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At least 631 records · Page 35

Materializing rival ground states in the barlowite family of kagome magnets: quantum spin liquid, spin ordered, and valence bond crystal states

The spin- 1 2 kagome antiferromagnet is considered an ideal host for a quantum spin liquid ground state. We find that when the bonds of the kagome lattice are modulated with a periodic pattern, new quantum ground states emerge. Newly synthesized crystalline barlowite (Cu 4 (OH) 6 FBr) and Zn-substituted barlowite demonstrate the delicate interplay between singlet states and spin order on the spin- 1 2 kagome lattice. Comprehensive structural measurements demonstrate that our new variant of barlowite maintains hexagonal symmetry at low temperatures with an arrangement of distorted and undistorted kagome triangles, for which numerical simulations predict a pinwheel va- lence bond crystal (VBC) state instead of a quantum spin liquid (QSL). The presence of interlayer spins eventually leads to an interesting pinwheel q=0 magnetic order. Partially Zn-substituted bar- lowite (Cu 3.44 Zn 0.56 (OH) 6 FBr) has an ideal kagome lattice and shows QSL behavior, indicating a surprising robustness of the QSL against interlayer impurities. The magnetic susceptibility is simi- lar to that of herbertsmithite, even though the Cu 2+ impurities are above the percolation threshold for the interlayer lattice and they couple more strongly to the nearest kagome moment. This system is a unique playground displaying QSL, VBC, and spin order, furthering our understanding of these highly competitive quantum states.

36 MATERIALS SCIENCE↗

Cu site differentiation in tetracopper(I) sulfide clusters enables biomimetic N 2 O reduction

Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu 4 (μ 4 -S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N 2 O gas. More precisely, we hypothesize that the Cu δ+ ∙∙∙Cu δ- pairs produced upon site differentiation are poised for N 2 O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genomic prediction of switchgrass winter survivorship across diverse lowland populations

Abstract In the North-Central United States, lowland ecotype switchgrass can increase yield by up to 50% compared with locally adapted but early flowering cultivars. However, lowland ecotypes are not winter tolerant. The mechanism for winter damage is unknown but previously has been associated with late flowering time. This study investigated heading date (measured for two years) and winter survivorship (measured for three years) in a multi-generation population generated from two winter-hardy lowland individuals and diverse southern lowland populations. Sequencing data (311,776 markers) from 1,306 individuals were used to evaluate genome-wide trait prediction through cross-validation and progeny prediction (n = 52). Genetic variance for heading date and winter survivorship was additive with high narrow-sense heritability (0.64 and 0.71, respectively) and reliability (0.68 and 0.76, respectively). The initial negative correlation between winter survivorship and heading date degraded across generations (F1 r = −0.43, pseudo-F2 r = −0.28, pseudo-F2 progeny r = −0.15). Within-family predictive ability was moderately high for heading date and winter survivorship (0.53 and 0.52, respectively). A multi-trait model did not improve predictive ability for either trait. Progeny predictive ability was 0.71 for winter survivorship and 0.53 for heading date. These results suggest that lowland ecotype populations can obtain sufficient survival rates in the northern United States with two or three cycles of effective selection. Despite accurate genomic prediction, naturally occurring winter mortality successfully isolated winter tolerant genotypes and appears to be an efficient method to develop high-yielding, cold-tolerant switchgrass cultivars.

60 APPLIED LIFE SCIENCES↗

Contributions of environmental and maternal transmission to the assembly of leaf fungal endophyte communities

Leaf fungal endophytes (LFEs) contribute to plant growth and responses to stress. Fungi colonize leaves through maternal transmission, e.g. via the seed, and through environmental transmission, e.g. via aerial dispersal. The relative importance of these two pathways in assembly and function of the LFE community is poorly understood. We used amplicon sequencing to track switchgrass (Panicum virgatum) LFEs in a greenhouse and field experiment as communities assembled from seed endophytes and rain fungi (integration of wet and dry aerial dispersal) in germinating seeds, seedlings, and adult plants. Rain fungi varied temporally and hosted a greater portion of switchgrass LFE richness (greater than 65%) than were found in seed endophytes (greater than 25%). Exposure of germinating seeds to rain inoculum increased dissimilarity between LFE communities and seed endophytes, increasing the abundance of rain-derived taxa, but did not change diversity. In the field, seedling LFE composition changed more over time, with a decline in seed-derived taxa and an increase in richness, in response to environmental transmission than LFEs of adult plants. Furthermore, we show that environmental transmission is an important driver of LFE assembly, and likely plant growth, but its influence depends on both the conditions at the time of colonization and plant life stage.

