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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modeling charging infrastructure impact on the electric vehicle market in China

The plug-in electric vehicle (PEV) is deemed as a critical technological revolution, and the governments are imposing various vehicle policies to promote its development. Meanwhile, the market success of PEVs depends on many aspects. The study reported herein integrates one’s use of charging infrastructure at home, public place and workplace into the market dynamics analysis tool, New Energy and Oil Consumption Credits (NEOCC) model, to systematically assess the charging infrastructure (home parking ratio, public charging opportunity, and charging costs) impact on PEV ownership costs and analyze how the PEV market shares may be affected by the attributes of the charging infrastructure. Compared to the charging infrastructure, the impact of battery costs is incontrovertibly decisive on PEV market shares, the charging infrastructure is still non-negligible in the PEV market dynamics. The simulation results find that the public charging infrastructure has more effectiveness on promoting the PEV sales in the PEV emerging market than it does in the PEV mature market. However, the improvement of charging infrastructure does not necessarily lead to a larger PEV market if the charging infrastructure incentives do not coordinate well with other PEV policies. Besides, the increase of public charging opportunities has limited motivations on the growth of public PEV fleets, which are highly correlated to the number of public fast charging stations or outlets. It also finds that more home parking spaces can stimulate more sales of personal plug-in hybrid electric vehicles instead of personal battery electric vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Convergence of Public-Private Benefits in Denver: Surveys and Analyses to Inform Urban Mobility-, Energy-, Infrastructure- and Behavior-Related Innovation: Preprint

Cities, public transit agencies, and new private ride hailing services seek to understand emerging traveler dynamics, the shifting demographics of urban travelers,and new energy-efficient mobility opportunities. This includes exploring how new infrastructure investments, public and private mobility services, and smart-phone mobility apps are reshaping behaviors, demands (e.g. mobility-on-demand services), travel experiences and energy-efficient urban travel preferences. Currently, cities and metropolitan regions are providing and experimenting with many new mobility options, technologies, and personalized information services at the intersection of urban mobility, energy, and infrastructure systems (e.g., new commuter rail). To date, technology alone has not been able to crack the nut of 'creating faster trip times, less congestion, safer streets, and cleaner air for its citizens through fewer cars on the road'. This paper focuses on this gap by offering new concepts and potential for integrated approaches. Accommodating more vehicles miles traveled in cities, without increases in person miles traveled (PMT), could be costly, generating: 1) tremendous demands for new infrastructure, land, road space, materials, and energy; 2) higher traffic fatality risks; and 3) worsening air quality. Therefore, this study focuses on reducing single occupancy vehicle use by enhancing integrated mobility, helping transit and ridehailing increase occupancy in ways that also reduce energy use, and improve quality of life for urban travelers and communities. This study focuses on a survey of urban travelers in Denver, as a representative case study for metropolitan regions experiencing rapid growth, ageing populations, increased urban sprawl, traffic-related delays, and inefficient energy use per PMT.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Particle resuspension: Challenges and perspectives for future models

Using what has become a celebrated catchphrase, Philip W. Anderson once wrote that “more is different” (Science, Vol. 177, Issue 4047, pp. 393–396, 1972). First formulated in the context of condensed matter, this statement carries far beyond the sole limits of solid-state physics. It emphasizes that collective behavior can be more than the mere sum of what happens for elementary constituents or the mere collation of the evolution of each degree of freedom. Said otherwise, complex phenomena can arise out of the interplay between multiple sub-phenomena each of which can be relatively simple. The process of particle resuspension, in which discrete particles adhering on a surface are pulled off and carried away by a fluid flow, is another example involving a web of phenomena pertaining to fluid mechanics, particle dynamics and interface chemistry whose cross-effects create an intricate topic. The purpose of this review is to analyze the physics at play in particle resuspension in order to bring insights into the rich complexity of this common but challenging concern. Following the more-is-different vision, this is performed by starting from a range of practical observations and experimental data. We then work our way through the investigation of the key mechanisms which play a role in the overall process. In turn, these mechanisms reveal an array of fundamental interactions, such as particle–fluid, particle–particle and particle–surface, whose combined effects create the tapestry of current applications. At the core of this analysis are descriptions of these physical phenomena and the different ways through which they are intertwined to build up various models used to provide quantitative assessment of particle resuspension. The physics of particle resuspension implies to hold together processes occurring at extremely different space and time scales and models are key in providing a single vehicle to lead us through such multiscale journeys. This raises questions on what makes up a model and one objective of the present work is to clarify the essence of a modeling approach. In spite of its ubiquitous nature, particle resuspension is still at the early stages of developments. Many extensions need to be worked out and revisiting the art of modeling is not a moot point. The need to consider more complex objects than small and spherical particles and, moreover, to come up with unified descriptions of mono- and multilayer resuspension put the emphasis on solid model foundations if we are to go beyond current limits. Further, this is very much modeling in the making and new ideas are proposed to stimulate interest into this everyday but challenging issue in physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

