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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

D retention and depth profile behavior for single crystal tungsten with high temperature neutron irradiation

Single crystalline W (tungsten) samples irradiated at 633, 963 and 1073 K by neutrons to a damage level of 0.1 dpa were exposed to a high-flux D (deuterium) plasma at 673, 873 and 973 K, respectively, in TPE (Tritium Plasma Experiment) at INL (Idaho National Laboratory). Deuterium desorption was analyzed by TDS (Thermal Desorption Spectroscopy), and D depth profiles were determined by NRA (Nuclear Reaction Analysis) at SNL (Sandia National Laboratories). HIDT (Hydrogen Isotope Diffusion and Trapping) simulation code was applied to evaluate D behavior for neutron-damaged W at higher temperature. The D retention at depths up to 3 f.tm for the neutron-damaged sample at 673 K was two orders of magnitude larger than that for undamaged tungsten, and its D desorption spectrum had a single broad stage at around 900 K. As the neutron irradiation/plasma exposure temperature increased, D retention was largely reduced, and the desorption temperature was increased to higher temperatures above 1100 K. The D depth profiles by NRA also showed D migration toward bulk by higher temperature irradiation, compared to undamaged W. The HIDT simulation indicated that the major binding energy of D was changed from 1.43 eV to 2.07 eV at higher neutron irradiation and plasma exposure temperatures, suggesting that some vacancies and small vacancy clusters would aggregate to form larger voids, or depopulation of weak traps at high D plasma exposure temperatures. It can be said that more stable trapping sites played dominant roles in the D retention at higher neutron irradiation and plasma exposure temperature. The binding energy by HIDT simulation was almost consistent with the reported value by TMAP, but the consideration of not only total D retention measured by TDS but also D depth profile by NRA led to the more accurate D behavior in neutron-damaged W.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Depth-specific distribution of bacterial MAGs in permafrost active layer in Ny Ålesund, Svalbard (79°N)

Arctic soil microbial communities may shift with increasing temperatures and water availability from climate change. We examined temperature and volumetric liquid water content (VWC) in the upper 80 cm of permafrost-affected soil over 2 years (2018–2019) at the Bayelva monitoring station, Ny Ålesund, Svalbard. We show VWC increases with depth, whereas in situ temperature is more stable vertically, ranging from -5°C to 5°C seasonally. Prokaryotic metagenome-assembled genomes (MAGs) were obtained at 2–4 cm vertical resolution collected while frozen in April 2018 and at 10 cm vertical resolution collected while thawed in September 2019. The most abundant MAGs were Acidobacteriota, Actinomycetota, and Chloroflexota. Actinomycetota and Chloroflexota increase with depth, while Acidobacteriota classes Thermoanaerobaculia Gp7-AA8, Blastocatellia UBA7656, and Vicinamibacteria Vicinamibacterales are found above 6 cm, below 6 cm, and below 20cm, respectively. All MAGs have diverse carbon-degrading genes, and Actinomycetota and Chloroflexota have autotrophic genes. Further, genes encoding β -glucosidase, N-acetyl-β-D-glucosaminidase, and xylosidase increase with depth, indicating a greater potential for organic matter degradation with higher VWC. Acidobacteriota dominate the top 6 cm with their classes segregating by depth, whereas Actinomycetota and Chloroflexota dominate below ~6 cm. This suggests that Acidobacteriota classes adapt to lower VWC at the surface, while Actinomycetota and Chloroflexota persist below 6cm with higher VWC. This indicates that VWC may be as important as temperature in microbial climate change responses in Arctic mineral soils. Here we describe MAG-based Seqcode type species in the Acidobacteriota, Onstottus arcticum, Onstottus frigus, and Gilichinskyi gelida and in the Actinobacteriota, Mayfieldus profundus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Depth-Resolved X-Ray Nanoimaging of Coherent and Incoherent Energy Transport in Silicon Carbide

