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At least 505 records · Page 28

Decarbonizing Medium & Heavy-Duty On-Road Vehicles

We analyze the decarbonization potential of medium and heavy-duty vehicles (MHDVs) across multiple vehicle classes and market segments. We evaluate the timeframe in which zero-emission vehicles (ZEVs) could achieve cost parity with conventional diesel vehicles and the implications for energy and emissions. Our results show that ZEVs can achieve cost parity with conventional vehicles by 2035 across the majority of vehicle classes and market segments. Emissions reductions range from 27% to 77% by 2050 relative to 2019 across multiple fuel cost and technology progress sensitivities. Multiple technology pathways are viable for decarbonization, including battery-electric vehicles and hydrogen fuel cell electric vehicles. This presentation is based on previous work published by NREL: Ledna, C., Muratori, M., Yip, A., Jadun, P., and Hoehne, C. 2022. Decarbonizing Medium & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost Analysis. National Renewable Energy Laboratory, https://www.nrel.gov/docs/fy22osti/82081.pdf.

ADVANCED PROPULSION SYSTEMS↗

Application of Monte Carlo code SHIFT for MSBR dose rate calculations

This paper presents a study that applied the Monte Carlo code SHIFT to calculate the radiological environment within a detailed Molten Salt Breeder Reactor (MSBR) model. It represents one of the first applications of the SHIFT code in stand-alone simulations for non-light water reactors to help demonstrate the code's potential uses in the design, licensing, and operation of advanced reactors. The radiological conditions of the MSBR were modeled when the reactor is at two different operation modes: normal full power and a drained state. The Forward Weighted-Consistent Adjoint Driven Importance Sampling (FW-CADIS) hybrid method in SHIFT was applied successfully to calculate the ex-core neutron and gamma dose rates for the MSBR at full power. Neutron and gamma dose rates within the drain cell were also calculated for the MSBR at the drained state by integrating the source terms obtained from an ORIGEN-S depletion calculation into the SHIFT simulation. The results indicate that in the drained state, the delayed gammas from the depleted fuel salt are the main contributors to the dose rates. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Direct Conversion of Delignified Biomass into Non-Volatile Products Using Thermophilic Bacteria

Butyric acid (BA) can be used as a platform intermediate for diesel and sustainable aviation fuels (SAFs) as well as a precursor for diverse commodity chemicals for the production of polymers, fibers, solvents, and preservatives. This work presents a co-culture-based bioprocess for the production of BA from corn stover by two thermophilic bacteria, Clostridium thermocellum, a well-known efficient degrader of insoluble and oligomeric cellulosic substrates, and Clostridium thermobutyricum, a highly efficient BA producer from monomeric sugars. First, we tested the capability of C. thermocellum to deconstruct three different biomass streams from the NREL pilot plant pretreatment process -raw, deacetylated, and deacetylated and mechanically refined corn stover (DMR)-, and up to 82% solids deconstruction and 91% carbohydrate utilization were obtained when using DMR solids. Then, the sugar utilization and by-product formation capabilities on various substrates by C. thermobutyricum were compared to evaluate its potential as a co-culture partner for C. thermocellum. Model carbon sources -glucose and xylose- were compared to a mixture of substrates present in soluble DMR hydrolysate streams, and the highest cell density as well as the maximum BA titer (8.3 g/L) were observed on DMR hydrolysate. Finally, clostridial co-cultivations on DMR solids were performed to investigate the inoculation time for both organisms that enhances BA production; while C. thermocellum was always inoculated at the beginning of the cultivation, C. thermobutyricum was inoculated at 0, 36, or 72h. It was found that BA production begins immediately upon inoculation of C. thermobutyricum regardless of the inoculation time. However, higher solids deconstruction and carbohydrate utilization results (83.7 and 95.6%, respectively) were obtained when both organisms were inoculated at the beginning of the fermentation. Under those conditions, up to 2.6 g/L of BA were obtained from DMR solids after 120h of cultivation. This work provides relevant information for the sustainable production of BA using thermophilic bacteria.

bacterial co-culture↗

City and County Vehicle Inventories

This light-duty vehicle inventory dataset provides information on vehicle registrations by vehicle type (car vs. truck), fuel type, and model year showing the changes in adoption trends over time and average fuel economies. This data is part of a suite of state and local energy profile data available at the "State and Local Energy Profile Data Suite" link below and builds on Cities-LEAP energy modeling, available at the "EERE Cities-LEAP Page" link below. Examples of how to use the data to inform energy planning can be found at the "Example Uses" link below.

