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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Surface-Enhanced Raman Scattering (SERS) Studies of Disc-on-Pillar (DOP) Arrays: Contrasting Enhancement Factor with Analytical Performance

The use of nanomachining methods capable of reproducible construction of nano-arrayed devices have revolutionized the field of plasmonic sensing by the introduction of a diversity of rationally engineered designs. Significant strides have been made to fabricate plasmonic platforms with tailored interparticle gaps to improve their performance for surface-enhanced Raman scattering (SERS) applications. Over time, a dichotomy has emerged in the implementation of SERS for analytical applications, the construction of substrates, optimization of interparticle spacing as a means to optimize electromagnetic field enhancement at the localized surface plasmon level, and the substrate sensitivity over extended areas to achieve quantitative performance. Here, we assessed the enhancement factor of plasmonic Ag/SiO 2 /Si disc-on-pillar (DOP) arrays of variable pitch with its analytical performance for quantitative applications. Experimental data were compared with those from finite-difference time-domain (FDTD) simulations used in the optimization of the array dimensions. A self-assembled monolayer (SAM) of benzenethiol rendered highly reproducible signals (RSD ~4–10%) and SERS substrate enhancement factor (SSEF) values in the orders of 10 6 –10 8 for all pitches. Furthermore, spectra corresponding to rhodamine 6G (R6G) and 4-aminobenzoic acid demonstrated the advantages of using the more densely packed DOP arrays with a 160 nm pitch (gap= 40 nm) for quantitation in spite of the strongest SSEF was attained for a pitch of 520 nm corresponding to a 400 nm gap.

36 MATERIALS SCIENCE↗
DOE OSTI2026

When does global attention help: a unified empirical study on atomistic graph learning

Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is constantly increasing to enable the modeling of complex physics. While most recent GNNs combine more traditional message passing neural networks (MPNNs) layers to model short-range interactions with more advanced graph transformers (GTs) with global attention mechanisms to model long-range interactions, it is still unclear when global attention mechanisms provide real benefits over well-tuned MPNN layers due to inconsistent implementations, features, or hyperparameter tuning. We introduce the first unified, reproducible benchmarking framework–built on HydraGNN–that enables seamless switching among four controlled model classes: MPNN, MPNN with chemistry/topology encoders, GPS-style hybrids of MPNN with global attention, and fully fused localglobal models with encoders. Using seven diverse open-source datasets for benchmarking across regression and classification tasks, we systematically isolate the contributions of message passing, global attention, and encoder-based feature augmentation. Our study shows that encoder-augmented MPNNs form a robust baseline, while fused localglobal models yield the clearest benefits for properties governed by long-range interaction effects. We further quantify the accuracycompute trade-offs of attention, reporting its overhead in memory. Together, these results establish the first controlled evaluation of global attention in atomistic graph learning and provide a reproducible testbed for future model development.

Equivariant graph neural networks↗
DOE OSTI2022

HT-SIP: a semi-automated stable isotope probing pipeline identifies cross-kingdom interactions in the hyphosphere of arbuscular mycorrhizal fungi

Abstract Background Linking the identity of wild microbes with their ecophysiological traits and environmental functions is a key ambition for microbial ecologists. Of many techniques that strive for this goal, Stable-isotope probing—SIP—remains among the most comprehensive for studying whole microbial communities in situ. In DNA-SIP, actively growing microorganisms that take up an isotopically heavy substrate build heavier DNA, which can be partitioned by density into multiple fractions and sequenced. However, SIP is relatively low throughput and requires significant hands-on labor. We designed and tested a semi-automated, high-throughput SIP (HT-SIP) pipeline to support well-replicated, temporally resolved amplicon and metagenomics experiments. We applied this pipeline to a soil microhabitat with significant ecological importance—the hyphosphere zone surrounding arbuscular mycorrhizal fungal (AMF) hyphae. AMF form symbiotic relationships with most plant species and play key roles in terrestrial nutrient and carbon cycling. Results Our HT-SIP pipeline for fractionation, cleanup, and nucleic acid quantification of density gradients requires one-sixth of the hands-on labor compared to manual SIP and allows 16 samples to be processed simultaneously. Automated density fractionation increased the reproducibility of SIP gradients compared to manual fractionation, and we show adding a non-ionic detergent to the gradient buffer improved SIP DNA recovery. We applied HT-SIP to 13 C-AMF hyphosphere DNA from a 13 CO 2 plant labeling study and created metagenome-assembled genomes (MAGs) using high-resolution SIP metagenomics (14 metagenomes per gradient). SIP confirmed the AMF Rhizophagus intraradices and associated MAGs were highly enriched (10–33 atom% 13 C), even though the soils’ overall enrichment was low (1.8 atom% 13 C). We assembled 212 13 C-hyphosphere MAGs; the hyphosphere taxa that assimilated the most AMF-derived 13 C were from the phyla Myxococcota, Fibrobacterota, Verrucomicrobiota, and the ammonia-oxidizing archaeon genus Nitrososphaera . Conclusions Our semi-automated HT-SIP approach decreases operator time and improves reproducibility by targeting the most labor-intensive steps of SIP—fraction collection and cleanup. We illustrate this approach in a unique and understudied soil microhabitat—generating MAGs of actively growing microbes living in the AMF hyphosphere (without plant roots). The MAGs’ phylogenetic composition and gene content suggest predation, decomposition, and ammonia oxidation may be key processes in hyphosphere nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The need for standardization and improved open (meta)data practices in metaproteomics

