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DOE OSTI2023

Progress and outlook of Sn–Pb mixed perovskite solar cells

Abstract Organic–inorganic hybrid perovskites have revolutionized solar cell research owing to their excellent material properties. Most previous research has been done on Pb-based perovskites. Recently, efforts to discover a Pb-free or Pb-less perovskite material with an ideal bandgap ranging 1.1–1.3 eV have led researchers to investigate Sn–Pb mixed perovskites. Sn–Pb mixed perovskites have a bandgap of ~ 1.25 eV, which is suitable for high-efficiency single-junction and perovskite/perovskite tandem solar cells. Moreover, the Pb content of Sn–Pb mixed perovskites is 50–60% lower than that of Pb-based perovskites, partially mitigating the Pb toxicity issue. However, incorporating Sn 2+ into the crystal structure also causes various drawbacks, such as inhomogeneous thin film morphologies, easy oxidation of Sn 2+ , and more vulnerable surface properties. Researchers have made substantial progress in addressing these challenges through improvements in compositional design, structural optimization, precursor design, and surface treatments. In this review, we provide a comprehensive overview of the progress in Sn–Pb mixed perovskite solar cells. Furthermore, we analyze the key variables and trends as well as provide an outlook for future directions in the research on Sn–Pb mixed perovskites. Graphical Abstract

14 SOLAR ENERGY↗

DOE OSTI2024

Spectroelectrochemical insights into the intrinsic nature of lead halide perovskites

Abstract Lead halide perovskites have emerged as a new class of semiconductor materials with exceptional optoelectronic properties, sparking significant research interest in photovoltaics and light-emitting diodes. However, achieving long-term operational stability remains a critical hurdle. The soft, ionic nature of the halide perovskite lattice renders them vulnerable to various instabilities. These instabilities can be triggered by factors such as photoexcitation, electrical bias, and the surrounding electrolyte/solvent or atmosphere under operating conditions. Spectroelectrochemistry offers a powerful approach to bridge the gap between electrochemistry and photochemistry (or spectroscopy), by providing a comprehensive understanding of the band structure and excited-state dynamics of halide perovskites. This review summarizes recent advances that highlight the fundamental principles, the electronic band structure of halide perovskite materials, and the photoelectrochemical phenomena observed upon photo- and electro-chemical charge injections. Further, we discuss halide instability, encompassing halide oxidation, vacancy formation, ion migration, degradation, and sequential expulsion under electrical bias. Spectroelectrochemical studies that provide a deeper understanding of interfacial processes and halide mobility can pave the way for the design of more robust perovskites, accelerating future research and development efforts. Graphical Abstract

Min, Seonhong↗

DOE OSTI2020

Large-scale inflatable structures for tunnel protection: a review of the Resilient Tunnel Plug project

The protection of underground civil infrastructure continues to be a high priority for transportation and transit security agencies. In particular, rail transit tunnels running under bodies of water are susceptible to disruptions due to flooding caused by extraordinary climatic events such as hurricanes or other events resulting from human activities. Several events have taken place in the past decades that have demonstrated the need to mitigate vulnerabilities or, at least, minimize the consequences of catastrophic events. Although it is impossible to prevent all situations that can lead to flooding, damage can be substantially decreased by reducing the area affected by the event. To minimize the effects of an event, a possible approach is to compartmentalize the tunnel system by creating temporary barriers that can contain the propagation of flooding until a more permanent solution can be implemented. One way to create a temporary barrier is by the deployment of a large-scale inflatable structure, also known as an inflatable plug. In such an application, the inflatable structure is prepared for placement, either permanently or temporally, and maintained ready for deployment, inflation, and pressurization when needed. The internal plug pressure imparts a normal force against the tunnel wall surface with the friction between the plug and tunnel surfaces opposing axial movement of the plug. The sealing effectiveness depends on the ability of the inflatable structure to self-deploy and fit, without human intervention, to the intricacies of the perimeter of the conduit being sealed. Primary design constraints include having the plug stowed away from the dynamic envelope of the trains and being able to withhold the pressure of the flooding water. This work presents a compilation of the main aspects of the activities completed for the development of large-scale inflatable structures as part of the Resilient Tunnel Plug (RTP) Project. The main test results and lessons learned are presented to demonstrate the viability of implementing large-scale inflatable plugs for the containment of flooding in rail tunnels systems. Over 400 coupon and specimen tests, 200 reduced scale tests, and 100 full-scale tests were conducted to demonstrate the efficacy of the design of different prototypes over a 10-year research and development project. The culmination of the work was 12 large-scale flooding demonstrations where the inflatable tunnel plug was shown able to be deployed remotely and withstand a simulated flooding event.

