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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Invite the Chaos Monkey: Test Effect Payloads for Tuning ICS Incident Response

In 2010, when Netflix moved their operational systems to the cloud, they developed a pseudo-random mechanism to cause deliberate outages and failures of key system elements to ensure that automated systems for detecting and remediating outages were mature and fully functional. This Chaos Monkey spawned an entire Simian Army designed to ensure system resilience and enable failure response before issues became outages. Through the DARPA RADICS program, Provatech, INL, and other researchers have developed a mechanism for creating controllable failures via Test Effect Payloads (TEPs) for Industrial Control Systems in order to enable an asset owner to tune network and process sensor technology, increase the effectiveness of incident response and remediation, and highlight areas where resilient technology could bring benefit to Operational Technology. This talk will explore what a TEP is, how to create a TEP, and suggest what a systematic system resilience plan using TEP’s might look like. We will also discuss how regulated entities might employ TEP’s in a compliant resilience strategy.

42 ENGINEERING↗
DOE OSTI2024

Aridity and forest age mediate landscape scale patterns of tropical forest resistance to cyclonic storms

Abstract Cyclonic storms, or hurricanes, are expected to intensify as ocean heat energy rises due to climate change. Ecological theory suggests that tropical forest resistance to hurricanes should increase with forest age and wood density. However, most data on hurricane effects on tropical forests come from a limited number of well‐studied long‐term monitoring sites, restricting our capacity to evaluate the resistance of tropical forests to hurricanes across broad environmental gradients. In this study, we assessed whether forest age and aridity mediate the effects of hurricanes Irma and Maria in Puerto Rico, Vieques and Culebra islands. We leveraged functional trait data for 410 tree species, remotely sensed measurements of canopy height and cover, along with data on forest stand characteristics of 180 of 338 forest monitoring plots, each covering an area of 0.067 ha. The plots represent a broad mean annual precipitation (MAP) gradient from 701 to 4598 mm and a complex mosaic of forest age from 5 to around 85 years since deforestation. Hurricanes resulted in a 25% increase in basal area mortality rates, a 45% decrease in canopy height and a 21% reduction in canopy cover. These effects intensified with forest age, even after considering proximity to the hurricane path. The links between forest age and hurricane disturbances were likely due the prevalence of tall canopies. Tall forest canopies were strongly linked with low community‐weighted wood density (WD). These characteristics were on average more common in moist and wet forests (MAP >1250 mm). Conversely, dry forests were dominated by short species with high wood density (WD > 0.6 g cm −3 ) and did not show significant increases in basal area mortality rates after the hurricanes. Synthesis . Our findings show that selection towards drought‐tolerant traits across aridity gradients, such as short stature and dense wood, enhances resistance to hurricanes. However, forest age modulated responses to hurricanes, with older forests being less resistant across the islands. This evidence highlights the importance of considering the intricate links between ecological succession and plant function when forecasting tropical forests’ responses to increasingly strong hurricanes.

Vargas G., German↗
DOE OSTI2023

Modeling immunity in microphysiological systems

There is a need for better predictive models of the human immune system to evaluate safety and efficacy of immunomodulatory drugs and biologics for successful product development and regulatory approvals. Current in vitro models, which are often tested in two-dimensional (2D) tissue culture polystyrene, and preclinical animal models fail to fully recapitulate the function and physiology of the human immune system. Microphysiological systems (MPSs) that can model key microenvironment cues of the human immune system, as well as of specific organs and tissues, may be able to recapitulate specific features of the in vivo inflammatory response. This minireview provides an overview of MPS for modeling lymphatic tissues, immunity at tissue interfaces, inflammatory diseases, and the inflammatory tumor microenvironment in vitro and ex vivo. Broadly, these systems have utility in modeling how certain immunotherapies function in vivo, how dysfunctional immune responses can propagate diseases, and how our immune system can combat pathogens.

Research & Experimental Medicine↗
DOE OSTI2020

Medium amplitude parallel superposition (MAPS) rheology. Part 2: Experimental protocols and data analysis