Understanding lattice dynamics is crucial for optimizing the process of creating functional structures, such as laser writing of color-center defects. However, existing structural probes have difficulty measuring structural dynamics with submicrometer depth sensitivity. Here, in this study, a depth-resolved ultrafast X-ray nanodiffraction technique is developed to track the lattice dynamics of silicon carbide (SiC) in three dimensions. Upon laser excitation of an aluminum layer that acts as a heat and strain transducer, a specular Bragg peak of SiC shows an overall increase in the X-ray diffraction intensity rather than a peak shift. The relaxation dynamics of the increased intensity are significantly different when probed on and off the Bragg peak. The fast subnanosecond relaxation probed at the maximum of the Bragg peak is a result of the propagation of a coherent strain wave along the depth direction, while a slow relaxation probed at the wings of the Bragg peak reflects a localized incoherent lattice heating. To further visualize these processes, spatiotemporal maps were obtained by scanning the relative position and delay between the laser pump and X-ray probe beams, which capture the propagation of the strain wave, as well as a stationary structural distortion close to the aluminum/SiC interface. These depth-resolved structural measurements disentangle energy dissipation mechanisms in laser-excited SiC, and they open opportunities for finer control of, for example, the formation of optically addressable defect complexes central to quantum information applications.

X-ray nanodiffraction↗
DOE OSTI2020

Depth Thermography: Noninvasive 3D Temperature Profiling Using Infrared Thermal Emission

Here, we introduce a technique based on infrared thermal emission, termed depth thermography, that can remotely measure the temperature distribution beneath the surface of certain objects. Depth thermography utilizes the thermal-emission spectrum in the semitransparent spectral region of the target object to extract its temperature as a function of depth, in contrast with conventional thermography, which uses the spectrally integrated thermally emitted power to measure the surface temperature. Coupled with two-dimensional imaging, for example using an infrared hyperspectral camera or scanning a single-pixel spectrometer, this technique can yield volumetric temperature distributions. Furthermore, we carried out a proof-of-concept experiment on an asymmetrically heated fused-silica window, extracting the temperature distribution throughout the sample. Depth thermography may enable noncontact volumetric temperature measurements of microscopic objects such as multilayer electronic devices or macroscopic volumes of liquids and gases, as well as simultaneous all-optical measurements of optical and thermal properties of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Depth dependence of climatic controls on soil microbial community activity and composition

Abstract Subsoil microbiomes play important roles in soil carbon and nutrient cycling, yet our understanding of the controls on subsoil microbial communities is limited. Here, we investigated the direct (mean annual temperature and precipitation) and indirect (soil chemistry) effects of climate on microbiome composition and extracellular enzyme activity throughout the soil profile across two elevation-bioclimatic gradients in central California, USA. We found that microbiome composition changes and activity decreases with depth. Across these sites, the direct influence of climate on microbiome composition and activity was relatively lower at depth. Furthermore, we found that certain microbial taxa change in relative abundance over large temperature and precipitation gradients only in specific soil horizons, highlighting the depth dependence of the climatic controls on microbiome composition. Our finding that the direct impacts of climate are muted at depth suggests that deep soil microbiomes may lag in their acclimation to new temperatures with a changing climate.

16S rRNA↗
DOE OSTI2022

Sensing depths in frequency domain thermoreflectance

In this work, a method is developed to calculate the length into a sample to which a Frequency Domain Thermoreflectance (FDTR) measurement is sensitive. Sensing depth and sensing radius are defined as limiting cases for the spherically spreading FDTR measurement. A finite element model for FDTR measurements is developed in COMSOL multiphysics and used to calculate sensing depth and sensing radius for silicon and silicon dioxide samples for a variety of frequencies and laser spot sizes. The model is compared to experimental FDTR measurements. Design recommendations for sample thickness are made for experiments where semi-infinite sample depth is desirable. For measurements using a metal transducer layer, the recommended sample thickness is three thermal penetration depths, as calculated from the lowest measurement frequency.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Cold and warm atomic gas around the Perseus molecular cloud. II. The impact of high optical depth on the HI column density distribution and its implication for the HI-TO-H{sub 2} transition

