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At least 991 records · Page 55

Studies of optical and chemical properties of aged and fresh biomass burning absorbing aerosols for climate models

Particulate emissions from burning fuels from sub-Saharan Africa is currently poorly characterized. With increasing population and industrialization, emissions are expected to grow. Optical methods for measuring light absorption in the ultraviolet (UV) and visible (vis) regions of the spectrum are crucial for understanding the optical properties of BB aerosols (Bond and Bergstrom, 2006; Lack and Cappa, 2010; Moschos et al., 2021). One such instrument is the dual-spot AE33 model aethalometer is a common filter-based instrument that can be used to measure aerosol absorption properties (Hansen et al., 1984). This instrument has many figures of merit; however, the method's limitations include potential biases from scattering within the filter material, multiple scattering effects of the particles, filter loading (i.e. particle shadowing), and the need for wavelength-specific correction factors (Cλ), which depend on accurate intercomparison with other in situ techniques (Bond et al., 1999; Collaud Coen et al., 2010). This work aims to: 1. Optically characterize BB aerosol generated from African fuel 2. Correct the aethalometer at multiple wavelengths 3. Parametrize these correction factors. 4. Combusting the same fuels with two difference tube furnace systems assess the general applicability of this flexible means of producing BB aerosol. This was accomplished by conducting laboratory studies at Los Alamos National Laboratory (LANL) and North Carolina A&T State University (NCA&T), where aethalometer measurements were compared to in situ optical measurements. Mass cross sections of BB aerosol from these under-studied fuels will be determined along with their wavelength dependence.

09 BIOMASS FUELS↗

Temperature Dependence of Band Gap Renormalization in High-T Sensor Materials via First-Principles and Experimental Corroboration

Understanding the temperature dependence of functional properties of high-T gas sensing materials is vital for their applications in combustion environments. The electron-phonon coupling that derives the electronic structure change with temperatures is a key property of interest as it affects other sensing responses. Herein, we assess the temperature dependence of band gap renormalization in metal oxides and perovskites by employing Allen-Heine-Cardona theory with first-principles simulations and corroborate with experimental observation. The calculated temperature-dependent band gap changes of these materials studied are in good agreement with in-house experimental data, proving that the theory can adequately predict renormalization on the band gap in the system of interest. The predicted and measured band gap variations are characterized using an analytical model, which can provide useful insights on the simulated zero-temperature band gaps. Based on the available data, a set of 53 metal oxides and perovskites were identified as potential high-T gas sensors. A machine learning model has been developed to predict the band-gap change by capturing the overall trend of the empirical parameters with respect to a reduced feature obtained by transforming the set of available physical features.

Park, Jongwoo↗

A carbon molecular sieve membrane-based reactive separation process for pre-combustion CO 2 capture

In this study, we discuss a hybrid system combining a membrane reactor (MR) and an adsorptive reactor (AR), with the MR's reject stream serving as the AR's feed. We apply this system for the water gas shift (WGS) reaction for H 2 generation and simultaneous CO 2 capture in the context of the Integrated Gas Combined Cycle (IGCC) process for power generation from coal and biomass. This MR-AR system attains a high conversion exceeding equilibrium, produces a pure H 2 product for power generation, and delivers a high-pressure CO 2 stream ready for sequestration. Specifically, in our study we use carbon molecular sieve membranes (CMSMs) and a commercial sour-shift WGS catalyst. Lab experiments were carried-out to determine the membrane characteristics, and the MR performance under IGCC-relevant conditions, i.e., for temperatures up to 250 °C and pressures up to 25 bar, employing a model coal gasifier syngas. The CMSM and the catalyst have displayed robust and stable performance during a long-term run (~750 h of syngas exposure). We evaluated the MR-AR system in multi-cycle runs and it has demonstrated superior performance to that of a conventional packed-bed reactor, producing a high-purity H 2 product directly useable in a turbine for power generation. We conclude from the study, that the CMSM-based MR-AR system is a good candidate technology for environmentally-benign power generation. We are currently constructing a pilot-scale system for field demonstration of the technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Reaction of HO2 and CH3O2: CH3OOH Formed from the Singlet Electronic State Surface

