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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 721 records · Page 40

A theoretical index for understanding distinct land relative humidity trends in observations, reanalyses, and models

Land surface relative humidity (RH) is a key variable in the coupled land–atmosphere system that profoundly influences terrestrial hydroclimate and ecosystems. Yet historical changes in land RH are not well understood due to limited observations, biased reanalyses, and the lack of a framework for interpreting RH changes under multiple influencing factors. Here, we show that the spatiotemporal variability of land RH and its distinct historical trends among observations, reanalyses, and Earth system models are captured by a simple index based on the ratio of precipitation (P) to a modified potential evapotranspiration formulated independently of RH (PET°). The index provides a physical calibration of biased land RH in reanalyses and a quantitative framework for interpreting land RH changes. Over 1973–2024, land RH has decreased substantially, owing to the intrinsic rise in PET° with temperature and little increase in land precipitation. Reanalyses overestimate the observed RH decrease, consistent with exaggerated surface warming and precipitation decline. The index captures this coherent bias and enables a calibration using observed precipitation and temperature. Models simulate a wide range of land RH trends, but nearly all runs underrepresent the historical drying. The index captures the model spread and discrepancy and attributes them to contributions of precipitation and PET°. Weaker land RH decreases in models arise mainly from weaker subtropical precipitation declines, linked to muted intensification of subtropical highs and biased subtropical climatology. The model–observation discrepancy is unlikely explained by internal variability, implying model underestimation of forced RH decrease and a drier land future than current projections.

Earth system models↗

Emerging protein sequencing technologies: proteomics without mass spectrometry?

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry. Areas Covered: We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture. Expert Opinion: Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

59 BASIC BIOLOGICAL SCIENCES↗

Distribution of plutonium and radium in the human heart

Since 1968, the United States Transuranium and Uranium Registries (USTUR) has studied the biokinetics and tissue dosimetry of uranium and transuranium elements in nuclear workers. As part of the USTUR collaboration with the Million Person Study of Low-Dose Health Effects, radiation dose to different parts of the human heart is being estimated for workers with documented intakes of 239 Pu or 226 Ra. The study may be expanded for workers with intakes of 238 U and other radionuclides. The distribution of radionuclides, expressed in terms of concentration (Bq per kg of tissue) serves as an important parameter for estimating radiation dose. Based on available organs from workers who donated their bodies or tissues for research, nine undissected hearts were selected: seven from USTUR registrants with plutonium exposure (males) and two individuals with radium intakes (female and male). For the plutonium workers, estimated 239 Pu systemic deposition ranged from <74 Bq to 1765 Bq. Estimated 226 Ra ‘initial systemic intakes’ were 10.1 MBq and 14.8 kBq for the female patient and male worker, respectively. Organ dissection was based on a heart model published by Borrego et al (2019 J. Radiol. Prot. 39 950–65). This model includes nine cardiac substructures: aorta, left main coronary artery, left atrium, left anterior descending artery, left circumflex artery, left ventricle, right atrium, right coronary artery, and right ventricle. In addition, heart valves, fat attached to epicardium, fluids, and a coronary bypass graft were collected resulting in 111 samples that are currently undergoing radiochemical analyses and mass-spectrometric measurements. The 239 Pu and 226 Ra evaluations are not completed. The results of this study are intended to support radiation worker health studies by improving associated dosimetric and epidemiological models.

USTUR↗

Integrative analysis of CAM photosynthesis reveals its impact on primary metabolism in Yucca

Crassulacean Acid Metabolism (CAM) is an adaptation that temporally separates carbon uptake at night from photosynthesis during the day. CAM has evolved repeatedly across vascular plants, as its emergence may depend on simple regulatory changes to deeply conserved metabolic pathways. Modern CAM research relies heavily on interpretation of transcriptomic data, though regulation occurs at multiple levels following transcription. Additionally, while most research to date has focused on a handful of genes and metabolites in the core CAM pathway, the co-option of conserved regulatory and functional genes is bound to have wide-ranging effects on other aspects of primary metabolism. In this study, we integrate transcriptomic, proteomic, and metabolomic data to compare primary metabolism between the CAM species Yucca aloifolia and closely related C 3 species, Y. filamentosa. We observe minimal correlation between protein abundance and mRNA expression, suggesting significant post-transcriptional regulation in CAM species. We also find evidence of shifts in gene expression and metabolite accumulation outside of the central CAM pathway, suggesting that the shift to CAM has cascading effects across primary metabolism, especially nitrogen metabolism. Our findings provide insights into the metabolic shifts associated with CAM evolution, and highlight the complexity of its regulation at multiple biological levels.

59 BASIC BIOLOGICAL SCIENCES↗

Mediation of Colloidal Encounter Dynamics by Surface Roughness

Rigorous understanding on the self-assembly of colloidal nanocrystals is crucial to develop tailored nanostructured materials for energy storage, sensing, and optical fields. Despite extensive studies on the self-assembly, a mechanistic understanding of self-assembly under an external field still remains an ongoing challenge. Here, in this work, we used optical tweezers that impose an external attractive force field, resulting in the self-assembly of alpha-phase sodium yttrium fluoride nanocrystals. The dynamic force that is strongly dependent on the surface roughness of the nanocrystals is shown to be a decisive factor for a direct contact between the nanocrystals, manifested by the roughness-dependent hydrodynamic resistivity and Langevin dynamic simulations. Our study provides direct evidence that the role of dynamics is equally important in understanding the self-assembly, which has been rarely observed in the self-assembly in contrast with many studies on the equilibrium forces. These results may have further impact in other fields, such as having explanatory power for the probability of nonclassical crystal growth or the structure of viral spike proteins that affect the probability of viruses binding with cells.

