A Comparative Study on the Combustion Chemistry of Two Bio-hybrid Fuels: 1,3-Dioxane and 1,3-Dioxolane.

Bio-hybrid fuels are a promising solution to accomplish a carbon-neutral and low-emission future for the transportation sector. Two potential candidates are the heterocyclic acetals 1,3-dioxane (C4H8O2) and 1,3-dioxolane (C3H6O2), which can be produced from the combination of biobased feedstocks, carbon dioxide, and renewable electricity. In this work, comprehensive experimental and numerical investigations of 1,3-dioxane and 1,3-dioxolane were performed to support their application in internal combustion engines. Ignition delay times and laminar flame speeds were measured to reveal the combustion chemistry on the macroscale, while speciation measurements in a jet-stirred reactor and ethylene-based counterflow diffusion flames provided insights into combustion chemistry and pollutant formation on the microscale. Comparing the experimental and numerical data using either available or proposed kinetic models revealed that the combustion chemistry and pollutant formation differ substantially between 1,3-dioxane and 1,3-dioxolane, although their molecular structures are similar. For example, 1,3-dioxane showed higher reactivity in the low-temperature regime (500-800 K), while 1,3-dioxolane addition to ethylene increased polycyclic aromatic hydrocarbons and soot formation in high-temperature (>800 K) counterflow diffusion flames. Reaction pathway analyses were performed to examine and explain the differences between these two bio-hybrid fuels, which originate from the chemical bond dissociation energies in their molecular structures.

Role of ring-enlargement reactions in the formation of aromatic hydrocarbons.

Ring-enlargement reactions can provide a fast route towards the formation of six-membered single-ring or polycyclic aromatic hydrocarbons (PAHs). To investigate the participation of the cyclopentadienyl (C5H5) radical in ring-enlargement reactions in high-temperature environments, a mass-spectrometric study was conducted. Experimental access to the C5H5 high-temperature chemistry was provided by two counterflow diffusion flames. Cyclopentene was chosen as a primary fuel given the large amount of resonantly stabilized cyclopentadienyl radicals produced by its decomposition and its high tendency to form PAHs. In a second experiment, methane was added to the fuel stream to promote methyl addition pathways and to assess the importance of ring-enlargement reactions for PAH growth. The experimental dataset includes mole fraction profiles of small intermediate hydrocarbons and of several larger species featuring up to four condensed aromatic rings. Results show that, while the addition of methane enhances the production of methylcyclopentadiene and benzene, the concentration of larger polycyclic hydrocarbons is reduced. The increase of benzene is probably attributable to the interaction between the methyl and the cyclopentadienyl radicals. However, the formation of larger aromatics seems to be dominated only by the cyclopentadienyl driven molecular-growth routes which are hampered by the addition of methane. In addition to the experimental work, two chemical mechanisms were tested and newly calculated reaction rates for cyclopentadiene reactions were included. In an attempt to assess the impact of cyclopentadienyl ring-enlargement chemistry on the mechanisms' predictivity, pathways to form benzene, toluene, and ethylbenzene were investigated. Results show that the updated mechanism provides an improved agreement between the computed and measured aromatics concentrations. Nevertheless, a detailed study of the single reaction steps leading to toluene, styrene, and ethylbenzene would be certainly beneficial.

Advanced Biofuels and Beyond: Chemistry Solutions for Propulsion and Production.

Sustainably produced biofuels, especially when they are derived from lignocellulosic biomass, are being discussed intensively for future ground transportation. Traditionally, research activities focus on the synthesis process, while leaving their combustion properties to be evaluated by a different community. This Review adopts an integrative view of engine combustion and fuel synthesis, focusing on chemical aspects as the common denominator. It will be demonstrated that a fundamental understanding of the combustion process can be instrumental to derive design criteria for the molecular structure of fuel candidates, which can then be targets for the analysis of synthetic pathways and the development of catalytic production routes. With such an integrative approach to fuel design, it will be possible to improve systematically the entire system, spanning biomass feedstock, conversion process, fuel, engine, and pollutants with a view to improve the carbon footprint, increase efficiency, and reduce emissions.