42 ENGINEERING↗

DOE OSTI2026

Dynamic Transmission Line Switching Amid Wildfire-Prone Weather Under Decision-Dependent Uncertainty

During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Estrada-Garcia, Juan-Alberto↗

DOE OSTI2021

REGULATORY REQUIREMENTS, GUIDANCE, AND REVIEW OF EMBEDDED DIGITAL DEVICES IN SAFETY SYSTEMS

Interest in embedded digital devices (EDDs) for monitoring and providing control of components is increasing in the nuclear power market as more and more users both within and outside the nuclear sector are employing EDDs. EDDs in other industries or countries may be known by the related terms as smart devices, devices of limited functionality, or intelligent devices. EDDs can sometimes perform a safety role when embedded in components such as temperature transmitters, pressure transmitters, voltage regulators, gas analyzers, boiler controllers, relays, and radiation monitors. The introduction of EDDs can affect safety by creating new hazards, vulnerabilities, failure modes, triggering mechanisms, and other potential safety concerns at both the component and system levels. The U.S. Nuclear Regulatory Commission’s (NRC’s) existing regulations and guidance cover the use of EDDs in safety-related and important to safety systems in nuclear power plants (NPPs). In addition to potential future challenges, the nature of EDDs being implemented in similar or identical manners between different plants and industries opens up the potential of leveraging the reviews of other regulators or utilization of industry certifications.Key words: embedded digital device, firmware

Halverson, D. S.↗

DOE OSTI2020

Cusp-artifacts in high order superresolution optical fluctuation imaging

Superresolution optical fluctuation imaging (SOFI) is a simple and affordable super-resolution imaging technique, and attracted a growing community over the past decade. However, the theoretical resolution enhancement of high order SOFI is still not fulfilled. In this study, we identify “cusp artifacts” in high order SOFI images, and show that the high-order cumulants, odd-order moments and balanced-cumulants (bSOFI) are highly vulnerable to cusp artifacts. Our study provides guidelines for developing and screening for fluorescence probes, and improving data acquisition for SOFI. The new insight is important to inspire positive utilization of the cusp artifacts.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Three-dimensional modeling of electric-field enhancement in multilayer dielectric gratings arising from inadvertent flaws

Pulse-compression gratings for high-power, short-pulse laser systems are exposed to high electric fields that are further enhanced locally due to their 2D nanostructured surface. This makes them vulnerable to laser-induced damage. The present work considers the effect on electric-field modulation caused by an array of commonly found inadvertent flaws in gratings including fabrication defects, contamination particles, and laser-induced–damage initiation. These defects affect the laser-damage performance characteristics of the grating. To understand the local field-enhancement distribution due these imperfections, 3D modeling of the electric-field distribution is performed with a sufficiently high resolution of 1/74 of the laser wavelength ( λ ) while considering a volume of ≈489 λ 3 . The results provide estimates for the ensuing electric-field intensification and projected reduction of the laser-damage thresholds, as well as the anticipated pattern of damage growth initiation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

A guide to the BRAIN Initiative Cell Census Network data ecosystem

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

A deep learning approach to real-time HIV outbreak detection using genetic data

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Modeling protected species distributions and habitats to inform siting and management of pioneering ocean industries: A case study for Gulf of Mexico aquaculture

