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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cooperative response of magnetism and superconductivity in the magnetic superconductor RbEuFe 4 As 4

Herein, we present a study of the magnetic-flux evolution in the magnetic superconductor RbEuFe 4 As 4 performed using magneto-optical imaging and magnetization measurements during field cooling and warming and magnetic field cycling at temperatures above and below the magnetic transition point, T$_m$. The vortex patterns emerging at T ≲ T$_m$ reveal that the Eu-spin subsystem serves as an internal pump of the magnetic flux while the superconducting critical current controls the delivery of magnetic-flux quanta into the bulk. The interplay of magnetic susceptibility amplifying the magnetic induction and vortex pinning attenuating the magnetic-flux entry results in a field- and temperature-dependent critical state that emulates a paramagnetic Meissner effect. The observed vortex dynamics corresponds to a nontrivial spatial current distribution and yields a self-consistent inhomogeneous enhancement of the sample magnetization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Castanha et al. 2018: Hopland Lysimeter 13C-Labeled Root Litter Decomposition Study.

The breakdown and decomposition of plant inputs are critical for nutrient cycling, soil development, and climate-ecosystem feedbacks, but uncertainties persist in how the rates and products of litter decomposition are affected by soil temperature, rhizosphere, and depth of input. To elucidate these questions we measured the effects of soil warming (+ 4 °C), rhizosphere, and depth of litter placement on the decomposition of Avena fatua (wild oat grass) root litter in a Mediterranean grassland ecosystem. Field lysimeters were subjected to three environmental treatments (heating, control, and plant removal) and three 13C-labeled root litter addition treatments (to A horizon, to B horizon, and no-addition disturbance control) for each of two harvest time points. We buried root litter in February 2014 and measured loss of 13C in CO2 from the soil surface and in leachate as dissolved organic carbon (DOC) over two growing seasons. At the end of each of the 2014 and 2015 growing seasons we recovered the 13C remaining in the soil. Loss of root litter C occurred almost entirely via heterotrophic respiration, with an estimated < 2% lost as DOC during the initial decay period. The added roots were broken down and incorporated into bulk soil material very quickly; only ~ 30% of added root was visible after 6 months. In the first growing season, decomposition occurred faster in the B than in the A horizon, the latter having greater moisture limitation. Subsequently, there was almost no further decomposition in the B horizon. After two growing seasons, less than 20% of the added root litter C remained in the A or B horizons of all environmental treatments. Heating did not stimulate decomposition, likely because it exacerbated the moisture limitation. However, while plots without plants dried down more slowly than plots with plants, their decomposition rate was not significantly greater, possibly due to the lack of rhizosphere processes such as priming. We conclude that in this Mediterranean grassland ecosystem, soil moisture, which is affected by season, depth, heating, and rhizosphere, plays a dominant role in mediating the effect of those factors on root litter decomposition, which after two seasons did not differ by depth or by treatment.The files in this dataset comprise (1) 13C-labeled litter additions made to each plot, (2) litter recovery after each of 2 growing seasons, (3) periodical soil flux measurements, (4) leachate measurements, and continuously monitored soil (5) temperature and (6) moisture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments

Tropical cyclones (TCs) rank as the deadliest and most financially crippling natural disasters in the United States for the last half-century. It is imperative to assess potential shifts in TC intensity within the paradigm of an evolving climate. In this study, we have modeled the intensities of 620 historical TC events in the North Atlantic Basin using the Risk Analysis Framework for Tropical Cyclones (RAFT)'s deep learning intensity model. By applying a thermodynamic warming signal extrapolated from Global Climate Models, we rerun historical events under eight different future climate scenarios, providing a spectrum of potential TC intensity outcomes. One of the future simulations indicates a staggering 43% increase in the number of major hurricanes, underscoring the critical impact of climate change on TC intensity. Additionally, an interactive dashboard has been created to enable users to explore individual storm simulations and understand the influence of future climate signals on environmental conditions of TC development and resulting TC intensities. This dataset and the user-friendly tool offer invaluable resources for systematic exploration of the discrete effects that changes in the air-sea thermodynamic state have on the intensities of TCs.