High-level coupled-cluster calculations in combination with two-dimensional master equation simulations were used to study the HO2 + CH3O2 reaction, which plays an important role in the oxidation of methane and hydrocarbons in the Earth’s atmosphere and low-temperature combustion. The main reaction pathways taking place on the lowest-lying triplet and singlet potential energy surfaces (PES) were characterized. Interestingly, methyl hydroperoxide (CH3OOH), the sole product, could be produced from both the triplet and singlet PESs, with a ratio of roughly 9:1. Formaldehyde is not made as a primary product, but can be formed via secondary chemistry. The formation of methyl tetraoxide (MTO) from the singlet PES is unimportant. The calculated reaction rate coefficients were found to be practically pressure-independent for p ≤ 760 Torr and can be given by k(T)=2.75×10−13×e+1.75 kcal mol−1/RT (in cm3/s), an expression useful for kinetics modeling over the range T = 200–800 K. The rate constant has a slight negative Arrhenius energy dependence of about −1.75 kcal mol–1, falling about a factor of 30 from 200 K to 800 K.

2DME↗

Acclimation of Phytoplankton Fe:C Ratios Dampens the Biogeochemical Response to Varying Atmospheric Deposition of Soluble Iron

Abstract Dissolved iron (dFe) plays an important role in regulating marine productivity. In high nutrient, low chlorophyll regions (>33% of the global ocean), iron is the primary growth limiting nutrient, and elsewhere iron can regulate nitrogen fixation by diazotrophs. The link between iron availability and carbon export is strongly dependent on the phytoplankton iron quotas or cellular Fe:C ratios. This ratio varies by more than an order of magnitude in the open ocean and is positively correlated with ambient dFe concentrations in field observations. Representing Fe:C ratios within models is necessary to investigate how ocean carbon cycling will interact with perturbations to iron cycling in a changing climate. The Community Earth System Model ocean component was modified to simulate dynamic, group‐specific, phytoplankton Fe:C that varies as a function of ambient iron concentration. The simulated Fe:C ratios improve the representation of the spatial trends in the observed Fe:C ratios. The acclimation of phytoplankton Fe:C ratios dampens the biogeochemical response to varying atmospheric deposition of soluble iron, compared to a fixed Fe:C ratio. However, varying atmospheric soluble iron supply has first order impacts on global carbon and nitrogen fluxes and on nutrient limitation spatial patterns. Our results suggest that pyrogenic Fe is a significant dFe source that rivals mineral dust inputs in some regions. Changes in dust flux and iron combustion sources (anthropogenic and wildfires) will modify atmospheric Fe inputs in the future. Accounting for dynamic phytoplankton iron quotas is critical for understanding ocean biogeochemistry and projecting its response to variations in atmospheric deposition.

Environmental Sciences & Ecology↗

CaMn 0.9 Ti 0.1 O 3 based redox catalysts for chemical looping – Oxidative dehydrogenation of ethane: Effects of Na 2 MoO 4 promoter and degree of reduction on the reaction kinetics

Reduction kinetics and stability of 20 wt% Na 2 MoO 4 -promoted CaMn 0.9 Ti 0.1 O 3 were investigated for its applications in Chemical Looping – Oxidative Dehydrogenation (CL-ODH) of ethane, a potential alternative for ethylene production with higher efficiency and lower emissions. Here, the present work reports a kinetics model and parameters for a Na 2 MoO 4 -promoted, Ti-doped CaMnO 3 (CaMn 0.9 Ti 0.1 O 3 ) redox catalyst under H 2 and C 2 H 4 . A first-order reaction model provides the best fit for the reduction of Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 under H 2 , while the C 2 H 4 reduction is well described by an Avrami–Erofe’ev model. The activation energy for C 2 H 4 oxidation is approximately three times higher than that for H 2 conversion, showing that the activation of C 2 H 4 is significantly more difficult on the surface of the redox catalyst. The reduction rate of Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 under H 2 at 750 °C is more than two orders of magnitude greater than that under C 2 H 4 , while the reduction rate of unpromoted CaMn 0.9 Ti 0.1 O 3 is comparable under H 2 and C 2 H 4 , showing that the addition of Na 2 MoO 4 effectively suppresses C 2 H 4 combustion relative to H 2 oxidation. The kinetics results for Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 confirm its excellent selectivity towards hydrogen combustion, making it a promising candidate under CL-ODH. Additionally, the stability of the CaMn 0.9 Ti 0.1 O 3 @ Na 2 MoO 4 core-shell structure, which was the underlying reason for the excellent selectivity, was examined under both shallow and deep reductions. It was determined that deep reduction of the redox catalyst, e.g. higher than 80% solid conversion, would lead to loss of sodium and hence to decreased selectivity for hydrogen combustion. In contrast, the core-shell structure was well-maintained, exhibiting excellent performance after 50 redox cycles when deep reduction of the redox catalyst was avoided. This study offers a basis for both the CL-ODH reactor design and redox catalyst optimizations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven selection of stiff chemistry ODE solver in operator-splitting schemes

