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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 829 records · Page 46

Using Natural Selection to Explore the Adaptive Potential of Chlamydomonas reinhardtii

Improving feedstock is critical to facilitate the commercial utilization of algae, in particular in open pond systems where, due to the presence of competitors and pests, high algal growth rates and stress tolerance are beneficial. Here we raised laboratory cultures of the model alga Chlamydomonas reinhardtii under serial dilution to explore the potential of crop improvement using natural selection. The alga was evolved for 1,880 generations in liquid medium under continuous light (EL population). At the end of the experiment, EL cells had a growth rate that was 35% greater than the progenitor population (PL). The removal of acetate from the medium demonstrated that EL growth enhancement largely relied on efficient usage of this organic carbon source. Genome re-sequencing uncovered 1,937 polymorphic DNA regions in the EL population with 149 single nucleotide polymorphisms resulting in amino acid substitutions. Transcriptome analysis showed, in the EL population, significant up regulation of genes involved in protein synthesis, the cell cycle and cellular respiration, whereas the DNA repair pathway and photosynthesis were down regulated. Like other algae, EL cells accumulated neutral lipids under nitrogen depletion. Our work demonstrates transcriptome and genome-wide impacts of natural selection on algal cells and points to a useful strategy for strain improvement.

59 BASIC BIOLOGICAL SCIENCES↗

CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking

RNA junctions are important structural elements of RNA molecules. They are formed when three or more helices come together in three-dimensional space. Recent studies have focused on the annotation and prediction of coaxial helical stacking (CHS) motifs within junctions. Here we exploit such predictions to develop an efficient alignment tool to handle RNA secondary structures with CHS motifs. Specifically, we build upon our Junction-Explorer software for predicting coaxial stacking and RNAJAG for modelling junction topologies as tree graphs to incorporate constrained tree matching and dynamic programming algorithms into a new method, called CHSalign, for aligning the secondary structures of RNA molecules containing CHS motifs. Thus, CHSalign is intended to be an efficient alignment tool for RNAs containing similar junctions. Experimental results based on thousands of alignments demonstrate that CHSalign can align two RNA secondary structures containing CHS motifs more accurately than other RNA secondary structure alignment tools. CHSalign yields a high score when aligning two RNA secondary structures with similar CHS motifs or helical arrangement patterns, and a low score otherwise. This new method has been implemented in a web server, and the program is also made freely available, at http://bioinformatics.njit.edu/CHSalign/.

59 BASIC BIOLOGICAL SCIENCES↗

The Paris pledges and the energy-water-land nexus in Latin America: Exploring implications of greenhouse gas emission reductions

In the 2015 Paris Agreement, nations worldwide pledged emissions reductions (Nationally Determined Contributions—NDCs) to avert the threat of climate change, and agreed to periodically review these pledges to strengthen their level of ambition. Previous studies have analyzed NDCs largely in terms of their implied contribution to limit global warming, their implications on the energy sector or on mitigation costs. Nevertheless, a gap in the literature exists regarding the understanding of implications of the NDCs on countries’ Energy-Water-Land nexus resource systems. The present paper explores this angle within the regional context of Latin America by employing the Global Change Assessment Model, a state-of-the-art integrated assessment model capable of representing key system-wide interactions among nexus sectors and mitigation policies. By focusing on Brazil, Mexico, Argentina and Colombia, we stress potential implications on national level water demands depending on countries’ strategies to enforce energy-related emissions reductions and their interplays with the land sector. Despite the differential implications of the Paris pledges on each country, increased water demands for crop and biomass irrigation and for electricity generation stand out as potential trade-offs that may emerge under the NDC policy. Hence, this study underscores the need of considering a nexus resource planning framework (known as “Nexus Approach”) in the forthcoming NDCs updating cycles as a mean to contribute toward sustainable development.