Modeling Ignition of a Heptane Isomer: Improved Thermodynamics, Reaction Pathways, Kinetics, and Rate Rule Optimizations for 2-Methylhexane.

Accurate chemical kinetic combustion models of lightly branched alkanes (e.g., 2-methylalkanes) are important to investigate the combustion behavior of real fuels. Improving the fidelity of existing kinetic models is a necessity, as new experiments and advanced theories show inaccuracies in certain portions of the models. This study focuses on updating thermodynamic data and the kinetic reaction mechanism for a gasoline surrogate component, 2-methylhexane, based on recently published thermodynamic group values and rate rules derived from quantum calculations and experiments. Alternative pathways for the isomerization of peroxy-alkylhydroperoxide (OOQOOH) radicals are also investigated. The effects of these updates are compared against new high-pressure shock tube and rapid compression machine ignition delay measurements. It is shown that rate constant modifications are required to improve agreement between kinetic modeling simulations and experimental data. We further demonstrate the ability to optimize the kinetic model using both manual and automated techniques for rate parameter tunings to improve agreement with the measured ignition delay time data. Finally, additional low temperature chain branching reaction pathways are shown to improve the model's performance. The present approach to model development provides better performance across extended operating conditions while also strengthening the fundamental basis of the model.

A Review of Terminology Used to Describe Soot Formation and Evolution under Combustion and Pyrolytic Conditions.

This review presents a glossary and review of terminology used to describe the chemical and physical processes involved in soot formation and evolution and is intended to aid in communication within the field and across disciplines. There are large gaps in our understanding of soot formation and evolution and inconsistencies in the language used to describe the associated mechanisms. These inconsistencies lead to confusion within the field and hinder progress in addressing the gaps in our understanding. This review provides a list of definitions of terms and presents a description of their historical usage. It also addresses the inconsistencies in the use of terminology in order to dispel confusion and facilitate the advancement of our understanding of soot chemistry and particle characteristics. The intended audience includes senior and junior members of the soot, black carbon, brown carbon, and carbon black scientific communities, researchers new to the field, and scientists and engineers in associated fields with an interest in carbonaceous material production via high-temperature hydrocarbon chemistry.

Lattice Boltzmann modeling of multicomponent diffusion in narrow channels.

We investigate lattice Boltzmann (LB) modeling of multicomponent diffusion for finite Knudsen numbers. Analytic solutions for binary diffusion in narrow channels, where both molecular and Knudsen diffusion are of importance, are obtained for the standard and higher-order LB methods and validated against the results from the direct simulation Monte Carlo (DSMC) method. The LB methods are shown to reproduce the diffusion slip phenomena. In the DSMC method, while fluid particles are diffusely reflected on a wall, significant component slip and a kinetic boundary layer are observed. It is shown that a higher-order LB method accurately captures the characteristics observed in the DSMC method.

Mechanistic Understanding of Cu-CHA Catalyst as Sensor for Direct NH3-SCR Monitoring: The Role of Cu Mobility.

The concept to utilize a catalyst directly as a sensor is fundamentally and technically attractive for a number of catalytic applications, in particular, for the catalytic abatement of automotive emission. Here, we explore the potential of microporous copper-exchanged chabazite (Cu-CHA, including Cu-SSZ-13 and Cu-SAPO-34) zeolite catalysts, which are used commercially in the selective catalytic reduction of automotive nitrogen oxide emission by NH3 (NH3-SCR), as impedance sensor elements to monitor directly the NH3-SCR process. The NH3-SCR sensing behavior of commercial Cu-SSZ-13 and Cu-SAPO-34 catalysts at typical reaction temperatures (i.e., 200 and 350 °C) was evaluated according to the change of ionic conductivity and was mechanistically investigated by complex impedance-based in situ modulus spectroscopy. Short-range (local) movement of Cu ions within the zeolite structure was found to determine largely the NH3-SCR sensing behavior of both catalysts. Formation of NH3-solvated, highly mobile CuI species showed a predominant influence on the ionic conductivity of both catalysts and, consequently, hindered NH3-SCR sensing at 200 °C. Density functional theory calculations over a model Cu-SAPO-34 system revealed that CuII reduction to CuI by coadsorbed NH3 and NO weakened significantly the coordination of the Cu site to the CHA framework, enabling high mobility of CuI species that influences substantially the NH3-SCR sensing. The in situ spectroscopic and theoretical investigations not only unveil the mechanisms of Cu-CHA catalyst as sensor elements for direct NH3-SCR monitoring but also allow us to get insights into the speciation of active Cu sites in NH3-SCR under different reaction conditions with varied temperatures and gas compositions.

