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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

SPC-71260 Rev 0 MARVEL Heat Extraction Subsystem Secondary Coolant Equipment (SCE) Design/Build

A. The Microreactor Applications Research Validation and Evaluation (MARVEL) reactor will offer experimental capabilities that are not currently available at DOE’s national laboratories. Idaho National Laboratory (INL), operated for the U.S. Department of Energy (DOE) by Battelle Energy Alliance, LLC (BEA) (Contractor hereafter) is procuring services for the design, analysis, fabrication, testing and delivery of a Secondary Coolant Equipment system (SCE). This specification contains the requirements for design, analysis, fabrication, testing and delivery of the SCE as described herein. The MARVEL reactor is a microreactor which uses eutectic sodium-potassium alloy (NaK) as a primary coolant. The primary coolant is circulated through four primary loops by natural convection of the coolant. In each loop is a closed well which will accommodate an intermediate heat exchanger (IHX) for extracting heat from the loop. These wells will be referred to in this specification as the “IHX wells.” It is intended for the IHX containment to also be filled with NaK. The MARVEL design team has determined that a Heat Extraction System (HES) using pumped NaK will be used to extract heat from the IHXs and deliver it to a downstream system for power generation or alternate process heat users. This Heat Extraction System will enable MARVEL operations including the ability to test, demonstrate, and address issues related to installation, startup, and operations. In addition, it will allow down-stream utilization of process heat for various uses. The objective of this specification is to develop the final design for the HES Secondary Coolant Equipment system (SCE) that will be used as the core of the HES. This system provides control of the NaK circulation between the MARVEL reactor and the subsequent process heat utilization systems. It does not include design of the Intermediate Heat Exchangers and piping inside the T-REXc pit in which the reactor is located. B. The MARVEL microreactor will be installed in the Transient Reactor Test Facility (TREAT) building in the Transient Reactor Test (TREAT) Micro-Reactor Experiment Cell (T-REXc) C. An INL Subcontractor has developed a conceptual design for this system per SPC-71145, referred to in that specification as the Process Heat Extraction System. SPC-71260 is based on the pumped NaK loop concept developed under SPC-71145. D. The SCE system design and (as option scope) fabrication shall be provided by the awardee of the subcontract (Subcontractor hereafter) pertaining to this Specification. Prior to shipment, the SCE will be fabricated, assembled, and tested at the Subcontractor’s facility. After successful completion of acceptance testing, the SCE and associated equipment will be shipped to the Materials and Fuels Complex (MFC) at the INL (Contractor’s Facility hereafter) to be installed by others in TREAT/T-REXc.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

Velocity Extraction Using Complete Time-Domain Waveform Data and Audio Machine Learning

We developed a new machine learning-based tool for extracting information from interferometry measurements: MIDWAZE (Modular Interferometry Direct Waveform AnalyZEr). This paper showcases MIDWAZE’s ability to extract an object’s velocity information from Photonic Doppler Velocimetry (PDV) data at near-human accuracy with little to no human intervention. MIDWAZE can extract velocities roughly 350 times as fast as a human analyst "rushing" to complete their extractions, with similar extraction accuracy. MIDWAZE’s most outstanding feature is that it operates directly in waveform/temporal space, freeing analysis from certain limitations imposed by traditional spectrogram-based approaches and opening the way to "phase aware" PDV analysis. MIDWAZE also has limited ability to discriminate between different solid objects, which we develop as a first step towards automated discrimination of different kinds of objects such as ejecta clouds.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Comparing the extraction performance of cyclodextrin-containing supramolecular deep eutectic solvents versus conventional deep eutectic solvents by headspace single drop microextraction