We investigate the impact of high optical depth on the HI saturation observed in the Perseus molecular cloud by using Arecibo HI emission and absorption measurements toward 26 radio continuum sources. The spin temperature and optical depth of individual HI components are derived along each line of sight, enabling us to estimate the correction for high optical depth. We examine two different methods for the correction, Gaussian decomposition and isothermal methods, and find that they are consistent (maximum correction factor ∼1.2), likely due to the relatively low optical depth and insignificant contribution from the diffuse radio continuum emission for Perseus. We apply the correction to the optically thin HI column density on a pixel-by-pixel basis and find that the total HI mass increases by ∼10%. Using the corrected HI column density image and far-infrared data from the IRIS Survey, we then derive the H{sub 2} column density on ∼0.4 pc scales. For five dark and star-forming sub-regions, the HI surface density is uniform with Σ{sub HI} ∼ 7–9 M{sub ⊙} pc{sup −2}, in agreement with the minimum HI surface density required for shielding H{sub 2} against photodissociation. As a result, Σ{sub H{sub 2}}/Σ{sub HI} and Σ{sub HI}+Σ{sub H{sub 2}} show a tight relation. Our results are consistent with predictions for H{sub 2} formation in steady state and chemical equilibrium and suggest that H{sub 2} formation is mainly responsible for the Σ{sub HI} saturation in Perseus. We also compare the optically thick HI with the observed “CO-dark” gas and find that the optically thick HI only accounts for ∼20% of the “CO-dark” gas in Perseus.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Root and xylem anatomy varies with root length, root order, soil depth and environment in intermediate wheatgrass (Kernza®) and alfalfa

Abstract Background and Aims Deep roots (i.e. >1 m depth) are important for crops to access water when the topsoil is dry. Root anatomy and hydraulic conductance play important roles in the uptake of soil water, particularly water located deep in the soil. We investigated whether root and xylem anatomy vary as a function of root type, order and length, or with soil depth in roots of two deep-rooted perennial crops: intermediate wheatgrass [Thinopyrum intermedium (Kernza®)] and alfalfa (Medicago sativa). We linked the expression of these anatomical traits to the plants’ capacity to take up water from deep soil layers. Methods Using laser ablation tomography, we compared the roots of the two crops for cortical area, number and size of metaxylem vessels, and their estimated root axial hydraulic conductance (ERAHCe). The deepest roots investigated were located at soil depths of 2.25 and at 3.5 m in the field and in rhizoboxes, respectively. Anatomical differences were characterized along 1-m-long individual roots, among root types and orders, as well as between environmental conditions. Key Results For both crops, a decrease in the number and diameter, or both, of metaxylem vessels along individual root segments and with soil depth in the field resulted in a decrease in ERAHCe. Alfalfa, with a greater number of metaxylem vessels per root throughout the soil profile and, on average, a 4-fold greater ERAHCe, took up more water from the deep soil layers than intermediate wheatgrass. Root anatomical traits were significantly different across root types, classes and growth conditions. Conclusions Root anatomical traits are important tools for the selection of crops with enhanced exploitation of deep soil water. The development and breeding of perennial crops for improved subsoil exploitation will be aided by greater understanding of root phenotypes linked to deep root growth and activity.

Plant Sciences↗
DOE OSTI2024

Constant-Depth Preparation of Matrix Product States with Adaptive Quantum Circuits

Adaptive quantum circuits, which combine local unitary gates, midcircuit measurements, and feedforward operations, have recently emerged as a promising avenue for efficient state preparation, particularly on near-term quantum devices limited to shallow-depth circuits. Matrix product states (MPS) comprise a significant class of many-body entangled states, efficiently describing the ground states of one-dimensional gapped local Hamiltonians and finding applications in a number of recent quantum algorithms. Recently, it has been shown that the Affleck-Kennedy-Lieb-Tasaki state—a paradigmatic example of an MPS—can be exactly prepared with an adaptive quantum circuit of constant depth, an impossible feat with local unitary gates alone due to its nonzero correlation length [Smith , PRX Quantum 4, 020315 (2023)]. In this work, we broaden the scope of this approach and demonstrate that a diverse class of MPS can be exactly prepared using constant-depth adaptive quantum circuits, outperforming theoretically optimal preparation with unitary circuits. We show that this class includes short- and long-ranged entangled MPS, symmetry-protected topological (SPT) and symmetry-broken states, MPS with finite Abelian, non-Abelian, and continuous symmetries, resource states for MBQC, and families of states with tunable correlation length. Moreover, we illustrate the utility of our framework for designing constant-depth sampling protocols, such as for random MPS or for generating MPS in a particular SPT phase. We present sufficient conditions for particular MPS to be preparable in constant time, with global on-site symmetry playing a pivotal role. Altogether, this work demonstrates the immense promise of adaptive quantum circuits for efficiently preparing many-body entangled states and provides explicit algorithms that outperform known protocols to prepare an essential class of states. Published by the American Physical Society 2024

