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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Recent Improvements in the Dart Model for Atmosphere, Topography, Large Landscape, Chlorophyll Fluorescence, Satellite Image Inversion

Physical models simulating the radiative budget (RB) and remote sensing (RS) observation of three-dimensional (3D) landscapes are critical to better understand human and natural components of the Earth system and further develop RS technology. DART is one of the most comprehensive 3D models of Earth-atmosphere optical radiative transfer (RT), from ultraviolet (UV) to thermal infrared (TIR). It simulates the optical signal of proximal, aerial and satellite imaging spectrometers and laser scanners, the 3D RB and solar induced chlorophyll fluorescence (SIF) signal, for any urban or natural landscape and any experimental or instrument configuration. It is freely available for research and teaching activities (https://dart.omp.eu). Here, five recent advances are presented. 1) Atmosphere RT. 2) RT in non repetitive topography. 3) Monte Carlo modelling for fast RS image simulation of large landscapes. 4) SIF modelling for vegetation simulated as facets and turbid cells. 5) RS image inversion for mapping the optical properties of urban material and the urban radiative budget.

DART↗
NASA NTRS2022

Resolving the fine structure in the energy landscapes of repeat proteins

Ankyrin (ANK) repeat proteins are coded by tandem occurrences of patterns with around 33 amino acids. They often mediate protein–protein interactions in a diversity of biological systems. These proteins have an elongated non-globular shape and often display complex folding mechanisms. This work investigates the energy landscape of representative proteins of this class made up of 3, 4 and 6 ANK repeats using the energy-landscape visualisation method (ELViM). By combining biased and unbiased coarse-grained molecular dynamics AWSEM simulations that sample conformations along the folding trajectories with the ELViM structure-based phase space, one finds a three-dimensional representation of the globally funnelled energy surface. In this representation, it is possible to delineate distinct folding pathways. We show that ELViMs can project, in a natural way, the intricacies of the highly dimensional energy landscapes encoded by the highly symmetric ankyrin repeat proteins into useful low-dimensional representations. These projections can discriminate between multiplicities of specific parallel folding mechanisms that otherwise can be hidden in oversimplified depictions.

Murilo N. Sanches↗
DOE OSTI2025

Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing

In this paper, we propose a method to perform empirical analysis of the loss landscape of machine learning (ML) models. The method is applied to two ML models for scientific sensing, which necessitates quantization to be deployed and are subject to noise and perturbations due to experimental conditions. Our method allows assessing the robustness of ML models to such effects as a function of quantization precision and under different regularization techniques -- two crucial concerns that remained underexplored so far. By investigating the interplay between performance, efficiency, and robustness by means of loss landscape analysis, we both established a strong correlation between gently-shaped landscapes and robustness to input and weight perturbations and observed other intriguing and non-obvious phenomena. Our method allows a systematic exploration of such trade-offs a priori, i.e., without training and testing multiple models, leading to more efficient development workflows. This work also highlights the importance of incorporating robustness into the Pareto optimization of ML models, enabling more reliable and adaptive scientific sensing systems.

Baldi, Tommaso [Pisa, Scuola Normale Superiore]↗
NASA NTRS2013

Constraining Landscape History and Glacial Erosivity Using Paired Cosmogenic Nuclides in Upernavik, Northwest Greenland

High-latitude landscape evolution processes have the potential to preserve old, relict surfaces through burial by cold-based, nonerosive glacial ice. To investigate landscape history and age in the high Arctic, we analyzed in situ cosmogenic Be(sup 10) and Al (sup 26) in 33 rocks from Upernavik, northwest Greenland. We sampled adjacent bedrock-boulder pairs along a 100 km transect at elevations up to 1000 m above sea level. Bedrock samples gave significantly older apparent exposure ages than corresponding boulder samples, and minimum limiting ages increased with elevation. Two-isotope calculations Al(sup26)/B(sup 10) on 20 of the 33 samples yielded minimum limiting exposure durations up to 112 k.y., minimum limiting burial durations up to 900 k.y., and minimum limiting total histories up to 990 k.y. The prevalence of BE(sup 10) and Al(sup 26) inherited from previous periods of exposure, especially in bedrock samples at high elevation, indicates that these areas record long and complex surface exposure histories, including significant periods of burial with little subglacial erosion. The long total histories suggest that these high elevation surfaces were largely preserved beneath cold-based, nonerosive ice or snowfields for at least the latter half of the Quaternary. Because of high concentrations of inherited nuclides, only the six youngest boulder samples appear to record the timing of ice retreat. These six samples suggest deglaciation of the Upernavik coast at 11.3 +/- 0.5 ka (average +/- 1 standard deviation). There is no difference in deglaciation age along the 100 km sample transect, indicating that the ice-marginal position retreated rapidly at rates of approx.120 m yr(sup−1).

