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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Microbial Community and Functional Potential in the Midland Basin Reveal a Community Dominated by Both Thiosulfate and Sulfate-Reducing Microorganisms

The Permian Basin is the highest producing oil and gas reservoir in the United States. Hydrocarbon resources in this region are often accessed by unconventional extraction methods, including horizontal drilling and hydraulic fracturing. Despite the importance of the Permian Basin, there is no publicly available microbiological data from this region. We completed an analysis of Permian produced water samples to understand the dynamics present in hydraulically fractured wells in this region. We analyzed produced water samples taken from 10 wells in the Permian region of the Midland Basin using geochemical measurements, 16S rRNA gene sequencing, and metagenomic sequencing. Compared to other regions, we found that Permian Basin produced water was characterized by higher sulfate and lower total dissolved solids (TDS) concentrations, with a median of 1,110 mg/L and 107,000 mg/L. Additionally, geochemical measurements revealed the presence of frac hits, or interwell communication events where an established well is affected by the pumping of fracturing fluid into a new well. The occurrence of frac hits was supported by correlations between the microbiome and the geochemical parameters. Our 16S rRNA gene sequencing identified a produced water microbiome characterized by anaerobic, halophilic, and sulfur reducing taxa. Interestingly, sulfate and thiosulfate reducing taxa including Halanaerobium, Orenia, Marinobacter, and Desulfohalobium were the most prevalent microbiota in most wells. We further investigated the metabolic potential of microorganisms in the Permian Basin with metagenomic sequencing. We recovered 15 metagenome assembled genomes (MAGs) from seven different samples representing 6 unique well sites. These MAGs corroborated the high presence of sulfate and thiosulfate reducing genes across all wells, especially from key taxa including Halanaerobium and Orenia. The observed microbiome composition and metabolic capabilities in conjunction with the high sulfate concentrations demonstrate a high potential for hydrogen sulfide production in the Permian Basin. Additionally, evidence of frac hits suggests the possibility for the exchange of microbial cells and/or genetic information between wells. This exchange would increase the likelihood of hydrogen sulfide production and has implications for the oil and gas industry.

16S RNA↗
DOE OSTI2023

Uncertainty-driven dynamics for active learning of interatomic potentials

Machine learning (ML) models, if trained to data sets of high-fidelity quantum simulations, produce accurate and efficient interatomic potentials. Active learning (AL) is a powerful tool to iteratively generate diverse data sets. In this approach, the ML model provides an uncertainty estimate along with its prediction for each new atomic configuration. If the uncertainty estimate passes a certain threshold, then the configuration is included in the data set. Here we develop a strategy to more rapidly discover configurations that meaningfully augment the training data set. The approach, uncertainty-driven dynamics for active learning (UDD-AL), modifies the potential energy surface used in molecular dynamics simulations to favor regions of configuration space for which there is large model uncertainty. The performance of UDD-AL is demonstrated for two AL tasks: sampling the conformational space of glycine and sampling the promotion of proton transfer in acetylacetone. The method is shown to efficiently explore the chemically relevant configuration space, which may be inaccessible using regular dynamical sampling at target temperature conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Implementation of replica-exchange umbrella sampling in GAMESS

In GAMESS-US quantum chemistry package, both replica-exchange molecular dynamics (REMD) and the umbrella sampling (US) methods are available. However, prior to this work, the replica-exchange umbrella sampling (REUS) method, combining REMD and US, was not implemented. Here, REUS affords a more efficient conformational sampling than the conventional US method and is often used in MD simulations. We implemented REUS in GAMESS-US and improved some routines of the existing REMD code. A density-functional tight-binding REMD (DFTB-REMD) simulation of alanine deca-peptide and a DFTB-MD REUS simulation of proton transfer in malonaldehyde were performed. The results of DFTB-MD REUS simulations performed with three different simulation packages were compared to validate our GAMESS-US implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Gas tungsten arc welding and friction stir welding of ultrafine grained AISI 304L stainless steel: Microstructural and mechanical behavior characterization

