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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

On Neural Architectures for Astronomical Time-series Classification with Application to Variable Stars

Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse data sets has thus far hampered a direct intercomparison of different approaches. Here we perform the first comprehensive study of variants of NN-based learning and inference for astronomical time series, aiming to provide the community with an overview on relative performance and, hopefully, a set of best-in-class choices for practical implementations. In both supervised and self-supervised contexts, we study the effects of different time-series-compatible layer choices, namely the dilated temporal convolutional neural network (dTCNs), long-short term memory NNs, gated recurrent units and temporal convolutional NNs (tCNNs). Additionally, we also study the efficacy and performance of encoder-decoder (i.e., autoencoder) networks compared to direct classification networks, different pathways to include auxiliary (non-time-series) metadata, and different approaches to incorporate multi-passband data (i.e., multiple time series per source). Performance—applied to a sample of 17,604 variable stars (VSs) from the MAssive Compact Halo Objects (MACHO) survey across 10 imbalanced classes—is measured in training convergence time, classification accuracy, reconstruction error, and generated latent variables. We find that networks with recurrent NNs generally outperform dTCNs and, in many scenarios, yield to similar accuracy as tCNNs. In learning time and memory requirements, convolution-based layers perform better. We conclude by discussing the advantages and limitations of deep architectures for VS classification, with a particular eye toward next-generation surveys such as the Legacy Survey of Space and Time, the Roman Space Telescope, and Zwicky Transient Facility.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Convolutional Neural Networks for Hydrometeor Classification using Dual Polarization Doppler Radars

Traditional fuzzy logic hydrometeor classification algorithm is a common way to classify precipitation type from dual polarization doppler radar. We propose a deep learning-based method to estimate hydrometeors efficiently using observed radar variables such as horizontal reflectivity (Z H ), differential reflectivity (Z DR ), correlation coefficient (ρ HV ) and specific differential phase (K DP ) from National Weather Service NEXRAD collected at Vance AFB facility at the first elevation angle from January 1st, 2015 to July 31th, 2019. We stack matrices of values from these four polarimetric variables as one 3D array. Samples are preprocessed and divided into training, validation and test set with four target hydrometeor categories (Ice Crystals (IC), Dry Snow (DS), Light and/or Moderate Rain (RA) and Big Drops (rain) (BD)). We developed and optimized five Convolutional Neural Networks (CNNs) architectures and achieved an accuracy of 87.23% and 93.736% respectively using modified ResNet with two different input data selection strategies for hydrometeor classification. Training data selection strategies were important to ensure use of available samples in training for robust performance evaluated by applying the models to novel time period beyond what was use to train the model. Seasonal variation in atmospheric conditions lead to seasonal patterns of liquid vs solid forms of precipitation, that poses challenge for classifier and offer insights into domain specific approaches required for problem of hydrometeor identification. Computationally efficient and scalable approach for classification of hydrometeors offer opportunties to effectively use the large volumes of rich time series of radar observations that are becoming increasingly available.

Lu, Yuping↗
DOE OSTI2020

Rapid Determination of Uranium Isotopic Abundance from Cotton Swipes: Direct Extraction via a Planar Surface Reader and Coupling to a Microplasma Ionization Source

