique can improve power capture by 25.6% while significantly reducing system complexity. This approach offers a practical alternative for WEC deployments where direct wave measurements are either infeasible or cost prohibitive.

PIDcontrol↗
NASA NTRS1991

Fiber Optic Tactical Local Network (FOTLAN)

A 100 Mbit/s FDDI (fiber distributed data interface) network interface unit is described that supports real-time data, voice and video. Its high-speed interrupt-driven hardware architecture efficiently manages stream and packet data transfer to the FDDI network. Other enhancements include modular single-mode laser-diode fiber optic links to maximize node spacing, optic bypass switches for increased fault tolerance, and a hardware performance monitor to gather real-time network diagnostics.

Bergman, L. A.↗
NASA NTRS1991

A high performance FDDI NIU for streaming voice, video, and data

A 100-Mbit/s FDDI network interface unit (NIU) is described that supports real-time data, voice and video. Its high-speed interrupt-driven hardware architecture efficiently manages stream and packet data transfers to the FDDI network. Other enhancements include modular single-mode laser-dioce fiber optic links to maximize node spacing, optic bypass switches for increased fault tolerance, and a hardware performance monitor to gather real-time network diagnostics.

Bergman, L. A.↗
NASA NTRS1998

Systems Issues Pertaining to Holographic Optical Data Storage in Thick Bacteriorhodopsin Films

The optical data storage capacity and raw bit-error-rate achievable with thick photochromic bacteriorhodopsin (BR) films are investigated for sequential recording and read- out of angularly- and shift-multiplexed digital holograms inside a thick blue-membrane D85N BR film. We address the determination of an exposure schedule that produces equal diffraction efficiencies among each of the multiplexed holograms. This exposure schedule is determined by numerical simulations of the holographic recording process within the BR material, and maximizes the total grating strength. We also experimentally measure the shift selectivity and compare the results to theoretical predictions. Finally, we evaluate the bit-error-rate of a single hologram, and of multiple holograms stored within the film.

Downie, John D.↗
NASA NTRSDate not supplied

Operational Analysis of Vertiport Surface Topology

Urban Air Mobility (UAM) concepts and technologies are being developed to safely enable operations of small, electric-powered or hybrid, pilot-optional, vertical-takeoff-and-landing (VTOL) passenger and cargo aircraft at vertiport facilities in urban and suburban environments. It is likely that many of the highest demand locations for vertiports will be in space constrained urban environments, requiring vertiport designs to maximize throughput within a compact surface footprint. This paper presents several generic vertiport topology design approaches and evaluates their relative surface area utilization and operational efficiency under different wind constrained configurations while meeting safety driven spacing constraints derived from heliport design standards and subject matter expert interviews.

Urban air mobility↗
DOE OSTI2018

Self-Navigating Robotic Assistant for Long-term Wide Area Floor Contamination Monitoring - 18213

For Routine Contamination Testing (RCT) of an operational nuclear facility or one undergoing Decontamination and Decommissioning (D and D), workers utilize specified travel corridors (enclosed hallways or areas designated with tape or rope in open spaces) to minimize the risk of spreading contamination. Radiation health technicians must continually monitor these areas for contamination to minimize worker dose and prevent its spread to uncontrolled areas. For many sites, it is impractical for the technician to adequately survey such areas. The Nuclear Robotics Group (NRG) at UT Austin has developed a self-navigating robotic platform equipped with radiation detectors to augment the technician to improve both survey coverage and frequency. While maintaining a controlled velocity and floor-to-sensor distance, the system takes radiation measurements to identify and/or localize contamination sources. Readings above background levels are reported to a remote workstation to allow technicians to then respond accordingly. The completion of these mundane tasks by a robot allows the trained technicians to focus instead on operational tasks, D and D, or responding to alarms. The robot generates a map using a Lidar range sensor with established Simultaneous Localization and Mapping (SLAM) techniques. Range data is then compared to previously generated maps for robot localization and autonomous navigation. To maximize coverage, the robot executes a Complete Coverage Path Planning (CCPP) algorithm using a static map that is discretized into cells to assure comprehensive yet efficient coverage. As the system executes the generated plan, it builds a radiation map of the area for the technician to validate and verify the results. If contamination is detected, the robot will minimize the spread of contamination by stopping, sounding an alarm, and alerting the remote technician. The proposed system allows for long-term deployment with minimal human intervention. It is robust to both highly dynamic obstacles (i.e. personnel) and low dynamic changes (i.e. temporally stored cart) in the environment. This is accomplished through continuous spatiotemporal updating of the static map, and the utilization of a supervisory controller that allows the system to reliably respond to unexpected events or states (i.e. low battery, closed door, etc.). While the supervisory controller can respond to temporary complications, the system also recognizes the environment can change slowly over time necessitating that the CCPP automatically be updated to account for observed 'permanent' changes to the environment. To do this, the robot uses intermediate probabilistic data to make intelligent planning decisions offline while still maintaining local reactive obstacle avoidance and safety features. The self-updating of the map allows the robot to run longer without the need to remake the map, leading to more consistent monitoring data and less maintenance from the human technician. This paper will review the current system hardware, the CCPP algorithm, the supervisory controller, the probabilistic algorithm for identifying permanent changes, and recent experiments at UT Austin to experimentally validate the reported sensor coverage. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

