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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A research agenda for nonvascular photoautotrophs under climate change

Nonvascular photoautotrophs (NVP), including bryophytes, lichens, terrestrial algae, and cyanobacteria, are increasingly recognized as being essential to ecosystem functioning in many regions of the world. Current research suggests that climate change may pose a substantial threat to NVP, but the extent to which this will affect the associated ecosystem functions and services is highly uncertain. Here, we propose a research agenda to address this urgent question, focusing on physiological and ecological processes that link NVP to ecosystem functions while also taking into account the substantial taxonomic diversity across multiple ecosystem types. Accordingly, we developed a new categorization scheme, based on microclimatic gradients, which simplifies the high physiological and morphological diversity of NVP and world-wide distribution with respect to several broad habitat types. We found that habitat-specific ecosystem functions of NVP will likely be substantially affected by climate change, and more quantitative process understanding is required on (1) potential for acclimation, (2) response to elevated CO 2 , (3) role of the microbiome, and (4) feedback to (micro)climate. We suggest an integrative approach of innovative, multimethod laboratory and field experiments and ecophysiological modelling, for which sustained scientific collaboration on NVP research will be essential.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A dissolution model of alite coupling surface topography and ions transport under different hydrodynamics conditions at microscale

Portland cement is the most produced material in the world. The hydration process of cement consists of a group of complex chemical reactions. In order to investigate the mechanism of cement hydration, it is vital to study the hydration of each phase separately. An integrated model is proposed in this paper to simulate the dissolution of alite under different hydrodynamic conditions at microscale, coupling Kinetic Monte Carlo model (KMC), Lattice Boltzmann method (LBM) and diffusion boundary layer (DBL). The dissolution of alite is initialised with KMC. Two Multiple-relaxation-time (MRT) LB models are used to simulate the fluid flow and transport of ions, respectively. For solid-liquid interface, DBL is adapted to calculate the concentration gradient and dissolution flux. The model is validated with experiment from literature. The simulation results show good agreements with the results published in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability

Abstract Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH 4 ) emissions; however, no earth system model (ESM) has represented lake CH 4 dynamics. To fill this gap, we refined a process‐based lake biogeochemical model to simulate global lake CH 4 emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non‐linear CH 4 oxidation kinetics, and the coupling of sediment carbon pools with in‐lake primary production and terrigenous carbon loadings. We compiled a lake CH 4 data set for model validation. The model shows promising performance in capturing the seasonal and inter‐annual variabilities of CH 4 emissions at 10 representative lakes for different lake types and the variations in mean annual CH 4 emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH 4 diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH 4 diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH 4 outgassing events in non‐floodplain lakes and the seasonal variability of CH 4 ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH 4 emissions and climate‐CH 4 feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Transient behavior of oxide fuels with controlled microstructure and Cr2O3 additive

Abstract Microstructure and Cr 2 O 3 doping profoundly impact the thermal-mechanical properties and fracture of oxides fuels. It is a challenge to study the transient behavior of nuclear fuels under loss-of-coolant-event (LOCA). In this study, the crack behavior of UO 2 pellets with controlled grain structure and Cr 2 O 3 doping was tested with rapid power ramping (300−900 °C per min) mimicking a prototypical LOCA heating profile. Dense micron-sized UO 2 pellets display well-maintained integrity without cracking with the ramping up to 1500 °C at a heating rate of 8 °C per second. Fracture occurs in both pure and Cr 2 O 3 -doped dense nano-sized UO 2 pellets. The Cr 2 O 3 doped oxide fuel pellet with a larger grain size (~ 22.2 μm) displays the best performance under LOCA testing due to its highest thermal conductivity under high temperature. FEA calculations suggest a temperature gradient across the fuel pellet during transient testing, resulting in residual stress and cracking, which can be correlated with their thermal-mechanical properties.