The collection of solid particulates and liquids from surfaces by the use of cloth swipes is fairly ubiquitous. In such methods, there is a continuous concern regarding the ability to locate and quantitatively sample the analyte species from the material. In this effort, we demonstrate the initial coupling of an Advion Plate Express plate reader to a liquid sampling–atmospheric pressure glow discharge (LS-APGD) microplasma ionization source with an Orbitrap mass spectrometer to perform uranium isotopic analyses of solution residues on cotton swipes. The Plate Express employs a sampling probe head to engage and seal against the swipe surface. Subsequentially, the analyte residues are desorbed and transported within a 2% HNO 3 electrolyte flow to the ionization source. Quantitative recoveries were observed following a single 30 s extraction step, with the absolute mass sampled per extraction being ~100 ng. While the intrasample variability in the analytical responses for triplicate sampling of the same swipe yield ~30% RSD, this lack of precision is offset by the ability to determine isotope ratios for enriched uranium specimens with a precision of better than 10% RSD. Pooled, intersample precision ( n = 9) was found to be <5%RSD across the various sample compositions. Finally, 235 U/ 238 U determinations (ranging from 0.053 to 1.806) were accurate with errors of <10%, absolute. The 234 U- and 236 U-inclusive ratios were determined with similar accuracy in enriched samples. While the driving force for the effort is in the realm of nuclear nonproliferation efforts, the ubiquitous use of cloth swipes across many application areas could benefit from this convenient approach, including the use of versatile, reduced-format mass spectrometer systems.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2016

Comparison of dielectric properties of additively manufactured vs. solvent cast polyimide dielectrics

The permittivity, dielectric loss, and DC dielectric breakdown strength of additively manufactured, solvent-cast, and commercial polyimide films are reported As expected, commercial films performed better than both AM and solvent-cast lab-made films. Solvent-cast films generally performed better than AM films, although performance depended on the optimization of the material for the specific deposition technique. The most significant degradation of performance in all the lab-made films was in the dispersion of both the x/Df measurements and the dielectric breakdown strength (Weibull β). Commercial films had a breakdown strength of 4891 kV/cm and β = 13.0 whereas the highest performing lab-made films had a breakdown strength of 4072 kV/cm and β = 3.8. Furthermore, this increase in dispersion in all the lab-made samples is attributed to higher variability in the preparation, a higher defect level related to fabrication in the lab environment and, for some AM samples, to morphology/topology features resulting from the deposition technique.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluation of a parasite-density based pooled targeted amplicon deep sequencing (TADS) method for molecular surveillance of Plasmodium falciparum drug resistance genes in Haiti

Sequencing large numbers of individual samples is often needed for countrywide antimalarial drug resistance surveillance. Pooling DNA from several individual samples is an alternative cost and time saving approach for providing allele frequency (AF) estimates at a population level. Using 100 individual patient DNA samples of dried blood spots from a 2017 nationwide drug resistance surveillance study in Haiti, we compared codon coverage of drug resistance-conferring mutations in four Plasmodium falciparum genes ( crt , dhps , dhfr , and mdr1 ), for the same deep sequenced samples run individually and pooled. Samples with similar real-time PCR cycle threshold (Ct) values (+/- 1.0 Ct value) were combined with ten samples per pool. The sequencing success for samples in pools were higher at a lower parasite density than the individual samples sequence method. The median codon coverage for drug resistance-associated mutations in all four genes were greater than 3-fold higher in the pooled samples than in individual samples. The overall codon coverage distribution for pooled samples was wider than the individual samples. The sample pools with < 40 parasites/μL blood showed more discordance in AF calls for dhfr and mdr1 between the individual and pooled samples. This discordance in AF estimation may be due to low amounts of parasite DNA, which could lead to variable PCR amplification efficiencies. Grouping samples with an estimated ≥ 40 parasites/μL blood prior to pooling and deep sequencing yielded the expected population level AF. Pooling DNA samples based on estimates of > 40 parasites/μL prior to deep sequencing can be used for rapid genotyping of a large number of samples for these four genes and possibly other drug resistant markers in population-based studies. As Haiti is a low malaria transmission country with very few mixed infections and continued chloroquine sensitivity, the pooled sequencing approach can be used for routine national molecular surveillance of resistant parasites.