Smith, Kevin C. (ORCID:0000000223971518)↗
DOE OSTI2020

Understanding Measurement Artifacts Causing Inherent Cation Gradients in Depth Profiles of Perovskite Photovoltaics with TOF-SIMS

Time-of-flight secondary-ion mass spectrometry (TOF-SIMS) is one of the few techniques that can obtain chemical information from the hybrid organic-inorganic perovskite solar cells (PSCs) in one dimension (standard depth profiling), two dimensions (high-resolution 100-nm imaging), as well as three dimensions (tomography combining high-resolution imaging with depth profiling). We have very recently developed thermo-mechanical methods to cleave perovskite samples at the back transparent conducting oxide/PSC interface. This allowed for depth-profiling from the back of the device to the front. The resultant profiles answered the lingering question of the apparent A-site cation gradient typically seen in TOF-SIMS depth profiles. In fact, this gradient is a measurement artifact due to beam damage that the community should be informed of as TOF-SIMS data become more commonly employed. Methods of mitigating this artifact by altering the measurement conditions are also presented.

14 SOLAR ENERGY↗
DOE OSTI2023

Protistan community composition and metabolism in the North Pacific Subtropical Gyre: Influences of mesoscale eddies and depth

Abstract Marine protists and their metabolic activities are intricately tied to the cycling of nutrients and the flow of energy through microbial food webs. Physiochemical changes in the environment, such as those that result from mesoscale eddies, may impact protistan communities, but the effects that such changes have on protists are poorly known. A metatranscriptomic study was conducted to investigate how eddies affected protists at adjacent cyclonic and anticyclonic eddy sites in the oligotrophic ocean at four depths from 25 to 250 m. Eddy polarity impacted protists at all depths sampled, although the effects of eddy polarity were secondary to the impact of depth across the depth range. Eddy‐induced vertical shifts in the water column yielded differences in the cyclonic and anticyclonic eddy protistan communities, and these differences were the most pronounced at and just below the deep chlorophyll maximum. An analysis of transcripts associated with protistan nutritional physiology at 150 m revealed that cyclonic eddies may support a more heterotrophic community, while anticyclonic eddies promote a more phototrophic community. The results of this study indicate that eddies alter the metabolism of protists particularly in the lower euphotic zone and may therefore impact carbon export from the euphotic zone.

Microbiology↗
DOE OSTI2022

Laser-induced damage characteristics of fused silica surfaces polished to different depths using fluid jet polishing

Deterministic finishing methods of optical components for high-peak-power laser applications that can meet the requirements for high laser damage resistance are not sufficiently developed to meet all needs. This is especially the case for ultraviolet (UV) laser applications. Fused silica is the material of choice for optics operating at UV wavelengths owing to its intrinsically large bandgap, high transparency, and excellent uniformity. Here we report on the laser damage behavior of fused silica surfaces finished by fluid jet polishing (FJP) as a function of removal depth. Fused silica test substrates were processed by FJP to depths ranging from 0.7 μm to 18 μm. Laser damage testing was conducted on these surfaces at 351 nm and 1-ns pulse lengths for both, 1-on-1 and R-on-1 testing protocols. The results for 1-on-1 testing showed no degradation in the laser-induced damage threshold (LIDT) of the substrates. Instead, a gradual improvement starting at a depth of 2.1 μm was observed and continued to the 18-μm surface. At 18-μm of removal, the LIDT was 16% higher than a surface that was not finished by FJP. For R-on-1 testing, all surfaces treated by FJP demonstrated an improvement in laser damage resistance. At depths greater than 5 μm, the improvements were significantly more pronounced and a 30% increase in the LIDT was realized.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Noise-Resilient and Reduced Depth Approximate Adders for NISQ Quantum Computing

