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At least 1,333 records · Page 74

Anharmonicity and Disorder in the Black Phases of Cesium Lead Iodide Used for Stable Inorganic Perovskite Solar Cells

Hybrid organic–inorganic perovskites emerged as a new generation of absorber materials for high-efficiency low-cost solar cells in 2009. Very recently, fully inorganic perovskite quantum dots also led to promising efficiencies, making them a potentially stable and efficient alternative to their hybrid cousins. Currently, the record efficiency is obtained with CsPbI 3 , whose crystallographical characterization is still limited. Here, we show through high-resolution in situ synchrotron XRD measurements that CsPbI 3 can be undercooled below its transition temperature and temporarily maintained in its perovskite structure down to room temperature, stabilizing a metastable perovskite polytype (black γ-phase) crucial for photovoltaic applications. Our analysis of the structural phase transitions reveals a highly anisotropic evolution of the individual lattice parameters versus temperature. Structural, vibrational, and electronic properties of all the experimentally observed black phases are further inspected based on several theoretical approaches. Whereas the black γ-phase is shown to behave harmonically around equilibrium, for the tetragonal phase, density functional theory reveals the same anharmonic behavior, with a Brillouin zone-centered double-well instability, as for the cubic phase. Using total energy and vibrational entropy calculations, we highlight the competition between all the low-temperature phases of CsPbI 3 (γ, δ, β) and show that avoiding the order–disorder entropy term arising from double-well instabilities is key to preventing the formation of the yellow perovskitoid phase. A symmetry-based tight-binding model, validated by self-consistent GW calculations including spin–orbit coupling, affords further insight into their electronic properties, with evidence of Rashba effect for both cubic and tetragonal phases when using the symmetry-breaking structures obtained through frozen phonon calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scaling of an Atmospheric Model to Simulate Turbulence and Cloud Microphysics in the Pi Chamber

Abstract The Pi Cloud Chamber offers a unique opportunity to study aerosol‐cloud microphysics interactions in a steady‐state, turbulent environment. In this work, an atmospheric large‐eddy simulation (LES) model with spectral bin microphysics is scaled down to simulate these interactions, allowing comparison with experimental results. A simple scalar flux budget model is developed and used to explore the effect of sidewalls on the bulk mixing temperature, water vapor mixing ratio, and supersaturation. The scaled simulation and the simple scalar flux budget model produce comparable bulk mixing scalar values. The LES dynamics results are compared with particle image velocimetry measurements of turbulent kinetic energy, energy dissipation rates, and large‐scale oscillation frequencies from the cloud chamber. These simulated results match quantitatively to experimental results. Finally, with the bin microphysics included the LES is able to simulate steady‐state cloud conditions and broadening of the cloud droplet size distributions with decreasing droplet number concentration, as observed in the experiments. The results further suggest that collision‐coalescence does not contribute significantly to this broadening. This opens a path for further detailed intercomparison of laboratory and simulation results for model validation and exploration of specific physical processes.

54 ENVIRONMENTAL SCIENCES↗

Hysteresis Patterns of Watershed Nitrogen Retention and Loss Over the Past 50 years in United States Hydrological Basins

Patterns of watershed nitrogen (N) retention and loss are shaped by how watershed biogeochemical processes retain, biogeochemically transform, and lose incoming atmospheric deposition of N. Loss patterns represented by concentration, discharge, and their associated stream exports are important indicators of integrated watershed N retention behaviors. We examined continental United States (CONUS) scale N deposition (e.g., wet and dry atmospheric deposition), vegetation trends, and stream trends as potential indicators of watershed N-saturation and retention conditions, and how watershed N retention and losses vary over space and time. By synthesizing changes and modalities in watershed nitrogen loss patterns based on stream data from 2200 U.S. watersheds over a 50 years record, our work revealed two patterns of watershed N-retention and loss. One was a hysteresis pattern that reflects the integrated influence of hydrology, atmospheric inputs, land-use, stream temperature, elevation, and vegetation. The other pattern was a one-way transition to a new state. We found that regions with increasing atmospheric deposition and increasing vegetation health/biomass patterns have the highest N-retention capacity, become increasingly N-saturated over time, and are associated with the strongest declines in stream N exports—a pattern, that is, consistent across all land cover categories. We provide a conceptual model, validated at an unprecedented scale across the CONUS that links instream nitrogen signals to upstream mechanistic landscape processes. Our work can aid in the future interpretation of in-stream concentrations of DOC and DIN as indicators of watershed N-retention status and integrators of watershed hydrobiogeochemical processes.