Most computational fluid dynamics simulations of practical combustion applications employ operator-splitting schemes, where chemistry and transport are separated and integrated with distinct numerical methods. The changes in composition due to chemistry are evaluated by solving ordinary differential equations (ODE) in each cell of the computational domain, which typically dominates the computational cost when detailed chemistry is considered. In this work, a data-driven approach for the selection of chemistry ODE solvers in operator-splitting schemes is presented. Neural networks are used to predict the ODE solvers CPU times and errors for a given thermochemical state. This allows the selection of an optimal ODE solver on a cell-by-cell, timestep-by-timestep basis. The models are trained using a wide set of thermochemical states generated through partially-stirred reactors and flames simulations. The methodology is validated by quantifying the prediction errors, the classification accuracy, and the computational speedup. The model predicts the optimal ODE solver for 70 to 95% of the validation cases and decreases the computional cost by a factor of 3 or more. The generalizability of the methodology to different chemical mechanisms and different fuels is assessed and it is shown that the model’s performance is only slightly degraded and its applicability is significantly enhanced if the inputs to the neural networks are restricted to a small set of thermochemical state variables present in most chemical mechanisms. In conclusion, the models are used in an homogeneous reactor case and a multi-dimensional CFD simulation of a diesel spray at high pressure where a speedup of more than 3 is achieved.

42 ENGINEERING↗

The Identity and Chemistry of C 7 H 7 Radicals Observed during Soot Formation

Here we used aerosol mass spectrometry coupled with tunable synchrotron photoionization to measure radical and closed-shell species associated with particle formation in premixed flames and during pyrolysis of butane, ethylene, and methane. We analyzed photoionization (PI) spectra for the C 7 H 7 radical to identify the isomers present during particle formation. For the combustion and pyrolysis of all three fuels, the PI spectra can be fit reasonably well with contributions from four radical isomers: benzyl, tropyl, vinylcyclopentadienyl, and o-tolyl. Although there are significant experimental uncertainties in the isomeric speciation of C7H 7 , the results clearly demonstrate that the isomeric composition of C 7 H 7 strongly depends on the combustion or pyrolysis conditions and the fuel or precursors. Fits to the PI spectra using reference curves for these isomers suggest that all of these isomers may contribute to m/z 91 in butane and methane flames, but only benzyl and vinylcyclopentadienyl contribute to the C 7 H 7 isomer signal in the ethylene flame. Only tropyl and benzyl appear to play a role during pyrolytic particle formation from ethylene, and only tropyl, vinylcyclopentadienyl, and o-tolyl appear to participate during particle formation from butane pyrolysis. There also seems to be a contribution from an isomer with an ionization energy below 7.5 eV for the flames but not for the pyrolysis conditions. Kinetic models with updated and new reactions and rate coefficients for the C 7 H 7 reaction network predict benzyl, tropyl, vinylcyclopentadienyl, and o-tolyl to be the primary C 7 H 7 isomers and predict negligible contributions from other C 7 H 7 isomers. These updated models provide better agreement with the measurements than the original versions of the models but, nonetheless, underpredict the relative concentrations of tropyl, vinylcyclopentadienyl, and o-tolyl in both flames and pyrolysis and overpredict benzyl in pyrolysis. Our results suggest that there are additional important formation pathways for the vinylcyclopentadienyl, tropyl, and o-tolyl radicals and/or loss pathways for the benzyl radical that are currently unaccounted for in the present models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three-Dimensional CFD Investigation of Pre-Spark Heat Release in a Boosted SI Engine