An experimental protocol is developed to directly measure the new material functions revealed by medium amplitude parallel superposition (MAPS) rheology. This protocol measures the medium amplitude response of a material to a simple shear deformation composed of three sine waves at different frequencies, revealing a rich dataset consisting of up to 19 measurements of the third-order complex modulus at distinct three-frequency coordinates. We discuss how the choice of input frequencies influences the features of the MAPS domain studied by the experiment. A polynomial interpolation method for reducing the bias of measured values from spectral leakage and reducing variance due to noise is discussed, including a derivation of the optimal range of amplitudes for the input signal. This leads to the conclusion that conducting the experiment in a stress-controlled fashion possesses a distinct advantage to the strain-controlled mode. The experimental protocol is demonstrated through measurements of the MAPS response of a model complex fluid: a surfactant solution of wormlike micelles. The resulting dataset is indeed large and feature-rich, while still acquired in a time comparable to similar medium amplitude oscillatory shear (MAOS) experiments. We demonstrate that the data represent measurements of an intrinsic material function by studying its internal consistency, compatibility with low-frequency predictions for Coleman–Noll simple fluids, and agreement with data obtained via MAOS amplitude sweeps. Finally, the data are compared to predictions from the corotational Maxwell model to demonstrate the power of MAPS rheology in determining whether a constitutive model is consistent with a material’s time-dependent response.

Lennon, Kyle R. (ORCID:0000000212515461)↗
DOE OSTI2020

Covalent Surface Modification Effects on Single‐Walled Carbon Nanotubes for Targeted Sensing and Optical Imaging

Abstract Optical nanoscale technologies often implement covalent or noncovalent strategies for the modification of nanoparticles, whereby both functionalizations are leveraged for multimodal applications but can affect the intrinsic fluorescence of nanoparticles. Specifically, single‐walled carbon nanotubes (SWCNTs) can enable real‐time imaging and cellular delivery; however, the introduction of covalent SWCNT sidewall functionalizations often attenuates SWCNT fluorescence. Recent advances in SWCNT covalent functionalization chemistries preserve the SWCNT's pristine graphitic lattice and intrinsic fluorescence, and here, such covalently functionalized SWCNTs maintain intrinsic fluorescence‐based molecular recognition of neurotransmitter and protein analytes. The covalently modified SWCNT nanosensor preserves its fluorescence response towards its analyte for certain nanosensors, presumably dependent on the intermolecular interactions between SWCNTs or the steric hindrance introduced by the covalent functionalization that hinders noncovalent interactions with the SWCNT surface. These SWCNT nanosensors are further functionalized via their covalent handles with a targeting ligand, biotin, to self‐assemble on passivated microscopy slides, and these dual‐functionalized SWCNT materials are explored for future use in multiplexed sensing and imaging applications.

Chio, Linda↗
DOE OSTI2023

Computational insights into the interaction of water with the UiO-66 metal–organic framework and its functionalized derivatives

The UiO-66 metal–organic framework (MOF) has been identified as a promising hydrophilic material for water harvesting. Recent studies show that its water uptake ability at low relative humidity (RH) can be improved by incorporating hydrophilic functional groups into the framework. In this work, we provide computational insights into the adsorption of water in UiO-66 and its functionalized derivatives to reveal the role played by different adsorption sites and functional groups in the adsorption mechanism. We started by developing molecular models for UiO-66, UiO-66-NH 2 , UiO-66-OH, and UiO-66-(OH) 2 compatible with the MB-pol data-driven many-body potential of water. We then benchmarked these models against ab initio data. Here we used these models to perform molecular dynamics simulations and calculate radial distribution functions, IR spectra, and two-dimensional density distribution maps for water in the MOFs. These results consistently show that the μ 3 -OH sites are the preferential interaction sites for water in UiO-66 and all its variants, and the formation of localised water clusters inside the octahedral pores is responsible for the abrupt step in the experimental adsorption isotherms. Furthermore, the presence of functional groups in the framework allows water to cluster in the octahedral pores at lower RH, thus making the MOF a more efficient water harvester. Overall, this study provides molecular-level insights into the pore filling process of UiO-66 and its functionalized derivatives, which are needed for the design of efficient water harvesting materials based on MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids—including the density response, surface tension and size-dependent cavitation free energies—for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Nitrogen Status Rewires Transcriptional Regulation of Dhurrin, a Dual‐Purpose Defense Metabolite in Sorghum bicolor

Dhurrin, a cyanogenic glucoside, plays an important role in Sorghum bicolor physiology and defense. The concentration of dhurrin in sorghum is influenced by both nitrogen status and stage of plant organ development. While nitrogen resupply activates the expression of genes for dhurrin biosynthesis, the molecular mechanisms underlying this regulation remain unclear. In this study, we investigated the transcriptional response of sorghum to nitrogen resupply following growth under nitrogen-limiting conditions. Using a time-course design, we measured hydrogen cyanide potential (HCNp), growth, and nitrate content at 0-, 2-, 6-, 12-, 24-, 36-, 48-, and 60-h after resupply and collected tissue for RNAseq analysis in parallel for analysis of gene expression and construction of gene regulatory networks (GRNs). HCNp (mg g −1 DW) increased significantly in leaf and stem tissues following nitrogen resupply, with increases in the leaf partially driven by continued declines in controls under ongoing nitrogen stress. Expression of the dhurrin pathway genes was upregulated in leaves from 24 h after nitrogen resupply, with diel expression patterns observable over the remaining time points. No upregulation was observed in roots or stems, suggesting that developmental context overrides environmental cues. GRN analysis identified candidate transcription factors regulating dhurrin biosynthesis genes, including members of the MYB, bZIP, and GARP-type transcription factor families. Some of these candidate transcription factors may be involved in relieving senescence-associated suppression of dhurrin biosynthesis and link nitrogen signaling to pathway activation. These findings provide new insight into the nitrogen-responsive regulation of dhurrin in sorghum, highlighting candidate regulators for future functional characterization.