A headspace single drop microextraction (HS-SDME) method coupled with high performance liquid chromatography was developed to compare the extraction of eighteen aromatic organic pollutants from aqueous solutions using cyclodextrin-based supramolecular deep eutectic solvents (SUPRADESs) and alkylammonium halide-based conventional deep eutectic solvents (DESs). Different derivatives of beta-cyclodextrin (β-CD) were employed as hydrogen bond acceptors (HBA) in SUPRADESs and the extraction performance investigated. SUPRADES comprised of the 20 wt% native β-CD HBA provided the highest enrichment factors of analytes compared to SUPRADESs comprised of other derivatives of β-CD (random methylated β-cyclodextrin, heptakis(2,3,6-tri-O-methyl)-β-cyclodextrin, and 2-hydroxypropyl β-cyclodextrin). In addition, native β-CD and its derivatives were dissolved in the neat DESs and their effect on the extraction of analytes examined. Dissolution of 20 wt% native β-CD in the choline chloride ([Ch + ][Cl - ]):2Urea DES resulted in a significant increase in the extraction efficiencies of target analytes compared to the neat [Ch + ][Cl - ]:2Urea DES. Under optimum conditions, the extraction method required a solvent microdroplet of 6.5 μL, 1000 rpm stir rate, 30% (w/v) salt concentration, and a temperature of 40 °C. The tetrabutylammonium chloride: 2 lactic acid DES resulted in the highest enrichment factors while the [Ch + ][Cl - ]:2Urea DES had the lowest for most of the analytes among the evaluated solvents. The method provided limits of detection (LODs) down to 35 μg L -1 . Finally, the developed method was applied for the analysis of spiked tap and lake water, where relative recoveries ranging from 83.7% -119.7% and relative standard deviations lower than 19.2% were achieved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Extraction of high-purity medium-chain-length polyhydroxyalkanoates via combined mechanical treatment and mild oxidation

Polyhydroxyalkanoates (PHAs) are a class of polyester polymers of microbial origin and considered biodegradable alternatives to conventional plastics. To make PHAs cost-competitive with synthetic plastics, their production cost, including extraction cost, should be significantly reduced. Herein, this study aimed to develop an effective extraction method based on combined mechanical disruption and chemical treatment for the recovery of high-purity medium-chain-length PHAs (mcl-PHAs) at a lower cost. mcl-PHAs-accumulating Pseudomonas strains were used for PHA extraction via high-pressure homogenization (HPH) coupled with surfactant treatment and mild alkaline hydrogen peroxide oxidation. The mechanical-chemical method was found to have strong synergy for PHA extraction while minimizing PHA depolymerization. The optimized condition resulted in nearly 90 % mcl-PHA recovery with high purity (>91 %). The extracted high-purity PHAs exhibited thermal and mechanical properties suitable for downstream applications entailing flexible and elastomeric materials.

42 ENGINEERING↗
DOE OSTI2020

Effect of hydrophobic ionic liquids aqueous solubility on metal extraction from hydrochloric acid media: Mathematical modelling and trivalent thallium behavior

A mathematical model to explain cations’ solubility of both protic and aprotic ionic liquids in a wide range of hydrochloric acid solutions has been developed. The concept of this model is based on an assumption of the mineral acid extraction into the organic phase, formation of a salt there between an ionic liquid cation and chloride-anion due to ions recombination and partial salt back-extraction. The proposed approach allows estimating corresponding extraction constants. Comparison of calculated and experimentally measured solubility product constants shows that they are in good agreement. It has been determined also that the more the hydrophilicity of the ionic liquids’ cation the more hydrochloric acid is extracted. Furthermore, this model has been utilized to facilitate analysis of thallium transfer into hydrophobic ionic liquids providing insights into the mechanism of metal extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Behavior of astatine and bismuth in non-conventional solvents: Extraction into imidazolium-based ionic liquid and methyl anthranilate with active pharmaceuticals binary mixtures from nitric acid media

Astatine is one of the least chemically studied elements and its behavior in the presence of non- conventional solvents has not been investigated before. This work considers both hydrophobic ionic liquids and binary mixtures as alternatives to conventional solvents. The study is based on the extraction of astatine and bismuth (target material required to produce astatine) into imidazolium-based ionic liquid, and binary mixtures formed by active pharmaceuticals (ibuprofen, lidocaine) and a food grade ingredient (methyl anthranilate). It is shown that both the ionic liquid and binary mixtures can successfully extract At from nitric acid media, but extraction of Bi into the ionic liquid is very inefficient, resulting in a good separation factor for these two elements in the entire studied acidity range. Extraction of At into binary mixtures is very efficient, having distribution ratio values as high as 1000, while the behavior of Bi under these conditions depends on the composition of the mixture. Furthermore, a mathematical model has been developed to fit both At and Bi experimental data and applied to determine corresponding thermodynamic extraction constants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Anhydrous volatile fatty acid extraction through omniphobic membranes by hydrophobic deep eutectic solvents: Mechanistic understanding and future perspective

