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This Project Execution Plan (PEP) sets forth plans, organizations, and systems to be employed for managing the Environmental Management Spent Nuclear Fuel (SNF) Technology Development (TD) Project (project number 33645).
Ternary nitrides in the family A 3 B x N (A=Co, Ni, Fe; B=Mo; x=2,3) identified and synthesized. Experiments with Co 3 Mo 3 N in Ammonia Synthesis Reactor demonstrate cyclable NH3 production from bulk nitride under pure H 2 . Production rates were approx. constant in all the reduction steps with no evident dependence on the consumed solid-state nitrogen up to formation of 661. Material can be re-nitridized under pure N 2 (or 10% H 2 /N 2 ). Bulk N utilization per reduction step averaged between 25 – 40% of the total (2-3 hours). Rate equations and parameters extracted from data. NH 3 selectivity exceeds gas phase equilibrium at higher temperatures (in a large excess of H 2 ). Selectivity begins to decrease significantly above 650 C, N 2 production rapidly increases above 650 C seemingly due to reaction that is zero order in H 2 (thermal reduction of the nitride?). Poised to begin the systematics studies of relationships between materials and reactions.
Research is reported on the development of sensors for gas turbine combustor applications that measure real-time gas temperature using near-infrared water vapor absorption and concentration in the combustor exhaust of trace quantities of pollutant NO and CO using mid-infrared absorption. Gas temperature is extracted from the relative absorption strength of two near-infrared transitions of water vapor. From a survey of the water vapor absorption spectrum, two overtone transitions near 1800 nm were selected that can be rapidly scanned in wavelength by injection current tuning a single DFB diode laser. From the ratio of the absorbances on these selected transitions, a path-integrated gas temperature can be extracted in near-real time. Demonstration measurements with this new temperature sensor showed that combustor instabilities could be identified in the power spectrum of the temperature versus time record. These results suggest that this strategy is extremely promising for gas turbine combustor control applications. Measurements of the concentration of NO and CO in the combustor exhaust are demonstrated with mid-infrared transitions using thermo-electrically cooled, quantum cascade lasers operating near 5.26 and 4.62 microns respectively. Measurements of NO are performed in an insulated exhaust duct of a C2H4-air flame at temperatures of approximately 600 K. CO measurements are performed above a rich H2-air flame seeded with CO2 and cooled with excess N2 to 1150 K. Using a balanced ratiometric detection technique a sensitivity of 0.36 ppm-m was achieved for NO and 0.21 ppm-m for CO. Comparisons between measured and predicted water-vapor and CO2 interference are discussed. The mid-infrared laser quantum cascade laser technology is in its infancy; however, these measurements demonstrate the potential for pollutant monitoring in exhaust gases with mid-IR laser absorption.
NASA Centers continue to collaborate to characterize the chemical species and smoke particles generated by the combustion of current space-rated non-metallic materials including fluoropolymers. This paper describes the results of tests conducted February through September 2012 to identify optimal chemical markers both for augmenting particle-based fire detection methods and for monitoring the post-fire cleanup phase in human spacecraft. These studies follow up on testing conducted in August 2010 and reported at ICES 2011. The tests were conducted at the NASA White Sands Test Facility in a custom glove box designed for burning fractional gram quantities of materials under varying heating profiles. The 623 L chamber was heavily instrumented to quantify organics (gas chromatography/mass spectrometry), inorganics by water extraction followed by ion chromatography, and select species by various individual commercially-available sensors. Evaluating new technologies for measuring carbon monoxide, hydrogen cyanide, hydrogen fluoride, hydrogen chloride and other species of interest was a key objective of the test. Some of these sensors were located inside the glovebox near the fire source to avoid losses through the sampling lines; the rest were located just outside the glovebox. Instruments for smoke particle characterization included a Tapered Element Oscillating Microbalance Personal Dust Monitor (TEOM PDM) and a TSI Dust Trak DRX to measure particle mass concentration, a TSI PTrak for number concentration and a thermal precipitator for collection of particles for microscopic analysis. Materials studied included Nomex®, M22759 wire insulation, granulated circuit board, polyvinyl chloride (PVC), Polytetrafluoroethylene (PTFE), Kapton®, and mixtures of PTFE and Kapton®. Furnace temperatures ranged from 340o to 640o C, focusing on the smoldering regime. Of particular interest in these tests was confirming burn repeatability and production of acid gases with different fuel mixture compositions, as well as the dependence of aerosol concentrations on temperature.
