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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 163 records · Page 9

Production, fuel properties and combustion testing of an iso-olefins blendstock for modern vehicles

With the increasing pressure to decarbonize the transportation sector, exploring strategies that can reduce emissions from light-duty vehicles (LDV) has become critical. Bioblendstocks that allow for higher engine efficiency and fuel economy could complement vehicle electrification and help reach carbon neutrality by 2050. In this context, the potential of a mixture of iso-olefins as a bioblendstock was investigated for multimode boosted spark-ignition (SI)/advanced compression ignition (ACI) engine operation designed to achieve higher overall vehicle fuel economy. By establishing the relationship between the molecular structure of iso-olefins and research octane number (RON), octane sensitivity (S) (i.e., the difference between RON and motor octane number [MON]), and phi-sensitivity a dimethyl-hexenes rich olefins mixture (DMHROM) was identified as a preferred blendstock for SI/ACI combustion engines. Here, a pathway for DMHROM production from biomass-derived ethanol was developed and scaled up. More than 1 gallon of DMHROM blendstock was produced for fuel properties assessment including engine testing. Measurements in a Cooperative Fuel Research Engine showed that the DMHROM blendstock possesses a RON of 94 and S of 13.5, and blends synergistically. Rapid compression machine tests coupled with single-cylinder gasoline direct injection engine measurements demonstrated the 20 vol.% DMHROM blend has higher phi-sensitivity than an olefin-free gasoline base fuel and a typical California Reformulated Gasoline Blendstock for Oxygenate Blending (CARBOB) gasoline fuel. These results demonstrate the potential of DMHROM for improving gasoline fuel performance and quality for operation under ACI conditions. The effectiveness of the aftertreatment system in mitigating emissions was verified and showed that the pure DMHROM blendstock and 20 vol.% blend would not increase non-methane organic gases, NO x , and carbon monoxide (CO) emissions. The DMHROM blendstock was found to slightly decrease sooting tendency when added to a gasoline-base fuel (i.e., ~6% reduction at 20 vol.% blending level). Oxidation stability and lubricant compatibility were both confirmed for the 20 vol.% blend. Overall, these results demonstrate that dimethyl-hexenes have potential for improving engine efficiency and fuel economy while meeting emissions regulations and ASTM specifications for gasoline fuel.

09 BIOMASS FUELS↗

Investigation of SF6 Alternatives in Spark Gap Switches for GWP Reduction

This primary purpose of this project was to evaluate alternative gas mixtures to sulfur hexafluoride (SF6) developed for high voltage power delivery applications for use in high voltage spark gap switches. These SF6 alternatives lower global warming potential emissions and enable improvements to the pressure-voltage design space. A combined experimental, computational, and theoretical study was used to quantify the impact of persistent breakdown products on the breakdown distribution of SF6-replacement gas mixtures. Viable SF6 replacements suitable for use in spark gap switches were studied to enable performance and agility improvements for next-generation pulsed power research relevant to national security missions. Experimental campaign included establishing parameters of switch gases as function of concentration. Various concentrations and pressures were tested for trends in breakdown voltage, repeatability, and durability, and breakdown constituents. A zero-dimensional plasma global model was used to simulate the plasma arc decay and recombination process in spark-gap switches relevant to the Z machine. Finally, a complete and consistent set of electron-neutral collision cross-sections for the novel insulating gas C4F7N is reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pyrene-fused hexaarylbenzene luminogens: Synthesis, characterization, and aggregation-induced emission enhancement

Six novel pyrene-fused hexaarylbenzene derivatives (3a-f) were designed, synthesized, and characterized, which exhibited aggregation-induced emission enhancement (AIEE) in the aggregated state by means of THF/H 2 O mixtures. Techniques such as theoretical calculations, single crystal X-ray diffraction, and photophysical measurements in solution and in the solid state were employed to illustrate the tunable, variable, and sensitive AIEE features in this system. Both theoretical and experimental results revealed that the nature of the multiple photoluminescence should be taken into account when elucidating and designing the multiple photoluminescence phenomenon and molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations

Solubility of redox-active molecules is an important determining factor of the energy density in redox flow batteries. However, the advancement of electrolyte materials discovery has been constrained by the absence of extensive experimental solubility datasets, which are crucial for leveraging data-driven methodologies. In this study, we design and investigate a highly automated workflow that synergizes a high-throughput experimentation platform with a state-of-the-art active learning algorithm to significantly enhance the solubility of redox-active molecules in organic solvents. Our platform identifies multiple solvents that achieve a remarkable solubility threshold exceeding 6.20 M for the archetype redox-active molecule, 2,1,3-benzothiadiazole, from a comprehensive library of more than 2000 potential solvents. Significantly, our integrated strategy necessitates solubility assessments for fewer than 10% of these candidates, underscoring the efficiency of our approach. Our results also show that binary solvent mixtures, particularly those incorporating 1,4-dioxane, are instrumental in boosting the solubility of 2,1,3-benzothiadiazole. Beyond designing an efficient workflow for developing high-performance redox flow batteries, our machine learning-guided high-throughput robotic platform presents a robust and general approach for expedited discovery of functional materials.

25 ENERGY STORAGE↗

Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis

Abstract Solid‐state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing reaction conditions and precursors for ceramic synthesis can be a laborious, trial‐and‐error process, as heterogeneous mixtures of precursors often evolve through a complicated series of reaction intermediates. Here, ab initio thermodynamics is used to model which pair of precursors has the most reactive interface, enabling the understanding and anticipation of which non‐equilibrium intermediates form in the early stages of a solid‐state reaction. In situ X‐ray diffraction and in situ electron microscopy are then used to observe how these initial intermediates influence phase evolution in the synthesis of the classic high‐temperature superconductor YBa 2 Cu 3 O 6+ x (YBCO). The model developed herein rationalizes how the replacement of the traditional BaCO 3 precursor with BaO 2 redirects phase evolution through a low‐temperature eutectic melt, facilitating the formation of YBCO in 30 min instead of 12+ h. Precursor selection plays an important role in tuning the thermodynamics of interfacial reactions and emerges as an important design parameter in planning kinetically favorable synthesis pathways to complex ceramic materials.

36 MATERIALS SCIENCE↗

Breakthrough Conductivity Enhancement in Deep Eutectic Solvents via Grotthuss–Type Proton Transport

There is an increasing demand for the development of ion-conducting electrolytes for energy storage systems. Much attention is directed toward deep eutectic solvents as potential candidates. In the search for highly conductive systems, the possibility of designing deep eutectic solvents with Grotthuss-type proton transport is widely overlooked. Herein, ethaline, a mixture of choline chloride and ethylene glycol is used in a 1:2 molar ratio, to induce a significant conductivity increase with the addition of water and sulfuric acid (H 2 SO 4 ). The achieved breakthrough conductivity is analyzed experimentally and simulated with ab initio molecular dynamics (AIMD). At sufficient water content, an H-bonding network is formed that leads to a significant breakthrough conductivity based on H 2 SO 4 -derived proton transfer following the long-established Grotthuss proton transport mechanism. This result is substantiated by the positive deviation from the ideal KCl line in the Walden plot. Specifically, the data series positioned above the reference line indicates a Grotthuss mechanism in action. The AIMD simulations demonstrate proton transfer between water and ethylene glycol, supported by simulation frames captured at various times.