Zhao, Dong (ORCID:0000000191377257)↗
DOE OSTI2026

Numerical Investigation of Fluid Flow and Space Charge in Liquid Argon Time Projection Chamber (LArTPC) Detectors

Overview This project focused on developing a high-fidelity numerical framework to simulate the multiphysics environment within Liquid Argon Time Projection Chamber (LArTPC) detectors. The primary objective was to characterize the complex interplay between ion transport, background fluid dynamics, and electric field distortions—a critical factor for the calibration and sensitivity of next-generation High Energy Physics experiments, such as DUNE. Technical Achievements The research successfully yielded a hybrid numerical space-charge solver utilizing a Cell-Centered Finite Volume Method (FVM) for ion transport coupled with a Finite Element Method (FEM) for electric potential. Key accomplishments include: • Verification & Validation: The 3-D solver was rigorously verified against 1-D analytical solutions, demonstrating high numerical accuracy in predicting space-charge-induced field deviations. • Field Distortion Analysis: 3D simulations revealed that space charge effects introduce significant non-uniformities in the electric field. Critically, the research identified that background LAr flow velocities, when comparable to ion drift velocities, markedly exacerbate these distortions. • Technology Transfer: The resulting source code and comprehensive user manuals were successfully transferred to collaborators at Fermilab, providing a portable computational tool for the broader scientific community. Challenges and Future Directions While the space-charge solver achieved all performance metrics, the integrated fluid dynamics modeling encountered convergence challenges stemming from the extreme 200-fold disparity in length scales between the detector's 37 mm inlet pipes and the 8-meter global domain. To address this, the project has identified a clear technical pivot toward Hierarchical Geometric Adaptive Mesh Refinement (HG-AMR). By implementing an h-type refinement strategy with hanging nodes, future iterations of this solver will be capable of resolving localized high-gradient inlet flows without the prohibitive computational costs of regular grids. This advancement, combined with data-driven uncertainty quantification based on MicroBooNE-style calibration, will enable the precise modeling of detector responses in large-scale cryogenic environments where direct measurement remains difficult. Impact The computational tools developed under this award provide a foundation for enhancing the energy resolution and spatial reconstruction of noble liquid detectors. By bridging the gap between theoretical fluid dynamics and experimental field calibration, this work supports the DOE’s mission to advance the frontiers of neutrino physics and dark matter detection.

42 ENGINEERING↗
DOE OSTI2025

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew↗
DOE OSTI2022

Interactions between molecular-scale processes and hyporheic exchange for understanding Fe-S-C cycling in riparian wetlands (Final Report)

Wetlands represent some of the most productive ecosystems on the planet and critically influence global environmental health. Specifically, wetlands promote water quality by transforming nutrients and organic compounds and sequestering metals and contaminants. Riparian wetland hyporheic zones, where toxic surface water and anoxic groundwater mix, exhibit dynamic conditions that drive steep redox gradients and promote hotspots of diverse and fluctuating microbial activity. Changes in climate, water quality, and water quantity can disturb hydrologic flow and biogeochemical processing in these environments. Understanding how sulfate loading, impacted by hydrologic flux and anthropogenic inputs, influences iron and carbon cycling in wetlands will be crucial for predicting water quality issues driven by iron mineral precipitation and sorption, such as the release of heavy metals and other toxic elements. We used a fully integrated multi-scale and multi-method approach to develop a mechanistic understanding of how hydrologic flow influences coupled iron and sulfur cycles in riparian wetlands. This entailed hydrological, geochemical, and microbial observations at two locations: an anthropogenic sulfate-impacted riparian wetland in northern Minnesota, and a low-sulfate Fe-rich riparian wetland in Tims Branch at the Savannah River Site (SRS). These sites were characterized by hydrologically dynamic conditions where the stream and wetland systems oscillated between gaining (upward flow) and losing (downward flow) conditions that recharged the system occasionally with oxidants that fueled a variety of biogeochemical reactions. Aqueous geochemical measurements of surface water, groundwater, and porewater samples were made alongside solid-phase geochemical analyses of sediment gravity cores. Bulk X-ray absorption spectroscopy at the Advanced Photon Source (APS; Argonne) interrogated the speciation and distribution of Fe and S mineral phases of the sediments. Interestingly, it was discovered that, despite strongly reducing conditions, Fe(III) compounds and a variety of intermediate valence S compounds were stable in the subsurface. Indeed, compounds like thiosulfate, S(0), and intermediate valence organosulfur compounds were more prevalent than FeS and pyrite. The composition of the sediments did change with changes in hydrologic flow, showing their reactivity in changing redox conditions. The abundance of these intermediate S compounds was likely formed as a result of anaerobic oxidation by aqueous and solid-phase Fe(III) compounds, fueling a cryptic S cycle that is driving the breakdown of organic matter in the hyporheic zone. Microbiome surveys showed a core community that seemed stable across the landscape, but changed with increasing depth into the sediment. The community composition did not seem to change dramatically with changes in season or hydrologic flow, except for some organisms that have the potential to contribute to S cycling. More work is needed to confirm their functional activity. These fine process-scale analyses were placed within a dynamic field context using physical flow parameters from surface water and groundwater level measurements. These data helped shed light on sulfur-driven biogeochemical processes in hydrologically dynamic riparian wetlands, addressing a gap in our understanding about the impacts of pollution and other anthropogenic changes on ecologically sensitive environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Nitrogen dynamics and physiological N use efficiency in high‐biomass sorghum

