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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Elucidating the phase transformations and grain growth behavior of O3-type sodium-ion layered oxide cathode materials during high temperature synthesis

Understanding the formation mechanism of layered oxide cathodes via solid-state synthesis is imperative to achieving controllability over their materials properties and electrochemical behaviors. In this work, we investigate the phase and microstructure evolution during the synthesis of NaNi 1/3 Fe 1/3 Mn 1/3 O 2 , a model sodium-ion layered oxide cathode, using a combination of imaging, diffraction, and spectroscopic techniques. We unravel the synthetic mechanistic pathways involved in the high-temperature calcination reaction, as well as elaborate the synthesis-microstructure-performance relationship of this material. The formation of the final layered oxide phase involves a gradual transformation through a sodiated oxyhydroxide intermediate. During the reaction, the precursor dehydration reaction dominates at 250–550 °C, while the major sodiation reaction occurs at 550–850 °C. Alongside multiple stages of phase transformations, the final grain structure formation occurs through the continuous growth of the (003) and (104) facets. During the reaction, Mn acts as the charge-compensating element and exhibits depth-dependent characteristics. When the sodiation reaction dominates over dehydration, the reaction intermediates undergo gradual electronic structure changes with increasing temperature, as indicated by the spectral features of TM3d-O2p hybrid states. Calcination duration is also a critical parameter governing the microstructure, surface reactivity, phase fraction distribution and electrochemical performance of the material. The optimal calcination duration was determined to be 18 hours at 850 °C under the conditions evaluated here. Calcination beyond this duration was found to be detrimental to electrochemical performance due to Na and O loss and heterogeneous sodium distribution throughout the particles. Our work sheds light on the complex crystallographic-chemical-microstructural evolution of sodium ion layered oxide cathodes and provides insight into precisely tuning material properties which are intimately linked to battery performances.

25 ENERGY STORAGE↗
DOE OSTI2023

Two-dimensional simulations of internal gravity waves in a $\mathrm{5M_⊙}$ zero-age-main-sequence model

Main-sequence intermediate-mass stars present a radiative envelope that supports internal gravity waves (IGWs). Excited at the boundary with the convective core, IGWs propagate towards the stellar surface and are suspected to impact physical processes such as rotation and chemical mixing. Using the fully compressible time-implicit code MUSIC, we study IGWs in two-dimensional simulations of a zero-age-main-sequence 5 solar mass star model up to 91 percent of the stellar radius with different luminosity and radiative diffusivity enhancements. Our results show that low-frequency waves excited by core convection are strongly impacted by radiative effects as they propagate. This impact depends on the radial profile of radiative diffusivity which increases by almost 5 orders of magnitude between the centre of the star and the top of the simulation domain. In the upper layers of the simulation domain, we observe an increase of the temperature. Our study suggests that this is due to heat added in these layers by IGWs damped by radiative diffusion. We show that non-linear effects linked to large amplitude IGWs may be relevant just above the convective core. Both these effects are intensified by the artificial enhancement of the luminosity and radiative diffusivity, with enhancement factors up to 10 4 times the realistic values. Our results also highlight that direct comparison between numerical simulations with enhanced luminosity and observations must be made with caution. Finally, our work suggests that thermal effects linked to the damping of IGWs could have a non-negligible impact on stellar structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quantifying Groundwater Response and Uncertainty in Beaver‐Influenced Mountainous Floodplains Using Machine Learning‐Based Model Calibration

Abstract Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model‐data integration workflow to address uncertainty in groundwater response to beaver‐induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning‐based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down‐valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down‐valley underflow, from 2 during dry pond periods to 20 during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down‐valley underflow, minimizes the effect of beaver‐induced inundation on water quality. We emphasize the need for field‐scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response. Plain Language Summary Beavers change the flow of water in river corridors by creating ponds, expanding wetlands, and flooding floodplains. This increases surface water area, promotes plant growth, and enhances biodiversity. However, the impact of this flooding on groundwater flow is not well understood, especially in mountainous areas with gravel layers where water moves easily beneath soil. In this study, we used numerical modeling to investigate how beaver ponds influence groundwater in a mountainous floodplain of the Upper Colorado River Basin. We adapted a machine learning method to validate our numerical models using multiple field data sets. Our findings show that beaver ponds significantly increase vertical water flow from the soil to the gravel during wet periods, compared to when the ponds are fully drained. The study also highlights the importance of floodplain structure in controlling both water flow in gravel layers along the river direction and vertical flow from the soil to the gravel with the presence of beavers. To reduce uncertainty in groundwater response, we emphasize the need for more field‐scale measurements of floodplain structure, hydraulic properties, and evapotranspiration changes. Key Points Floodplain structures and hydraulic conductivities are important for groundwater response with beaver ponds in mountainous floodplains Large down‐valley underflow in permeability‐stratified floodplains reduces beaver‐induced impacts on groundwater storage and water quality Machine learning‐based model calibration methods are effective for estimating posterior distributions of groundwater model parameters