Low-temperature heat release (LTHR) in spark-ignited internal combustion engines is a critical step toward the occurrence of auto-ignition, which can lead to an undesirable phenomenon known as engine knock. As such, correct predictions of LTHR are of utmost importance to improve the understanding of knock and enable techniques aimed at controlling it. While LTHR is typically obscured by the deflagration following the spark ignition, extremely late ignition timings can lead to LTHR occurrence prior to the spark, i.e., pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection SI engine was numerically investigated using three-dimensional computational fluid dynamics (CFD). A hybrid approach was used, based on the G-equation model for representing the turbulent flame front and the multi-zone well-stirred reactor model for tracking the chemical reactions within the unburnt region. A recently developed best practice was also employed which keeps the well-stirred reactor model active throughout the entire simulation. This allowed for correct predictions of the previous cycle trapped residuals which have a considerable effect on the onset of LTHR. Multi-cycle simulations were conducted using Co-Optima alkylate and E30 fuels. The predicted in-cylinder pressure and heat release rate agreed well with the experimental data and served as validation for the CFD model. Following the initial validation, the dynamics of PSHR was discussed and a series of parameters of interest were assessed. First, the effect of exhaust valve temperature was investigated, qualitatively highlighting the importance of boundary conditions uncertainty. Further analyses were carried out on the effects of fuel properties, including laminar flame speed (LFS) and heat of vaporization (HOV). The results indicate that PSHR phasing is slightly advanced with lower LFS as more trapped unburnt fuel is made available for the next cycle. A similar trend was observed with lower HOV as less intense spray cooling led to higher mixture temperatures, i.e., higher mixture reactivity. Finally, a comparison of Co-Optima alkylate and E30 fuels was made using the pressure-temperature trajectory framework. It was shown that the differences between Co-Optima alkylate and E30 in PSHR tendency are correlated with both HOV and chemical effects.

33 ADVANCED PROPULSION SYSTEMS↗

Probing the antiknock effect of anisole through an ignition, speciation and modeling study of its blends with isooctane

In order to unravel the reaction pathways relevant to anisole co-oxidation within a fuel blend, a detailed study of isooctane/anisole blends was performed with the ULille RCM. Ignition delays as well as mole fraction profiles were measured during a two-stage ignition delay using sampling and GC techniques. These results are used to validate a kinetic model developed from ab initio calculations for the most relevant rate constants which included H-atom abstraction reactions from anisole, and reactions on the potential energy surfaces of methoxyphenyl + O 2 and anisyl + O 2 . Pressure dependent rate constants were computed for the methoxyphenyl + O 2 and anisyl + O 2 reactive systems using master equation code analysis. The new kinetic model shows good agreement with the experimental data. Dual brute-force sensitivity analysis was performed, on both first- and second-stages of ignition, allowing the identification of the most important reactions in the prediction of both ignition delays. It was observed that while pure anisole does not show NTC behavior, a 60/40 isooctane/anisole blend displays such behavior, as well as two-stage ignition. This suggests anisole addition may not be as beneficial to knock resistance as expected from its high octane number. The kinetic modeling results demonstrate the importance of H-abstraction reactions both from the methoxy group and from the aryl ring in ortho-position and the addition of the resultant radicals to O2, mostly leading to the formation of polar or non-aromatic products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupling of Lipid Peroxidation and Criegee Intermediate Mediated Autoxidation in the Heterogeneous Oxidation of Linoleic Acid Aerosols

Autoxidation is an established mechanism for the degradation of organic molecules, which is relevant in the atmosphere, combustion processes, the environment, and the rancidification of lipids (commonly known as lipid peroxidation). Autoxidation proceeds via radical chain reactions involving hydroxyl (•OH), peroxy (RO2•), and alkoxy radicals, which are also prominent oxidants in the atmosphere. Recent reports have provided evidence for an alternative autoxidation mechanism driven instead by Criegee intermediates (CIs), which are produced from the reaction of β-hydroxy peroxy radicals (β-OH-RO2•). This work evaluates the contributions of these two mechanisms in the •OH initiated heterogeneous oxidation of linoleic acid (LA) aerosols. Reaction kinetics and product distributions are monitored using a vacuum ultraviolet photoionization aerosol time-of-flight mass spectrometer. To explain the observed kinetics, a kinetic model is developed that incorporates both the conventional peroxidation and alternative CI-mediated autoxidation mechanisms. We observe that the CI-mediated autoxidation pathways enhance the heterogeneous autoxidation rate, while the peroxidation reactions, although present, contributes less to the overall oxidation rate. α-Acyloxyalkyl hydroperoxides (AAHPs) are identified as key indicators for bimolecular reactions of CI with LA, highlighting the role of LA as a CI scavenger. Moreover, the measured functionalized LA products with hydroxyl or carbonyl group(s), serve as markers for the peroxidation reactions. In summary, this work presents a quantitative framework to understand the coupled reaction network of •OH, RO2•, β-OH-RO2• radicals, and CI in driving heterogeneous autoxidation, which is crucial for understanding degradation mechanisms of organic molecules in the environment and atmosphere.