Alternative Fuel↗

Integration of Nuclear Material Accounting Data and Process Monitoring Data for Improvement on Detection Probability in Safeguarding Electrochemical Processing Facilities (Final Technical Report)

The KAERI advanced spent fuel conditioning process (ACP) process is a critical component of the US- South Korean nuclear cooperation and the following “123 Agreement.” Its development has received considerable attention in both countries. The ACP is an electrochemical processing (pyroprocessing) that recycles over 96% of the used nuclear fuel (UNF). It is also intrinsically proliferation-resistant in theory. In normal operation, the U/TRU product is very hot radiologically. In addition, the Cm provides a high level of spontaneous neutrons, making the product unsuitable for weapon use. However, as pointed in some study, “the need for safeguards to protect against the diversion and misuse of separated plutonium applies essentially equally to all grades of plutonium.” As pointed by many studies, the well-established traditional Nuclear Material Accounting (NMA) approach cannot be directly applied to electrochemical processing because of the lack of an input accountability tank, the non-continuous material flow, and the unsatisfactory level of confidence in sampling methods. Therefore, nuclear safeguards remain a grand challenge in the developing of commercial electrochemical separations facilities, especially around the heart of such facilities, the electrorefiner (ER) systems. In contrast to NMA data, process monitoring (PM) data is normally an indirect measurement of the SNM and is acquired much more frequently. In a broad sense, PM includes monitoring by various types of equipment, e.g. radiation detectors, cameras, voltage, current sensors. Because it is already being collected by the operator, the additional cost to safeguards is low. It has long been believed that PM data can supplement NMA data and help improve safeguards, although the benefits are hard to quantify. The U.S. DOE’s Material Protection, Accounting, and Control Technology (MPACT) campaign has made substantial investments into innovative PM sensor technology and predictive model development for real- or near real-time measurement and prediction of molten salt density and level, salt composition and actinide concentration especially Pu, the cell voltage, and the cell current to supplement traditional NMA. For aqueous-based reprocessing facilities, it is reported that PM, integrated with traditional NMA, have a high detection probability for specific diversions. For electrochemical reprocessing, preliminary studies have shown that PM data can support traditional NMA in various ways by providing a basis to estimate some of the in-processing nuclear material inventories. Despite early success, further studies on fusion of PM data and NMA data are still needed, which is the goal of this proposed work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Irradiation Effect on Noble Metal Particles in Water Using in situ Liquid Cell STEM Observation

During geologic disposal of spent nuclear fuel (SNF) in an engineered nuclear waste repository, once all other barriers have degraded, oxidizing may occur at the solid-water interface owing to a self-generated radiolytic field. The repository design includes large quantities of iron (Fe), that is anticipated to corrode under an anoxic environment, and generate hydrogen (H 2 ) gas. This H 2 gas is thought to be able to suppress the dissolution of SNF through a catalytic reaction with noble metal particles (NMP) that are pre-existing in the SNF. This interaction leads to the decomposition of the major oxidant, hydrogen peroxide (H 2 O 2 ). In conclusion, these processes are described in the Fuel Matrix Degradation (FMD) model that is being used to predict SNF degradation rates. The NMP, therefore, plays an important role within the FMD model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Ultra-fast Proton Conduction and Photocatalytic Water Splitting in a Pillared Metal–Organic Framework