Santos Da Silva, Silvia Regina↗

Exploring the fragmentation efficiency of proteins analyzed by MALDI-TOF-TOF tandem mass spectrometry using computational and statistical analyses

Matrix-assisted laser desorption/ionization time-of-flight-time-of-flight (MALDI-TOF-TOF) tandem mass spectrometry (MS/MS) is a rapid technique for identifying intact proteins from unfractionated mixtures by top-down proteomic analysis. MS/MS allows isolation of specific intact protein ions prior to fragmentation, allowing fragment ion attribution to a specific precursor ion. However, the fragmentation efficiency of mature, intact protein ions by MS/MS post-source decay (PSD) varies widely, and the biochemical and structural factors of the protein that contribute to it are poorly understood. With the advent of protein structure prediction algorithms such as Alphafold2, we have wider access to protein structures for which no crystal structure exists. In this work, we use a statistical approach to explore the properties of bacterial proteins that can affect their gas phase dissociation via PSD. We extract various protein properties from Alphafold2 predictions and analyze their effect on fragmentation efficiency. Our results show that the fragmentation efficiency from cleavage of the polypeptide backbone on the C-terminal side of glutamic acid (E) and asparagine (N) residues were nearly equal. In addition, we found that the rearrangement and cleavage on the C-terminal side of aspartic acid (D) residues that result from the aspartic acid effect (AAE) were higher than for E- and N-residues. From residue interaction network analysis, we identified several local centrality measures and discussed their implications regarding the AAE. We also confirmed the selective cleavage of the backbone at D-proline bonds in proteins and further extend it to N-proline bonds. Finally, we note an enhancement of the AAE mechanism when the residue on the C-terminal side of D-, E- and N-residues is glycine. To the best of our knowledge, this is the first report of this phenomenon. Our study demonstrates the value of using statistical analyses of protein sequences and their predicted structures to better understand the fragmentation of the intact protein ions in the gas phase.

59 BASIC BIOLOGICAL SCIENCES↗

New River Geothermal Exploration (Ram Power Inc.)

The New River Geothermal Exploration (DOE Award No. EE0002843) is located approximately 25km south of the Salton Sea, near town of Brawley in Imperial County and approximately 150km east of San Diego, California. A total of 182 MT Logger sites were completed covering the two separate Mesquite and New River grids. The data was collected over a frequency range of 320Hz to 0.001Hz with variable site spacing. A number of different inversion algorithms in 1D, 2D and 3D were used to produce resistivity-depth profiles and maps of subsurface resistivity variations over the survey area. For 2D inversions, a total of eighteen lines were constructed in east-west and north-south orientations crossing the entire survey area. For MT 3D inversion, the New River property was divided in two sub-grids, Mesquite and New River areas. The report comprises of two parts. For the first part, inversions and geophysical interpretation results are presented with some recommendations of the potential targets for future follow up on the property. The second part of the report describes logistics of the survey, survey parameters, methodology and the survey results (data) in digital documents. The report reviews a Spartan MT survey carried out by Quantec Geoscience Limited over the New River Project in California, USA on behalf of Ram Power Inc. Data was acquired over a period of 29 days from 2010/06/26 to 2010/07/24.

15 GEOTHERMAL ENERGY↗

Exploration for Blind Geothermal Resources in the State of Hawaii Utilizing Dissolved Noble Gasses in Well Waters

This study is an extension of the Hawaii Play Fairway Analysis (PFA), a statewide geothermal exploration project funded by the United States Department of Energy. Based on results from prior phases of the PFA, this project targeted 66 wells on the islands of Hawaii, Maui, Lanai, Oahu, and Kauai for sampling of dissolved noble gases, trace metals, common ions, and the stable isotopes 2H and 18O. Ultimately, 23 of the 66 well targets were sampled. The noble gas helium is used as an indicator of geothermal heat when excess 3He and/or 4He is present when compared to the atmospheric ratio of those isotopes (R/Ra). R/Ra is minimally affected by dilution and transport, allowing even those wells not perfectly situated over a geothermal system to indicate a geothermal anomaly. R/Ra anomalies are present on every island in this study. There is a strong correlation between R/Ra anomalies and proximity to rift zones and calderas. Across the islands R/Ra ranged from 15-16 on Kilauea's lower east rift zone, which is a mantle plume value, to 0.37 on Lanai, which is a crustal value. The majority of anomalous well samples had R/Ra values consistent with an upper mantle source. Mixing between upper mantle and crustal helium is evident on all islands. Geographically, R/Ra decreases from the high at Kilauea to upper mantle values at Mauna Loa, and remains at upper mantle values for all wells across the other volcanoes, with the exception of two of four sampled wells on Lanai.