The "Noisy intermediate-scale quantum" NISQ machine era primarily focuses on mitigating noise, controlling errors, and executing high-fidelity operations, hence requiring shallow circuit depth and noise robustness. Approximate computing is a novel computing paradigm that produces imprecise results by relaxing the need for fully precise output for error-tolerant applications including multimedia, data mining, and image processing. We investigate how approximate computing can improve the noise resilience of quantum adder circuits in NISQ quantum computing. We propose five designs of approximate quantum adders to reduce depth while making them noise-resilient, in which three designs are with carryout, while two are without carryout. We have used novel design approaches that include approximating the Sum only from the inputs (pass-through designs) and having zero depth, as they need no quantum gates. The second design style uses a single CNOT gate to approximate the SUM with a constant depth of O(1). We performed our experimentation on IBM Qiskit on noise models including thermal, depolarizing, amplitude damping, phase damping, and bitflip: (i) Compared to exact quantum ripple carry adder without carryout the proposed approximate adders without carryout have improved fidelity ranging from 8.34% to 219.22%, and (ii) Compared to exact quantum ripple carry adder with carryout the proposed approximate adders with carryout have improved fidelity ranging from 8.23% to 371%. Further, the proposed approximate quantum adders are evaluated in terms of various error metrics.

Gaur, Bhaskar↗
DOE OSTI2024

Code Description for "Brief Communication: Monitoring snow depth using small, cheap, and easy-to-deploy ground surface temperature sensors"

Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.

Bachand, Claire↗
DOE OSTI2026

The Role of Subcloud Mesoscale Convergence in Sculpting Convective Updraft Width and Depth

The initiation of deep moist convection is governed in part by the horizontal width of updrafts near cloud base, which limits the deleterious effects of entrainment-driven dilution on buoyant thermals ascending through the free troposphere. However, the factors controlling cloud-base updraft width, which in turn dictates cloud depth, are not well understood. We track the evolving three-dimensional structure of the mesoscale subcloud forcing for vertical motion and near-cloud thermodynamic ingredients within a high-resolution ensemble of simulations of seven realistic daytime orographic convection initiation events to determine their relative roles in controlling cloud width and depth. Statistical analysis of approximately 5000 cloudy updraft samples indicates that the most important contributors to the width of cloudy updrafts across the ensemble are the depth and magnitude of the subcloud mesoscale ascent. However, the depth achieved by clouds is more consistently predicted by the near-cloud ambient relative humidity within the lower to middle free troposphere and convective available potential energy. Therefore, although the width of cloudy updrafts may be partly set at low levels by the mesoscale vertical mass and moisture flux, the likelihood of deep moist convection is governed by the generation of positive buoyancy within cumulus thermals and entrainment-driven dilution that reduces it. The persistence of the low-level mesoscale vertical forcing locally consolidates and vertically transports boundary layer moisture, helping to reduce updraft dilution. However, these factors vary in relative impacts on cloudy updrafts across individual cases, indicating multiple pathways for deep convection initiation.

Convective storms↗
DOE OSTI2022

Predicting variations of the least principal stress with depth: Application to unconventional oil and gas reservoirs using a log-based viscoelastic stress relaxation model

Knowledge of layer-to-layer variations of the least principal stress, S hmin , with depth is essential for optimization of multi-stage hydraulic fracturing in unconventional reservoirs. Utilizing a geomechanical model based on viscoelastic stress relaxation in relatively clay rich rocks, we present a new method for predicting continuous S hmin variations with depth. The method utilizes geophysical log data and S hmin measurements from routine diagnostic fracture injection tests (DFITs) at several depths for calibration. We consider a case study in the Wolfcamp formation in the Midland Basin, where both geophysical logs and values of S hmin from DFITs are available. We compute a continuous stress profile as a function of the well logs that fits all of the DFITs well. We utilized several machine learning technologies, such as bootstrap aggregation (or bagging), to improve the generalization of the model and demonstrate that the excellent fit between predicted and observed stress values is not the result of over-fitting the calibration points. The model is then validated by accurately predicting hold-out stress measurements from four wells within the study area and, without recalibration, accurately predicting stress as a function of depth in an offset pad about 6 miles away.