glacial↗
DOE OSTI2026

Characterization of the biofilm landscape of Bacillus subtilis by spatial microproteomics

Bulk proteomics has been demonstrated to differentiate subpopulations within bacterial colonies, yet advanced analyses by mass spectrometry imaging (MSI) hold even greater promise for the future. This technology can enable high-throughput spatial phenotyping that can reshape biological discovery by providing visualization of components of various biomolecular mechanisms. With high mass resolving power and high spatial resolution analyses being routine, we can confidently enable intact protein imaging directly from samples with minimal preparation. Pairing those analyses with bulk experimental libraries can provide high confidence in annotations of post-translational modifications (PTMs) and truncations. Revealing PTM localization within the samples unlocks a direct window into unknown biology at the microscale. However, top-down proteomics (TDP) is not commonplace for microbial species, largely due to challenges in identifying detected peptides and proteins; considering the theoretical proteome of even the well-studied model bacterium Bacillus subtilis was only partially mapped recently. With little still known about the form and function of many of these proteins – let alone proteoforms, where PTMs and truncations of the same protein may possess unique physiological roles – there is a wealth of work to be done. Here we jointly apply TDP and MSI to describe the microscale spatial proteomic landscape within B. subtilis and further demonstrate the feasibility of detecting differentiated subpopulations through proteoforms across the biofilm landscape.

bacterial biofilms↗
DOE OSTI2025

Urban morphology from a landscape perspective: How building morphology distribution land models (BMDLM) emulate pattern and process

Urban form (e.g., building morphology such as height or footprint) can be used to predict environmental footprints, such as energy/water consumption and carbon emissions. Although progress has been made in predicting building characteristics to fill gaps in observation or derive 3-D representations, the relationships between morphology and other variables such as land use and population are poorly understood. Understanding these relationships may enable projections for how cities will evolve with landscapes in the future. A suite of random forest models, the Building Morphology Distribution Land Models (BMDLM), was developed to determine how well building morphology for two distinct statistical measures (central tendency and frequency) can be predicted using land use (e.g., zoning) and population at different resolutions. Clark County, Nevada and Los Angeles County, California are explored as case studies. Generally, 1-km models outperformed 30-m models. Frequency distribution models had the best performance, especially in LA County. Frequency models significantly outperformed spatial autocorrelative models using inverse distance weighting (IDW). BMDLM offers a new take on modeling urban form in which generalized landscape patterns are characterized to understand the influence of population and zoning on urban development, as described by urban scaling theory.

Sturtevant, Jillian [Baylor Univ., Waco, TX (Unite↗
DOE OSTI2026

SMEFT ATLAS: The landscape beyond the Standard Model

The Standard Model Effective Field Theory (SMEFT) based on the unbroken gauge group SU(3) 𝐶 ⊗SU(2) 𝐿 ⊗U(1) 𝑌 and containing only particles of the Standard Model (SM) has developed in the last decade to a mature field. It is the framework to be used in the energy gap from scales sufficiently higher than the electroweak scale up to the lowest energy scale at which new particles show up. We summarize the present status of this theory with a particular emphasize on its role in the indirect search for new physics (NP). While flavour physics of both quarks and leptons is the main topic of our review, we also discuss electric dipole moments, anomalous magnetic moments (𝑔−2) 𝜇,𝑒 , 𝑍-pole observables, Higgs observables and high-𝑝𝑇 scattering processes within the SMEFT. We group the observables into ten classes and list for each class the most relevant operators and the corresponding renormalization group equations (RGEs). We exhibit the correlations between different classes implied both by the operator mixing and the SU(2) 𝐿 gauge symmetry. Our main goal is to provide an insight into the complicated operator structure of this framework which hopefully will facilitate the identification of valid ultraviolet completions behind possible anomalies observed in future data. Numerous colourful charts, and 85 tables, while representing rather complicated RG evolution from the NP scale down to the electroweak scale, beautify the involved SMEFT landscape. Over 1000 references to the literature underline the importance and the popularity of this field. We discuss both top-down and bottom-up approaches as well as their interplay. This allows us eventually to present an atlas of different landscapes beyond the SM that includes heavy gauge bosons and scalars, vector-like quarks and leptons and leptoquarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape

Arctic warming is altering vegetation and carbon dynamics with global implications, yet Earth System Model (ESM) predictions in the Arctic remain highly uncertain, in part due to historically limited data for model parameterization and validation. As such, ESMs typically represent Arctic ecosystems in an oversimplified manner. Recently, nine plant functional types (PFTs) designed to realistically represent tundra vegetation were integrated into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) and parameterized using plot-scale observations from a single site. Additional evaluation was needed to determine their transferability across the Arctic. Here, in this study, we evaluated whether refined representation of tundra vegetation improved model accuracy by conducting spatially explicit 100 × 100 m resolution ELM simulations on Alaska's Seward Peninsula. Simulations with the default two-PFT configuration and with the nine Arctic-specific PFTs were benchmarked against observations of net ecosystem exchange, gross primary production, and aboveground biomass from multiple data streams including an eddy covariance flux tower, flux chambers, and aircraft and unoccupied aerial system hyperspectral remote sensing. Evaluation revealed that Arctic-specific PFT simulations produced more realistic landscape-level carbon exchanges, and better captured observed heterogeneity in biomass and productivity, explaining 60%–70% of spatial variance (R 2 = 0.6–0.7) compared to just 12%–18% (R 2 = 0.12–0.18) with the default configuration. However, the refined model failed to reproduce observed aboveground biomass for highly productive alder-willow communities, requiring further evaluation of carbon allocation parameterizations for tall shrubs that are increasingly expanding across tundra landscapes. Our results demonstrate that enhanced representation of vegetation heterogeneity boosts predictive understanding of tundra carbon dynamics, facilitating regional to pan-Arctic model and remote-sensing scaling.

Murphy, Bailey A. [Oak Ridge National Laboratory (↗
DOE OSTI2024

Metadynamics investigation of lanthanide solvation free energy landscapes and insights into separations energetics

Lanthanide ion solvation chemistry in nonaqueous phases is key to understanding and developing effective separation processes for these critical materials. Due to the complexity and inherent disorder of the solution phase, a comprehensive picture of the solvated metal ion is often difficult to generate solely from conventional spectroscopic approaches and electronic structure calculations, particularly in the extractant phase. In this work, we use classical molecular dynamics (MD) simulation with an advanced sampling technique, metadynamics, supplemented by experimental spectroscopy and speciation analysis, to measure lanthanide solvation free energy landscapes. We define coordination-based collective variables to probe the entire range of solvation configurations in the organic phase of lanthanum (La), europium (Eu), and lutetium (Lu) nitrate salts bound with a commonly used extractant, N,N′-dimethyl, N,N′-dioctylhexylethoxymalonamide (DMDOHEMA). The known lanthanide extraction trend of La ≈ Eu > Lu is readily explained by the measured free energy surfaces, which show consistent DMDOHEMA coordination from La to Eu, followed by loss of DMDOHEMA coordination from Eu to Lu. These simulations suggest how ligand crowding at the metal center can control selectivity, in this case resulting in the opposite extraction trend as observed with other conventional extractants, where the enthalpic contribution from increasing lanthanide charge density across the series dominates the extraction energetics. We also find that the presence of inner-sphere water, verified by time-resolved fluorescence, diversifies the accessible solvation structures. As a result, understanding solvation requires consideration of an entire thermodynamic ensemble, rather than the single dominant lowest-energy structure, as is often considered out of necessity in interpretation of spectroscopic data or in electronic structure-based ligand design approaches. In general, we demonstrate how metadynamics uniquely enables investigation of complex, multidimensional solvation energetic landscapes, and how it can explain selectivity trends where extraction is controlled by more complex mechanisms than simple charge density-based selectivity.

Wang, Xiaoyu↗
DOE OSTI2025

Exploring the energy landscape of RBMs: reciprocal space insights into bosons, hierarchical learning and symmetry breaking

Deep generative models have become ubiquitous due to their ability to learn and sample from complex distributions. Despite the proliferation of various frameworks, the relationships among these models remain largely unexplored, a gap that hinders the development of a unified theory of AI learning. In this work, we address two central challenges: clarifying the connections between different deep generative models and deepening our understanding of their learning mechanisms. We focus on Restricted Boltzmann Machines (RBMs), a class of generative models known for their universal approximation capabilities for discrete distributions. By introducing a reciprocal space formulation for RBMs, we reveal a connection between these models, diffusion processes, and systems of coupled bosons. Our analysis shows that at initialization, the RBM operates at a saddle point, where the local curvature is determined by the singular values of the weight matrix, whose distribution follows the Marc̆enko-Pastur law and exhibits rotational symmetry. During training, this rotational symmetry is broken due to hierarchical learning, where different degrees of freedom progressively capture features at multiple levels of abstraction. This leads to a symmetry breaking in the energy landscape, reminiscent of Landau’s theory. This symmetry breaking in the energy landscape is characterized by the singular values and the weight matrix eigenvector matrix. We derive the corresponding free energy in a mean-field approximation. We show that in the limit of infinite size RBM, the reciprocal variables are Gaussian distributed. Our findings indicate that in this regime, there will be some modes for which the diffusion process will not converge to the Boltzmann distribution. To illustrate our results, we trained replicas of RBMs with different hidden layer sizes using the MNIST dataset. Our findings not only bridge the gap between disparate generative frameworks but also shed light on the fundamental processes underpinning learning in deep generative models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Landscape of 4d N = 1 SCFTs with a = c

