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At least 793 records · Page 44

Selective sulfidation of metal compounds

There is urgent, unprecedented demand for critical by-product and co-product metallic elements for the infrastructure (magnets, batteries, catalysts and electronics) needed to power society with renewable electricity1,2,3. However, the extraction of d-block and f-block metals from mineral and recycled streams is thermodynamically difficult, typically requiring complete dissolution of the materials, followed by liquid–liquid separation using metal-ion complexing or chelating behaviour4,5. The similar electronic structure of these metals results in poor separation factors, necessitating immense energy, water and chemicals consumption6,7,8. Here a metal-processing approach based on selective anion exchange is proposed. Several simple process levers (gas partial pressure, gas flowrate and carbon addition) are demonstrated to selectively sulfidize a target metal from a mixed metal-oxide feed. The physical and chemical differences between the sulfide and oxide compounds (for example, density, magnetic susceptibility and surface chemistry) can then be exploited for vastly improved separation compared with liquid–liquid methods9. The process conditions of sulfidation are provided for 56 elements and demonstrated for 15 of them. An assessment of the environmental and economic impacts suggests a path towards 60–90% reductions in greenhouse gas emissions while offering substantial capital cost savings compared with liquid–liquid hydrometallurgy.

36 MATERIALS SCIENCE↗

Dynamical topological phase realized in a trapped-ion quantum simulator

Nascent platforms for programmable quantum simulation offer unprecedented access to new regimes of far-from-equilibrium quantum many-body dynamics in almost isolated systems. Here achieving precise control over quantum many-body entanglement is an essential task for quantum sensing and computation. Extensive theoretical work indicates that these capabilities can enable dynamical phases and critical phenomena that show topologically robust methods to create, protect and manipulate quantum entanglement that self-correct against large classes of errors. However, so far, experimental realizations have been confined to classical (non-entangled) symmetry-breaking orders. In this work, we demonstrate an emergent dynamical symmetry-protected topological phase, in a quasiperiodically driven array of ten 171 Yb + hyperfine qubits in Quantinuum’s System Model H1 trapped-ion quantum processor. This phase shows edge qubits that are dynamically protected from control errors, cross-talk and stray fields. Crucially, this edge protection relies purely on emergent dynamical symmetries that are absolutely stable to generic coherent perturbations. Here, this property is special to quasiperiodically driven systems: as we demonstrate, the analogous edge states of a periodically driven qubit array are vulnerable to symmetry-breaking errors and quickly decohere. Our work paves the way for implementation of more complex dynamical topological orders that would enable error-resilient manipulation of quantum information.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A detailed map of Higgs boson interactions by the ATLAS experiment ten years after the discovery

The standard model of particle physics describes the known fundamental particles and forces that make up our Universe, with the exception of gravity. One of the central features of the standard model is a field that permeates all of space and interacts with fundamental particles. The quantum excitation of this field, known as the Higgs field, manifests itself as the Higgs boson, the only fundamental particle with no spin. In 2012, a particle with properties consistent with the Higgs boson of the standard model was observed by the ATLAS and CMS experiments at the Large Hadron Collider at CERN. Since then, more than 30 times as many Higgs bosons have been recorded by the ATLAS experiment, enabling much more precise measurements and new tests of the theory. Here, on the basis of this larger dataset, we combine an unprecedented number of production and decay processes of the Higgs boson to scrutinize its interactions with elementary particles. Interactions with gluons, photons, and W and Z bosons—the carriers of the strong, electromagnetic and weak forces—are studied in detail. Interactions with three third-generation matter particles (bottom (b) and top (t) quarks, and tau leptons (τ)) are well measured and indications of interactions with a second-generation particle (muons, μ) are emerging. These tests reveal that the Higgs boson discovered ten years ago is remarkably consistent with the predictions of the theory and provide stringent constraints on many models of new phenomena beyond the standard model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evidence for Dirac flat band superconductivity enabled by quantum geometry