California Price Response Potential Study

California's energy landscape is undergoing a significant transformation, driven by the increasing integration of renewable energy sources, the increased adoption of distributed energy resources, the electrification of end-use loads, and the growing need for grid efficiency. To address these challenges, recent revisions to the State’s Load Management Standards (LMS) require all of California’s large utilities and community choice aggregators (CCAs) to offer dynamic electricity pricing options to customers by 2027. Dynamic pricing, which involves varying electricity rates based on real-time supply and demand conditions, offers a promising solution for optimizing grid operations, reducing costs, and incentivizing efficient use of grid capacity. Effective implementation of dynamic pricing requires understanding the potential impacts on customer bills, system load, and the cost-effectiveness of automation technologies. This study aims to evaluate the load response of various end-use devices to hourly dynamic prices. The end-uses studied here are space cooling, space heating, water heating, crop irrigation, pool and spa pumps, and electric vehicle (EV) charging, all for both residential and commercial applications, except for crop irrigation. In 2030, these end uses are forecasted to account for 18% of annual electricity demand in the state, but 40% of demand in the peak net load hour. By modeling possible price-responsive load dispatch algorithms and assessing the resulting impacts on both individual bills and the overall grid, we seek to inform policymakers and utilities about the potential benefits and challenges associated with dynamic pricing, and considerations for the design of dynamic pricing tariffs. Additionally, we will explore the cost effectiveness of adopting automation technologies to enable devices to respond more effectively to real-time price signals. This study considers a range of price profiles, accounting for differences across utilities and customer classes, and presents scenarios for dynamic price design via variation in the percentage of total customer electric costs that are allocated dynamically (versus constituting a fixed portion of the hourly volumetric price). We present results focused primarily on 2030, forecasting electricity prices under both low and high-cost scenarios, to inform longer-term tariff design considerations. We design tariffs by starting with 2019 prices that were calculated according to CalFUSE guidance (CPUC, 2022) and that have been used in recent studies; these prices are all-in volumetric rates that vary by utility and are revenue-neutral to each customer class. They are developed by considering six electricity cost components that are allocated hourly based on system load indicators (gross and net load, and wholesale prices). These prices are forecasted to 2030 for low and high cost scenarios, considering recent trends in total electricity costs with and without years of substantial wildfire mitigation investments. These tariffs, which allocate all costs on an hourly basis, are considered our “Full” dynamic tariff design scenario, while two additional scenarios explore allocating a portion of costs as a flat volumetric charge: the “Medium” scenario allocates 50% of revenue dynamically (and keeps 50% flat), while the “Mild” scenario allocates 20% of revenue dynamically. The 20% dynamic allocation on the Mild scenario aims to represent a case where only the marginal operating costs of the grid are included in the dynamic price.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Propulsion Electrification Architecture Selection Process and Cost of Carbon Abatement Analysis for Heavy-Duty Off-Road Material Handler

The heavy-duty off-road industry continues to expand efforts to reduce fuel consumption and CO 2 e (carbon dioxide equivalent) emissions. Many manufacturers are pursuing electrification to decrease fuel consumption and emissions. Future policies will likely require electrification for CO2e savings, as seen in light-duty on-road vehicles. Electrified architectures vary widely in the heavy-duty off-road space, with parallel hybrids in some applications and series hybrids in others. The diverse applications for different types of equipment mean different electrified configurations are required. Companies must also determine the value in pursuing electrified architectures; this work analyzes a range of electrified architectures, from micro hybrids to parallel hybrids to series hybrids to a BEV, looking at the total cost, total CO 2 e, and cost per CO 2 e (cost of carbon abatement, or cost of carbon reduction) using data for the year 2021. This study is focused on a heavy-duty off-road material handler, the Pettibone Cary-Lift 204i. This machine’s specialty application, including events like unloading large oil pipes from a railcar, requires a unique electrified architecture that suits its specific needs. However, the results from this study may be extrapolated to similar machinery to inform fuel savings options across the heavy-duty off-road industry. In this study, a unique electrified architecture is determined for the Cary-Lift. This architecture is informed by multiple rounds of a Pugh matrix decision analysis to select a shortened list of desirable electrified architectures. The shortened list is modeled and simulated to determine CO 2 e, cost, and cost per CO 2 e. A final architecture is determined as a plug-in series hybrid that reduces fuel consumption by 65%, targeting the large fuel and CO 2 e savings that are likely to be required for the future of the heavy-duty off-road industry.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Sustainable Public Transport: Providing Responsive, On-Demand Service with Clean Energy