Climate Change↗
DOE OSTI2024

Breakthrough innovations in carbon dioxide mineralization for a sustainable future

Greenhouse gas emissions and climate change concerns have prompted worldwide initiatives to lower carbon dioxide (CO 2 ) levels and prevent them from rising in the atmosphere, thereby controlling global warming. Effective CO 2 management through carbon capture and storage is essential for safe and permanent storage, as well as synchronically meeting carbon reduction targets. Lowering CO 2 emissions through carbon utilization can develop a wide range of new businesses for energy security, material production, and sustainability. CO 2 mineralization is one of the most promising strategies for producing thermodynamically stable solid calcium or magnesium carbonates for long-term sequestration using simple chemical reactions. Current advancements in CO 2 mineralization technologies, focusing on pathways and mechanisms using different industrial solid wastes, including natural minerals as feedstocks, are briefly discussed. However, the operating costs, energy consumption, reaction rates, and material management are major barriers to the application of these technologies in CO 2 mineralization. Further, the optimization of operating parameters, tailor-made equipment, and smooth supply of waste feedstocks require more attention to make the carbon mineralization process economically and commercially viable. Here, carbonation mechanisms, technological options to expedite mineral carbonation, environmental impacts, and prospects of CO 2 mineralization technologies are critically evaluated to suggest a pathway for mitigating climate change in the future. The integration of industrial wastes and brine with the CO 2 mineralization process can unlock its potential for the development of novel chemical pathways for the synthesis of calcium or magnesium carbonates, valuable metal recovery, and contribution to sustainability goals while reducing the impact of global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mechanisms and Impacts of Earth System Tipping Elements

Tipping elements are components of the Earth system which may respond nonlinearly to anthropogenic climate change by transitioning toward substantially different long-term states upon passing key thresholds or “tipping points.” In some cases, such changes could produce additional greenhouse gas emissions or radiative forcing that could compound global warming. Improved understanding of tipping elements is important for predicting future climate risks and their impacts. Here we review mechanisms, predictions, impacts, and knowledge gaps associated with 10 notable Earth system components proposed to be tipping elements. We evaluate which tipping elements are approaching critical thresholds and whether shifts may manifest rapidly or over longer timescales. Some tipping elements have a higher risk of crossing tipping points under middle-of-the-road emissions pathways and will possibly affect major ecosystems, climate patterns, and/or carbon cycling within the 21st century. However, literature assessing different emissions scenarios indicates a strong potential to reduce impacts associated with many tipping elements through climate change mitigation. The studies synthesized in our review suggest most tipping elements do not possess the potential for abrupt future change within years, and some proposed tipping elements may not exhibit tipping behavior, rather responding more predictably and directly to the magnitude of forcing. Nevertheless, uncertainties remain associated with many tipping elements, highlighting an acute need for further research and modeling to better constrain risks.

58 GEOSCIENCES↗
DOE OSTI2024

Improved Decarbonization Planning through Climate Resiliency Modeling

California has set ambitious decarbonization goals concerning both emissions and the portion of energy generated by renewable resources. However, climate change poses considerable uncertainties. Variation in load is driven both by the level of electrification as well as the impact of climate change on weather. Further, climate change stands to make weather more variable, impacting not just load but generation from renewable resources. In this paper, we approach the issue of the impacts of climate change on decarbonization planning from two perspectives. First, we look at the range of decarbonization pathways through 8 pathways that account for differences in socioeconomic development, global emissions, and warming. Second, we develop a more robust way of ensuring the reliability of energy resources planning than the commonly used planning reserve margin. We show that the proposed method can save between 6 and 14 billion dollars in investment and maintenance costs and outline critical policy implications concerning the reliance of power plants for satisfying planning reliability requirements, including the potential retirement of dozens of peaker power plants.

Anderson, Osten P.↗
DOE OSTI2022

Do Machine Learning Approaches Offer Skill Improvement for Short-Term Forecasting of Wind Gust Occurrence and Magnitude?