Wang, Lijing↗
DOE OSTI2025

The chromatin remodeler ADNP regulates neurodevelopmental disorder risk genes and neocortical neurogenesis

Although chromatin remodelers are among the most important risk genes associated with neurodevelopmental disorders (NDDs), the roles of these complexes during brain development are in many cases unclear. Here, we focused on the recently discovered ChAHP chromatin remodeling complex. The zinc finger and homeodomain transcription factor ADNP is a core subunit of this complex, and de novoADNPmutations lead to intellectual disability and autism spectrum disorder. However, germlineAdnpknockout mice were previously shown to exhibit early embryonic lethality, obscuring subsequent roles for the ChAHP complex in neurogenesis. To circumvent this early developmental arrest, we generated a conditionalAdnpmutant allele. Using single-cell transcriptomics, cut&run-seq, and histological approaches, we show that during neocortical development, Adnp orchestrates the production of late-born, upper-layer neurons through a two-step process. First, Adnp is required to sustain progenitor proliferation specifically during the developmental window for upper-layer cortical neurogenesis. Accordingly, we found that Adnp recruits the ChAHP subunit Chd4 to genes associated with progenitor proliferation. Second, in postmitotic differentiated neurons, we define a network of risk genes linked to NDDs that are regulated by Adnp and Chd4. Taken together, these data demonstrate that ChAHP is critical for driving the expansion of upper-layer cortical neurons and for regulating neuronal gene expression programs, suggesting that these processes may potentially contribute to NDD etiology.

Science & Technology - Other Topics↗
DOE OSTI2022

Permafrost Active Layer Microbes From Ny Ålesund, Svalbard (79°N) Show Autotrophic and Heterotrophic Metabolisms With Diverse Carbon-Degrading Enzymes

The active layer of permafrost in Ny Ålesund, Svalbard (79°N) around the Bayelva River in the Leirhaugen glacier moraine is measured as a small net carbon sink at the brink of becoming a carbon source. In many permafrost-dominating ecosystems, microbes in the active layers have been shown to drive organic matter degradation and greenhouse gas production, creating positive feedback on climate change. However, the microbial metabolisms linking the environmental geochemical processes and the populations that perform them have not been fully characterized. In this paper, we present geochemical, enzymatic, and isotopic data paired with 10 Pseudomonas sp. cultures and metagenomic libraries of two active layer soil cores (BPF1 and BPF2) from Ny Ålesund, Svalbard, (79°N). Relative to BPF1, BPF2 had statistically higher C/N ratios (15 ± 1 for BPF1 vs. 29 ± 10 for BPF2; n = 30, p < 10 –5 ), statistically lower organic carbon (2% ± 0.6% for BPF1 vs. 1.6% ± 0.4% for BPF2, p < 0.02), statistically lower nitrogen (0.1% ± 0.03% for BPF1 vs. 0.07% ± 0.02% for BPF2, p < 10 –6 ). The d 13 C values for inorganic carbon did not correlate with those of organic carbon in BPF2, suggesting lower heterotrophic respiration. An increase in the δ 13 C of inorganic carbon with depth either reflects an autotrophic signal or mixing between a heterotrophic source at the surface and a lithotrophic source at depth. Potential enzyme activity of xylosidase and N-acetyl-β-D-glucosaminidase increases twofold at 15°C, relative to 25°C, indicating cold adaptation in the cultures and bulk soil. Potential enzyme activity of leucine aminopeptidase across soils and cultures was two orders of magnitude higher than other tested enzymes, implying that organisms use leucine as a nitrogen and carbon source in this nutrient-limited environment. Besides demonstrating large variability in carbon compositions of permafrost active layer soils only ∼84 m apart, results suggest that the Svalbard active layer microbes are often limited by organic carbon or nitrogen availability and have adaptations to the current environment, and metabolic flexibility to adapt to the warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Environmental sensitivities of shallow-cumulus dilution – Part 2: Vertical wind profile

