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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Revisiting the Origin of Macromolecular Carbon (MMC) in Lunar Basalts 15556 & 10044

Volatile elements influence the geo-chemical evolution of planetary bodies and they are in magmas at every stage, from melting within planetary interiors to eruption at the surface. Analyses of lunar mare basalts supported the hypothesis that lunar mag-mas were depleted in volatiles (H-C-F-Cl-S), relative to their terrestrial analogs [1]. Nevertheless, several early studies of samples returned during the Apollo program proposed that the mare basalt eruptions, including the “fire fountain” eruptions, were propelled by the oxidation of magmatic graphite to CO (and/or CO2) gas [2, 3]. Seminal studies during the 1970’s measured the bulk concentration and isotopic compositions of C from Apollo 11 samples, and identified several carbonaceous compounds, including: (a) gaseous (CO, CO2, and traces of CH4), (b) metallic carbide, and (c) potentially elemental carbon [4-6]. These studies reported a relatively broad range of C contents (~100-400 μg/g) and isotopic values (δC13 = -30 to +20), and suggested that these heterogeneities can be explained by contribution from multiple factors, including: (a) indigenous carbon, (b) solar wind implantation, (c) bombardment and/or meteorite impact, and (d) terrestrial contamination [5,6]. However, unequivocal observations of magmatic graphite in lunar basalts have never been made. Macromolecular carbon (MMC)—graphitic carbon varying from nearly amorphous to highly crystalline varieties—was identified as inclusions hosted by igneous pyroxenes from Martian meteorites and were attributed to being indigenous to Mars [8]. The authors carefully considered the textural and mineralogical relationship of the MMC phases, and concluded that the subset of MMC located within and/or adjacent to cracks, or at a disrupted surface (e.g., cut) were most consistent with terrestrial contamination. The near absence of con-firmed instances of lunar magmatic MMC within the literature [9], combined with the wide range of isotopic values and bulk carbon contents measured in lunar bas-alts begs the question as to whether previously measured carbon is of an indigenous origin, or the result of terrestrial contamination. Using Raman spectroscopy, we have observed MMC in lunar basalts subjected to different forms of anthropogenic modification related to sample preparation including polished sections, sawn surfaces, and fractured surfaces adjacent to sawn sur-faces. We have observed MMC of unknown origin in all of these settings. Here we report the preliminary textural and spectroscopic characteristics of MMC hosted within the groundmass of Apollo 15 (15556) and Apollo 11 basalts (10044) as part of our ongoing investigation of the origin of these carbonaceous materials.

lunar↗
NASA NTRS1994

Scaling craters in carbonates: Electron paramagnetic resonance analysis of shock damage

Carbonate samples from the 8.9-Mt nuclear (near-surface explosion) crater, OAK, and a terrestrial impact crater, Meteor Crater, were analyzed for shock damage using electron paramagnetic resonance (EPR). Samples from below the OAK apparent crater floor were obtained from six boreholes, as well as ejecta recovered from the crater floor. The degree of shock damage in the carbonate material was assessed by comparing the sample spectra to the spectra of Solenhofen and Kaibab limestone, which had been skocked to known pressures. Analysis of the OAK Crater borehole samples has identified a thin zone of allocthonous highly shocked (10-13 GPa) carbonate material underneath the apparent crater floor. This approx. 5- to 15-m-thick zone occurs at a maximum depth of approx. 125 m below current seafloor at the borehole, sited at the initial position of the OAK explosive, and decreases in depth towards the apparent crater edge. Because this zone of allocthonous shocked rock delineates deformed rock below, and a breccia of mobilized sand and collapse debris above, it appears to outline the transient crater. The transient crater volume inferred in this way is found to by 3.2 +/- 0.2 times 10(exp 6)cu m, which is in good agreement with a volume of 5.3 times 10(exp 6)cu m inferred from gravity scaling of laboratory experiments. A layer of highly shocked material is also found near the surface outside the crater. The latter material could represent a fallout ejecta layer. The ejecta boulders recovered from the present crater floor experienced a range of shock pressures from approx. 0 to 15 GPa with the more heavily shocked samples all occurring between radii of 360 and approx. 600 m. Moreover, the fossil content, lithology and Sr isotopic composition all demonstrate that the initial position of the bulk of the heavily shocked rock ejecta sampled was originally near surface rock at initial depths in the 32 to 45-m depth (below sea level) range. The EPR technique is also sensitive to prehistoric shock damage. This is demonstrated by our study of shocked Kaibab limestone from the 49,000-year-old Meteor (Barringer) Crater Arizona.