Proton-exchange membrane fuel cells enable the portable utilization of hydrogen (H 2 ) as an energy resource. Current electrolytic materials have limitation, and there is an urgent need to develop new materials showing especially high proton conductivity. Here, we report the ultra-fast proton conduction in a novel metal–organic framework, MFM-808, which adopts an unprecedented topology and a unique structure consisting of two-dimensional layers of {Zr 6 }-clusters. By replacing the bridging formate with sulfate ligands within {Zr 6 }-layers, the modified MFM-808-SO 4 exhibits an exceptional proton conductivity of 0.21 S·cm –1 at 85 °C and 99% relative humidity. Modeling by molecular dynamics confirms that proton transfer is promoted by an efficient two-dimensional conducting network assembled by sulfate–{Zr 6 }-layers. MFM-808-SO 4 also possesses excellent photocatalytic activity for water splitting to produce H 2 , paving a new pathway to achieve a renewable hydrogen-energy cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Abundance of Major Cell Wall Components in Natural Variants and Pedigrees of Populus trichocarpa

The rapid analysis of biopolymers including lignin and sugars in lignocellulosic biomass cell walls is essential for the analysis of the large sample populations needed for identifying heritable genetic variation in biomass feedstocks for biofuels and bioproducts. In this study, we reported the analysis of cell wall lignin content, syringyl/guaiacyl (S/G) ratio, as well as glucose and xylose content by high-throughput pyrolysis-molecular beam mass spectrometry (py-MBMS) for >3,600 samples derived from hundreds of accessions of Populus trichocarpa from natural populations, as well as pedigrees constructed from 14 parents (7 × 7). Partial Least Squares (PLS) regression models were built from the samples of known sugar composition previously determined by hydrolysis followed by nuclear magnetic resonance (NMR) analysis. Key spectral features positively correlated with glucose content consisted of m/z 126, 98, and 69, among others, deriving from pyrolyzates such as hydroxymethylfurfural, maltol, and other sugar-derived species. Xylose content positively correlated primarily with many lignin-derived ions and to a lesser degree with m/z 114, deriving from a lactone produced from xylose pyrolysis. Models were capable of predicting glucose and xylose contents with an average error of less than 4%, and accuracy was significantly improved over previously used methods. The differences in the models constructed from the two sample sets varied in training sample number, but the genetic and compositional uniformity of the pedigree set could be a potential driver in the slightly better performance of that model in comparison with the natural variants. Broad-sense heritability of glucose and xylose composition using these data was 0.32 and 0.34, respectively. In summary, we have demonstrated the use of a single high-throughput method to predict sugar and lignin composition in thousands of poplar samples to estimate the heritability and phenotypic plasticity of traits necessary to develop optimized feedstocks for bioenergy applications.

09 BIOMASS FUELS↗

Assessment of the polygeneration approach in wastewater treatment plants for enhanced energy efficiency and green hydrogen/ammonia production

Wastewater treatment plants (WWTPs) offer opportunities to optimize resource utilization and enhance energy efficiency. Here, this study provides a comprehensive analysis of using the polygeneration approach in WWTPs to reduce grid energy dependence, optimize energy distribution, and utilize surplus energy for hydrogen (H 2 ) and ammonia (NH 3 ) production. Several models were employed, including photovoltaic (PV) cells, parabolic trough collectors (PTCs), steam methane reforming, and polymer electrolyte membranes, to assess the feasibility of this approach. Three scenarios were evaluated and compared: Scenario 1 (Baseline) represents the current situation, Scenario 2 maximizes the Net Present Value (NPV), and Scenario 3 minimizes NH 3 production costs. Real data from As-Samra WWTP in Jordan was used to accurately assess the feasibility of each scenario. The results show that Scenario 2 offers the highest profitability and efficiency, with a NPV of 87.48 million USD and an annual NH 3 production of 15,417 tons, reducing both grid dependency and biogas fuel consumption. Both Scenarios 2 and 3 demonstrate the ability to meet thermal demands efficiently while generating significant revenue from NH 3 production. Scenario 3, in particular, achieves competitive H 2 and NH 3 production costs. Environmentally, Scenario 2 significantly reduces annual greenhouse gas emissions by 12.66 kilotons of CO 2eq , with near-zero carbon intensity for thermal energy due to solar reliance. In conclusion, the polygeneration approach offers a promising pathway for WWTPs to achieve greater sustainability, economic gains, and reduced environmental impact, providing valuable insights for decision-makers.

42 ENGINEERING↗

An experimental database of cell performance for vanadium redox flow battery

The continual growth in energy demand has resulted in the deployment of renewable energy generators to reduce the impact of fossil fuel dependence. However, these generators often suffer from intermittency and require energy storage when there is over-generation and the subsequent release of this stored energy at high demand. One promising energy storage technology which can provide a solution to improve energy management and grid stability, is the redox flow battery. Among the numerous flow battery systems, vanadium redox flow battery is the most iconic solution to large scale energy storage, giving a more efficient link between energy production, especially from renewables, and energy demand. The aim of the current database is to characterize the performance of the cell design and to provide training/validation data for physical model or data-driven model. The database includes hundreds of experimental cell performance data of vanadium redox flow battery with various current densities for multiple charge-discharge cycles. All the cell parameters, chemical parameters, material parameters, operation parameters and thermodynamic parameters of the cell system are listed. Coulomb, voltaic and energy efficiencies are also provided. The database will be helpful for researchers in the field of redox flow batteries.

Gao, Peiyuan↗

Improvement of SCALE-XSPROC Multigroup Cross Section Processing Based on the CENTRM Pointwise Slowing Down Calculation

The SCALE-XSProc multigroup (MG) cross section processing procedure based on the CENTRM pointwise slowing down calculation is the primary procedure to process problem-dependent self-shielded MG cross sections and scattering matrices for neutron transport calculations.This procedure supports various cell-based geometries including slab, 1-D cylindrical, 1-D spherical and 2-D rectangular configurations and doubly heterogeneous particulate fuels. Recently, this procedure has been significantly improved to be applied to any advanced reactor analysis covering thermal and fast reactor systems, and to be comparable to continuous energy (CE) Monte Carlo calculations. Some reactivity bias and reaction rate differences have been observed compared with CE Monte Carlo calculations, and several areas for improvement have been identified in the SCALE-XSProc MG cross section processing: (1) resonance self-shielding calculations within the unresolved resonance range, (2) 10 eV thermal cut-off energy for the free gas model, (3) on-the-fly adjustments to the thermal scattering matrix, (4) normalization of the pointwise neutron flux, and (5) fine MG energy structure. This procedure ensures very accurate MG cross section processing for high-fidelity deterministic reactor physics analysis for various advanced reactor systems.

Kim, Kang Seog↗

Interfacial Water Manipulation with Ionic Liquids for the Oxygen Reduction Reaction

The role that interfacial water plays in both promoting and inhibiting the electrochemical oxygen reduction reaction (ORR) remains somewhat unclear and controversial. Here, we use electroanalytical chemistry, spectroscopy, and microkinetic modeling to probe the impact of hydrophobic ionic liquid (IL) thin films on interfacial water structure and its role in promoting or inhibiting the ORR. Through the use of in situ ATR-SEIRAS, we find that the IL thin films limit the content of water at the interface and prevent the formation of hydrogen bond stabilized water organization. The impact of this exclusion of water on the promotion of the ORR is through the reduced coverage of OH ad spectator species. The decreased solvation of “active” OH ad species weakens its interaction with the catalyst surface, lowering the barrier to the last step in the ORR mechanism. This “destabilized” OH ad impact on ORR kinetics is confirmed through a microkinetic model. Furthermore, the results presented here highlight the mechanistic pathway through which hydrophobic ILs enhance ORR kinetics and point to pathways to both further improve this performance enhancement and the potential for integration of hydrophobic ILs into other technologically relevant elementary electrochemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generalized and Mechanistic PV Module Performance Prediction From Computer Vision and Machine Learning on Electroluminescence Images

