Magnetoelectric coupling in the multiferroic hybrid-improper ferroelectric Ca 3 Mn 1.9 Ti 0.1 O 7
Not provided.
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Not provided.
Not Available
Radii of nuclear charge distributions carry information about the strong and electromagnetic forces acting inside the atomic nucleus. Whereas the global behavior of nuclear charge radii is governed by the bulk properties of nuclear matter, their local trends are affected by quantum motion of proton and neutron nuclear constituents. The measured differential charge radii δ$\langle$$r^{2}_{c}$$\rangle$ between neutron numbers N = 28 and N = 40 exhibit a universal pattern as a function of n = N – 28 that is independent of the atomic number. In this work, we analyze this remarkable behavior in even-even nuclei from calcium to zinc using two state-of-the-art theories based on quantified nuclear interactions: the ab initio coupled cluster theory and nuclear density functional theory. Both theories reproduce the smooth rise of differential charge radii and their weak dependence on the atomic number. By considering a large set of isotopic chains, we show that this trend can be captured by just two parameters: the slope and curvature of δ$\langle$$r^{2}_{c}$$\rangle$(n). We demonstrate that these parameters show appreciable model dependence, and the statistical analysis indicates that they are not correlated with any single model property, i.e., they are impacted by both bulk nuclear properties as well as shell structure.
Hybridization of Bogoliubov quasiparticles (BQPs) between the CuO 2 layers in the triple-layer cuprate high-temperature superconductor Bi 2 Sr 2 Cu 2 Cu 3 O 10+δ is studied by angle-resolved photoemission spectroscopy (ARPES). In the superconducting state, an anticrossing gap opens between the outer- and inner-BQP bands, which we attribute primarily to interlayer single-particle hopping with possible contributions from interlayer Cooper pairing. We find that the d-wave superconducting gap of both BQP bands smoothly develops with momentum without an abrupt jump in contrast to a previous ARPES study. Hybridization between the BQPs also gradually increases in going from the off nodal to the antinodal region, which is explained by the momentum dependence of the interlayer single-particle hopping. As possible mechanisms for the enhancement of the superconducting transition temperature, the hybridization between the BQPs as well as the combination of phonon modes of the triple CuO 2 layers and spin fluctuations represented by a four-well model are discussed.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Not Available
Abstract not provided
As part of the Billion Ton resource assessment projections created in 2016 (see https://www.energy.gov/sites/prod/files/2016/12/f34/2016_billion_ton_report_12.2.16_0.pdf, DOI: 10.2172/1435342) -henceforth "BT16", this dataset was used as an assumption to limit the availability of residues under a "base-case" scenario (BC1). Crop residues that had this assumption applied include corn stover, cereal (wheat, oats, and barley) straws, and sorghum stubble. What is the purpose of the data set? Why were the data collected? Per request for use in subsequent research, we have summarized assumptions for California only and selected years (2020, 2030, 2040) that were used in the BT16's base-case projections for agricultural residues and have provided details by tillage class that limited residue availability for harvest (dry tons of residues that must remain). Note: '10' is a high number that assures that no residue harvested could occur. Note: Tillage classification assumptions are also of importance: a low flexibility was applied, allowing a moderate deviation from a baseline situation (using historic CTIC data on tillage type used in counties for each crop). A moderate flexibility, allows farmers to put land into another tillage type (no till, conservation till, and reduced till) where a higher net present value was calculated. This dataset includes all allowable tillage types by crop, but each tillage type may not have occurred in BT16 simulations.
This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.
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.
All data is collected from across 3 soil cores spanning a pH gradient at Point Reyes National Seashore, as part of a recent publication. The bulk data csv includes hygroscopic moisture content, soil pH, total C and N values, particle size distributions, cation exchange capacity and extractable cations. The STXM data package includes raw spectra data from scanning transmission X-ray microscopy C near-edge X-ray absorption fine structure spectroscopy analysis, extracted from STXM Image Reader analysis and then subsequently normalised in Athena (see details in paper). The data file also contains a bulk chemistry and mineralogy dataset, including total and trace element contents from 3 depths and mineral compositions as measured at BL 11-3 SSRL and semi-quantified in HighScore. Finally the final data file is calcium K-edge X-ray absorption near-edge structure spectroscopy (BL 4-3) and micro-XANES and micro-X-ray fluorescence (BL 14-3b) data.