In a flat band superconductor, the charge carriers’ group velocity v F is extremely slow. Superconductivity therein is particularly intriguing, being related to the long-standing mysteries of high-temperature superconductors and heavy-fermion systems. Yet the emergence of superconductivity in flat bands would appear paradoxical, as a small v F in the conventional Bardeen–Cooper–Schrieffer theory implies vanishing coherence length, superfluid stiffness and critical current. Here, using twisted bilayer graphene, we explore the profound effect of vanishingly small velocity in a superconducting Dirac flat band system. Using Schwinger-limited non-linear transport studies we demonstrate an extremely slow normal state drift velocity v n ≈ 1,000 m s –1 for filling fraction ν between -1/2 and -3/4 of the moiré superlattice. In the superconducting state, the same velocity limit constitutes a new limiting mechanism for the critical current, analogous to a relativistic superfluid. Importantly, our measurement of superfluid stiffness, which controls the superconductor’s electrodynamic response, shows that it is not dominated by the kinetic energy but instead by the interaction-driven superconducting gap, consistent with recent theories on a quantum geometric contribution. Here we find evidence for small Cooper pairs, characteristic of the Bardeen–Cooper–Schrieffer to Bose–Einstein condensation crossover, with an unprecedented ratio of the superconducting transition temperature to the Fermi temperature exceeding unity and discuss how this arises for ultra-strong coupling superconductivity in ultra-flat Dirac bands.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

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↗

Towards linking lab and field lifetimes of perovskite solar cells

Metal halide perovskite solar cells (PSCs) represent a promising low-cost, thin-film photovoltaic (PV) technology, with unprecedented power conversion efficiencies (PCEs) obtained for both single-junction and tandem applications. To push PSCs toward commercialization, it is critical, albeit challenging, to understand device reliability under real-world outdoor conditions where multiple stress factors (e.g., light, heat, humidity) coexist, generating complicated degradation behaviors. It is necessary to identify accelerated indoor testing protocols - which can correlate specific stressors with observed degradation modes in fielded devices - to quickly guide PSC development. Here, we use a state-of-the-art p-i-n PSC stack (with PCE up to ~25.5%) to show that indoor accelerated stability tests can predict our 6-month outdoor aging tests. Device degradation rates under illumination and at elevated temperatures are most instructive for understanding outdoor device reliability. Further, we also find that the indium tin oxide (ITO)/self-assembled monolayer (SAM)-based hole transport layer (HTL)/perovskite interface most strongly affects our device operation stability. Improving the ion-blocking properties of the SAM HTL increases averaged device operational stability at 50 degree C-85 °C by a factor of ~2.8, reaching over 1000 h at 85 °C and to near 8200 h at 50 °C with a projected 20% degradation, which is among the best to date for high-efficiency p-i-n PSCs.

14 SOLAR ENERGY↗

Light-wave-controlled Haldane model in monolayer hexagonal boron nitride

In recent years, the stacking and twisting of atom-thin structures with matching crystal symmetry has provided a unique way to create new superlattice structures in which new properties emerge. In parallel, control over the temporal characteristics of strong light fields has allowed researchers to manipulate coherent electron transport in such atom-thin structures on sublaser-cycle timescales. Here we demonstrate a tailored light-wave-driven analogue to twisted layer stacking. Tailoring the spatial symmetry of the light waveform to that of the lattice of a hexagonal boron nitride monolayer and then twisting this waveform result in optical control of time-reversal symmetry breaking and the realization of the topological Haldane model in a laser-dressed two-dimensional insulating crystal. Further, the parameters of the effective Haldane-type Hamiltonian can be controlled by rotating the light waveform, thus enabling ultrafast switching between band structure configurations and allowing unprecedented control over the magnitude, location and curvature of the bandgap. This results in an asymmetric population between complementary quantum valleys that leads to a measurable valley Hall current, which can be detected by optical harmonic polarimetry. The universality and robustness of our scheme paves the way to valley-selective bandgap engineering on the fly and unlocks the possibility of creating few-femtosecond switches with quantum degrees of freedom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Two-dimensional-lattice-confined single-molecule-like aggregates