Metaproteomics enables functional insight into microbial communities by identifying and quantifying proteins in complex samples. Yet, heterogeneous analytical workflows and the lack of standardization across experimental and bioinformatics stages hinder reproducibility and comparability, limiting integration with other omics data. We here present a community-developed reporting checklist tailored to the specific needs of metaproteomics. We also outline current efforts to enable structured and interoperable metadata capture, drawing on standards from proteomics and microbiome research wherever possible. By promoting transparent reporting and advancing metadata practices, our recommendations aim to align metaproteomics more closely with FAIR principles and support reproducible and interoperable research practices.

Armengaud, Jean [Universite Paris-Saclay, France]↗
DOE OSTI2024

ExaCA grain structure predictions for laser powder bed fusion processing

This dataset contains simulated cross-sections of laser powder bed fusion grain structures produced using the microstructure model ExaCA, in turn using time-temperature history data produced using the heat transport model AdditiveFOAM. These predictions show the grain structure using various permutations of hatch spacing and nucleation density. Also contained in the dataset are the input files necessary to reproduce the results. AdditiveFOAM (https://github.com/ORNL/AdditiveFOAM) and ExaCA (https://github.com/LLNL/ExaCA), both open source software, are required to reproduce the results in this dataset using the given input files. This DOI was updated 12/09/2025.

36 MATERIALS SCIENCE↗
DOE OSTI2025

SCALE Non-LWR Models for NRC Volume 3

This dataset contains input and result files of computational simulations with the SCALE code system. The simulations cover radionuclide inventory and reactivity analyses of various advanced reactors. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

SCALE Non-LWR Models for NRC Volume 5

This dataset contains input and result files of computational simulations with the SCALE code system. The simulations cover radionuclide inventory generation, criticality calculations, and dose rate/shielding analyses of various advanced reactors. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

SCALE HTR-PROTEUS Benchmark Model

This dataset contains input and result files of computational simulations of HTR-PROTEUS benchmark with the latest version of SCALE code system. The simulations cover criticality control rod worth calculations as well as sensitivity analysis and uncertainty quantification. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Impact of increased smoothing by spectral dispersion bandwidth on stimulated Brillouin scattering in laser driven Hohlraums

Experiments were conducted at the National Ignition Facility (NIF) to investigate the impact of increased smoothing by spectral dispersion (SSD) bandwidth on the production of stimulated Brillouin scattering (SBS) within an indirect-drive inertial confinement fusion (ICF) Hohlraum. This was done in a subscale gold Hohlraum driven by 192 laser beams depositing 1.1 MJ of energy. The laser bandwidth was increased from 45 to 118 GHz (before frequency tripling) on the 30° and 50° cones, where backscatter could be measured using the Full Aperture Backscatter Station (FABS). It was expected that this 2.6-fold increase in bandwidth would suppress SBS generated within the Hohlraum plasma and lower the backscattered SBS energy on the 50° cones by over a factor of four. Experimental results, however, show that this SSD change only reduced the 50° cone SBS during the main capsule drive by -18±31% and -4.5±7.8% over the entire pulse. This is small compared to expected shot-to-shot SBS reproducibility (∼30%), such that the result can be considered within normal performance fluctuations. New 3D parallel paraxial code (pF3D) simulations, accounting for beam refractive intensification reproduce this result, suggesting that closer to 300 GHz of bandwidth would have been required to mitigate SBS to the expected level. Delivering such a high bandwidth is not feasible at NIF when operating at high peak power and would potentially prevent NIF’s ability to use cross-beam energy transfer (CBET) for implosion symmetry tuning.