Louha, Swarnali (ORCID:0000000207778507)↗
DOE OSTI2026

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the hillslope of East River (ER) near Pump House (PH) at Mount Crested Butte (ER-PHS1 to 4), and the other four are in the Snodgrass Mountain (SG) area (SG-EHS5 to 8). In terms of vegetation cover, three sites are in montane grasslands (ER-PHS1, ER-PHS2, and SG-EHS5), three are below evergreen conifer canopy (ER-PHS3, SG-EHS6, and SG-EHS7), and two are below deciduous aspen canopy (ER-PHS4 and SG-EHS8). The monitoring period began in October 2019 at the East River sites, in October 2020 at SG-EHS5 and SG-EHS6, and in October 2021 at SG-EHS7 and SG-EHS8. In September 2024, all four East River sites were fully retired. The four Snodgrass Mountain sites remain active. Each site is equipped with a comprehensive suite of meteorological sensors on a tripod and soil sensors that measure weather, energy fluxes, and soil variables. This data package includes measurements from ten different types of sensors and up to thirteen individual sensors per site, including (1) a weather station (measurement height ranges from 2.8~3.8 meters (m) above ground), (2) a quantum sensor for photosynthetic active radiation (PAR) (2.4~3.3m), (3) a net radiometer (1.7~2.1m), (4) an infrared radiometer (1.6~2.2m), (5) a sonic distance sensor (1.5~1.9m), (6) a soil carbon dioxide (CO2) flux chamber (0m), (7) a soil heat flux plate (-0.05m below ground), (8) a soil oxygen sensor (-0.3m), (9) a soil water potential sensor (-0.3m), and (10) soil water content sensors at 3~4 depths (-1.15 ~ -0.1m). A total of twenty-three variables is reported in this data package, including (1) atmospheric variables: air temperature (TA), atmospheric pressure (PA), vapor pressure (VP), and vapor pressure deficit (VPD), (2) precipitation variables: rain precipitation (P) and snow depth (D_SNOW), (3) energy fluxes variables: four-component net radiation (NETRAD) (shortwave/longwave incoming/outgoing radiation, SW_IN, SW_OUT, LW_IN, LW_OUT), photosynthetic photon flux density (PPFD), and soil heat flux (G), (4) soil variables: soil water content (SWC), soil water potential (SWP), soil temperature (TS), soil bulk electrical conductivity (COND_SOIL), and soil gaseous oxygen concentration (O2_SOIL), (5) wind variables: two-dimensional wind speed (WS), gust speed (WS_MAX), and wind direction (WD), and (6) surface variables: surface infrared temperature (T_CANOPY) and soil CO2 flux (CO2_SOIL). Please see the Methods section for data processing and QA/QC steps taken to generate the hourly datasets. The following files are included in this data package (notes on version: v{x}-{y}, where x is the metadata version, and y is the data version, when applicable): (1) “metadata_site_v{x}-{y}.csv” - a site metadata file that summarizes location information of all sites, including site ID, description, coordinates, timeframe, elevation, and vegetation cover, (2) “metadata_instrument_v{x}-{y}.csv” - an instrument metadata file that summarizes sensor information of all sites, including sensor manufacturer and model, measurement height, and sampling and averaging interval of all variables, (3) "data_{SITE_ID}_v{x}-{y}.csv" - eight data files that contain hourly data of each site indicated by {SITE_ID} in the filename, (4) “/figure/data_{SITE_ID}_v{x}-{y}.png" - eight figures that help visualize data of each site indicated by {SITE_ID} in the filename, (5) “/photo/*” - photos of each site indicated by {SITE_ID} in the filename, and (6) four file level metadata (flmd.csv) and data dictionary (*_dd.csv) files that summarize file, header, column, and variable information of all files. Notes: (1) Measurement height: Each variable name is followed by conventional positional qualifiers “H_V_R”, where H indicates the relative horizontal positions of that specific variable, V the vertical positions, and R the replicates. In this data package, only the vertical qualifier V varies, and V increases from the highest vertical position (V=1) to the lowest. Variables with the same qualifier are not necessarily measured by the same sensor, and the same variable with the same qualifier across different sites are not necessarily measured at the same height. Please refer to “metadata_instrument.csv” for the sensor information and measurement heights, and whether a variable is measured below the canopy. (2) Variable availability: Snow depth is not available at ER-PHS3 and SG-EHS7. SWC, soil temperature, and soil bulk EC at the deepest depth (<-1m) are not available at SG-EHS6 and SG-EHS7. The missing value code for numeric variables is -9999, except for SWP. For SWP, the missing value code is +9999, because SWP values are negative. (3) Sampling frequency: Please refer to “metadata_instrument.csv” for the increase of sampling frequency of some variables from 30-min to 1-min at ER-PHS1 to 4 in July 2020. (4) Sensors: While the methods of each sensor are not detailed, all sensors are commercially available, and their methods can be found in their manuals. Please refer to “metadata_instrument.csv” for the sensor manufacturer and model information. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Enhancement of Kerr Signal in Co Thin Films Incorporating Ag Nanoparticles Surrounded by TiO{sub 2}