Criegee intermediate↗

Utilization of an Advanced Sensor network to determine fuel heating value and Real-Time net unit heat rate during transient operation

Coal-fired utility boilers are being increasingly used as variable electricity generation to resolve the imbalance in the energy market from the expansion of intermittent renewable energy. The frequent transient operation required to meet residual energy demand has created a challenge for coal-fired units to operate efficiently. This work utilizes an advanced sensor network (ASN) to calculate net unit heat rate (NUHR) of a coal-fired boiler in real time through combustion calculations and statistical correlations to provide the tools for optimizing dynamic operation. Real-time heating values that were necessary to determine fuel input energy to calculate accurate NUHR were found using both fundamental and data-driven methods. Real-time NUHR shows distinct shifts that reflect changes in process conditions that will improve the ability to optimize transient operation. Data-driven heating value correlations had 24% lower root mean square error (RMSE) than the fundamental combustion calculation approach when compared to daily retrospective proximate analysis. Furthermore, the data-driven method RMSE improved by 7% with the inclusion of ASN data. Future work is to validate by comparing unit performance with and without the inclusion of NUHR as a control parameter for the dynamic neural network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

TGA Study of the Reaction Kinetics of a CuFeMnAlO 4+δ Oxygen Carrier for Methane Chemical Looping Combustion under High Pressure and Atmospheric Pressure Conditions

Reduction and oxidation kinetics of a CuFeMnAlO 4+δ oxygen carrier for methane were studied using an atmospheric thermogravimetric analyzer (TGA) and a pressurized TGA. Important parameters such as temperature (500–900 °C), particle size distribution (150–650 μm), and partial pressures of reactants (methane and oxygen) were evaluated. Results showed that the reduction of the oxygen carrier was not affected by particle size distribution studied in this work, and that above 750 °C, the effect of the temperature on oxygen carrier reduction started to diminish. The reaction time approaches an asymptotic limit as methane partial pressure increases. For oxygen carrier oxidation, it was found that the rate of oxidation increased with increasing oxygen concentration. The effect of the oxygen concentration was more noticeable when the oxygen concentration was below 7.5%. Because of the inherent feature of the oxygen carrier, its chemical looping with oxygen uncoupling property was also assessed. A phase boundary-controlled shrinking sphere model was used to model the test data from the TGAs. Modeling results showed that the oxygen carrier reduction had a reaction order of 1 with an activation energy of ∼46 kJ/mol. Oxygen carrier oxidation demonstrated a reaction order of 1.1 with an activation energy of ∼55 kJ/mol. Additionally, the differences of the experimental results between the atmospheric pressure TGA and the pressurized TGA were discussed in detail and the limitations of the pressurized TGA were highlighted.

Hydrocarbons↗

Experimental measurement of the rapid mixing of fuel and air in a multi-element diffusion (Hencken) burner

Flat flame burners are valuable tools for studying complex combustion phenomena like particle synthesis due to the well-controlled and well-behaved initial and boundary conditions. In this study, the methane/air flame temperature and tracer density profiles of a multi-element diffusion burner equipped with a central tube were characterized using krypton (Kr) x-ray fluorescence at the Advanced Photon Source at Argonne National Laboratory. The experiments were performed using a fuel-to-oxygen equivalence ratio of 0.8 and 3.3% Kr by volume was added to the reactant gases. One- and two-dimensional scans of non-combusting (i.e., cold flow) and combusting conditions, both with and without flow through the central tube were performed. Spatially-resolved Kr number density profiles were obtained at different planar locations and heights above the surface of the burner. The results show rapid mixing occurred near the exit-plane of the burner and increased spatial uniformity was achieved from 0.1 mm to 0.5 mm above the surface of the burner. Further, the data also showed the impact of the central tube flow on the main methane/air flame, including evidence of the central tube flow mixing with the main flow. Flame temperatures were calculated from the fluorescence measurements at various heights above the burner surface and were in good agreement with model predictions for a burner stabilized flame. These high-fidelity measurements provide accurate baseline data that are particularly valuable for understanding the effects of fuel and air mixing on downstream phenomena, such as the formation of condensed-phase products.