Intermolecular distance largely determines the optoelectronic properties of organic matter. Conventional organic luminescent molecules are commonly used either as aggregates or as single molecules that are diluted in a foreigner matrix. They have garnered great research interest in recent decades for a variety of applications, including light-emitting diodes, lasers and quantum technologies, among others. However, there is still a knowledge gap on how these molecules behave between the aggregation and dilution states. Here we report an unprecedented phase of molecular aggregate that forms in a two-dimensional hybrid perovskite superlattice with a near-equilibrium distance, which we refer to as a single-molecule-like aggregate (SMA). By implementing two-dimensional superlattices, the organic emitters are held in proximity, but, surprisingly, remain electronically isolated, thereby resulting in a near-unity photoluminescence quantum yield, akin to that of single molecules. Moreover, the emitters within the perovskite superlattices demonstrate strong alignment and dense packing resembling aggregates, allowing for the observation of robust directional emission, substantially enhanced radiative recombination and efficient lasing. Molecular dynamics simulations together with single-crystal structure analysis emphasize the critical role of the internal rotational and vibrational degrees of freedom of the molecules in the two-dimensional lattice for creating the exclusive SMA phase. Furthermore, this two-dimensional superlattice unifies the paradoxical properties of single molecules and aggregates, thus offering exciting possibilities for advanced spectroscopic and photonic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Copper-dependent halogenase catalyses unactivated C−H bond functionalization

Carbon–hydrogen (C–H) bonds are the foundation of essentially every organic molecule, making them an ideal place to do chemical synthesis. The key challenge is achieving selectivity for one particular C(sp 3 )−H bond. In recent years, metalloenzymes have been found to perform C(sp 3 )−H bond functionalization. Despite substantial progresses in the past two decades, enzymatic halogenation and pseudohalogenation of unactivated C(sp 3 )−H—providing a functional handle for further modification—have been achieved with only non-haem iron/α-ketoglutarate-dependent halogenases, and are therefore limited by the chemistry possible with these enzymes. Here, in this work, we report the discovery and characterization of a previously unknown halogenase ApnU, part of a protein family containing domain of unknown function 3328 (DUF3328). ApnU uses copper in its active site to catalyse iterative chlorinations on multiple unactivated C(sp 3 )−H bonds. By taking advantage of the softer copper centre, we demonstrate that ApnU can catalyse unprecedented enzymatic C(sp 3 )−H bond functionalization such as iodination and thiocyanation. Using biochemical characterization and proteomics analysis, we identified the functional oligomeric state of ApnU as a covalently linked homodimer, which contains three essential pairs—one interchain and two intrachain—of disulfide bonds. The metal-coordination active site in ApnU consists of binuclear type II copper centres, as revealed by electron paramagnetic resonance spectroscopy. This discovery expands the enzymatic capability of C(sp 3 )−H halogenases and provides a foundational understanding of this family of binuclear copper-dependent oxidative enzymes.

biocatalysis↗

Superconducting gap of H 3 S measured by tunnelling spectroscopy

Several hydrogen-rich superconductors have been found to show unprecedentedly high critical temperatures, stimulating investigations into the nature of the superconductivity in these materials. Although their macroscopic superconducting properties are established, microscopic insights into the pairing mechanism remains unclear. Here we characterize the superconducting gap structure in the high-temperature superconductor H 3 S and its deuterium counterpart D 3 S by performing tunnelling spectroscopy measurements. The tunnelling spectra reveal that H 3 S and D 3 S both have a fully gapped structure, which could be well described by a single s-wave Dynes model, with gap values 2Δ of approximately 60 meV and 44 meV, respectively. Furthermore, we observed gap features of another likely H-depleted H x S superconducting phase in a poorly synthesized hydrogen sulfide sample. Our work offers direct experimental evidence for superconductivity in the hydrogen-rich superconductor H 3 S from a microscopic perspective. It validates the phonon-mediated mechanism of superconducting pairing and provides a foundation for further understanding the origins of high-temperature superconductivity in hydrogen-rich compounds.

