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DOE OSTI2023

Emergence of the Central Atlantic Niño

The Atlantic Niño is characterized by sea surface warming in the equatorial Atlantic, which can trigger La Niña, the cold phase of El Niño–Southern Oscillation (ENSO). Although observations show that the Atlantic Niño has weakened by approximately 30% since the 1970s, its remote influence on ENSO remains strong. Here, we show that this apparent discrepancy is due to the existence of two types of Atlantic Niño with distinct patterns and climatic impacts, which we refer to as the central and eastern Atlantic Niño. Our results show that with equal strength, the central Atlantic Niño has a stronger influence on tropical climate than its eastern counterpart. Meanwhile, the eastern Atlantic Niño has weakened by approximately 50% in recent decades, allowing the central Atlantic Niño to emerge and dominate the remote impact on ENSO. Given the distinct climatic impacts of the two types, it is necessary to distinguish between them and investigate their behaviors and influences on climate in future studies.

Science & Technology - Other Topics↗

NASA NTRS1993

Vector Quantization With Emergent Codebook Structure

Proposed scheme under development for transmission of vector-quantized digital video images, vector quantizer codebook updated to adapt quantizer to changing signal statistics. Intended to be realized with electronic neural network. Codebook, which consists of patterns constituting video images, will undergo training during operation and scheme will develop codebooks ordered during training. System enables coding more compact, more immune to noise, and supports variable rate compression.

Ahalt, Stanley C.↗

DOE OSTI2024

Systematic Underestimation of Canopy Conductance Sensitivity to Drought by Earth System Models

The response of vegetation canopy conductance (g c ) to changes in moisture availability ($γ^{m}_{gc}$) is a major source of uncertainty in climate projections. While vegetation typically reduces stomatal conductance during drought, accurately modeling how and to what degree stomata respond to changes in moisture availability at global scales is particularly challenging, because no global scale g c observations exist. Here, we leverage a collection of satellite, reanalysis and station-based near-surface air and surface temperature estimates, which are physically and statistically linked to $γ^{m}_{gc}$ due to the local cooling effect of g c through transpiration, to develop a novel emergent constraint of $γ^{m}_{gc}$ in an ensemble of Earth System Models (ESMs). We find that ESMs systematically underestimate $γ^{m}_{gc}$ by ~33%, particularly in grasslands, croplands, and savannas in semi-arid and bordering regions of the Central United States, Central Europe, Southeastern South America, Southern Africa, Eastern Australia, and parts of East Asia. We show that this underestimation occurs because ESMs inadequately reduce g c when soil moisture decreases. As g c controls carbon, water and energy fluxes, the misrepresentation of modeled $γ^{m}_{gc}$ contributes to biases in ESM projections of gross primary production, transpiration, and temperature during droughts. Our results suggest that the severity and duration of droughts may be misrepresented in ESMs due to the impact of sustained g c on both soil moisture dynamics and the biosphere-atmosphere feedbacks that affect local temperatures and regional weather patterns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Soft interface instability and gas flow channeling in low-permeability deformable media

Understanding gas percolation through a clay layer or a shale formation is of great importance for the development of a geologic repository for nuclear waste disposal, a subsurface system for gas storage, and an engineering approach for hydrocarbon extraction from unconventional reservoirs. Gas injection experiments have revealed complex dynamic behaviours of gas percolation through water saturated compacted bentonite, characterized by a high breakthrough pressure, rapid breakthrough, a pressure/stress decay after the breakthrough, a relatively high migration rate, high-frequency periodic/nonperiodic variations in flow rate, stepwise rate reductions during relaxation, and low gas saturation over the whole process, all indicating channelling nature of the processes. Using linear stability analyses, we show that this channelling can autonomously emerge from the instability of the deformable interface between the injected gas and the compacted bentonite matrix driven by local stress concentration, pore dilation, and hydrologic gradient. Channel patterns formed would possess a fractal geometry. We further show that, once a percolating channel is established, the gas injected would percolate through the channel in a chain of gas bubbles, also due to the interface instability, resulting in periodic/chaotic variations in gas flow rate. Our work provides a unified explanation for key features observed for gas percolation in low-permeability deformable media. The work also suggests a possibility of designing an engineered barrier system for a nuclear waste repository that can have controllable gas release while limit water transport.