Abstract Wind gusts, and in particular intense gusts, are societally relevant but extremely challenging to forecast. This study systematically assesses the skill enhancement that can be achieved using artificial neural networks (ANNs) for forecasting of wind gust occurrence and magnitude. Geophysical predictors from the ERA5 reanalysis are used in conjunction with an autoregressive term in regression and ANN models with different predictors, and varying model complexity. Models are derived and assessed for the warm (April–September) and cold (October–March) seasons for three high passenger volume airports in the United States. Model uncertainty is assessed by deriving models for 1000 different randomly selected training (70%) and testing (30%) subsets. Gust prediction fidelity in independent test samples is critically dependent on inclusion of an autoregressive term. Gust occurrence probabilities derived using five-layer ANNs exhibit consistently higher fidelity than those from regression models and shallower ANNs. Inclusion of the autoregressive term and increasing the number of hidden layers in ANNs from 1 to 5 also improve the model performance for gust magnitudes (lower RMSE, increased correlation, and model standard deviations that more closely approximate observed values). Deeper ANNs (e.g., 20 hidden layers) exhibit higher skill in forecasting strong (17–25.7 m s −1 ) and damaging (≥25.7 m s −1 ) wind gusts. However, such deep networks exhibit evidence of overfitting and still substantially underestimate (by 50%) the frequency of strong and damaging wind gusts at the three airports considered herein. Significance Statement Improved short-term forecasting of wind gusts will enhance aviation safety and logistics and may offer other societal benefits. Here we present a rigorous investigation of the relative skill of models of wind gust occurrence and magnitude that employ different statistical methods. It is shown that artificial neural networks (ANNs) offer considerable skill enhancement over regression methods, particularly for strong and damaging wind gusts. For wind gust magnitudes in particular, application of deeper learning networks (e.g., five or more hidden layers) offers tangible improvements in forecast accuracy. However, deeper networks are vulnerable to overfitting and exhibit substantial variability with the specific training and testing data subset used. Also, even deep ANNs reproduce only half of strong and damaging wind gusts. These results indicate the need for future work to elucidate the dynamical mechanisms of intense wind gusts and advance solutions to their prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation

The Arctic Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO 2 . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models (TBMs) such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Furthermore, we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multiphysics and Multiscale Modeling of Coupled Transport of Chloride Ions in Concrete

Chloride ions (Cl−)-induced corrosion is one of the main degradation mechanisms in reinforced concrete (RC) structures. In most situations, the degradation initiates with the transport of Cl− from the surface of the concrete towards the reinforcing steel. The accumulation of Cl− at the steel-concrete interface could initiate reinforcement corrosion once a threshold Cl− concentration is achieved. An accurate numerical model of the Cl− transport in concrete is required to predict the corrosion initiation in RC structures. However, existing numerical models lack a representation of the heterogenous concrete microstructure resulting from the varying environmental conditions and the indirect effect of time dependent temperature and relative humidity (RH) on the water adsorption and Cl− binding isotherms. In this study, a numerical model is developed to study the coupled transport of Cl− with heat, RH and oxygen (O2) into the concrete. The modeling of the concrete microstructure is performed using the Virtual Cement and Concrete Testing Laboratory (VCCTL) code developed by the U.S. National Institute of Standards and Technology (NIST). The concept of equivalent maturation time is utilized to eliminate the limitation of simulating concrete microstructure using VCCTL in specific environmental conditions such as adiabatic. Thus, a time-dependent concrete microstructure, which depends on the hydration reactions coupled with the temperature and RH of the environment, is achieved to study the Cl− transport. Additionally, Cl− binding isotherms, which are a function of the pH of the concrete pore solution, Cl− concentration, and weight fraction of mono-sulfate aluminate (AFm) and calcium-silicate-hydrate (C-S-H), obtained from an experimental study by the same authors are utilized to account for the Cl− binding of cement hydration products. The temperature dependent RH diffusion was considered to account for the transport of Cl− with moisture transport. The temperature and RH diffusion in the concrete domain, composite theory, and Cl− binding and water adsorption isotherms are used in combination, to estimate the ensuing Cl− diffusion field within the concrete. The coupled transport process of heat, RH, Cl−, and O2 is implemented in the Multiphysics Object-Oriented Simulation Environment (MOOSE) developed by the U.S. Idaho National Laboratory (INL). The model was verified and validated using data from multiple experimental studies with different concrete mixture proportions, curing durations, and environmental conditions. Additionally, a sensitivity analysis was performed to identify that the water-to-cement (w/c) ratio, the exposure duration, the boundary conditions: temperature, RH, surface Cl− concentration, Cl− diffusion coefficient in the capillary water, and the critical RH are the important parameters that govern the Cl− transport in RC structures. In a case study, the capabilities of the developed numerical model are demonstrated by studying the complex 2D diffusion of Cl− in a RC beam located in two different climatic regions: warm and humid weather in Galveston, Texas, and cold and dry weather in North Minnesota, Minnesota, subjected to time varying temperature, RH, and surface Cl− concentrations.

