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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Aspects of rare earth element enrichment in Allegheny Plateau coals, Pennsylvania, USA

The Allegheny Plateau in western Pennsylvania, western Maryland, and northern West Virginia has relatively flat-lying strata with southwest-northeast-trending anticlines cored by splay faults originating from the thrust faults and southeast-northwest-trending lineaments. The lineaments define both the structural relief of the anticlines and the coal rank. Coal rank in the Pennsylvanian Allegheny Group coals is medium volatile bituminous in the region of less-prominent structural relief and low volatile bituminous in the region with more pronounced anticlines. Zinc and Cl exhibit high values in coals in the vicinity of the lineaments. Although coal rank was not a parameter in the Principal components analysis, the highest rank coals clustered together in a quadrant defined, in part, by the Zn concentration. Zinc was selected as a parameter due to its possible link with hydrothermal mineralization and Zr and TiO 2 /Al 2 O 3 were selected based on their presumed association with detrital mineral influences. The highest rare earths + Y values in benches of the Lower Kittanning coal were found at sites close to the lineaments. Negative or negligible Ce anomalies (δCe) and strongly positive Gd anomalies (δGd) suggest marine or hydrothermal influences and negative Eu anomalies (δEu) along with high TiO 2 /Al 2 O 3 values suggest a terrestrial input. In conclusion, the plots of δCe vs. δGd and δCe vs. δEu show that the low volatile bituminous coals are segregated from the other coals, suggesting that the factors that influenced coal rank also influenced the distribution of the rare earth elements.

58 GEOSCIENCES↗
DOE OSTI2021

Comparative geochemistry of flowback chemistry from the Utica/Point Pleasant and Marcellus formations

Flowback/Produced fluid samples were collected from several wells from two Utica/Point Pleasant (UPP) sites (UPPW and UPPS) in Ohio, and one Marcellus (Marcellus Shale Energy and Environment Laboratory (MSEEL)) site in West Virginia over a period of approximately two years. Although these formations have different ages, depositional environments, diagenetic histories, and geochemical and mineralogical compositions (i.e. the UPP is significantly more carbonate rich than the Marcellus which is more siliceous), analysis of trends in fluid species over time shows that, overall, the TDS and major solubilized elements (Na, Ca, Cl) in the UPP and Marcellus brines are remarkably similar. Total dissolved solutes (TDS) in these brines ranged from approximately 40 to 250 g/L salt, and in general, concentrations increased with time elapsed since natural gas well completion and stimulation. The behavior of Na, Br, and Cl suggests that the produced water signatures from these formations are largely derived from the native formational brines which display evidence of originating from evaporated seawater. There is a strong correlation between Cl and Br, indicating that both species behave conservatively, and the similarity among each of these brines suggests no appreciable contribution of salt from halite dissolution because Br is excluded from the halite structure. Cl/Br ratios in the brines range from ~80 to 120 (mg/L/mg/L). Other elements, such as K, which readily reacts between fluids and ion exchange sites on clays, generally exhibit conservative behavior for an individual site, but show significant variations among each of the different well pads. The concentrations of Sr and Ba vary dramatically among well sites, and increase with respect to Cl- over time, suggesting increasing solubilization, presumably from desorption from clay minerals or dissolution of carbonates or sulfates from the source formation(s). The UPPW well site has very low Ba due to high-sulfate input fluid, which resulted in precipitation of barite/celestite in the brines. In contrast the UPPS well site had elevated Sr (~ 3500 mg/L), presumably due to the use of Sr-rich recycled brine used in hydraulic fracturing. The Marcellus site had the highest Ba concentrations (up to 10 g/L) and highest Ba/Sr ratios in the fluids, due to the high concentration of barium in the Marcellus target (~ 1000 ppm, as compared to ~200 ppm in the UPP). These observations suggest that solutes in the FP fluids are derived from native brines, water-rock interactions that have occurred over geologic time scales, as well as some contribution from contemporaneous reactions in the subsurface. The results also show that the composition of the injected fluid can influence flowback fluid chemistry and possibly production efficiency.

