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We present a semi-analytic model for a novel plasma-assisted chemical conversion pathway using triboplasmas generated in granular flows. Triboelectric charge relaxation is a well known phenomena where the potential generated from contact charging of particles exceeds the breakdown voltage of the background gas. In this work, we extend the triboelectric charge relaxation theory to include non equilibrium plasma energy and particle balance equations to predict the formation of dissociated and excited species that act as precursors to chemical conversion, for example in plasma-assisted ammonia synthesis. Our example case study with nitrogen background gas and teflon/aluminum tribomaterial system yielded high excited nitrogen species densities per collision that are comparable to current plasma-assisted conversion pathways. We also present a regime diagram for various gases where Paschen breakdown parameters are used to determine whether triboplasmas can be formed for a given effective work-function difference between two materials. Our sensitivity studies indicate particle velocity, particle radius, solids fraction and space charge effects play a critical role in overall plasma densities and excited species production.

Gas-particle flows are commonly simulated through two-fluid model at industrial-scale. However, these simulations need very fine grid to have accurate flow predictions, which is prohibitively demanding in terms of computational resources. To circumvent this problem, the filtered two-fluid model has been developed, where large-scale flow field is numerically resolved and small-scale fluctuations are accounted for through subgrid-scale modeling. In this study, we have performed fine-grid two-fluid simulations of dilute gas-particle flows in periodic domains and applied explicit filtering to generate datasets. Then, these datasets have been used to develop artificial neural network (ANN) models for closures such as the filtered drag force and solid phase stress for the filtered two-fluid model. The set of input variables for the subgrid drag force ANN model that has been found previously to work well for dense flow regimes is found to work as well for the dilute regime. In addition, we present a Galilean invariant tensor basis neural network (TBNN) model for the filtered solid phase stress which can capture nicely the anisotropic nature of the solid phase stress arising from subgrid-scale velocity fluctuations. Finally, the predictions provided by this new TBNN model are compared with those obtained from a simple eddy-viscosity ANN model.

Contact electrification, or contact charging, refers to the process of static charge accumulation after rubbing, or even simple touching, of two materials. Despite its relevance in static electricity, various natural phenomena, and numerous technologies, contact charging remains poorly understood. For insulating materials, even the species of charge carrier may be unknown, and the direction of charge-transfer lacks firm molecular-level explanation. We use all-atom molecular dynamics simulations to investigate whether thermodynamics can explain contact charging between insulating polymers. Building on prior work implicating water-ions (e.g., hydronium and hydroxide) as potential charge carriers, we predict preferred directions of charge-transfer between polymer surfaces according to the free energy of water-ions within water droplets on such surfaces. Broad agreement between our predictions and experimental triboelectric series indicate that thermodynamically driven ion-transfer likely influences contact charging of polymers. Importantly, simulation analyses reveal how specific interactions of water and water-ions proximate to the polymer-water interface explains observed trends. This study establishes relevance of thermodynamic driving forces in contact charging of insulators with new evidence informed by molecular-level interactions. These insights have direct implications for future mechanistic studies and applications of contact charging involving polymeric materials.

A fundamental understanding of plasma-catalyst interactions is important for understanding reaction mechanisms, optimizing the catalyst, and increasing the efficiency of plasma-assisted catalytic process for ammonia (\ce{NH3}) synthesis. We report on the effect of the surface porosity of the catalyst support on this reaction carried out in a coaxial dielectric barrier discharge (DBD) plasma reactor. The discharge was created using a variable AC applied voltage at room temperature and near atmospheric pressure (550 Torr). Two catalyst supports were compared: porous silica (\ce{SiO2}) ceramic beads and smooth, non-porous soda lime glass beads of almost equal diameter ($\sim$1.5 mm) were used. \ce{N2} conversion and the \ce{NH3} synthesis rate was increased with increasing voltage for both supports, but the energy yield for \ce{NH3} production increased for the \ce{SiO2} beads and decreased for the glass beads. All three of these parameters were always higher when using the \ce{SiO2} beads, which suggests that porosity can be a small advantage for plasma assisted \ce{NH3} synthesis. Discharge and plasma properties were estimated from Lissajous plots and using calculations with the BOLSIG+ software. The effect of different catalyst supports on the physical properties of the discharge was negligible. High resolution optical emission spectra (OES) were used to explore the evolution of gas phase active species, \ce{N2+}, atomic N, electronically excited \ce{N2}, and atomic H (H$_\alpha$, H$_\beta$), in the plasma in the presence of both supports. The relative concentration of these species was lower in the case of the porous \ce{SiO2} beads for all applied voltages, which suggests that surface reactions are more significant than gas phase reactions for the formation of \ce{NH3} in plasma assisted \ce{NH3} synthesis.