36 MATERIALS SCIENCE↗

Characterization of the ALSEP Process at Equilibrium: Speciation and Stoichiometry of the Extracted Complex

We have determined the identity of the complexes extracted into the ALSEP process solvent from solutions of nitric acid. The ALSEP process is a new solvent extraction separation designed to separate americium and curium from trivalent lanthanides in irradiated nuclear fuel. ALSEP employs a mixture of two extractants, 2-ethylhexyl phosphonic acid mono-2-ethylhexyl ester (HEH[EHP]) and N,N,N',N'-tetra(2-ethylhexyl)diglycolamide (TEHDGA) in n-dodecane, which makes it difficult to ascertain the nature of the extracted metal complexes. It is often asserted that the weak acid extractant HEH[EHP] does not participate in the extracted complex under ALSEP extraction conditions (2–4 M HNO 3 ). However, the analysis of the Am extraction equilibria, Nd absorption spectra, and Eu fluorescence emission spectra of metal-loaded organic phases argues for the participation of HEH[EHP] in the extracted complex despite the high acidity of the aqueous phases. The extracted complex was determined to contain fully protonated molecules of HEH[EHP] with an overall stoichiometry of M(TEHDGA) 2 (HEH[EHP]) 2 ·3NO 3 . Computations also demonstrate that replacing one TEHDGA molecule with one (HEH[EHP]) 2 dimer is likely energetically favorable compared to Eu(TEHDGA) 3 ·3NO 3 , whether the HEH[EHP] dimer is monodentate or bidentate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intelligent Electrochemical Sensors for Precise Identification of Volatile Organic Compounds Enabled by Neural Network Analysis

The volatile organic compounds (VOCs) in a wide spectrum of categories were identified as biomarkers in aquatic environments, playing an important role in marine and freshwater ecology and global atmospheric chemistry. VOCs released from biofuel have also attracted increasing attention. Although the importance has been recognized, the portable detection and analysis methods of VOC in aquatic systems have not yet been well developed and understood. Here, in this work, we innovatively proposed an intelligent electrochemical sensing approach to classify and quantify VOCs in solution. Utilizing the cyclic voltammetry (CV) method with an ionic liquid (IL)-based electrolyte, we analyzed 50 μL samples of various VOC analytes, including acetic acid (AC), acetone, dimethylformamide (DMF), dimethyl sulfoxide (DMSO), ethanol, formaldehyde, formic acid, methanol, methyl formate (MF), toluene, and a formaldehyde-methanol mixture, along with deionized water (DI water). The generated voltammograms were subsequently analyzed using our uniquely designed and optimized 1-D convolutional neural network (1D-CNN). This deep-learning algorithm achieved a 99.09% accuracy in VOC classification validated through fivefold cross-validation and demonstrated an impressive 94.4% test accuracy for methanol detection within a 10 μL error range. For quantification, the system accurately categorized methanol volumes ranging from 0 to 50 μL in 10 μL increments, achieving a 98.18% accuracy. A notable linear correlation (R2 = 95.56%) was found between max current density at the oxidation peak and methanol volume, with the limit of detection (LOD) at 9.3 μL. Such a sensing method exhibits potential for portability, high accuracy, and generalization in the classification and quantification, ultimately reshaping the realm of VOC analysis in solution.

42 ENGINEERING↗

Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures

Bacterial mRNA sequencing is inefficient due to the abundance of ribosomal RNA that is challenging to deplete. While commercial kits target rRNA from common bacterial species, they are frequently inefficient when applied to divergent species, including those from environmental isolates. Similarly, other methods typically employ large probe sets that tile the entire length of rRNAs; however, such approaches are infeasible when applied to many species. Therefore, we present EMBR-seq+, which requires fewer than 10 oligonucleotides per rRNA by combining rRNA blocking primers with RNase H-mediated depletion to achieve rRNA removal efficiencies of up to 99% in diverse bacterial species. Furthermore, in more complex microbial co-cultures between Fibrobacter succinogenes strain UWB7 and anaerobic fungi, EMBR-seq+ depleted both bacterial and fungal rRNA, with a fourfold improvement in bacterial rRNA depletion compared with a commercial kit, thereby demonstrating that the method can be applied to non-model microbial mixtures. Notably, for microbes with unknown rRNA sequences, EMBR-seq+ enables rapid iterations in probe design without requiring to start experiments from total RNA. Finally, efficient depletion of rRNA enabled systematic quantification of the reprogramming of the bacterial transcriptome when cultured in the presence of the anaerobic fungi Anaeromyces robustus or Caecomyces churrovis. We observed that F. succinogenes strain UWB7 downregulated several lignocellulose-degrading carbohydrate-active enzymes in the presence of anaerobic gut fungi, suggesting close interactions between two cellulolytic species that specialize in different aspects of biomass breakdown. Thus, EMBR-seq+ enables efficient, cost-effective, and rapid quantification of the transcriptome to gain insights into non-model microbial systems.