Marine Spatial Planning (MSP) provides a process that uses spatial data and models to evaluate environmental, social, economic, cultural, and management trade-offs when siting (i.e., strategically locating) ocean industries. Aquaculture is the fastest-growing food sector in the world. The United States (U.S.) has substantial opportunity for offshore aquaculture development given the size of its exclusive economic zone, habitat diversity, and variety of candidate species for cultivation. However, promising aquaculture areas overlap many protected species habitats. Aquaculture siting surveys, construction, operations, and decommissioning can alter protected species habitat and behavior. Additionally, aquaculture-associated vessel activity, underwater noise, and physical interactions between protected species and farms can increase the risk of injury and mortality. In 2020, the U.S. Gulf of Mexico was identified as one of the first regions to be evaluated for offshore aquaculture opportunities as directed by a Presidential Executive Order. We developed a transparent and repeatable method to identify aquaculture opportunity areas (AOAs) with the least conflict with protected species. First, we developed a generalized scoring approach for protected species that captures their vulnerability to adverse effects from anthropogenic activities using conservation status and demographic information. Next, we applied this approach to data layers for eight species listed under the Endangered Species Act, including five species of sea turtles, Rice’s whale, smalltooth sawfish, and giant manta ray. Next, we evaluated four methods for mathematically combining scores (i.e., Arithmetic mean, Geometric mean, Product, Lowest Scoring layer) to generate a combined protected species data layer. The Product approach provided the most logical ordering of, and the greatest contrast in, site suitability scores. Finally, we integrated the combined protected species data layer into a multi-criteria decision-making modeling framework for MSP. This process identified AOAs with reduced potential for protected species conflict. These modeling methods are transferable to other regions, to other sensitive or protected species, and for spatial planning for other ocean-uses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Engineering well-expressed, V2-immunofocusing HIV-1 envelope glycoprotein membrane trimers for use in heterologous prime-boost vaccine regimens

HIV-1 vaccine immunofocusing strategies may be able to induce broadly-reactive neutralizing antibodies (NAbs). Here, we engineered a panel of diverse, membrane-resident native HIV-1 trimers vulnerable to two broad targets—the V2 apex and fusion peptide (FP). Selection criteria included i) high expression and ii) infectious function, so that trimer neutralization sensitivity can be profiled in pseudovirus (PV) assays. Initially, we boosted the expression of 17 candidate trimers by truncating gp41 and introducing a gp120-gp41 SOS disulfide to prevent gp120 shedding. "Repairs" were made to fill glycan holes and eliminate other strain-specific aberrations. A new neutralization assay allowed PV infection when our standard assay was insufficient. Trimers with exposed V3 loops, a target of non-NAbs, were discarded. To try to increase V2-sensitivity, we removed clashing glycans and modified the C-strand. Notably, a D167N mutation improved V2-sensitivity in several cases. Glycopeptide analysis of JR-FL trimers revealed near complete sequon occupation and that filling the N197 glycan hole was well-tolerated. In contrast, sequon optimization and inserting/removing glycans at other positions frequently had global "ripple" effects on glycan maturation and sequon occupation throughout the gp120 outer domain and gp41. V2 MAb CH01 selectively bound to trimers with small high mannose glycans near the base of the V1 loop, thereby avoiding clashes. Knocking in a rare N49 glycan was found to perturb gp41 glycans, increasing FP NAb sensitivity—and sometimes improving expression. Finally, a biophysical analysis of VLPs revealed that i) ~25% of particles bear Env spikes, ii) spontaneous particle budding is high and only increases 4-fold upon Gag transfection, and iii) Env+ particles express ~30–40 spikes. Taken together, we identified 7 diverse trimers with a range of sensitivities to two targets to allow rigorous testing of immunofocusing vaccine concepts.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Quantum-enhanced detection of viral cDNA via luminescence resonance energy transfer using upconversion and gold nanoparticles

Abstract The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a sensitive and highly specific detection method for cDNA, leveraging Luminescence Resonance Energy Transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs), and achieves a detection limit of 242 fM for SARS-CoV-2 cDNA. This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5′ and 3′ ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched cDNA sequences and significantly improving detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4 % to 73.6 %, with an optimal midpoint of 42 %, thereby demonstrating the superior sensitivity of our method. Our work uses SARS-CoV-2 cDNA as a model system to demonstrate the potential of our LRET-based detection method. This proof-of-concept study highlights the adaptability of our platform for future diagnostic applications. Instrumental validation confirms the synthesis and formation of AuNPs, addressing the need for experimental verification of the preparation of nanomaterial. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach provides a low detection limit and high specificity for target cDNA sequences, underscoring its potential for targeted COVID-19 diagnostics. This study demonstrates the superior sensitivity and adaptability of using UCNPs and AuNPs for cDNA detection, offering significant advances in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in developing next-generation biosensors for managing current and future viral outbreaks. By adjusting primer sequences, this platform can be tailored to detect other pathogens, contributing to the enhancement of global healthcare responsiveness and infectious disease control.

