Seeing the Canopy for the Branches: Improved Within Canopy Scaling of Leaf Nitrogen
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The active layer morphology transition of organic photovoltaics under non-equilibrium conditions are of vital importance in determining the device power conversion efficiency and stability; however, a general and unified picture on this issue has not been well addressed. Using combined in situ and ex situ morphology characterizations, morphological parameters relating to kinetics and thermodynamics of morphology evolution are extracted and studied in model systems under thermal annealing. The coupling and competition of crystallization and demixing are found to be critical in morphology evolution, phase purification and interfacial orientation. A unified model summarizing different phase diagrams and all possible kinetic routes is proposed. The current observations address the fundamental issues underlying the formation of the complex multi-length scale morphology in bulk heterojunction blends and provide useful morphology optimization guidelines for processing devices with higher efficiency and stability.
The chemical durability of borosilicate glass used to confine nuclear wastes is known to vary nonlinearly with their composition, making glass dissolution rate predictions difficult. Here, we focus on the effect of Al, an important oxide of these materials. The initial and residual glass dissolution rates were investigated through experiments conducted at 90 °C and pH 9. Our results show that low Al content glasses dissolve initially faster than glasses with higher Al content, but quickly achieve a lower residual rate due to the rapid formation of a more passivating gel. Nevertheless, the high Al content gel will eventually achieve passivation with a slower reorganization. The strengthening effect of Al on the Si-O bond hydrolysis will result in more stable gels, suggesting that slightly higher Al content in the gel will improve nuclear high-level waste glass durability in geological disposal conditions.
The colour centre platform holds promise for quantum technologies, and hexagonal boron nitride has attracted attention due to the high brightness and stability, optically addressable spin states and wide wavelength coverage discovered in its emitters. However, its application is hindered by the typically random defect distribution and complex mesoscopic environment. In this study, employing cathodoluminescence, we demonstrate on-demand activation and control of colour centre emission at the twisted interface of two hexagonal boron nitride flakes. Further, we show that colour centre emission brightness can be enhanced by two orders of magnitude by tuning the twist angle. Additionally, by applying an external voltage, nearly 100% brightness modulation is achieved. Our ab initio GW and GW plus Bethe–Salpeter equation calculations suggest that the emission is correlated to nitrogen vacancies and that a twist-induced moiré potential facilitates electron–hole recombination. This mechanism is further exploited to draw nanoscale colour centre patterns using electron beams.
The perovskite oxide strontium titanate (SrTiO 3 ) combines electrostatic tunability, superconductivity and spin–orbit coupling, and is of potential use in the development of quantum devices. However, exploring quantum effects in SrTiO 3 nanostructures is challenging because of the presence of disorder. Here, in this work, we report high-mobility, gate-tunable devices in SrTiO 3 that have ballistic constrictions and clean normal-state conductance quantization. Our devices are based on SrTiO 3 two-dimensional electron gas channels that have a thin hafnium oxide barrier layer between the channel and an ionic liquid gate. Conductance plateaus show twofold degeneracy that persists for magnetic fields of at least 5 T. This is above what is expected from the g factors extracted at high fields and could be a signature of electron pairing extending outside the superconducting regime.
SrTiO 3 and aluminum-doped SrTiO 3 are synthesized by calcination of metal salts dissolved in a deep eutectic solvent (DES) without any post-synthesis treatment.
We perform spectroscopic surface characterization on mesoporous ceria (CeO 2 ) under exposure of sarin gas, also known as GB. We find mesoporous CeO 2 displays extraordinary reactivity towards GB dissociation under high vacuum. The spectroscopic results combined with density functional theory (DFT) calculations suggest that the cleavage of the P–F and P–OR bonds are both possible pathways for GB to dissociate on the CeO 2 surfaces. The modeling reveals differences in dissociation pathways of GB on the crystallographic (111)- and (110)-surfaces of ceria. Here we also report some dissociation of GB on mesoporous CeO 2 under ambient conditions. The finding that mesoporous CeO 2 can degrade GB under mild conditions is encouraging and implies the strong potential of ceria-based materials to be applied in combating chemical warfare agents related to the GB series.