Physics↗
DOE OSTI2026

A standardized workflow for kinetic metabolic model curation and dissemination

Kinetic metabolic models provide invaluable insights into cellular metabolism, supporting applications in synthetic biology, metabolic engineering, and systems biology. However, reproducibility and utility of these models hinge on clear and rigorous documentation, standardized annotation, and accessible visualization. This paper presents a workflow for building, annotating, visualizing, and sharing kinetic metabolic models. Our method integrates community standards and open-source tools to ensure reproducibility, interoperability, and user accessibility. This procedure enables researchers to produce reusable and well-documented kinetic models, advancing their role as powerful tools in metabolic research.

Cook, Margaret [Univ. of Washington, Seattle, WA (↗
DOE OSTI2023

Pangeo-Enabled ESM Pattern Scaling (PEEPS): A customizable dataset of emulated Earth System Model output

Emulation through pattern scaling is a well-established method of rapidly producing climate fields (like temperature or precipitation) from existing Earth System Model (ESM) output that, while inaccurate, is often useful for a variety of downstream purposes. Conducting pattern scaling has historically been a laborious process, in large part due to the increasing volume of ESM output data that has often required downloading and storing locally to train on. Here we describe the Pangeo-Enabled ESM Pattern Scaling (PEEPS) dataset, a repository of trained annual and monthly patterns from CMIP6 outputs. This manuscript describes and validates these updated patterns so that users can save effort calculating and reporting error statistics in manuscripts focused on the use of patterns. The trained patterns are available as NetCDF files on Zenodo for ease of use in the impact community, and are reproducible with the code provided via GitHub in both Jupyter notebook and Python script formats. Because all training data for the PEEPS data set is cloud-based, users do not need to download and house the ESM output data to reproduce the patterns in the zenodo archive, should that be more efficient. Validating the PEEPS data set on the CMIP6 archive for annual and monthly temperature, precipitation, and near-surface relative humidity, pattern scaling performs well over a variety of future scenarios except for regions in which there are strong, potentially nonlinear climate feedbacks. Although pattern scaling is normally conducted on annual mean ESM output data, it works equally well on monthly mean ESM output data. We identify several downstream applications of the PEEPS data set, including impacts assessment and evaluating certain types of Earth system uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern

Researchers published many studies which sought to predict and forecast important features of Zika virus (ZIKV) infections and their spread during the 2016–2017 ZIKV pandemic. We conducted a comprehensive review of such ZIKV prediction studies and evaluated their aims, the data sources they used, which methods were used, how timely they were published, and whether they provided sufficient information to be used or reproduced by others. Of the 73 studies evaluated, we found the accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied; indicating there is substantial room for improvement. We identified that the release of study findings before formal journal publication (‘pre-prints’) increased the timeliness of Zika prediction studies, but note they were infrequently used during this public health emergency. Addressing these areas can improve our understanding of Zika and other outbreaks and ensure forecasts can inform preparedness and response to future outbreaks, epidemics, and pandemics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A novel assay to measure low-density lipoproteins binding to proteoglycans

Background: The binding of low-density lipoprotein (LDL) to proteoglycans (PGs) in the extracellular matrix (ECM) of the arterial intima is a key initial step in the development of atherosclerosis. Although many techniques have been developed to assess this binding, most of the methods are labor-intensive and technically challenging to standardize across research laboratories. Thus, sensitive, and reproducible assay to detect LDL binding to PGs is needed to screen clinical populations for atherosclerosis risk. Objectives: The aim of this study was to develop a quantitative, and reproducible assay to evaluate the affinity of LDL towards PGs and to replicate previously published results on LDL-PG binding. Methods: Immunofluorescence microscopy was performed to visualize the binding of LDL to PGs using mouse vascular smooth muscle (MOVAS) cells. An in-cell ELISA (ICE) was also developed and optimized to quantitatively measure LDL-PG binding using fixed MOVAS cells cultured in a 96-well format. Results: We used the ICE assay to show that, despite equal APOB concentrations, LDL isolated from adults with cardiovascular disease bound to PG to a greater extent than LDL isolated from adults without cardiovascular disease (p<0.05). Conclusion: We have developed an LDL-PG binding assay that is capable of detecting differences in PG binding affinities despite equal APOB concentrations. Future work will focus on candidate apolipoproteins that enhance or diminish this interaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Correlating transcription and protein expression profiles of immune biomarkers following lipopolysaccharide exposure in lung epithelial cells

