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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 127 records · Page 7

Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1- 13 C]Pyruvate

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1- 13 C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker’s yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1- 13 C]pyruvate into oxidative decarboxylation products CO 2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO 2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1- 13 C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.

fungi↗

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗

Volumetric imaging of the 3D orientation of cellular structures with a polarized fluorescence light-sheet microscope

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations in biological samples, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the diffraction-limited three-dimensional distribution of the orientations and positions of ensembles of fluorescent dipoles that label biological structures. We share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model the distributions based on the polarization-dependent efficiency of excitation and detection of emitted fluorescence, using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labeled giant unilamellar vesicles, fast-scarlet-labeled cellulose in xylem cells, and phalloidin-labeled actin in U2OS cells. Additionally, we observe phalloidin-labeled actin in mouse fibroblasts grown on grids of labeled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.

Science & Technology - Other Topics↗

Structural basis for aminoacylation of cellular modified tRNALys3 by human lysyl-tRNA synthetase

Abstract The average eukaryotic transfer ribonucleic acid (tRNA) contains 13 post-transcriptional modifications; however, their functional impact is largely unknown. Our understanding of the complex tRNA aminoacylation machinery in metazoans also remains limited. Herein, using a series of high-resolution cryo-electron microscopy (cryo-EM) structures, we provide the mechanistic basis for recognition and aminoacylation of fully modified cellular tRNALys3 by human lysyl-tRNA synthetase (h-LysRS). The tRNALys3 anticodon loop modifications S34 (mcm5s2U) and R37 (ms2t6A) play an integral role in recognition by h-LysRS. Modifications in the T-, variable-, and D-loops of tRNALys3 are critical for ordering the metazoan-specific N-terminal domain of LysRS. The two catalytic steps of tRNALys3 aminoacylation are structurally ordered; docking of the 3′-CCA end in the active site cannot proceed until the lysyl–adenylate intermediate is formed and the pyrophosphate byproduct is released. Association of the h-LysRS–tRNALys3 complex with a multi-tRNA synthetase complex-derived peptide shifts the equilibrium toward the 3′-CCA end “docked” conformation and allosterically increases h-LysRS catalytic efficiency. The insights presented here have broad implications for understanding the role of tRNA modifications in protein synthesis, the human aminoacylation machinery, and the growing catalog of metabolic and neurological diseases linked to it.

Devarkar, Swapnil C. (ORCID:000000029271243X)↗

Towards rational control of seed oil composition: dissecting cellular organization and flux control of lipid metabolism

Plant lipids represent a fascinating field of scientific study, in part due to a stark dichotomy in the limited fatty acid (FA) composition of cellular membrane lipids vs the huge diversity of FAs that can accumulate in triacylglycerols (TAGs), the main component of seed storage oils. With few exceptions, the strict chemical, structural, and biophysical roles imposed on membrane lipids since the dawn of life have constrained their FA composition to predominantly lengths of 16–18 carbons and containing 0–3 methylene-interrupted carbon-carbon double bonds in cis-configuration. However, over 450 “unusual” FA structures can be found in seed oils of different plants, and we are just beginning to understand the metabolic mechanisms required to produce and maintain this dichotomy. Here we review the current state of plant lipid research, specifically addressing the knowledge gaps in membrane and storage lipid synthesis from 3 angles: pathway fluxes including newly discovered TAG remodeling, key acyltransferase substrate selectivities, and the possible roles of “metabolons.”

59 BASIC BIOLOGICAL SCIENCES↗

Repositioning Quantum Cellular Automata for Dependable Quantum-Classical Systems

Quantum Cellular Automata (QCA) provides a structured model of distributed quantum computation with inherent locality and regularity properties that are suited to dependable execution. However, QCA remain largely absent from discussions on reproducibility, fault management, and orchestration in heterogeneous quantum-classical systems. We propose a dual-axis framework that situates QCA within both computation and physical realizability, revealing regions where robust, scalable, and hardware-constrained quantum dynamics may reside. By revisiting prior results through the lens of reproducibility and architecture resilience, we suggest that QCA offers a potential substrate for benchmarking and system-level co-design.