This second part of a numerical study on shallow-cumulus dilution focuses on the sensitivity of cloud dilution to changes in the vertical wind profile. Insights are obtained through large-eddy simulations of maritime and continental cloud fields. In these simulations, the speed of the initially uniform geostrophic wind and the strength of geostrophic vertical wind shear in the cloud and subcloud layer are varied. Increases in the cloud-layer vertical wind shear (up to 9 ms -1 km -1 ) lead to 40%–50% larger cloud-core dilution rates compared to their respective unsheared counterparts. When the background wind speed, on the other hand, is enhanced by up to 10 ms -1 and subcloud-layer vertical wind shear develops or is initially prescribed, the dilution rate decreases by up to 25%. The sensitivities of the dilution rate are linked to the updraft strength and the properties of the entrained air. Increases in the wind speed or vertical wind shear result in lower vertical velocities across all sets of experiments with stronger reductions in the cloud-layer wind shear simulation (27%–47%). Weaker updrafts are exposed to mixing with the drier surrounding air for a longer time period, allowing more entrainment to occur (i.e., the “core-exposure effect”). However, reduced vertical velocities, in concert with increased cloud-layer turbulence, also assist in widening the humid shell surrounding the cloud cores, leading to entrainment of more humid air (i.e., the “core–shell dilution effect”). In the experiments with cloud-layer vertical wind shear, the core-exposure effect dominates and the cloud-core dilution increases with increasing shear. Conversely, when the wind speed is increased and subcloud-layer vertical wind shear develops or is imposed, the core–shell dilution effect dominates to induce a buffering effect. The sensitivities are generally stronger in the maritime simulations, where weaker sensible heat fluxes lead to narrower, more tilted, and, therefore, more suppressed cumuli when cloud-layer shear is imposed. Moreover, in the experiments with subcloud wind shear, the weaker baseline turbulence in the maritime case allows for a larger turbulence enhancement, resulting in a widening of the transition zones between the cores and their environment, leading to the entrainment of more humid air.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Roles of miR-204 in retinal development and maintenance

Highlights: • miR-204 plays an important role in the development, maintenance, and diseases of the retina. • Various layers of the retina including RPE express miR-204. • Retinoblastoma, age-related macular degeneration, glaucoma and optic nerve injury are among the most common retinopathies caused by miR-204 dysfunction. • miR-204 target genes are involved in diverse signaling pathways crucial for retinal physiology. The retina is the innermost part of the eye of most vertebrates and it is essential for vision. The development, maintenance, and function of this laminated structure is tightly regulated by numerous genes. Deficiencies in the expression of these genes as well as deregulation of various molecular mechanisms can cause retinopathies and blindness. MicroRNAs (miRNAs) are one of the most important and effective molecular regulatory mechanisms that underlie the biology of the retina. miRNAs have specific functional roles in the development and maintenance of different retinal layers and retinal cell types. While previous studies have reported a large number of miRNAs linked to development, maintenance and diseases of the retina, no comprehensive study has properly discussed and integrated data from these studies. Given the particular importance of miR-204 in retinal biology, we intend to critically discuss the expression and functional significance of this miRNA in the development, maintenance, and pathologies of the retina. Moreover, we explore biological processes through which miR-204 influences retinal pathophysiology. This review highlights the crucial functions of miR-204 in the retina and suggests the putative mechanism of miR-204 action in retinal biology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Strain-insensitive intrinsically stretchable transistors and circuits

An all-elastomer strain engineering approach, which uses patterned elastomer layers with tunable stiffnesses, can be used to create intrinsically stretchable transistor arrays with a device density of 340 transistors cm -2 and strain insensitivity of less than 5% performance variation when stretched to 100% strain. Intrinsically stretchable electronics can form intimate interfaces with the human body, creating devices that could be used to monitor physiological signals without constraining movement. However, mechanical strain invariably leads to the degradation of the electronic properties of the devices. Here we show that strain-insensitive intrinsically stretchable transistor arrays can be created using an all-elastomer strain engineering approach, in which the patterned elastomer layers with tunable stiffnesses are incorporated into the transistor structure. By varying the cross-linking density of the elastomers, areas of increased local stiffness are introduced, reducing strain on the active regions of the devices. This approach can be readily incorporated into existing fabrication processes, and we use it to create arrays with a device density of 340 transistors cm -2 and a strain insensitivity of less than 5% performance variation when stretched to 100% strain. We also show that it can be used to fabricate strain-insensitive circuit elements, including NOR gates, ring oscillators and high-gain amplifiers for the stable monitoring of electrophysiological signals.