We study a landscape of four-dimensional N = 1 superconformal field theories (SCFTs) with identical central charges. These theories are obtained by renormalization group flows triggered by supersymmetry-preserving superpotential deformations of the N = 1 gauging of the flavor symmetry of a collection of N = 2 D p ( G ) Argyres-Douglas SCFTs. In this work, we focus on the fixed points in the landscape of the S U ( 3 ) gauging of three copies of the D 2 ( S U ( 3 ) ) = H 2 theory together with an adjoint-valued chiral multiplet. We catalog the network of a = c fixed points, and, along the way, we find a variety of dualities and instances of supersymmetry enhancement. Published by the American Physical Society 2025

Kang, Monica Jinwoo (ORCID:0000000204542064)↗
DOE OSTI2025

Diurnal urban rainfall anomalies across different landscapes

Urbanization influences regional climates and extreme weather. While previous research has documented urban-induced precipitation for specific cities or storm cases, diurnal urban precipitation anomalies across different landscapes remain poorly understood. Analyzing diurnal and seasonal variations of urban precipitation anomalies across 175 US cities, we found strong urban effects on precipitation especially during summer afternoons. Large, inland cities can receive 10% more summer afternoon rainfall, and the pattern varies with urban heat islands and wind conditions. Coastal cities, under the influence of sea-land breeze, experience three times amplified daily urban precipitation enhancements than inland cities. Urban impacts are also noted for mountain cities, affecting their topography-dominated precipitation patterns. With increasing thresholds of extreme precipitation, most US cities experience more intense rainfall compared to their rural backgrounds. This study enhances our understanding of hitherto poorly documented diurnal aspects of urban rainfall through geographically distributed, landscape-specific rainfall anomalies.

Science & Technology - Other Topics↗
DOE OSTI2024

Feedbacks Regulating the Salinization of Coastal Landscapes

The impact of saltwater intrusion on coastal forests and farmland is typically understood as sea-level-driven inundation of a static terrestrial landscape, where ecosystems neither adapt to nor influence saltwater intrusion. Yet recent observations of tree mortality and reduced crop yields have inspired new process-based research into the hydrologic, geomorphic, biotic, and anthropogenic mechanisms involved. We review several negative feedbacks that help stabilize ecosystems in the early stages of salinity stress (e.g., reduced water use and resource competition in surviving trees, soil accretion, and farmland management). However, processes that reduce salinity are often accompanied by increases in hypoxia and other changes that may amplify saltwater intrusion and vegetation shifts after a threshold is exceeded (e.g., subsidence following tree root mortality). This conceptual framework helps explain observed rates of vegetation change that are less than predicted for a static landscape while recognizing the inevitability of large-scale change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Magnesium ions mitigate metastable states in the regulatory landscape of mRNA elements

Residing in the 5' untranslated region of the mRNA, the 2'-deoxyguanosine (2'-dG) riboswitch mRNA element adopts an alternative structure upon binding of the 2'-dG molecule, which terminates transcription. RNA conformations are generally strongly affected by positively charged metal ions (especially Mg 2+ ). We have quantitatively explored the combined effect of ligand (2'-dG) and Mg 2+ binding on the energy landscape of the aptamer domain of the 2'-dG riboswitch with both explicit solvent all-atom molecular dynamics simulations (99 μsec aggregate sampling for the study) and selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) experiments. We show that both ligand and Mg 2+ are required for the stabilization of the aptamer domain; however, the two factors act with different modalities. The addition of Mg 2+ remodels the energy landscape and reduces its frustration by the formation of additional contacts. In contrast, the binding of 2'-dG eliminates the metastable states by nucleating a compact core for the aptamer domain. Mg 2+ ions and ligand binding are required to stabilize the least stable helix, P1 (which needs to unfold to activate the transcription platform), and the riboswitch core formed by the backbone of the P2 and P3 helices. Mg 2+ and ligand also facilitate a more compact structure in the three-way junction region.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Landscape of Cross-Laminated Timber in the United States