In the present study, an ultrafine grained (UFG) AISI 304L stainless steel with the average grain size of 650 nm was successfully welded by both gas tungsten arc welding (GTAW) and friction stir welding (FSW). GTAW was applied without any filler metal. FSW was also performed at a constant rotational speed of 630 rpm and different welding speeds from 20 to 80 mm/min. Microstructural characterization was carried out by High Resolution Scanning Electron Microscopy (HRSEM) with Electron Backscattered Diffraction (EBSD) and Transmission Electron Microscopy (TEM). Nanoindentation, microhardness measurements and tensile tests were also performed to study the mechanical properties of the base metal and weldments. The results showed that the solidification mode in the GTAW welded sample is FA (ferrite–austenite) type with the microstructure consisting of an austenite matrix embedded with lath type and skeletal type ferrite. The nugget zone microstructure in the FSW welded samples consisted of equiaxed dynamically recrystallized austenite grains with some amount of elongated delta ferrite. Sigma phase precipitates were formed in the region ahead the rotating tool during the heating cycle of FSW, which were finally fragmented into nanometric particles and distributed in the weld nugget. Also there is a high possibility that the existing delta ferrite in the microstructure rapidly transforms into sigma phase particles during the short thermal cycle of FSW. These suggest that high strain and deformation during FSW can promote sigma phase formation. The final austenite grain size in the nugget zone was found to decrease with increasing Zener–Hollomon parameter, which was obtained quantitatively by measuring the peak temperature, calculating the strain rate during FSW and exact examination of hot deformation activation energy by considering the actual grain size before the occurrence of dynamic recrystallization. Mechanical properties observations showed that the welding efficiency of the FSW welded sample is around 70%, which is more than 20% higher than the GTAW welded sample. - Highlights: • Microstructure and mechanical properties of UFG 304L stainless steel were studied during GTAW and FSW. • Sigma phase formation mechanism was studied during FSW of 304L stainless steel. • THERMOCALC analysis was performed to obtain possible formation temperatures for sigma phase. • Nano-mechanical twins were found in the TMAZ region.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Chloride Ion Transport by the E. coli CLC Cl – /H + Antiporter: A Combined Quantum-Mechanical and Molecular-Mechanical Study

We performed steered molecular dynamics (SMD) and umbrella sampling simulations of Cl – ion migration through the transmembrane domain of a prototypical E. coli CLC Cl – /H + antiporter by employing combined quantum-mechanical (QM) and molecular-mechanical (MM) calculations. The SMD simulations revealed interesting conformational changes of the protein. While no large-amplitude motions of the protein were observed during pore opening, the side chain rotation of the protonated external gating residue Glu148 was found to be critical for full access of the channel entrance by Cl – . Moving the anion into the external binding site (S ext ) induced small-amplitude shifting of the protein backbone at the N-terminal end of helix F. As Cl – traveled through the pore, rigid-body swinging motions of helix R separated it from helix D. Helix R returned to its original position once Cl – exited the channel. Population analysis based on polarized wavefunction from QM/MM calculations discovered significant (up to 20%) charge loss for Cl – along the ion translocation pathway inside the pore. The delocalized charge was redistributed onto the pore residues, especially the functional groups containing π bonds (e.g., the Tyr445 side chain), while the charges of the H atoms coordinating Cl – changed almost negligibly. Potentials of mean force computed from umbrella sampling at the QM/MM and MM levels both displayed barriers at the same locations near the pore entrance and exit. However, the QM/MM PMF showed higher barriers (~10 kcal/mol) than the MM PMF (~2 kcal/mol). Binding energy calculations indicated that the interactions between Cl – and certain pore residues were overestimated by the semi-empirical PM 3 Hamiltonian and underestimated by the CHARMM36 force fields, both of which were employed in the umbrella sampling simulations. In particular, CHARMM36 underestimated binding interactions for the functional groups containing π bonds, missing the stabilizations of the Cl – ion due to electron delocalization. The results suggested that it is important to explore these quantum effects for accurate descriptions of the Cl – transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Implementation of Dynamic Extensible Adaptive Locally Exchangeable Measures (IDEALEM) v 0.1