58 GEOSCIENCES↗
DOE OSTI2024

Active Layer Depth and Permafrost Temperatures at the Teller 47 Field Site, Seward Peninsula, Alaska, 2022

With extreme climate warming in the Arctic, there is increasing focus on mapping permafrost stability and improving understanding of the impacts of thawing permafrost. Summer active layer depths and temperatures at the top of the permafrost were collected at the Teller 47 field site on the Seward Peninsula, Alaska to better understand permafrost thermal state in areas of discontinuous permafrost. Measurements were taken between August 14th and August 20th, 2022. Active layer depths were measured with a 120 cm thaw probe, and temperature measurements were taken with a SpotOn Temperature probe at the top of permafrost and at a maximum depth of XYZ, when no near-surface permafrost (within 120 cm of the surface) was present. Measurements were co-located with ground surface displacement measurements, which can be found in the associated dataset, NGA254. Precise location data were collected at each observation point using a GNSS RTK GPS unit. This dataset contains a *.csv file of permafrost temperature and active layer depths and a *.kml file of measurement locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Soil properties and root characteristics across four lowland Panamanian forests from 0 - 1 m soil depths

Objectives:Fine roots significantly influence ecosystem-scale cycling of nutrients, carbon (C), and water, yet there is limited understanding of how fine root traits vary across and within tropical forests, some of Earth's most C-rich ecosystems. The biomass of fine roots can impact soil carbon storage, as root mortality is a primary source of new carbon to soils. A positive relationship has been observed between fine root biomass and soil carbon stocks in Panama (Cusack et al 2018). Beyond biomass, root characteristics like specific root length (SRL) could also influence soil carbon, as roots with higher SRL are less dense and thinner, potentially decomposing more easily or promoting soil aggregation. Understanding the effects of root morphology and tissue quality on soil carbon storage and with soil properties in general can improve predictions of landscape-scale carbon patterns. We aggregated new data of root biomass, morphology and nutrient content at 0-10 cm, 10-20 cm, 20-50 cm and 50-100 cm depth increments across four distinct lowland Panamanian forests and paired with already published datasets (Cusack et al 2018; Cusack and Turner 2020) of soil chemistry from the same sites and soil depths to explore relationship between soil carbon stocks and root characteristics.Datasets included:The datasets provided include .csv and .xlsx files for fine root characteristics and soil chemistry from four different forests across 0-10 cm, 10-20 cm, 20-50 cm, and 50-100 cm depth increments. Root characteristics include live fine root biomass, dead fine root biomass, coarse root biomass, specific root length, root diameter, root tissue density, specific root area, root %N, root %C, and root C/N ratio. Soil chemistry data includes total carbon (TC), dissolved organic carbon (DOC), bulk density, total phosphorus (TP), available phosphorus (AEM Pi), and various Mehlich-extractable elements such as aluminum, calcium, iron, potassium, manganese, phosphorus, and zinc. Nitrogen content measures include ammonium, nitrate, total dissolved nitrogen (TDN), dissolved inorganic nitrogen (DIN), and dissolved organic nitrogen (DON). The dataset also includes total exchangeable bases (TEB) and effective cation exchange capacity (ECEC) in both centimoles of charge per kilogram and micromoles of charge per gram. The soil chemistry data was obtained from Cusack et al (2018) and Cusack and Turner (2020) and paired with root characteristics data for the same depth increments and sites. Additionally, a .kml file is provided with coordinates for all 32 plots included in the study across four forests (n = 8 plots per site). Root data was averaged across these 8 plots per site and soil data was collected in one pit in each site. This dataset serves as baseline data before a throughfall exclusion experiment, Panama Rainforest Changes with Experimental Drying (PARCHED), was implemented. No special software is needed to open these files.

54 ENVIRONMENTAL SCIENCES↗