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At least 1,315 records · Page 73

Odd- and even-denominator fractional quantum Hall states in monolayer WSe 2

Monolayer semiconducting transition-metal dichalcogenides (TMDs) represent a unique class of two-dimensional (2D) electron systems. Their atomically thin structure facilitates gate tunability just like graphene does, but unlike graphene, TMDs have the advantage of a sizable band gap and strong spin–orbit coupling. Measurements under large magnetic fields have revealed an unusual Landau level (LL) structure, distinct from other 2D electron systems. However, owing to the limited sample quality and poor electrical contact, probing the lowest LLs has been challenging, and observation of electron correlations within the fractionally filled LL regime has not been possible. Here, through bulk electronic compressibility measurements, we investigate the LL structure of monolayer WSe 2 in the extreme quantum limit, and observe fractional quantum Hall states in the lowest three LLs. The odd-denominator fractional quantum Hall sequences demonstrate a systematic evolution with the LL orbital index, consistent with generic theoretical expectations. In addition, we observe an even-denominator state in the second LL that is expected to host non-Abelian statistics. Finally, our results suggest that the 2D semiconductors can provide an experimental platform that closely resembles idealized theoretical models in the quantum Hall regime.

36 MATERIALS SCIENCE↗

Plasmon-enhanced ultralow-threshold solid-state triplet fusion upconversion

Triplet fusion upconversion has potential applications in solar cells, photoredox catalysis, additive manufacturing and bioimaging. However, solid-state upconversion systems have struggled to measure up to their solution-phase counterparts, often requiring enormous optical power densities to operate at the maximum efficiency. Here we substantially improve the performance of upconversion films through excitation with surface plasmons that propagate along a planar silver-film interface, leading to an absorption enhancement that reduces the intensity threshold I th by a factor of 19 and enhances the external quantum efficiency by a factor of 17. From this, we achieve I th values as low as 3.4 mW cm −2 and an external quantum efficiency up to 0.094%. To demonstrate real-world viability, we couple the upconversion film to plasmons generated by the near-field of excitons in an organic light-emitting diode. As a result, this scheme is then used to fabricate a white-emitting organic light-emitting diode where blue emission sources from plasmon-excited upconversion, achieving a high colour rendering index of 86.2 and setting precedent for blue emission in the absence of high-energy polarons or triplets.

36 MATERIALS SCIENCE↗

Direct observation of two-dimensional magnons in atomically thin CrI 3

Magnons are collective spin excitations in crystals with long-range magnetic order. The emergent van der Waals magnets provide a highly tunable platform to explore magnetic excitations in the two-dimensional limit with intriguing properties, manifesting from their honeycomb lattice structure and switchable magnetic configurations. Here, we report the direct observation of two-dimensional magnons through magneto-Raman spectroscopy with optical selection rules determined by the interplay between crystal symmetry, layer number and magnetic states in atomically thin CrI 3 . In monolayers, we observe an acoustic magnon mode at ~0.3 meV. It has strict cross-circularly polarized selection rules locked to the magnetization direction that originates from the conservation of angular momentum of photons and magnons dictated by three-fold rotational symmetry. Additionally, we reveal optical magnon modes at ~17 meV. This mode is Raman silent in monolayers, but optically active in bilayers and bulk due to a relaxation of the parity criterion resulting from the layer index. In the layered antiferromagnetic states, we directly resolve two degenerate optical magnon modes with opposite angular momentum and conjugate optical selection rules. From these measurements, we quantitatively extract the spin-wave gap, magnetic anisotropy and intralayer and interlayer exchange constants, and establish two-dimensional magnets as a new platform for exploring magnon physics.

36 MATERIALS SCIENCE↗

Layer-by-layer disentanglement of Bloch states

Layer-by-layer material engineering has produced interesting quantum phenomena such as interfacial superconductivity and the quantum anomalous Hall effect. However, probing electronic states layer-by-layer remains challenging. This is exemplified by the difficulty in understanding the layer origins of topological electronic states in magnetic topological insulators. In this work, we report a layer-encoded frequency-domain photoemission experiment on the magnetic topological insulator (MnBi 2 Te 4 )(Bi 2 Te 3 ) that characterizes the origins of its electronic states. Infrared laser excitations launch coherent lattice vibrations with the layer index encoded by the vibration frequency. Photoemission spectroscopy then tracks the electron dynamics, where the layer information is carried in the frequency domain. This layer-frequency correspondence reveals wavefunction relocation of the topological surface state from the top magnetic layer into the buried second layer, reconciling the controversy over the vanishing broken-symmetry energy gap in (MnBi 2 Te 4 )(Bi 2 Te 3 ) and its related compounds. The layer-frequency correspondence can be harnessed to disentangle electronic states layer-by-layer in a broad class of van der Waals superlattices.