Handling large streaming data is essential for various applications such as network traffic analysis, social networks, energy cost trends, and environment modeling. However, it is in general intractable to store, compute, search, and retrieve large streaming data. This software addresses a fundamental issue, which is to reduce the size of large streaming data and still obtain accurate statistical analysis. As an example, when a high-speed network such as 100 Gbps network is monitored, the collected measurement data rapidly grows so that polynomial time algorithms (e.g., Gaussian processes) become intractable. One possible solution to reduce the storage of vast amounts of measured data is to store a random sample, such as one out of 1000 network packets. However, such static sampling methods (linear sampling) have drawbacks: (1) it is not scalable for high-rate streaming data, and (2) there is no guarantee of reflecting the underlying distribution. In this software, we implemented a dynamic sampling algorithm, based on the recent technology from the relational dynamic bayesian online locally exchangeable measures, that reduces the storage of data records in a large scale, and still provides accurate analysis of large streaming data. The software can be used for both online and offline data records.

Sim, Alex↗
DOE OSTI2021

Trace explosive residue detection of HMX and RDX in post-detonation dust from an open-air environment

Explosives are often used in industry, geology, mining, and other applications, but it is not always clear what remains after a detonation or the fate and transport of any residual material. The goal of this study was to determine to what extent intact molecules of high explosive (HE) compounds are detectable and quantifiable from post-detonation dust and particulates in a field experiment with varied topography. We focused on HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane), which is less studied in field detonation literature, as the primary explosive material and RDX (1,3,5-Trinitroperhydro-1,3,5-triazine) as the secondary material. The experiment was conducted at Site 300, Lawrence Livermore National Laboratory’s Experimental Test Site, in California, USA. Two 20.4 kg and one 40.8 kg above ground explosions (primarily comprised of LX-14, an HMX-based polymer-bonded high explosive) were detonated on an open-air firing area on separate days. The complex terrain of the firing area (e.g., buildings, berm, low-height obstacles) was advantageous to study HE deposition in relation to plume dynamics. Three types of samples were collected up to 100 m away from each shot: surface swipes of aluminum plates, surface swipes of fixed objects, and filters from air samples. We used atmospheric flow tube-mass spectrometry (AFT-MS) to quantify picogram levels of molecular residue of HE material in the post-detonation dust. An aliquot of sample extract in methanol (e.g., 1 µL of 0.5 mL) was placed onto a resistive material and then thermally desorbed into the AFT-MS. We successfully detected and quantified both HMX and RDX in many of the samples. Based on mass (pg) detected and solution dilution, we back-calculated the mass collected on the swipe or filter (ng per sample). The aerial distribution of molecular residue was consistent with the path of the plume, which was strongly determined by wind speed and direction at the time of each shot. The quantity of material detected appeared to correlate more with distance from the shot and the wind conditions than with shot size. This study demonstrates that the picogram detection levels of AFT-MS are well-suited for quantification of analytes (e.g., HMX and RDX) in environmental samples.

atmospheric flow tube-mass spectrometry (AFT-MS), ↗
DOE OSTI2015

Operation of the “Small” BioAMS spectrometers at CAMS: Past and future prospects

A summary of results from the solid samples run on our compact 1 MV AMS system over its 13.5 years of operation is presented. On average 7065 samples per year were measured with that average dropping to 3278 samples per year following the deployment of our liquid sample capability. Although the dynamic range of our spectrometer is 4.5 orders in magnitude, most of the measured graphitic samples had 14 C/C concentrations between 0.1 and 1 modern. Furthermore, the measurements of our ANU sucrose standard followed a Gaussian distribution with an average of 1.5082 ± 0.0134 modern. The LLNL biomedical AMS program supported many different types of experiments, however, the large majority of samples measured were derived from animal model systems. We have transitioned all of our biomedical AMS measurements to the recently installed 250 kV SSAMS instrument with good agreement compared in measured 14C/C isotopic ratios between sample splits. We then present results from replacement of argon stripping gas with helium in the SSAMS with a 22% improvement in ion transmission through the accelerator and high-energy analyzing magnet.