Stapleton, Nicholas [ORNL] (ORCID:0000000335305325↗

Neutral rhenium(i) tricarbonyl complexes with sulfur-donor ligands: anti-proliferative activity and cellular localization

Rhenium(I) tricarbonyl complexes are widely studied for their cell imaging properties and anticancer and anti-microbial activities, but the complexes with S-donor ligands remain relatively unexplored. A series of six fac-[Re(NN)(CO) 3 (SR)] complexes, where (NN) is 2,2'-bipyridyl (bipy) or 1,10-phenanthroline (phen), and RSH is a series of thiocarboxylic acid methyl esters, have been synthesized and characterized. Cellular uptake and anti-proliferative activities of these complexes in human breast cancer cell lines (MDA-MB-231 and MCF-7) were generally lower than those of the previously described fac-[Re(NN)(CO) 3 (OH 2 )] + complexes; however, one of the complexes, fac-[Re(CO) 3 (phen)(SC(Ph)CH 2 C(O)OMe))] (3b), was active (IC 50 ~ 10 μM at 72 h treatment) in thiol-depleted MDA-MB-231 cells. Moreover, unlike fac- [Re(CO) 3 (phen)(OH 2 )] + , this complex did not lose activity in the presence of extracellular glutathione. Taken together these properties show promise for further development of 3b and its analogues as potential anti-cancer drugs for co-treatment with thiol-depleting agents. Conversely, the stable and non-toxic complex, fac-[Re(bipy)(CO) 3 (SC(Me)C(O)OMe)] (1a), predominantly localized in the lysosomes of MDA-MB-231 cells, as shown by live cell confocal microscopy (λ ex = 405 nm, λ em = 470-570 nm). It is strongly localized in a subset of lysosomes (25 μM Re, 4 h treatment), as shown by co-localization with a Lysotracker dye. Longer treatment times with 1a (25 μM Re for 48 h) resulted in partial migration of the probe into the mitochondria, as shown by co-localization with a Mitotracker dye. These properties make complex 1a an attractive target for further development as an organelle probe for multimodal imaging, including phosphorescence, carbonyl tag for vibrational spectroscopy, and Re tag for X-ray fluorescence microscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling the Next Generation of Smart Sensors in Coal Fired Power Plants using Cellular 5G Technology

An important need for coal fired power plants is the ability to monitor multiple systems with ease and accuracy. Common implementations of these monitoring systems come with drawbacks due to the nature of coal fired power plants. Harsh environments, High Temperatures, and lots of RF (Radio Frequency) noise can create issues for accurately recording and transmitting data across wireless signals. In addition, as renewable energy sources come online, existing fossil fueled plants will need to operate more flexibly with their maintenance schedules outside of standard conditions. Therefore, additional sensing and control mechanisms need placed in existing plants to provide operators with more information such that maintenance decisions can be made well in advance of failures. A solution to this problem is the Next Generation of Smart Sensors, which leverages the power of 5G cellular signals and machine learning to overcome the myriad of problems with current implementations

20 FOSSIL-FUELED POWER PLANTS↗

FY25 Cellular Silicone Foam Friction Testing Summary Report

This effort was a collaboration between LANL groups MPA-CINT, E-13, and V-14 to characterize various properties of foam materials for programmatic work. Specifically, MPA-CINT staff members’ contribution to this effort was to perform friction testing of cellular silicone foams of two different porosities with respect to two engineering materials with predefined surface roughnesses. The selected foams (henceforth serving as the sled material interface exposed to motion) had porosities of 67% and 70% with respect to fabricated values. The other materials used in the friction testing measurement couple (static track material) were 304 Stainless Steel (304 SS) and Very High-Temperature Glass-Mica Ceramic, known as Macor®.

36 MATERIALS SCIENCE↗

T3tris: AI-Driven Inverse Design of Cellular Materials

Los Alamos National Laboratory has developed T3tris, a generative AI platform that enables real-time inverse design of architected cellular materials. This capability transforms how mechanical metamaterials are designed by generating microstructural topologies that conform to target nonlinear stress-strain curves, even at high compressive strain (up to 50%).

36 MATERIALS SCIENCE↗

Human Lung Cellular Response to HCoV-229E Infection, Post-Translational Modification Proteomics Time Course (ACS-TZ-DP6)

The purpose of this experiment was to evaluate the human lung cellular response to wild type human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock-infected and HCoV-229E infected immortalized human lung epithelial cells (A549) (MOI 3) and immortalized human lung fibroblasts (MRC-5) (MOI 3). Whole cell lysates were collected at 8, 16, and 24 hours post infection and were processed for post translational modification (PTM) proteomics analysis to determine the HCoV-229E phosphoproteome, redox proteome, and acetylation proteome.