Crystallographic orientation plays a central role in determining transport properties in correlated oxides with low-hysteresis metal–insulator transitions. Here, V3O5 thin films were grown on Al2O3 (0001) and their crystallographic registry was evaluated using x-ray diffraction and cross-sectional transmission electron microscopy. θ–2θ measurements show a single out-of-plane orientation defined by the (202) reflection. Azimuthal φ-scans of the V3O5 (310) reflection exhibit twelve discrete maxima over 360°, indicating a finite set of in-plane orientations imposed by the substrate symmetry. High-resolution TEM and fast Fourier transform analysis confirm crystallographic coherence at the film–substrate interface. The electrical conductivity exhibits a metal–insulator transition at TMIT ≈ 423 K with no measurable thermal hysteresis and a total change of ~1.6 orders of magnitude between 300 and 480 K. These results establish crystallographic registry in epitaxial V3O5 thin films and provide a structurally well-defined system for future studies of orientation-dependent transport.\r\nT
Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find these transitions are extremely computationally intensive. Even with large-scale, accelerated material simulations, the computational cost constrains the applicable domain in practice. Machine learning models, with the potential to learn the complex emergent behaviors governing atomistic transitions as a fast surrogate model, have great promise to predict transitions with a vastly reduced computational cost. Here, we demonstrate how transformers can be trained to predict atomistic transitions in nano-clusters. We show how we evaluate physical validity of the predictions and how a multitude of additional, different microstates can be generated by slightly varying the data provided to the model.
Sb is topologically non-trivial and semi-metallic, but differs from many topological semi-metals because of its continuous band gap. By measuring its (112) surface using angle- and spin-resolved photoemission spectroscopy, Sb(112) was shown to have 1D spin-polarised surface states resembling those on vicinal Bi surfaces and many topological insulators and topological semi-metals. The shape and spin-polarisation of the measured features and the calculated bands agreed. However, the measured features had a slightly steeper energy dispersion and different Fermi-momenta than the calculated bands. Both theoretical and experimental methods were necessary when determining the topology of Sb(112). The presence of projected bulk states near the Fermi-level and varying surface localisation of the electronic states meant it was challenging to deduce the topology of Sb(112) from the number of bands crossing the Fermi-level or a continuous contour in the bulk band gap. Ultimately, the calculations and measurements suggest that there are topological surface states on the Sb(112) surface.
This dataset captures the difference in concentration over the difference in discharge across upper and lower reaches of the East River watershed for 2015 and 2016 water years. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Herein, the upper reach is defined as the segment between EAQ (East Above Quigley) and EBC (East Below Copper), and the lower reach is defined as the segment between EBC and PH (Pump House). The overall purpose of the dataset is to provide a better accounting of the gains, losses or fractional solute turnover between sampling stations. Compiled data for the two segments (EAQ to EBC and EBC to PH) are provided in two Excel files, and the same data are provided in csv format in the corresponding zip files.