14C↗
DOE OSTI2016

Measurement of Size-dependent Dynamic Shape Factors of Quartz Particles in Two Flow Regimes

Understanding and modeling the behavior of quartz dust particles, commonly found in the atmosphere, requires knowledge of many relevant particles properties, including particle shape. This study uses a single particle mass spectrometer, a differential mobility analyzer, and an aerosol particle mass analyzer to measure quartz aerosol particles mobility, aerodynamic, and volume equivalent diameters, mass, composition, effective density, and dynamic shape factor as a function of particle size, in both the free molecular and transition flow regimes. The results clearly demonstrate that dynamic shape factors can vary significantly as a function of particle size. For the quartz samples studied here, the dynamic shape factors increase with size, indicating that larger particles are significantly more aspherical than smaller particles. In addition, dynamic shape factors measured in the free-molecular (χv) and transition (χt) flow regimes can be significantly different, and these differences vary with the size of the quartz particles. For quartz, χv of small (d < 200 nm) particles is 1.25, while χv of larger particles (d ~ 440 nm) is 1.6, with a continuously increasing trend with particle size. In contrast χt, of small particles starts at 1.1 increasing slowly to 1.34 for 550 nm diameter particles. The multidimensional particle characterization approach used here goes beyond determination of average properties for each size, to provide additional information about how the particle dynamic shape factor may vary even for particles with the same mass and volume equivalent diameter.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

Imaging via complete cantilever dynamic detection: General dynamic mode imaging and spectroscopy in scanning probe microscopy

We develop and implement a multifrequency spectroscopy and spectroscopic imaging mode, referred to as general dynamic mode (GDM), that captures the complete spatially- and stimulus dependent information on nonlinear cantilever dynamics in scanning probe microscopy (SPM). GDM acquires the cantilever response including harmonics and mode mixing products across the entire broadband cantilever spectrum as a function of excitation frequency. GDM spectra substitute the classical measurements in SPM, e.g. amplitude and phase in lock-in detection. Here, GDM is used to investigate the response of a purely capacitively driven cantilever. We use information theory techniques to mine the data and verify the findings with governing equations and classical lock-in based approaches. We explore the dependence of the cantilever dynamics on the tip–sample distance, AC and DC driving bias. This approach can be applied to investigate the dynamic behavior of other systems within and beyond dynamic SPM. In conclusion, GDM is expected to be useful for separating the contribution of different physical phenomena in the cantilever response and understanding the role of cantilever dynamics in dynamic AFM techniques.

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

Trajectory Ensemble Methods Provide Single-Molecule Statistics for Quantum Dynamical Systems

The emergence of experiments capable of probing quantum dynamics at the single-molecule level requires the development of new theoretical tools capable of simulating and analyzing these dynamics beyond an ensemble-averaged description. In this article, we present an efficient method for sampling and simulating the dynamics of the individual quantum systems that make up an ensemble and apply it to study the nonequilibrium dynamics of the ubiquitous spin-boson model. We generate an ensemble of single-system trajectories, and we analyze this trajectory ensemble using tools from classical statistical mechanics. Our results demonstrate that the dynamics of quantum coherence is highly heterogeneous at the single-system level due to variations in the initial bath configuration, which significantly affects the transient exchange of coherence between the system and its bath. Here, we observe that single systems tend to retain coherence over time scales longer than that of the ensemble. We also compute a novel thermodynamic entanglement entropy that quantifies a thermodynamic driving force favoring system–bath entanglement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Sampling the isothermal-isobaric ensemble by Langevin dynamics

We present a new method of conducting fully flexible-cell molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way, in the sense that the stationary configurational distribution is proved to be consistent with that of the isothermal-isobaric ensemble. In order to apply the proposed method in computer simulations, a second order symmetric numerical integration scheme is developed by Trotter’s splitting of the single-step propagator. Moreover, a practical guide of choosing working parameters is suggested for user specified thermo- and baro-coupling time scales. The method and software implementation are carefully validated by a numerical example.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Forward flux sampling calculation of homogeneous nucleation rates from aqueous NaCl solutions

We used molecular dynamics simulations and the path sampling technique known as forward flux sampling to study homogeneous nucleation of NaCl crystals from supersaturated aqueous solutions at 298 K and 1 bar. Nucleation rates were obtained for a range of salt concentrations for the Joung-Cheatham NaCl force field combined with the Extended Simple Point Charge (SPC/E) water model. The calculated nucleation rates are significantly lower than the available experimental measurements. The estimates for the nucleation rates in this work do not rely on classical nucleation theory, but the pathways observed in the simulations suggest that the nucleation process is better described by classical nucleation theory than an alternative interpretation based on Ostwald’s step rule, in contrast to some prior simulations of related models. In addition to the size of NaCl nucleus, we find that the crystallinity of a nascent cluster plays an important role in the nucleation process. Nuclei with high crystallinity were found to have higher growth probability and longer lifetimes, possibly because they are less exposed to hydration water.