Polanskey, Carol A.↗
NASA NTRS2000

The Next Generation MOD: A Microchip Amino Acid Analyzer for Detecting Extraterrestrial Life

The MOD (Mars Organic Detector) instrument which has selected for the definition phase of the BEDS package on the 2005 Mars Explorer Program spacecraft is designed to simply detect the presence of amino acids in Martian surface samples at a sensitivity of a few parts per billion (ppb). An additional important aspect of amino acid analyses of Martian samples is identifying and quantifying which compounds are present, and also distinguishing those produced abiotically from those synthesized by either extinct or extant life. Amino acid homochirality provides an unambiguous way of distinguishing between abiotic vs. biotic origins. Proteins made up of mixed D- and L-amino acids would not likely have been efficient catalysts in early organisms because they could not fold into bioactive configurations such as the a-helix. However, enzymes made up of all D-amino acids function just as well as those made up of only L-amino acids, but the two enzymes use the opposite stereoisomeric substrates. There are no biochemical reasons why L-amino acids would be favored over Damino acids. On Earth, the use of only L-amino acids in proteins by life is probably simply a matter of chance. We assume that if proteins and enzymes were a component of extinct or extant life on Mars, then amino acid homochirality would have been a requirement. However, the possibility that Martian life was (or is) based on D-amino acids would be equal to that based on L-amino acids. The detection of a nonracemic mixture of amino acids in a Martian sample would be strong evidence for the presence of an extinct or extant biota on Mars. The finding of an excess of D-amino acids would provide irrefutable evidence of unique Martian life that could not have been derived from seeding the planet with terrestrial life (or the seeding of the Earth with Martian life). In contrast, the presence of racemic amino acids, along with non-protein amino acids such as alpha-aminoisobutyric acid and isovaline, would be indicative of an abiotic origin, although we have to consider the possibility that the racemic amino acids were generated from the racemization of biotically produced amino acids.

Mathies, R. A.↗
DOE OSTI2020

Machine learning to predict biomass sorghum yields under future climate scenarios

Crop yield modeling is critical in the design of national strategies for agricultural production, particularly in the context of a changing climate. Forecasting yields of bioenergy crops at fine spatial resolutions can help to evaluate near-term and long-term pathways for scaling up bio-based fuel and chemical production, and for understanding the impacts of abiotic stressors such as severe droughts and temperature extremes on potential biomass supply. In this work we used a large dataset of 28,364 Sorghum bicolor yield samples (uniquely identified by county and year of observation), environmental variables, and multiple approaches to analyze historical trends in sorghum productivity across the USA. We selected the most accurate machine learning approach (a variation of the random forest approach) to predict future trends in sorghum yields under four greenhouse gas (GHG) emission scenarios and two irrigation regimes. We identified irrigation practices, vapor pressure deficit, and time (a proxy for technological improvement) as the most important predictors of sorghum productivity. Our results showed a decreasing trend of sorghum yields over future years (on average 2.7% from 2018 to 2099), with greater decline under a high GHG emissions scenario (3.8%) and in the absence of irrigation (4.6%). Geographically, we observed the steepest predicted declines in the Great Lakes (8.2%), Upper Midwest (7.5%), and Heartland (6.7%) regions. Our study demonstrates the use of machine learning to identify environmental controllers of sorghum biomass yield and predict yields with reasonable accuracy. These results can inform the development of more realistic biomass supply projections for bioenergy if sorghum production is scaled up. (c) 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

09 BIOMASS FUELS↗
DOE OSTI2021

Effects of spatial energy distribution-induced porosity on mechanical properties of laser powder bed fusion 316L stainless steel