S. bicolor↗
DOE OSTI2026

Complex magnetic ground state driving a large rotating magnetocaloric effect in Tb 3 Ni at low temperature

The rotating magnetocaloric effect (RMCE) offers a promising alternative to conventional magnetocaloric configurations by taking advantage of magnetic anisotropy to simplify device architecture and enhance refrigeration efficiency. In this study, the RMCE in a high-quality single crystal of Tb 3 Ni is investigated, a compound previously shown to exhibit significant magnetocaloric behavior along its easy axis of magnetization. By measuring the magnetization and corresponding entropy change along the three principal crystallographic axes using a discontinuous measurement protocol, we verify the anisotropic magnetic properties and derive the RMCE from rotations between hard ( a, b ) and easy ( c ) axes of magnetization. Our results show a maximum value for the rotating entropy change of 19.5 J kg −1 K −1 for µ 0 H = 7 T around 60 K, within the critical temperature window for industrial gas liquefaction applications. Neutron diffraction and magnetic Pair-Distribution Function (mPDF) analysis reveal that the origin of this large anisotropic response lies in a partially ordered incommensurate spin-density wave phase and persistent short-range ferromagnetic (FM) correlations. These complex magnetic states enable the release of a substantial amount of magnetic entropy when the field is applied along the easy c-axis, effectively driving the large RMCE. Comparison with other RMCE materials confirms Tb 3 Ni as one of the most promising candidates in this temperature regime, offering both a large magnetic entropy change and a wide operating window.

Gas liquefaction↗
DOE OSTI2024

Reactive oxygen species control protein degradation at the mitochondrial import gate

While reactive oxygen species (ROS) have long been known to drive aging and neurodegeneration, their persistent depletion below basal levels also disrupts organismal function. Cells counteract loss of basal ROS via the reductive stress response, but the identity and biochemical activity of ROS sensed by this pathway remain unknown. Here, we show that the central enzyme of the reductive stress response, the E3 ligase Cullin 2-FEM1 homolog B (CUL2 FEM1B ), specifically acts at mitochondrial TOM complexes, where it senses ROS produced by complex III of the electron transport chain (ETC). ROS depletion during times of low ETC activity triggers the localized degradation of CUL2 FEM1B substrates, which sustains mitochondrial import and ensures the biogenesis of the rate-limiting ETC complex IV. As complex III yields most ROS when the ETC outpaces metabolic demands or oxygen availability, basal ROS are sentinels of mitochondrial activity that help cells adjust their ETC to changing environments, as required for cell differentiation and survival.

FEM1B↗
DOE OSTI2023

Effects of Salt on Phase Behavior and Rheological Properties of Alginate–Chitosan Polyelectrolyte Complexes

Oppositely charged polyelectrolytes often form polyelectrolyte complexes (PECs) due to the association through electrostatic interactions. Obtaining PECs using natural, biocompatible polyelectrolytes is of interest in the food, pharmaceutical, and biomedical industries. In this work, PECs were prepared from two biopolymers, positively charged chitosan and negatively charged alginate. We investigate the changes in the structure and properties of PECs by adding sodium chloride (salt doping) to the system. The shear modulus of PECs can be tuned from ~10 to 10 4 Pa by changing the salt concentration. The addition of salt led to a decrease in the water content of the complex phase with increasing shear modulus. However, at a very high salt concentration, the shear modulus of the complex phase decreased but did not lead to the liquid coacervate formation, typical of synthetic polyelectrolytes. This difference in phase behavior has likely been attributed to the hydrophobicity of chitosan and long semiflexible alginate and chitosan chains that restrict the conformational changes. Large amplitude oscillatory shear experiments captured nonlinear responses of PECs. The compositions of the PECs, determined as a function of salt concentration, signify the preferential partitioning of salt into the complex phase. Small-angle X-ray scattering of the salt-doped PECs indicates that the Kuhn length and radius of the alginate–chitosan associated structure qualitatively agree with the captured phase behavior and rheological data. This study provides insights into the structure–property as a function of salt concentration of natural polymer-based PECs necessary for developing functional materials from natural polyelectrolytes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Contrasting the Biophysical and Radiative Effects of Rising CO 2 Concentrations on Ozone Dry Deposition Fluxes