Universal and early recognition of pathogens occurs through recognition of evolutionarily conserved pathogen associated molecular patterns (PAMPs) by innate immune receptors and the consequent secretion of cytokines and chemokines. The intrinsic complexity of innate immune signaling and associated signal transduction challenges our ability to obtain physiologically relevant, reproducible and accurate data from experimental systems. One of the reasons for the discrepancy in observed data is the choice of measurement strategy. Immune signaling is regulated by the interplay between pathogen-derived molecules with host cells resulting in cellular expression changes. However, these cellular processes are often studied by the independent assessment of either the transcriptome or the proteome. Correlation between transcription and protein analysis is lacking in a variety of studies. In order to methodically evaluate the correlation between transcription and protein expression profiles associated with innate immune signaling, we measured cytokine and chemokine levels following exposure of human cells to the PAMP lipopolysaccharide (LPS) from the Gram-negative pathogen Pseudomonas aeruginosa . Expression of 84 messenger RNA (mRNA) transcripts and 69 proteins, including 35 overlapping targets, were measured in human lung epithelial cells. We evaluated 50 biological replicates to determine reproducibility of outcomes. Following pairwise normalization, 16 mRNA transcripts and 6 proteins were significantly upregulated following LPS exposure, while only five (CCL2, CSF3, CXCL5, CXCL8/IL8, and IL6) were upregulated in both transcriptomic and proteomic analysis. This lack of correlation between transcription and protein expression data may contribute to the discrepancy in the immune profiles reported in various studies. The use of multiomic assessments to achieve a systems-level understanding of immune signaling processes can result in the identification of host biomarker profiles for a variety of infectious diseases and facilitate countermeasure design and development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Challenges in correlating oxygen stable isotope ratios of hydrates on uranium ore concentrates to process waters

Exchange of oxygen stable isotopes (δ 18 O values) between precipitation waters and uranium oxides is governed by thermodynamics or kinetics. It has been assumed that meteoric waters can be related to precipitation waters in uranium ore concentrates and their calcination and reduced uranium oxide products. With this assumption, the δ 18 O values of uranium materials could provide forensic signatures that identify the production history and geolocation of nuclear materials. To further exploit the potential of δ 18 O values in nuclear material analysis, this study examines the oxygen stable isotope exchange in two UOCs, magnesium diuranate (MDU) and sodium diuranate (SDU). MDU and SDU were synthesized from solutions of uranyl nitrate hexahydrate using precipitation waters with unique oxygen isotope compositions. The structures of the MDU and SDU were analyzed using powder X-ray diffraction (p-XRD) and thermal mass loss curves, while the δ 18 O values of waters generated during thermal decomposition were analyzed using a thermogravimetric analyzer coupled to an isotope ratio infrared spectrometer (TGA-IRIS). By p-XRD, the MDU was uniform and amorphous across all syntheses with residual crystalline material incorporated as a minor component. Combined with the TGA results, all of the MDU is likely amorphous MgU 2 O 7 ·3H 2 O with MgO impurities present throughout. In contrast, the SDU synthesis resulted in multiple phases with many samples exhibiting crystalline phases including a combination of Na(UO 2 ) 4 O 2 (OH) 5 ·5H 2 O and Na 2 (UO2) 6 O 4 (OH) 6 ·8H 2 O with a Na 2 U 2 O 7 minor phase. A small fraction of the SDU samples were amorphous with no crystalline XRD peaks observed. Mass loss curves of the SDU samples revealed that the amorphous samples contained inclusions of similar crystalline phases compared to the crystalline materials. The uniformity of the MDU samples enabled highly reproducible measurements of δ 18 O values of the water vapor yielded for two dehydration events at 170 °C and 500 °C. In contrast, the multiphase composition of the SDU samples resulted in poor reproducibility in δ 18 O values. In conclusion, neither system revealed any correlation between the δ 18 O values of precipitation water, and the waters released during dehydration of the UOCs.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Manuscript model outputs, model source code, and figure scripts: The role of geomorphology in mediating biomass allocation impacts on salt-marsh resilience and carbon accumulation