Laser powder bed fusion (LPBF) additive manufacturing (AM) offers a variety of advantages over traditional manufacturing, however its usefulness for manufacturing of high-performance components is currently hampered by internal defects (porosity) created during the LPBF process that have an unknown impact on global mechanical performance. By inducing porosity distributions through variations in print energy density and inspecting the resulting tensile samples using computed tomography, nearly 50,000 pores across 75 samples were identified. Porosity characteristics were quantitatively extracted from inspection data and compared with mechanical properties to understand the strength of relationships between porosity and global tensile performance. Useful porosity characteristics were identified for prediction of part performance. Results indicate that ductility and strain at ultimate tensile strength are the global tensile properties most significantly impacted by porosity and can be predicted with reasonable accuracy using simple porosity shape descriptors such as volume, diameter, and surface area. Moreover, it was found that the largest pores influenced behavior most significantly. Specifically, pores in excess of 125 µm in diameter were found to be a sufficient threshold for property estimation. These results establish an initial understanding of the complex defect-performance relationship in AM 316L stainless steel and can be leveraged to develop certification standards and improve confidence in part quality and reliability for the broader set of engineering alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by the solution of Darcy’s partial differential equation for a given permeability field. The subsurface permeability is modeled as a random field since it is known only up to statistical properties. This induces uncertainty in the computed pressure. Solving the partial differential equation for an ensemble of random permeability simulations enables estimating a probability distribution for the pressure at the critical location. These simulations are computationally expensive, and practitioners often need rapid online guidance for real-time pressure management. An ensemble of numerical partial differential equation solutions is used to construct a Gaussian process regression model that can quickly predict the pressure at the critical location as a function of the extraction rate and permeability realization. The Gaussian process surrogate analyzes the ensemble of numerical pressure solutions at the critical location as noisy observations of the true pressure solution, enabling robust inference using the conditional Gaussian process distribution. Our first novel contribution is to identify a sampling methodology for the random environment and matching kernel technology for which fitting the Gaussian process regression model scales as O ( n log n ) instead of the typical O ( n 3 ) rate in the number of samples n used to fit the surrogate. The surrogate model allows almost instantaneous predictions for the pressure at the critical location as a function of the extraction rate and permeability realization. Our second contribution is a novel algorithm to calibrate the uncertainty in the surrogate model to the discrepancy between the true pressure solution of Darcy’s equation and the numerical solution. Finally, although our method is derived for building a surrogate for the solution of Darcy’s equation with a random permeability field, the framework broadly applies to solutions of other partial differential equations with random coefficients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Random field optimization

Herein we present a new modeling paradigm for optimization that we call random field optimization. Random fields are a powerful modeling abstraction that aims to capture the behavior of random variables that live on infinite-dimensional spaces (e.g., space and time) such as stochastic processes (e.g., time series, Gaussian processes, and Markov processes), random matrices, and random spatial fields. This paradigm involves sophisticated mathematical objects (e.g., stochastic differential equations and space-time kernel functions) and has been widely used in neuroscience, geoscience, physics, civil engineering, and computer graphics. Despite of this, however, random fields have seen limited use in optimization; specifically, existing optimization paradigms that involve uncertainty (e.g., stochastic programming and robust optimization) mostly focus on the use of finite random variables. This trend is rapidly changing with the advent of statistical optimization (e.g., Bayesian optimization) and multi-scale optimization (e.g., integration of molecular sciences and process engineering). Our work extends a recently-proposed abstraction for infinite-dimensional optimization problems by capturing more general uncertainty representations. Moreover, we discuss solution paradigms for this new class of problems based on finite transformations and sampling, and identify open questions and challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Incorporating civilian radioxenon background estimates in anomaly detection

A nuclear explosion screening exercise in 2023 (Maurer et al., 2023) found challenges with discerning anomalous radioxenon activity concentrations relative to elevated background concentrations. Research has continued into methods to detect anomalous radioxenon concentrations by comparing samples to estimates of atmospheric radioxenon background concentrations caused by releases at nuclear reactors or medical isotope production facilities. A new approach estimates the sample concentrations using time-varying radioxenon release rates obtained using optimization techniques that constrain the facility release rates to plausible amounts based on historical data or facility knowledge. The purpose of the optimization is to determine whether any combination of plausible release rates from emitting facilities can explain a series of radioxenon measurements at one or more sampling stations. A case study uses radioxenon data collected at three locations in western Europe for a month in 2021 and considers releases from 77 locations. Fewer samples are identified as being anomalous using a simplistic flagging rule than from an application of the current International Monitoring System (IMS) activity concentration-level rule.