36 MATERIALS SCIENCE↗

Weyl, Dirac and high-fold chiral fermions in topological quantum matter

Quantum materials hosting Weyl fermions have opened a new era of research in condensed matter physics. First proposed in 1929 in the context of particle physics, Weyl fermions have yet to be observed as elementary particles. In 2015, Weyl fermions were detected as collective electronic excitations in the strong spin–orbit coupled material tantalum arsenide, TaAs. This discovery was followed by a flurry of experimental and theoretical explorations of Weyl phenomena in materials. Weyl materials naturally lend themselves to the exploration of the topological index associated with Weyl fermions and their divergent Berry curvature field, as well as the topological bulk–boundary correspondence, giving rise to protected conducting surface states. Here, we review the broader class of Weyl topological phenomena in materials, starting with the observation of emergent Weyl fermions in the bulk and Fermi arc states on the surface of the TaAs family of crystals by photoemission spectroscopy. We then discuss several exotic optical and magnetic responses observed in these materials, as well as progress in developing related chiral materials. We discuss the conceptual development of high-fold chiral fermions, which generalize Weyl fermions, and we review the observation of high-fold chiral fermion phases by taking the rhodium silicide, RhSi, family of crystals as a prime example. Lastly, we discuss recent advances in Weyl line phases in magnetic topological materials. With this Review, we aim to provide an introduction to the basic concepts underlying Weyl physics in condensed matter, and to representative materials and their electronic structures and topology as revealed by spectroscopic studies. Finally, we hope this work serves as a guide for future theoretical and experimental explorations of chiral fermions and related topological quantum systems with potentially enhanced functionalities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A plant genetic network for preventing dysbiosis in the phyllosphere

The aboveground parts of terrestrial plants, collectively called the phyllosphere, have a key role in the global balance of atmospheric carbon dioxide and oxygen. The phyllosphere represents one of the most abundant habitats for microbiota colonization. Whether and how plants control phyllosphere microbiota to ensure plant health is not well understood. Here we show that the Arabidopsis quadruple mutant (min7 fls2 efr cerk1; hereafter, mfec)1, simultaneously defective in pattern-triggered immunity and the MIN7 vesicle-trafficking pathway, or a constitutively activated cell death1 (cad1) mutant, carrying a S205F mutation in a membrane-attack-complex/perforin (MACPF)-domain protein, harbour altered endophytic phyllosphere microbiota and display leaf-tissue damage associated with dysbiosis. The Shannon diversity index and the relative abundance of Firmicutes were markedly reduced, whereas Proteobacteria were enriched in the mfec and cad1S205F mutants, bearing cross-kingdom resemblance to some aspects of the dysbiosis that occurs in human inflammatory bowel disease. Bacterial community transplantation experiments demonstrated a causal role of a properly assembled leaf bacterial community in phyllosphere health. Here, the pattern-triggered immune signalling, MIN7 and CAD1 are found in major land plant lineages and are probably key components of a genetic network through which terrestrial plants control the level and nurture the diversity of endophytic phyllosphere microbiota for survival and health in a microorganism-rich environment.