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

AI-enabled high-resolution scanning coherent diffraction imaging

Ptychographic imaging is a powerful means of imaging beyond the resolution limits of typical x-ray optics. Capturing recovered images from raw ptychographic data, however, requires the solution of an inverse problem, namely, phase retrieval. Phase retrieval algorithms are computationally expensive, which precludes real-time imaging. In this work, we propose PtychoNN, an approach to solve the ptychography data inversion problem based on a deep convolutional neural network. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. Our results demonstrate the practical application of machine learning to recover high fidelity amplitude and phase contrast images of a real sample hundreds of times faster than current ptychography reconstruction packages. Furthermore, by overcoming the constraints of iterative model-based methods, we can significantly relax sampling constraints on data acquisition while still producing an excellent image of the sample. Besides drastically accelerating acquisition and analysis, this capability has profound implications for the imaging of dose sensitive, dynamic, and extremely voluminous samples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Sub-daily virus sampling at the Bermuda Atlantic Time Series reveals diel and depth-structured population dynamics without community-level shifts

Ocean microbes contribute to biogeochemical cycles and ecosystem function, but they do so under top-down pressure imposed by viruses. While viruses are increasingly understood spatially and beginning to be incorporated into predictive modeling, high-frequency ocean virus dynamics remain understudied due to methodological challenges. Here we sampled stratified Bermuda Atlantic Time Series (BATS) waters for 112 hours at sub-daily 4- (surface) or 12- (deep chlorophyll maximum) hour intervals, purified viral particles from these samples, sequenced their metagenomes, and used the resulting data to characterize high-frequency virus community dynamics. Aggregated community diversity metrics changed with depth, but were not statistically significant temporally at a fixed location. However, finer-scale population-level analyses revealed both depth and temporal change, including physicochemical depth-driven differences and, in surface waters, thousands of viral populations that exhibited statistically significant diel rhythms. Statistical analyses revealed three main archetypes of temporal dynamics that themselves differed in abundance patterns, host predictions, viral taxonomy, and gene functions. Among these, highlights include viruses resembling an archetype with a night peaking pattern in activity that include an over-representation of viruses that putatively infect Prochlorococcus, a phototrophic cyanobacteria. Together, these efforts provide baseline community- and population-scale short-time-frame observations relevant to future climate state modeling.

Carrillo, Alfonso [The Ohio State University, Colu↗
DOE OSTI2019

Thermo-Mechanical Behavior of Genetically Modified Populus trichocarpa

Wood processing is often performed at elevated temperatures under moisture-saturated conditions; therefore, it is important to understand the impact of the lignin content and lignin chemical structure on the thermo-mechanical properties of wood. In this study, genetically modified Populus trichocarpa wood specimens with down-regulated cinnamyl alcohol dehydrogenase, cinnamate 3-hydroxylase, and cinnamate 4-hydroxylase with altered lignin contents and/or lignin structures were utilized to probe the relationship between the lignin content, lignin monomer composition, and thermo-mechanical properties of solid wood. The thermo-mechanical properties of these unique samples were measured using dynamic mechanical analysis and the nuclear magnetic resonance (NMR) spin-spin relaxation time. The results showed that the transgenic P. trichocarpa samples had decreased storage and loss moduli compared with the wildtype. The solid-state NMR revealed increased lignin molecular mobility in the reduced-lignin transgenic lines. Also, noticeably reduced glass transition temperatures (Tg) were observed in the transgenic lines with reduced lignin contents and altered lignin monomer compositions compared with the wildtype. The increased lignin molecular mobility and reduced Tg in these samples can probably contribute to wood utilization and processing, such as lignin removal for pulp and paper and biofuels production, as well as particle consolidation during wood composite manufacturing.

09 BIOMASS FUELS↗