Environmental sciences↗
DOE OSTI2020

Large-Grained Cylindrical Block Copolymer Morphologies by One-Step Room-Temperature Casting

We report a facile method of ordering block copolymer (BCP) morphologies in which the conventional two-step casting and annealing steps are replaced by a single-step process where microphase separation and grain coarsening are seamlessly integrated within the casting protocol. This is achieved by slowing down solvent evaporation during casting by introducing a non-volatile solvent into the BCP casting solution what effectively prolongs the duration of the grain-growth phase. We demonstrate the utility of this solvent evaporation annealing (SEA) method by producing well-ordered large molecular-weight BCP thin films in a total processing time shorter than 3 minutes without resorting to any extra laboratory equipment other than a basic casting-device i.e., spin- or blade-coater. By analyzing the morphologies of the quenched samples, we identify a relatively narrow range of polymer concentration in the wet film, just above the order-disorder concentration, to be critical for obtaining large-grained morphologies. This finding is corroborated by the analysis of the grain-growth kinetics of horizontally-oriented cylindrical domains where relatively large growth exponents (1/2) are observed, indicative of a more rapid defect-annihilation mechanism in the concentrated BCP solution than in thermally-annealed BCP melts. Furthermore, the analysis of temperature-resolved kinetics data allows us to calculate the Arrhenius activation energy of the grain-coarsening in this one-step BCP ordering process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Microbial species and intraspecies units exist and are maintained by ecological cohesiveness coupled to high homologous recombination

Abstract Recent genomic analyses have revealed that microbial communities are predominantly composed of persistent, sequence-discrete species and intraspecies units (genomovars), but the mechanisms that create and maintain these units remain unclear. By analyzing closely-related isolate genomes from the same or related samples and identifying recent recombination events using a novel bioinformatics methodology, we show that high ecological cohesiveness coupled to frequent-enough and unbiased (i.e., not selection-driven) horizontal gene flow, mediated by homologous recombination, often underlie these diversity patterns. Ecological cohesiveness was inferred based on greater similarity in temporal abundance patterns of genomes of the same vs. different units, and recombination was shown to affect all sizable segments of the genome (i.e., be genome-wide) and have two times or greater impact on sequence evolution than point mutations. These results were observed in bothSalinibacter ruber, an environmental halophilic organism, andEscherichia coli, the model gut-associated organism and an opportunistic pathogen, indicating that they may be more broadly applicable to the microbial world. Therefore, our results represent a departure compared to previous models of microbial speciation that invoke either ecology or recombination, but not necessarily their synergistic effect, and answer an important question for microbiology: what a species and a subspecies are.

Science & Technology - Other Topics↗
DOE OSTI2023

Mapping brucellosis risk in Kenya and its implications for control strategies in sub-Saharan Africa

In Sub-Saharan Africa (SSA), effective brucellosis control is limited, in part, by the lack of long-term commitments by governments to control the disease and the absence of reliable national human and livestock population-based data to inform policies. Therefore, we conducted a study to establish the national prevalence and develop a risk map for Brucella spp. in cattle to contribute to plans to eliminate the disease in Kenya by the year 2040. We randomly generated 268 geolocations and distributed them across Kenya, proportionate to the area of each of the five agroecological zones and the associated cattle population. Cattle herds closest to each selected geolocation were identified for sampling. Up to 25 cattle were sampled per geolocation and a semi-structured questionnaire was administered to their owners. We tested 6,593 cattle samples for Brucella immunoglobulin G (IgG) antibodies using an Enzyme-linked immunosorbent assay (ELISA). We assessed potential risk factors and performed spatial analyses and prevalence mapping using approximate Bayesian inference implemented via the integrated nested Laplace approximation (INLA) method. The national Brucella spp. prevalence was 6.8% (95% CI: 6.2–7.4%). Exposure levels varied significantly between agro-ecological zones, with a high of 8.5% in the very arid zone with the lowest agricultural potential relative to a low of 0.0% in the agro-alpine zone with the highest agricultural potential. Additionally, seroprevalence increased with herd size, and the odds of seropositivity were significantly higher for females and adult animals than for males or calves. Similarly, animals with a history of abortion, or with multiple reproductive syndromes had higher seropositivity than those without. At the herd level, the risk of Brucella spp. transmission was higher in larger herds, and herds with a history of reproductive problems such as abortion, giving birth to weak calves, or having swollen testes. Geographic localities with high Brucella seroprevalence occurred in northern, eastern, and southern regions of Kenya all primarily characterized by semi-arid or arid agro-ecological zones dominated by livestock pastoralism interspersed with vast areas with mixed livestock-wildlife systems. The large spatial extent of our survey provides compelling evidence for the widespread geographical distribution of brucellosis risk across Kenya in a manner easily understandable for policymakers. Our findings can provide a basis for risk-stratified pilot studies aiming to investigate the cost-effectiveness and efficacy of singular and combined preventive intervention strategies that seek to inform Kenya’s Brucellosis Control Policy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Statistical analysis of Al III and C III ] emission lines as virial black hole mass estimators in quasars