42 ENGINEERING↗
DOE OSTI2023

Continuous wave room temperature operation of the 2 $μ$m GaSb-based photonic crystal surface emitting diode lasers

Continuous wave room temperature operation of 2 μm GaSb-based photonic-crystal surface-emitting diode lasers has been realized. The deep etched square mesa devices showed threshold current densities of 500 A/cm 2 at 20 °C. The epi-side down mounted lasers generated above 10 mW of output power in the continuous wave regime and tens of milliwatts in pulses from the 200 × 200 μm 2 aperture. Here, the breakthrough in the device performance parameters was achieved thanks to a highly homogeneous air-pocket retaining epitaxial regrowth process optimized for a specifically designed antimonide diode laser heterostructure. The nanofabrication method utilizing low temperature atomic hydrogen surface cleaning yielded low disorder square lattice of droplet-shaped voids covered by uniform p-cladding layer. The laser emission spectrum as well as near/far field patterns demonstrated peculiar features presumably linked to deformation of the void shape during regrowth and formation of the array of filaments.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project. Layers include potential structural setting ellipses, centroids, and distance-to-centroid raster. A submission linking the full GitHub repository for our machine learning Jupyter Notebooks will appear in the related datasets section of this page once available.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗
DOE OSTI2026

Hydrogen defects in LaBi 2 O 4 X (X = Cl, Br, and I) Sillén oxyhalide phases and their impacts on ionic transport

Sillén oxyhalides have recently emerged as promising materials for both photocatalytic and ionic transport applications, yet the role of likely-ubiquitous hydrogen-related defects in these layered compounds remains largely unexplored. Here, we employ first-principles defect calculations to investigate incorporation energetics for hydrogen- and oxygen-related defects, as well as their migration barriers in LaBi 2 O 4 X (X = Cl, Br, I) phases. We find that hydrogen interstitials, particularly protonic species (H i + ), are readily accommodated within the open Bi–O layers. Protons compete with oxygen vacancy donors (V O 2+ ) and charge-compensate with oxygen interstitial acceptors (O i 2− ). By linking hydrogen defect formation to water- and oxygen-related redox equilibria, we reveal that V O 2+ facilitates H i + incorporation, while O i 2− promotes interstitial hydroxide formation, establishing a direct connection between proton and oxide-ion transport. Calculated migration barriers indicate that ionic diffusion is confined to Bi–O layers with low barriers of 0.20–0.25 eV for H i + and 0.14–0.25 eV for V O 2+ , suggesting that the materials contain intrinsic pathways for mixed ionic conduction. These results provide a microscopic picture of hydrogen behavior in Sillén oxyhalides and point to design strategies for integrating protonic and oxide-ion transport in layered oxyhalide electrolytes. Band-edge alignment analysis shows that LaBi 2 O 4 I provides the optimal combination of hydrogen solubility, oxygen defect stability, and mixed ionic conductivity, highlighting its potential for low-temperature electrochemical and energy-conversion applications. Overall, this work establishes the defect-driven origin of hydrogen transport in Sillén oxyhalides and expands their applicability beyond photocatalysis to mixed ionic conduction and hydrogen electrochemistry.

