Polaritonic chemistry is emerging as a powerful approach to modifying the properties and reactivity of molecules and materials. However, probing how the electronics and dynamics of molecular systems change under strong coupling has been challenging due to the narrow range of spectroscopic techniques that can be applied in situ. Here we develop microfluidic optical cavities for vibrational strong coupling (VSC) that are compatible with nuclear magnetic resonance (NMR) spectroscopy using standard liquid NMR tubes. VSC is shown to influence the equilibrium between two conformations of a molecular balance sensitive to London dispersion forces, revealing an apparent change in the equilibrium constant under VSC. In all compounds studied, VSC does not induce detectable changes in chemical shifts, J-couplings, or spin-lattice relaxation times. This unexpected finding indicates that VSC does not substantially affect molecular electron density distributions, and in turn has profound implications for the possible mechanisms at play in polaritonic chemistry under VSC and suggests that the emergence of collective behavior is critical.

The macroscopic simulation of soot production in flames by CFD approaches often assumes of spherical particles or considers ad-hoc formulas in order to take the particle fractal aggregates’ morphology into account. On the other hand, numerically simulated aggregates can be generated by Discrete Element Modeling (DEM) simulations at the nanoscopic scale. However, the change in thermodynamic conditions, surface growth, oxidation, and nucleation mechanisms are commonly neglected by this approach. This work combines these complementary approaches to investigate the detailed morphology of soot along 4 different particle trajectories in a diffusion flame. The proposed multi-scale approach shows remarkably larger and more compact aggregates near the wings of the flame as compared to the centerline, in agreement with previous experimental studies. This approach allows to analyse the particle polydispersity and morphological parameters beyond the fractal dimension, such as anisotropy coefficient and monomers overlapping coefficient. It becomes possible to reveal clear morphological signatures of soot formed along different streamlines in the flame. Finally, we have also observed a positive correlation between primary particle diameter and aggregate gyration diameter due to the predominance of surface reactions over aggregation. The proposed post-processing of CFD results based on DEM methods, bringing new information on soot morphology, is a proof of concept of a more accurate procedure for validating soot models used in CFD codes as compared to existing methods in the literature.

The morphological description of fractal agglomerates is generally reduced to only two parameters, namely the mass fractal dimension and its prefactor. In the most evolved approaches, a stretching exponent is also introduced, while a packing factor is preferred to the fractal prefactor. In any case, the current analytical description of agglomerates morphology is accurate only for sufficiently large agglomerates, which is due to the limited spatial extension of the clusters that are actually quasi-fractal. In the present study, a cutoff function of the pair correlation function is considered for both larger and smaller scales. This enables a more accurate morphological description valid for any cluster size is to be given taking into account the polydispersity of the primary spheres. This new analytical morphological description relying on 5 parameters, is presented here for the first time. The physical range covered by these morphological parameters is determined based on virtually generated Diffusion Limited Cluster Agglomeration. Finally, the model is used to express the fractal prefactor and structure factors and their dependence on agglomerate size and morphological parameters is investigated.

The application of Monte Carlo methods to simulate the agglomeration of suspended nanoparticles is currently limited to specific agglomeration regimes with reduced accuracy in terms of the particle's physical residence time. The definition of specific particles persistent distance, its corresponding time step and subsequent probabilities for particle displacements may improve the accuracy of this method. To solve these issues, a new persistent distance and its corresponding time step based on Langevin dynamics simulations are introduced. Additionally, a probability of particle displacements, not restricted to a specific agglomeration regime, is introduced. All the modifications are validated by comparison with Langevin dynamics simulations. Finally, the above mentioned modifications considerably improve the accuracy of Monte Carlo methods to predict the dynamics and agglomeration of suspended nanoparticles.