composite theory↗
DOE OSTI2025

Rising temperatures intensify drought propagation and severity across the contiguous United States

Droughts can propagate from meteorological droughts (MD) into agricultural (AD) and hydrological droughts (HD). However, the mechanisms by which rising temperatures and changes in precipitation amount influence MD propagation, and how these dynamics vary across U.S., are not yet fully understood. This gap is critical given the U.S.’s diverse climates and land-use patterns, which lead to region-specific drought vulnerabilities and impacts, such as the 2012 AD in the Great Plains and the 2014 HD in the western U.S. Using a dynamical-statistical framework, we assess warming impacts on drought propagation. Results reveal that the Midwest and Southeast, key agricultural regions, show the largest increases in MD propagation to AD/HD, driven by rising temperatures and declining precipitation, though magnitudes vary regionally. In contrast, the Northeast shows reduced propagation due to increased year-round precipitation. Higher-intensity AD/HD events become disproportionately more likely, with rates varying by region and MD intensity.

Yan, Hongxiang [Pacific Northwest National Laborat↗
DOE OSTI2025

Sustainable recovery of critical metals from spent lithium-ion batteries through gluconic acid-based bioleaching: Techno-economic analysis, life cycle assessment and process optimization

Recycling spent lithium-ion batteries (LIB) could potentially bridge the ever increasing supply and demand gap for critical metals and simultaneously facilitate the management of hazardous battery waste. This study investigated the optimization of gluconic acid-based bioleaching technology through design of experiments (DOE), combined with techno-economic analysis (TEA), and life cycle assessment (LCA) with the aim of maximizing the net present value (NPV) and minimizing global warming impacts of the process. Biolixiviant containing predominantly gluconic acid produced by the genetically engineered (ΔpstS, P 112 :mgdh) Gluconobacter oxydans B58 through fermentation using non-recyclable paper as a growth substrate was used for the LIB leaching. At optimal bioleaching conditions of gluconic acid (160 mM), leaching time (2.5 h), reducing agent FeSO 4 to metal, i.e., cobalt (Co), nickel (Ni) and manganese (Mn), mole ratio (0.88), temperature (55 °C) and pulp density (2.5 %), the leaching efficiency was 87 % 72 %, 94 %, and 88 % for Co, Ni, Mn and lithium (Li), respectively. TEA analysis confirmed that bioleaching plant with an annual black mass processing capacity of 10,000 metric tons and plant life of 30 years would be economically viable with an NPV and profit margin of $136 million and 11 %, respectively. The predicted carbon footprint of gluconic acid-based bioleaching for recovering 1 kg of Co (13.2 kg of CO 2 eq.) is lower compared to that of most state-of-the-art leaching technologies. Moreover, gluconic acid-based bioleaching effectively recovered target metals when tested for different black mass chemistries.

Bioleaching↗
DOE OSTI2024

District heating utilizing waste heat of a data center: High-temperature heat pumps