59 BASIC BIOLOGICAL SCIENCES↗

Alkaline-SDS cell lysis of microbes with acetone protein precipitation for proteomic sample preparation in 96-well plate format

Plate-based proteomic sample preparation offers a solution to the large sample throughput demands in the biotechnology field where hundreds or thousands of engineered microbes are constructed for testing is routine. Meanwhile, sample preparation methods that work efficiently on broader microbial groups are desirable for new applications of proteomics in other fields, such as microbial communities. Here, we detail a step-by-step protocol that consists of cell lysis in an alkaline chemical buffer (NaOH/SDS) followed by protein precipitation with high-ionic strength acetone in 96-well format. The protocol works for a broad range of microbes ( e . g ., Gram-negative bacteria, Gram-positive bacteria, non-filamentous fungi) and the resulting proteins are ready for tryptic digestion for bottom-up quantitative proteomic analysis without the need for desalting column cleanup. The yield of protein using this protocol increases linearly with respect to the amount of starting biomass from 0.5–2.0 OD*mL of cells. By using a bench-top automated liquid dispenser, a cost-effective and environmentally-friendly option to eliminating pipette tips and reducing reagent waste, the protocol takes approximately 30 minutes to extract protein from 96 samples. Tests on mock mixtures showed expected results that the biomass composition structure is in close agreement with the experimental design. Lastly, we applied the protocol for the composition analysis of a synthetic community of environmental isolates grown on two different media. This protocol has been developed to facilitate rapid, low-variance sample preparation of hundreds of samples and allow flexibility for future protocol development.

59 BASIC BIOLOGICAL SCIENCES↗

Rational Electrolyte Design for Elevated-Temperature and Thermally Stable Lithium-Ion Batteries with Nickel-Rich Cathodes

As the energy density of lithium-ion batteries (LIBs) increases, the shortened cycle life and the increased safety hazard of LIBs are drawing increasing concerns. To address such challenges, a series of localized high-concentration electrolytes (LHCEs) based on a solvating-solvent mixture of tetramethylene sulfone and trimethyl phosphate and a high flash-point diluent 1H,1H,5H-octafluoropentyl 1,1,2,2-tetrafluoroethyl ether were designed. The LHCEs exhibited non-flammability and greatly suppressed heat release at high temperatures, which would potentially improve the safety performance of the LIBs. Moreover, the optimal LHCE achieved capacity retentions of 87.1% and 81.7% in graphite||LiNi 0.8 Mn 0.1 Co 0.1 O 2 cells after 500 cycles at 25 °C and 45 °C, respectively, which were significantly better than the conventional electrolyte, whose capacity retentions were only 75.2% and 38.5% under the same condition. Mechanistic studies revealed that the LHCE not only formed a more robust solid electrolyte interphase, but also exhibited improved anodic stability, compared with the conventional electrolyte. Further, this work sheds light in rational electrolyte design for high energy density LIBs with high battery performance and low safety concerns.