Esmaeili, Shahriar [Institute for Quantum Science ↗

DOE OSTI2020

Regional Tau Effects on Prospective Cognitive Change in Cognitively Normal Older Adults

Studies suggest that tau deposition starts in the anterolateral entorhinal cortex (EC) with normal aging, and that the presence of β-amyloid (Aβ) facilitates its spread to neocortex, which may reflect the beginning of Alzheimer's disease (AD). Functional connectivity between the anterolateral EC and the anterior-temporal (AT) memory network appears to drive higher tau deposition in AT than in the posterior-medial (PM) memory network. Here, we investigated whether this differential vulnerability to tau deposition may predict different cognitive consequences of EC, AT, and PM tau. Using 18 F-flortaucipir (FTP) and 11 C-Pittsburgh compound-B (PiB) positron emission tomography (PET) imaging, we measured tau and Aβ in 124 cognitively normal human older adults (74 females, 50 males) followed for an average of 2.8 years for prospective cognition. We found that higher FTP in all three regions was individually related to faster memory decline, and that the effects of AT and PM FTP, but not EC, were driven by Aβ+ individuals. Moreover, when we included all three FTP measures competitively in the same model, only AT FTP significantly predicted memory decline. Our data support a model whereby tau, facilitated by Aβ, transits from EC to cortical regions that are most closely associated with the anterolateral EC, which specifically affects memory in the initial stage of AD. Memory also appears to be affected by EC tau in the absence of Aβ, which may be less clinically consequential. These findings may provide clarification of differences between normal aging and AD, and elucidate the transition between the two stages. SIGNIFICANCE STATEMENT Tau and β-amyloid (Aβ) are hallmarks of Alzheimer's disease (AD) but are also found in cognitively normal people. It is unclear whether, and how, this early deposition of tau and Aβ may affect cognition in normal aging and the asymptomatic stage of AD. We show that tau deposition in the entorhinal cortex (EC), which is common in advanced age, predicts memory decline in older adults independent of Aβ, likely reflecting normal, age-related memory loss. In contrast, tau in anterior-temporal (AT) regions is most predictive of memory decline in Aβ+ individuals. These data support the idea that tau preferentially spreads to specific cortical regions, likely through functional connections, which plays a primary role in memory decline in the early stage of AD.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

The impact of freeze-thaw history on soil carbon response to experimental freeze-thaw cycles

This dataset contains data used for the paper "The impact of freeze-thaw history on soil carbon response to experimental freeze-thaw cycles". The Related References field will be updated with a full citation when available.Freeze-thaw is a disturbance process in cold regions where permafrost soils are becoming vulnerable to temperature fluctuations above 0˚C. Freeze-thaw alters soil physical and biogeochemical properties with implications for carbon persistence and emissions in Arctic landscapes. We examined whether different freeze-thaw histories in two soil systems led to contrasting biogeochemical responses under a laboratory-controlled freeze-thaw incubation. We investigated controls on soil organic matter (SOM) composition through Fourier-transform ion cyclotron resonance mass spectroscopy (FT-ICR-MS) to identify nominal carbon oxidation states and relative abundances of aliphatic-type carbon molecules in both surface and subsurface soils. Soil cores (~ 60 cm-depth) were sampled from two sites in Alaskan permafrost landscapes with different in situ freeze-thaw characteristics: Healy (>40 freeze-thaw cycles annually) and Toolik (<150 freeze-thaw cycles annually). FT-ICR-MS was coupled with in situ temperature data and soil properties (i.e., soil texture, mineralogy) to assess (1) differences in SOM composition associated with previous freeze-thaw history and (2) sensitivity to experimental freeze-thaw in the extracted cores. Control (freeze-only) samples showed greater carbon oxidation in Healy soils compared with Toolik, even in lower mineral horizons where freeze-thaw history was comparable across both sites. Healy showed the most loss of carbon compounds following experimental freeze-thaw in the lower mineral depths, including a decrease in aliphatics. Toolik soils responded more slowly to freeze-thaw as shown by intermediary carbon oxidation distributed across multiple carbon compound classes. Variations in the response of permafrost carbon chemistry to freeze-thaw is an important factor for predicting changes in soil function as permafrost thaws in high northern latitudes.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/Erin-Rooney/FTC-FTICR (DOI 10.5281/zenodo.6533064).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Soil C stock and CO2 production data for Soong et al. 2021: Effects of five years of soil warming at Blodgett Forest, CA.