Abstract The dry deposition of ozone from the atmosphere to ecosystems is an important coupling mechanism between atmospheric chemistry and terrestrial biogeochemical processes. In most Earth system models, dry deposition is simulated using a resistor‐in‐series approach that aims to parameterize the governing biological, chemical, and physical processes through a series of functional approximations. Here, we evaluate the influence of carbon cycle‐climate responses on this parameterization using the results of the Energy Exascale Earth System Model v1.1 Biogeochemistry simulation campaign. This simulation campaign was designed in part to explore the biophysical and radiative effects of rising historical CO 2 concentrations on the Earth system. We find that while the global annual ozone dry deposition is relatively insensitive to these effects, regionally the influence can be up to 10%. The strongest regional sensitivities in ozone dry deposition are predominantly in higher latitudes over land in the northern hemisphere and are dominated by the radiative effect of CO 2 , with little net influence of biophysical responses. Of all the impacts of the radiative effect of CO 2 , we point to the potential importance of accurately representing ozone deposition to snow in Earth System Models and provide recommendations for future simulation campaigns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Diffractive optical computing in free space

Abstract Structured optical materials create new computing paradigms using photons, with transformative impact on various fields, including machine learning, computer vision, imaging, telecommunications, and sensing. This Perspective sheds light on the potential of free-space optical systems based on engineered surfaces for advancing optical computing. Manipulating light in unprecedented ways, emerging structured surfaces enable all-optical implementation of various mathematical functions and machine learning tasks. Diffractive networks, in particular, bring deep-learning principles into the design and operation of free-space optical systems to create new functionalities. Metasurfaces consisting of deeply subwavelength units are achieving exotic optical responses that provide independent control over different properties of light and can bring major advances in computational throughput and data-transfer bandwidth of free-space optical processors. Unlike integrated photonics-based optoelectronic systems that demand preprocessed inputs, free-space optical processors have direct access to all the optical degrees of freedom that carry information about an input scene/object without needing digital recovery or preprocessing of information. To realize the full potential of free-space optical computing architectures, diffractive surfaces and metasurfaces need to advance symbiotically and co-evolve in their designs, 3D fabrication/integration, cascadability, and computing accuracy to serve the needs of next-generation machine vision, computational imaging, mathematical computing, and telecommunication technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Gallium oxide (Ga2O3) as a radiation detector distinguishing neutrons and gammas

Gallium oxide (Ga2O3) is a promising ultrawide bandgap semiconductor for radiation detection with the potential of integrating electronic and scintillation functions within a single crystal device. This study establishes the scintillation response of β-Ga2O3 gamma irradiation from yttrium-88 (88Y). Then, californium-252 (252Cf) is used as a spontaneous fission source of mixed neutron and gamma radiation field to measure scintillation signals. Pulse shape discrimination and constant fraction discrimination techniques were used to separate neutron and gamma interaction events. Further investigation indicates that the prompt temporal responses of β-Ga2O3 for gammas and neutrons may enable discrimination of the two by prompt pulse fitting methods, focused around the initial peak. For gamma irradiation, we observed a rise time (τr) of 2.1 ns, decay time (τd) of 9.5 ns, and a full width at half maximum (FWHM) of 6.2 ns. For neutrons, it showed a τr of 2.3 ns, a τd of 12.1 ns, 9.4 ns FWHM, and reduced peak intensity. A diamond detector exhibited a more symmetrical τr and τd for both gamma and neutron signals and therefore is less effective at discriminating between the two by this method. This draws attention to β-Ga2O3’s ability to distinguish neutron and gamma particles. These findings showcase Ga2O3’s potential as a next-generation semiconductor for applications in nuclear safety and medical imaging, where precise discrimination between neutron and gamma interactions is essential.