The National Renewable Energy Laboratory (NREL) uses the Mobility Energy Productivity (MEP) as a metric and a lens to guide applied research into high performance public mobility. In the current initiative to abate global warming, the US needs not only zero-emission vehicles in the transit fleet (such as buses and shuttles) but also time- and cost-effective services to connect people with goods, services and employment toward a high-quality of life. Our current transportation system is overly dependent on personally-owned automobiles for high quality mobility, with public modes being less viable in many areas. Simply electrifying the drivetrains of existing public transit modes will fail to improve the quality of mobility for those that do not have access to private automobiles. The slow rebound by transit from the pandemic reveals the need to reinvent public transit service. Using the MEP lens, NREL researchers have tracked various novel developments in the public mobility space, with the confluence of shared, on-demand transit (ODT) services using light duty vehicles emerging as a key enabler of high-efficiency public mobility. Deployments such as those in Arlington, TX, Dallas, TX, Fort Erie, ON, and Innisfil, ON showcase the use of fleets of light-duty vehicles as the basis for community circulation and first/last mile to intra-regional transit. ODT services have demonstrated improvements in being more time efficient for riders, more energy efficient in operation (even before the introduction of fully electric vehicles), as well as being cost effective. It appears that aspects of the long-awaited promise of Personal Rapid Transit from the 1970s are beginning to be realized through ODT deployments, leveraging transportation network company (TNC) logistics, popularized by Uber and Lyft, but applied to public mobility. Currently, manually driven ODT operations are already cost competitive with traditional transit systems on a cost per ride basis, and full automation promises to reduce costs by 50% while providing additional safety and verified customer service. Connecting these ODT systems with efficient and effective intra-regional backbone transit service is the next step, with transit agencies like DART providing early results. This discussion will walk through the evidence for this postulated outcome and show results from a series of case-studies.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

Photovoltaic device innovation for a solar future

Photovoltaics (PV), also known as solar cells, are now found everywhere - in utility plants; on roofs of homes and commercial buildings; on platforms at sea; in agricultural fields; on vehicles, buildings, drones, and backpacks; and, in their longest running application, providing power in space. Continuous device innovation has led to increased efficiency and improved reliability for multiple PV technologies. Confronted with an urgent need to deploy PV at multiterawatt (TW) scale over the next two decades to mitigate greenhouse gas emissions, PV device innovation takes on new urgency and impact. This perspective reviews recent progress in device design and performance for PV technologies that are currently in commercial production at greater than 1 GW/year or enabling significant space-based power generation - Si, CdTe, CIGS, and multijunction III-V - and looks ahead to the next 5 years. In conclusion, we also identify device-related topics requiring cross-cutting research and innovation.

14 SOLAR ENERGY↗
DOE OSTI2022

A branch-and-price algorithm for a team orienteering problem with fixed-wing drones

This paper formulates a team orienteering problem with multiple fixed-wing drones and develops a branch-and-price algorithm to solve the problem to optimality. Fixed-wing drones, unlike rotary drones, have kinematic constraints associated with them, thereby preventing them to make on-the-spot turns and restricting them to a minimum turn radius. This paper presents the implications of these constraints on the drone routing problem formulation and proposes a systematic technique to address them in the context of the team orienteering problem. Furthermore, a novel branch-and-price algorithm with branching techniques specific to the constraints imposed due to fixed-wing drones are proposed. Extensive computational experiments on benchmark instances corroborating the effectiveness of the algorithms are also presented.