Subsoils below 20 cm are an important reservoir in the global carbon cycle, but little is known about their vulnerability under climate change. We measured subsoil carbon in warmed vs control plots of a conifer forest after 4.5 years of whole-soil warming (4°C). We also measured soil CO2 efflux at the surface and soil CO2 concentrations along the soil profile. Over the 4.5 years we observed that warming resulted in a loss of subsoil carbon stocks (−33 ± 11%), primarily from unprotected particulate organic matter. Warming also stimulated a sustained 30 ± 4% increase in soil CO2 efflux due to increased CO2 production through the whole-soil profile. The observed in situ decline in subsoil carbon stocks with warming is now definitive evidence of a positive soil carbon-climate feedback, which could not be concluded based on increases in CO2 effluxes alone. This dataset comprises (1) 13C and C recovery in 2014, 2016, and 2018 1m soil cores sampled in 10cm increments. (2) Monthly surface CO2 fluxes from 2014 to 2018. (3) Monthly gas well sample [CO2] and production data. And (4) density fraction data for three depths of cores recovered in 2017.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Plot and Tree Characteristics from the 2022-2023 field experiment at Game Ridge, Missoula County, Montana, USA

This dataset contains plot and study tree characteristics including identifiers, latitude and longitude data, tree heights, tree diameters, and distance between trees within a study plot. Data files and data dictionary(ies) are uploaded as .csv files and .xlsx files. The Users Guide is a .pdf file. Location data can be found in the Google Earth file GameRidge_SitePlotCoordinates.kmz.kml included here. These datasets were collected for Plant Carbohydrate Depletion, Mycorrhizal Networks, and Vulnerability to Drought: An Experimental Test in the Field. This experiment examined the interdependency between plant hydraulics and carbohydrate availability and sought to develop ways to incorporate interactions with below ground symbiotic organisms to better model and quantify forest response to drought. This environmental data was collected to provide context for the fungal community data and Pinus ponderosa physiological data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Pinus ponderosa physiology data from the 2022 shade manipulation field experiment at Game Ridge, Missoula County, Montana, USA

This dataset contains physiology data on Pinus ponderosa saplings, including: leaf water potential (MPa, megapascals), leaf osmotic potential (MPa, megapascals), leaf pressure potential (MPa, megapascals), leaf relative water content (% saturated mass), as well as soluble sugars (% dry mass),starch (% dry mass), and total nonstructural carbohydrates (% dry mass) found in branch phloem and xylem. Data files and data dictionary(ies) are uploaded as .csv files and .xlsx files. The Users Guide is a .pdf file. Location data can be found in the Google Earth file GameRidge_SitePlotCoordinates.kmz.kml included here. These datasets were collected for Plant Carbohydrate Depletion, Mycorrhizal Networks, and Vulnerability to Drought: An Experimental Test in the Field. This experiment examined the interdependency between plant hydraulics and carbohydrate availability and sought to develop ways to incorporate interactions with below ground symbiotic organisms to better model and quantify forest response to drought.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Pinus ponderosa physiology data from the 2023 girdling manipulation field experiment at Game Ridge, Missoula County, Montana, USA

54 ENVIRONMENTAL SCIENCES↗