Valdes, D. J. (ORCID:0000000304373720)↗
DOE OSTI2024

A minimal complex of KHNYN and zinc-finger antiviral protein binds and degrades single-stranded RNA

Detecting viral infection is a key role of the innate immune system. The genomes of some RNA viruses have a high CpG dinucleotide content relative to most vertebrate cell RNAs, making CpGs a molecular marker of infection. The human zinc-finger antiviral protein (ZAP) recognizes CpG, mediates clearance of the foreign CpG-rich RNA, and causes attenuation of CpG-rich RNA viruses. While ZAP binds RNA, it lacks enzymatic activity that might be responsible for RNA degradation and thus requires interacting cofactors for its function. One of these cofactors, KHNYN, has a predicted nuclease domain. Using biochemical approaches, we found that the KHNYN NYN domain is a single-stranded RNA ribonuclease that does not have sequence specificity and digests RNA with or without CpG dinucleotides equivalently in vitro. We show that unlike most KH domains, the KHNYN KH domain does not bind RNA. Indeed, a crystal structure of the KH region revealed a double-KH domain with a negatively charged surface that accounts for the lack of RNA binding. Rather, the KHNYN C-terminal domain (CTD) interacts with the ZAP RNA-binding domain (RBD) to provide target RNA specificity. We define a minimal complex composed of the ZAP RBD and the KHNYN NYN-CTD and use a fluorescence polarization assay to propose a model for how this complex interacts with a CpG dinucleotide-containing RNA. In the context of the cell, this module would represent the minimum ZAP and KHNYN domains required for CpG-recognition and ribonuclease activity essential for attenuation of viruses with clusters of CpG dinucleotides.

Yeoh, Zoe C. (ORCID:0000000226949068)↗
DOE OSTI2021

A novel construct for scaling groundwater–river interactions based on machine-guided hydromorphic classification

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. Predictive numerical models are needed to understand responses of river corridors to environmental change and to support sustainable watershed management. We posit that systematic hydromorphic classification provides a scaling construct that facilitates extrapolation of outputs from local-scale mechanistic models to reduced-order models applicable at reach and watershed scales. This in turn offers the potential to improve large-scale predictions of river corridor hydrobiogeochemical processes. Here we present a new machine-guided hydromorphic classification methodology that addresses the key requirements of this objective, and we demonstrate its application to a segment of the Columbia River in the northwestern United States. The resulting hydromorphic classes form spatially coherent and physically interpretable hydromorphic units that exhibit distinct behaviors in terms of distributions of subsurface residence times (a primary control on critical biogeochemical reactions). This approach forms the basis of ongoing research that is evaluating the formulation of reduced-order models and transferability of results to other river reaches and larger scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Understanding Quantum Control Processor Capabilities and Limitations through Circuit Characterization

Continuing the scaling of quantum computers hinges on building classical control hardware pipelines that are scalable, extensible, and provide real time response. The instruction set architecture (ISA) of the control processor provides functional abstractions that map high-level semantics of quantum programming languages to low-level pulse generation by hardware. Here, we provide a methodology to quantitatively assess the effectiveness of the ISA to encode quantum circuits for intermediate-scale quantum devices with O(10 2 ) qubits. The characterization model that we define reflects performance, the ability to meet timing constraint implications, scalability for future quantum chips, and other important considerations making them useful guides for future designs. Using our methodology, we propose scalar (QUASAR) and vector (qV) quantum ISAs as extensions and compare them with other ISAs in metrics such as circuit encoding efficiency, the ability to meet real-time gate cycle requirements of quantum chips, and the ability to scale to more qubits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Permafrost thaw with warming reduces microbial metabolic capacities in subsurface soils

Abstract Microorganisms are major constituents of the total biomass in permafrost regions, whose underlain soils are frozen for at least two consecutive years. To understand potential microbial responses to climate change, here we examined microbial community compositions and functional capacities across four soil depths in an Alaska tundra site. We showed that a 5‐year warming treatment increased soil thaw depth by 25.7% ( p = .011) within the deep organic layer (15–25 cm). Concurrently, warming reduced 37% of bacterial abundance and 64% of fungal abundances in the deep organic layer, while it did not affect microbial abundance in other soil layers (i.e., 0–5, 5–15, and 45–55 cm). Warming treatment altered fungal community composition and microbial functional structure ( p < .050), but not bacterial community composition. Using a functional gene array, we found that the relative abundances of a variety of carbon (C)‐decomposing, iron‐reducing, and sulphate‐reducing genes in the deep organic layer were decreased, which was not observed by the shotgun sequencing‐based metagenomics analysis of those samples. To explain the reduced metabolic capacities, we found that warming treatment elicited higher deterministic environmental filtering, which could be linked to water‐saturated time, soil moisture, and soil thaw duration. In contrast, plant factors showed little influence on microbial communities in subsurface soils below 15 cm, despite a 25.2% higher ( p < .05) aboveground plant biomass by warming treatment. Collectively, we demonstrate that microbial metabolic capacities in subsurface soils are reduced, probably arising from enhanced thaw by warming.

Wu, Linwei↗