Volatile fatty acids (VFAs) derived from arrested anaerobic digestion (AD) can be recovered as a valuable commodity for value-added synthesis. However, separating VFAs from digestate with complex constituents and a high-water content is an energy-prohibitive process. This study developed an innovative technology to overcome this barrier by integrating deep eutectic solvents (DESs) with an omniphobic membrane into a membrane contactor for efficient extraction of anhydrous VFAs with low energy consumption. Here, a kinetic model was developed to elucidate the mechanistic differences between this novel omniphobic membrane-enabled DES extraction and the previous hydrophobic membrane-enabled NaOH extraction. Experimental results and mechanistic modeling suggested that VFA extraction by the DES is a reversible adsorption process facilitating subsequent VFA separation via anhydrous distillation. High vapor pressure of shorter-chain VFAs and low Nernst distribution coefficients of longer-chain VFAs contributed to DES-driven extraction, which could enable continuous and in-situ recovery and conversion of VFAs from AD streams.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Establishing a versatile toolkit of flux enhanced strains and cell extracts for pathway prototyping

Building and optimizing biosynthetic pathways in engineered cells holds promise to address societal needs in energy, materials, and medicine, but it is often time-consuming. Cell-free synthetic biology has emerged as a powerful tool to accelerate design-build-test-learn cycles for pathway engineering with increased tolerance to toxic compounds. However, most cell-free pathway prototyping to date has been performed in extracts from wildtype cells which often do not have sufficient flux towards the pathways of interest, which can be enhanced by engineering. Here, in this study, to address this gap, we create a set of engineered Escherichia coli and Saccharomyces cerevisiae strains rewired via CRISPR-dCas9 to achieve high-flux toward key metabolic precursors; namely, acetyl-CoA, shikimate, triose-phosphate, oxaloacetate, α-ketoglutarate, and glucose-6-phosphate. Cell-free extracts generated from these strains are used for targeted enzyme screening in vitro. As model systems, we assess in vivo and in vitro production of triacetic acid lactone from acetyl-CoA and muconic acid from the shikimate pathway. The need for these platforms is exemplified by the fact that muconic acid cannot be detected in wildtype extracts provided with the same biosynthetic enzymes. We also perform metabolomic comparison to understand biochemical differences between the cellular and cell-free muconic acid synthesis systems (E. coli and S. cerevisiae cells and cell extracts with and without metabolic rewiring). While any given pathway has different interfaces with metabolism, we anticipate that this set of pre-optimized, flux enhanced cell extracts will enable prototyping efforts for new biosynthetic pathways and the discovery of biochemical functions of enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Multiplicity of Th(IV) and U(VI) HEH[EHP] Chelates at Low Temperatures from Concentrated Nitric Acid Extractions

Organophosphorus extractants have been widely investigated for lanthanide recovery from ore and for application in the reprocessing of spent nuclear fuel, such as in Advanced TALSPEAK schemes. Determining the speciation of the extracted metal complex in the organic phase remains a significant challenge. A better understanding of the variability of HEH[EHP]–actinide complexes and the speciation of chelates for tetra- and hexavalent actinides can improve the predictability of actinide phase transfer in such biphasic systems. Here, the extraction of Th(IV) and U(VI) from nitric acid media using HEH[EHP] in heptane is examined. The distribution ratio as a function of nitric acid concentration was quantified using UV–vis spectroscopy, and then the speciation of HEH[EHP]–metal complexes in the organic phase was investigated using Fourier transform infrared (FTIR) spectroscopy and low-temperature 31 P nuclear magnetic resonance (NMR) spectroscopy. In addition to perturbation of the vibrational modes proximal to the phosphonic moiety in HEH[EHP] in the FTIR spectra, the appearance of a nitrate signal was found in the organic phase following extraction from the highest acidity conditions for U(VI). The 31 P NMR spectra of the organic phase at a low temperature (-70 °C) exhibited a surprising number (n) of resonances (n ≥ 7 for Th(IV) and n ≥ 11 for U(VI)), with the distribution between these resonances changing with the initial concentration of nitric acid in the aqueous phase. These results indicate that the compositions of the inner and outer spheres of the extracted actinides in the organic phase are more diverse than initially thought.