58 GEOSCIENCES↗

From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers

Abstract Quantitative predictions of natural and induced phenomena in fractured rock is one of the great challenges in the Earth and Energy Sciences with far‐reaching economic and environmental impacts. Fractures occupy a very small volume of a subsurface formation but often dominate fluid flow, solute transport and mechanical deformation behavior. They play a central role in CO 2 sequestration, nuclear waste disposal, hydrogen storage, geothermal energy production, nuclear nonproliferation, and hydrocarbon extraction. These applications require predictions of fracture‐dependent quantities of interest such as CO 2 leakage rate, hydrocarbon production, radionuclide plume migration, and seismicity; to be useful, these predictions must account for uncertainty inherent in subsurface systems. Here, we review recent advances in fractured rock research covering field‐ and laboratory‐scale experimentation, numerical simulations, and uncertainty quantification. We discuss how these have greatly improved the fundamental understanding of fractures and one's ability to predict flow and transport in fractured systems. Dedicated field sites provide quantitative measurements of fracture flow that can be used to identify dominant coupled processes and to validate models. Laboratory‐scale experiments fill critical knowledge gaps by providing direct observations and measurements of fracture geometry and flow under controlled conditions that cannot be obtained in the field. Physics‐based simulation of flow and transport provide a bridge in understanding between controlled simple laboratory experiments and the massively complex field‐scale fracture systems. Finally, we review the use of machine learning‐based emulators to rapidly investigate different fracture property scenarios and accelerate physics‐based models by orders of magnitude to enable uncertainty quantification and near real‐time analysis.

58 GEOSCIENCES↗

Convective and Orographic Origins of the Mesoscale Kinetic Energy Spectrum

The mesoscale spectrum describes the distribution of kinetic energy in the Earth's atmosphere between length scales of 10 and 400 km. Since the first observations, the origins of this spectrum have been controversial. At synoptic scales, the spectrum follows a –3 spectral slope, consistent with two-dimensional turbulence theory, but a shallower –5/3 slope was observed at the shorter mesoscales. The cause of the shallower slope remains obscure, illustrating our lack of understanding. Through a novel coarse-graining methodology, we are able to present a spatio-temporal climatology of the spectral slope. We find convection and orography have a shallowing effect and can quantify this using “conditioned spectra.” These are typical spectra for a meteorological condition, obtained by aggregating spectra where the condition holds. This allows the investigation of new relationships, such as that between energy flux and spectral slope. Potential future applications of our methodology include predictability research and model validation.

54 ENVIRONMENTAL SCIENCES↗

Taxonomic and environmental distribution of bacterial amino acid auxotrophies

Abstract Many microorganisms are auxotrophic—unable to synthesize the compounds they require for growth. With this work, we quantify the prevalence of amino acid auxotrophies across a broad diversity of bacteria and habitats. We predicted the amino acid biosynthetic capabilities of 26,277 unique bacterial genomes spanning 12 phyla using a metabolic pathway model validated with empirical data. Amino acid auxotrophy is widespread across bacterial phyla, but we conservatively estimate that the majority of taxa (78.4%) are able to synthesize all amino acids. Our estimates indicate that amino acid auxotrophies are more prevalent among obligate intracellular parasites and in free-living taxa with genomic attributes characteristic of ‘streamlined’ life history strategies. We predicted the amino acid biosynthetic capabilities of bacterial communities found in 12 unique habitats to investigate environmental associations with auxotrophy, using data compiled from 3813 samples spanning major aquatic, terrestrial, and engineered environments. Auxotrophic taxa were more abundant in host-associated environments (including the human oral cavity and gut) and in fermented food products, with auxotrophic taxa being relatively rare in soil and aquatic systems. Overall, this work contributes to a more complete understanding of amino acid auxotrophy across the bacterial tree of life and the ecological contexts in which auxotrophy can be a successful strategy.