42 ENGINEERING↗
DOE OSTI2026

An On-Demand Electric Transit Case Study of New Rochelle, New York

Here, this article characterizes the performance and ridership patterns of an on-demand transit (ODT) service utilizing lightweight electric vehicles (EVs) in New Rochelle, New York. Ridership sociodemographics, travel patterns (both temporal and spatiotemporal), and energy use from the service were explored using travel and survey data from September 2019 through December 2023. The ODT service was found to be used more by women (nearly 60%) and younger demographics (>65% under the age of 42), with peak use in the middle of the day and a grocery store as a top origin and destination. The service was utilized primarily for short trips (86% under 2 mi), with approximately one-third of riders using the ODT service to connect to a train or bus. The costs associated with fueling/charging were compared for different types of fleet vehicles, and the small, right-sized EVs were found to have annual charging costs that were roughly half of the refueling costs for conventional hybrid vans, and 24 times lower than a fleet of diesel buses. Evaluating the vehicle fleet and mapping current socio-spatial travel demand can inform system performance, guide service area development, and support future planning such as expansion to nearby communities and transit hubs. The findings in this case study suggest that on-demand electric transit may be a significant and growing space for advancing highly valued public mobility services. Public transport interventions that consider right-sized, electric, on-demand vehicles can help improve mobility access and reduce energy use and refueling costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Quantum Computing in Next-Generation Transportation Optimization

We explore how quantum computing (QC) can advance transportation optimization, with a focus on two high-impact areas: traffic signal control and vehicle electrification with grid integration. As transportation systems grow in complexity, classical optimization methods increasingly struggle to deliver scalable and efficient solutions, particularly for real-time, data-rich environments. This work identifies key challenges within these two domains where QC may offer advantages, particularly in handling combinatorial decision spaces and dynamic constraints. We begin by outlining the limitations of classical approaches for traffic signal control optimization and electric vehicle charging coordination, highlighting where computational limitations arise. Previous quantum formulations are presented and new formulations are proposed to demonstrate how emerging quantum algorithms, including quantum annealing and the Quantum Approximation Optimization Algorithm, could be leveraged to reformulate and address these problems. We also evaluate the suitability of current quantum hardware and discuss recent trends that indicate when QC may become a viable tool for transportation applications. While acknowledging the present limitations of QC technologies, this poster emphasizes the importance of preparing quantum-compatible models today. By reviewing and establishing formulations that align with the strengths of quantum algorithms, researchers and practitioners can better position themselves to take advantage of QC advancements as they occur. This work aims to provide a practical, forward-looking perspective on the near-term potential of quantum computing in transportation optimization.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Assessment of Near-Term Fuel Screening and Qualification Needs for Nuclear Thermal Propulsion Systems

Nuclear thermal propulsion (NTP) is an in-space propulsion technology capable of both high specific impulse (850–1000 s) and thrust (44–1112 kN), which can help reduce trip times for crewed missions beyond low Earth orbit. NTP technology has been demonstrated during historic programs. Over 20 ground test reactor experiments were performed, which demonstrated the prototypic reactor operations, during the Nuclear Engine for Rocket Vehicle Application (NERVA)/Rover program (1955–1972). Although historical programs have shown that NTP is a viable in-space propulsion technology, developing NTP in modern programs is contingent on the development and qualification of ultrahigh-temperature nuclear fuel technologies that can withstand engine operating conditions. In historical NTP development programs such as NERVA/Rover, prototypic reactor/engine schemes were ground tested to assess the overall system feasibility and to qualify the reactor fuel forms for eventual flight systems. Although this approach is effective to verify fuel performance under prototypic conditions, relying solely on full-scale NTP reactor tests as the pathway for verifying or qualifying fuel is inefficient and cost prohibitive today. Additionally, modern nuclear licensing requirements state that before test reactor approval, reactor components and fuel elements should be qualified via non-nuclear (out-of-pile) and nuclear (in-pile) testing under representative operating conditions. Using this methodology, fuel matures as production scale fabrication methods are established, and as produced fuel performance is demonstrated. Here, this paper provides an overview of historical approaches to NTP fuel performance maturation, including fuel screening and qualification needs, and provides insight for establishing an efficient testing paradigm that can be implemented to rapidly and affordably develop NTP fuel forms for eventual qualification.

42 ENGINEERING↗
DOE OSTI2025

Secure and Privacy Aware Data Sharing Approach for Smart Electric Vehicles

The integration of smart electric vehicles (SEVs) into smart cities marks a significant step toward creating efficient, sustainable, and connected urban spaces. However, secure and private data sharing is a major challenge as SEVs connect with smart city systems. The interaction between SEVs and consumer electronic devices (CEDs) raises serious concerns about data security and privacy. Here, to address these challenges, this article presents how blockchain technology and federated learning (FL) can address these issues. The proposed approach provides a secure and privacy-aware framework for data exchange between SEVs and CEDs in smart cities. The experiment results demonstrate the effectiveness of the proposed framework for secure data sharing and maintaining system reliability in smart city environments. It also enables trust and promotes the widespread adoption of interconnected urban technologies.

Das, Debashis [Meharry Medical College, Nashville,↗
DOE OSTI2024

Extracting Vehicle Trajectories from Partially Overlapping Roadside Radar

This work presents a methodology for extracting vehicle trajectories from six partially-overlapping roadside radars through a signalized corridor. The methodology incorporates radar calibration, transformation to the Frenet space, Kalman filtering, short-term prediction, lane-classification, trajectory association, and a covariance intersection-based approach to track fusion. The resulting dataset contains 79,000 fused radar trajectories over a 26-h period, capturing diverse driving scenarios including signalized intersections, merging behavior, and a wide range of speeds. Compared to popular trajectory datasets such as NGSIM and highD, this dataset offers extended temporal coverage, a large number of vehicles, and varied driving conditions. The filtered leader–follower pairs from the dataset provide a substantial number of trajectories suitable for car-following model calibration. The framework and dataset presented in this work has the potential to be leveraged broadly in the study of advanced traffic management systems, autonomous vehicle decision-making, and traffic research.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Formation and reconfiguration of tight multi-lane platoons

Advances in vehicular communication technologies are expected to facilitate cooperative driving in the future. Connected and Automated Vehicles (CAVs) are able to collaboratively plan and execute driving maneuvers by sharing their perceptual knowledge and future plans. In this paper, an architecture for autonomous navigation of tight multi-lane platoons traveling on public roads is presented. Using the proposed approach, CAVs are able to form single or multi-lane platoons of various geometrical configurations. They are able to reshape and adjust their configurations according to changes in the environment. The proposed architecture consists of two main components: an offline motion planner system and an online hierarchical control system. The motion planner uses an optimization-based approach for cooperative formation and reconfiguration in tight spaces. A constrained optimization scheme is used to plan smooth, dynamically feasible and collision-free trajectories for all the vehicles within the platoon. The paper addresses online computation limitations by employing a family of maneuvers precomputed offline and stored on a look-up table on the vehicles. The online hierarchical control system is composed of three levels: a traffic operation system (TOS), a decision-maker, and a path-follower. The TOS determines the desired platoon reconfiguration. The decision-maker checks the feasibility of the reconfiguration plan based on real-time information about the surrounding traffic. The reconfiguration maneuver is executed by a low-level path-following feedback controller in real-time. The effectiveness of the approach is demonstrated through simulations of three case studies: (1) formation reconfiguration (2) obstacle avoidance, and (3) benchmarking against behavior-based planning in which the desired formation is achieved using a sequence of motion primitives.

42 ENGINEERING↗
DOE OSTI2025

A Mössbauer Spectroscopy Investigation of Nickel‐Zinc Ferrites Synthesized by a Self‐Combustion Method for Soft Magnetic Core Applications

Soft ferrites are materials of interest for magnetic cores, as used for wireless charging transformers. Their low permeabilities, high resistivity, and magnetic polarization make them interesting for high-power electric vehicle charging and drive systems. The nickel-zinc-doped ferrites are of particular interest; however, the compositional space is quite large with respect to dopant concentrations, stoichiometric ratios and synthesis technique. Nickel-zinc spinel ferrites with varying nickel-zinc ratios prepared by a self-combustion reaction followed by heat treatment exhibit good crystallinity, and their low-temperature Mössbauer spectra show local magnetism and site occupation in agreement with materials prepared by solid-state reaction. Thus, the combustion synthesis method offers a facile tunability of compositions, which, combined with the possibility of rapid characterization of atomic-scale magnetism by Mössbauer spectroscopy, enables advances in the compositional and processing space at a fast pace. Low-temperature Mössbauer spectroscopy data for samples with increasing nickel content reveals a systematic increase in average hyperfine field (2.8 T/Ni) and decrease in average isomer shift (−0.036 mm/s/Ni) that can determine the nickel/zinc content, even in the absence of applied magnetic field data. Furthermore, a gradual evolution of color is also observed with increasing nickel content, albeit trends in color depend on sintering conditions.

Mössbauer spectroscopy↗
DOE OSTI2024

Overview of Building Electrification Technologies and Market Opportunities

This report provides an overview of building electrification drivers and select building electrification technologies and their markets and performance. Covered topics: Building Electrification Drivers and Context; Heat Pumps for Space Conditioning; Heat Pump Market Opportunities; Life Cycle GHG Emissions Impacts of Heat Pump Space Conditioning Technologies; Heat Pump Water Heaters; Electrification of Gas Loads: Commercial and Residential; Residential Panel Capacity; Electric Vehicle Impacts and Connections to Buildings; and Building Envelope Improvements and Thermal Energy Storage (TES) Opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