TOWARD A COMPLETE ACCOUNTING OF ENERGY AND MOMENTUM FROM STELLAR FEEDBACK IN GALAXY FORMATION SIMULATIONS

We investigate the momentum and energy budget of stellar feedback during different stages of stellar evolution, and study its impact on the interstellar medium (ISM) using simulations of local star-forming regions and galactic disks at the resolution affordable in modern cosmological zoom-in simulations. In particular, we present a novel subgrid model for the momentum injection due to radiation pressure and stellar winds from massive stars during early, pre-supernova (pre-SN) evolutionary stages of young star clusters. Early injection of momentum acts to clear out dense gas in star-forming regions, hence limiting star formation. The reduced gas density mitigates radiative losses of thermal feedback energy from subsequent SN explosions. The detailed impact of stellar feedback depends sensitively on the implementation and choice of parameters. Somewhat encouragingly, we find that implementations in which feedback is efficient lead to approximate self-regulation of the global star formation efficiency. We compare simulation results using our feedback implementation to other phenomenological feedback methods, where thermal feedback energy is allowed to dissipate over timescales longer than the formal gas cooling time. We find that simulations with maximal momentum injection suppress star formation to a similar degree as is found in simulations adopting adiabatic thermal feedback. However, different feedback schemes are found to produce significant differences in the density and thermodynamic structure of the ISM, and are hence expected to have a qualitatively different impact on galaxy evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sub-quantum Fisher information

We report the quantum Fisher information (QFI) plays a crucial role in quantum information theory and in many practical applications such as quantum metrology. However, computing the QFI is generally a computationally demanding task. In this work we analyze a lower bound on the QFI which we call the sub-quantum Fisher information (sub-QFI). The bound can be efficiently estimated on a quantum computer for an n-qubit state using 2n qubits. The sub-QFI is based on the super-fidelity, an upper bound on Uhlmann's fidelity. We analyze the sub-QFI in the context of unitary families, where we derive several crucial properties including its geometrical interpretation. In particular, we prove that the QFI and the sub-QFI are maximized for the same optimal state, which implies that the sub-QFI is faithful to the QFI in the sense that both quantities share the same global extrema. Based on this faithfulness, the sub-QFI acts as an efficiently computable surrogate for the QFI for quantum sensing and quantum metrology applications. Finally, we provide additional meaning to the sub-QFI as a measure of coherence, asymmetry, and purity loss.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Prioritizing circular economy strategies for sustainable PV deployment at the TW scale