Electroluminescence (EL) imaging of photovoltiac (PV) modules offers high-speed, high-resolution information about device performance, affording opportunities for greater insight and efficiency in module characterization across manufacturing, research and development, and power plant operations and management. Predicting module electrical properties from EL image features is a critical step toward these applications. In this article, we demonstrate quantification of both generalized and performance mechanism-specific EL image features, using pixel intensity-based and machine learning classification algorithms. From EL image features, we build predictive models for PV module power and series resistance, using time-series current-voltage (I-V) and EL data obtained stepwise on five brands of modules spanning three Si cell types through two accelerated exposures: damp heat (DH) (85°C/85% RH) and thermal cycling (TC) (IEC 61215). Overall, 195 pairs of EL images and I-V characteristics were analyzed, yielding 11700 individual PV cell images. A convolutional neural network was built to classify cells by the severity of busbar corrosion with high accuracy (95%). Generalized power predictive models estimated the maximum power of PV modules from EL images with high confidence and an adjusted-R 2 of 0.88, across all module brands and cell types in extended DH and TC exposures. Mechanistic degradation prediction was demonstrated by quantification of busbar corrosion in EL images of three module brands in DH, and subsequent modeling of series resistance using these mechanism-specific EL image features. For modules exhibiting busbar corrosion, we demonstrated series resistance predictive models with adjusted-R 2 of up to 0.73.

14 SOLAR ENERGY↗

Understanding the Active Site Structures and Achieving Catalytic Activity Tuning of Atomically Dispersed FeN 4 Sites for Oxygen Reduction Reaction

Atomically dispersed Fe–—N—C catalysts with high oxygen reduction reaction (ORR) activity have attracted great attention since the last decade. Due to comparable ORR activity and low material cost, they are promising platinum group metal (PGM)-free catalysts that can replace the commercialized Pt/C materials; furthermore, it can facilitate the efficiency of the fuel cell technologies and mitigate dependence on fossil fuels. Great advancements have been made to experimentally optimize the synthesis approach of the Fe–—N—C catalysts, enhance the ORR activity, and improve the catalyst stability. Similarly, recent theoretical studies also provide enriched understanding of the active site structures, properties, and reaction mechanisms. In this review, discussions are made upon utilizing combined experimental and computational spectroscopy to reveal the active site structures, employing mechanistic studies to investigate reaction thermodynamics and kinetics, as well as developing scaling relationships to assist the design and development of future PGM-free catalyst materials. Furthermore, recent advances in studying Fe–—N—C catalysts utilizing electrified surface models and explicit solvation models are also discussed. Not only can these aspects improve the accuracy of theoretical simulation and predictions but also deepen the understanding of the catalyst properties and reaction mechanisms under the effect of surface charges and solvent molecules.

Fe single-atom catalysts↗

Numerical study on spray collapse process of ECN spray G injector under flash boiling conditions

This work features a numerical study of the spray collapse process that occurs under flash-boiling, gasoline-direct-injection conditions. The Engine Combustion Network's Spray G injector was modeled, and iso-octane, n-hexane, and propane were used as fuels with the goal to investigate fuel property effects. The development of individual jets and jet-to-jet interaction were analyzed to reveal the physical mechanisms of spray collapse. The results agreed qualitatively well with the experimental data of propane available from the literature and the predictions revealed the model's ability to capture the near-nozzle shock structures witnessed in the experiments. Simulations showed that the flow development of flashing sprays was strongly tied with the fuel properties. Specifically, under-expanded jets were not observed with iso-octane due to the fuel's low vapor pressure. In the case of n-hexane, the jets were under-expanded, and a low-pressure core was observed inside the jets due to the flow expansion. With propane, the very strong expansion caused the flow to become transonic and generate a unique shock structure near the nozzle exit. The shock structure revealed the formation of primary shock cells within the jets and secondary shock cells induced by jet-to-jet interaction. Based on the results, the spray collapse under flash boiling conditions was mainly attributed to two effects, i.e., the decrease in pressure at the spray center induced by the low-pressure cores inside and between the jets, and the isolation effect due to the jet-to-jet interaction which contributed to maintain the pressure differential between the spray center and the ambient.

42 ENGINEERING↗

Computational analysis of metal–metal bonded dimetal tetrabenzoate redox potentials in the context of ammonia oxidation electrocatalysis

Metal–metal bonded complexes are promising candidates for catalyzing redox transformations. Of particular interest is the oxidation of ammonia to dinitrogen, an important half reaction for the potential utilization of ammonia as a fuel or hydrogen carrier. This work computationally explores 30 different metal–metal bonded dimers (5 different metal centers and 6 different benzoate ligand derivatives) to explore the tunability of the redox potential when ammonia is bound to the complexes as an axial ligand, modeling the first step in ammonia oxidation electrocatalysis. We calculate the redox potentials of these compounds, making reference to experimental data when appropriate, identifying two degrees of tunability: a coarse adjustment, changing the metal center, allows for a wide range of redox potentials to be accessed (from +1.0 to –2.0 V vs. ferrocene/ferrocenium in acetonitrile solution) and a fine adjustment, the para-substituent of the benzoate derivative, which affects the redox potential in a smaller range based on the electron donating/withdrawing effects of the substituent. Ruthenium and osmium tetrabenzoate catalysts are prime candidates for next generation ammonia oxidation catalysts because their redox potentials fall within the direct ammonia fuel cell “viability zone” bracketed by the thermodynamic potentials of oxygen reduction (ORR) and nitrogen reduction (NRR). Rhodium tetrabenzoate species fall above the ORR potential, suggesting ammonia oxidation promoted by Rh 2 catalysts could instead be used to facilitate hydrogen production through coupling to hydrogen evolution at a cathode. The redox potentials of rhenium and iridium tetrabenzoate catalysts fall below the NRR potential suggesting that these compounds could be further investigated in the context of electrochemical ammonia synthesis. Each redox event studied involves electron transfer from the M–M δ* orbital regardless of choice of metal or benzoate ligand derivative; this leads us to believe that the chemical reactivity of the various studied compounds will be similar in the context of ammonia oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Verification of a Monte Carlo binary collision model for simulating elastic and inelastic collisions in particle-in-cell simulations

We present the development and verification of a Monte Carlo binary collision model for simulating elastic and inelastic collisions in particle-in-cell simulations. We apply the corrected binary collision model originally developed for charged-particles collisions to all considered scattering channels, including Coulomb collisions, elastic neutral–neutral and charged–neutral collisions, ionization, excitation, and fusion. The model's implementation is described and verified through a series of simulations, including charged- and neutral-particle thermal equilibration, slowing of electrons in warm solid-density aluminum, collisional damping of a Langmuir wave, helium gas breakdown in an applied electric field, and thermonuclear and beam–target fusion. Then, we demonstrate the model within simulations of hydrogen plasma formation in the Princeton Field-Reversed Configuration as well as of the burning of aneutronic fusion fuel p-11B. The latter includes measurement of the fusion power density in a low-density plasma and fusion production due to the stopping of a proton ignitor beam in a compressed boron target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Platinum Group Metals Global Economics Market Supply

Due to uncertainty in the transition away from internal combustion engines (and more importantly, the catalytic convertors these automobiles use), there is large uncertainty in the future of the PGM market. However, proton exchange membrane (PEM) electrolyzers could be a new demand application for PGMs. Therefore, a model was developed which utilizes the system dynamics approach to predict supply and prices for specific demand scenarios. Results indicated that the total PGM market value sees a decline in the late 2020s due to changing automotive application demand. Market decline was due to decreasing internal combustion engine (ICE) vehicle demand resulting in less PGMs supplied for automotive applications. Compounding market decline was an increase in secondary supply of PGMs as more ICE automotives reach their EOL pushing PGM prices down as secondary supply increases while demand simultaneously decreases. Following the market decline, an increase in market value in the early 2030s was observed due to deployment of hydrogen fuel cell technologies and subsequent increase in PGM demand

Kulkarni, Sameer (0000000227573592)↗