In this study, we demonstrate the effect of localized surface plasmon resonance (LSPR) on magneto-optical (MO) activity of Co thin films incorporating Ag nanoparticles (NPs) so that the Ag NPs were surrounded by TiO{sub 2} (Ag [TiO{sub 2}]). The deposition of Co on glass substrates was performed using an oblique deposition technique, thereby obtaining a variable film thickness. Three samples of glass/Co, glass/Co/Ag NPs, and glass/Co/Ag [TiO{sub 2}] were compared with each other in terms of Kerr signal intensity. Our results show that while all samples have an easy axis in the film plane, the corresponding Kerr signal is amplified in the glass/Co/Ag [TiO{sub 2}] structure. A combination of SPR and light localization is the reasoning behind the amplification. These studies may open a new route in the research area of LSPR-based MO Kerr effect since the improved LSPR enhances MO properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

New compositional data on ancient mortars and plasters from Pompeii (Campania – Southern Italy): Archaeometric results and considerations about their time evolution

Highlights: • Mortar samples from Pompeii, with different constructive functions, were studied. • Characterization of the materials can be used for preparing compatible mortars. • Analogies and differences were highlighted to identify the constructive phases. • Preliminary statistic models were proposed to discriminate materials and constructive phases. Twenty-six samples of mortar used for various construction applications (joint mortars, floor mortars, filling mortars and plasters) were collected from different areas of the archaeological site of Pompeii (Campania - Sothern Italy). The mortar samples belong to various historical periods covering approximately 2000 years, from the 2nd century BC to the post excavation period (18–19th century). The samples were characterized employing Optical Microscopy (OM), X-ray Powder Diffraction (XRPD), X-ray Fluorescence (XRF), Electron Probe Micro Analysis (EPMA) and Raman Spectroscopy. Moreover, image analysis was carried out using JMicroVision software in order to determine the percentages of binder, macropores and aggregate, in terms of crushed ceramic fragments (cocciopesto), rock fragments and monocrystals. The application of these techniques allowed obtaining a complete chemical and minero-petrographic characterization of the samples, which may prove useful for preparing compatible repair mortars for future restoration works. The archaeometric study provided new data on the production technology of the mortars and the analogies and differences observed among the samples, enabled us to distinguish different constructive phases, thus confirming or rebutting the archaeological hypothesis on the dating of some samples. By combining compositional variables through the discriminant analysis, it was also possible to analyse the time evolution of the materials and to construct preliminary multivariate statistical models, helpful to identify the various typologies of mortars used in the different historical periods.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Characterizing Defect Dynamics in Silicon Carbide Using Symmetry-Adapted Collective Variables and Machine Learning Interatomic Potentials