This data package provides model source code (C++), model outputs, and figure generation scripts (R) needed to reproduce the following manuscript: Bruns, Nicholas E., Genevieve L. Noyce, and Matthew L. Kirwan. "The Role of Geomorphology in Mediating Biomass Allocation Impacts on Salt-Marsh Resilience and Carbon Accumulation." Estuarine, Coastal and Shelf Science 327 (December 2025): 109549. https://doi.org/10.1016/j.ecss.2025.109549. This manuscript investigates how geomorphology mediates the impact of biomass allocation shifts on salt marsh persistence and carbon (C) sequestration under sea level rise. We use a 1-D soil-column model (Kirwan and Mudd 2012) to perform experiments across a range of static root:shoot ratios (RSR = 1-4) spanning observed values. The model explicitly simulates interactions between tidal inundation, productivity, inorganic sediment deposition, and organic matter accumulation. Experiments determine whether geomorphic feedbacks amplify, dampen, or leave unchanged the ecosystem response to biomass allocation shifts. A first experiment uses constant sea level rise (2.5 mm/yr) to examine equilibrium dynamics and their influence on carbon accumulation rates across different suspended sediment concentrations (SSC). A second set of experiments calculates threshold sea level rise rates for marsh drowning across RSR and SSC combinations. Final experiments apply accelerating sea level rise scenarios (2000-2200) derived from NOAA projections (Sweet et al. 2022) to generate an envelope of expected responses, quantifying the importance of biomass allocation shifts on marsh carbon accumulation and persistence. All experiments are repeated across SSC ranging from 5-50 mg/L to investigate how these interactions vary in micro-tidal marshes with different sediment supplies. Package contents: * README.txt with detailed description of package contents and instructions for reproducing manuscript figures and model outputs * R scripts for generating all manuscript figures * C++ baseline model code from Kirwan and Mudd (2012) * C++ source code for 4 experimental model variants used in the manuscript, extending above baseline code * Model input files (.csv, .txt) including sea level rise scenarios * Model output files (.txt) used in manuscript analyses Temporal coverage: Model simulations span years 1900-2200, with accelerating sea level rise scenarios for 2000-2200. Key variables: Root:shoot ratio, suspended sediment concentration, carbon accumulation rate, vertical accretion rate, marsh elevation, inundation depth, threshold sea level rise rate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Model Data Archive Associated with Manuscript "Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon"

This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.

ATS↗
DOE OSTI2026

Data & Code from Phoenix CPPP Phase 2 Analysis

This data and code package supports the analysis presented in “Beyond Surface Cooling: Comprehensive Field Assessment of Reflective Pavement Thermal Performance in Phoenix, Arizona” and provides fully reproducible workflows for evaluating the thermal performance of cool pavement treatments in a hot urban environment. The dataset integrates multi-modal field measurements collected across residential and nonresidential settings, including mobile air temperature traverses, stationary air temperature monitoring, residential mean radiant temperature (MRT) measurements, subsurface temperature profiles, and controlled testbed observations. The data package contains raw and processed datasets in comma-separated value (CSV) format, accompanying metadata files describing site characteristics and measurement protocols, and R scripts (.R files) used for data cleaning, time synchronization, spatial and temporal matching, quality control filtering, statistical comparison, and figure generation. All analyses were conducted using R (version ≥ 4.2.0) with commonly available packages (e.g., tidyverse, lubridate, data.table, ggplot2). No proprietary software is required to reproduce results. Field campaigns were designed to quantify the effects of high-reflectance pavement coatings on surface temperature, near-surface air temperature, subsurface heat propagation, and radiative heat exposure. Temporal alignment procedures include standardized timestamp conversion and nearest-neighbor matching of high-frequency sensor measurements to stop-based metadata within defined tolerance windows to ensure comparability across instruments. The workflows generate summary statistics, treatment–control contrasts, depth-dependent thermal gradients, and time-series visualizations used in the associated publication. By integrating mobile, stationary, radiative, and subsurface measurements within a unified and transparent processing framework, this package enables comprehensive evaluation of cool pavement performance across multiple thermal exposure pathways and supports reuse in future urban heat mitigation and climate resilience studies.

AIR TEMPERATURE↗