Sims, Amy C [Pacific Northwest National Laboratory↗

Human Host Cellular Response to HCoV-229E Infection Transcriptomics (ACS-DP1)

The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock and infected immortalized human lung epithelial cells (A549) (MOI 5), immortalized human lung fibroblasts cells (MRC5) (MOI5), and primary human airway epithelial (HAE) (MOI 3) cells from lung tissue. Sample data was acquired using an Illumina HiSeq 2000 sequencer system and processed for RNA sequencing (RNA-Seq) expression analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Human Host Cellular Response to HCoV-229E Infection Proteomics (ACS-JM-DP2)

The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock and infected immortalized human lung epithelial cells (A549) (MOI 5) nuclear extracts, immortalized human lung fibroblasts cells (MRC5) (MOI5) nuclear extracts, and primary human airway epithelial (HAE) (MOI 3) cells from lung tissue and processed for proteome analysis. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files and supporting metadata materials. Experimental proteomics samples were prepared using Limited Proteolysis (LiP) methods for Label-free quantification (LFQ) and global proteomic evaluation. Sample data was acquired using a Q-Exactive HF-X mass spectrometer and was processed and compiled using MaxQuant software (v.1.6.17.0). Processed proteomic data downloads include a sample naming key, processed MaxQuant results/parameters, and protein annotated relative abundance files. See corresponding primary data accessions below and Viral Experiment LiP Analysis source code supporting data transparency and reuse. Experimental transcriptomics samples were collected in parallel and processed for RNA sequencing (RNA-Seq) as summarized under ACS-DP1 (https://data.pnnl.gov/group/nodes/dataset/34069).

59 BASIC BIOLOGICAL SCIENCES↗

Influence of cellular redox reactions on the structure and function of light harvesting and photosystems

Photosynthesis enables the conversion of one of the most abundant and free forms of energy, sunlight, into chemical bonds through the utilization of highly tailored protein complexes. These enzymes work in unison to absorb, convert, and transform light into high-energy electrons which are used for various functions important to metabolism and cellular protection. Over the last ∼50 years, photosynthetic organisms, such as cyanobacteria, have been adapted and engineered to produce valuable compounds like hydrogen and ethylene, among others. Often this is performed by removing native and/or adding in exogenous energy utilization pathways so that light energy is re-directed towards the synthesis of desired compounds. However, the interplay between primary light capture, conversion reactions, and the downstream electron utilization sinks is not fully understood. Further complicating these strategies are the plethora of compensatory mechanisms that facilitate steady electron flow and the maintenance of photosynthesis under dynamic conditions. This manifests as structural and functional plasticity of the photosynthetic machinery, often seen in modulations of oligomeric compositions or changes in protein-protein interactions and coupling with redox enzymes. Understanding these mechanisms is crucial to biotechnology applications because re-engineering electron utilization sinks has profoundly different effects on the light capture and conversion reactions of photosynthesis. Optimization requires a molecular-level understanding of the functional interrelationships between electron sinks and photosynthetic components that influence photosynthetic efficiencies to realize potential improvements in product yields. Here, we aim to highlight how perturbation of reductive reactions is revealing the functional plasticity in key components of the photosynthetic energy transduction pathway.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling the Impact of Grain Size on Corrosion Behavior of Ni-Based Alloys in Molten Chloride Salt via Cellular Automata

Molten chloride salts hold significant promise as both thermal transfer and storage media for next-generation concentrated solar power (CSP) systems. However, molten chlorides pose a considerable corrosion risk to structural materials, particularly Ni-based alloys. One approach to enhancing corrosion resistance is through the optimization of grain structure; however, it remains uncertain whether increasing or decreasing grain size enhances corrosion resistance. A cellular automata (CA) program was developed to evaluate the interplay between grain size and corrosion in Ni-based alloy. Our CA program tracks alloy composition, surface roughness, and thickness loss via a graphical user interface, displaying corrosion and diffusion status, and multiple user input cards for tuning the simulation. CA simulations of Inconel 625 indicate enhanced corrosion resistance with increased grain size, with passivating oxides offering limited protection. Additionally, the temporal evolution of alloy surface roughness demonstrates notable fluctuations, with abrupt increases attributed to corrosion along vertical grain boundaries and sudden decreases to grain detachment from the protective film.

Materials Science↗