15 GEOTHERMAL ENERGY↗

Exploring the impact of vibrational cavity coupling strength on ultrafast CN + c -C 6 H 12 reaction dynamics

Abstract Molecular polaritons, hybrid light-matter states resulting from strong cavity coupling of optical transitions, may provide a new route to guide chemical reactions. However, demonstrations of cavity-modified reactivity in clean benchmark systems are still needed to clarify the mechanisms and scope of polariton chemistry. Here, we use transient absorption to observe the ultrafast dynamics of CN radicals interacting with a cyclohexane ( c -C 6 H 12 ) and chloroform (CHCl 3 ) solvent mixture under vibrational strong coupling of a C–H stretching mode of c- C 6 H 12 . By modulating the c -C 6 H 12 :CHCl 3 ratio, we explore how solvent complexation and hydrogen (H)-abstraction processes proceed under collective cavity coupling strengths ranging from 55 to 85 cm −1 . Reaction rates remain unchanged for all extracavity, on-resonance, and off-resonance cavity coupling conditions, regardless of coupling strength. These results suggest that insufficient vibrational cavity coupling strength may not be the determining factor for the negligible cavity effects observed previously in H-abstraction reactions of CN with CHCl 3 .

Chen, Liying↗

Experimental Exploration of Near-Field Radiative Heat Transfer

This article presents an in-depth review of on-going experimental research efforts to fundamentally understand the strong near-field enhancement of radiative heat transfer and make use of the underlying physics for various novel applications. Compared to theoretical studies on near-field radiative heat transfer (NFRHT), its experimental demonstration has not been explored as much until recently due to technical challenges in precision gap control and heat transfer measurement. However, recent advances in micro/nanofabrication and nanoscale instrumentation/control techniques as well as unprecedented growth in material science and engineering have created remarkable opportunities to overcome the existing challenges in the measurement and engineering of NFRHT. Furthermore, beginning with the pioneering works in 1960s, this article tracks the past and current experimental efforts of NFRHT in three different configurations (i.e., sphere-plane, plane-plane, and tip-plane). Additionally, future remarks on how to address current challenges in the experimental research of NFRHT are briefly discussed.

42 ENGINEERING↗

Exploring Uncertainty in Moment Estimation for Small Earthquakes in Southern Nevada Using the Coda Envelope Method

Compiling source parameter estimates for small earthquakes is important both for our understanding of earthquake physics and for accurately assessing earthquake hazard. Reliable source parameter estimates are difficult to achieve for small earthquakes, in part due to our inability to accurately model the relevant physical processes at high frequencies. The coda envelope methodology developed by Mayeda and Walter (1996) and Mayeda et al. (2003) can mitigate this concern and estimate the moment of small earthquakes by determining the parameters that control the shape of the S-wave coda envelope while eliminating path effects by minimizing the scatter between seismic stations. Here, we use an open-source implementation of this technique called the Coda Calibration Tool (CCT; Barno, 2017) to calculate CCT-based moment magnitude estimates of small earthquakes (M L 0–3) in the Rock Valley, Nevada, region within the Nevada National Security Site. The Rock Valley data set is of particular interest because it allows us to explore the changes in uncertainties of the coda calibration method with earthquake size and depth. We found that a consistent linear relationship exists between the local magnitude M L and our coda-derived M w estimates for earthquakes as small as M L 0–3, but that current CCT workflows do not accurately characterize very shallow events. We also demonstrate that the epistemic uncertainty in the apparent stress value assumed by the CCT algorithm can influence magnitude estimates of small earthquakes. In conclusion, these results provide valuable insight into the seismicity of this region, and inform future analysis and modeling efforts for nuclear monitoring and seismic hazard.

58 GEOSCIENCES↗

Exploring Data Set Bias and Decision Support with Predictive Uncertainty Through Bayesian Approximations and Convolutional Neural Networks

Individual seismic catalogs can contain multiscale observations from fault level to global scales and associated waveforms from discrete events reflect crustal structure across many different scales and locations. Seismic network aperture, geographic location, and observation distance may not provide informative guidance or intuition on how different catalogs will behave across models trained under different conditions. We rely on uncertainty to provide guardrails for when to trust model decisions, but understanding when our uncertainty is trustworthy is an open challenge. Here, in this work, we explore Bayesian approximation methods for assigning predictive uncertainty in seismic event classification problems. We find that computationally expensive Bayesian approximations do not outperform simple ensemble methods. We also find that when exploiting multiple seismic event catalogs, joint training with data from all the catalogs combined with Bayesian approximations and supervised training for classification can obscure bias and result in less robust uncertainty while also not providing substantial performance benefits compared to training individual models for each catalog.