59 BASIC BIOLOGICAL SCIENCES↗

Hierarchical transfer learning: an agile and equitable strategy for machine-learning interatomic models

Machine-learned interatomic models are growing in popularity due to their ability to afford near quantum-accurate predictions for complex phenomena with orders-of-magnitude greater computational efficiency. However, these models struggle when applied to systems of many element types due to the approximately exponential increase in number of parameters that must be determined. To mitigate this challenge, we present a new hierarchical transfer learning approach that allows the fitting problem to be decomposed into smaller independent and reusable parameter blocks that enable development of explicitly chemically extensible ML-IAM. Application of this strategy is demonstrated for C and N mixtures under conditions ranging from nominally ambient to ~10,000 K and 200 GPa for compositions from 0 to 100% N. Ultimately, this strategy makes model generation for chemically complex systems more tractable and efficient, facilitates comprehensive model validation, and makes ML-IAM development for problems of this nature more accessible to users with limited access to extreme computing infrastructure.

Lindsey, Rebecca K. [Univ. of Michigan, Ann Arbor,↗

Electromagnetic levitation containerless processing of metallic materials in microgravity: rapid solidification

Space levitation processing allows researchers to conduct benchmark tests in an effort to understand the physical phenomena involved in rapid solidification processing, including alloy thermodynamics, nucleation and growth, heat and mass transfer, solid/liquid interface dynamics, macro- and microstructural evolution, and defect formation. Supported by ground-based investigations, a major thrust is to develop and refine robust computational tools based on theoretical and applied approaches. This work is accomplished in conjunction with experiments designed for precise model validation with application to a broad range of industrial processes.

42 ENGINEERING↗

Six years of ecosystem-atmosphere greenhouse gas fluxes measured in a sub-boreal forest

Carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) are the greenhouse gases largely responsible for anthropogenic climate change. Natural plant and microbial metabolic processes play a major role in the global atmospheric budget of each. We have been studying ecosystem-atmosphere trace gas exchange at a sub-boreal forest in the northeastern United States for over two decades. Historically our emphasis was on turbulent fluxes of CO 2 and water vapor. In 2012 we embarked on an expanded campaign to also measure CH 4 and N 2 O. Here we present continuous tower-based measurements of the ecosystem-atmosphere exchange of CO 2 and CH 4 , recorded over the period 2012–2018 and reported at a 30-minute time step. Additionally, we describe a five-year (2012–2016) dataset of chamber-based measurements of soil fluxes of CO 2 , CH 4 , and N 2 O (2013–2016 only), conducted each year from May to November. These data can be used for process studies, for biogeochemical and land surface model validation and benchmarking, and for regional-to-global upscaling and budgeting analyses.

54 ENVIRONMENTAL 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↗

In situ melt pool measurements for laser powder bed fusion using multi sensing and correlation analysis

Laser powder bed fusion is a promising technology for local deposition and microstructure control, but it suffers from defects such as delamination and porosity due to the lack of understanding of melt pool dynamics. To study the fundamental behavior of the melt pool, both geometric and thermal sensing with high spatial and temporal resolutions are necessary. This work applies and integrates three advanced sensing technologies: synchrotron X-ray imaging, high-speed IR camera, and high-spatial-resolution IR camera to characterize the evolution of the melt pool shape, keyhole, vapor plume, and thermal evolution in Ti–6Al–4V and 410 stainless steel spot melt cases. Aside from presenting the sensing capability, this paper develops an effective algorithm for high-speed X-ray imaging data to identify melt pool geometries accurately. Preprocessing methods are also implemented for the IR data to estimate the emissivity value and extrapolate the saturated pixels. Quantifications on boundary velocities, melt pool dimensions, thermal gradients, and cooling rates are performed, enabling future comprehensive melt pool dynamics and microstructure analysis. The study discovers a strong correlation between the thermal and X-ray data, demonstrating the feasibility of using relatively cheap IR cameras to predict features that currently can only be captured using costly synchrotron X-ray imaging. Such correlation can be used for future thermal-based melt pool control and model validation.