59 BASIC BIOLOGICAL SCIENCES↗

Chemical crystallography by serial femtosecond X-ray diffraction

Abstract Inorganic–organic hybrid materials represent a large share of newly reported structures, owing to their simple synthetic routes and customizable properties 1 . This proliferation has led to a characterization bottleneck: many hybrid materials are obligate microcrystals with low symmetry and severe radiation sensitivity, interfering with the standard techniques of single-crystal X-ray diffraction 2,3 and electron microdiffraction 4–11 . Here we demonstrate small-molecule serial femtosecond X-ray crystallography (smSFX) for the determination of material crystal structures from microcrystals. We subjected microcrystalline suspensions to X-ray free-electron laser radiation 12,13 and obtained thousands of randomly oriented diffraction patterns. We determined unit cells by aggregating spot-finding results into high-resolution powder diffractograms. After indexing the sparse serial patterns by a graph theory approach 14 , the resulting datasets can be solved and refined using standard tools for single-crystal diffraction data 15–17 . We describe the ab initio structure solutions of mithrene (AgSePh) 18–20 , thiorene (AgSPh) and tethrene (AgTePh), of which the latter two were previously unknown structures. In thiorene, we identify a geometric change in the silver–silver bonding network that is linked to its divergent optoelectronic properties 20 . We demonstrate that smSFX can be applied as a general technique for structure determination of beam-sensitive microcrystalline materials at near-ambient temperature and pressure.

36 MATERIALS SCIENCE↗

Natural switches in behaviour rapidly modulate hippocampal coding

Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat. Hippocampal CA1 neurons represented the bat’s own position when flying alone (place coding). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast—as fast as 100 ms—which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

60 APPLIED LIFE SCIENCES↗

Shape memory in self-adapting colloidal crystals

We report reconfigurable, mechanically responsive crystalline materials are central components in many sensing, soft robotic, and energy conversion and storage devices1,2,3,4. Crystalline materials can readily deform under various stimuli and the extent of recoverable deformation is highly dependent upon bond type1,2,5,6,7,8,9,10. Indeed, for structures held together via simple electrostatic interactions, minimal deformations are tolerated. By contrast, structures held together by molecular bonds can, in principle, sustain much larger deformations and more easily recover their original configurations. In this report we study the deformation properties of well-faceted colloidal crystals engineered with DNA. These crystals are large in size (greater than 100 µm) and have a body-centred cubic (bcc) structure with a high viscoelastic volume fraction (of more than 97%). Therefore, they can be compressed into irregular shapes with wrinkles and creases, and, notably, these deformed crystals, upon rehydration, assume their initial well-formed crystalline morphology and internal nanoscale order within seconds. For most crystals, such compression and deformation would lead to permanent, irreversible damage. The substantial structural changes to the colloidal crystals are accompanied by notable and reversible optical property changes. For example, whereas the original and structurally recovered crystals exhibit near-perfect (over 98%) broadband absorption in the ultraviolet–visible region, the deformed crystals exhibit significantly increased reflection (up to 50% of incident light at certain wavelengths), mainly because of increases in their refractive index and inhomogeneity.

36 MATERIALS SCIENCE↗

Single-cell, whole-embryo phenotyping of mammalian developmental disorders

Mouse models are a critical tool for studying human diseases, particularly developmental disorders. However, conventional approaches for phenotyping may fail to detect subtle defects throughout the developing mouse. Here we set out to establish single-cell RNA sequencing of the whole embryo as a scalable platform for the systematic phenotyping of mouse genetic models. We applied combinatorial indexing-based single-cell RNA sequencing to profile 101 embryos of 22 mutant and 4 wild-type genotypes at embryonic day 13.5, altogether profiling more than 1.6 million nuclei. The 22 mutants represent a range of anticipated phenotypic severities, from established multisystem disorders to deletions of individual regulatory regions. We developed and applied several analytical frameworks for detecting differences in composition and/or gene expression across 52 cell types or trajectories. Some mutants exhibit changes in dozens of trajectories whereas others exhibit changes in only a few cell types. We also identify differences between widely used wild-type strains, compare phenotyping of gain- versus loss-of-function mutants and characterize deletions of topological associating domain boundaries. Notably, some changes are shared among mutants, suggesting that developmental pleiotropy might be ‘decomposable’ through further scaling of this approach. Overall, our findings show how single-cell profiling of whole embryos can enable the systematic molecular and cellular phenotypic characterization of mouse mutants with unprecedented breadth and resolution.