Improving nitrogen (N) efficiency is essential for sustainable high-biomass sorghum ( Sorghum bicolor L. Moench) production. This study evaluated leaf and stem N dynamics, canopy N remobilization, and physiological nitrogen use efficiency (pNUE) in two photoperiod-sensitive sorghum hybrids under two N rates (0 and 168 kg-N ha −1 ) across multiple environments in Texas and Illinois. Leaf N concentrations increased with plant height in the canopy with steeper gradients under low-N conditions, indicating enhanced N remobilization when N is limited. Stem tissue showed less variation in N concentration across canopy nodal positions, with within-plant differences ranging from 1.2 to 7.6 g kg −1 , compared to 3.1 to 16.3 g kg −1 in leaves. While pNUE was generally higher under unfertilized conditions, it varied largely by site; however, genotypic differences were minimal within the given year. These results highlight the importance of integrating environmental and management factors into breeding and fertilization strategies to enhance N efficiency in high-biomass sorghum.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Operando measurement of lattice strain in internal combustion engine components by neutron diffraction

Significance Internal combustion engine components experience extreme thermomechanical cycling during operation, and the continuing need to improve engine efficiency while maintaining or improving reliability drives the development of lightweight materials with improved thermal and mechanical integrity. Understanding the behavior of new materials in dynamic operation requires operando characterization tools, but conventional in situ measurements of material behavior during real engine operation are very limited, and no practical means exist to replicate such extreme dynamics for ex situ study. In this work, we demonstrate that the penetrating power of neutrons can provide noninvasive measurement of lattice strains inside components of a firing engine, enabling the operando study of complex load states and thermal gradients throughout the solid materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Spatial and temporal trends and variabilities of hailstones in the United States Northern Great Plains and their possible attributions

Following on our study of hail for the Southern Great Plains (SGP), we investigated the spatial and temporal hail trends and variabilities for the Northern Great Plains (NGP) and the contributing factors for summer seasons (June–August) over 2004–2016 using two independent hail datasets. Both severe hail (1 < diameter = 2 inches) and significant severe hail (diameter > 2 inches) were examined and similar results were obtained. The hailstones in the NGP demonstrate a large interannual variability, with an overall increasing trend over 2004–2016. Spatially, the positive trend is mainly located in the western part of South Dakota and North Dakota. We find the three major dynamical factors that most likely contribute to the hail interannual variability in the NGP are the El Niño-Southern Oscillation (ENSO), North Atlantic subtropical high (NASH), and low-level jet (LLJ). With a thermodynamical variable integrated water vapor transport (IVT) that is strongly controlled by LLJ, the four factors can explain 76% of the hail interannual variability from the hail reports based on the multivariate linear regression. Hail occurrences are 73% higher during the cold phase of ENSO (La Nin~a) than the warm phase of ENSO (El Nin~o). When the NASH has a larger northwestward expansion or stronger intensity, more hail occurs over the NGP, because the increases of latitudinal gradient of pressure leads to a stronger LLJ. Interestingly, the important factors impacting hail interannual variability over the NGP are quite different from those for the SGP, except ENSO.

Jeong, Jong-Hoon↗
DOE OSTI2026

Interactions between molecular-scale biogeochemical processes and hyporheic exchange for understanding coupled Fe-S-C cycling in iron-rich riparian wetlands (Final Technical Report)