We test the usefulness of the intermediate ionisation lines Al IIIλ1860 and C III]λ1909 as reliable virial mass estimators for quasars. We identified a sample of 309 quasars from the Sloan Digital Sky Survey Data Release 16 (SDSS DR16) in the redshift range 1.2 ≤ z ≤ 1.4 that have [O II]λ3728 recorded on the same spectrum as Al IIIλ1860, Si III]λ1892, and C III]λ1909. We set the systemic quasar redshift using careful measurements of [O II]λ3728. We then classified the sources as Population A (Pop. A), extreme Population A (Pop. xA), and Population B (Pop. B), and analysed the 1900 Å blend using multi-component models to look for systematic line shifts of Al IIIλ1860 and C III]λ1909 along the quasar main sequence. We do not find significant shifts of the Al IIIλ1860 line peak in Pop. B or in the vast majority of Pop. A. For Pop. xA, a small median blueshift of -250 km s -1 was observed, motivating a decomposition of the Al III line profile into a virialised component centred at rest frame and a blueshifted component for an outflow emission. For Pop. B objects, we proved the empirical necessity to fit a redshifted very broad component, clearly seen in C III], and analysed the physical implications on a Pop. B composite spectrum using CLOUDY simulations. We find consistent black hole mass estimations using Al III and C III] as virial estimators for the bulk of Pop. A. Al III (and even C III]) is a reliable virial black hole mass estimator for Pop. A and Pop. B objects. The Pop. xA sources deserve special attention due to the significant blueshifted excess observed in the line profile of Al III, although it is not as large as the excess observed in C IVλ1549.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Abundance analysis of APOGEE spectra for 58 metal-poor stars from the bulge spheroid

The central part of the Galaxy hosts a multitude of stellar populations, including the spheroidal bulge stars, stars moved to the bulge through secular evolution of the bar, inner halo, inner thick disc, inner thin disc, as well as debris from past accretion events. We identified a sample of 58 candidate stars belonging to the stellar population of the spheroidal bulge, and analyse their abundances. The present calculations of Mg, Ca, and Si lines are in agreement with the ASPCAP abundances, whereas abundances of C, N, O, and Ce are re-examined. We find normal α-element enhancements in oxygen, similar to magnesium, Si, and Ca abundances, which are typical of other bulge stars surveyed in the optical in Baade’s Window. The enhancement of [O/Fe] in these stars suggests that they do not belong to accreted debris. No spread in N abundances is found, and none of the sample stars is N-rich, indicating that these stars are not second generation stars originated in globular clusters. Ce instead is enhanced in the sample stars, which points to an s-process origin such as due to enrichment from early generations of massive fast rotating stars, the so-called spinstars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A subcellular biochemical model for T6SS dynamics reveals winning competitive strategies

Abstract The type VI secretion system (T6SS) is a broadly distributed interbacterial weapon that can be used to eliminate competing bacterial populations. Although unarmed target populations are typically used to study T6SS function in vitro, bacteria most likely encounter other T6SS-armed competitors in nature. However, the connection between subcellular details of the T6SS and the outcomes of such mutually lethal battles is not well understood. Here, we incorporate biological data derived from natural competitors of Vibrio fischeri light organ symbionts to build a biochemical model for T6SS at the single-cell level, which we then integrate into an agent-based model (ABM). Using the ABM, we isolate and experiment with strain-specific physiological differences between competitors in ways not possible with biological samples to identify winning strategies for T6SS-armed populations. Through in vitro experiments, we discover that strain-specific differences exist in T6SS activation speed. ABM simulations corroborate that faster activation is dominant in determining survival during competition. Once competitors are fully activated, the energy required for T6SS creates a tipping point where increased weapon building and firing becomes too costly to be advantageous. Through ABM simulations, we identify the threshold where this transition occurs in the T6SS parameter space. We also find that competitive outcomes depend on the geometry of the battlefield: unarmed target cells survive at the edges of a range expansion where unlimited territory can be claimed. Alternatively, competitions within a confined space, much like the light organ crypts where natural V. fischeri compete, result in the rapid elimination of the unarmed population.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Intricate short-range order in GeSn alloys revealed by atomistic simulations with highly accurate and efficient machine-learning potentials

