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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 109 records · Page 6

Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria

Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach for discovering the functions of bacterial genes. However, the development of a suitable TnSeq strategy for a given bacterium can be costly and time-consuming. To meet this challenge, we describe a part-based strategy for constructing libraries of hundreds of transposon delivery vectors, which we term “magic pools.” Within a magic pool, each transposon vector has a different combination of upstream sequences (promoters and ribosome binding sites) and antibiotic resistance markers as well as a random DNA barcode sequence, which allows the tracking of each vector during mutagenesis experiments. To identify an efficient vector for a given bacterium, we mutagenize it with a magic pool and sequence the resulting insertions; we then use this efficient vector to generate a large mutant library. We used the magic pool strategy to construct transposon mutant libraries in five genera of bacteria, including three genera of the phylum Bacteroidetes .

59 BASIC BIOLOGICAL SCIENCES↗

Test methodology for validation of multi-frequency models of renewable energy generators using small-signal perturbations

Providing trustworthy and accurate multi-frequency (or harmonic) models for renewable energy generators (REG) is an ongoing challenge for harmonic studies. There have been effective attempts to propose and design a test device to validate the harmonic models, mainly based on shunt current perturbations. However, using additional devices for perturbations is costly for converter-based test sites. This paper provides the test specifications to extend the application of the grid emulators for voltage perturbations and appropriate harmonic model validation. Besides, the effects of the sequence couplings, initial emissions, and power set-points on the test results have been overlooked in the literature. Considering these effects, this paper proposes a generic test methodology to obtain more accurate models in the sequence domain. The experimental verification of the proposed methodology is demonstrated using a 7 MVA grid emulator for testing of a 2 MVA photo-voltaic converter and a 2 MVA Type 3 wind turbine. This way, the test challenges, specifications, and recommendations are presented using the MW-scale experiments on different REGs. Furthermore, the effects of sequence couplings and initial emissions on the calculation results are investigated and compared. The proposed methodology is applicable for harmonic model validation as well as empirical modelling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Depth-dependent Metagenome-Assembled Genomes of Agricultural Soils under Managed Aquifer Recharge

Abstract Managed Aquifer Recharge (MAR) systems, which intentionally replenish groundwater aquifers with excess water, are critical for addressing water scarcity exacerbated by demographic shifts and climate variability. To date, little is known about the functional diversity of the soil microbiome at different soil depth inhabiting agricultural soils used for MAR. Knowing the functional diversity is pivotal in regulating nutrient cycling and maintaining soil health. Metagenomics, particularly Metagenome-Assembled Genomes (MAGs), provide a powerful tool to explore the diversity of uncultivated soil microbes, facilitating in-depth investigations into microbial functions. In a field experiment conducted in a California vineyard, we sequenced soil DNA before and after water application of MAR. Through this process, we assembled 146 medium and 14 high-quality MAGs, uncovering a wide array of archaeal and bacterial taxa across different soil depths. These findings advance our understanding of the microbial ecology and functional diversity of soils used for MAR, contributing to the development of more informed and sustainable land management strategies.

Science & Technology - Other Topics↗

Examining the role of flame topologies and in-cylinder flow fields on cyclic variability in spark-ignited engines using large-eddy simulation

In this work we have studied cycle-to-cycle variation (CCV) in a spark-ignited (SI) engine using large-eddy simulation (LES) in conjunction with the G-equation combustion model. A single cylinder of a four-cylinder port-fueled SI engine was simulated. 49 consecutive full cycles were computed. The operating condition studied in this work is stoichiometric and stable, and represents a load of 16 bar brake mean effective pressure (BMEP), and an engine speed of 2500 revolutions per minute (r/min). The CFD simulation shows good agreement in terms of in-cylinder pressure prediction with respect to the experiments, and is also able to capture the range of CCV observed in experiments. Further, neither the simulation, nor the experiments show any distinguishable pattern in the sequence of high and low cycles. We numerically decoupled the effects of variations in equivalence ratio fields and velocity fields to isolate the effects of differences in the velocity field and differences in the equivalence ratio field on flame development and propagation. Based on this study we inferred that for this engine, under the operating conditions studied, the differences in burn rates can be attributed to the differences in the velocity flow-field in the region around the spark gap during ignition. We then performed an analysis to identify the correlation between peak cylinder pressure (PCP) and flame topologies over all the simulated cycles. We found that high cycles (higher PCP values) are strongly correlated to flatter flame volume shapes (flattened in the piston-to-head direction), and volumes that are more symmetric about the ignition axis. In addition, these kinds of flame volumes were found to correlate well with lower values of prior-to-ignition velocity going from the intake to the exhaust side (mean flow caused by tumble) at the spark, and also higher values of prior-to-ignition velocity in the piston-to-head direction.