Silicon carbide (SiC) divacancies are attractive candidates for spin-defect qubits possessing long coherence times and optical addressability. The high activation barriers associated with SiC defect formation and motion pose challenges for their study by first-principles molecular dynamics. In this work, we develop and deploy machine learning interatomic potentials (MLIPs) to accelerate defect dynamics simulations while retaining ab initio accuracy. We employ an active learning strategy comprising symmetry-adapted collective variable discovery and enhanced sampling to compile configurationally diverse training data, calculation of energies and forces using density functional theory (DFT), and training of an E(3)-equivariant MLIP based on the Allegro model. Here, the trained MLIP reproduces DFT-level accuracy in defect transition activation free energy barriers, enables the efficient and stable simulation of multidefect 216-atom supercells, and permits an analysis of the temperature dependence of defect thermodynamic stability and formation/annihilation kinetics to propose an optimal annealing temperature to maximally stabilize VV divacancies.

Computer simulations↗
DOE OSTI2018

Biasing Smarter, Not Harder, by Partitioning Collective Variables into Families in Parallel Bias Metadynamics

Molecular simulations of systems with multiple copies of identical atoms or molecules may require the biasing of numerous, degenerate collective variables (CVs) to accelerate sampling. Recently, a variation of metadynamics (MetaD) named parallel bias metadynamics (PBMetaD) has been shown to make biasing of many CVs more tractable. We extended the PBMetaD scheme so that it partitions degenerate CVs into families that share the same bias potential, consequently expediting convergence of the free-energy landscape. We tested our method, named parallel bias metadynamics with partitioned families, on 3, 21, and 78 CV systems and obtained an approximately proportional increase in convergence speed compared to standard PBMetaD.

Prakash, Arushi↗
DOE OSTI2017

Thiophene Derivatives on Gold and Molecular Dissociation Processes

Here, we report a systematic study of thiophene derivatives on gold surfaces. These molecules are of interest in molecular electronics, and the characracteristics of the thiophene–electrode interface in devices needs to be understood as it affects electron transport characteristics. Some experiments indicated S–C bond scission in contact with metals resulting in disruption of the $π$-electron system that affects charge transport, which would also be affected by presence of split-off chemisorbed sulfur. We explored this dissociation aspect by photoemission for the case of monocrystalline Au(111) surfaces and Au films grown on mica for a series of polythiophenes molecules ( n T, n = 1–4, 6) as well as for α,ω-diquaterthiophene (DH 4 T) and dihexylsexithiophene (DH6T). The S 2p X-ray photoelectron spectroscopy peaks are found to have complex line shapes corresponding to S atoms with different core level binding energies (CLBE). Density functional theory calculations of adsorption energies and CLBEs were performed for various adsorption configurations of thiophene on a perfect Au(111) plane and for comparison, calculations were also performed for bithiophene, terthiophene, alkenethiol, alkenethiol chain, and a broken thiophene related metallocycle, incorporating an Au adatom and an S atom. On the basis of these results we relate the different contributions to the S 2p peak to intact molecules on different adsorption sites and broken molecules. Calculations in particular show that the CLBEs for intact thiophene (1T) can be the same as for the alkene and alkanethiol cases as opposed to usual assumptions in the literature. The existence of intact thiophenes is confirmed by the presence of clear $π$ resonance peaks in the near edge X-ray fine structure (NEXAFS) spectra. Spontaneous dissociation appears to a variable extent in different samples, and we tentatively relate this to the presence of a more or less large number of steps and defects sites. X-ray induced beam damage was investigated for 1T and 3T using an intense synchrotron beam of 260 eV photons, and showed changes in the S 2p spectra related to S–C bond scission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Development of Nanocrystalline Graphite from Lignin Sources