This data package is associated with the publication “Dissolved Organic Matter Functional Trait Relationships are Conserved Across Rivers” submitted to PNAS (Stegen et al., 2023). The study aims to understand large-scale spatial structure of the dissolved organic matter (DOM) thermodynamic traits and inter-trait relationships by investigating (1) river water and sediments collected along 97 rivers spanning 3 continents and (2) coastal sediment collected from fresh and saline locations in Pacific and Gulf/Atlantic rivers. Sediment extracts and water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). This dataset is comprised of three folders (1) Coastal, (2) WHONDR_S19S, and (3) Data_Dictionaries. Coastal contains (1) a subfolder with processed FTICR-MS data as csv files and sample collection metadata, (2) a subfolder with R scripts used to process the data and create associated figures, (3) a subfolder with the raw, unprocessed FTICR-MS data as .xml files, and (4) a readme file with more information about the dataset and instructions for using Formularity (https://omics.pnl.gov/software/formularity). WHONDRS_S19S contains (1) a csv file with processed FTICR data, (2) a csv with sample collection metadata, (3) a csv with sample geospatial data, (4) a csv with simulated lambda model outputs, (5) a subfolder with R scripts used to process the data and create associated figures, and (6) a readme file with more information regarding WHONDRS raw FTICR data and processing scripts. Data_Dictionaries contains data dictionaries for each csv file in the data package. The 97 global river corridors were part of a WHONDRS (https://whondrs.pnnl.gov) study. The raw, unprocessed FTICR-MS data with additional data can be found at doi:10.15485/1729719 for sediments and doi:10.15485/1603775 for water. This data package contains the processed data used in the associated manuscript. The coastal data has not been previously published, and this data package contains both the raw and processed data. Version 3 of this data package published February 2023 includes updates to the title of the manuscript, additional data and data dictionary and updated scripts linked to new analysis.
This dataset supports a broader study examining drivers of organic matter chemistry in variably inundated hyporheic zone sediments and further linking that chemistry to biogeochemical rates. The dataset provides physical and chemical sediment data collected from 48 rivers across North America. There are related data that will be published, including surficial sediment temperature time series that can be used to infer the dynamics of inundation prior to the collection of sediments. This dataset is comprised of two folders: (1) ECA2_Sediment and (2) ECA2_SitePhotos. The ECA2_Sediment folder contains: (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) non-purgeable organic carbon (NPOC), total nitrogen (TN), and sediment moisture; (5) sediment sampling protocol, (6) readme, and (7) folder of high resolution characterization of organic matter from sediment extracts via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR-MS files are .xml, and the data package includes instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All other files are .csv, .txt, or .pdf. The ECA2_SitePhotos folder contains a readme and site photographs taken in the field. All files are .txt or .jpg.
Pond B at Savannah River Site (SRS, South Carolina) is a monomictic reservoir that received SRS R reactor cooling water from 1961–1964. Previous studies conducted between the 1980s–1990s on the water column and sediments of Pond B measured trace amounts of Pu (33 MBq 238Pu and 430 MBq 239,240Pu), 241Am, and 137Cs. Since then, the pond has been relatively isolated and the radionuclide concentrations have not been monitored over time. Herein, about 30 years after the last publication on Pond B, we are re-evaluating the geochemistry and radionuclide distribution within Pond B at five locations along a horizontal transect from the inlet to outlet. In addition, we are conducting the first analysis of the microbial community composition. This data package consists of water column measurements (1) using a multi-probe sonde, (2) plutonium isotopes and total concentrations, (3) total organic/inorganic carbon concentrations, (4) trace metals and major ions concentrations, and (6) microbial community composition. Sediment measurements include (1) plutonium isotopes and total concentrations and (2) microbial community composition.For sediment core and porewater, please see other Pond B data package (ess-dive-60d2352a4495472-20200615T203925174).The data in this package will be submitted for peer review in 2023.
This dataset provides geospatial information, metadata, and maps for the Pacific Northwest National Laboratory (PNNL) River Corridor Science Focus Area (RC-SFA; https://www.pnnl.gov/projects/river-corridor) sites. The RC-SFA works to transform understanding of spatial and temporal dynamics in river corridor hydrobiogeochemical functions from molecular reaction to watershed and basin scales. The knowledge we gain is used to formulate and test hypotheses and to improve mechanistic representation of river corridor processes and their response to disturbances in multiscale models of integrated hydrobiogeochemical function. The data provided includes Site ID, latitude, longitude, stream name, and common ID (COMID) for sites used across the RC-SFA. The COMID can be used to find and download data from NHDPlus (https://www.epa.gov/waterdata/nhdplus-national-hydrography-dataset-plus) and other platforms. The sites included are non-exhaustive. Sites (including past sites) will be added to this data package in the future. Data generated from the RC SFA can be accessed at https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA. This data package was originally published in April 2023. It was updated in June 2023 (v2; modified files), December 2023 (v3; modified files), January 2025 (v4; modified files), and December 2025 (v5; modified files). See the change history section in the readme for more details. This dataset is comprised of one main data folder. The data folder consists of (1) file-level metadata; (2) data dictionary; (3) readme; (4) methods codes; (5) geospatial information for all RC SFA sites including International Generic Sample Number (IGSN); (6) maps of all sites and sites in Washington State, USA; and (7) a subfolder with the shapefile of all sites. All files are .csv, .pdf, .shp, .cpg, .dbf, .prj, .qmd, or .shx. We thank the Confederated Tribes and Bands of the Yakama Nation for access to field locations where some data were collected in Washington state. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.