Felsted, Robert G. [Univ. of Washington, Seattle, ↗

Hybrid Symbolic-Numerical Modeling and Parametric Stability Analysis of DC–AC Power Systems

Hybrid DC-AC power systems integrating diverse inverter-based resources (IBRs) and multi-terminal high-voltage direct current (MTDC) networks represent a promising architecture for future power grids, while introducing challenges for modeling, stability analysis, and control design. This paper develops a hybrid symbolic-numerical modeling framework and tool to characterize the parametric small-signal stability of DC-AC coupled power systems. The proposed approach constructs parametric state-space models to enable efficient representation of system dynamics under varying control parameters and network configurations, with target parameters retained as symbolic variables and the remainder treated numerically. The stability analysis framework covers eigenvalue, sensitivity, and stability boundary and region characterization. Enhanced linear matrix inequality (LMI) techniques are proposed to directly certify small-signal stability over regions of parameter space while also reducing the conservativeness and computational burden. The resulting tools and frameworks enable rapid parametric model construction across diverse grid conditions, thereby facilitating stability-informed control and operation in complex DC–AC power systems.

DC–AC power systems↗

pnnl-predictive-phenomics/csc031-gem

Genome-Scale Metabolic Model of CarbStor Community member Microbacterium (csc031) Continuous Validation with Memote These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity

McNaughton, Andrew [@PNNL]↗

pnnl-predictive-phenomics/csc040-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Rhodococcus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

McNaughton, Andrew [@PNNL]↗

pnnl-predictive-phenomics/csc043-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Paenibacillus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

Zucker, Jeremy [Pacific Northwest National Laborat↗

LIB Design Module for Grid Energy System Application

We will employ a machine learning approach with intelligent data mining and database construction to analyze enormous data repositories for identifying and extracting geographic-dependent cell design specifications from publicly accessible grid-scale energy storage usage databases in an automated way at scale.

Liu, Dianying [Pacific Northwest National Laborato↗

Prompt-Based Development of Domain-Specific Taxonomies

Framework for interacting with prompt-based LLMs (Large Language Models such as, but not limited to, ChatGPT) in order to develop domain specific taxonomies. The software itself is a series of prompts designed to extract hierarchical taxonomy categories from an LLM, as well as guidelines for how to fine-tune LLMs in order to provide better domain-specific taxonomic categories.

Grundy, Jon [Pacific Northwest National Laboratory↗

Grid-Kitchen/grid-meta (33407-E)

A repository for extracting dehydrated metadata for distribution power grid model.

Duwadi, Kapil [Pacific Northwest National Laborato↗

pnnl/LL-risk-assessment (33525-E)

A suite of scripts that helps evaluate and visualize the grid reliability risk due to events introduced by large dynamic digital loads (LDDLs) at the planning stage.

Biswas, Shuchismita [Pacific Northwest National La↗

NWChem

NWChem is a computational chemistry software package which includes quantum chemical and molecular dynamics functionality. It aims to be scalable both in its ability to treat large problems efficiently, and in its usage of available parallel computing resources.

Apra, Edoardo [Pacific Northwest National Laborato↗

A Concept of a Convection–Cloud Chamber to Study Aerosol–Cloud–Drizzle Interactions

Understanding and quantifying the full chain of processes from aerosol activation to drizzle formation, and the associated feedbacks to the aerosol chemical and physical properties, all within a turbulent cloud are some of the toughest challenges in atmospheric chemistry and physics and are keys to the cloud–precipitation puzzle. This paper describes a concept for a new type of research facility consisting of a cloud chamber plus associated instrumentation and computational models, to explore aerosol–cloud interactions and processing, cloud optical properties, entrainment–cloud interactions, and quantitative assessment of drizzle onset. The envisioned design is for a 3 m × 3 m × 9 m chamber, such that the height is sufficient to achieve long lifetimes for aerosol processing and for significant drizzle growth by collision and coalescence. A suite of computational tools for simulating microphysical properties in the chamber provides a digital twin for designing the chamber and a range of example experiments. Theory and test results from novel remote sensing systems for exploring chemical and physical interactions and evolution of aerosols, cloud droplets, and drizzle within turbulent clouds are described. Testing of technology needed for the operation of a large-volume chamber, including aerosol generation methods and novel materials for water vapor boundary conditions, is described. Simulations suggest that spatially uniform turbulence and microphysical properties can be sustained in a steady state, with reasonable aerosol and water vapor fluxes, and that substantial drizzle can be produced through collision and coalescence of cloud droplets. Remaining challenges for more detailed engineering design and a discussion of possible first-light experiments are described.

54 ENVIRONMENTAL SCIENCES↗