Carbon composites are attractive to a variety of high-impact applications, such as carbon fibers, batteries, and vehicle parts, due to their multifunctional properties. The properties of carbon are highly dependent on the allotrope the carbon takes and the functionality, impurities, and defects contained within the structure. The increase in demand for sustainable carbon sources in energy storage devices motivates interest in understanding synthesis parameters of lignin value-added products. Also, as the dependence on oil for fuel decreases, alternative sources for carbon in many applications will be needed. In this work, the thermochemical conversion of lignin powders from different feedstocks was evaluated via small and wide-angle X-ray scattering techniques to resolve the amorphous, disordered, and crystalline domains present in the lignin carbons. Scattering analyses indicated an evolution of hierarchical structures along with an increase in ordered domains as a function of carbonization temperature. Qualitative and quantitative methods were used to describe isotropic scattering intensity profiles at multiple length scales. The use of power law models in the mesoscopic region served as the basis to describe morphological changes related to structural features, for example, graphene stacking, degree of roughness, and surface fractals. Kraft softwood and switchgrass produced carbon powder with the most crystalline domains and the least surface roughness. Softwoods reached the highest degree of crystallinity followed by switchgrass samples and had less variability in particle sizes. These results suggest lignin carbons extracted from softwoods and switchgrass are viable substitutes for graphite. Interpretation of X-ray scattering data from lignin carbon powders elucidates feedstock- and processing-dependent morphological features across multiple length scales providing a straightforward framework to evaluate the feasibility of leveraging lignin carbons for producing tunable application-specific materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Coherent Streamflow Variability in Monsoon Asia Over the Past Eight Centuries—Links to Oceanic Drivers

The Monsoon Asia region is home to ten of the world’s biggest rivers, supporting the lives of 1.7 billion people who rely on streamflow for water, energy, and food. Yet, a synoptic understanding of multi-centennial streamflow variability for this region is lacking. Here we produce the first large scale streamflow reconstruction over Monsoon Asia (63 stations in 16 countries), using a novel climate-informed dynamic algorithm that is skillful over 92% of the gauging stations. In this work, we show that streamflow in Monsoon Asia is spatially coherent, owing to common drivers from the Pacific, Indian, and Atlantic Oceans that exert their greatest influence over the Mekong and Chao Phraya basins. This work increases our understanding of streamflow variability over Monsoon Asia. We suggest that future water management in the region should be coordinated between basins, taking into account the states of the oceans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Variability and origins of grain boundary electric potential detected by electron holography and atom-probe tomography

A number of grain boundary phenomena in ionic materials, in particular, anomalous (either depressed or enhanced) charge transport, have been attributed to space charge effects. Developing effective strategies to manipulate transport behaviour requires deep knowledge of the origins of the interfacial charge, as well as its variability within a polycrystalline sample with millions of unique grain boundaries. Electron holography is a powerful technique uniquely suited for studying the electric potential profile at individual grain boundaries, whereas atom-probe tomography provides access to the chemical identify of essentially every atom at individual grain boundaries. Using these two techniques, we show in this paper that the space charge potential at grain boundaries in lightly doped, high-purity ceria can vary by almost an order of magnitude. We further find that trace impurities (<25 ppm), rather than inherent thermodynamic factors, may be the ultimate source of grain boundary charge. These insights suggest chemical tunability of grain boundary transport properties. A number of grain boundary phenomena in ionic materials, such as anomalous charge transport, have been attributed to space charge effects. Space charge potential at grain boundaries in lightly doped, high-purity ceria is now shown to vary by almost an order of magnitude.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Emergence of unprecedented climate change in projected future precipitation

The future time of emergence when precipitation changes due to anthropogenic influences begins to continuously exceed the previous maximum value is defined as the ‘tipping year’ Historical experiments and future experiments simulated by state-of-the-art climate models were utilized. A total of 510,000 time series from year 1856 to 2095 were generated by sampling the natural internal variability in precipitation. The time evolutions of internal variability in the whole time period were estimated from the combination of past and future experiments with preindustrial control experiments. A large ensemble size enabled an estimation of the probability density function of the tipping year at each grid point, providing precise information on the uncertainty of the projection. The tipping year of average precipitation emerges earlier in high latitudes than in lower latitudes. In some regions in lower latitudes and mid-latitudes, the tipping year of intense precipitation emerges faster than that of average precipitation. The tipping years of average and intense precipitation are earlier for higher anthropogenic forcing scenarios than for lower scenarios. The global average of the tipping year for intense precipitation might be attributed to the enhancement of the thermodynamic effect (moisture) rather than the dynamic effect (vertical motion).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The metagenomic data life-cycle: standards and best practices