59 BASIC BIOLOGICAL SCIENCES↗

Optical Trapping of High-Aspect-Ratio NaYF Hexagonal Prisms for kHz-MHz Gravitational Wave Detectors

Here, we present experimental results on optical trapping of Yb-doped β-NaYF subwavelength-thickness high-aspect-ratio hexagonal prisms with a micron-scale radius. The prisms are trapped in vacuum using an optical standing wave, with the normal vector to their face oriented along the beam propagation direction, yielding much higher trapping frequencies than those typically achieved with microspheres of similar mass. This platelike geometry simultaneously enables trapping with low photon-recoil-heating, high mass, and high trap frequency, potentially leading to advances in high frequency gravitational wave searches in the Levitated Sensor Detector, currently under construction. The material used here has previously been shown to exhibit internal cooling via laser refrigeration when optically trapped and illuminated with light of suitable wavelength. Employing such laser refrigeration methods in the context of our work may enable higher trapping intensity and thus higher trap frequencies for gravitational wave searches approaching the several hundred kilohertz range.

47 OTHER INSTRUMENTATION↗

Site-Specific Structure at Multiple Length Scales in Kagome Quantum Spin Liquid Candidates

Realizing a quantum spin liquid (QSL) ground state in a real material is a leading issue in condensed matter physics research. In this pursuit, it is crucial to fully characterize the structure and influence of defects, as these can significantly affect the fragile QSL physics. In this work, we perform a variety of cutting-edge synchrotron x-ray scattering and spectroscopy techniques, and we advance new methodologies for site-specific diffraction and L-edge Zn absorption spectroscopy. The experimental results along with our first-principles calculations address outstanding questions about the local and long-range structures of the two leading kagome QSL candidates, Zn-substituted barlowite Cu 3 Zn x Cu 1-x (OH) 6 FBr and herbertsmithite Cu 3 Zn(OH) 6 Cl 2 . On all length scales probed, there is no evidence that Zn substitutes onto the kagome layers, thereby preserving the QSL physics of the kagome lattice. Our calculations show that antisite disorder is not energetically favorable and is even less favorable in Zn-barlowite compared to herbertsmithite. Site-specific x-ray diffraction measurements of Zn-barlowite reveal that Cu 2+ and Zn 2+ selectively occupy distinct interlayer sites, in contrast to herbertsmithite. Using the first measured Zn L-edge inelastic x-ray absorption spectra combined with calculations, we discover a systematic correlation between the loss of inversion symmetry from pseudo-octahedral (herbertsmithite) to trigonal prismatic coordination (Zn-barlowite) with the emergence of a new peak. Overall, our measurements suggest that Zn-barlowite has structural advantages over herbertsmithite that make its magnetic properties closer to an ideal QSL candidate: its kagome layers are highly resistant to nonmagnetic defects while the interlayers can accommodate a higher amount of Zn substitution.

36 MATERIALS SCIENCE↗

Photon-Counting Interferometry to Detect Geontropic Space-Time Fluctuations with GQuEST

The gravity from the quantum entanglement of space-time (GQuEST) experiment uses tabletop-scale Michelson laser interferometers to probe for fluctuations in space-time. We present a practicable interferometer design featuring a novel photon-counting readout method that provides unprecedented sensitivity, as it is not subject to the interferometric standard quantum limit. We evaluate the potential of this design to measure space-time fluctuations motivated by recent “geontropic” quantum gravity models. The accelerated accrual of Fisher information offered by the photon-counting readout enables GQuEST to detect the predicted quantum gravity phenomena within measurement times at least 100 times shorter than equivalent conventional interferometers. The GQuEST design, thus, enables a fast and sensitive search for signatures of quantum gravity in a laboratory-scale experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Long‐term yields in annual and perennial bioenergy crops in the Midwestern United States