60 APPLIED LIFE SCIENCES↗

Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine

The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs. Designing precision medicine approaches that incorporate microbial metabolism would require strain- and molecule-resolved, scalable computational modeling. Here, we extend our previous resource of genome-scale metabolic reconstructions of human gut microorganisms with a greatly expanded version. AGORA2 (assembly of gut organisms through reconstruction and analysis, version 2) accounts for 7,302 strains, includes strain-resolved drug degradation and biotransformation capabilities for 98 drugs, and was extensively curated based on comparative genomics and literature searches. The microbial reconstructions performed very well against three independently assembled experimental datasets with an accuracy of 0.72 to 0.84, surpassing other reconstruction resources and predicted known microbial drug transformations with an accuracy of 0.81. We demonstrate that AGORA2 enables personalized, strain-resolved modeling by predicting the drug conversion potential of the gut microbiomes from 616 patients with colorectal cancer and controls, which greatly varied between individuals and correlated with age, sex, body mass index and disease stages. AGORA2 serves as a knowledge base for the human microbiome and paves the way to personalized, predictive analysis of host–microbiome metabolic interactions.

59 BASIC BIOLOGICAL SCIENCES↗

A database of refractive indices and dielectric constants auto-generated using ChemDataExtractor

The ability to auto-generate databases of optical properties holds great potential for advancing optical research, especially with regards to the data-driven discovery of optical materials. An optical property database of refractive indices and dielectric constants is presented, which comprises a total of 49,076 refractive index and 60,804 dielectric constant data records on 11,054 unique chemicals. The database was auto-generated using the state-of-the-art natural language processing software, ChemDataExtractor, using a corpus of 388,461 scientific papers. The data repository offers a representative overview of the information on linear optical properties that resides in scientific papers from the past 30 years. Public availability of these data will enable a quick search for the optical property of certain materials. The large size of this repository will accelerate data-driven research on the design and prediction of optical materials and their properties. To the best of our knowledge, this is the first auto-generated database of optical properties from a large number of scientific papers. We provide a web interface to aid the use of our database.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A high spatial resolution land surface phenology dataset for AmeriFlux and NEON sites

Abstract Vegetation phenology is a key control on water, energy, and carbon fluxes in terrestrial ecosystems. Because vegetation canopies are heterogeneous, spatially explicit information related to seasonality in vegetation activity provides valuable information for studies that use eddy covariance measurements to study ecosystem function and land-atmosphere interactions. Here we present a land surface phenology (LSP) dataset derived at 3 m spatial resolution from PlanetScope imagery across a range of plant functional types and climates in North America. The dataset provides spatially explicit information related to the timing of phenophase changes such as the start, peak, and end of vegetation activity, along with vegetation index metrics and associated quality assurance flags for the growing seasons of 2017–2021 for 10 × 10 km windows centred over 104 eddy covariance towers at AmeriFlux and National Ecological Observatory Network (NEON) sites. These LSP data can be used to analyse processes controlling the seasonality of ecosystem-scale carbon, water, and energy fluxes, to evaluate predictions from land surface models, and to assess satellite-based LSP products.

59 BASIC BIOLOGICAL SCIENCES↗

Crowd cluster data in the USA for analysis of human response to COVID-19 events and policies

We provide data on daily social contact intensity of clusters of people at different types of Points of Interest (POI) by zip code in Florida and California. This data is obtained by aggregating fine-scaled details of interactions of people at the spatial resolution of 10 m, which is then normalized as a social contact index. We also provide the distribution of cluster sizes and average time spent in a cluster by POI type. This data will help researchers perform fine-scaled, privacy-preserving analysis of human interaction patterns to understand the drivers of the COVID-19 epidemic spread and mitigation. Current mobility datasets either provide coarse-level metrics of social distancing, such as radius of gyration at the county or province level, or traffic at a finer scale, neither of which is a direct measure of contacts between people. We use anonymized, de-identified, and privacy-enhanced location-based services (LBS) data from opted-in cell phone apps, suitably reweighted to correct for geographic heterogeneities, and identify clusters of people at non-sensitive public areas to estimate fine-scaled contacts.

60 APPLIED LIFE SCIENCES↗

HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data

Abstract Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km 2 across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems.