36 MATERIALS SCIENCE↗

Unconventional solitonic high-temperature superfluorescence from perovskites

Fast thermal dephasing limits macroscopic quantum phenomena to cryogenic conditions and hinders their use at ambient temperatures. For electronic excitations in condensed media, dephasing is mediated by thermal lattice motion. Therefore, taming the lattice influence is essential for creating collective electronic quantum states at high temperatures. Although there are occasional reports of high-T c quantum effects across different platforms, it is unclear which lattice characteristics and electron–lattice interactions lead to macroscopically coherent electronic states in solids. Here we studied intensity fluctuations in the macroscopic polarization during the emergence of superfluorescence in a lead halide perovskite and showed that spontaneously synchronized polaronic lattice oscillations accompany collective electronic dipole emission. We further developed an effective field model and theoretically confirmed that exciton–lattice interactions lead to a new electronically and structurally entangled coherent extended solitonic state beyond a critical polaron density. The analysis shows a phase transition with two processes happening in tandem: incoherent disordered polaronic lattice deformations establish an order, while macroscopic quantum coherence among excitons simultaneously emerges. Recombination of excitons in this state culminates in superfluorescence at high temperatures. Our study establishes fundamental connections between the transient superfluorescence process observed after the impulsive excitation of perovskites and general equilibrium phase transitions achieved by thermal cooling. By identifying various electron–lattice interactions in the perovskite structure and their respective role in creating collectively coherent electronic effects in solids, our work provides unprecedented insight into the design and development of new materials that exhibit high-temperature macroscopic quantum phenomena.

36 MATERIALS SCIENCE↗

A novel bacterial protein family that catalyses nitrous oxide reduction

Nitrous oxide (N 2 O), a driver of global warming and climate change, has reached unprecedented concentrations in Earth’s atmosphere. Current N 2 O sources outpace N 2 O sinks, emphasizing the need for comprehensive understanding of processes that consume N 2 O. Microbes that express the enzyme N 2 O reductase (N 2 OR) convert N 2 O to climate change-neutral dinitrogen (N 2 ). Known N 2 ORs belong to the canonical clade I and clade II NosZ reductases and are considered key enzymes for N 2 O reduction. Here we report a previously unrecognized protein family with a role in N 2 O reduction, clade III lactonase-type N 2 OR (L-N 2 OR), which diverges in sequence from canonical NosZ but conserves three-dimensional protein structural features. Integrated physiological, metagenomic, proteomic and structural modelling studies demonstrate that L-N 2 ORs catalyse N 2 O reduction. L-N 2 OR genes occur in several phyla, predominantly in uncultured taxa with broad geographic distribution. Our findings expand the known diversity of N 2 ORs and implicate previously unrecognized taxa (for example, Nitrospinota) in N 2 O consumption. In conclusion, the expansion of N 2 OR diversity and the identification of a novel type of catalyst for N 2 O reduction advances the understanding of N 2 O sinks, has implications for greenhouse gas emission and climate change modelling, and expands opportunities for innovative biotechnologies aimed at curbing N 2 O emissions.