47 OTHER INSTRUMENTATION↗

Quantifying motion blur by imaging shock front propagation with broadband and narrowband X-ray sources

Time-integrated radiography using MeV Bremsstrahlung X-ray sources is the norm for imaging during system-level testing of components and structures under dynamic condition. One source of error in the analysis of the time-integrated radiography data sets stems from motion blur which smears out sharp interfaces to a greater degree with longer exposure times, which become necessary to provide sufficient signal-to-noise with low X-ray penetration of objects of interest. To quantify motion blur, a 1D shock wave through PMMA was investigated experimentally at The Dynamic Compression Sector at The Advanced Photon Source (DCS@APS) with tapered broadband and 25.46 ± 1.06 keV narrowband X-rays. Four cameras with different exposure times were used for each experiment to compare the effect that exposure time has on motion blur. In addition, our methodology to accurately simulate motion blur in terms of transmission and shape is presented and compared to our experimental results and quantified. There is a high level of agreement between the experimental and simulation results across the range of data sets investigated in this study with a percent difference range of 0.29–1.31% for the four shots. The methodology of this work serves as a steppingstone towards a physically validated model that could be used in conjunction with experimental results to deconvolve physical parameters, densities, and interfaces of interest in a way that would not be possible with experimental results alone.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A multi-ancestry GWAS of Fuchs corneal dystrophy highlights the contributions of laminins, collagen, and endothelial cell regulation

Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular etiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program followed by multi-ancestry meta-analysis with the previous largest FECD GWAS, for a total of 3970 cases and 333,794 controls. We confirm the previous four loci, and identify eight novel loci: SSBP3, THSD7A, LAMB1, PIDD1, RORA, HS3ST3B1, LAMA5, and COL18A1. We further confirm the TCF4 locus in GWAS for admixed African and Hispanic/Latino ancestries and show an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling, validated through homology, suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and colocalization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.

59 BASIC BIOLOGICAL SCIENCES↗

Slippery liquid infused porous surface (SLIPS) condensers for high efficiency air gap membrane distillation

Abstract To address growing water scarcity, we must improve the energy efficiency of thermal desalination technologies such as air gap membrane distillation. However, promising functional materials such as slippery liquid infused porous surfaces have not yet implemented for any desalination technology. Here, we fabricate and test slippery liquid infused porous surfaces (using Krytox 16,256 lubricant and CuO nanostructures) in an air gap membrane distillation apparatus. System-level transport models, validated by experimental data, establish a framework for improving performance through enhanced condensation surfaces. Results are obtained across a range of temperatures (50–80 °C), salinities (5–105 g/kg), and module lengths. We find that small air gap thickness and efficient droplet shedding significantly improves performance. The CuO Krytox process achieves these with a conductive-self-limiting coating, high nanostructure rugosity, strong covalent and metallic bonding, high hydrophobicity, minimal droplet pinning sites, and ultra-low contact angle hysteresis. The greatest efficiency enhancement from SLIPS is derived from the improved droplet shedding, which allows for reduced gap sizes without flooding, and is further augmented by the increased permeate flux.

Yogi, Yashwant S.↗

Resolving Local Configurational Contributions to X-ray and Neutron Radial Distribution Functions Within Solutions of Concentrated Electrolytes – A Case Study of Concentrated NaOH

Extreme conditions of complex materials often lead to a manifold of local environments that challenge characterization and require new advances at the intersection of modern experimental and theoretical techniques. In this contribution, highly caustic and viscous aqueous NaOD solutions were characterized with a combination of X-ray and neutron radial distribution function (RDF) analyses, molecular dynamics simulations and sub-ensemble analysis. The interpretation of the experimental RDFs extends beyond the traditional understanding of atom-pair interactions and to the individual contributions of specific molecular-scale configurations (below 3.5 Å). This integrated approach yields unique insight into the complex and significant breath of ion solvation and pairing structural motifs present, the experimental sensitivity of RDFs to changes in local geometries, and the challenge of experimentally differentiating the ensemble of all superimposed local environments — a feature of increasing importance within the extreme condition of high ionic strength. This study was facilitated by the development of a chemically resistant sample cell for in-situ neutron total scattering measurements of highly caustic materials at elevated temperature and pressure conditions. Advancing these integrated capabilities is critical for ongoing model validation efforts and for extending the predictive capabilities needed for the extremes of chemical composition, aiding a variety of industrial processes that include advanced nuclear waste remediation and metal refining strategies.