CCV↗

Assurance of Reasoning Enabled Systems (ARES)

ARES was in part motivated by the determination of President’s Council of Advisors on Science and Technology (PCAST) on May 13th, 2023 that published a set of inquiries: In an era in which convincing images, audio, and text can be generated with ease on a massive scale, how can we ensure reliable access to verifiable, trustworthy information? How can we be certain that a particular piece of media is genuinely from the claimed source? What technologies, policies, and infrastructure can be developed to detect and counter AI-generated disinformation? In an effort to automatically analyze and patch/optimize code the work in this report describes various neural Machine Learning (ML) analysis engine implementations to assist in situations where source code is deficient or completely lacking to decompile (lift) binary code to ’C’. The goal is to gradually reduce human intervention. To this end, two Large Language Model (LLM) variants (Code LLama 2, LLama 3.1 and Starcoder1, Starcoder 2) where finetuned with ’before/after’ code pairs on the OpenBLAS library. LLama trained on the lowering process, Starcoder trained on the lifting process with National Security Agency’s (NSA) open-source Ghidra decompiler assist. The inferencing test results indicate correctness for only very short sequences for Starcoder 2. Moving forward, the experiments conclude with a set of recommendations of required resources and technologies

97 MATHEMATICS AND COMPUTING↗

The International Space Station Environment Triggers Molecular Responses in Aspergillus niger

Due to immense phenotypic plasticity and adaptability, Aspergillus niger is a cosmopolitan fungus that thrives in versatile environments, including the International Space Station (ISS). This is the first report of genomic, proteomic, and metabolomic alterations observed in A. niger strain JSC-093350089 grown in a controlled experiment aboard the ISS. Whole-genome sequencing (WGS) revealed that ISS conditions, including microgravity and enhanced irradiation, triggered non-synonymous point mutations in specific regions, chromosomes VIII and XII of the JSC-093350089 genome when compared to the ground-grown control. Proteome analysis showed altered abundance of proteins involved in carbohydrate metabolism, stress response, and cellular amino acid and protein catabolic processes following growth aboard the ISS. Metabolome analysis further confirmed that space conditions altered molecular suite of ISS-grown A. niger JSC-093350089. After regrowing both strains on Earth, production of antioxidant—Pyranonigrin A was significantly induced in the ISS-flown, but not the ground control strain. In summary, the microgravity and enhanced irradiation triggered unique molecular responses in the A. niger JSC-093350089 suggesting adaptive responses.

59 BASIC BIOLOGICAL SCIENCES↗

(-)ESI/CAD MS n Procedure for Sequencing Lignin Oligomers Based on a Study of Synthetic Model Compounds with β-O-4 and 5-5 Linkages