Data centers are energy-intensive facilities with substantial low-grade waste heat. High-temperature heat pumps can be critical in boosting the data center’s waste heat for district heating, improving the system-level energy efficiency of data centers, and reducing CO 2 emissions in district heating. This study built thermodynamic models to assess high-temperature heat pumps with six configurations using low global warming potential refrigerants to supply heat up to 120 °C. The heat pump configurations include single-stage or two-stage cycles with advanced components, such as internal heat exchanger, economizer, flash tank, or parallel compressor. The refrigerants include R1234ze(Z), R1233ed(E), R1224yd(Z), R600, and R600a, and R245fa is used as a reference. A case study was carried out to recover the waste heat from the Frontier high-performance computing data center and provide hot water for district heating at the US Department of Energy’s Oak Ridge National Laboratory campus. The optimized performance of high-temperature heat pumps is characterized with various effectiveness of internal heat exchangers, and the operating parameters of economizer or flash tank, as well as their combination. The results show that the configurations of two-stage cycles with internal heat exchanger + flash tank and internal heat exchanger + economizer/parallel-compressor provide the highest coefficient of performance under scenarios of the maximum allowable value and a fixed value (0.3) of the internal heat exchangers’ effectiveness, respectively. R1234ze(Z) and R600a are the most promising refrigerants, considering trade-offs between the coefficient of performance and the volumetric heating capacity. The single-stage cycle with internal heat exchanger + economizer/parallel-compressor using R1234ze(Z) is recommended for utilizing Fronter’s waste heat in district heating. A one mega-watt high-temperature heat pump will reduce 33,100–33,200 metric tons of CO2 emission annually, corresponding to 85.4 %–85.6 % of equivalent CO2 emissions from natural gas boilers. Here, this study provides good guidelines for designing and deploying high-temperature heat pumps to support sustainable data centers and decarbonize district heating in the US.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Warming Pattern over the Northern Hemisphere Midlatitudes in Boreal Summer 1979–2020

Abstract Significant surface air temperature warming during summer 1979–2020 is not uniformly distributed in the northern midlatitudes over land but rather is confined to several longitudinal sectors including Europe, central Siberia and Mongolia, and both coasts of North America. These hot spots are accompanied by a chain of high pressure ridges from an anomalous, circumglobal Rossby wave train in the upper troposphere. From reanalysis data and several baseline experiments from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we find that the circulation trend pattern is associated with fluctuations of the Atlantic multidecadal variability (AMV) and the interdecadal Pacific oscillation. The phase shift of AMV in the 1990s is particularly noteworthy for accelerating warming averaged over the northern midlatitude land. The amplitude of the observed trend in both surface air temperature and the upper-level geopotential height generally falls beyond the range of multidecadal trends simulated by the CMIP6 preindustrial control runs, supporting the likelihood that anthropogenic forcing played a critical role in the observed trend. On the other hand, the fidelity of the simulated low-frequency modes of variability and their teleconnections, especially on multidecadal time scales, is difficult to assess because of the relatively short observational records. Our mechanistic modeling results indicate that synoptic eddy–mean flow interaction is a key to the formation of the anomalous wave train but how the multidecadal modes can modulate the synoptic eddies through atmosphere–ocean and atmosphere–land interactions remains poorly understood. This gap in our knowledge makes it challenging to quantify the roles of the low-frequency modes and external forcings in causing the observed multidecadal trends.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enhancing the Faradaic efficiency of solid oxide electrolysis cells: progress and perspective

Abstract To reduce global warming, many countries are shifting to sustainable energy production systems. Solid oxide electrolysis cells (SOECs) are being considered due to their high hydrogen generation efficiency. However, low faradaic efficiency in scaling SOEC technology affects costs and limits large-scale adoption of hydrogen as fuel. This review covers SOECs’ critical aspects: current state-of-the-art anode, cathode, and electrolyte materials, operational and materials parameters affecting faradaic efficiency, and computational modeling techniques to resolve bottlenecks affecting SOEC faradaic efficiency.

Gaikwad, Prashik S. (ORCID:0000000179510115)↗
DOE OSTI2025

Global climate mode resonance due to rapidly intensifying El Niño-Southern Oscillation

The El Niño-Southern Oscillation (ENSO) influences climate variability globally, encompassing various other modes of variability, and thus represents a key predictable climate signal on seasonal timescales. Yet, its response to greenhouse warming remains uncertain, with models projecting a range of outcomes. Here, we demonstrate that in response to warming, a state-of-the-art high-resolution climate model simulates a rapid transition from a moderate-amplitude irregular regime, as observed in the current climate, to a highly regular oscillation with intensifying amplitude. This behaviour can be attributed to increasing air-sea feedbacks, which approach criticality in the second half of this century, and growing atmospheric noise. As ENSO intensifies in this model, it synchronizes with other prominent climate modes, such as the North Atlantic Oscillation and the Indian Ocean Dipole, thereby imprinting its regular, predictable variability on them. If realized, this global climate mode resonance would have wide-ranging whiplash impacts on regional hydroclimates.