Riparian wetlands are dynamic interfaces that exert strong control over water quality, contaminant mobility, and greenhouse gas emissions. These systems are characterized by hyporheic exchange between oxic surface water and anoxic groundwater, which generates steep redox gradients and promotes spatially and temporally variable microbial activity. Despite growing recognition of tightly coupled iron (Fe), sulfur (S), and carbon (C) cycling in these environments, the mechanisms governing these interactions—particularly under low-sulfate freshwater conditions—remain poorly constrained. This project developed a mechanistic understanding of how hydrologic variability and microbial processes interact to control Fe–S–C cycling in iron-rich riparian wetlands. Using a multi-scale and multi-method approach integrating field observations, geochemical and spectroscopic analyses, metagenomics, and reactive transport modeling, we demonstrate that “cryptic” sulfur cycling—rapid sulfur transformations involving intermediate-valence species—plays a dominant and previously underrecognized role in freshwater wetlands. These processes persist despite low sulfate concentrations and significantly influence iron reduction, carbon mineralization, and methane dynamics. The results show that cryptic sulfur cycling enhances dissolved Fe 2+ production, regulates methane concentrations, and is strongly controlled by climate-driven hydrologic fluxes. By linking hydroclimate, subsurface flow, and biogeochemical reactions, this work provides a predictive framework for understanding how wetland systems respond to environmental change, with direct implications for water quality and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Anisotropic fluid dynamical simulations of heavy-ion collisions

We present VAH, a (3+1)–dimensional simulation that evolves the far-from-equilibrium quark-gluon plasma produced in ultrarelativistic heavy-ion collisions with anisotropic fluid dynamics. We solve the hydrodynamic equations on an Eulerian grid using the Kurganov–Tadmor algorithm in combination with a new adaptive Runge–Kutta method. Our numerical scheme allows us to start the simulation soon after the nuclear collision, largely avoiding the need to integrate it with a separate pre-equilibrium dynamics module. We test the code's performance by simulating on the Eulerian grid conformal and non-conformal Bjorken flow as well as conformal Gubser flow, whose (0+1)–dimensional solutions are precisely known. Finally, we compare non-conformal anisotropic hydrodynamics to second-order viscous hydrodynamics in central Pb+Pb collisions and find that the former's longitudinal flow profile responds more consistently to the fluid's gradients along the spacetime rapidity direction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

An arbitrarily high-order three-dimensional Cartesian-grid method for reconstructing interfaces from volume fraction fields

Here Tthis work describes a newly developed, arbitrarily high-order Cartesian-grid method for reconstructing material interfaces from a volume fraction field. The method begins by identifying all of the grid cells in the volume fraction field that are intersected by the interface and need to be approximated by the reconstruction scheme. Finite-differences are used to calculate the gradient of the volume fraction field and provide an estimate of the surface normal in all of the interfacial grid cells. Groups of connected grid cells are then identified which all have the same dominant component of the normal vector. This grouping by orientation determines the proper dependent variable to use in the surface reconstruction (e.g. for a 2D curve, this step determines if the surface will be approximated by a function of x or y). A cumulative integral over the surface is constructed and fit using b-splines for two-dimensional problems or tensor-product b-splines for three-dimensional problems. This construction allows for the interface to be recovered through application of the second fundamental theorem of calculus. Fitting the cumulative integral with $\mathscr{N}$ th-order b-splines (or tensor-product b-splines) yields an ($\mathscr{N}$-1) th-order convergence rate of the interface shape. Differentiation of the b-spline interface function(s) allows for the high-order approximation of the normal vector and curvature to be obtained directly anywhere along b-spline. Together, the proposed reconstruction technique can achieve arbitrarily high mesh convergence rates. Validation tests are presented with mesh convergence rates ranging from fourth- to tenth-order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Data from a throughfall exclusion experiment: Fine root dynamics, morphology, chemistry, and AMF colonization across four lowland Panamanian forests

Fine roots regulate forest nutrient, carbon, and water cycling, yet their variation within and among tropical forests remains under-characterized. We quantified root productivity, disappearance, and stocks to 1 m using minirhizotron imaging, and we measured morphology, elemental composition [root carbon (C), root nitrogen (N), root phosphorus (P)], and arbuscular mycorrhizal fungi (AMF) colonization to 20 cm using ingrowth cores and sequential coring. Sampling took place in four distinct lowland Panamanian forests (32 plots; 8 per forest) from 2018 through 2022 under control and throughfall-exclusion (drought) treatments in the Panama Rainforest Changes with Experimental Drying (PARCHED) experiment.The dataset is presented as an Excel workbook with six tabs. The first tab is the data dictionary. Tab S1 contains ingrowth-core production and mortality, morphology and soil moisture. Tab S2 contains sequential-coring standing stocks with associated morphology and soil moisture. Tab S3 contains minirhizotron row data records to 1 m depth, including per-frame root length and diameter, normalized length metrics, and session timing. Tab S4 contains AMF colonization. Tab S5 contains fine-root chemistry at 0–10 cm, reporting %P, %C, %N, and C:N for samples collected via ingrowth cores and sequential-coring standing stocks. CSV mirrors for each tab are provided, and a KML file supplies coordinates for all 32 plots.Key variables span live and dead fine-root biomass (and coarse fractions where applicable), specific root length (SRL) and area (SRA), diameter, root tissue density (RTD), soil moisture, AMF colonization, root %N, %C, %P, and C:N, along with minirhizotron root length and diameter. Depth, season, treatment, and plot/site identifiers are included to support cross-tab integration and analysis from 0–100 cm (minirhizotron) and 0–20 cm (cores).Units are reported in-column and missing values are coded as NA. No special software is required to open or use the files (Excel, CSV, and KML compatible).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Geometrically Tunable Beamed Light Emission from a Quantum‐Dot Ensemble Near a Gradient Metasurface