He, Guang 何广 [Univ. of Tennessee, Knoxville, TN (U↗

Atomic-scale imaging of frequency-dependent phonon anisotropy

Directly visualizing vibrational anisotropy in individual phonon modes is essential for understanding a wide range of intriguing optical, thermal and elastic phenomena in materials. Although conventional optical and diffraction techniques have been used to estimate vibrational anisotropies, they fall short in achieving the spatial and energy resolution necessary to provide detailed information. Here, we introduce a new form of momentum-selective electron energy-loss spectroscopy, which enables the element-resolved imaging of frequency- and symmetry-dependent vibrational anisotropies with atomic resolution. Vibrational anisotropies manifest in different norms of orthogonal atomic displacements, known as thermal ellipsoids. Using the centrosymmetric strontium titanate as a model system, we observed two distinct types of oxygen vibrations with contrasting anisotropies: oblate thermal ellipsoids below 60 meV and prolate ones above 60 meV. In non-centrosymmetric barium titanate, our approach can detect subtle distortions of the oxygen octahedra by observing the unexpected modulation of q-selective signals between apical and equatorial oxygen sites near 55 meV, which originates from reduced crystal symmetry and may also be linked to ferroelectric polarization. These observations are quantitatively supported by theoretical modelling, which demonstrates the reliability of our approach. The measured frequency-dependent vibrational anisotropies shed new light on the dielectric and thermal behaviours governed by acoustic and optical phonons. Furthermore, the ability to visualize phonon eigenvectors at specific crystallographic sites with unprecedented spatial and energy resolution opens new avenues for exploring dielectric, optical, thermal and superconducting properties.

Ferroelectrics and multiferroics↗

High-resolution mapping of spatial heterogeneity in ice wedge polygon geomorphology near Prudhoe Bay, Alaska

It is well known that microtopography associated with ice wedge polygons drives pronounced, meter-scale spatial gradients in hydrologic and ecological processes on the tundra. However, highresolution maps of polygonal geomorphology are rarely available, due to the complexity and subtlety of ice wedge polygon relief at landscape scales. Here we present a sub-meter resolution map of >106 discrete ice wedge polygons across a ~1200 km2 landscape, delineated within a lidar-derived digital elevation model. The delineation procedure relies on a convolutional neural network paired with a set of common image processing operations and permits explicit measurement of relative elevation at the center of each ice wedge polygon. The resulting map visualizes meter- to kilometer-scale spatial gradients in polygonal geomorphology across an extensive landscape with unprecedented detail. This high-resolution inventory of polygonal geomorphology provides rich spatial context for extrapolating observations of environmental processes across the landscape. The map also represents an extensive baseline dataset for quantifying contemporary land surface deformation (i.e., thermokarst) at the survey area, through future topographic surveys.

54 ENVIRONMENTAL SCIENCES↗

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

60 APPLIED LIFE SCIENCES↗

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗

Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001–2020), future mid-term (2041–2060), and future long-term (2081–2100). The datasets were generated from projections of one regional climate model, which were bias-corrected using multiyear observational data for each city. The methodology used makes the datasets among the first to incorporate complex changes in the future climate for the frequency, duration, and magnitude of extreme temperatures. These datasets, created within the IEA EBC Annex 80 “Resilient Cooling for Buildings”, are ready to be used for different types of building adaptation and resilience studies to climate change and heatwaves.

54 ENVIRONMENTAL SCIENCES↗

Coassembly and binning of a twenty-year metagenomic time-series from Lake Mendota

Abstract The North Temperate Lakes Long-Term Ecological Research (NTL-LTER) program has been extensively used to improve understanding of how aquatic ecosystems respond to environmental stressors, climate fluctuations, and human activities. Here, we report on the metagenomes of samples collected between 2000 and 2019 from Lake Mendota, a freshwater eutrophic lake within the NTL-LTER site. We utilized the distributed metagenome assembler MetaHipMer to coassemble over 10 terabases (Tbp) of data from 471 individual Illumina-sequenced metagenomes. A total of 95,523,664 contigs were assembled and binned to generate 1,894 non-redundant metagenome-assembled genomes (MAGs) with ≥50% completeness and ≤10% contamination. Phylogenomic analysis revealed that the MAGs were nearly exclusively bacterial, dominated by Pseudomonadota (Proteobacteria, N = 623) and Bacteroidota (N = 321). Nine eukaryotic MAGs were identified by eukCC with six assigned to the phylum Chlorophyta. Additionally, 6,350 high-quality viral sequences were identified by geNomad with the majority classified in the phylum Uroviricota. This expansive coassembled metagenomic dataset provides an unprecedented foundation to advance understanding of microbial communities in freshwater ecosystems and explore temporal ecosystem dynamics.

59 BASIC BIOLOGICAL SCIENCES↗