58 GEOSCIENCES↗
DOE OSTI2022

Effect of secondary gas-phase reactions (SGR) in pyrolysis of carbon feedstocks for anisotropic carbon materials production – 2: Effects of SGR on tars produced from varying ranks of coal

Herein, this work explores the extent to which secondary gas-phase reactions (SGR) in pyrolysis can be used to modify coal tar chemistries from coals of different ranks in favor of improved anisotropy formation in their respective pitches. Pyrolysis was performed on four different coals of varying bituminous rank (Utah Sufco, Wyoming PRB Black Thunder, Illinois #6, and West Virginia Flying Eagle), with SGR temperatures ranging from 800 to 900° C and nominal SGR gas-phase residence times from 1 to 2.5 s. The oxygen content, aliphatic content, and molecular weight distributions of the coal tar samples were measured to indicate the changes with increasing levels of SGR, and microscopy was also used to measure changes in anisotropy formation in the resulting pitch samples. Generally, for all coals tested, increased levels of pyrolysis SGR led to decreased oxygen and aliphatic content, increased molecular weight sizes, and improved anisotropy formation. However, it was clear that the extent of these property changes depended on the chemistry and rank of the starting coal feedstock. Despite the relatively high rank of the Illinois #6 coal, its respective pitch samples performed poorly in improving anisotropy formation, due to its high sulfur content. The PRB, Sufco, and Flying Eagle coals performed better in their anisotropy formation than Illinois #6, depending on their respective coal ranks. Statistical analysis (analysis of variance, ANOVA) performed on the sample characterization data also suggests that SGR temperature is consistently the most dominant and significant effect on the resulting coal products.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Assessing high fidelity multi-component models to facilitate safeguards at Gas Centrifuge Enrichment Plants

We report that the International Atomic Energy Agency (IAEA) inspectors routinely carry out environmental sampling (ES) as a verification method. Collection of environmental swipe samples at various locations in Gas Centrifuge Enrichment Facilities (GCEPs) is an important process in detecting misuse of a declared facility and possibly the existence of undeclared nuclear material. These samples are measured for isotopic composition in uranium containing particles by Thermal Ionization Mass Spectrometry (TIMS) or Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Even though ES is highly effective in detecting the absolute value of enrichments and their deviations from the declared values, it cannot explain the cause of those changes. Several potential explanations can serve as possibilities for particles detected above or other than the declared enrichment. These include normal and non-malicious events such as the design of the enrichment cascades, unintentional failures of the machines, or overshoot during startup of a cascade. It can also be the result of deliberate misuse by the facility operators. The primary objective of this work is to understand how these factors affect the enrichments produced by a cascade and quantify anticipated multi-isotopic concentrations for each case. The following methodology is employed to determine signatures at a particular facility. 1) Utilize a new two-dimensional multi-component diffusion code to obtain centrifuge performance data and use that information to design and perform cascade analysis. Compare and contrast the results with previous 1-D radially averaged solutions from the Pancake code. 2) Design a GCEP cascade with the production goal of 19.75% 235 U for each set of machine data above. Investigate two cascade scenarios that include enrichment of natural uranium (NU) feed to 19.75% 235U in a single cascade compared to a two-step process of NU to 5% and then 5% to 19.75%. 3) Simulate the intentional vs. unintentional off-normal scenarios in the cascades to assess the differences in isotopic concentrations. A non-ideal squared-off cascade model developed at the University of Virginia is used to calculate flow rates and isotopic concentrations of the process gas. The analysis is performed using the Rome machine model operated at 600 m/s rotor speed. The upper and lower bounds of normal and abnormal enrichments in a typical facility are used in conjunction with ES results to understand the root causes of such observations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Overview of the physics basis for the ARC fusion power plant

Commonwealth Fusion Systems plans to build ARC as the first fusion power plant at a site in Chesterfield County, Virginia, USA by the early 2030s. We present an overview of analysis comprising the physics basis of the ARC V3A design, a high-magnetic-field tokamak with 𝐵 0 =11.4 T, 𝐼 𝑝 =12.0 MA, 𝑅 0 =4.62 m, 𝑎 =1.18 m. ARC V3A is designed to produce 𝑃 𝑓⁡𝑢⁢𝑠 ≈1.13 GW DT fusion power and deliver ⩾400 MW net electric power to the grid. This overview includes quantitative analysis of fundamental issues for design of and operational plasma scenarios for a tokamak power plant, and lays out the design targets and strategic choices for ARC, including empirical fusion performance projections, assessment of H-mode access, ion cyclotron resonance heating simulations, alpha particle physics and time-dependent full-pulse simulations. This is complemented by topical papers on fusion performance and transport, disruption physics, boundary physics and magnetohydrodynamic stability. Critically, these studies identify key model uncertainties and physics risks to be retired through SPARC operation. Due to the modular nature of ARC, early results from SPARC can be incorporated into the design of the first ARC as well as subsequent replacements of the ARC vacuum vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Can Common Pool Resource Theory Catalyze Stakeholder-Driven Solutions to the Freshwater Salinization Syndrome?