Analytic solution for a higher-order lattice Boltzmann method: slip velocity and Knudsen layer.

We present the analysis of a higher-order lattice Boltzmann (LB) method based on the fourth-order Gauss-Hermite quadrature, with emphasis on the slip velocity and the Knudsen layer. The exact solution of the slip velocity for the higher-order LB equation is obtained for Poiseuille flows with finite Knudsen numbers. Due to increased accuracy in velocity space discretization, the higher-order scheme gives much improved slip coefficients as compared with the standard LB method based on the third-order Gauss-Hermite quadrature. A multiple relaxation time model is investigated to show the effects of the relaxation times for higher-order moments on the slip phenomena.

Slip velocity and Knudsen layer in the lattice Boltzmann method for microscale flows.

We present mesoscopic fluid-wall interaction models for lattice Boltzmann (LB) model simulations of microscale flows. The exact solution of the slip velocity for the LB equation with the Bhatnagar-Gross-Krook collision operator is obtained for Poiseuille flow at finite Knudsen numbers. With a consistent definition of the Knudsen number, the slip coefficients of the LB equation with the standard D2Q9 scheme are found to be slightly larger than those of the Boltzmann equation with the same boundary condition, which makes the standard LB method remain quantitatively accurate only for small Knudsen numbers. By modifying the nonequilibrium energy flux or introducing the effective relaxation time, the LB method is analytically shown to reproduce the slip phenomena up to second order in the Knudsen number. For the standard LB method, the Knudsen layer is captured only with modification of the relaxation dynamics such as in the effective relaxation time model.

Electrochemical and Electronic Charge Transport Properties of Ni-Doped LiMn2O4 Spinel Obtained from Polyol-Mediated Synthesis.

LiNi0.5Mn1.5O4 (LNMO) spinel has been extensively investigated as one of the most promising high-voltage cathode candidates for lithium-ion batteries. The electrochemical performance of LNMO, especially its rate performance, seems to be governed by its crystallographic structure, which is strongly influenced by the preparation methods. Conventionally, LNMO materials are prepared via solid-state reactions, which typically lead to microscaled particles with only limited control over the particle size and morphology. In this work, we prepared Ni-doped LiMn2O4 (LMO) spinel via the polyol method. The cycling stability and rate capability of the synthesized material are found to be comparable to the ones reported in literature. Furthermore, its electronic charge transport properties were investigated by local electrical transport measurements on individual particles by means of a nanorobotics setup in a scanning electron microscope, as well as by performing DFT calculations. We found that the scarcity of Mn3+ in the LNMO leads to a significant decrease in electronic conductivity as compared to undoped LMO, which had no obvious effect on the rate capability of the two materials. Our results suggest that the rate capability of LNMO and LMO materials is not limited by the electronic conductivity of the fully lithiated materials.

Combustion instability mitigation by magnetic fields.

The present interdisciplinary study combines electromagnetics and combustion to unveil an original and basic experiment displaying a spontaneous flame instability that is mitigated as the non-premixed sooting flame experiences a magnetic perturbation. This magnetic instability mitigation is reproduced by direct numerical simulations to be further elucidated by a flow stability analysis. A key role in the stabilization process is attributed to the momentum and thermochemistry coupling that the magnetic force, acting mainly on paramagnetic oxygen, contributes to sustain. The spatial local stability analysis based on the numerical simulations shows that the magnetic field tends to reduce the growth rates of small flame perturbations.

Elucidation and Comparison of the Effect of LiTFSI and LiNO3 Salts on Discharge Chemistry in Nonaqueous Li-O2 Batteries.