NASA Centers continue to collaborate to characterize the chemical species and smoke particles generated by the combustion of current space-rated non-metallic materials including fluoropolymers. This paper describes the results of tests conducted February through September 2012 to identify optimal chemical markers both for augmenting particle-based fire detection methods and for monitoring the post-fire cleanup phase in human spacecraft. These studies follow up on testing conducted in August 2010 and reported at ICES 2011. The tests were conducted at the NASA White Sands Test Facility in a custom glove box designed for burning fractional gram quantities of materials under varying heating profiles. The 623 L chamber was heavily instrumented to quantify organics (gas chromatography/mass spectrometry), inorganics by water extraction followed by ion chromatography, and select species by various individual commercially-available sensors. Evaluating new technologies for measuring carbon monoxide, hydrogen cyanide, hydrogen fluoride, hydrogen chloride and other species of interest was a key objective of the test. Some of these sensors were located inside the glovebox near the fire source to avoid losses through the sampling lines; the rest were located just outside the glovebox. Instruments for smoke particle characterization included a Tapered Element Oscillating Microbalance Personal Dust Monitor (TEOM PDM) and a TSI Dust Trak DRX to measure particle mass concentration, a TSI PTrak for number concentration and a thermal precipitator for collection of particles for microscopic analysis. Materials studied included Nomex(R), M22759 wire insulation, granulated circuit board, polyvinyl chloride (PVC), Polytetrafluoroethylene (PTFE), Kapton(R), and mixtures of PTFE and Kapton(R). Furnace temperatures ranged from 340 to 640 C, focusing on the smoldering regime. Of particular interest in these tests was confirming burn repeatability and production of acid gases with different fuel mixture compositions, as well as the dependence of aerosol concentrations on temperature.
We report a means for efficient and selective extraction of carbon dioxide (CO(2)) at low to medium concentration from mixed gas streams. CO(2) capture was accomplished by use of a novel enzyme-based, facilitated transport contained liquid membrane (EBCLM) reactor. The parametric studies we report explore both structural and operational parameters of this design. The structural parameters include carbonic anhydrase (CA) concentration, buffer concentration and pH, and liquid membrane thickness. The operational parameters are temperature, humidity of the inlet gas stream, and CO(2) concentration in the feed stream. The data show that this system effectively captures CO(2) over the range 400 ppm to at least 100,000 ppm, at or around ambient temperature and pressure. In a single pass across this homogeneous catalyst design, given a feed of 0.1% CO(2), the selectivity of CO(2) versus N(2) is 1,090 : 1 and CO(2) versus O(2) is 790 :1. CO(2) permeance is 4.71 x 10(-8) molm(-2) Pa(-1) sec(-1). The CLM design results in a system that is very stable even in the presence of dry feed and sweep gases.
Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.
Vacuum extraction with subsequent mass spectrometric analysis of evolved volatiles was selected as the analytical procedure. The high-vacuum gas-handling system was constructed of stainless steel. The system was completely free from mercury, grease, or volatile organic materials. The furnace for heating the samples is discussed together with the high-vacuum crusher, the mass spectrometer, and approaches for water determination. The analytical procedure is considered, giving attention to the extraction of volatiles, adsorption studies, and the analysis of volatiles.