Freshwater salinity is rising across many regions of the United States as well as globally, a phenomenon called the freshwater salinization syndrome (FSS). The FSS mobilizes organic carbon, nutrients, heavy metals, and other contaminants sequestered in soils and freshwater sediments, alters the structures and functions of soils, streams, and riparian ecosystems, threatens drinking water supplies, and undermines progress toward many of the United Nations Sustainable Development Goals. There is an urgent need to leverage the current understanding of salinization’s causes and consequences–in partnership with engineers, social scientists, policymakers, and other stakeholders–into locally tailored approaches for balancing our nation’s salt budget. In this feature, we propose that the FSS can be understood as a common pool resource problem and explore Nobel Laureate Elinor Ostrom’s social-ecological systems framework as an approach for identifying the conditions under which local actors may work collectively to manage the FSS in the absence of top-down regulatory controls. We adopt as a case study rising sodium concentrations in the Occoquan Reservoir, a critical water supply for up to one million residents in Northern Virginia (USA), to illustrate emerging impacts, underlying causes, possible solutions, and critical research needs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Carbamoylation as an Effective Tool in the Analysis of the Soman Nerve Agent Marker Pinacolyl Alcohol in Soil Matrices by EI-GC-MS and LC-HRMS

Pinacolyl alcohol (PA) is a Schedule 2 chemical commonly featured in most proficiency tests (PTs) administered by the Organisation for the Prohibition of Chemical Weapons (OPCW) due to its direct as well as forensic link to the nerve agent Soman. Therefore, its detection by Chemical Weapons Convention (CWC) inspection teams during on-site investigations is a strong indicator of the past or latent presence of Soman in the environment. Its small molecular weight (102), early elution time, and poor ionization profile make PA a challenging analyte to detect particularly at low concentrations (∼1–10 μg/g). In this work, 1,1′-carbonyldimidazole (CDI) has been used to effectively modify PA for the first time in two different soil matrices (Virginia type A soil and silt sediment) at two separate concentrations (1 and 10 μg/g) for its subsequent detection by EI-GC-MS and LC-HRMS methods. For the EI-GC-MS analysis, the PA carbamate derivative (PIC) exhibits improved chromatography relative to PA such as improved peak shape, increased molecular weight (196 for PIC and 102 for PA) and increased retention time (16.9 min for PIC and ∼4.1 min for PA). In addition, the derivatization also improves the detection of PA by LC-HRMS as the PIC product possesses protonation sites (i.e., imidazole ring) relative to none exhibited by PA. More importantly, the carbamoylation proceeds under mild conditions (55 °C, no base) and rapidly (3 h), characteristics that make it an appealing protocol for the analysis of PA during OPCW PTs or real case scenarios particularly in instances where it is present at low concentrations. It is anticipated that the protocol can be applied to the forensic analysis of this important Soman marker in various environmental matrices.

Chemistry↗
DOE OSTI2021

A measured energy use, solar production, and building air leakage dataset for a zero energy commercial building

This paper provides an open dataset of measured energy use, solar energy production, and building air leakage data from a 328 m 2 (3,531 ft 2 ) all-electric, zero energy commercial building in Virginia, USA. Over two years of energy use data were collected at 1-hour intervals using circuit-level energy monitors. Over six years of solar energy production data were measured at 1-hour resolution by 56 microinverters (presented as daily and monthly data in this dataset). The building air leakage data was measured post-construction per ASTM-E779 Standard Test Method for Determining Air Leakage Rate by Fan Pressurization and the United States Army Corps (USACE) Building Enclosure Testing procedure; both pressurization and depressurization results are provided. The architectural and engineering (AE) documents are provided to aid researchers and practitioners in reliable modeling of building performance. The paper describes the data collection methods, cleaning, and convergence with weather data. This dataset can be employed to predict, benchmark, and calibrate operational outcomes in zero energy commercial buildings.

14 SOLAR ENERGY↗
DOE OSTI2025

Building Inclusive Educational and Career Pathways in Fusion Energy

This paper was written in preparation for the Workforce Accelerator for Fusion Energy Development conference, which was funded by the National Science Foundation. Prior to the conference, participants from academia, government, industry, national laboratories, and nonprofit organizations worked together to write White papers. Held in Hampton, Virginia, in May 2024, the conference convened participants to discuss various topics in support of workforce development in fusion energy. As the fusion industry expands, efforts to recruit and retain a diverse workforce, ensure equitable access to fusion education, and gain public support will be critical to meeting workforce needs in this field. We outline strategic recommendations across three vital areas: improving diversity data collection; supporting career advancement and retention with a diversity, equity, inclusion, accessibility, and belonging focus; and strengthening community engagement and education in fusion energy.

Cote, Laleh [Lawrence Berkeley National Laboratory↗
DOE OSTI2025

Accelerating the fusion workforce in the USA

The fusion energy research and development landscape has seen significant advances in recent years, with important scientific and technological breakthroughs and a rapid rise of investment in the private sector. The workforce needs of the nascent fusion industry are growing at a rate that academic workforce development programs are not currently able to match. This paper presents the findings of the Workforce Accelerator for Fusion Energy Development Conference held in Hampton, Virginia, United States of America (USA), on 29–30 May 2024, which was funded by the National Science Foundation of the USA. A major goal of the conference was to focus on bringing public and private stakeholders together to identify opportunities for partnership in fusion research and education with the goal of meeting the needs for a talented and diverse workforce. Representatives from industry, academia, and national laboratories participated in the conference through the preparation of white papers, presentations, and group discussions, and the production of recommendations to address the challenges facing the fusion workforce in the USA.

diversity↗
DOE OSTI2022

From legacy contamination to watershed systems science: a review of scientific insights and technologies developed through DOE-supported research in water and energy security

Abstract Water resources, including groundwater and prominent rivers worldwide, are under duress because of excessive contaminant and nutrient loads. To help mitigate this problem, the United States Department of Energy (DOE) has supported research since the late 1980s to improve our fundamental knowledge of processes that could be used to help clean up challenging subsurface problems. Problems of interest have included subsurface radioactive waste, heavy metals, and metalloids (e.g. uranium, mercury, arsenic). Research efforts have provided insights into detailed groundwater biogeochemical process coupling and the resulting geochemical exports of metals and nutrients to surrounding environments. Recently, an increased focus has been placed on constraining the exchanges and fates of carbon and nitrogen within and across bedrock to canopy compartments of a watershed and in river–floodplain settings, because of their important role in driving biogeochemical interactions with contaminants and the potential of increased fluxes under changing precipitation regimes, including extreme events. While reviewing the extensive research that has been conducted at DOE’s representative sites and testbeds (such as the Oyster Site in Virginia, Savannah River Site in South Carolina, Oak Ridge Reservation in Tennessee, Hanford in Washington, Nevada National Security Site in Nevada, Riverton in Wyoming, and Rifle and East River in Colorado), this review paper explores the nature and distribution of contaminants in the surface and shallow subsurface (i.e. the critical zone) and their interactions with carbon and nitrogen dynamics. We also describe state-of-the-art, scale-aware characterization approaches and models developed to predict contaminant fate and transport. The models take advantage of DOE leadership-class high-performance computers and are beginning to incorporate artificial intelligence approaches to tackle the extreme diversity of hydro-biogeochemical processes and measurements. Recognizing that the insights and capability developments are potentially transferable to many other sites, we also explore the scientific implications of these advances and recommend future research directions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Offshore lightning more active and intense in U.S. East Coast wind areas than in North Sea

Fast winds over open areas off the U.S. East Coast resulted in many offshore areas being opened for wind power deployment. Yet lightning is active in this same general area. Lightning damage has been noted as the leading cause of unplanned downtime of wind farms. Here we use lightning observations from 2020–2022 to quantify lightning activity—U.S. East Coast Wind Lease and Wind Planning areas received about 14-times the lightning strokes and about 18-times the energy transfer compared to the operational wind farms in the North Sea. A strong north-south U.S. gradient of lightning exists : low off the coast of Maine, growing higher off Chesapeake Bay, and high south of Virginia. Very high lightning activity also occurs about 250 km from the U.S. coastline, which is 50–100 km outside currently designated Wind Areas but likely relevant to planning floating wind farms further from shore. International lightning protection standards, such as IEC 614200-24, use lightning stroke density and turbine top-height to estimate damage to wind turbines, but it remains unclear if such standards could protect U.S. offshore wind turbines in active lightning areas where the turbine top-height can be 100 m taller than the next tallest object for tens to hundreds of kilometers. This analysis suggests U.S. East Coast offshore wind farms will be subjected to much higher lightning stroke and lightning energy densities than the North Sea counterparts. Preparing the turbine designs in anticipation of these more active U.S. lightning risks will help foster wind’s growing contribution to a reliable and resilient low-carbon energy future.

lightning↗
DOE OSTI2022

Effects-Based Monitoring of Geomagnetically-Induced Current Using a Convolutional Neural Network

Geomagnetically-induced current (GIC) due to space weather can flow in the power grid causing undesirable effects such as transformer overheating, misoperation of protection devices, and potential blackouts. It is therefore important to monitor GIC in the power grid to improve online situational awareness and decision-making of system operators during a geomagnetic disturbance. To avoid the costly installation of GIC monitors at transformers’ neutrals, it is desirable to find correlations between GIC and already-monitored parameters. Hence, this work proposed the use of a convolutional neural network (CNN) to compute GIC amplitudes from learned patterns in the time-series data of transformer even harmonic currents. Using an electromagnetic transient program, GIC injection simulations were performed for a modeled Dominion Energy Virginia (DEV) substation with two 504 MVA, 500/230 kV transformers. Data collected from these offline simulations were used to train the CNN to provide online GIC monitoring. Testing the CNN performance involved using real GIC measurements from published literature and from a physical GIC monitor in the DEV area. Finally, the results showed that the proposed method was able to provide GIC readings with a root mean squared error of 1.56 A/phase (equivalent to an average accuracy of 94%) for these real GIC waveforms.

42 ENGINEERING↗
DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2022

Neural net detection of seismic features related to gas hydrates and free gas accumulations on the northern U.S. Atlantic margin

Bottom-simulating reflections (BSRs) that sometimes mark the base of the gas hydrate stability zone in marine sediments are often identified based on the reverse polarity reflections that cut across stratigraphic layering in seismic amplitude data. On the northern U.S. Atlantic margin (USAM) between Cape Hatteras and Hudson Canyon, legacy seismic data have revealed pronounced BSRs south of the deepwater extension of Hudson Canyon and more subtle ones from offshore Delaware south to Cape Hatteras, where the reflections sometimes follow stratigraphic layering. Using high-resolution seismic data acquired during the 2018 Mid-Atlantic Resource Imaging Experiment and a supervised neural net, we identify seismic features associated with gas hydrates and/or the top of gas between Hudson Canyon and Cape Hatteras. Using seismic attributes especially sensitive to the presence of gas, we train a neural network algorithm on seismic data from an area with strong BSRs and then apply the model to the rest of the data set. The results indicate that gas hydrate and/or shallow free gas are significantly more widespread on the northern part of the USAM than previously known. Seismic indicators of gas extend landward from the 2000 m isobath to the upper continental slope in sectors with (offshore Virginia) and, to a lesser extent, without (offshore New Jersey) pervasive upper slope methane seeps. Higher sand content and intermediate sediment thickness, factors related to the container size and gas charge in a petroleum systems framework, are associated with more robust gas indicators.

Geochemistry & Geophysics↗
DOE OSTI2022

Advanced Terrestrial Simulator (ATS) evaluation dataset at 7 catchments across the continental United States