31P NMR↗
DOE OSTI2023

Controlling Extraction of Rare Earth Elements Using Functionalized Aryl-vinyl Phosphonic Acid Esters

Ligands that can discriminate between individual rare earth elements are important for production of these critical elements. A set of aryl-vinyl phosphonic acid ligands for extracting rare earth elements were designed and synthesized under the hypothesis that the strength of the rare earth-ligand interactions could be tuned by changing the dipole moment of the ligand. The ligands were synthesized via a two-step reaction procedure using a Heck coupling reaction to functionalize vinyl phosphonic acid, followed by Steglich esterification to obtain high-purity styryl phosphonic acid monoesters with varying dipole moments along the P-C bond. The metal binding strength and composition of the rare earth complexes formed with these styryl phosphonic acid monoesters were experimentally studied by liquid-liquid extraction techniques, while DFT calculations were performed to determine the dipole moments of the free and complexed ligands and the electronic structure of the complexes formed. All three prepared ligands were much stronger extracting agents for europium(III) than the dialkylphosphonic acids usually used for this separation. However, the order of increasing extraction strength was found to match the order of the decreasing calculated dipole moment along the P-C bond of the three styryl-based ligands, rather than correlating with increasing ligand basicity, as reflected by the pK a of the ligands. Finally, these findings suggest that this approach can be used to systematically alter the extraction strength of aromatic phosphonic monoesters for rare earth element purification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mechanistic Insights into Cell-Free Gene Expression through an Integrated -Omics Analysis of Extract Processing Methods

Cell-free systems derived from crude cell extracts have developed into tools for gene expression, with applications in prototyping, biosensing, and protein production. Key to the development of these systems is optimization of cell extract preparation methods. However, the applied nature of these optimizations often limits investigation into the complex nature of the extracts themselves, which contain thousands of proteins and reaction networks with hundreds of metabolites. In this report we sought to uncover the black box of proteins and metabolites in Escherichia coli cell-free reactions based on different extract preparation methods. We assess changes in transcription and translation activity from σ70 promoters in extracts prepared with acetate or glutamate buffer and the common post-lysis processing steps of a runoff incubation and dialysis. We then utilize proteomic and metabolomic analyses to uncover potential mechanisms behind these changes in gene expression, highlighting the impact of cold shock-like proteins and the role of buffer composition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Poplar lignin structural changes during extraction in γ-valerolactone (GVL)

In this paper, we describe an approach for producing both high quality and high quantity of lignin through studying the structural change of lignin during treatment of poplar wood in γ-valerolactone (GVL) for a range of temperatures (from 80 to 120 °C) and reaction time at temperature (from 1 to 24 h). Throughout the study, various techniques, including nuclear magnetic resonance (NMR) spectroscopies (solution- and gel-state 1 H –13 C 2D HSQC and 31 P) and gel-permeation chromatography (GPC) were applied to characterize the lignin structures. As the GVL-extracted lignin yield increases, the level of β-ether units decreases and the level of condensation products increases. The β-ether content, the aliphatic hydroxyl group content, and the molecular weight of the GVL-extracted lignin fractions were close to the poplar lignin from other preparation methods (e.g., enzyme lignin). A two-step hydrolytic process (120 °C, 2 × 15 min) gave a higher lignin yield (56.5% vs. 54.8%) with three times higher β-ether content (31.9% vs. 10.6%) than lignin extracted from a single-step process at 120 °C for 1 h. The results demonstrate that multiple-step cycling of cosolvent-assisted hydrolysis can help preserve more of the virgin ether-bond structures of GVL-extracted poplar lignin. Such a strategy can also be applied to a fully continuous-flow reactor system in future research to further improve both the productivity and quality of GVL-extracted lignin.