Soot primary particle size distribution along the centerline of a laminar coflow methane/air diffusion flame doped with vaporized n-heptane at atmospheric pressure was studied using the planar two-color time-resolved laser-induced incandescence (TiRe-LII) technique and analysis of transmission electron microscope images. An improved thermophoretic probe sampling procedure was used to collect samples of soot particles. The LII signals captured at two wavelength bands in the visible are used to determine the soot effective temperature by two-color pyrometry. The methodology was first validated against the literature data obtained in a laminar coflow ethylene/air diffusion flame. The same methodology is then applied to the n-heptane doped methane flame along the flame centerline. The Sauter and geometric mean diameters of soot primary particles were obtained. Good agreement is found between the soot primary particle size distributions obtained by the two techniques.

During the agglomeration of nanoparticles and in particular, soot, a change in both the flow regime (from free molecular to near continuum) as well as the change of agglomeration regime (from ballistic to diffusive) is expected. However, these effects are rarely taken into account in numerical simulations of particle agglomeration and yet, they are suspected to have an important impact on the agglomeration kinetics, particle morphologies, and size distributions. This work intends to study these properties by using the Monte Carlo Aggregation Code (MCAC) presented in the preceding work (part 1), focusing on the physical impacts of varying the particle volume fraction and monomers size and polydispersity. The results show an important sensitivity of the kinetics of agglomeration, coagulation homogeneity, and agglomerate morphology to the size of monomers. First, for smaller monomer diameters, the agglomeration kinetic is enhanced and agglomerates are characterized by larger fractal dimensions. Second, for large monomer diameters, fractal dimensions down to 1.67 can be found being smaller than the classical 1.78 for Diffusion Limited Cluster Agglomeration (DLCA) mechanism. One important conclusion is that variation in time of both regimes has to be considered for a more accurate simulation of the agglomerate size distribution and morphology.

Site-selectivity is fundamental for steering chemical reactivity towards a given product and various efficient chemical methods have been developed for this purpose. Here we explore a very different approach by using vibrational strong coupling (VSC) between a reactant and the vacuum field of a microfluidic optical cavity. For this purpose, the reactivity of a compound bearing two possible silyl bond cleavage sites, at Si-C and Si-O, was studied as a function of VSC of its various vibrational modes in the dark. The results show that VSC can indeed tilt the reactivity landscape to favor one product over the other. Thermodynamic parameters reveal the presence of a large activation barrier and significant changes to the activation entropy, confirming the modified chemical landscape under strong coupling. This study shows for the first time that VSC can impart site-selectivity for chemical reactions without the need for chemical intervention.

In this study, the tunable algorithm of cluster-cluster aggregation developed by Filippov et al. (2000) for generating fractal aggregates formed by monodisperse spherical primary particles is extended to polydisperse primary particles. This new algorithm, termed FracVAL, is developed by using an innovative aggregation strategy. The algorithm is able to preserve the prescribed fractal dimension (D-f )and prefactor (k(f)) for each aggregate, regardless of its size, with negligible error for lognormally distributed primary particles with the geometric standard deviation sigma(p,geo) being as large as 3. In contrast, for polydisperse primary particles the direct use of Filippov et al. (2000) method, as is done by Skorupski et al. (2014), does not ensure the preservation of D-f and k(f) for individual aggregates and it is necessary to generate a large number of aggregates to achieve the prescribed D-f and k(f) on an ensemble basis. The performance of FracVAL is evaluated for aggregates consisting of 500 and 1000 monomers and for fractal dimension variation over the entire range of D-f between 1 and 3 and k(f) between 0.1 and 2.7. Aggregates consisting of 500 monomers are generated on average in less than 2.4 min on a common laptop, illustrating the efficiency of the proposed algorithm. Crown Copyright (C) 2019 Published by Elsevier B.V. All rights reserved.