Global decarbonization requires an unprecedented scale-up of photovoltaic (PV) manufacturing and deployment. The material demand and eventual end of life management associated with multi-TW scale deployment poses many challenges. Circular Economy (CE) and it's associated R-Actions (Reduce, Reuse, Recycle) have been proposed to mitigate end of life management and material sourcing concerns. However, CE metrics typically focus on a single product and only consider mass, excluding energy flows. This work leverages the PV in Circular Economy (PV ICE) tool to quantify the deployment, mass, and energy impacts of R-Actions and proposed sustainable PV designs in the context of achieving energy transition deployment goals (75 TW in 2050). 13 module scenarios are established and evaluated across 6 capacity, mass and energy metrics to identify tradeoffs and priorities. We find that increasing module efficiency can reduce near-term material demands up to 30% and improve energy metrics by up to 9%. Material circularity (recycling) can minimize lifecycle wastes and reduce material demands at the cost of higher energy demands. Increasing module lifetime, including reliability improvements and reuse strategies, is effective at reducing both material (>10%) and energy demands (24%). Uniquely, lifetime improvements maximize benefits and minimize the harms across all six metrics while achieving multi-TW scale deployment.

Photovoltaics↗
DOE OSTI2014

Center for Energy Efficient Materials (CEEM) (Final Technical Report)

The mission of the Center for Energy Efficient Materials (CEEM) was to serve the Department of Energy and the nation as a center of excellence dedicated to advancing basic research in nano-structured materials and devices for applications to solar electricity, thermoelectric conversion of waste heat to electricity, and solidstate lighting. The foundation of CEEM was based on the unique capabilities of UCSB and its partner institutions to control, synthesize, characterize, model, and apply materials at the nanoscale for more efficient sustainable energy resources. This unique expertise was a key source of the synergy that unified the research of the Center. Although the Center’s focus was basic research, It’s longer-term objective has been to transfer new materials and devices into the commercial sector where they will have a substantial impact on the nation’s need for efficient sustainable energy resources. As one measure of the impact of the Center, two start-up companies were formed based on its research. In addition, Center participants published a total of 210 archival journal articles, of which 51 were exclusively sponsored by the DOE grant. The work of the Center was structured around four specific tasks: Organic Solar Cells, Solid-State Lighting, Thermoelectrics, and High Efficiency Multi-junction Photovoltaic devices. A brief summary of each follows – detailed descriptions are in Sections 4 & 5 of this report. Research supported through CEEM led to an important shift with respect to the choice of materials used for the fabrication of solution deposited organic solar cells. Solution deposition opens the opportunity to manufacture solar cells via economically-viable high throughput tools, such as roll to roll printing. Prior to CEEM, most organic semiconductors utilized for this purpose involved polymeric materials, which, although they can form thin films reliably, suffer from batch to batch variations due to the statistical nature of the chemical reactions that produce them. In response, the CEEM team developed well-defined molecular semiconductors that produce active layers with very high power conversion efficiencies, in other words they can convert a very high fraction of sunlight into useful electrical power. The fact that the semiconductor is formed from molecular species provides the basis for circumventing the unreliability of polymer counterparts and, as an additional bonus, allows one to attain much grater insight into the structure of the active layer. The latter is particularly important because efficient conversion is the result of a complex arrangement of two semiconductors that need to phase separate in a way akin to oil and water, but with domains that are described by nanoscale dimensions. CEEM was therefore able to provide deep insight into the influence of nanostructure, through the application of structural characterization tools and theoretical methods that describe how electrical charges migrate through the organic layer. Our research in light emitting diode (LED)-based solid state lighting (SSL) was directed at improving efficiency and reducing costs to enable the widespread deployment of economically-viable replacements for inefficient incandescent, halogen, and fluorescent-based lighting. Our specific focus was to advance the fundamental science and technology of light emitting diodes to both understand factors that limit efficiencies and to provide innovative and viable solutions to the current impediments. One of the main challenges we faced is the decrease in efficiency when LEDs are driven harder to increase light output---the so called “droop” effect. It requires large emitting surfaces to reach a desired optical output, and necessitates the use of costly heat sinks, both of which increase the cost. We successfully reduced droop by growing LED crystals having non-conventional orientations. As recognized by the award of the 2014 Nobel prize to the inventors of the nitride LEDs (one of whom was a member of CEEM), LEDs already have a large societal impact in both developed (leading to large energy savings) and developing countries (bringing light where there is no electrical grid). The improvements in efficiency sought after in the CEEM project are key to a further impact of solid state lighting by LEDs with a projected doubling in efficiency by year 2020. Direct generation of electricity from heat has enormous promise for beneficial use of waste heat. But practical power generation directly from heat requires understanding and development of new and improved materials that will be more efficient and rugged than today’s thermoelectric materials. To accomplish this goal CEEM has synthesized five distinct and promising new classes of thermoelectric materials: (a) nanoparticle arrays that are effective in maximizing electric power generation and reducing detrimental loss of heat; (b) nitride and (c) oxide thermal electric materials that are effective at high temperatures where much beneficial heat is available; (d) arrays of silicon nano-wires that integrate thermal electricity generation into silicon-based electronics and materials; and (e) chemically synthesized nanostructured compounds that are cost effective, earth abundant, and environmentally friendly. The further development of these thermoelectric sources of electricity could have revolutionary impact for society in the recovery of waste heat from sources such as power plants and automobile exhaust, where there could be significant associated energy saving. It could even, in the future, provide disruptive alternatives and replacements for today’s internal combustion engines and could enable improved all-electric propulsion by the heat from shipboard nuclear reactors. The High Efficiency Multi-junction Photovoltaics task was a UCSB/NREL collaboration which bonded sub-cells from two different compound semiconductors material systems to make high efficiency multijunction solar cells for concentrating photovoltaic applications thathave substantially higher efficiency than single substrate cells made of elemental semiconductors such as silicon. This task required the development of new cell bonding methods with excellent coupling of both photons and electrons between the sub-cells. To accomplish this, we developed (1) GaInN solar cells with enhanced performance by using quantum-well absorbers and front-surface optical texturing, (2) a hybrid "pillar-array" bond which uses an array of metal pillars for electrical coupling, and (3) a "hybrid moth-eye" optical coating which combines the benefits of nano-imprinted moth-eye coatings and traditional multilayer coatings. The technical effectiveness was assessed by measurement of the photovoltaic efficiency of solar cells made using these techniques; the ultrahigh efficiencies targeted by this work are of compelling economic value for concentrating photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2020