Abstract Many yield predictions in perennial bioenergy species have been made based on data collected during the establishment phase of growth or a limited number of long‐term studies. Few studies compare multiple perennial crops with the dominant agricultural vegetation of the landscape over long time periods. Here, we present the results of 11 years of perennial crop management on fertile agricultural soils in central Illinois, compared with conventional row crop maize/soybean ( Zea mays L., Glycine max L.) production. We examined the long‐term productivity and drought susceptibility of Miscanthus x giganteus Greef et. Deu. ex. Hodkinson et Renvoize (miscanthus), Panicum virgatum L., Cave‐in‐Rock cultivar (switchgrass), and a native prairie mix, in contrast to annual maize/soybean agriculture. Long‐term yields for miscanthus and switchgrass failed to reach initial predictions made during the establishment phase; however, in miscanthus, the 11 th year of production shows little progressive yield loss with age, exceeding the modeled limit for the onset of age‐related decline. Harvest timing and differences in yields from hand and machine harvests in perennial crops likely contribute to overestimates of potential yields. Application of fertilizer to mature miscanthus resulted in significant increases in yield after a severe drought, though modeled effects of management and drought in miscanthus point to a more complex mechanism for yield response.

09 BIOMASS FUELS↗

Biomass yield improvement in switchgrass through genomic prediction of flowering time

The seasonal timing of the transition from vegetative to reproductive growth has a major impact on biomass accumulation in switchgrass. Late-flowering switchgrass cultivars produce greater biomass, a critical trait for sustainable bioenergy production. Genomic prediction (GP) may allow rapid selection of late-flowering individuals with reduced time and expense for field evaluations. To evaluate GP, two flowering time traits (heading date and anthesis date) were collected on 1532 genotypes from four breeding populations: Midwest, Gulf, Atlantic, and Hybrid. These were sequenced using genotype-by-sequencing (530,792 single-nucleotide polymorphisms). Predictive ability of single-trait and multi-trait models were evaluated by cross-validation, by prediction of a progeny trial (n = 122), and through prediction of yield performance in a parallel experiment (n = 52). Predictive ability was not improved by sharing information among breeding groups. Overall, multi-trait models provided an advantage during cross-validation, but a smaller advantage during progeny prediction. Within populations, GP resulted in lower per-cycle progress than previously reported field evaluations (3.1 vs. 5.0 day –1 cycle –1 ). However, GP cycles are potentially much faster than field evaluations. When directly predicting biomass yield, the Hybrid training population had a predictive ability of 0.54–0.63. This reinforces the strong linkage between biomass yields in swards and flowering time. Furthermore, these results highlight the value of GP for rapid yield improvement in switchgrass, particularly in a breeding program designed to share information between biomass yield trials and low-cost flowering time evaluations.

09 BIOMASS FUELS↗

Brachypodium Phenylalanine Ammonia Lyase (PAL) Promotes Antiviral Defenses against Panicum mosaic virus and Its Satellites

Brachypodium distachyon has recently emerged as a premier model plant for monocot biology, akin to Arabidopsis thaliana. We previously reported genome-wide transcriptomic and alternative splicing changes occurring in Brachypodium during compatible infections with Panicum mosaic virus (PMV) and its satellite virus (SPMV). Here, we dissected the role of Brachypodium phenylalanine ammonia lyase 1 (PAL1), a key enzyme for phenylpropanoid and salicylic acid (SA) biosynthesis and the induction of plant defenses. Targeted metabolomics profiling of PMV-infected and PMV- plus SPMV-infected (PMV/SPMV) Brachypodium plants revealed enhanced levels of multiple defense-related hormones and metabolites such as cinnamic acid, SA, and fatty acids and lignin precursors during disease progression. The virus-induced accumulation of SA and lignin was significantly suppressed upon knockdown of B. distachyon PAL1 (BdPAL1) using RNA interference (RNAi). The compromised SA accumulation in PMV/SPMV-infected BdPAL1 RNAi plants correlated with weaker induction of multiple SA-related defense gene markers (pathogenesis related 1 [PR-1], PR-3, PR-5, and WRKY75) and enhanced susceptibility to PMV/SPMV compared to that of wild-type (WT) plants. Furthermore, exogenous application of SA alleviated the PMV/SPMV necrotic disease phenotypes and delayed plant death caused by single and mixed infections. Together, our results support an antiviral role for BdPAL1 during compatible host-virus interaction, perhaps as a last resort attempt to rescue the infected plant.