Here, seven synthesized G-lignin oligomer model compounds (ranging in size from dimers to an octamer) with 5-5 and/or β-O-4 linkages, and three synthesized S-lignin model compounds (a dimer, trimer, and tetramer) with β-O-4 linkages, were evaporated and deprotonated using negative-ion mode ESI in a linear quadrupole ion trap/Fourier transform ion cyclotron resonance mass spectrometer. The collision-activated dissociation (CAD) fragmentation patterns (obtained in MS 2 and MS 3 experiments, respectively) for the negative ions were studied to develop a procedure for sequencing unknown lignin oligomers. On the basis of the observed fragmentation patterns, the measured elemental compositions of the most abundant fragment ions, and quantum chemical calculations, the most important reaction pathways and likely mechanisms were delineated. Many of these reactions occur via charge-remote fragmentation mechanisms. Deprotonated compounds with only β-O-4 linkages, or both 5-5 and β-O-4 linkages, showed major 1,2-eliminations of neutral compounds containing one, two, or three aromatic rings. The most likely mechanisms for these reactions are charge-remote Maccoll and retro-ene eliminations resulting in the cleavage of a β-O-4 linkage. Finally, facile losses of H 2 O and CH 2 O were also observed for all deprotonated model compounds, which involve a previously published charge-driven mechanism. Characteristic “ion groups” and “key ions” were identified that, when combined with their CAD products (MS 3 experiments), can be used to sequence unknown oligomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Permafrost Degradation and Subsidence Observations during a Controlled Warming Experiment

Global climate change has resulted in a warmer Arctic, with projections indicating accelerated modifications to permafrost in the near future. The thermal, hydrological, and mechanical physics of permafrost thaw have been hypothesized to couple in a complex fashion but data collection efforts to study these feedbacks in the field have been limited. As a result, laboratory and numerical models have largely outpaced field calibration datasets. We present the design, execution, and initial results from the first decameter-scale controlled thawing experiment, targeting coupled thermal/mechanical response, particularly the temporal sequence of surface subsidence relative to permafrost degradation at depth. The warming test was conducted in Fairbanks, AK, and utilized an array of in-ground heaters to induce thaw of a ~11 × 13 × 1.5 m soil volume over 63 days. The 4-D temperature evolution demonstrated that the depth to permafrost lowered 1 m during the experiment. The resulting thaw-induced surface deformation was ~10 cm as observed using a combination of measurement techniques. Surface deformation occurred over a smaller spatial domain than the full thawed volume, suggesting that gradients in cryotexture and ice content were significant. Our experiment provides the first large field calibration dataset for multiphysics thaw models.

54 ENVIRONMENTAL SCIENCES↗

16S and ITS Amplicon Sequencing Fastq files and metadata from PARCHED Panama Tropical Forest soils, 2019-2020,

Model projections predict tropical forests will experience longer periods of drought and more intense precipitation cycles under a changing climate. Such transitions have implications for structure-function relationships within microbial communities. We examine how chronic drying might reshape prokaryotic and fungal communities across four lowland forests in Panama with a wide variation in mean annual precipitation and soil fertility. Four sites were established across a 1000 mm span in mean annual precipitation (2335 to 3300 mm). We expected microbial communities at sites with lower MAP to be less sensitive to chronic drying than sites with higher MAP; while fungal communities to be more resistant to disturbance than prokaryotes. At each location, partial throughfall exclusion structures were established over 10 x 10 m plots to reduce direct precipitation input. Raw demultiplexed sequences (bacteria, archaea, fungal) from soil samples taken from PARCHED Panama Tropical Forest throughfall exclusion experiments. Files that contain 16S are sequences from prokaryotes, ITS indicates sequences from fungi. Compressed fastq files are contained in Field_PARCHED_ITS_fastq_2020.zip, Field_PARCHED_ITS_fastq_2019.zip, Field_PARCHED_16S_fastq_2020.zip, Field_PARCHED_16S_fastq_2019.zip.There are four sites across the isthmus of Panama, each with 4 control and 4 exclusion plots. Throughfall exclusion shelters were built to intercept 50% of throughfall precipitation that hits the soil. Samples were taken on May 2019 and Jan 2020 from 0-10 cm and 10-20 cm depth approximately 9 and 18 months after shelter installation. Metadata and sample IDs for fastq files for 2019 sampling are within Field_PARCHED_Metadata_2019_ITS.csv and Field_PARCHED_Metadata_2019_16S.csv. The metadata for both 16S and ITS fastq files for January 2020 is included in Field_PARCHED_Metadata_2020.csv. No data processing or QA/QC was done on the raw data. Data processing example provided in R notebook file.