58 GEOSCIENCES↗

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗

Nb₃Sn at Fermilab: Exploring Performance

Fermilab’s Nb₃Sn coating program produced its first 1.3 GHz single cell cavities in early 2017 and since then has explored the performance of Nb₃Sn on a wide variety of cavity substrates and performed microscopic studies down to atomic resolution. Results to present in this talk include a study of frequency dependence from 650 MHz to 1.3 GHz of BCS resistance, residual resistance, and magnetic flux sensitivity. We show microscopic studies performed in collaboration with Northwestern University’s Materials Science and Engineering Department of limitation mechanisms in Nb₃Sn, including thin film regions and tin segregation at grain boundaries, discussing correlations with RF performance and mechanisms for the formation of these features during growth. Finally, we present results of the first 1.3 GHz 9-cell cavity coated with Nb₃Sn.

43 PARTICLE ACCELERATORS↗

pyro: a framework for hydrodynamics explorations and prototyping

pyro is a Python-based simulation framework designed for ease of implementation and exploration of hydrodynamics methods. It is built in a object-oriented fashion, allowing for the reuse of the core components and fast prototyping of new methods.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring unsupervised top tagging using Bayesian inference

Recognizing hadronically decaying top-quark jets in a sample of jets, or even its total fraction in the sample, is an important step in many LHC searches for Standard Model and Beyond Standard Model physics as well. Although there exists outstanding top-tagger algorithms, their construction and their expected performance rely on Montecarlo simulations, which may induce potential biases. For these reasons we develop two simple unsupervised top-tagger algorithms based on performing Bayesian inference on a mixture model. In one of them we use as the observed variable a new geometrically-based observable \tilde{A}_{3} A ̃ 3 , and in the other we consider the more traditional \tau_{3}/\tau_{2} τ 3 / τ 2 N N -subjettiness ratio, which yields a better performance. As expected, we find that the unsupervised tagger performance is below existing supervised taggers, reaching expected Area Under Curve AUC \sim 0.80-0.81 ∼ 0.80 − 0.81 and accuracies of about 69% - − 75% in a full range of sample purity. However, these performances are more robust to possible biases in the Montecarlo that their supervised counterparts. Our findings are a step towards exploring and considering simpler and unbiased taggers.

Alvarez, Ezequiel↗

Using Comprehensive Two-Dimensional Gas Chromatography to the Explore the Geochemistry of the Santa Barbara Oil Seeps

The development of comprehensive two-dimensional gas chromatography (GC x GC) has expanded the analytical window for studying complex mixtures like oil. Compared to traditional gas chromatography, this technology separates and resolves at least an order of magnitude more compounds, has a much larger signal to noise ratio, and sorts compounds based on their chemical class; hence, providing highly refined inventories of petroleum hydrocarbons in geochemical samples that was previously unattainable. In addition to the increased resolution afforded by GC x GC, the resulting chromatograms have been used to estimate the liquid vapor pressures, aqueous solubilities, octanol-water partition coefficients, and vaporization enthalpies of petroleum hydrocarbons. With these relationships, powerful and incisive analyses of phase-transfer processes affecting petroleum hydrocarbon mixtures in the environment are available. For example, GC x GC retention data has been used to quantitatively deconvolve the effects of phase transfer processes such as water washing and evaporation. In short, the positive attributes of GC x GC-analysis have led to a methodology that has revolutionized the analysis of petroleum hydrocarbons. Overall, this research has opened numerous fields of study on the biogeochemical "genetics" (referred to as petroleomics) of petroleum samples in both subsurface and surface environments. Furthermore, these new findings have already been applied to the behavior of oil at other seeps as well, for petroleum exploration and oil spill studies.

02 PETROLEUM↗

Advanced Concept Exploration for Fast Ignition Science Program (Final Report)

The Fast Ignition (FI) Concept for Inertial Confinement Fusion (ICF) has the potential to provide a significant advance in the technical attractiveness of Inertial Fusion Energy reactors. FI differs from conventional “central hot spot” (CHS) target ignition by decoupling compression from heating: using a laser (or heavy ion beam or Z pinch) drive pulse (10’s of nanoseconds) to create a dense fuel and a second, much shorter (~10 picoseconds) high intensity pulse to ignite a small volume within the dense fuel. The physics of fast ignition process was the focus of our Advanced Concept Exploration (ACE) program. Ignition depends critically on two major issues involving Relativistic High Energy Density (RHED) physics: The laser-induced creation of fast electrons and their propagation in high-density plasmas. Our program has developed new experimental platforms, diagnostic packages, computer modeling analyses, and taken advantage of the increasing energy available at laser facilities to advance understanding of the fundamental physics underlying these issues.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