Mass timber construction is an emerging sustainable construction practice in the United States given its renewable nature and its ability to store carbon during its use. Cross-laminated timber (CLT) is a type of mass timber construction that involves a wood panel system that is manufactured by gluing alternating lumber board layers at right angles. CLT panels have high strength, dimensional stability, and the ability to resist high compressive forces. They are considered a sustainable alternative to reinforced concrete construction because of the renewable nature of the primary wood material in CLT panels. Despite its environmental and structural benefits, the adoption rate of CLT remains low. This report investigates the current landscape of CLT use in buildings, providing information on the types of building that use CLT, how those buildings are used, and in what U.S. regions CLT is manufactured and used. This information helps identify potential barriers to adoption to inform ways to reduce these barriers. This review synthesizes insights from recent studies to offer a detailed perspective on the state of CLT adoption, its barriers, and the evolving landscape of opportunities that may facilitate its broader acceptance and use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Editorial: Transcriptional and epigenetic landscapes of abiotic stress response in plants

In nature, plants constantly face various biotic and abiotic stresses that impact their growth, development, and productivity. Among these, abiotic stresses often have a more severe impact than biotic stresses. For instance, drought has been reported to cause greater yield losses than the combined impact of all plant pathogens (Gupta et al., 2020). Abiotic stresses are the immediate outcome of climate change, and the magnitude of these stresses has gradually increased every year with the rise in global temperatures. Thus, it has become imperative to study the impact of these stresses on plants and how plants respond to them at different levels to show resilient traits. This includes analysing the plants at morpho-physiological, biochemical, and molecular levels. Researchers often compare stressed plants to control (non-stressed) plants or evaluate contrasting genotypes, such as tolerant and sensitive lines, to elucidate the mechanisms underlying stress responses. While these studies have provided some insights, a comprehensive understanding of the intricate mechanisms governing plant responses to abiotic stress remains largely unknown. Recent advances in next-generation tools and technologies have enabled researchers to dissect the molecular basis of plant stress responses at genomic, transcriptomic, proteomic, metabolomic, epigenetic and epigenomic levels. Among these, knowledge of the transcriptional/epigenomic landscape of the trait-associated variations is limited. Given the importance of transcriptional changes and histone modifications in abiotic stress responses, this Research Topic was edited to collage the knowledge available on transcriptional and epigenetic landscapes of abiotic stress response in plants. The Research Topic features eight original research articles and one review, covering various aspects of transcriptome and epigenetic reprogramming in plants during abiotic stresses. Four of the research articles employ transcriptomics integrated with other omics approaches to explore transcriptome reprogramming, candidate gene identification, and the role of long non-coding RNA during different stresses. Two articles focus on the functional characterization of specific candidate genes involved in stress response, while another provides a genome-wide analysis of a stress-responsive gene family. Additionally, one study investigates genome-wide histone modifications, specifically H3K4me3 and H3K27me3, in response to abiotic stresses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Holographic Constraints on the String Landscape

We show that holography imposes strong and general constraints on scalar field potentials in the string landscape, determined by the asymptotic structure of the underlying spacetime. Applying these holographic consistency conditions, we identify broad classes of scalar potentials that are incompatible with a well-defined dual description. These include potentials with extended plateaus, excessively steep or shallow asymptotics, certain zero crossings, and specific alignments of stable AdS minima in moduli space. In particular, making the standard assumption that the CFT dual to a stable AdS vacuum must be realized as a worldvolume theory of a brane in string theory, we show that the brane selects an infinite-distance limit in moduli space where parametric scale separation is forbidden. Furthermore, the steepness and positivity of the potential are restricted in that infinite distance direction. We also find that requiring the validity of the effective theory in the future vacuum, a natural holographic criterion, automatically enforces the Trans-Planckian Censorship Conjecture (TCC) for classical cosmological solutions with positive potentials. Taken together, these constraints exclude the leading proposals to realize scale-separated AdS vacua and metastable de Sitter vacua in the string theory landscape such as DGKT and KKLT.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗
NASA NTRS1973

Geographic applications of ERTS-1 imagery to rural landscape change in eastern Tennessee

There are no author-identified significant results in this report. A multistage sampling experiment was conducted using low (10,000') and high (60,000') altitude aircraft imagery in comparison with orbital (560 miles) ERTS imagery. Although the aircraft data provide detailed landscape observations similar to ground truth data, they cover relatively small areas per image frame for irregular static slices of time. By comparison, ERTS provides repetitive observations in a regional perspective for broad areal coverage. Microdensitometric and computer techniques are being used to analyze the ERTS imagery for gray tone signatures, comparisons, and ultimately for landscape change detection.

Rehder, J. B.↗