25 ENERGY STORAGE↗

Characteristics of oxide-dispersion strengthened alloys produced by high-temperature severe deformation

This study is to explore an economically attractive and technically feasible processing method for oxide-nanoparticle strengthened alloys for fusion reactor application. Despite many scientific merits of the advanced oxide-dispersion strengthened (ODS) alloys, such as the nanostructured ferritic alloy (NFA) 14YWT, the only viable production path for a high-quality NFA is the high-power mechanical alloying process. This process is often a multi-day high-speed ball milling of alloy powder with a small quantity of yttria (Y 2 O 3 ) powder, followed by the milled-powder consolidation using extrusion or other methods and additional thermomechanical processing (TMP) for property control. This complex production path, including the low-temperature mechanical alloying in particular, has limited technical advancement toward the cost-effective and scale-up production of ODS alloy components. To overcome such a practical limitation, we proposed to explore alternative low-cost processing routes using traditional thermomechanical processing (TMP) method only. Further, a series of continuous TMP cycles, which were designed to impose high-temperature severe plastic deformation (HT-SPD) conditions to the consolidated powder mixtures, were applied to achieve the effective distribution of oxide particles in nanograin structure and thus desirable mechanical properties. Since the reduced-activation ferritic-martensitic (RAFM) alloy powders (Fe-10Cr and Fe-14Cr alloys with various Y contents) are available in our inventory, we focused to utilize the new solid-state synthesis approach for controlling oxide (oxygen source) dissolution and nanoscale clustering in nanograin structure in those alloys. A combination of powder consolidation at 900 °C and continuous thermomechanical activation at 600 °C yielded two essential ODS alloy microstructure contents–nanograin structure and nanoparticle distribution–and thus demonstrated a good combination of strength and ductility.

36 MATERIALS SCIENCE↗

Designing Peptide Fossils That Model the Evolution of the Bacterial Ferredoxin Fold

Electron transfer coupled to redox chemistry is at the heart of metabolism. The proteins responsible for moving electrons (protein electron carriers) must have emerged at the origin of life. The small iron–sulfur-binding bacterial ferredoxins were likely among these first proteins. Embedded within the ferredoxin sequence and structure is a symmetry that points to an ancient gene duplication event. Little is understood about the nature of ferredoxins prior to this duplication event or what environmental factors may have driven the selection for more complex forms. The deep-time molecular history of ferredoxins goes back billions of years and cannot be reconstructed by phylogenetic analyses based on amino acid sequences. Here, we use structure-guided protein design to model a fossil half-ferredoxin stage in the evolution of this fold, the semidoxins, and their symmetric full-length counterparts, the symdoxins. Semidoxin designs homodimerize, exhibiting structural, thermodynamic, and electrochemical behaviors in most cases identical to cognate symdoxins. However, the semi- and symdoxin fossil stages behave differently when incorporated into an in vivo electron transfer complementation assay. Both can support bacterial growth dependent on protein expression. Growth rates of bacteria expressing the semidoxins are much more sensitive to oxygen than those of bacteria expressing symdoxins. Motivated by the in vivo functionality of designed semidoxins, we identified putative naturally occurring semidoxins in extant anaerobic microorganisms. This is consistent with the observed in vivo oxygen sensitivity of the semidoxin designs. One natural semidoxin is shown to be folded and redox active. However, it exists as a mixture of monomers and dimers, suggesting a potential connection between semidoxins and even simpler single iron–sulfur cluster-binding peptides.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Thermolytic Production of Hydrogen from Glycolate and Common Tank Farm Organics in Simulated Waste

The Savannah River National Laboratory (SRNL) has performed testing to investigate the thermolytic production of hydrogen gas from organic species present in the Savannah River Site (SRS) Concentration, Storage, and Transfer Facilities (CSTF). SRNL designed an experimental apparatus to measure the timedependent concentration of hydrogen in the headspace over a reacting mixture of simulated caustic waste media and organic compounds as well as a methodology to calculate a steady-state hydrogen generation rate (HGR) from this data. Special focus was given to glycolate, which is not currently present in CSTF waste but will be contained in the recycle stream from the Defense Waste Processing Facility (DWPF) under the upcoming alternate reductant flowsheet.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of an In Situ Fission Gas Release Instrument for Fuel Sample Irradiations in the High Flux Isotope Reactor