Bentonite↗

DOE OSTI2026

Dissecting Disorder: Defect-Driven Structural Complexity in Layered Li3InCl6 Solid Electrolyte

Halide solid electrolytes have emerged as promising candidates for solid-state batteries owing to their high oxidative stability and ionic conductivity. Among them, Li3InCl6 (LIC) has attracted significant attention. However, diffraction patterns of LIC synthesized via different methods exhibit distinct differences particularly at low-angle reflectionsindicative of underlying structural disorder. These variations are attributed to deviations from ideal crystallographic order, especially stacking faults, whose impact on structure and ion transport remains poorly understood. Here, we identify and quantify stacking faults in LIC samples prepared under different synthetic conditions. Using X-ray diffraction and time-of-flight neutron diffraction, we construct and refine stacking fault models that accurately reproduce the experimental diffraction features. LIC samples with higher degrees of stacking faults exhibit only negligible differences in ionic conductivities and activation energies. This indicates that stacking faults have a limited impact on altering the Li+ diffusion pathway along the c-axis, likely due to the high concentration of vacancies in the In layers, while Li+ diffusion remains nearly unchanged in the ab-plane. Our results account for the observed differences in diffraction patterns across samples and provide a quantitative assessment of faulting probabilities and stacking sequences. The insights gained from this study are expected to be broadly applicable to other layered halide solid electrolytes and contribute to a deeper understanding of the role of structural disorder in ion transport.

Liu, Jue [ORNL] (ORCID:000000024453910X)↗

DOE OSTI2025

Understanding the structural mechanics of ligated DNA crystals via molecular dynamics simulation

DNA self-assembly is a highly programmable method to construct arbitrary architectures based on sequence complementarity. Among various constructs, DNA crystals are macroscopic crystalline materials formed by assembling motifs via sticky end association. Due to their high structural integrity and size ranging from tens to hundreds of micrometers, DNA crystals offer unique opportunities to study the structural properties and deformation behaviors of DNA assemblies. For example, enzymatic ligation of sticky ends can selectively seal nicks resulting in more robust structures with enhanced mechanical properties. However, the research efforts have been mostly on experiments involving different motif designs, structural optimization, or new synthesis methods, while their mechanics are not yet fully understood. The complex properties of DNA crystals are difficult to study via experiments alone, and numerical simulation can complement and aid the experiments. The coarse-grained molecular dynamics (MD) simulation is a powerful tool that can probe the mechanics of DNA assemblies. Here, we investigate DNA crystals made of four different motif lengths with various ligation patterns (full ligation, major directions, connectors, and in-plane) using oxDNA, an open-source, coarse-grained MD platform. We found that several distinct deformation stages emerge in response to mechanical loading and that the number and the location of ligated nucleotides can significantly modulate structural behaviors. These findings should be useful for predicting crystal properties and thus improving the design.

DNA crystal↗

DOE OSTI2024

Structural phase diagram for Sm-substituted BiFeO 3 multiferroics

The structural evolution of Sm substituted BiFe⁢O 3 is studied by total x-ray scattering and structure modeling. It is shown that the crystal structure changes from polar to antipolar and then to nonpolar when the Sm to Bi ratio in the material approaches 20% and 40%, respectively, with no intermixing between the structure types. The evolution is driven by lattice strain induced by the difference in the size of Sm and Bi atoms, leading to changes in the pattern of octahedral tilts and Bi off-centering, which, in turn, induce changes in the multiferroic properties. Furthermore, the substitution ratio at which the different structure types emerge appears to be tied up with the average radius of the atomic species occupying the Bi sites in the perovskite lattice and volume occupied by a formula unit, rendering both quantities useful predictor variables for guiding computational searches for substituted BiFe⁢O 3 multiferroics with improved functional properties.

Ferroelectricity↗

DOE OSTI2021

Direct visualization of magnetic domains and moiré magnetism in twisted 2D magnets

Moiré superlattices of twisted nonmagnetic two-dimensional (2D) materials are highly controllable platforms for the engineering of exotic correlated and topological states. In this work, we report emerging magnetic textures in small-angle twisted 2D magnet chromium triiodide (CrI 3 ). Using single-spin quantum magnetometry, we directly visualized nanoscale magnetic domains and periodic patterns, a signature of moiré magnetism, and measured domain size and magnetization. In twisted bilayer CrI 3 , we observed the coexistence of antiferromagnetic (AFM) and ferromagnetic (FM) domains with disorder-like spatial patterns. In twisted double-trilayer CrI 3 , AFM and FM domains with periodic patterns appear, which is in good agreement with the calculated spatial magnetic structures that arise from the local stacking-dependent interlayer exchange interactions in CrI 3 moiré superlattices. Our results highlight magnetic moiré superlattices as a platform for exploring nanomagnetism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Automatic Differentiation of C++ Codes on Emerging Manycore Architectures with Sacado

Automatic differentiation (AD) is a well-known technique for evaluating analytic derivatives of calculations implemented on a computer, with numerous software tools available for incorporating AD technology into complex applications. However, a growing challenge for AD is the efficient differentiation of parallel computations implemented on emerging manycore computing architectures such as multicore CPUs, GPUs, and accelerators as these devices become more pervasive. In this work, we explore forward mode, operator overloading-based differentiation of C++ codes on these architectures using the widely available Sacado AD software package. In particular, we leverage Kokkos, a C++ tool providing APIs for implementing parallel computations that is portable to a wide variety of emerging architectures. Here we describe the challenges that arise when differentiating code for these architectures using Kokkos, and two approaches for overcoming them that ensure optimal memory access patterns as well as expose additional dimensions of fine-grained parallelism in the derivative calculation. We describe the results of several computational experiments that demonstrate the performance of the approach on a few contemporary CPU and GPU architectures. We then conclude with applications of these techniques to the simulation of discretized systems of partial differential equations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2021

Hybrid phenology matching model for robust crop phenological retrieval

Crop phenology regulates seasonal agroecosystem carbon, water, and energy exchanges, and is a key component in empirical and process-based crop models for simulating biogeochemical cycles of farmlands, assessing gross and net primary production, and forecasting the crop yield. The advances in phenology matching models provide a feasible means to monitor crop phenological progress using remote sensing observations, with a priori information of reference shapes and reference phenological transition dates. Yet the underlying geometrical scaling assumption of models, together with the challenge in defining phenological references, hinders the applicability of phenology matching in crop phenological studies. The objective of this study is to develop a novel hybrid phenology matching model to robustly retrieve a diverse spectrum of crop phenological stages using satellite time series. The devised hybrid model leverages the complementary strengths of phenometric extraction methods and phenology matching models. It relaxes the geometrical scaling assumption and can characterize key phenological stages of crop cycles, ranging from farming practice-relevant stages (e.g., planted and harvested) to crop development stages (e.g., emerged and mature). To systematically evaluate the influence of phenological references on phenology matching, four representative phenological reference scenarios under varying levels of phenological calibrations in terms of time and space are further designed with publicly accessible phenological information. The results indicate that the hybrid phenology matching model can achieve high accuracies for estimating corn and soybean phenological growth stages in Illinois, particularly with the year- and region-adjusted phenological reference (R-squared higher than 0.9 and RMSE less than 5 days for most phenological stages). The inter-annual and regional phenological patterns characterized by the hybrid model correspond well with those in the crop progress reports (CPRs) from the USDA National Agricultural Statistics Service (NASS). Compared to the benchmark phenology matching model, the hybrid model is more robust to the decreasing levels of phenological reference calibrations, and is particularly advantageous in retrieving crop early phenological stages (e.g., planted and emerged stages) when the phenological reference information is limited. This innovative hybrid phenology matching model, together with CPR-enabled phenological reference calibrations, holds 3 considerable promise in revealing spatio-temporal patterns of crop phenology over extended geographical regions.

Phenology↗

DOE OSTI2024

Self-assembled reconfigurable pump architectures via magnetic colloidal swarms

Self-assembled swarms of interactive active units, which are adaptive and dynamically reconfigurable to accommodate different functionalities, represent a promising platform for the development of next-generation robotics. Here, we utilize the emergent collective behavior of active magnetic colloids confined in quasi-two-dimensional arrays of overlapping wells to demonstrate the self-organization of a colloidal swarm into a dynamic pump architecture capable of controlled transport of passive cargo particles. This dynamic architecture provides a global unidirectional looping flow pattern along the entire length of the system. We show that the flow direction of the dynamic swarm-based pump can be externally controlled by a phase shift of a driving magnetic field energizing the swarm. The experimental observations are supported by computational modeling based on phenomenological coarse-grained particle dynamics coupled to shallow-water Navier-Stokes hydrodynamics. In conclusion, our findings demonstrate how the emergent collective behavior of a swarm can be orchestrated into a desired functionality by exploiting the interplay between activity and confinement potentials.

36 MATERIALS SCIENCE↗

NASA NTRS2001

EIT Crinkles as Evidence for the Breakout Model of Solar Eruptions

We present observations of two homologous flares in NOAA active region 8210 occurring on 1998 May 1 and May 2, using EUV data from the Extreme Ultraviolet Radiation Imaging Telescope (EIT) on the Solar and Heliospheric Observatory (SOHO), high-resolution and high-time cadence images from the soft X-ray telescope (SXT) on Yohkoh, images or fluxes from the hard X-ray telescope (HXT) on Yohkoh and the BATSE experiment on the Compton Gamma Ray Observatory (CGRO), and Ca xix soft X-ray spectra from the Bragg crystal spectrometer (BCS) on Yohkoh. Magnetograms indicate that the flares occurred in a complex magnetic topology, consisting of an emerging flux region (EFR) sandwiched between a sunspot to the west and a coronal hole to the east. In an earlier study we found that in EIT images, both flaring episodes showed the formation of a crinkle-like pattern of emission ("EIT crinkles") occurring in the coronal hole vicinity, well away from a central "core field" area near the EFR-sunspot boundary. With our expanded data set, here we find that most of the energetic activity occurs in the core region in both events, with some portions of the core brightening shortly after the onset of the EIT crinkles, and other regions of the core brightening several minutes later, coincident with a burst of hard X-rays: there are no obvious core brightenings prior to the onset of the EIT crinkles. These timings are consistent with the "breakout model" of solar eruptions, whereby the emerging flux is initially constrained by a system of overlying magnetic field lines, and is able to erupt only after an opening develops in the overlying fields as a consequence of magnetic reconnection at a magnetic null point. In our case, the EIT crinkles would be a signature of this pre-impulsive-phase magnetic reconnection, and brightening of the core only occurs after the core fields begin to escape through the newly-created opening in the overlying fields. Morphology in soft X-ray images and properties in hard X-rays differ between the two events, with complexities that preclude a simple determination of the dynamics in the core at the times of eruption. From the BCS spectra, we find that the core region expends energy at a rate of approx. 10(exp 26) erg per second during the time of the growth of the EIT crinkles; this rate is an upper limit to energy expended in the reconnections opening the overlying fields. Energy losses occur at an order-of-magnitude higher rate near the time of the peak of the events. There is little evidence of asymmetry in the spectra, consistent with the majority of the mass flows occurring normal to the line-of-sight. Both events have similar electron temperature dependencies on time.

Sterling, Alphonse C.↗

NASA NTRS2001

EIT Crinkles as Evidence for the Breakout Model of Solar Eruptions

We present observations of two homologous flares in NOAA Active Region 8210 occurring on 1998 May 1 and 2, using EUV data from the EUV Imaging Telescope (EIT) on board the Solar and Heliospheric Observatory, high-resolution and high-time cadence images from the soft X-ray telescope on Yohkoh, images or fluxes from the hard X-ray telescope on Yohkoh and the BATSE experiment on board the Compton Gamma Ray Observatory, and Ca(XIX) soft X-ray spectra from the Bragg crystal spectrometer (BCS) on Yohkoh. Magnetograms indicate that the flares occurred in a complex magnetic topology, consisting of an emerging flux region (EFR) sandwiched between a sunspot to the west and a coronal hole to the east. In an earlier study we found that in EIT images, both flaring episodes showed the formation of a crinkle-like pattern of emission (EIT crinkles) occurring in the coronal hole vicinity, well away from a central 'core field' area near the EFR-sunspot boundary. With our expanded data set, here we find that most of the energetic activity occurs in the core region in both events, with some portions of the core brightening shortly after the onset of the EIT crinkles, and other regions of the core brightening several minutes later, coincident with a burst of hard X-rays; there are no obvious core brightenings prior to the onset of the EIT crinkles. These timings are consistent with the 'breakout model' of solar eruptions, whereby the emerging flux is initially constrained by a system of overlying magnetic field lines, and is able to erupt only after an opening develops in the overlying fields as a consequence of magnetic reconnection at a magnetic null point. In our case, the EIT crinkles would be a signature of this pre-impulsive phase magnetic reconnection, and brightening of the core only occurs after the core fields begin to escape through the newly created opening in the overlying fields. Morphology in soft X-ray images and properties in hard X-rays differ between the two events, with complexities that preclude a simple determination of the dynamics in the core at the times of eruption. From the BCS spectra, we find that the core region expends energy at a rate of approximately 10(exp 26) ergs/s during the time of the growth of the EIT crinkles; this rate is an upper limit to energy expended in the reconnections opening the overlying fields. Energy losses occur at an order of magnitude higher rate near the time of the peak of the events. There is little evidence of asymmetry in the spectra, consistent with the majority of the mass flows occurring normal to the line of sight. Both events have similar electron temperature dependencies on time.

Sterling, Alphonse C.↗

DOE OSTI2023

Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite profiling of single immune and cancer cells in male human tissues by incorporating untargeted spatial metabolomics and targeted multiplexed protein imaging in a single pipeline. We utilized the scSpaMet to profile cell types and spatial metabolomic maps of 19507, 31156, and 8215 single cells in human lung cancer, tonsil, and endometrium tissues, respectively. The scSpaMet analysis revealed cell type-dependent metabolite profiles and local metabolite competition of neighboring single cells in human tissues. Deep learning-based joint embedding revealed unique metabolite states within cell types. Trajectory inference showed metabolic patterns along cell differentiation paths. Here we show scSpaMet’s ability to quantify and visualize the cell-type specific and spatially resolved metabolic-protein mapping as an emerging tool for systems-level understanding of tissue biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

$β$-delayed-neutron studies of 135,136 Sb and 140 I performed with trapped ions

In this work, Beta-delayed-neutron $(βn)$ spectroscopy was performed using the Beta-decay Paul Trap and an array of radiation detectors. The $βn$ branching ratios and energy spectra for 135,136 Sb and 140 I were obtained by measuring the time of flight of recoil ions emerging from the trapped ion cloud. These nuclei are located at the edge of an isotopic region identified as having $βn$ branching ratios that impact the $r$-process abundance pattern around the A ≈ 130 peak. For 135,136 Sb and 140 I, $βn$ branching ratios of 14.6(13)%, 17.6(29)%, and 7.6(28)% were determined, respectively. The $βn$ energy spectra obtained for 135 Sb and 140 I are compared with results from direct neutron measurements, and the $βn$ energy spectrum for 136 Sb has been measured for the first time.

42 ENGINEERING↗

DOE OSTI2023

PRIMED for the Future: Purposing Raw Intake for Machine Learning-Enabled Detection

The COVID-19 pandemic demonstrated how a novel, elusive, and diffuse biological threat can engender uncertainty and misinformation, and it underscored the need for flexible analytical modalities agnostic to the identity of biological material. Yet even before the pandemic recognition of the limitations of the current, list-based approach, which focuses on known pathogens and biotoxins, and of the importance of agent-agnostic biodetection, was growing within the biosecurity community. In a 2018 report on “Biodefense in the Age of Synthetic Biology,” for example, the National Academy of Sciences stated that “an overreliance on the Select Agent List is a systematic weakness affecting many aspects of the United States’ current biodefense mitigation capability." More recently, a group of biodefense researchers proposed the identification and adoption of “bioagent-agnostic signatures (BASs)” as a way of detecting and characterizing not only existing agents but also novel ones, an approach they believe will “enable a more flexible and resilient biodefense posture." Indeed, the future of biodetection requires us to begin developing novel analytics that can identify anomalies and/or characteristics that indicate a potential threat, whether known or unknown, without looking for a specific signature that has been identified previously. To assess potential threats more rapidly, it is critical to develop agnostic artificial intelligence (AI)/machine learning (ML) systems that can be employed for real-time assessment of the nature and source of a perturbation. Such systems should be multiscale and multi-dimensional, integrating sensor data from a range of biological, chemical, and physical application spaces. Emerging deep learning (DL) models demonstrate exceptional promise for identification of discriminatory features within multi-dimensional datasets. DL models have the capacity to recognize and encode highly complex patterns in a wide range of input data modalities, including images, text, and biological/chemical/physical spectra. As such, they can execute a wide range of assessments and determinations that have traditionally required a human operator.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1986

Utilizing remote sensing of Thematic Mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

LANDSAT thematic mapper (TM) data are being used to refine and validate a stochastic spatial computer model to be applied to coastal resource management problems in Louisiana. Two major aspects of the research are: (1) the measurement of area of land (or emergent vegetation) and water and the length of the interface between land and water in TM imagery of selected coastal wetlands (sample marshes); and (2) the comparison of spatial patterns of land and water in the sample marshes of the imagery to that in marshes simulated by a computer model. In addition to activities in these two areas, the potential use of a published autocorrelation statistic is analyzed.

Browder, J. A.↗

NASA NTRS2013

Materials Manufactured from 3D Printed Synthetic Biology Arrays

Many complex, biologically-derived materials have extremely useful properties (think wood or silk), but are unsuitable for space-related applications due to production, manufacturing, or processing limitations. Large-scale ecosystem-based production, such as raising and harvesting trees for wood, is impractical in a self-contained habitat such as a space station or potential Mars colony. Manufacturing requirements, such as the specialized equipment needed to harvest and process cotton, add too much upmass for current launch technology. Cells in nature are already highly specialized for making complex biological materials on a micro scale. We envision combining these strengths with the recently emergent technologies of synthetic biology and 3D printing to create 3D-structured arrays of cells that are bioengineered to secrete different materials in a specified three-dimensional pattern.

Gentry, Diana↗