42 ENGINEERING↗

Characterizing Tradeoffs in Memory, Accuracy, and Speed for Chemistry Tabulation Techniques

Chemistry tabulation is a common approach in practical simulations of turbulent combustion at engineering scales. Linear interpolants have traditionally been used for accessing precomputed multidimensional tables but suffer from large memory requirements and discontinuous derivatives. Higher-degree interpolants address some of these restrictions but are similarly limited to relatively low-dimensional tabulation. Artificial neural networks (ANNs) can be used to overcome these limitations but cannot guarantee the same accuracy as interpolants and introduce challenges in reproducibility and reliable training. These challenges are enhanced as the physics complexity to be represented within the tabulation increases. Here, we assess the efficiency, accuracy, and memory requirements of Lagrange polynomials, tensor product B-splines, and ANNs as tabulation strategies. We analyze results in the context of nonadiabatic flamelet modeling where higher dimension counts are necessary. While ANNs do not require structuring of data, providing benefits for complex physics representation, interpolation approaches often rely on some structuring of the table. Interpolation using structured table inputs that are not directly related to the variables transported in a simulation can incur additional query costs. This is demonstrated in the present implementation of heat losses. We show that ANNs, despite being difficult to train and reproduce, can be advantageous for high-dimensional, unstructured datasets relevant to nonadiabatic flamelet models. Furthermore we demonstrate that Lagrange polynomials show significant speedup for similar accuracy compared to B-splines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact Analysis of Transitioning to Heat Pump Rooftop Units for the U.S. Commercial Building Stock: Preprint

20% of the U.S. commercial building sector's energy usage is from on-site combustion of fossil fuels for heating. Decarbonization will require electrification of these systems to meet climate goals, often by transitioning to heat pumps. Rooftop units (RTU) are the most prominent commercial building HVAC system type and should therefore be prioritized for decarbonization solutions. However, there is limited understanding of the impact on emissions that considers regional electricity generation methods, as well as the impact of other heat pump intricacies such as the effects of temperature on capacity/efficiency, defrost operation, realistic sizing methodologies, and supplementary heating. This study explores the effects of transitioning all conventional RTUs to high-performance heat pump RTUs for the U.S. commercial building stock. The analysis is performed using ComStock, DOE's calibrated model of the U.S. commercial building stock developed by NREL. Results show 9% and 17% reductions in stock aggregate energy consumption and GHG emissions, respectively. Furthermore, average heat pump operational details are presented by state. This analysis will help inform the transition to heat pump RTUs for the U.S. commercial building stock.

commercial building electrification↗

Reentrant polar phase induced by the ferroionic coupling in B⁢i 1−𝑥 ⁢S⁢m 𝑥 ⁢Fe⁢O 3 nanoparticles

Using the model of four sublattices, the Landau-Ginzburg-Devonshire-Kittel phenomenological approach and the Stephenson-Highland ionic adsorption model for the description of coupled polar and antipolar long-range orders in ferroics, we analytically calculated the phase diagrams and polar properties of B⁢i 1−𝑥 ⁢S⁢m 𝑥⁢ Fe⁢O 3 nanoparticles covered by surface ions with dependence on their size, surface ions density, samarium content 𝑥 , and temperature. The size effects and ferroionic coupling govern the appearance and stability conditions of the long-range ordered ferroelectric, reentrant ferrielectric, and antiferroelectric phases in B⁢i 1−𝑥 ⁢S⁢m 𝑥 ⁢Fe⁢O 3 nanoparticles. Calculated phase diagrams are in qualitative agreement with the x-ray diffraction phase analysis, electron paramagnetic resonance, infrared spectroscopy, and electrophysical measurements of B⁢i 1−𝑥 ⁢S⁢m 𝑥 ⁢Fe⁢O 3 nanopowders sintered by the solution combustion method. The combined theoretical-experimental approach allows us to explain the influence of the ferroionic coupling and size effects in B⁢i 1−𝑥 ⁢S⁢m 𝑥 ⁢Fe⁢O 3 nanoparticles on their polar properties.

antiferroelectricity↗

Evaluating Class 6 Delivery Truck Fuel Economy and Emissions Using Vehicle System Simulations for Conventional and Hybrid Powertrains and Co-Optima Fuel Blends

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance. Comparisons were made between ultralow-sulfur diesel and a blend of 25% hexyl hexanoate with diesel. Model validation data were informed by 2019 model year Cummins ISB 6.7 L diesel engine maps and transient validation data in a pre-production hybrid configuration and a direct dyno coupled configuration with diesel fuel and a blend of 25% hexyl hexanoate with diesel.

33 ADVANCED PROPULSION SYSTEMS↗