This dataset comprises of the input files and other files required for Advanced Terrestrial Simulator (ATS) simulations at 7 catchments across the continental United States. ATS is an integrated surface-subsurface hydrology model. We include Jupyter notebooks (within scripts folder) for individual catchments showing information (including data sources, river network, soil, geology, landuse types etc.) on preparing the machine readable input files. ATS observation output files are provided in the output folder. Figures and analyses (.xlsx sheets) are also provided. The catchments include, Taylor River Upstream (Colorado); (b) Cossatot River (Arkansas); (c) Panther Creek (Alabama); (d) Little Tennessee River (North Carolina and Georgia); (e) Mayo River (Virginia); (f) Flat Brook (New Jersey); (g) Neversink River headwaters (New York). Readme files are provided inside the directories providing more details. Files types include: .xml, .h5, .xlsx, .png, .ipynb, .py, .nc, .txt. All of the files types can be accessed by open source software, details on software requirements are following: .xml (any text editors including notepad and textedit), .h5 (in python using hdf libraries), .xlsx (WPS Office Spreadsheets, OpenOffice Calc, LibreOffice Calc, Microsoft Office etc.), .png (any image viewer), .ipynb (Jupyter notebook), .py (any text editors including notepad and textedit), .nc (using python or other open source software).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluating the Persistence of Soil Carbon After a 30-Year Nitrogen Fertilization Experiment at the Fernow Experimental Forest, WV

We sampled soils in a previously nitrogen (N)-fertilized watershed (Watershed 3), which received 35 kg N per hectare annually for 30 years, and a reference watershed (Watershed 7), 4 years after the end of a 30-year N fertilization experiment at the Fernow Experimental Forest in West Virginia. As N deposition has reduced soil pH and plant carbon (C) investments into the rhizosphere, we compared the extent to which removing these potential limitations to microbial decomposition by increasing soil pH, adding artificial root exudates, or elevating soil temperature would increase microbial decomposition (and soil C losses) in soils that have and have not received excess N inputs. As such, we incubated soils with and without the addition of artificial root exudates and dolomitic lime (2 amendment treatments and 1 untreated control), at three different temperatures (15, 20, and 25 C) to simulate warming. We measured soil respiration, enzyme activity (acid phosphatase, N -acetyl-β-glucosaminidase, beta-glucosidase, phenol oxidase, and peroxidase), and microbial biomass carbon in a 15-week microcosm experiment. All of the datasheets include the metadata for all of the treatment combinations from this incubation experiment (ID, incubation temperature, treatment, watershed).The "Soil_Chemistry_Data.csv" data includes (1) the ratio of dry soil weight (g) by wet (or fresh) soil weight (g) after 72 hours at 65 C, (2) the wet (or fresh) weight of the soil samples used to determine soil pH, and (3) soil pH, which was measured in CaCl2. Detailed methods for the measurements of soil pH are described in the datasheet itself.The "Respiration_Data.csv" data includes (1) respiration day for the measurement, and (2) cumulative CO2 respiration (mmol) measured in the microcosms on specific days.The "Microbial_Biomass_Data.csv" data includes (1) mmol microbial biomass carbon per g (dry weight) of soil in each microcosm.The "Enzyme_Data.csv" data includes (1) all extracellular soil enzyme activity (N-acetyl-glucosaminidase (NAG), acid phosphatase (AP), β-glucosidase (BG), phenol oxidase and peroxidase) that we measured in our microcosms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Mesoscale Design of Magnetoelectric Heterostructures and Nanocomposites

Multiferroic materials have a coexistence of at least two ferroic orders. The coupling interaction between the different order parameters can produce new phenomena, such as the magnetoelectric (ME) effect. The ME response is the appearance of an electric polarization P upon applying a magnetic field H, and/or vice versa. Magnetoelectricity has been observed as an intrinsic effect in some natural materials at low temperature; however, such single phase materials suffer from extremely weak ME exchange. Better alternatives are two-phase composites consisting of magnetostrictive and piezoelectric phases, which have been shown to have large ME coefficients. Said composites exploit a unique product ME tensor property that depends upon the individual strictions of the piezoelectric and magnetostrictive phases, the elastic stiffness and integrity of the interphase interfaces, the phase distribution and the dimensionality of its connectivity, and any elastic constraint; amongst other things. This research program between D. Viehland PI and S.Priya at Virginia Tech investigated the mesoscale physics and chemistry of such two-phase ME heterostructures. The results of the proposed research are relevant to new generations of multifunctional materials involving heterogeneous components. How the product ME property be optimized? The answers lies with the interphase-interfaces, where the atomic layers coordinate stress transfer from one phase to another. It was the primary goal of this research program to discover such fundamental relationship for two phase ME heterostructures and nanocomposites. This research program integrated all the components required to fully investigate the ME phenomenon: starting from synthesis of nanomaterials with diversified interfacial characteristics; to full electrical, magnetic, and structural characterizations.

36 MATERIALS SCIENCE↗