Semrouni, David↗

Destructive reverse bias pinning in perovskite/silicon tandem solar modules caused by perovskite hysteresis under dynamic shading

In this work, we demonstrate how perovskite hysteresis can result in permanent reductions in power output in perovskite/silicon tandem modules—including irreversible hotspot-induced damage—from only brief periods of shading. We show that reverse bias events in which a perovskite cell is biased above a threshold voltage—which in this work we find to be as low as –1.1 V—produces a temporary reduction in power output that is of sufficient magnitude to keep the cell pinned in reverse bias after the shading event ends. As a hysteretic phenomena, this crucial failure mode may be overlooked by static models of perovskite-based solar cells. Higher reverse bias voltages exacerbate the temporary reduction in short-circuit photocurrent, which is also sensitive to the level of illumination under reverse bias. Numerical device modelling demonstrates that this effect is consistent with our understanding of perovskite hysteresis as a consequence of mobile ion-electron coupling controlling rates of non-radiative recombination over time. Measurements of the dynamic response of single-junction perovskite cells are extrapolated to two-terminal and four-terminal perovskite/silicon tandem module modelling. We validate these models with measurements from an equivalent electronic circuit that represents a two-terminal perovskite–silicon tandem mini module. Two module-level solutions are discussed that address this issue, which includes increasing the number of bypass diodes and choosing better suited silicon bottom cells with higher shunter resistance in two-terminal tandem modules.

14 SOLAR ENERGY↗

In-situ Experiments to Capture the Evolution of Microstructure During Phase Transformation of Titanium Under Dynamic Loading

Under sufficient stresses, such as during dynamic loading, titanium experiences a phase transformation from hcp alpha phase to hexagonal omega phase. Omega phase is often retained in the microstructure after unloading, and has a strong influence on subsequent mechanical properties. Simulations suggest there are multiple pathways and underlying mechanisms for this transformation. Due to the incredibly short timescales involved, experimental measurements for model validation have been difficult. However, new capabilities at the Advanced Photon Source have enabled diffraction measurements during plate impact experiments to study the evolution of titanium during transformation. These high-rate data allow us to probe the mechanism and kinetics of phase transformations in new ways. Recent results will be presented and compared to post-mortem characterization of soft-recovered shocked specimens. Comparisons are then made with previous tests where material was shock-loaded and soft recovered for microstructural analysis. Together these techniques create a consistent picture of material behavior during the shock-induced α–ω phase transformation in titanium.

36 MATERIALS SCIENCE↗

Predicting Damages to Remainder Parcels in Right-of-Way Acquisitions for Expanding Transportation Infrastructure: Using a Truncated Finite-Mixture Model

Right-of-way acquisition is a critical component of transportation infrastructure development. Transportation infrastructure projects cannot proceed without proper right-of-way acquisition or may face significant delays. State Departments of Transportation frequently acquire parcels of land for roadway expansion projects. A majority of these acquisitions can be partial takings, referring to a portion of a parcel that is acquired. The remainder of the property usually suffers economic changes due to the partial acquisition, which can be calculated as damage percentages. The damage percentage represents the extent to which the remaining land or property value has been diminished due to the acquisition. It reflects the remaining property value percentage that may have been lost or compromised due to the acquisition. Here, this study aims to provide a robust model to estimate damage percentages to the remainder parcels that may help state Departments of Transportation appraisers make early predictions about the damages in cases involving partial takings. The research uses 509 appraisal reports from the Tennessee Department of Transportation to identify the key parcel attributes that influence the percentage of damages. Three regression models are developed: a linear regression model, a finite-mixture model (FMM), and a truncated FMM with two latent classes. The modeling results show that the truncated FMM with two classes outperforms the other models. To validate the models, actual sales data is collected and analyzed for 59 properties, and the results suggest that the model predictions are fairly accurate. A predictive tool is developed based on the models to help appraisers anticipate right-of-way damages under different scenarios and can provide early predictions about the damages.

42 ENGINEERING↗