Atmospheric dynamics↗
DOE OSTI2025

Interactions between macro‐ and micro‐climate: Effects on phenolic compound production in Nardus stricta at high elevations

Abstract Phenolic compounds are key to plant defence, offering protection as antioxidants, UV shields, and antimicrobials. Their production is largely shaped by environmental conditions. It is believed that plants at lower elevations increase phenolic content to counter herbivory, while those at higher elevations rely on phenolics to manage abiotic stresses, such as climate variability. Microhabitat warming also affects phenolic levels, but responses differ, depending on broader climatic contexts: plants in warmer, lower‐elevation environments show limited adaptability, whereas high‐elevation plants demonstrate greater plasticity. Despite the importance of these environmental interactions, many small‐scale abiotic studies lack sufficient spatial replication across broader gradients like elevation or latitude, while large‐scale studies frequently overlook microscale factors. This study investigated the effects of macroclimate factors and microhabitat warming on phenolic production in Nardus stricta across five semi‐natural grassland sites (1546–1875 m a.s.l.) in Portugal's Serra da Estrela. Warming was simulated using open‐top chambers over two growing seasons, after which leaf samples were analysed for phenolic compounds, and soil nutrients were measured. The N. stricta plants at the highest elevation site contained significantly higher leaf flavonoid concentrations. Microhabitat warming led to a significant decrease in flavonoid concentrations, but only at the highest elevation site. These effects occurred independently of soil nutrient levels, suggesting direct thermal effects or stress responses might be involved. Our findings highlight the complex interactions between macro‐ and microenvironmental factors in shaping plant chemistry, underscoring critical considerations for plant resilience in the face of climate change. This understanding is essential for developing strategies to support plant and ecosystem adaptation to changing climates.

Moreira, X. [Misión Biológica de Galicia (MBG‐CSIC↗
DOE OSTI2021

Uncertainty in El Niño-like warming and California precipitation changes linked by the Interdecadal Pacific Oscillation

Abstract Marked uncertainty in California (CA) precipitation projections challenges their use in adaptation planning in the region already experiencing severe water stress. Under global warming, a westerly jet extension in the North Pacific analogous to the El Niño-like teleconnection has been suggested as a key mechanism for CA winter precipitation changes. However, this teleconnection has not been reconciled with the well-known El Niño-like warming response or the controversial role of internal variability in the precipitation uncertainty. Here we find that internal variability contributes > 70% and > 50% of uncertainty in the CA precipitation changes and the El Niño-like warming, respectively, based on analysis of 318 climate simulations from several multi-model and large ensembles. The Interdecadal Pacific Oscillation plays a key role in each contribution and in connecting the two via the westerly jet extension. This unifying understanding of the role of internal variability in CA precipitation provides critical guidance for reducing and communicating uncertainty to inform adaptation planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Rapid Cryogenic Electrical Characterization of Materials and Devices Using Gifford-McMahon Cryocoolers

Thin-film heterostructures are necessary building blocks for superconducting and phononic quantum computing devices. Many new generations of quantum hardware demand extensive materials research to optimize performances at cryogenic temperatures (below 10 K). Here, we demonstrate compact cryogenic measurement systems capable of reaching sub-10K temperatures in less than three hours with the ability to measure AC/DC resistance and dielectric properties of thin-film materials. Our platform utilizes Gifford-McMahon (GM) cryocoolers as effective tools for providing high throughput cooling-warming cycles. We successfully used the GM-based measurement systems to measure 1) the superconducting transition temperature for Nb thin films (T c ~7.8 K), and 2) the temperature dependence of the dielectric constant in SiO 2 thin films down to 10 K. The fast electrical characterization feedback will be critical in developing robust materials and components for cryogenic computing devices.

36 MATERIALS SCIENCE↗