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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 109 records · Page 6

Measuring the growth of Alfvén wave parametric decay instability using counter-propagating waves: Theory and simulations

The parametric decay instability (PDI) of Alfvén waves—where a pump Alfvén wave decays into a backward-propagating child Alfvén wave and a forward ion acoustic wave—is a fundamental nonlinear wave-wave interaction and holds significant implications for space and laboratory plasmas. However, to date there has been no direct experimental measurement of PDI. Here, we propose a novel and experimentally viable scheme to quantify the growth of Alfvén wave PDI on a linear device using a large pump Alfvén wave and a small counter-propagating seed Alfvén wave, with the seed-wave frequency tuned to match the backward Alfvén wave generated by standard PDI. Using hybrid simulations, we show that energy transfer from the pump to the seed reduces the latter's spatial damping. By comparing seed-wave amplitudes with and without the pump wave, this damping reduction can be used as a direct and reliable proxy for PDI growth. The method is validated in our simulations across a range of plasma and wave parameters and agrees well with theoretical predictions. Notably, the scheme exhibits no threshold for PDI excitation and is, in principle, readily implementable under current laboratory conditions. Finally, this scheme is a critical step toward solving the challenge of experimentally accessing Alfvén wave PDI and provides an elegant method that may be used to validate fundamental theories of parametric instabilities in controlled laboratory settings.

heliosphere↗

Time-Resolved Hanbury Brown–Twiss Interferometry of On-Chip Biphoton Frequency Combs Using Vernier Phase Modulation

Biphoton frequency combs (BFCs) are promising quantum sources for large-scale and high-dimensional quantum information and networking systems. In this context, the spectral purity of individual frequency bins will be critical for realizing quantum networking protocols like teleportation and entanglement swapping. Measurement of the temporal autocorrelation function of the unheralded signal or idler photons comprising the BFC is a key tool for characterizing their spectral purity and in turn verifying the utility of the biphoton state for networking protocols. Yet the experimentally obtainable precision for measuring BFC correlation functions is often severely limited by detector jitter. The fine temporal features in the correlation function—not only of practical value in quantum information, but also of fundamental interest in the study of quantum optics—are lost as a result. We propose a scheme to circumvent this challenge through electro-optic phase modulation, experimentally demonstrating time-resolved Hanbury Brown–Twiss characterization of BFCs generated from an integrated 40.5-GHz Si 3 N 4 microring, up to a 3×3-dimensional two-qutrit Hilbert space. Through slight detuning of the electro-optic drive frequency from the comb’s free spectral range, our approach leverages Vernier principles to magnify temporal features, which would otherwise be averaged out by detector jitter. We demonstrate our approach under both continuous-wave and pulsed-pumping regimes, finding excellent agreement with theory. In conclusion, our method reveals not only the collective statistics of the contributing frequency bins but also their temporal shapes—features lost in standard fully integrated autocorrelation measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stimulated Emission of Signal Photons from Dark Matter Waves

The manipulation of quantum states of light has resulted in significant advancements in both dark matter searches and gravitational wave detectors. Current dark matter searches operating in the microwave frequency range use nearly quantum-limited amplifiers. Future high frequency searches will use photon counting techniques to evade the standard quantum limit. We present a signal enhancement technique that utilizes a superconducting qubit to prepare a superconducting microwave cavity in a nonclassical Fock state and stimulate the emission of a photon from a dark matter wave. By initializing the cavity in an | n = 4 ⟩ Fock state, we demonstrate a quantum enhancement technique that increases the signal photon rate and hence also the dark matter scan rate each by a factor of 2.78. Using this technique, we conduct a dark photon search in a band around 5.965 GHz ( 24.67 μ eV ), where the kinetic mixing angle ε ≥ 4.35 × 10 − 13 is excluded at the 90% confidence level. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Distributed Brillouin fiber laser sensor

Brillouin fiber sensors can provide distributed strain and temperature measurements over long distances in standard off-the-shelf fiber by measuring the Brillouin frequency shift as a function of position along a fiber. The primary drawback of these systems is their limited sensitivity, which results from the challenge in identifying the Brillouin frequency shift to within a small fraction of the Brillouin linewidth. In this work, we introduce a technique that overcomes this fundamental limitation by establishing a series of lasing modes that experience Brillouin amplification at discrete spatial locations in the test fiber. The linewidth narrowing and high intensity associated with the lasing transition enable precise measurements of this lasing frequency. As an initial demonstration, we present a sensor that simultaneously excites 40 lasing modes in a 400 m fiber, providing a measurement of the strain at 40 discrete locations with a spatial resolution of 4 m. Each sensor exhibits a minimum detectable strain as low as 4 nε/Hz 1/2 with a dynamic range of >5 mε and a bandwidth of ~10 kHz. As the first demonstration that Brillouin lasing can be used for distributed fiber sensing, this work establishes an approach that could enable ultra-high strain sensitivity using off-the-shelf fiber.