This data set reports a suite of complementary biogeochemical analyses of peat samples from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment. Results were collected using quantitative molecular analysis of bulk soil carbon to assess the stability of soil organic carbon following whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (eCO2). Targeted soil organic carbon components include solvent-extractable compounds (alkanoic acids, alkanols, alkanes, steroids, and terpenoids), ester-bound hydrolysable biopolymers (cutin and suberin markers), lignin phenols, and pyrogenic carbon. Bulk peat samples were analysed by Soxhlet extraction and solid phase separation for solvent-extractable compounds, alkaline hydrolysis to extract hydrolysable biopolymers, copper (II) oxide oxidation to extract lignin phenols and benzene polycarboxylic acids (BPCAs) as an approximation of pyrogenic carbon. Samples were analysed by gas chromatography (GC) equipped with a flame ionization detector (GC-FID) and compound identification was performed on GC coupled to mass selective detector (MS) for solvent-extractable compounds, ester-bound hydrolysable biopolymers and lignin phenols, and high-performance liquid chromatograph (HPLC) for pyrogenic carbon. Results are presented in Ofiti et al. (accepted). The experimental work was conducted on samples collected in August 2018 at the SPRUCE climate manipulation experiment in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Samples were collected and later analysed in a 10 cm increments over 0 to 50 cm depth and 25 cm intervals from 50 to 75 cm. Samples were analyzed for lignin phenols over 0 to 30 cm depth. This data set contains one file in comma separate (*.csv) format. This dataset contains data used to produce: Ofiti, N.O.E., Schmidt, M.W.I., Abiven, S., Hanson, P.J., Iversen, C.M., Wilson, R.M., Kostka, J.E., Wiesenberg, G.L.B., Malhotra, A. 2023. Climate warming and elevated CO2 rapidly alter peatland soil carbon sources and stability. Nat Commun 14, 7533. https://doi.org/10.1038/s41467-023-43410-z.
Conventional and advanced gas turbine engines are coming under increased scrutiny regarding pollutant emissions. This, in turn, has created a need to obtain in-situ experimental data at practical conditions, as well as exhaust data, and to obtain the data in combustors that reflect modern designs. The in-situ data are needed to (1) assess the effects of design modifications on pollutant formation, and (2) develop a detailed data base on combustor performance for the development and verification of computer modeling. This paper reports on a novel high pressure, high temperature facility designed to acquire such data under controlled conditions and with access (optical and extractive) for in-situ measurements. To evaluate the utility of the facility, a model gas turbine combustor was selected which features practical hardware design, two rows of jets (primary and dilution) with four jets in each row, and advanced wall cooling techniques with laser drilled effusive holes. The dome is equipped with a flat-vaned swirler with vane angles of 60 degrees. Data are obtained at combustor pressures ranging from 2 to 10 atmospheres of pressure, levels of air preheat to 427 C, combustor reference velocities from 10.0 to 20.0 m/s, and an overall equivalence ratio of 0.3. Exit plane and in-situ measurements are presented for HC, O2, CO2, CO, and NO(x). The exit plane emissions of NO(x) correspond to levels reported from practical combustors and the in-situ data demonstrate the utility and potential for detailed flow field measurements.
This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (ALWR) and a high-temperature gas-cooled reactor (HTGR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. Cost functions for the A-LWR were derived from the fully balanced models that were developed based on three different coupling options with three different thermal energy bypass ratios. For the next steps, cost functions for the HTGR will also be derived, and additional nuclear reactors (e.g., a liquid-cooled fast reactor [LFR] or molten-salt reactor [MSR]) will be evaluated for coupling with TES in similar fashion, including the evaluation of their steady-state condition models and cost functions. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state operation with minimum disruption to the nuclear power generation cycle. This report presents the results of steady state models developed using Aspen HYSYS®, wherein the thermal energy bypass for an NPP-TES coupling was varied up to 50%. The various components were sized using Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The current steady-state models and cost functions provide a baseline for additional work focusing on dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools to evaluate the technoeconomic viability and transient operations of TES-coupled A-NPPs.