Combustion generated soot appears as fractal aggregates formed by polydisperse nearly spherical primary particles. Knowledge of their radiative properties is a prerequisite for laser based diagnostics of soot. In this parametric study, the effect of primary particle polydispersity on soot aggregate absorption and scattering properties is investigated numerically. Two series of fractal aggregates formed by normal and lognormal distributed primary particles of different levels of standard deviation were numerically generated for typical flame soot with a fractal dimension and prefactor fixed to D-f = 1.73 and k(f) approximate to 1.5, respectively. Three aggregate sizes consisting of N-p = 15, 50 and 150 monomers per aggregate were investigated. Due to the uncertainty in soot refractive index, radiative properties were calculated by considering two different refractive indices at lambda approximate to 532 nm recommended in the literature using the Discrete Dipoles Approximation and the Generalized Multiparticle Mie method. The results are interpreted in terms of correction factors to the Rayleigh-Debye-Gans theory for fractal aggregates (RDG-FA) for the forward scattering cross section A and for the absorption cross section h. It is shown that differential cross section for vertically polarized incident light, total scattering and absorption cross sections are well predicted by the RDG-FA theory for all considered aggregates formed by normally (sigma/(d) over bar (p) <= 30%) and lognormally (sigma(geo) <= 1.6) distributed primary particles. The refractive index is found to be of greater impact than primary particle polydispersity on the importance of multiple scattering. The radiative force per unit laser power experienced by the soot aggregates was found primarily determined by the aggregate volume, regardless of the level of primary particle polydispersity. (C) 2018 Published by Elsevier Inc. on behalf of The Combustion Institute.

Experimental studies of soot morphology based on analysis of transmission electron microscopy (TEM) images usually neglect the potential effects of primary particle polydispersity and overlapping. In this study, fractal aggregates of different sizes consisting of polydisperse and overlapping primary particles were numerically generated using typical fractal dimension and prefactor relevant to soot. A total of 3600 simulated two-dimensional projections for each primary particle size distribution and level of overlapping considered was produced and analyzed using two TEM image analysis methods commonly used in the literature to evaluate the effects of primary particle polydispersity and overlapping on the recovered morphological parameters of soot. Fairly large deviations in the recovered number of primary particles in aggregates were obtained by both methods considered using the procedure commonly used in the literature. A recommendation was proposed to improve the accuracy of the retrieved number of polydisperse primary particles in an aggregate. We show that the results obtained by using both the Tian et al. (2006) and Brasil et al. (1999) methods can be significantly improved by using the recommended modification for primary particle polydispersity levels commonly encountered in flame soot. Finally, we recommend to use the modified Tian et al. 2006 method for recovering the number of primary particles of aggregates consisting of both polydisperse and overlapped primary particles.

The morphological characteristics of soot are of primary importance to quantify its effect on climate forcing and human health and also to interpret the signals acquired in optically based soot diagnostics. In the present study, the morphology of soot particles produced in laminar coflow diffusion flames was investigated under different fuel and oxidizer conditions. Particles were sampled thermophoretically at the centerline at different heights above the burner in laminar diffusion flames of three common fuels, namely, ethylene, propane, and butane, at two sooting statuses, i.e., under the smoke point and at the smoke point. The oxygen content in the oxidizer stream was systematically varied. Different morphological parameters of mature soot, including primary particle number, aggregate radius of gyration, fractal dimension and prefactor, and overlapping, were obtained based on analysis of transmission electron microscopy images. The diameter and number of monomers were calculated by using automated methods based on the Euclidean distance mapping and the relative optical density methods, respectively. The other parameters were derived from these two parameters and some empirical correlations. The fractal dimension under different fuel and oxidizer conditions falls in a relatively narrow range from 1.68 to 2.05, while the derived fractal prefactor varies significantly from 0.24 to 2.66. An exhaustive comparison of the morphological parameters obtained in this study with the literature data suggests that our results fall within a range similar to those reported in previous studies. The present results suggest that the soot morphology does not display a clear trend of variation with the change in oxygen index for all three hydrocarbon fuels studied, at least for the fractal dimension and primary particle diameters obtained in this study.