47 OTHER INSTRUMENTATION↗

Two-dimensional heteronuclear single quantum coherence (HSQC) NMR spectra of lignin isolated from field grown transgenic poplar

Here we present a curated dataset of a series of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from a field grown transgenic poplar engineered with a monolignol 4-O-methyltransferase (MOMT4). The poplar was collected from a 2-year-old rotation trees within a three-year field trial experiment. The poplar was Soxhlet-extracted with toluene/ethanol and the extractives-free poplar was then ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96:4 (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover the lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide for NMR experiments. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence (hsqcetgpsisp2.2) on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 220 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 1024 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. All the data was processed using the Bruker’s TopSpin 3.6 software. The NMR spectra provides structural characteristics information about lignin in field grown transgenic MOMT4 poplar. Additional meta data is embedded in the raw spectra figures.

Lignin structure, HSQC, poplar, field trial, MOMT4↗

Carbon-13 NMR spectra of lignin isolated from field grown transgenic poplar

Here we present a curated dataset of a series of 13C nuclear magnetic resonance (NMR) spectra of lignin isolated from transgenic monolignol 4-O-methyltransferase (MOMT4) engineered poplar. The transgenic poplar was collected from a 3-year field trial experiment. The poplar was Soxhlet-extracted with toluene/ethanol and the extractives-free poplar was then ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h. The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96:4 (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover the lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide for NMR characterization. 13C experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence (zgpg) on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following conditions: spectra width 229 ppm, 64k data points, 1s pulse delay, and 6k scans. All the data was processed using the Bruker’s TopSpin 3.6 software. Additional meta data is embedded in the raw spectra files.

13C NMR, lignin, poplar, field trial, MOMT4, CBI↗

Proton NMR spectra of lignin isolated from field grown transgenic poplar

Here we present a curated dataset of a series of 1H nuclear magnetic resonance (NMR) spectra of lignin isolated from transgenic monolignol 4-O-methyltransferase (MOMT4) engineered poplar. The transgenic poplar was collected from a 2-year-old rotation trees within a three-year field trial experiment. Two replicates were collected for each transgenic poplar for the 1H NMR analysis. The poplar samples were Soxhlet-extracted with toluene/ethanol to remove the extractives and the extractives-free poplar was then ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h. The ball-milled materials were subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96:4 (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide and transferred into a 5 mm NMR tube. 1H NMR experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence (zg) on a Prodigy platform cryoprobe. The NMR spectra were acquired with 16 ppm spectra width, 32k data points, 3s pulse delay, and 16 scans. All the data was processed using the Bruker’s TopSpin 3.6 software. Additional meta data is embedded in the raw spectra files.

1H NMR, lignin, poplar, field trial, MOMT4, CBI↗

HSQC spectra of lignin isolated from poplar stems

Here we present a curated dataset of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from stems of genetically engineered poplar through auxin signaling gene modification. The plants were grown in greenhouse with temperatures between 21 and 23 °C. Plants were harvested and the aboveground stems were cut off an approximately five-inch-long segment from the bottom end of the plant stem, debarked and air-dried for three weeks. The dried stem samples were Wiley milled (mesh size 20), Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extracted biomass was ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was freeze-dried to recover the lignin. The dry stem lignin samples were dissolved in deuterated dimethyl sulfoxide (d6) and transferred into a 5 mm tube. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 230 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 2048 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. Spectra were processed using the Bruker TopSpin 3.6 software. Additional meta data is embedded in the raw spectra figures.

HSQC, lignin, poplar, stems, CBI↗

HSQC spectra of lignin isolated from poplar roots

Here we present a curated dataset of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from roots of a greenhouse grown natural population of an energy crop poplar (Populus trichocarpa). Dormant cuttings of field-grown poplar were grown in 6-liter pots in a peat-based media containing bark, perlite, vermiculite, dolomite lime and a wetting agent in an environmentally controlled greenhouse. Temperatures were between 21 and 23 °C, with supplemental lighting to support a 16-h day length using 1000-watt high-pressure sodium lights in greenhouse. Once established, all plants were cut-back, allowed to regrow and harvested at the same time following an eight-month long growth period. Plants were harvested and the belowground roots were washed off soils, blotted, dried in an oven at 70 °C for 3 days, and Wiley milled (mesh size 20). The roots were Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extracted roots were ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96% (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide (d6) and transferred into a 5 mm tube. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 220 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 1024 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. Spectra were processed using the Bruker TopSpin software. Additional meta data is embedded in the raw spectra figures.