59 BASIC BIOLOGICAL SCIENCES↗

Data for "Field-scale Evaluation of Ecosystem Service Benefits of Bioenergy Switchgrass"

Purpose-grown perennial herbaceous species are nonfood crops specifically cultivated for bioenergy production and have the potential to secure bioenergy feedstock resources while enhancing ecosystem services. This study assessed soil greenhouse gas emissions (CO2 and N2O), nitrate (NO3-N) leaching reduction potential, evapotranspiration (ET), and water-use efficiency (WUE) of bioenergy switchgrass ( Panicum virgatum L.) in comparison to corn ( Zea mays L.). The study was conducted on field-scale plots in Urbana, IL, during the 2020–2022 growing seasons. Switchgrass was established in 2020 and urea-fertilized at 56 kg N ha−1 year−1. Corn management followed best management practices for the US Midwest, including no-till and 202 kg N ha−1 year−1 fertilization, applied as urea–ammonium nitrate (32%). Our results showed lower direct N2O emissions in switchgrass compared to corn. Although soil CO2 emissions did not differ significantly during the establishment year, emissions in subsequent years were over 50% higher in switchgrass than in corn, likely due to increased belowground biomass, which was over five times higher in switchgrass. Nitrate-N leaching decreased as the switchgrass stand matured, reaching 80% lower than in corn by the third year. Differences in ET and WUE between corn and switchgrass were not significant; however, results indicate a trend toward reduced WUE in switchgrass under drought, driven by lower aboveground biomass production. Our study demonstrates that switchgrass can be implemented at a commercial scale without negatively impacting the hydrological cycle, while potentially reducing N losses through nitrate-N leaching and soil N2O emissions, and enhancing belowground C storage.

field data↗

UAV remote sensing imagery - Miscanthus trials 2020 - Energy Farm - UIUC

Aerial imagery utilized as input in the manuscript "Deep convolutional neural networks exploit high spatial and temporal resolution aerial imagery to predict key traits in miscanthus" . Data was collected over M. Sacchariflorus and Sinensis breeding trials at the Energy Farm, UIUC in 2020. Flights were performed using a DJI M600 mounted with a Micasense Rededge multispectral sensor at 20 m altitude around solar noon. Imagery is available as tif file by field trial and date (10). The post-processing of raw images into orthophoto was performed in Agisoft Metashape software. Each crop surface model and multispectral orthophoto was stacked into an unique raster stack by date and uploaded here. Each raster stack includes 6 layers in the following order: Layer 1 = crop surface model, Layer 2 = Blue, Layer 3 = Green, Layer 4 = Red, Layer 5 = Rededge, and Layer 6 = NIR multispectral bands. Msa raster stacks were resampled to 1.67 cm spatial resolution and Msi raster stacks were resampled to 1.41 cm spatial resolution to ease their integration into further analysis. 'MMDDYYYY' is the date of data collection, 'MSA' is M. Sacchariflorus trial, 'MSI' is Miscanthus Sinensis trial, 'CSM' is crop surface model layer, and 'MULTSP' are the five multispectral bands.

bioenergy↗

RAD-seq genotypes for a Miscanthus sacchariflorus diversity panel

Restriction site-associated DNA sequencing (RAD-seq) data from 643 Miscanthus accessions from a diversity panel, including 613 Miscanthus sacchariflorus, three M. sinensis, and 27 M. xgiganteus. DNA was digested with PstI and MspI, and single-end Illumina sequencing was performed adjacent to the PstI site. Variant and genotype calling was performed with TASSEL-GBSv2, using the Miscanthus sinensis v7.1 reference genome from Phytozome 12 (https://phytozome.jgi.doe.gov). Additional ploidy-aware genotype calling was performed by polyRAD v1.1.

biomass↗

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. * Todorov and Worsham are co–first authors.

2018 NEON and 2025 CHESS Campaigns↗