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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Parametric study of operating conditions of an SO 2 -depolarized electrolyzer

Large-scale hydrogen generation is needed to satisfy both existing commercial demands and the realization of a hydrogen economy. The hybrid sulfur cycle has the potential to meet this goal without the use of fossil fuels. The ability to model and predict how the electrolyzer step of the cycle is affected by independent and interdependent variables is vital to maximizing the efficiency of the overall cycle. Herein, we report that our parametric study of the SO 2 -depolarized electrolyzer, representing one half of the overall reaction cycle, has identified desirable conditions and will help guide further development for operation that will achieve the benchmarks for economic feasibility. We discuss the interactions among the inlet flow rates, applied current, and cell temperature and pressure, on the resulting cell voltage and acid concentration in the liquid product stream. For example, we find that using a sulfonated polybenzimidazole (s-PBI) membrane and a platinum catalyst, a constant current density of either 0.5 A cm -2 , 0.75 A cm -2 , or 1 A cm -2 with an acid concentration of 65 wt% H 2 SO 4 can be produced at a cell voltage of 0.59 V, 0.63 V, and 0.67 V, respectively, by maintaining a cell temperature of 130 °C, a pressure of 2 bar, and a water-to-SO 2 stoichiometry of 2.77. Finally, we discuss directions for future research based on the findings in this manuscript.

08 HYDROGEN↗
DOE OSTI2014

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principal components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Transition state stabilization depends on solvent identity, pore size, and hydrophilicity for epoxidations in zeolites

Ti-silicates activate H 2 O 2 to form Ti-hydroperoxo and Ti-peroxo intermediates that can react with alkenes to form epoxide products. Comparisons of kinetics for 1-octene epoxidation with H 2 O 2 on Ti-BEA and Ti-MFI catalysts with different hydrophilicities in methanol (CH 3 OH) or acetonitrile (CH 3 CN) solvents show the significance of the solvent for stabilizing catalytically-relevant species and the complex interdependencies between solvent, catalyst topology, and hydrophilicity. Epoxidation turnover rates are higher in CH 3 CN than CH 3 OH for Ti-BEA, but the opposite trend is observed for Ti-MFI. Ti-silicates with greater silanol densities, however, give greater epoxidation turnover rates than their hydrophobic counterparts in both solvents. Kinetic, spectroscopic, and thermodynamic analyses show that differences in turnover rates mainly arise from changes in the stabilization of reactive surface species by solvent mediated interactions, because the mechanism of the reaction and stability of the fluid-phase reactants remain similar in CH 3 CN and CH 3 OH. Specifically, apparent activation free energy values ($ΔG^{‡}_{App}$) indicate that surface intermediates responsible for alkene epoxidation are stabilized to a greater extent in CH 3 CN on Ti-BEA and in CH 3 OH on Ti-MFI. Hydrophilic Ti-silicates present lower ($ΔG^{‡}_{App}$) values regardless of solvent identity, which suggests that these differences correspond to the number of hydrogen-bonding solvent molecules found near reactive species bound to Ti active sites. Finally, taken together, these findings demonstrate the role of solvent molecules in allowing reactive intermediates to recognize the properties of active sites beyond the length-scale of covalent bonds, which carry implications for epoxidation but also other reactions within solvent-filled pores of microporous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Analysis of water–energy nexus and trends in support of the sustainable development goals: A study using longitudinal water–energy use data

Water and energy are two critical natural resources necessary for human activities and socioeconomic development. Water and energy systems are highly interdependent, and water efficiency and energy efficiency are two related indicators for the United Nations' Sustainable Development Goals. It is critical to improve energy–water use efficiency to sustain socioeconomic development while reducing adverse effects on natural resources, society and the environment. By using longitudinal energy–water use data for China over the past 21 years, this paper develops a temporo-spatial study to address key issues and introduce analytical approaches needed to understand the water–energy nexus and support integrated resource planning and management to achieve the Sustainable Development Goals. Decomposition analysis indicates that the production effect was the dominating factor contributing the increase in the country's energy–water use, while energy–water efficiency is the major factor slowing the growth of the country's energy–water use. Changes and trends analyses show that the country's energy intensity, water intensity, and water/energy ratio significantly decreased from 1999 to 2019, but the rate of decline has slowed. The disparities of the country's provincial energy intensities, water intensities, and water/energy ratios significantly decreased with economic growth. Results suggest that improving energy–water efficiency is critical for the country to curb increasing energy and water use and achieve resource and environmental protection targets with rapid economic development. Furthermore, the disparities between regional energy-water efficiencies can be reduced along with economic growth, while an overheated economy can widen the disparities and result in unsustainable and inefficient utilization of resources. Government coordination, targets and policy as part of the efficiency governance system are critical for continuous energy–water efficiency improvement and directly influence the implementation and effectiveness of energy–water efficiency policy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

A multiphase three-dimensional multi-relaxation time (MRT) lattice Boltzmann model with surface tension adjustment

The interdependence of surface tension and density ratio is a weakness of pseudo-potential based lattice Boltzmann models (LB). In this paper, we propose a 3D multi-relaxation time (MRT) model for multiphase flows at large density ratios. The proposed model is capable of adjusting the surface tension independently of the density ratio. We also present the 3D macroscopic equations recovered by the proposed forcing scheme. A high order of isotropy for the interaction force is used to reduce the amplitude of spurious currents. The proposed 3D-MRT model is validated by verifying Laplace's law and by analyzing its thermodynamic consistency and the oscillation period of a deformed droplet. The model is then applied to the simulation of the impact of a droplet on a dry surface. Impact dynamics are determined and the maximum spread factor calculated for different Reynolds and Weber numbers. The numerical results are in agreement with data published in the literature. The influence of surface wettability on the spread factor is also investigated. Finally, our 3D-MRT model is applied to the simulation of the impact of a droplet on a wet surface. The propagation of transverse waves is observed on the liquid surface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

The effect of Na on Cu-K-In-Se thin film growth

Co-evaporation of Cu-KF-In-Se was performed on substrates with varied Na supply. Compositions of interest for photovoltaic absorbers were studied, with ratios of (K + Cu)/In ~ 0.85 and K/(K + Cu) ~ 0-0.57. Bare soda-lime glass (SLG) substrates had the highest Na supply as measured by secondary ion mass spectrometry, while SLG/Mo and SLG/SiO 2 /Mo substrates led to 3x and 3000x less Na in the growing film, respectively. Increased Na supply favored Cu 1-x K x InSe 2 (CKIS) alloy formation as proven by X-ray diffraction (XRD), while decreased Na supply favored the formation of CuInSe 2 + KInSe 2 mixed-phase films. Scanning electron microscopy and energy dispersive X-ray spectroscopy revealed the KInSe 2 precipitates to be readily recognizable planar crystals. Extrinsic KF addition during film growth promoted diffusion of Na out from the various substrates and into the growing film, in agreement with previous reports. Time-resolved photoluminescence showed enhanced minority carrier lifetimes for films with moderate K compositions (0.04 < K/(K + Cu) < 0.14) grown on SLG/Mo. Due to the relatively high detection limit of KInSe 2 by XRD and the low magnitude of chalcopyrite lattice shift for CKIS alloys with these compositions, it is unclear if the lifetime gains were associated with CKIS alloying, minor KInSe 2 content, or both. The identified Na-K interdependency can be used to engineer alkali metal bonding in Cu(In,Ga)(Se,S) 2 absorbers to optimize both initial and long-term photovoltaic power generation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Dynamics of virtual water networks: Role of national socio-economic indicators across the world

Intensified water usage due to rapid industrialization is often dictated by economic policies based on monetary growth rather than sustainable use of environmental resources. In addition, interdependence within economic sectors further interweaves water usage through product transactions, which further makes it difficult to quantify the dynamics of hydro-economic systems at regional, national and global scale. In this study, we investigated the dynamics of domestic virtual water networks (VWN) of 189 countries based on concept of information theory by quantifying network metrics that describes VWN flow capacity, robustness, efficiency and flexibility. These networks represent virtual water interconnected through economic sectors within a specified country built based on environmentally extended multi region input output (EE-MRIO) approach. We further estimated trends associated with network metrics, as well as coupling intensity between metrics with respect to socio-economic indicators, such as, population, Gross Domestic Product (GDP) and Gross National Income (GNI). It was observed that capacity and flexibility of VWNs are strongly and positively correlated indicating that a high capacity VWN can be more flexible. Our results also indicate that, in general a higher percentage of developing countries (i.e. both least developing and developing nations) have exhibited increasing trends in capacity, robustness, efficiency and flexibility of VWN compared to developed nations. It was revealed that the dynamics of VWNs are positively coupled with socio-economic growth for few countries, which indicates the sustainable behavior of VWN with socio-economic growth. Our results argue that the information theory-based metrics by embedding water footprints can holistically capture sustainability aspect of the VWN dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Process parameters and system responses in friction extrusion

We report friction extrusion is an emerging manufacturing process that imparts improved properties and unique microstructures to materials. In this study, the effects of die features (i.e., the absence or presence of die face scrolling) and process parameters (i.e., die rotational speeds and feed rates) on response variables (e.g., extrusion force, torque, power, and temperature) were investigated. During this work, wires with good integrity and similar geometries were extruded over a range of experimental trials with different rotational speeds and feed rates at a constant extrusion ratio. The extrusion force linearly varies with die advance per revolution, which is the ratio of feed rate and rotational speed. The extrusion energy per kilogram mass of extrudate varies non-linearly and asymptotically such that energy consumption is highest at the lowest feed rate and lowest at the highest feed rate. Additionally relationships among other variables (i.e., die advance per revolution, torque, power heat input, and temperature) also were evaluated to elucidate their interdependences.

42 ENGINEERING↗
DOE OSTI2021

First-principles calculation of lattice distortions in four single phase high entropy alloys with experimental validation

Exceptional properties of high entropy alloys (HEAs) are attributed to the disordered random solid solution of multiple alloying elements. Despite numerous studies, the fundamental understanding at the electronic and atomic levels is still missing. We report a comparative study of four fcc HEAs of NiFeCoCr and NiFeCoCrX (X = Mn, Cu, or Pd) based on ab initio calculations using large supercells with 500 atoms in equal composition. After fully optimizing their structures using the VASP package, their electronic structure, interatomic bonding, partial charge distribution, and mechanical properties are calculated and compared, revealing the intricate interdependence among them. A novel parameter based on the quantum mechanical metric for internal cohesion, the total bond order density (TBOD), is used to interpret the calculated properties. The highest TBOD is found in Cantor alloy NiFeCoCrMn but lower in NiFeCoCrPd. The atomic radii vary depending on their local chemical environment. The resulting lattice distortions is validated experimentally in NiFeCoCrMn and NiFeCoCrPd. Moreover, modeling of Cu and Pd clustering in the supercell shows they have lower total energy in agreement with the observation of Cu-enhanced nano-participates in NiFeCoCrCu and Pd-induced concentration wave in NiFeCoCrPd HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Effects of annealing temperature on the physicochemical, optical and photoelectrochemical properties of nanostructured hematite thin films prepared via electrodeposition method

Highlights: • Nanostructured hematite thin films were synthesized via electrodeposition method. • Effects of annealing on size, grain boundary and PEC properties were examined. • Photocurrents generation was enhanced when the thin films were annealed at 600 °C. • The highest photocurrent density of 1.6 mA/cm{sup 2} at 0.6 V vs Ag/AgCl was achieved. - Abstract: Hematite (α-Fe{sub 2}O{sub 3}) is a promising photoanode material for hydrogen production from photoelectrochemical (PEC) water splitting due to its wide abundance, narrow band-gap energy, efficient light absorption and high chemical stability under aqueous environment. The key challenge to the wider utilisation of nanostructured hematite-based photoanode in PEC water splitting, however, is limited by its low photo-assisted water oxidation caused by large overpotential in the nominal range of 0.5–0.6 V. The main aim of this study was to enhance the performance of hematite for photo-assisted water oxidation by optimising the annealing temperature used during the synthesis of nanostructured hematite thin films on fluorine-doped tin oxide (FTO)-based photoanodes prepared via the cathodic electrodeposition method. The resultant nanostructured hematite thin films were characterised using field emission-scanning electron microscopy (FE-SEM) coupled with energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), UV-visible spectroscopy and Fourier transform infrared spectroscopy (FTIR) for their elemental composition, average nanocrystallites size and morphology; phase and crystallinity; UV-absorptivity and band gap energy; and the functional groups, respectively. Results showed that the nanostructured hematite thin films possess good ordered nanocrystallites array and high crystallinity after annealing treatment at 400–600 °C. FE-SEM images illustrated an increase in the average hematite nanocrystallites size from 65 nm to 95 nm when the annealing temperature was varied from 400 °C to 600 °C. As the crystallites size increases, the grain boundaries reduce and this suppresses the recombination rate of electron–hole pairs on the nanostructured hematite thin films. As a result, the measured photocurrent densities of nanostructured hematite thin films also increased. The highest measured photocurrent density of 1.6 mA/cm{sup 2} at 0.6 V vs Ag/AgCl in 1 M NaOH electrolyte was achieved for the nanostructured hematite thin film annealed at 600 °C. This study had confirmed that strong interdependencies exist between the average hematite nanocrystallites size and grain boundaries with annealing temperature on the eventual PEC water splitting performance of nanostructured hematite thin films. The annealed hematite thin films at a higher temperature will enhance the nanocrystals growth and thus, suppressing the electron–hole pairs recombination rate, lowering the grain boundary resistance and enabling higher photocurrent flow at the molecular level. As a result, the photocurrent density and thus, the overall PEC water splitting performance of the nanostructured hematite thin films are significantly enhanced.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Self-regulating behavior of hybrid membrane systems as demonstrated in an element-scale forward osmosis-reverse osmosis hybrid system

Hybrid membrane systems can be difficult to design due to the requisite flow rate matching between up- and downstream unit operations. In this work, we use a forward osmosis-reverse osmosis (FO-RO) hybrid system to demonstrate how some membrane systems can exhibit self-regulating behavior due to osmotic coupling. This can reduce the need for complex control systems for flow balancing. We show this behavior using a module-scale test bed that can mimic the behavior of larger scale operations. The system shows permeate flow rate near-convergence between the FO and RO modules after startup or when perturbed by a change in RO module pressure. The behavior of this hybrid system demonstrates that some membrane operations can exploit osmotic interdependence, rather than expensive control systems, to achieve steady state operation.

Debottlenecking↗
DOE OSTI2026

Reliable statistics-based detection and investigation of anomalies in a SMART valve system

Reliable anomaly detection and diagnosis are critical for the safe operation of complex engineered systems. This study presents a unified framework that integrates statistical, model-based, and data-driven techniques for anomaly detection and investigation, demonstrated on SMART valve systems in hybrid energy applications. Four detection methods—mean deviation, seasonal extreme studentized deviate, ARIMA forecasting, and matrix profiling—were implemented and compared. Matrix profiling was particularly effective in revealing subtle deviations and hidden relationships among variables. Anomaly investigation was performed by analyzing variable-level and grouped signal profiles, with system topology incorporated to distinguish primary faults from propagated effects. Grouping signals by type enhanced interpretability, enabling accurate localization of anomalies across multi-dimensional datasets. Experimental results confirmed the framework's capability to consistently detect and isolate anomalies while providing actionable insights into system interdependencies. The proposed methodology offers a robust, interpretable, and scalable solution for condition monitoring, with potential applications in safety-critical domains such as nuclear energy, aerospace, and process industries.

ARIMA models↗
DOE OSTI2019

Using an onion like neutron scattering instrument model to quickly optimize design parameters

When designing a neutron scattering instrument, one of the major challenges is the many parameters, generally interdependent, within the optimization. In this work we describe an approach using McStas 1-3 to quickly get a good overview of how changes in instrument parameters will impact neutron scattering instrument performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Exploration of mass splitting and muon/tau mixing parameters for an eV-scale sterile neutrino with IceCube

We present the first three-parameter fit to a 3+1 sterile neutrino model using 7.634 years of data from the IceCube Neutrino Observatory on $ν$ μ + $\overline{ν}$ μ charged-current interactions in the energy range 500–9976 GeV. Our analysis is sensitive to the mass-squared splitting between the heaviest and lightest mass state (Δm$^{2}_{41}$), the mixing matrix element connecting muon flavor to the fourth mass state (|U μ4 | 2 ), and the element connecting tau flavor to the fourth mass state (|U $\tau$4 | 2 ). Predicted propagation effects in matter enhance the signature through a resonance as atmospheric neutrinos from the Northern Hemisphere traverse the Earth to the IceCube detector at the South Pole. The remaining sterile neutrino matrix elements are left fixed, with |U e4 | 2 = 0 and δ 14 = 0, as they have a negligible effect, and δ 24 = π is set to give the most conservative limits. The result is consistent with the no-sterile neutrino hypothesis with a probability of 4.3%. Profiling the likelihood of each parameter yields the 90% confidence levels: 2.4eV 2 < Δm$^{2}_{41}$) < 9.6eV 2 , 0.0081< |U μ4 | 2 < 0.10, and |U $\tau$4 | 2 < 0.035, which narrows the allowed parameter-space for |U $\tau$4 | 2 . However, the primary result of this analysis is the first map of the 3+1 parameter space exploring the interdependence of Δm$^{2}_{41}$, |U μ4 | 2 , and |U $\tau$4 | 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems

The number of connections between physical and cyber security systems is rapidly increasing due to centralized control from automated and remotely connected means. As the number of interfaces between systems continues to grow, the interactions and interdependencies between them cannot be ignored. Historically, physical and cyber vulnerability assessments have been performed independently. This independent evaluation omits important aspects of the integrated system, where the impacts resulting from malicious or opportunistic attacks are not easily known or understood. Here, we describe a discrete event simulation model that uses information about integrated physical and cyber security systems, attacker characteristics and simple response rules to identify key safeguards that limit an attacker's likelihood of success. Key features of the proposed model include comprehensive data generation to support a variety of sophisticated analyses, and full parameterization of safeguard performance characteristics and attacker behaviours to evaluate a range of scenarios. Lastly, we also describe the core data requirements and the network of networks that serves as the underlying simulation structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Global critical materials markets: An agent-based modeling approach

As part of efforts to position the United States as a leader in clean energy technology production, the U. S. Department of Energy (DOE) issued two Critical Materials Strategy reports, which assessed 16 materials on the basis of their importance to clean energy development and their supply risk ( U.S. Department of Energy (DOE), 2010 and DOE, 2011). To understand the implications for clean energy of disruptions in supplies of critical materials, it is important to understand supply chain dynamics from mining to final product production. As a case study of critical material supply chains, we focus on the supply of two rare earth metals, neodymium (Nd) and dysprosium (Dy), for permanent magnets used in wind turbines, electric vehicles and other applications. We introduce GCMat, a dynamic agent-based model that includes interacting agents at five supply chain stages consisting of mining, metal refining, magnet production, final product production and demand. Agents throughout the supply chain make pricing, production and inventory management decisions. Deposit developers choose which deposits to develop based on market conditions and detailed data on 57 rare earth deposits. Wind turbine and electric vehicle producers choose from a set of possible production technologies that require different amounts of rare earths. We ran the model under a baseline scenario and four alternative scenarios with different demand and production technology inputs. Model results from 2010 to 2013 fit well with historical data. Projections through 2025 show a number of possible future price, demand, and supply trajectories. For each scenario, we highlight reasons for turning points under market conditions, for differences between Nd and Dy markets, and for differences between scenarios. Because GCMat can model causal dynamics and provide fine-grain representation of agents and their decisions, it provides explanations for turning points under market conditions that are not otherwise available from other modeling approaches. Our baseline projections show very different behaviors for Nd and Dy prices. Nd prices continue to drop and remain low even at the end of our simulation period as new capacity comes online and leads to a market in which production capacity outpaces demand. Dy price movements, on the other hand, change directions several times with several key turning points related to inventory behaviors of particular agents in the supply chain and asymmetric supply and demand trends. Scenario analyses show the impact of stronger demand growth for rare earths, and in particular finds that Nd price impacts are significantly delayed as compared to Dy. This is explained by the substantial excess production capacity for Nd in the early simulation years that keeps prices down. Scenarios that explore the impact of reducing the Dy content of magnets show the intricate interdependencies of these two markets as price trends for both rare earths reverse directions – reducing the Dy content of magnets reduces Dy demand, which drives down Dy prices and translates into lower magnet prices. This in turn raises the demand for magnets and therefore the demand for Nd and eventually drives up the Nd price.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The electric vehicles-solar photovoltaics Nexus: Driving cross-sectoral adoption of sustainable technologies

Residential and transportation energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics [PVs]) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market shares for both EVs and PVs continue to grow, both of these emerging technologies are deployed rather disjointly, without considering the existence of potential similarities among users who own (or aspire to own) these technologies. This might be due to lack of understanding of the behavioral interdependence in consumer preferences toward these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores interactive EV and PV adoption behaviors. A structural equation model is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values, and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive bundled adoption of EV-PV systems could accelerate the adoption of both of these sustainable technologies. In conclusion, this study highlights the need to consider transport and building energy-efficient technology adoption behavior in a single integrated structure.

14 SOLAR ENERGY↗