Experimental measurement of gaseous fission product release with respect to temperature and burnup is a critical aspect of understanding nuclear fuel performance, validating predictive models, and qualifying new fuels. To measure this phenomenon in real-time, Oak Ridge National Laboratory has developed an instrument for measuring in situ fission gas release from small-scale fuel samples irradiated in the High Flux Isotope Reactor (HFIR). The instrument uses a continuous flow of Heover the fuel samples to sweep gaseous fission products from a sealed capsule in the HFIR Be reflector to an instrument station adjacent to the reactor. The instrument station houses two high-purity germanium (HPGe) detectors that measure decay gamma rays from fission products passing through a room temperature dwell chamber placed over the detector crystal. The sealed capsules in the reactor are designed to modulate fuel sample temperatures between 700 and 1,100°C by changing the Ar/He gas mixture surrounding the capsules during irradiation. N-type thermocouples are incorporated into the capsule housing to record real-time fuel temperatures. The capsules are heated primarily by prompt gamma rays emitted from the HFIR core with minimal heat contributions from fission in the fuel samples to minimize temperature gradients in the specimens for separate-effects characterization of the material. This paper describes modeling of time-dependent nuclear heating and fission product formation in fuel samples, thermal characteristics of the in-core capsules, and expected gaseous fission product gamma spectra at the HPGe instrument station.

Mulligan, Padhraic L [ORNL] (ORCID:000000025826540↗

Thermal-hydraulic Performance of Emerging Low GWP Refrigerant Mixture under Flow Boiling in Brazed Plate Heat Exchangers

The hydrofluorocarbon (HFC) refrigerants used in the current refrigeration systems are facing a phase-down due to their higher greenhouse effect resulting in global warming, and thus HVAC&R industry has undergone a transition to low Global Warming Potential (GWP) refrigerants. Refrigerant mixtures are attractive alternatives since their composition can be tailored to comply with environmental regulations while preserving favorable thermophysical properties. However, the new low-GWP zeotropic mixture refrigerants have two or more components with different saturation temperatures at the same pressure level, known as temperature glide, which can cause the degradation of the overall heat transfer performance. The brazed plate heat exchangers (BPHX) provide excellent heat transfer performance due to a compact design and are used in several air-conditioning and refrigeration applications. In this study, flow boiling heat transfer and the associated pressure drop of the refrigerant mixture in a vertical BPHX were experimentally investigated. The single-phase water-to-water experiments were conducted in the tested heat exchanger with a counter-flow configuration. The flow boiling experiments charged with R-134a and R-454C were then performed in a pumped refrigerant loop to evaluate its thermal-hydraulic performance. Furthermore, parametric studies of various heat fluxes, mass fluxes, vapor qualities, and saturation temperatures were also conducted.

Yang, Cheng-Min↗

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗

Characterization of a new ultra-high pressure shock tube facility for combustion and propulsion studies

A new shock tube facility has been designed, constructed, and characterized at the University of Central Florida. This facility is capable of withstanding pressures of up to 1000 atm, allowing for combustion diagnostics of extreme conditions, such as in rocket combustion chambers or in novel power conversion cycles. For studies with toxic gas impurities, the high initial pressures required the development of a gas delivery system to ensure the longevity of the facility and the safety of the personnel. Data acquisition and experimental propagation were implemented with remote access to ensure safety, paired with a LabVIEW- and Python-based user interface. Thus far, test pressures of 270 atm, blast pressures of 730 atm, and temperatures approaching 10 000 K have been achieved. The extreme limitations of this facility allow for emission spectroscopy to be performed during the oxidation of fuel mixtures, e.g., alkanes diluted in argon and carbon dioxide. Ignition delay times were determined and compared to simulations using chemical kinetic mechanisms. The design, experimental procedures, processes of analysis, and uncertainty determination are outlined, and typical pressure profiles are compared with a new gas dynamics solver and empirical correlations developed across multiple shock tube facilities. Preliminary reactive mixture analyses are included with further investigation of the mixtures outlined.

47 OTHER INSTRUMENTATION↗