54 ENVIRONMENTAL SCIENCES↗

Analysis of Previously Classified White Dwarf–Main-sequence Binaries Using Data from the APOGEE Survey

We present analyses of near-infrared spectroscopic data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey for 45 previously confirmed or candidate white dwarf–main-sequence (WDMS) binaries identified by the optical Sloan Digital Sky Survey (SDSS) and LAMOST surveys. Among these 45 systems, we classify three as having red giant primaries in the LAMOST sample and 14 as young stellar object contaminants in the photometrically identified SDSS sample. From among the subsample of 28 systems that we confirm to have MS primaries, we derive and place limits on orbital periods and velocity amplitudes for 14. Seven systems have significant velocity variations that warrant a post-common-envelope (PCE) binary classification, four of which are newly classified, three of which are newly confirmed, and five for which we can derive full orbital parameters. If confirmed, one of these newly discovered systems (2M14544500+4626456) will have the second-longest orbital period reported for a typical compact PCE WDMS binary (P = 15.1 days). In addition to the seven above, we also recover and characterize with APOGEE data the well-known PCE WDMS systems EG UMa and HZ 9. We also investigate the overall metallicity distribution of the WDMS sample, which is a parameter space not often explored for these systems. Of note, we find one system (2M14244053+4929580) to be extremely metal-poor ([Fe/H] = − 1.42) relative to the rest of the near-solar sample. Additionally, the PCE systems in our sample are found to be, on average, higher in metallicity than their wide-binary counterparts, though we caution that with this small number of systems, the sample may not be representative of the overall distribution of WDMS systems.

36 MATERIALS SCIENCE↗

Adapting CLUTCH methodology to multigroup TSUNAMI-3D for eigenvalue sensitivity calculations

The sensitivity of the eigenvalue to uncertainties in nuclear data and its evaluation are important for nuclear criticality safety. TSUNAMI-3D sequences within the SCALE code system offer several options to the user community for calculating eigenvalue sensitivity coefficients with multigroup (MG) and continuous energy (CE) 3D transport capabilities. TSUNAMI-3D sequences implement the adjoint-based perturbation theory with MG KENO code, the Contributon Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance CHaracterization (CLUTCH) method with CE KENO code, and the Iterated Fission Probability (IFP) method with CE KENO and Shift codes. Each method has benefits and limitations depending on the problem that is run. The work presented here aims to adapt the CLUTCH method, which enables the Contributon method's mesh-free, memory-efficient approach for calculating adjoint-weighted tallies for sensitivity calculations, to the MG TSUNAMI-3D sequence. This application would eliminate the explicit adjoint KENO calculation, as well as the memory-consuming mesh flux moment tallies required by the conventional MG TSUNAMI-3D. Smaller memory footprints in the CLUTCH methodology and relatively shorter runtimes in MG KENO transport can make MG TSUNAMI-3D a viable method for some complex problems. Moreover, this adaptation allows MG sensitivity calculations with Shift, ORNL's next-generation high-performance Monte Carlo transport code, which currently does not offer any sensitivity capabilities with MG particle transport simulations. Initial implementation of the new MG TSUNAMI-3D sequence and its preliminary results with a selected critical benchmark experiment in the Verified, Archived Library of Inputs and Data (VALID) are presented in this study.

KENO↗

Targeted mutagenesis and high-throughput screening of diversified gene and promoter libraries for isolating gain-of-function mutations

Targeted mutagenesis of a promoter or gene is essential for attaining new functions in microbial and protein engineering efforts. In the burgeoning field of synthetic biology, heterologous genes are expressed in new host organisms. Similarly, natural or designed proteins are mutagenized at targeted positions and screened for gain-of-function mutations. Here, we describe methods to attain complete randomization or controlled mutations in promoters or genes. Combinatorial libraries of one hundred thousands to tens of millions of variants can be created using commercially synthesized oligonucleotides, simply by performing two rounds of polymerase chain reactions. With a suitably engineered reporter in a whole cell, these libraries can be screened rapidly by performing fluorescence-activated cell sorting (FACS). Within a few rounds of positive and negative sorting based on the response from the reporter, the library can rapidly converge to a few optimal or extremely rare variants with desired phenotypes. Library construction, transformation and sequence verification takes 6–9 days and requires only basic molecular biology lab experience. Screening the library by FACS takes 3–5 days and requires training for the specific cytometer used. Further steps after sorting, including colony picking, sequencing, verification, and characterization of individual clones may take longer, depending on number of clones and required experiments.