Abstract Optical metasurfaces have been widely investigated in recent years as a means to tailor the wavefronts of externally incident light for passive device applications. At the same time, their use in active optoelectronic devices such as light emitters is far less established. This work explores their ability to control the radiation properties of a nearby continuous ensemble of randomly oriented incoherent dipole sources via near‐field interactions. Specifically, a film of colloidal quantum dots is deposited on a plasmonic metasurface consisting of a 1D array of metallic nanoantennas on a metal film. The array is designed to introduce a linear phase profile upon reflection, and a bi‐periodic nanoparticle arrangement is introduced to ensure adequate sampling of the desired phase gradient. Highly directional radiation patterns are correspondingly obtained from the quantum dots at an enhanced emission rate. The underlying radiation mechanism involves the near‐field excitation of surface plasmon polaritons at the metal film, and their selective diffractive scattering by the metasurface into well‐collimated beams along predetermined geometrically tunable directions. These results underscore the distinctive ability of metasurfaces to control radiation properties directly at the source level, which is technologically significant for the continued miniaturization and large‐scale integration of optoelectronic devices.

Wang, Xiaowei↗
DOE OSTI2025

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗
DOE OSTI2024

Retrofittable Thermal Switches for Dynamic Building Envelopes Integrated with Thermal Energy Storage: Preprint

Buildings in the United States consume about 40 quadrillion BTU of primary energy annually, which accounts for the nation's 40% of total energy use, 75% of all electricity use, and 35% of the net carbon emissions. Deploying thermal energy storage in the form of phase change material (PCM) in building envelopes is an effective method to reduce space heating/cooling loads, provide load shedding, and shift demand to periods of lower energy cost. However, the full potential of PCM-integrated envelopes can only be realized if the PCM undergoes complete phase change using free ambient heating/cooling, and the stored energy is effectively transferred between the exterior and the interior environments. Conventional thermal insulation (with a fixed thermal resistance) limits PCM utilization, particularly with the increasing emphasis on higher R-value in building envelopes, which negatively affects the energy-saving potential of a PCM-integrated envelope. In contrast, dynamic building envelopes integrated with PCMs provide the option of varying the thermal resistance based on the indoor and outdoor conditions, thereby enhancing utilization of free ambient cooling and heating to charge/discharge the PCM thermal storage, reducing the buildings' heating and cooling load, and shifting the peak energy demand. In this study, we demonstrate innovative retrofittable thermal switches in the form of the insertable plugs inside an insulation to provide variable thermal resistance depending on the operating temperature and direction of temperature gradient, thus allowing preferential directional heat flow. Notably, they are passive in nature, requiring no external power, and work solely based on the ambient temperature.

buildings↗
DOE OSTI2022

Toward an integrated platform for characterizing laser-driven, isochorically heated plasmas with 1 µm spatial resolution

Warm dense matter is a region of phase space that is of high interest to multiple scientific communities ranging from astrophysics to inertial confinement fusion. Further understanding of the conditions and properties of this complex state of matter necessitates experimental benchmarking of the current theoretical models. We discuss the development of an x-ray radiography platform designed to measure warm dense matter transport properties at large laser facilities such as the OMEGA Laser Facility. Our platform, Fresnel Diffractive Radiography, allows for high spatial resolution imaging of isochorically heated targets, resulting in notable diffractive effects at sharp density gradients that are influenced by transport properties such as thermal conductivity. We discuss initial results, highlighting the capabilities of the platform in measuring diffractive features with micron-level spatial resolution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