The role of lithium salts in determining the discharge capacity of Li-O2 batteries has been highlighted in several recent studies; however, questions pertaining to their effect on the cathode surface and in the solution phase still remain unanswered. We conducted galvanostatic discharge experiments with different compositions of a binary mixture of 1 M of LiNO3 and LiTFSI in tetraglyme (TEGDME) as the electrolyte and analyzed the discharge products using techniques such as FT-IR, Raman spectroscopy, and SEM. It was observed that there is a nonlinear correlation between the electrolyte composition and the first discharge capacity, with the highest discharge capacity achieved with the electrolyte composition as 0.75 M LiNO3 and 0.25 M LiTFSI. The ID/IG values obtained from Raman spectroscopy, which represent the degree of order in the carbon cathode surface, were found to be correlated to the measured capacity. Our results indicate that at concentrations of LiNO3 higher than 0.75 M in the electrolyte, nitrogen doping of the carbon surface reaches a critical limit, beyond which it becomes unfavorable for the discharge process. On the other hand, decomposition of the electrolyte and formation of an amorphous layer on the cathode surface was found to intensify with increasing LiTFSI concentration. Our results show that the maximum discharge capacity of the cells is strongly dependent on the surface structure of the carbon cathode, which in turn is heavily influenced by the electrolyte composition. Classical molecular dynamics simulations of the same system indicated no such nonlinearity in the co-ordination of Li+ ions with respect to electrolyte composition, indicating that the ionic association strength of the anion may have only a limited effect.

Viability of human composite tissue model for experimental study of burns.

Experimental studies of burns are primarily performed with animal models that have important anatomical and physiological differences relative to human systems. The aim of this study was to develop a human experimental burn model using composite tissue obtained from bariatric surgery. We established a new protocol to maintain viable sections of human cutaneous and subcutaneous (sub/cutaneous) tissue in vitro. Under the conditions selected, multiparametric flow cytometry and histological analysis confirmed the viability and integrity of the human sub/cutaneous tissue for at least 5 days. Furthermore, we utilized a precision McKenna burner to inflict burns on the human tissue model under well-defined thermal conditions in vitro. Our data showed a localized, temporally restricted polarization of the resident macrophages in the subcutaneous human tissue in response to specific thermal forces. Therefore, our model provides a useful alternative to animal studies for further detailed investigations of human responses to injuries and treatments.

Stochastic mixing model with power law decay of variance.

A stochastic mixing model based on the law of large numbers is presented that describes the decay of the variance of a conserved scalar in decaying turbulence as a power law, sigma2(c) proportional t(-alpha). A general Lagrangian mixing process is modeled by a stochastic difference equation where the mixing frequency and the ambient concentration are random processes. The mixing parameter lambda is introduced as a coefficient in the mixing frequency in order to account for initial length-scale ratio of the velocity and scalar field and other physical dependencies. We derive a nonlinear integral equation for the probability density function (pdf) of a conserved scalar that describes the relaxation of an arbitrary initial distribution to a delta-function. Numerical studies of this equation are conducted, and it is shown that lambda has a distinct influence on the decay rate of the scalar. Results obtained from the model for the evolution of the pdf are in a good agreement with direct numerical simulation (DNS) data.

Identifying Descriptors for Solvent Stability in Nonaqueous Li-O2 Batteries.

One crucial challenge in developing rechargeable Li-O2 batteries is to identify a stable solvent that is resistant to decomposition in the electrochemical environment of Li2O2. We attempt to identify descriptors that could be used to test for solvent stability. We build on the recent quantitative experimental results on oxygen consumption and release during discharge and charge respectively. We limit our focus to understanding trends in oxidative stability of solvents and based on a systematic treatment of the electrochemical environment of Li2O2, we propose that, to a first approximation, the highest occupied molecular orbital (HOMO) level could be a good descriptor. We demonstrate that this descriptor correlates well with the experimentally measured degree of rechargeability. We utilize this descriptor to screen a large number of solvents and identify several solvents that could enhance the rechargeability of nonaqueous Li-O2 batteries. We provide a comprehensive compilation of available computational and experimental data of several key solvent parameters that we believe will be the genesis for an 'electrolyte genome'.

Solvent Degradation in Nonaqueous Li-O2 Batteries: Oxidative Stability versus H-Abstraction.