59 BASIC BIOLOGICAL SCIENCES↗

AlphaFold Protein Structure Database for Sequence-Independent Molecular Replacement

Crystallographic phasing recovers the phase information that is lost during a diffraction experiment. Molecular replacement is a commonly used phasing method for crystal structures in the protein data bank. In one form it uses a protein sequence to search a structure database to find suitable templates for phasing. However, sequence information is not always available, such as when proteins are crystallized with unknown binding partner proteins or when the crystal is of a contaminant. The recent development of AlphaFold published the predicted protein structures for every protein from twenty distinct species. In this work, we tested whether AlphaFold-predicted E. coli protein structures were accurate enough to enable sequence-independent phasing of diffraction data from two crystallization contaminants of unknown sequence. Using each of more than 4000 predicted structures as a search model, robust molecular replacement solutions were obtained, which allowed the identification and structure determination of YncE and YadF. Our results demonstrate the general utility of the AlphaFold-predicted structure database with respect to sequence-independent crystallographic phasing.

59 BASIC BIOLOGICAL SCIENCES↗

MR13A-3183: Microbial and Geochemical Characterization of Groundwater: Implications for Underground Hydrogen Storage Leakage

Underground hydrogen storage (UHS) in geological formations is a key element of the clean energy transition as it enables the decarbonization of the transportation and industrial sectors by decoupling hydrogen production and storage. UHS has many benefits, including low cost, much wider availability, large storage capacity, well-established infrastructure, and increased safety because of geological sealing capabilities. However, the impact of hydrogen (H2) biogeochemical interactions in the presence of subsurface microorganisms is largely neglected from UHS perspectives. These interactions might affect the effectiveness of storage and can even cause H2 to leak into the shallow aquifers. Leakage of H2 into groundwater can change the geochemistry and induce several microbial-driven processes. Microorganisms, such as sulfate-reducers, are naturally abundant in groundwater and consume H2 to produce hydrogen sulfide (H2S), which can contaminate the freshwater drinking groundwater and cause damage to infrastructure. Hydrogen leakage can also trigger microbial reactions responsible for metal mobility, which can impact the water quality. However, the kinetics of these reactions and the temporal impact of hydrogen leakage in groundwater are still unknown. Therefore, a time series hydrogen-groundwater interaction experiment was conducted, and the changes in fluid chemistry and headspace gas composition will be analyzed along with DNA sequencing results to understand the extent and kinetics of biogeochemical reactions that occur if hydrogen leaks into groundwater. In the experiments, Ultra High Purity (UHP) hydrogen gas will be injected into glass vials with groundwater samples, for a designated time period. For each glass-sealed vial, 16S rRNA gene sequencing, IC, ICP-MS, and GC-TCD will be performed. The experiments provide insights into plausible impacts of hydrogen leakage into shallow drinking water aquifers.

Clark, Allison [West Virginia University (WVU)]↗

Dissimilatory Sulfate Reduction Under High Pressure by Desulfovibrio alaskensis G20

Biosouring results from production of H2S by sulfate-reducing microorganisms (SRMs) in oil reservoirs. H2S is toxic, corrosive, and explosive, and as such, represents a significant threat to personnel, production facilities, and transportation pipelines. Since typical oil reservoir pressures can range from 10 to 50 MPa, understanding the role that pressure plays in SRM metabolism is important to improving souring containment strategies. To explore the impact of pressure, we grew an oil-field SRM isolate, Desulfovibrio alaskensis G20, under a range of pressures (0.1–14 MPa) at 30°C. The observed microbial growth rate was an inverse function of pressure with an associated slight reduction in sulfate and lactate consumption rate. Competitive fitness experiments with randomly bar-coded transposon mutant library sequencing (RB-TnSeq) identified several genes associated with flagellar biosynthesis and assembly that were important at high pressure. The fitness impact of specific genes was confirmed using individual transposon mutants. Confocal microscopy revealed that enhanced cell aggregation occurs at later stages of growth under pressure. We also assessed the effect of pressure on SRM inhibitor potency. Dose-response experiments showed a twofold decrease in the sensitivity of D. alaskensis to the antibiotic chloramphenicol at 14 MPa. Fortuitously, pressure had no significant influence on the inhibitory potency of the common souring controlling agent nitrate, or the emerging SRM inhibitors perchlorate, monofluorophosphate, or zinc pyrithione. Our findings improve the conceptual model of microbial sulfate reduction in high-pressure environments and the influence of pressure on souring inhibitor efficacy.