Science & Technology - Other Topics↗

A dataset of recorded electricity outages by United States county 2014–2022

In this Data Descriptor, we present county-level electricity outage estimates at 15-minute intervals from 2014 to 2022. By 2022 92% of customers in the 50 US States, Washington DC, and Puerto Rico are represented. These data have been produced by the Environment for Analysis of Geo-Located Energy Information (EAGLE-I TM ), a geographic information system and data visualization platform created at Oak Ridge National Laboratory to map the population experiencing electricity outages every 15 minutes at the county level. Although these data do not cover every US customer, they represent the most comprehensive outage information ever compiled for the United States. The rate of coverage increases through time between 2014 and 2022. We present a quantitative Data Quality Index for these data for the years 2018–2022 to demonstrate temporal changes in customer coverage rates by FEMA region and indicators of data collection gaps or other errors.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Novel Relative Permeability Model for Gas and Water Flow in Hydrate-Bearing Sediments With Laboratory and Field-Scale Application

In a producing gas hydrate reservoir the effective porosity available for fluid flow constantly changes with dissociation of gas hydrate. Therefore, accurate prediction of relative permeability using legacy models (e.g. Brooks-Corey (B-C), van Genuchten, etc.) that were developed for conventional oil and gas reservoirs would require empirical parameters to be calibrated at various S h over its range of variation, but such calibrations are precluded because of lack of experimental relative permeability data. This study proposes a new relative permeability model for gas hydrate-bearing media that is a function of maximum capillary pressure, capillary entry pressure, pore size distribution index, residual saturations, hydrate saturation, and four other constants. The three novel features of the proposed model are: (i) requires fitting its six empirical parameters only once using experimental data from any single S h , and the same set of empirical parameters predict relative permeability at all S h , (ii) includes the effect of capillarity, and (iii) includes the effect of pore-size distribution. From practical standpoint, the model can be used to simulate multiphase flow in gas hydrate-bearing sediments where the proposed relative permeability can account for the evolving hydrate saturation. The proposed model is implemented in a numerical simulator and the wall time required to perform simulations using the proposed model is shown to be similar to the time it takes to run same simulations with the B-C model. The proposed model is a step forward towards achieving the goal of physically accurate modeling of multiphase flow for gas hydrate-bearing sediments that accounts for the effect of gas hydrate saturation change on relative permeability.

54 ENVIRONMENTAL SCIENCES↗

Competing effects of soil fertility and toxicity on tropical greening

Tropical forests are expected to green up with increasing atmospheric CO 2 concentrations, but primary productivity may be limited by soil nutrient availability. However, rarely have canopy-scale measurements been assessed against soil measurements in the tropics. Here, we sought to assess remotely sensed canopy greenness against steep soil nutrient gradients across 50 1-ha mature forest plots in Panama. Contrary to expectations, increases in in situ extractable soil phosphorus (P) and base cations (K, Mg) corresponded to declines in remotely sensed mean annual canopy greenness (r 2 = 0.77– 0.85; p < 0.1), controlling for precipitation. The reason for this inverse relationship appears to be that litterfall also increased with increasing soil P and cation availability (r 2 = 0.88–0.98; p < 0.1), resulting in a decline in greenness with increasing annual litterfall (r 2 = 0.94; p < 0.1). As such, greater soil nutrient availability corresponded to greater leaf turnover, resulting in decreased greenness. However, these decreases in greenness with increasing soil P and cations were countered by increases in greenness with increasing soil nitrogen (N) (r 2 = 0.14; p < 0.1), which had no significant relationship with litterfall, likely reflecting a direct effect of soil N on leaf chlorophyll content, but not on litterfall rates. In addition, greenness increased with extractable soil aluminum (Al) (r 2 = 0.97; p < 0.1), but Al had no significant relationship with litterfall, suggesting a physiological adaptation of plants to high levels of toxic metals. Thus, spatial gradients in canopy greenness are not necessarily positive indicators of soil nutrient scarcity. Using a novel remote sensing index of canopy greenness limitation, we assessed how observed greenness compares with potential greenness. We found a strong relationship with soil N only (r 2 = 0.65; p < 0.1), suggesting that tropical canopy greenness in Panama is predominantly limited by soil N, even if plant productivity (e.g., litterfall) responds to rock-derived nutrients. Moreover, greenness limitation was also significantly correlated with fine root biomass and soil carbon stocks (r 2 = 0.62–0.71; p < 0.1), suggesting a feedback from soil N to canopy greenness to soil carbon storage. Altogether, these data point to the potential utility of a remote sensing product for assessing belowground properties in tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