Even though over half of the world's soil organic carbon (SOC) is stored in subsoils (>20 cm deep), and the old ages of subsoil OC indicate its cycling differs from surface SOC, there are few studies examining in situ decomposition processes in deep soils. The purpose of this dataset is to elucidate these processes. In this study we added 13C-labeled fine roots to 15, 55, and 95 cm depths of a well-characterized coniferous forest Alfisol and monitored the amount of root-derived C remaining over 6, 12, and 30 months. We recovered the root-derived C in microbial phospholipid fatty acids (PLFAs) after 6 months and in coarse (>2 mm) particulate, fine (<2 mm) particulate, and dense, mineral-associated pools after 6, 12, and 30 months. Overall, root decomposition in the first 6 months was similar among all depths but significantly diverged at 30 months with faster decomposition at 15 cm than at 95 cm. There were more fungal and Gram negative-associated PLFAs at 15 cm than at 95 cm, and 13C analysis revealed those microbial groups preferred the added root carbon to native SOC. Mineral-associations were not the cause of slower decomposition at depth because similar amounts of applied root C was recovered in the dense fraction at all depths. The largest difference among depths was in the amount of root C recovered in the coarse particulate fraction, which was greater at 95 cm (50%) than at 15 cm (15%). Slower decomposition of the particulate pool at depth likely contributed to the increase in C:N ratios and depletion of δ13C values below 60 cm depth in our soil profiles. Simulations of these soils using the CORPSE model, which incorporates microbial priming effects and mineral stabilization of SOC, reproduced patterns of particulate and mineral-associated SOC over both time and depth and suggested that a lack of priming by root exudates at depth could account for the slower decomposition rate of particulate root material. Decomposition of deep particulate SOC may increase if root exudation or dissolved OC transport to depth increases.This dataset includes (1) characterization of the soil pits prior to litter addition, (2) characterization of how the litter changed after 6, 12, and 30 months, and (3) the CORPSE model structure, parameterization, and output.
The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.This package contains Fourier transform ion cyclotron resonance mass spectrometry (21 Tesla FTICR-MS) data measured in negative and positive ionization mode from water and methanol soil extracts. Soil samples were collected in 2014/06/03 and 2018/06/04 from 3 replicated paired plots that had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. The following files are included: (1) fticr_neg_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (2) fticr_neg_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (3) fticr_neg_metadata.csv: metadata for samples/measurements in negative ion mode, (4) fticr_pos_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (5) fticr_pos_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (6) fticr_pos_metadata.csv: metadata for samples/measurements in positive ion mode.
The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of LBNL (Lawrence Berkeley National Laboratory) TES (Terrestrial Ecosystem Science) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from soil depth profiles collected from 2014 to 2021 from three paired control and warming plots. We collected soil samples across a range of depth profiles (spanning surface to 90 cm deep) from three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. 101 soil metagenomes were sequenced at JGI (Joint Genome Institute) and UCSF (University of California San Francisco) Center for Advanced Technology and can be found under the JGI (Joint Genome Institute) GOLD (Genomes Online Database) Sequencing project Gs0151586 and NCBI (National Center for Biotechnology Information) Projects PRJNA1225762 and PRJEB39497. Metagenomes were assembled using JGI (Joint Genome Institute) Metagenome Workflow (10.1128/mSystems.00804-20). For each metagenome, the assembled contigs were binned into genomes using 3 binning algorithms (cocacola, metabat, and maxbin) and the resulting bins were consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>50%) and contamination (<25%), and dereplicated at 99% ANI (average nucleotide identity) using dRep (https://github.com/MrOlm/drep).The dataset includes a zip file of 2321 MAG (Metagenome Assembled Genome) fasta files, the accession numbers for the underlying metagenomes, and a csv file with MAG (Metagenome Assembled Genome) quality metrics and taxonomic classification (GTDB -Genome Taxonomy Database-RS220). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.
The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization. This package contains soil metaproteomics data in the context of site specific metagenomes from soil depth profiles in three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. These metaproteomes were collected in 2018 after 4.5 years of warming from five depth intervals (0-10 cm, 10-30 cm, 30-45 cm, 45-60 cm, 60-80 cm). For protein identification, the collected spectra were searched following a target-decoy search strategy against a database of metagenome predicted proteins (covering 96 samples from 2014 to 2021) representing the complete sequence diversity at the site. Data was searched with mass spectrometry database search tool (MS-GF+) using Pacific Northwest National Laboratory (PNNL)'s Data Management System (DMS) Processing pipeline. The metagenomes are published as part of another data package. Raw metaproteomic data and the data products from MS-GF+ are deposited in the Mass Spectrometry Interactive Virtual Environment (MassIVE) database under accession no. MSV000097826. Here we present a dataset that includes spectral counts for the detected proteins across samples (EMSL50964_BrodieAllMAGs_Globals_SC.txt), the sequences of the detected proteins, and sample metadata file that contains site information for the soil metaproteome samples.