59 BASIC BIOLOGICAL SCIENCES↗

Supervisory Control and Data Acquisition for Electrochemical Separation Experimentation

The Python-based program is a laboratory automation tool designed to control and monitor electrochemical systems. The tool was developed for capacitive deionization (CDI) experiments, but it can be used for any system that requires controlled voltage or current segments and multi-parameter monitoring. The program integrates hardware components to run user-defined experimental parameters, providing operational control of a programmable power supply, peristaltic pump, and data acquisition devices. Currently, the program is structured with a workflow that includes an initialization (or pre-run) phase, a main loop, and a post-experiment stabilization (or post-run) phase. The initialization phase prepares and stabilizes the cell, ensuring that the electrodes and solution reach a baseline state before the experiment begins. The main loop consists of multiple voltage segments that repeat, controlling the experiment while recording key parameters such as time, voltage, current, pH, and conductivity. Finally, the post-experiment stabilization phase allows the system to stabilize after the experiment, returning the cell and solution to equilibrium conditions before ending the sequence. The program is designed with four variations, each tailored to different experimental needs. All variations include both the initialization and post-experiment stabilization stages, which run for a set amount of time, voltage, current, and flow rate before and after the main experiment block. The main loop runs for a set number of cycles, as defined by the user input, and each cycle is composed of 2 or 4 segments. The 4 program variations are described as follows: Program 1: The main program includes 2 segments. Each segment is defined to have a set duration, flow rate, voltage, and current. This program measures conductivity, flow rate, voltage, and current. Program 2: The main program expands Program 1 to include 4 segments. Each segment has a specified duration, flow rate, voltage, and current. Like Program 1, it measures conductivity, flow rate, voltage, and current. Program 3: The main program consists of 2 segments, each defined by time, flow rate, voltage, and current. In addition to conductivity, flow rate, voltage, and current, Program 3 collects pH and temperature data through a 4-channel data acquisition device. Program 4: This program independently controls two channels of a multi-channel power supply simultaneously. While conductivity can only be measured for one cell at a time, the dual-channel control makes it possible to operate two cells simultaneously under different voltage/current conditions. The main program includes 2 segments.For each program, all measurements are automatically logged and integrated into a single Excel output file. Data are displayed in numerical format and plotted, both in real time, to track system performance. A key feature of the program is its ability to synchronize all outputs so that every measurement shares a single timestamp, ensuring accurate alignment of voltage, current, pH, conductivity, and pH data.By combining hardware control, real-time monitoring, and unified data collection, this program significantly reduces manual workload and minimizes errors, making it a reliable platform for researchers, engineers, and laboratory technicians conducting CDI experiments, among other electrochemical tests.

Valentino, Lauren [Argonne National Laboratory (AN↗

Advances in gap-filling genome-scale metabolic models and model-driven experiments lead to novel metabolic discoveries

With rapid improvements in next-generation sequencing technologies, our knowledge about metabolism of many organisms is rapidly increasing. However, gaps in metabolic networks exist due to incomplete knowledge (e.g., missing reactions, unknown pathways, unannotated and misannotated genes, promiscuous enzymes, and underground metabolic pathways). Here in this review, we discuss recent advances in gap-filling algorithms based on genome-scale metabolic models and the importance of both high-throughput experiments and detailed biochemical characterization, which work in concert with in silico methods, to allow a more accurate and comprehensive understanding of metabolism.

59 BASIC BIOLOGICAL SCIENCES↗