GeSn alloys hold promise for silicon-compatible integrated applications in electronics, photonics, and topological quantum devices. However, understanding their intricate structures using density functional theory (DFT) calculations is hindered by spatiotemporal constraints. To overcome this limitation, we develop highly accurate and efficient machine-learning interatomic potentials based on a neuroevolution potential approach with farthest point sampling on a comprehensive DFT data set. The application of the developed machine-learning potential in large-scale atomistic simulations bridges the spatiotemporal gap between modeling and advanced characterizations, and facilitates the discovery of structural intricacies in GeSn alloys. Through extensive statistical sampling, we identify a type of short-range order (SRO) that is distinguished by both its structural signature and electronic band gap from the SRO structure previously predicted. Modeling based on a large simulation cell reveals the coexistence of nano SRO domains with various degrees of ordering, demonstrating a complex spatial heterogeneity of SRO structure. Finally, our study not only reinforces the significance of fine-level structural information in alloys, but it also constitutes an effective framework for exploring SRO in a broad range of complex alloys based on highly accurate and effective machine-learning potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Enhanced resonant ultrasound spectroscopy for measurement of the elastic properties of multi-material systems

Understanding the elastic properties of materials is critical for their safe incorporation and predictable performance. Current methods of bulk elastic characterization often have notable limitations for in situ structural applications, with usage restricted to simple geometries and material distributions. To address these existing issues, this study sought to expand the capabilities of resonant ultrasound spectroscopy (RUS), an established nondestructive evaluation method, to include the characterization of isotropic multi-material samples. In this work, finite-element-based RUS analysis consisted of numerical simulations and experimental testing of composite samples comprised of material pairs with varying elasticity and density contrasts. Utilizing genetic algorithm inversion and mode matching, our results demonstrate that elastic properties of multi-material samples can be reliably identified within several percent of known or nominal values using a minimum number of identified resonance modes, given sample mass is held consistent. The accurate recovery of material properties for composite samples of varying material similarity and geometry expands the pool of viable samples for RUS and advances the method towards in situ inspection and evaluation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cation and Anion Channelrhodopsins: Sequence Motifs and Taxonomic Distribution

Cation and anion channelrhodopsins (CCRs and ACRs, respectively) primarily from two algal species, Chlamydomonas reinhardtii and Guillardia theta, have become widely used as optogenetic tools to control cell membrane potential with light. We mined algal and other protist polynucleotide sequencing projects and metagenomic samples to identify 75 channelrhodopsin homologs from four channelrhodopsin families, including one revealed in dinoflagellates in this study. We carried out electrophysiological analysis of 33 natural channelrhodopsin variants from different phylogenetic lineages and 10 metagenomic homologs in search of sequence determinants of ion selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins. Our results show that association of a reduced number of glutamates near the conductance path with anion selectivity depends on a wider protein context, because prasinophyte homologs with a glutamate pattern identical to that in cryptophyte ACRs are cation selective. Desensitization is also broadly context dependent, as in one branch of stramenopile ACRs and their metagenomic homologs, its extent roughly correlates with phylogenetic relationship of their sequences. Regarding spectral tuning, we identified two prasinophyte CCRs with red-shifted spectra to 585 nm. They exhibit a third residue pattern in their retinal-binding pockets distinctly different from those of the only two types of red-shifted channelrhodopsins known (i.e., the CCR Chrimson and RubyACRs). In cryptophyte ACRs we identified three specific residue positions in the retinal-binding pocket that define the wavelength of their spectral maxima. Lastly, we found that dinoflagellate rhodopsins with a TCP motif in the third transmembrane helix and a metagenomic homolog exhibit channel activity. Channelrhodopsins are widely used in neuroscience and cardiology as research tools and are considered prospective therapeutics, but their natural diversity and mechanisms remain poorly characterized. Genomic and metagenomic sequencing projects are producing an ever-increasing wealth of data, whereas biophysical characterization of the encoded proteins lags behind. In this study, we used manual and automated patch clamp recording of representative members of four channelrhodopsin families, including a family in dinoflagellates that we report in this study. Our results contribute to a better understanding of molecular determinants of ionic selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins.

59 BASIC BIOLOGICAL SCIENCES↗