Brilliant Execution of Smart Labs: Employing Best Practices to Improve Safety and Reduce Energy for Sustainable Labs: Preprint

Laboratory buildings often dominate the energy use on research campuses, consuming three to four times the energy of a typical office building. In most cases, these facilities are defined as “mission critical,” with excessive energy use as simply an unfortunate truth that cannot be avoided without compromising safety. However, case studies indicate cost savings opportunities of up to 40% in laboratories (compared to standard practices) by employing energy efficient design strategies that also improve the safety of lab spaces (Better Buildings 2018). To help stakeholders implement improvement measures, the Smart Labs Toolkit describes a proven approach to optimizing performance of laboratories and critical control environments in new or existing facilities. The Toolkit outlines distinct phases for building a successful Smart Labs program that include: Plan, Assess, Optimize, and Manage. Each phase has specific tasks, training videos, and resources to educate users, support the efforts of key stakeholders, and maximize benefits for the organization in implementing high-performance labs. The Toolkit also includes case studies from the 17 Better Buildings Smart Labs Accelerator partners, sharing lessons learned and supporting the Smart Labs approach to safe, efficient world class science. This paper reviews the technology choices for implementing Smart Labs ventilation strategies, controls, and other efficiency measures. Better Building Smart Lab Accelerator partners provide case study examples of safety and energy-savings results of using Smart Labs approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Privacy by Design in Distributed Edge Systems: Innovating Secure Workflows for Smart Cities

The proliferation of distributed edge systems, such as those in smart cities, healthcare, and industrial IoT, offers unprecedented opportunities for data processing closer to its source, thereby reducing latency and enhancing efficiency. However, these systems also present significant privacy challenges due to the handling of sensitive data from multiple sources. This article explores the critical need for designing privacy-preserving workflows in distributed edge systems to ensure data security while maximizing the potential of edge computing. By examining the challenges, technological advancements, and potential of privacy-by-design approaches, we highlight the importance of integrating advanced privacy-preserving techniques like federated learning, differential privacy, homomorphic encryption, secure multi-party computation, and zero-knowledge proofs. These innovations are crucial for enhancing data security, regulatory compliance, and public trust in smart city applications, ultimately leading to safer and more efficient urban environments.

Kotevska, Olivera↗