This archived model data is related to a study introducing a unique method that employs a stream-aligned mixed-polyhedral mesh to effectively and accurately represent river valleys, stream corridors, and narrow engineered channels in integrated hydrology simulations. The study finds that utilizing stream-aligned mixed-polyhedral meshes in integrated hydrology simulations achieves accuracy on par with a finely refined TIN-based mesh while markedly diminishing computational costs. This archive contains scripts and data files needed to generate the ATS model input, including mesh and ATS input files, for all mesh scenarios using the Watershed Workflow package. Additionally, this archive also provides key outputs from the model simulations that are used in the analysis and post-processing scripts to reproduce figures in the manuscript. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model are in XML format and can be edited in any commonly used text editors.
This data package is associated with the publication "Organic Molecules are Deterministically Assembled in River Sediments" submitted to Scientific Reports (Stegen et al., 2024). The study applies community ecology methods to dissolved organic matter (DOM) chemistry from variably inundated riverbed sediments to uncover principles governing DOM composition at a reach-scale. This data package documents the workflow used to process and generate the main findings in the manuscript. The R scripts reference the raw, unprocessed Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data from another data package, available on ESS-DIVE at https://data.ess-dive.lbl.gov/view/doi:10.15485/1834208. The scripts then process the raw FTICR-MS data and generate the findings and figures presented in the associated manuscript. In brief, this study demonstrates that DOM assemblages in variably inundated sediments are primarily governed by deterministic variable selection, including sediment moisture effecting the degree of deterministic assembly. See the manuscript for more details pertaining to interpretation and implications of the findings. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/ECA_2020_Sed.This data package is comprised of 6 scripts and 7 folders. The file-level metadata file (file ending in "flmd.csv") lists all files contained in this data package and descriptions for each. The data dictionary (file ending in "dd.csv) describes all tabular data columns and their respective definitions and units. The FTICR_Processing_Scripts produce the outputs found in the "Processed_Data" folder. The remaining scripts (located in the parent directory) produce the outputs found in the following four folders: (1) "MCD_Dendrograms", "MCD_Randomizations", "MCD_bNTI_Outcomes", and "OM_Null_Modeling". The fifth script additionally takes the three comma-separated values (CSV) files found in the parent directory as input ("VGC_texture.csv", "merged_weights.csv", and "ECA2_FTICR_BetaDisp.csv"). The outputs of each of the five scripts serve as the input to the following script, with the final outputs stored in the folder "OM_Null_Modeling".
This study builds on Rathore et al. (2024, WRR) and investigates the role of artificial tile-drainage on various aspects of watershed hydrological response, with a particular focus on peakflow. The model-data for the original modeling-focused paper (Rathore et al., 2024, WRR) is archived at Rathore et al. (2024, ESS-DIVE). Hence, this model-data archive provides scripts that are specific to this study that includes model updates, processing and analysis scripts. For details and models files of original model, readers are referred to Rathore et al. (2024, ESS-DIVE). The key difference between the model configuration in this study and Rathore et al. (2024, WRR) is that the tile drains are applied to the entire domain, to study the impact of tile-drains on different aspects of hydrological response. Additional scenario considering intensified precipitation after a dry period was also simulated. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts.