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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Comparing Synoptic Pattern Evolution for Flash‐Flood‐Producing and Non‐Flash‐Flood‐Producing Mesoscale Convective Systems in the United States

Understanding how the short-term evolution of synoptic weather patterns influence Mesoscale Convective Systems (MCSs) is essential, as these systems are responsible for over half of central U.S. flash floods, leading to substantial socioeconomic and water resource management impacts. This study analyzes long-term MCS data, flash flood reports, and atmospheric reanalyses from 2007 to 2017 using a machine learning clustering algorithm to examine how the synoptic weather patterns evolve prior to MCS initiation. While the clusters reflect seasonal and regional differences in MCS occurrence, they do not consistently distinguish between MCSs that do and do not produce flash floods. Systems in the southern Great Plains are more flood-prone when a synoptic-scale forcing, located near the system, drives strong water vapor transport from the nearby moisture source. More generally under different synoptic weather patterns, a broader precipitating area is the most dominant factor governing MCS flash flood potential.

atmospheric dynamics↗
DOE OSTI2024

Predicting Fracture Porosity Evolution in Sandstone (Final Report)

To better understand porosity, strength, chemical reactivity, and patterns of fractures, we developed methods using mineral deposits to unravel how fracture growth and diagenesis interact to create and destroy fracture porosity. Quartz and dolomite cement textures and associated fluid inclusion assemblage sequences and thermal histories provided data to infer the duration and rates at which fractures open. We developed and tested a model that accounts for how fracture porosity and rock properties change as a function of thermal exposure and how fracture size and arrangement evolve. Effects of cement deposits on growth were investigated with new geomechanical models and new methods to quantify fracture spatial arrangement. We tested these concepts in a wide range of rock types using outcrop and core-based datasets. We documented opening histories of fractures and fracture arrays in contrasting tectonic and thermal regimes. Our methods set a new standard for fracture characterization and our diagenetic-geomechanical model accurately predicts fluid flow characteristics of fractured rocks based on coupled effects of diagenesis and deformation. Results represent a significant advance in fundamental understanding of fractures in the Earth and have application to improving subsurface engineering operations in a wide range of contexts including geothermal and sequestration applications. The breakthrough of successfully reconstructing the timing and opening rates of parts of single fractures and portions of fracture arrays to document the growth and linkage of fracture arrays was an accomplishment of this grant that is being followed up in our current BES grant DE-SC0022968, ‘Reconstructing and Predicting Fracture Pattern Evolution‘

58 GEOSCIENCES↗
DOE OSTI2021

Comparative phylogenetics of repetitive elements in a diverse order of flowering plants (Brassicales)

Genome sizes of plants have long piqued the interest of researchers due to the vast differences among organisms. However, the mechanisms that drive size differences have yet to be fully understood. Two important contributing factors to genome size are expansions of repetitive elements, such as transposable elements (TEs), and whole-genome duplications (WGD). Although studies have found correlations between genome size and both TE abundance and polyploidy, these studies typically test for these patterns within a genus or species. The plant order Brassicales provides an excellent system to further test if genome size evolution patterns are consistent across larger time scales, as there are numerous WGDs. This order is also home to one of the smallest plant genomes, Arabidopsis thaliana—chosen as the model plant system for this reason—as well as to species with very large genomes. With new methods that allow for TE characterization from low-coverage genome shotgun data and 71 taxa across the Brassicales, we confirm the correlation between genome size and TE content, however, we are unable to reconstruct phylogenetic relationships and do not detect any shift in TE abundance associated with WGD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Strain release through hydrogen bond–mediated layer twisting

Strain engineering, enabling the precise control over structure and functional properties, is a key strategy for the design of advanced materials. However, the mechanisms governing strain evolution and release at the nanoscale remain largely unexplored. In this study, we leverage in situ heating transmission electron microscopy and synchrotron x-ray spectroscopy to investigate the strain relaxation pathways of boehmite (γ-AlOOH) at 575 kelvin by revealing real-time structural dynamics. Through tracking the moiré pattern evolution, we identify distinct strain release mechanisms, including layer twisting, defect formation, and domain restructuring. Our neural network potential calculations reveal that energy fluctuations at small twist angles are dominated by an interference-like interaction modulation of hydrogen bonds between boehmite interlayers, with metastable twisted structures corresponding to local minima of the potential energy landscape. This work establishes a previously unidentified paradigm of two-dimensional layer twisting mediated by hydrogen bonding, offering insights into strain-driven transformation mechanisms, and thus may have broad implications for strain in material and earth sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testisspecific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Interplay of Quantum Size Effect and Tensile Strain on Surface Morphology of β-Sn(100) Islands

The quantum size effect (QSE) and strain effect are two key factors influencing the surface morphology of thin films, which can increase film surface roughness through QSE-induced thickness oscillation and strain-induced island formation, respectively. Surface roughness usually manifests in the early stages of film growth and diminishes beyond a critical thickness. In this work, we employ molecular beam epitaxy (MBE) to grow β-Sn(100) islands with varying thickness N on bilayer graphene-terminated 6H-SiC(0001) substrates. Scanning tunneling microscopy and spectroscopy measurements reveal an inverse surface roughness effect that highlights the interplay of QSE and misfit strain in shaping the surface morphology of β-Sn(100) islands. For N ≤ 10, the islands exhibit flat surfaces, while for N ≥ 26, the island surfaces become corrugated and patterned. For the intermediate range, i.e., 12 ≤ N ≤ 24, both flat and patterned surfaces coexist, with the percentage coverage of the patterned surface oscillating as a function of N. By performing density functional theory calculations, we demonstrate that the unusual surface pattern evolution in our MBE-grown β-Sn(100) islands is a result of the interplay between QSE-induced surface roughing and tensile strain-induced smoothening effect.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

A deep learning-based direct forecasting of CO 2 plume migration

Accurate and timely forecasts of CO 2 plume evolution in geological reservoirs are crucial for CO 2 migration detection, leakage risk assessment, and operation decision support. Conventional forecasting usually adopts a two-step strategy, first calibrating reservoir model parameters against observations using iterative inverse modeling (or history matching) and then applying the calibrated model for predictions. This method impedes real-time forecasts due to the heavy computational demand in inverse modeling and may suffer from poor prediction accuracy because of the limited observation data. In this work, we propose a deep learning-based latent space mapping framework to forecast CO 2 plume migration directly by avoiding the inverse modeling. We first use the convolutional autoencoder to map the high-dimensional complex plume extents onto low-dimensional latent space. Next, we use neural networks to learn the relationship between the observation variables and the prediction latent variables. And then for given observation data, we infer the prediction values directly. This one-step direct forecasting is computationally efficient which requires a few number of parallelizable reservoir simulations and it can provide accurate predictions with limited observations by learning the observation-prediction relationship in the reduced dimension. Therefore, our proposed method enables an in-time forecast of dynamic CO 2 plume distributions. In this work, we demonstrate the effectiveness and accuracy of our method in predicting the CO 2 plume migration using four metrics such as plume area, centroid movement distance, and plume spreading in the primary and secondary directions. And the spatio-temporal evolution patterns of plume migration under diverse geological complexities are also accurately quantified.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Crushing behaviors of unidirectional carbon fiber reinforced plastic composites under dynamic bending and axial crushing loading

The dynamic crushing characteristics of unidirectional carbon fiber reinforced plastic composites under two loading types, dynamic three-point bending and axial crushing, are investigated by experiment and finite element simulation. Hat section samples with two different layup orientations are tested at various impact velocities to investigate its effects. The experiment results show that delamination plays a critical role in dynamic bending deformation. Different layup orientations lead to similar crushing bending behaviors, but remarkable variations in delamination pattern evolutions. In contrast, layup orientation exerts more significant effects on failure modes and energy absorption in axial crushing. A finite element model with multiple layers of thick shell element and cohesive element is established, and simulations are performed for both dynamic three-point bending and axial crushing. The model can capture the crushing behaviors in the two loading types reasonably well. The damage evolution and energy absorption through various mechanisms at different loading conditions are discussed.

42 ENGINEERING↗
DOE OSTI2023

Decoding the flow evolution in Au+Au reactions at 1.23 A GeV using hadron flow correlations and dileptons

We investigate the development of the directed, v 1 , and elliptic flow, v 2 , in heavy ion collisions in mid-central Au+Au reactions at E lab = 1.23A GeV. We demonstrate that the elliptic flow of hot and dense matter is initially positive (v 2 >0) due to the early pressure gradient. This positive v 2 transfers its momentum to the spectators, which leads to the creation of the directed flow v 1 . In turn, the spectator shadowing of the in-plane expansion leads to a preferred decoupling of hadrons in the out-of-plane direction and results in a negative v 2 for the observable final state hadrons. We propose a measurement of v 1 −v 2 flow correlations and of the elliptic flow of dileptons as methods to pin down this evolution pattern. The elliptic flow of the dileptons allows then to determine the early-state EoS more precisely, because it avoids the strong modifications of the momentum distribution due to shadowing seen in the protons. This opens the unique opportunity for the HADES and CBM collaborations to measure the Equation-of-State directly at 2-3 times nuclear saturation density.

Reichert, Tom↗
DOE OSTI2024

Deciphering the Role of Total Water Storage Anomalies in Mediating Regional Flooding

Regional floods result from various flood generation mechanisms. Traditional analyses mainly link flooding to extreme rainfall, with limited input from soil moisture. Total water storage (TWS) is a holistic measure of basin wetness, including additional storage components from surface water, snow, and groundwater. Utilizing a new 5-day Gravity Recovery and Climate Experiment and its Follow On (GRACE(-FO)) data set, we investigated the linkage between short-term TWS anomaly (TWSA) and regional flooding. The 5-day TWSA solutions revealed flood signals missed by monthly TWSA solutions. Global basins exhibit distinct storage-discharge co-evolution patterns, offering new insights into flood mechanisms and propensity. Our bivariate event analyses show the annual maximum river discharges co-occur more often with the TWSA maxima than with precipitation in many basins. Further analyses revealed TWSA's time-lagged effect on river discharge, particularly in basins susceptible to floods triggered by saturation-excess runoff. The 5-day TWSA provides a new source of information for enhancing global flood preparedness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dynamical phase-field model of coupled electronic and structural processes

Abstract Many functional and quantum materials derive their functionality from the responses of both their electronic and lattice subsystems to thermal, electric, and mechanical stimuli or light. Here we propose a dynamical phase-field model for predicting and modeling the dynamics of simultaneous electronic and structural processes and the accompanying mesoscale pattern evolution under static or ultrafast external stimuli. As an illustrative example of application, we study the transient dynamic response of ferroelectric domain walls excited by an ultrafast above-bandgap light pulse. We discover a two-stage relaxational electronic carrier evolution and a structural evolution containing multiple oscillational and relaxational components across picosecond to nanosecond timescales. The phase-field model offers a general theoretical framework which can be applied to a wide range of functional and quantum materials with interactive electronic and lattice orders and phase transitions to understand, predict, and manipulate their ultrafast dynamics and rich mesoscale evolution dynamics of domains, domain walls, and charges.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The GAPS programme at TNG

Neptunes represent one of the main types of exoplanets and have chemical-physical characteristics halfway between rocky and gas giant planets. Therefore, their characterization is important for understanding and constraining both the formation mechanisms and the evolution patterns of planets. We investigate the exoplanet candidate TOI-1422 b, which was discovered by the TESS space telescope around the high proper-motion G2 V star TOI-1422 (V = 10.6 mag), 155 pc away, with the primary goal of confirming its planetary nature and characterising its properties. We monitored TOI-1422 with the HARPS-N spectrograph for 1.5 yr to precisely quantify its radial velocity (RV) variation. We analyse these RV measurements jointly with TESS photometry and check for blended companions through high-spatial resolution images using the AstraLux instrument. We estimate that the parent star has a radius of R$_\star$ = 1.019 -0.013 +0.014 R ⊙ , and a mass of M$_\star$ = 1.019 -0.013 +0.014 M ⊙ . Our analysis confirms the planetary nature of TOI-1422 b and also suggests the presence of a Neptune-mass planet on a more distant orbit, the candidate TOI-1422 c, which is not detected in TESS light curves. The inner planet, TOI-1422 b, orbits on a period of P b = 12.9972 ± 0.0006 days and has an equilibrium temperature of T eq,b = 867 ± 17 K. With a radius of R b = 3.96 -0.11 +0.13 R ⊕ , a mass of M b = 9.0 -2.0 +2.3 M ⊕ and, consequently, a density of ρ b = 0.795 -0.235 +0.290 g cm -3 , it can be considered a warm Neptune-sized planet. Compared to other exoplanets of a similar mass range, TOI-1422 b is among the most inflated, and we expect this planet to have an extensive gaseous envelope that surrounds a core with a mass fraction around 10% – 25% of the total mass of the planet. The outer non-transiting planet candidate, TOI-1422 c, has an orbital period of P c = 29.29 -0.20 +0.21 days, a minimum mass, M c sin i, of 11.1 -2.3 +2.6 M ⊕ , an equilibrium temperature of T eq,c = 661 ± 13 K and, therefore, if confirmed, could be considered as another warm Neptune.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Medium-assisted enhancement of χ c 1 ( 3872 ) production from small to large colliding systems

Studies of exotic hadrons such as the χ c 1 ( 3872 ) state provide crucial insights into the fundamental force governing the strong interaction dynamics, with an emerging frontier to investigate their production in high energy collisions where a partonic medium is present. The latest experimental measurements from the Large Hadron Collider show an intriguing evolution pattern of the χ c 1 ( 3872 ) -to- ψ ( 2 S ) yield ratio from proton-proton collisions with increasing multiplicities toward proton-lead and lead-lead collisions. Here we propose a mechanism of medium-assisted enhancement for the χ c 1 ( 3872 ) production, which competes with the more conventional absorption-induced suppression and results in a nonmonotonic trend from small to large colliding systems. Realistic simulations from this model offer a quantitative description of all available data. Predictions are made for the centrality dependence of this observable in PbPb collisions as well as for its system-size dependence from OO and ArAr to XeXe and PbPb collisions. In both cases, a nonmonotonic behavior emerges as the imprint of the competition between enhancement and suppression and can be readily tested by future data. Published by the American Physical Society 2024

Physics↗
DOE OSTI2023

Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth

In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by molecular beam epitaxy (MBE) and pulsed laser deposition. With the recent development of machine learning (ML), ML-assisted analysis of RHEED videos aids in interpreting the complete RHEED data of oxide thin films. The quantitative analysis of RHEED data allows us to characterize and categorize the growth modes step by step, and extract hidden knowledge of the epitaxial film growth process. In this study, we employed the ML-assisted RHEED analysis method to investigate the growth of 2D thin films of transition metal dichalcogenides (ReSe2) on graphene substrates by MBE. Principal component analysis (PCA) and K-means clustering were used to separate statistically important patterns and visualize the trend of pattern evolution without any notable loss of information. Using the modified PCA, we could monitor the diffraction intensity of solely the ReSe2 layers by filtering out the substrate contribution. These findings demonstrate that ML analysis can be successfully employed to examine and understand the film-growth dynamics of 2D materials. Further, the ML-based method can pave the way for the development of advanced real-time monitoring and autonomous material synthesis techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical “doses” of the HealtheRx shared their information with others (“social doses”). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population (“agents”) using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.

59 BASIC BIOLOGICAL SCIENCES↗