The use of silver(I) ions in chemical separations, also known as argentation separations, is a powerful approach for the selective separation and analysis of many natural and synthetic organic compounds. In this review, a comprehensive discussion of the most common argentation separation techniques, including argentation-liquid chromatography (Ag-LC), argentation-gas chromatography (Ag-GC), argentation-facilitated transport membranes (Ag-FTMs), and argentation-solid phase extraction (Ag-SPE) is provided. For each of these techniques, notable advancements, optimized separations, and innovative applications are discussed. The review begins with an explanation of the fundamental chemistry underlying argentation separations, mainly the reversible π-complexation between silver(I) ions and carbon-carbon double bonds. Within Ag-LC, the use of silver(I) ions in thin-layer chromatography, high-performance liquid chromatography, as well as preparative LC are explored. This discussion focuses on how silver(I) ions are employed in the stationary and mobile phase to separate unsaturated compounds. For Ag-GC and Ag-FTMs, different silver compounds and supporting media are discussed, often with relation to olefin-paraffin separations. Ag-SPE has been widely employed for the selective extraction of unsaturated compounds from complex matrices in sample preparation. This comprehensive review of Ag-LC, Ag-GC, Ag-FTMs, and Ag-SPE techniques emphasizes the immense potential of argentation separations in separations science and serves as a valuable resource for researchers seeking to learn, optimize, and utilize argentation separations.
Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine learning (ML) implementation for the discovery of innovative polymers with ideal performance. Specifically, multitask ML models are trained on experimental data to link polymer chemistry to gas permeabilities of He, H 2 , O 2 , N 2 , CO 2 , and CH 4 . We interpret the ML models and extract valuable insights into the contributions of different chemical moieties to permeability and selectivity. We then screen over 9 million hypothetical polymers and identify thousands that lie well above current performance upper bounds, including hundreds of never-before-seen ultrapermeable polymer membranes with O 2 and CO 2 permeability greater than 10 4 and 10 5 Barrers, respectively. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.
Lithium is a critical mineral used in rechargeable batteries for electric vehicles (EVs) and future modernization of electric grids with sensitive supply chains that are subject to volatility. Therefore, methods to recover lithium from domestic unconventional sources are actively being pursued in the United States. Herein, we report on the lithium recovery potential from four fossil energy waste feedstocks: oil and gas drill cuttings (sample number n = 16); oil and gas produced waters (n > 200) from Marcellus, Bakken and Permian basins; coal byproducts (n>20), such as coal ash; and acid mine drainage treatment solids (AMD solids). Select solid samples underwent sequential extraction to explore lithium hosting phases and simple organic and inorganic acid extraction to explore lithium recovery potential. Our preliminary results found lithium concentrations up to 440 mg/kg in select AMD treatment solids and up to 300 mg/L in Marcellus Shale produced waters, demonstrating these sources have lithium yield potentials comparable to conventionally mined lithium ores and brines. Sequential extractions revealed that lithium is mostly associated with clay and silicate phases in shale drill cuttings, whereas lithium resides in Fe,Mn-oxide reducible phases in AMD solids. Further, the lithium content in produced waters has a strong linear relationship with total dissolved solid (TDS) levels in three separate oil and gas basins. At the same TDS level, Marcellus Shale produced waters contain more lithium compared to Bakken Shale and Permian Basin waters, with higher percentages of Ca and Mg, major cations that might impact lithium recovery efficiencies. Our study demonstrates the heterogeneity of lithium hosts from different fossil energy wastes. Characterization results will inform future lithium recovery from these different feedstocks.