Developing rechargeable Li-O2 batteries hinges on identifying stable solvents resistant to decomposition. Here, we focus on solvent stability against adsorption-induced H-abstraction during discharge. Using a detailed thermodynamic analysis, we show that a solvent's propensity to resist H-abstraction is determined by its acid dissociation constant, pKa, in its own environment. Upon surveying hundreds of solvents for their pKa values in different media, we find linear correlations between the pKa values across various classes of solvents in any two given media. Utilizing these correlations, we choose DMSO as the common standard to compare the relative stability trends. We construct a stability plot based on the solvent's HOMO level and its pKa in DMSO, which reveals that most solvents obey a correlation where solvents with lower HOMO levels tend to have lower pKa values in DMSO. However, this is at odds with the stability requirement that demands deep HOMO levels and high pKa values. Thus, stable solvents need to be outliers to this observed correlation.

Advancing predictive models for particulate formation in turbulent flames via massively parallel direct numerical simulations.

Combustion of fossil fuels is likely to continue for the near future due to the growing trends in energy consumption worldwide. The increase in efficiency and the reduction of pollutant emissions from combustion devices are pivotal to achieving meaningful levels of carbon abatement as part of the ongoing climate change efforts. Computational fluid dynamics featuring adequate combustion models will play an increasingly important role in the design of more efficient and cleaner industrial burners, internal combustion engines, and combustors for stationary power generation and aircraft propulsion. Today, turbulent combustion modelling is hindered severely by the lack of data that are accurate and sufficiently complete to assess and remedy model deficiencies effectively. In particular, the formation of pollutants is a complex, nonlinear and multi-scale process characterized by the interaction of molecular and turbulent mixing with a multitude of chemical reactions with disparate time scales. The use of direct numerical simulation (DNS) featuring a state of the art description of the underlying chemistry and physical processes has contributed greatly to combustion model development in recent years. In this paper, the analysis of the intricate evolution of soot formation in turbulent flames demonstrates how DNS databases are used to illuminate relevant physico-chemical mechanisms and to identify modelling needs.

An algorithm for mass matrix calculation of internally constrained molecular geometries.

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model.

Generation of optimal artificial neural networks using a pattern search algorithm: application to approximation of chemical systems.

A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters in optimization. When used together with a surrogate, the resulting algorithm is highly efficient for expensive objective functions. Results demonstrate the effectiveness of this method in optimizing an ANN for the number of neurons, the type of transfer function, and the connectivity among neurons. The optimization method is applied to a chemistry approximation of practical relevance. In this application, temperature and a chemical source term are approximated as functions of two independent parameters using optimal ANNs. Comparison of the performance of optimal ANNs with conventional tabulation methods demonstrates equivalent accuracy by considerable savings in memory storage. The architecture of the optimal ANN for the approximation of the chemical source term consists of a fully connected feedforward network having four nonlinear hidden layers and 117 synaptic weights. An equivalent representation of the chemical source term using tabulation techniques would require a 500 x 500 grid point discretization of the parameter space.

Thermochemical properties of polycyclic aromatic hydrocarbons (PAH) from G3MP2B3 calculations.

In this article, we present a new database of thermodynamic properties for polycyclic aromatic hydrocarbons (PAH). These large aromatic species are formed in very rich premixed flames and in diffusion flames as part of the gas-phase chemistry. PAH are commonly assumed to be the intermediates leading to soot formation. Therefore, accurate prediction of their thermodynamic properties is required for modeling soot formation. The present database consists of 46 species ranging from benzene (C6H6) to coronene (C24H12) and includes all the species usually present in chemical mechanisms for soot formation. Geometric molecular structures are optimized at the B3LYP/6-31++G(d,p) level of theory. Heat capacity, entropy, and energy content are calculated from these optimized structures. Corrections for hindered rotor are applied on the basis of torsional potentials obtained from second-order Møller-Plesset perturbation (MP2) and Dunning's consistent basis sets (cc-pVDZ). Enthalpies of formation are calculated using the mixed G3MP2//B3 method. Finally, a group correction is applied to account for systematic errors in the G3MP2//B3 computations. The thermodynamic properties for all species are available in NASA polynomial form at the following address: http://www.stanford.edu/group/pitsch/.