Energy - Conversion↗
DOE OSTI2021

Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Collaboration (FY2020 Final Report)

R2R processing is used to manufacture a wide range of products for various applications which span many industrial business sectors. The overall R2R methodology has been in use for decades and this continuous technique traditionally involves deposition of material(s) onto moving webs, carriers or other continuous belt-fed or conveyor-based processes that enable successive steps to build a final version which serves to support the deposited materials. Established methods that typify R2R processing include tape casting, silk-screen printing, reel-to-reel vacuum deposition/coating, and R2R lithography. Products supported by R2R manufacturing include micro-electronics, electro-chromic window films, PVs, fuel cells for energy conversion, battery electrodes for energy storage, and barrier and membrane materials. Due to innovation in materials and process equipment, high-quality yet very low-cost multilayer technologies have the potential to be manufactured on a very cost-competitive basis. To move energy-related products from high-cost niche applications to the commercial sector, the means must be available to enable manufacture of these products in a cost-competitive manner that is affordable. Fortunately, products such as fuel cells, thin- and mid-film PVs, batteries, electrochromic and piezoelectric films, water separation membranes, and other energy saving technologies readily lend themselves to manufacture using R2R approaches. However, more early-stage research is needed to solve the challenge of linking the materials (particles, polymers, solvents, additives) used in ink and slurry formulations and the coating and drying processes to the ultimate performance of the final R2R product, especially for a process that uses multiple layers of deposition to achieve the end product. To solve the problems associated with these challenges, the R2R Collaboration is executing a research program with outcomes that will ultimately link modeling, processing, metrology and defect detection tools, thereby directly relating the properties of constituent particles and processing conditions to the performance of final devices. This collaborative approach was designed to foster identification and development of materials and processes related to R2R for clean-energy materials development. Using computational and experimental capabilities by acknowledged subject matter experts within the supported National Laboratory system, this project leverages the capabilities and expertise at each of five National Laboratories to further the development of multilayer technologies that will enable high-volume, cost-competitive platforms. A typical R2R process has three steps: (1) mixing of particles and various constituents in a slurry, (2) coating of the ink/slurry mixture on a substrate, and (3) drying/curing and processing of the coating. Final performance of devices made via R2R processes is dependent on the active materials (e.g., electrochemical particles in battery or fuel cell electrodes) and the device structure that stems from the governing component interactions within the various steps. However, a fundamental understanding of the underlying mechanisms and phenomena is still lacking, which is why industrial-scale R2R process development and manufacturing is still largely empirical in nature. The FY 2019 through FY 2021 program addresses aspects of the following two targets from the AMO Multi-Year Program Plan: (1) Target 8.1 Develop technologies to reduce the cost per manufactured throughput of continuous R2R manufacturing processes. (A) Increasing throughput of R2R processes by 5 times for batteries (to 50 square feet per minute (50 ft 2 /min)) and capacitors and 10 times for printed electronics and the manufacture of other substrates and MEs used in support of these products. (B) Developing resolution capabilities to enable registration and alignment that will detect, align, and co-deposit multiple layers of coatings and print < 1-micron (1 µm) features using continuous process scalable for commercial production. (C) Developing scalable and reliable R2R processes for solution deposition of ultra-thin (<10 nm) films for active and passive materials. (D) Develop in-line multilayer coating technology on thin films with yields greater than 95%. (2) Target 8.2 Develop in-line instrumentation tools that will evaluate the quality of single and multilayer materials in-process. (A) Developing in-line QC technologies and methodologies for real-time identification of defects and expected product properties “in-use/application” during continuous processing at all size-scales with a focus on the “micro” and “nano” scale traces, lines, and devices, i.e., <1 μm at 300 ft./min for R2R processing in air and <10 nm at 20 ft./min for vacuum (B) Developing technologies to increase the measurement frequency of surface rheology without significant cost increases with a goal of a 10-nanometer in-line profilometry at a production rate of 100,000 square millimeters per minute (100,000 mm 2 /min).

42 ENGINEERING↗
DOE OSTI2025

Electrical Transport Interplay with Charge Density Waves, Magnetization, and Disorder Tuned by 2D van der Waals Interface Modification via Elemental Intercalation and Substitution in ZrTe 3 , 2H-TaS 2 , and Cr 2 Si 2 Te 6 Crystals