We present theoretical predictions of granular flow in a conical hopper based on a continuum theory employing a recently-developed constitutive model with microstructure evolution by Sun and Sundaresan [1]. The model is developed for strain rate-independent granular flows. The closures for the pressure and the macroscopic friction coefficient are linked to microstructure through evolution equations for the coordination number and fabric. The material constants in the model are functions of particle-level properties. A salient prediction is the variable stress ratio along the flow direction, in contrast to the constant ratio employed in some widely-used plasticity theories, but supported by results obtained from discrete element simulations. The model permits direct interrogation of the influence of particle-particle friction as well as normal-stress differences on the stress distribution and discharge rate. Increasing particle friction leads to higher stress ratios, but lower normal stress and flow rates, while considering normal-stress differences results in the opposite effects.

Using the kinetic-theory-based two-fluid models as a starting point, we develop filtered two-fluid models for a gas-particle flow in the presence of an isothermal, first-order, solid-catalyzed reaction of a gaseous species. As a consequence of the filtering procedure, terms describing the filtered reaction rate and filtered reactant dispersion need to be constituted in order to close the filtered species balance equation. In this work, a constitutive relation for filtered reaction rate is developed by performing fine-grid, two-fluid model simulations of an isothermal, solid-catalyzed, first-order reaction in a periodic domain. It is observed that the cluster-scale effectiveness factor, defined as the ratio between the reaction rate observed in a fine-grid simulation to that observed in a coarse-grid simulation, can be substantially smaller than unity, and it manifests an inverted bell shape dependence on filtered particle volume fraction in all simulation cases. Moreover, the magnitude of the deviation in the cluster-scale effectiveness factor from unity is a strong function of the meso-scale Thiele modulus and dimensionless filter size. Thus coarse-grid simulations of a reacting gas-particle flow will overestimate the reaction rate if the cluster-scale effectiveness factor is not accounted for.

We investigate the rheology of granular materials via molecular dynamics simulations of homogeneous, simple shear flows of soft, frictional, noncohesive spheres. In agreement with previous results for frictionless particles, we observe three flow regimes existing in different domains of particle volume fraction and shear rate, with all stress data collapsing upon scaling by powers of the distance to the jamming point. Though this jamming point is a function of the interparticle friction coefficient, the relation between pressure and strain rate at this point is found to be independent of friction. We also propose a rheological model that blends the asymptotic relations in each regime to obtain a general description for these flows. Finally, we show that departure from inertial number scalings is a direct result of particle softness, with a dimensionless shear rate characterizing the transition., Comment: Accepted to Physical Review E

Acceleration and sound measurements during granular discharge from silos are used to show that silo music is a sound resonance produced by silo quake. The latter is produced by stick-slip friction between the wall and the granular material in tall narrow silos. For the discharge rates studied, the occurrence and frequency of flow pulsations are determined primarily by the surface properties of the granular material and the silo wall. The measurements show that the pulsating motion of the granular material drives the oscillatory motion of the silo and the occurrence of silo quake does not require a resonant interaction between the silo and the granular material., Comment: 16 pages, submitted to Powder Technology