HSQC, lignin, poplar, roots, CBI↗

Weather and climate extremes in a changing Arctic

Weather and climate extremes are increasingly occurring in the Arctic. Here, in this Review, we evaluate historical and projected changes in rare Arctic extremes across the atmosphere, cryosphere and ocean and elucidate their driving mechanisms. Clear shifts occur in mean and extreme distributions after ~2000. For instance, pre-2000 to post-2000 observational probabilities of 1.5 standard deviation events increase by 20% for atmospheric heat waves, 76.7% for Atlantic layer warm events, 83.5% for Arctic sea ice loss and 62.9% for Greenland Ice Sheet melt extent — in many cases, low probability, rare extreme events in the early period become the norm in the latter period. These observed changes can be explained using a ‘pushing and triggering’ concept, representing interplay between external forcing and internal variability: long-term warming destabilizes the climate system and ‘pushes’ it to a new state, allowing subsequent variability associated with large-scale atmosphere–ocean–ice interactions and synoptic systems to ‘trigger’ extreme events over different timescales. Ongoing anthropogenic warming is expected to further increase the frequency and magnitude of extremes, such that simulated probabilities of 1.5 standard deviation events increase by 72.6% for atmospheric heat waves, 68.7% for Atlantic layer warm events and 93.3% for Greenland Ice Sheet melt rate between historic (1984–2014) and future (2069–2099) periods under a very high emission scenario. Future research should prioritize the development of physically based metrics, enhance high-resolution observation and modelling capabilities and improve understanding of multiscale Arctic climate drivers.

atmospheric dynamics↗

Factors That Influence Variability in Stress-Drop Measurements Using Spectral Decomposition and Spectral-Ratio Methods for the 2019 Ridgecrest Earthquake Sequence

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately. To better understand how different factors influence stress-drop measurements, we compare two different methods using the Ridgecrest stress-drop validation data set: spectral decomposition (SD) and spectral ratio (SR), each with different processing options. Here, we also examine the influence of spectral complexity on source parameter measurement. Applying the SD method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, while depth-dependent attenuation is important to correctly map stress-drop variations. For the SR method, we find that the selected source model has limited influence on the measurements; however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction, and spectral complexity strongly influence the result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

58 GEOSCIENCES↗

Associations between Frequency of Culinary Herb Use and Gut Microbiota

While evidence suggests that culinary herbs have the potential to modulate gut microbiota, much of the current research investigating the interactions between diet and the human gut microbiome either largely excludes culinary herbs or does not assess use in standard culinary settings. As such, the primary objective of this study was to evaluate how the frequency of culinary herb use is related to microbiome diversity and the abundance of certain taxa, measured at the phylum level. In this secondary data analysis of the INCLD Health cohort, we examined survey responses assessing frequency of culinary herb use and microbiome analysis of collected stool samples. We did not observe any associations between frequency of culinary herb use and Shannon Index, a measure of alpha diversity. Regarding the abundance of certain taxa, the frequency of use of polyphenol-rich herbs and herbs with certain quantities of antibacterial compounds was positively associated with Firmicutes abundance, and negatively associated with Proteobacteria abundance. Additionally, the total number of herbs used with high frequency, defined as over three times per week, was also positively associated with Firmicutes abundance, independent of adjustments, and negatively associated with Proteobacteria abundance, after adjusting for dietary factors. Frequency of culinary herb use was not associated with Bacteroidota or Actinobacteria abundance.

59 BASIC BIOLOGICAL SCIENCES↗

Synchro-Waveform-Based Event Identification Using Multi-Task Time-Frequency Transform Networks

Influenced by the transient dynamics and reduced inertia characteristics of high-penetration renewable energy systems, power system events frequently exhibit distinct characteristics such as high-frequency components including wide-band oscillations and hyper-harmonics. This makes standard systems face challenges including significant latency and reduced accuracy due to limited data resolution. However, current methods face significant limitations, including insufficient pattern capture ability, low noise immunity, limited feature learning, and restricted localization capabilities, thereby hindering real-time performance. To tackle this issue, this paper proposed a novel synchro-waveform-based event identification approach via a Multi-task Time-frequency Transform Network (MTTNet). Initially, a Time-frequency Transform Block (TTB) is developed to extract both local and global information. The TTB leverages both Fourier and S-transforms to derive comprehensive time-frequency information from synchro-waveforms. Subsequently, a multi-task learning strategy is employed to identify the type and distinguish localization of events. Integrating the TTB and multi-task learning, the MTTNet is designed for synchro-waveform-based event identification, incorporating an adaptive weighting strategy and simplified computation for the S-transform. Two different datasets, comprising simulated and actual synchro-waveforms, are collected from the IEEE 123 bus system and a real-world high-penetration renewable energy system using a universal grid analyzer. Extensive experiments on various conditions are carried out. In conclusion, results demonstrated that the MTTNet consistently surpasses both basic and advanced baselines, with maximum improvements of 13.24% and 9.86%, respectively, while reducing the calculation burden by 15-19 times to achieve real-time event identification.