Metagenomics data analyses from independent studies can only be compared if the analysis workflows are described in a harmonised way. In this overview, we have mapped the landscape of data standards available for the description of essential steps in metagenomics: (1) material sampling, (2) material sequencing (3) data analysis and (4) data archiving & publishing. Taking examples from marine research, we summarise essential variables used to describe material sampling processes and sequencing procedures in a metagenomics experiment. These aspects of metagenomics dataset generation have been to some extent addressed by the scientific community but greater awareness and adoption is still needed. We emphasise the lack of standards relating to reporting how metagenomics datasets are analysed and how the metagenomics data analysis outputs should be archived and published. We propose best practice as a foundation for a community standard to enable reproducibility and better sharing of metagenomics datasets, leading ultimately to greater metagenomics data reuse and repurposing.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Randomized Adiabatic Quantum Linear Solver Algorithm with Optimal Complexity Scaling and Detailed Running Costs

Solving linear systems of equations is a fundamental problem with a wide variety of applications across many fields of science, and there is increasing effort to develop quantum linear solver algorithms. Subaşı et al. [Phys. Rev. Lett. 122, 060504 (2019)] proposed a randomized algorithm inspired by adiabatic quantum computing, based on a sequence of random Hamiltonian simulation steps, with suboptimal scaling in the condition number 𝜅 of the linear system and the target error 𝜖. Here we go beyond these results in several ways. Firstly, using filtering [Lin and Tong, Quantum 4, 361 (2020)] and Poissonization techniques [Cunningham and Roland, ArXiv:2406.03972 (2024)], the algorithm complexity is improved to the optimal scaling 𝑂⁡(𝜅⁢log (1/𝜖))—an exponential improvement in 𝜖, and a shaving of a log 𝜅 scaling factor in 𝜅. Secondly, the algorithm is further modified to achieve constant factor improvements, which are vital as we progress towards hardware implementations on fault-tolerant devices. We introduce a cheaper randomized walk operator method replacing Hamiltonian simulation—which also removes the need for potentially challenging classical precomputations; randomized routines are sampled over optimized random variables; circuit constructions are improved. We obtain a closed formula rigorously upper bounding the expected number of times one needs to apply a block-encoding of the linear system matrix to output a quantum state encoding the solution to the linear system. The upper bound is 837⁢𝜅 at 𝜖 = 10 −10 for Hermitian matrices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The emerging role of 4D synchrotron X-ray micro-tomography for climate and fossil energy studies: five experiments showing the present capabilities at beamline 8.3.2 at the Advanced Light Source

Here, continuous improvements at X-ray imaging beamlines at synchrotron light sources have made dynamic synchrotron X-ray micro-computed tomography (SXR-µCT) experiments more routinely available to users, with a rapid increase in demand given its tremendous potential in very diverse areas. In this work a survey of five different four-dimensional SXR-µCT experiments is presented, examining five different parameters linked to the evolution of the investigated system, and tackling problems in different areas in earth sciences. SXR-µCT is used to monitor the microstructural evolution of the investigated sample with the following variables: (i) high temperature, observing in situ oil shale pyrolysis; (ii) low temperature, replicating the generation of permafrost; (iii) high pressure, to study the invasion of supercritical CO 2 in deep aquifers; (iv) uniaxial stress, to monitor the closure of a fracture filled with proppant, in shale; (v) reactive flow, to observe the evolution of the hydraulic properties in a porous rock subject to dissolution. For each of these examples, it is shown how dynamic SXR-µCT was able to provide new answers to questions related to climate and energy studies, highlighting the significant opportunities opened recently by the technique.

47 OTHER INSTRUMENTATION↗