An improved method of flow injection analysis for aqueous nitrite ion exploits the sensitivity and selectivity of the nitric oxide (NO) chemilluminescence detector. Trace analysis of nitrite ion in a small sample (5-160 microL) is accomplished by conversion of nitrite ion to NO by aqueous iodide in acid. The resulting NO is transported to the gas phase through a semipermeable membrane and subsequently detected by monitoring the photoemission of the reaction between NO and ozone (O3). Chemiluminescence detection is selective for measurement of NO, and, since the detection occurs in the gas-phase, neither sample coloration nor turbidity interfere. The detection limit for a 100-microL sample is 0.04 ppb of nitrite ion. The precision at the 10 ppb level is 2% relative standard deviation, and 60-180 samples can be analyzed per hour. Samples of human saliva and food extracts were analyzed; the results from a standard colorimetric measurement are compared with those from the new chemiluminescence method in order to further validate the latter method. A high degree of selectivity is obtained due to the three discriminating steps in the process: (1) the nitrite ion to NO conversion conditions are virtually specific for nitrite ion, (2) only volatile products of the conversion will be swept to the gas phase (avoiding turbidity or color in spectrophotometric methods), and (3) the NO chemiluminescence detector selectively detects the emission from the NO + O3 reaction. The method is free of interferences, offers detection limits of low parts per billion of nitrite ion, and allows the analysis of up to 180 microL-sized samples per hour, with little sample preparation and no chromatographic separation. Much smaller samples can be analyzed by this method than in previously reported batch analysis methods, which typically require 5 mL or more of sample and often need chromatographic separations as well.
About 1.3 billion tons of global food production end up in landfills and composting, leading to significant anthropogenic greenhouse gas (GHG) emissions. Extracting antioxidant and antimicrobial chemicals (flavonoids, phenolic acids, etc.) from food waste is an economically lucrative valorization strategy but is hindered by efficient solvent selection. Here we perform in silico high throughput screening to identify high solubility solvents for key phenolics and reveal more than 100+ higher-performing solvents than the traditional ethanol and methanol. Solubilities of nine shortlisted solvents are measured and found in reasonable agreement with model predictions. Analysis of the Conductor like Screening Model for Real Solvents (COSMO-RS) σ-profiles and Hansen Solubility Parameters reveals that polarity and hydrogen bonding make dimethylformamide (DMF) an excellent single solvent. We showcase the replacement of high-solubility toxic solvents with green mixtures and demonstrate the approach to potato peel waste. As a result, our work provides a blueprint for solvent selection and generates new insights into extraction from food waste.
Understanding the surface chemistry of CH 3 O species is essential for the production of methanol by CO 2 hydrogenation over Cu-based heterogeneous catalysts, as it facilitates the rational design of more efficient conversion processes. Recent research has identified inverse ZrO 2 /Cu catalysts as highly active and selective systems for the transformation of CO 2 to methanol with a performance that can be better than that of commercial Cu/ZnO catalysts. Here, we employed synchrotron-based ambient pressure X-ray photoelectron spectroscopy (AP-XPS) and calculations based on density functional theory (DFT) to understand the fate of CH 3 O groups under dry and wet environments. AP-XPS spectra revealed that under CO 2 hydrogenation conditions, formate and methoxy are two key intermediates to produce methanol. Furthermore, there are three different types of reactive sites on the surface: One is active for methoxy adsorption, which is stable and responsible for the methanol synthesis; Another one transforms CO 2 into CO; and a third one is active for CO 2 and methoxy dissociation, leading to C and methane formation. The theoretical calculations indicate that CH 3 OH readily dissociates to CH 3 O species following a highly exothermic (ΔE = -20.99 kcal/mol) and barrierless process. The water produced by the reverse water-gas shift reaction (CO 2 + H 2 → H 2 O + CO) can prevent the decomposition of CH 3 O species. We discovered that by introducing a tiny amount of water vapor (2 × 10 -6 Torr) into the reaction chamber, the energy barrier for the reaction CH 3 O(ads) + H(ads) → CH 3 OH(gas) is dramatically reduced. AP-XPS and computational modelling showed that water is quite capable of extracting adsorbed methoxy to form gaseous methanol. With this in mind, one could boost the methanol selectivity by adding appropriate amounts of water or steam, which is an inexpensive and feasible solution for industrial operations.
An adsorbent, carbon molecular sieve containing copper oxide, selectively removes oxygen from gas mixtures, producing gas containing less than 1 part per billion of oxygen. Used to help prevent oxidation of chemicals being prepared in dry boxes or to extract undesired traces of oxygen from inert-gas chambers in which flammable gases are stored.