Electrical transport in 2D materials exhibits unique behaviors due to reduced dimensionality, broken symmetries, and quantum confinement. It serves as both a sensitive probe for the emergence of coherent electronic phases and a tool to actively manipulate many-body correlated states. Exploring their interplay and interdependence is crucial but remains underexplored. This review integratively cross-examines the atomic and electronic structures and transport properties of van der Waals-layered crystals ZrTe 3 , 2H-TaS 2 , and Cr 2 Si 2 Te 6 , providing a comprehensive understanding and uncovering new discoveries and insights. A common observation from these crystals is that modifying the atomic and electronic interface structures of 2D van der Waals interfaces using heteroatoms significantly influences the emergence and stability of coherent phases, as well as phase-sensitive transport responses. In ZrTe 3 , substitution and intercalation with Se, Hf, Cu, or Ni at the 2D vdW interface alter phonon–electron coupling, valence states, and the quasi-1D interface Fermi band, affecting the onset of CDW and SC, manifested as resistance upturns and zero-resistance states. We conclude here that these phenomena originate from dopant-induced variations in the lattice spacing of the quasi-1D Te chains of the 2D vdW interface, and propose an unconventional superconducting mechanism driven by valence fluctuations at the van Hove singularity, arising from quasi-1D lattice vibrations. Short-range in-plane electronic heterostructures at the vdW interface of Cr 2 Si 2 Te 6 result in a narrowed band gap. The sharp increase in in-plane resistance is found to be linked to the emergence and development of out-of-plane ferromagnetism. The insertion of 2D magnetic layers such as Mn, Fe, and Co into the vdW gap of 2H-TaS 2 induces anisotropic magnetism and associated transport responses to magnetic transitions. Overall, 2D vdW interface modification offers control over collective electronic behavior, transport properties, and their interplays, advancing fundamental science and nanoelectronic devices.

2D van der Waals interfaces↗
DOE OSTI2022

Crystal structure of diclazuril, C 17 H 9 Cl 3 N 4 O 2

The crystal structure of diclazuril has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Diclazuril crystallizes in space group P2 1 /a (#14) with a = 27.02080(18), b = 11.42308(8), c = 5.36978(5) Å, β = 91.7912(7)°, V = 1656.629(15) Å 3 , and Z = 4. The crystal structure consists of layers of molecules parallel to the ac-plane. A strong N–H∙∙∙O hydrogen bond links the molecules into dimers along the a-axis with a graph set R2,2(8). The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗
DOE OSTI2023

Near-Cloud Atmospheric Ingredients for Deep Convection Initiation

A lack of routine environmental observations located near deepening cumulus congestus clouds limits verification of important theorized and simulated updraft–environment interaction processes occurring during deep convection initiation (CI). We analyze radiosonde profiles collected during several hundred CI events near a mountain range in central Argentina during the CACTI field campaign. Statistical analyses illustrate environmental conditions supporting radar-observed CI outcomes that span a spectrum of convective cell depths, widths, and durations, as well as events lacking precipitating convection. Tested environmental factors include a large variety of sounding-derived measurements of CAPE, CIN, moisture, terrain-relative winds, vertical shear, and lifted parcel properties, with supplemental model reanalysis of background larger-scale vertical motion. CAPE and CIN metrics do not consistently differentiate CI success from failure. Only a few environmental factors contain consistent monotonic relationships among the spectrum of cloud depths achieved during CI: (i) the depth and strength of background ascent, and (ii) the component of low-level flow oriented parallel to the ridgeline. These metrics suggest that the ability of the surrounding flow to lift parcels to their LFC and terrain-modified flow are consistently relevant processes for CI. Low- to midlevel relative humidity strongly discriminated between CI and non-CI events, likely reflecting entrainment-driven dilution processes. However, we could not confidently conclude that relative humidity similarly discriminated robust from marginal CI events. Circumstantial evidence was found linking cell width, an important cloud property governing the probability of CI, to LCL height, boundary layer depth, depth and magnitude of the CIN layer, and ambient wind shear.

Storm environments↗
DOE OSTI2022

Modular power conversion system with galvanic insulation

A modular power conversion system is provided which includes a plurality of building blocks comprised of transformers and power conversion bridges, and a high frequency AC link that transfers power and provides galvanic isolation between the building blocks. The high frequency link includes an insulating tube separating an AC link conductor and the building blocks. The insulating tube is further provided with conductive or semiconductive layers on its inner and outer surfaces for referencing them to the electric potentials of the adjacent conductors and windings, thereby placing the high electric fields substantially directly across the tube and reducing electric fields and partial discharge or corona in the adjoining space or media. The building blocks may be arranged in multiple stacks for DC or AC interface, preferably with neutral or lower voltage connections at the outer edges of the stacks and higher voltage terminals at the centers of the stack.

24 POWER TRANSMISSION AND DISTRIBUTION↗