2D HSQC NMR↗
DOE OSTI2021

The pervasive impact of critical fluctuations in liquid–liquid extraction organic phases

Liquid-liquid extraction is an essential chemical separation technique where polar solutes are extracted from an aqueous phase into a nonpolar organic solvent by amphiphilic extractant molecules. A fundamental limitation to the efficiency of this important technology is third phase formation, wherein the organic phase splits upon sufficient loading of polar solutes. The nanoscale drivers of phase splitting are challenging to understand in the complex hierarchically structured organic phases. In this study, we demonstrate that the organic phase structure and phase behavior are fundamentally connected in a way than can be understood with critical phenomena theory. For a series of binary mixtures of trialkyl phosphate extractants with linear alkane diluents, we combine small angle x-ray scattering and molecular dynamics simulations to demonstrate how the organic phase mesostructure over a wide range of compositions is dominated by critical concentration fluctuations associated with the critical point of the third phase formation phase transition. These findings reconcile many longstanding inconsistencies in the literature where small angle scattering features, also consistent with such critical fluctuations, were interpreted as reverse micellar-like particles. Altogether, this study shows how the organic phase mesostructure and phase behavior are intrinsically linked, deepening our understanding of both and providing a new framework for using molecular structure and thermodynamic variables to control mesostructure and phase behavior in liquid-liquid extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

HyPerPy (Hydrogen Extraction and Parabolic Trough Plant Performance Models using Python) [SWR-21-53]

The HyPerPy package consists of three scripts: 1) Model for Hydrogen Tracking in Parabolic Trough Power Plants, 2) Model for Receiver Performance, and 3) Model for Hydrogen Extraction Process. The power plant model (1) tracks hydrogen generation and transport within the circulating heat transfer fluid (HTF) of the power plant. This script is a transient, initial value simulation, in which the hydrogen concentration in the circulating HTF is 0 moles per cubic meter everywhere at time 0 seconds. Hydrogen concentration is calculated at discrete locations within the circulating HTF with 4-second time resolution. During each time step, the change in hydrogen concentration due to hydrogen generation and permeation is calculated for each location according to the local HTF temperature, vessel or piping properties, hydrogen concentration and partial pressure. This model predicts hourly hydrogen concentrations for typical operating days in the spring, summer, fall, and winter seasons. Data is used to create hourly mappings of hydrogen concentrations for a typical operating year. The receiver model (2) uses a 1-hour time step to estimate getter loading and annulus pressure. For each time step, the model uses HTF and ambient temperature data to estimate absorber tube, bellows, and getter temperatures for the time step. In addition, the model uses hourly HTF hydrogen concentrations that are generated by the power plant model (1), and annulus hydrogen pressure from the previous time step. With these data, the model calculates the moles of hydrogen permeating across the absorber tube and bellows during the time step. The net change in moles hydrogen is added or subtracted from the getter loading for the previous time step, and the hydrogen pressure is re-calculated based on getter loading and temperature. The model uses this algorithm to simulate hydrogen permeation and loading 24 hours per day, 365 days per year using seasonal temperature data. The model repeats these calculations for 25 years to create a mapping of receiver getter loading and annulus hydrogen pressure for four seasons of each year. The model for hydrogen extraction (3) estimates hydrogen extraction rates for a specific separation module configuration. The rate depends primarily on membrane area, vacuum pump performance, headspace gas flowrate to the membrane, and headspace gas hydrogen partial pressure. This model has two versions. The steady-state version predicts hydrogen extraction rates when the module is operating in separation mode. The dynamic version predicts hydrogen transfer through the membrane when the module is operating in sensor mode. The steady-state version is used with the plant model (1) to predict hydrogen partial pressures in the power plant when the extraction process is operating.