Event identification↗

Do Remote Camera Arrangements and Image Capture Settings Improve Individual Identification of Golden Eagles?

Individual identification of animals from camera traps has become an important task in wildlife research, but camera deployment methods often do not facilitate this important undertaking. Identification of individual golden eagles (Aquila chrysaetos) is possible using uniquely marked rectrices, but no studies have explored methods to maximize the rate of individual identification from camera images. Furthermore, our objectives were to assess whether different camera heights (1 m vs. 3 m), image capture settings (one image after a 1-min delay vs. burst of 5 images after a 30 sec delay), and arrangements relative to bait (dorsally vs. ventrally aimed) affected views of rectrices on golden eagles and our ability to identify individuals. We conducted our study from 15 December 2016 to 3 March 2017 on the Savannah River Site, South Carolina. First, we developed a scoring system based on views of rectrices and used a linear mixed-effects model to compare image scores among different camera arrangements and image settings. Next, after identifying individual eagles, we used generalized linear mixed-effects models to compare total individual eagle detections, total days an individual was detected, and probability of obtaining an unknown individual identification among camera arrangements and settings. Overall, we scored a total of 27,499 images, with 8,083 providing views of marked rectrices that allowed identification of 18 individual eagles. Average image scores and proportion of images suitable for individual identification were higher from elevated (3 m) camera arrangements than standard arrangements (1 m) across sites. Regardless of camera height, faster frequency of image capture provided more images that could be used to identify individuals and the most trap days per individual. Researchers and managers should consider deploying elevated cameras traps with faster frequency of image capture to improve data quality and potential for analysis of golden eagle populations and trends across the species’ range.

60 APPLIED LIFE SCIENCES↗

Ultralight dark matter detection with mechanical quantum sensors

Abstract We consider the use of quantum-limited mechanical force sensors to detect ultralight (sub-meV) dark matter (DM) candidates which are weakly coupled to the standard model. We show that mechanical sensors with masses around or below the milligram scale, operating around the standard quantum limit, would enable novel searches for DM with natural frequencies around the kHz scale. This would complement existing strategies based on torsion balances, atom interferometers, and atomic clock systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

On the role of mode resonances in regulating zonal-flow-moderated plasma microturbulence

Abstract The onset of turbulent heat transport at a higher temperature gradient than the critical gradient of linear instability, known as the Dimits shift, is a recurring feature of nonlinear simulations for magnetically confined fusion plasmas. Resonance in the nonlinear coupling between the modes that dominate energy transfer can lead to suppression of turbulence and transport above the linear critical gradient. As an expression of this resonance, gyrokinetic simulations show a quasi-coherent interaction between streamers and sidebands coupled through the zonal flow within the Dimits regime. This mechanism is further confirmed by use of artificial complex frequencies which break the resonance. By incorporating corresponding saturation physics, the standard quasilinear model for rapid head flux prediction is improved, which can now predict reduced heat flux in the Dimits regime. In particular, the triplet correlation time, the lifetime of the nonlinear interaction, is shown to be well-approximated by combinations of linear eigenvalues, and yields good representations of the heat flux variation both in and above the Dimits regime. Thus, a reduced but predictive model for transport near the critical gradient of zonal-flow saturated turbulence now exists.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Medium Voltage Three-Stage Power Converter Topology for Distribution Grid Scale Energy Storage Systems

This work proposes a three-stage converter topology with a medium frequency isolation transformer for direct integration of energy storage systems into medium voltage distribution grids. The distributed architecture of the topology, using standard AC/DC converters, has been developed with the aim of plug-and-play capability and voltage and power scalability. The medium frequency transformer facilitates improved power density, while its 20:1 voltage translation capability enables the use of limited voltage level (500 Vdc) of the commercially available batteries. This paper presents the topology structure and details how it can be scaled to reach the full range of the distribution grid voltages and the required power levels. A transformer design for 500 Hz rated frequency is discussed. The control scheme of the converter equipped with voltage support, frequency support, and black start capabilities is also presented. Control hardware-in-the-loop results using OPAL-RT, with converter switching models connected to a weak IEEE-4 node test feeder modified for the aforementioned grid services, are provided to show the topology feasibility.

Chinthavali, Madhu Sudhan↗

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↗