Glatzmaier, Gregory↗
DOE OSTI2024

From Text to Maps: LLM-Driven Extraction and Geotagging of Epidemiological Data

Epidemiological datasets are essential for public health analysis and decision-making, yet they remain scarce and often difficult to compile due to inconsistent data formats, language barriers, and evolving political boundaries. Traditional methods of creating such datasets involve extensive manual effort and are prone to errors in accurate location extraction. To address these challenges, we propose utilizing large language models (LLMs) to automate the extraction and geotagging of epidemiological data from textual documents. Our approach significantly reduces the manual effort required, limiting human intervention to validating a subset of records against text snippets and verifying the geotagging reasoning, as opposed to reviewing multiple entire documents manually to extract, clean, and geotag. Additionally, the LLMs identify information often overlooked by human annotators, further enhancing the dataset’s completeness. Our findings demonstrate that LLMs can be effectively used to semi-automate the extraction and geotagging of epidemiological data, offering several key advantages: (1) comprehensive information extraction with minimal risk of missing critical details; (2) minimal human intervention; (3) higher-resolution data with more precise geotagging; and (4) significantly reduced resource demands compared to traditional methods.

Harrod, Karly↗
DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Feature Extraction: Improving Remote Sensor Classification of Non-Proliferation

This research focuses on developing algorithms for nuclear non-proliferation detection using remote sensor modeling. To improve the performance of classification models, we implemented a data pipeline with feature extraction. This pipeline takes raw data and transforms it into smaller data points called features that still describe the model. Improving this classification works towards the departments of energy’s missions of ensuring American’s security and prosperity by creating technology that addresses nuclear challenges. To conduct this analysis, we used the Python programming language and some key packages, including tsfresh and TSFEL. Originally tsfresh was selected because it has the most statistical features out of all the packages. Later TSFEL was incorporated due to the additional features it can extract from data, such as temporal and spectral. However, feature extraction becomes challenging in the presence of missing values. In this case, two additional Python packages were added to our workflow, NumPy and pandas, allowing for the feature extraction process to handle unknown values. Our data pipeline was tested on data collected from a simulation that describes the process state of a physical example. The results show the pipeline’s capability to consume and extract a total 17 features from tabular data. Future work includes producing classifications using decision tree-based models such as XGBoost and improving data collection by analyzing feature importance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Evaluation of DNA Extraction Efficiency in Diverse Algae Strains Using Commercial Kits and Lysis Approaches

Efficient DNA extraction is essential for accurately monitoring microalgae communities in large-scale cultivation systems such as raceway ponds and wastewater ponds. Traditional phenol chloroform extracts are a staple in microbiology but are obsolete for routine sampling due to its high toxicity reagents and time intensive setups. Commercial DNA extraction kits are more favorable for the microbes found in these ponds, but lack specific kits made for these communities. Little is known about which kits perform the best, leading researchers to use a variety of different kits with inconsistent results. This project compared one precipitation based commercial kit (Lucigen Masterpure) and five wash based kits (Monarch, Zymo Quick-DNA, and three Qiagen DNeasy kits) using four brackish algae strains to determine which methods yield the greatest quantity and quality of genomic DNA. Extractions were evaluated using the manufacturers protocol, and additional pretreatment options were administered before a single kit to compare its potential in being added routinely before extractions. Pretreatment options included both cryogenic freeze-thawing and heat incubation using enzymes. DNA was quantified using Qubit fluorometry and NanoDrop purity ratios. Overall, the Qiagen PowerWater kit provided the highest DNA yield and purity, but at a significantly higher cost then the precipitation-based kit (MasterPure). It was also noted that while the precipitation-based kit was significantly cheaper, provided similar results, it took significantly more time to complete a single run. Cryogenic pretreatment (6x cycles) increased average DNA yields by up to 80%, whereas enzymatic pretreatment most improved purity ratios without substantially improving quantity. The results suggest that it may be more cost and time efficient to use Qiagen kits with the addition of lysis pretreatments to procure better results. Future works includes developing a better system to efficiently collect multi variable data, and to upscale to artificial polycultures using similar methodologies alongside sequencing to confirm kit results.

59 BASIC BIOLOGICAL SCIENCES↗