Publications

2021

Uncertainty-based weight determination for surrogate optimization

REF Doohyun Kim and Angela Violi

Fuel surrogates are simplified models that mimic the combustion characteristics of very complex real transportation fuels and enable a detailed description of the computational system for the targeted real fuels. Current efforts in surrogate development focus on matching multiple target properties of the real fuel using numerical optimization of species compositions. A way to solve the multi-objective optimization problem is to employ the weighted-sum approach with arbitrarily assigned weights. In this paper, we propose a novel approach to reduce such arbitrariness by incorporating physical information into the surrogate optimization process, leveraging uncertainties from experimental measurements and mixture property predictions to determine the weight of each target property.

Scaling of silicon nanoparticle growth in low temperature flowing plasmas

REF Steven J. Lanham, Jordyn Polito, Xuetao Shi, Paolo Elvati, Angela Violi, Mark J. Kushner

Low temperature plasmas are an emerging method to synthesize high quality nanoparticles (NPs). An established and successful technique to produce NPs is using a capacitively coupled plasma (CCP) in cylindrical geometry. Although a robust synthesis technique, optimizing or specifying NP properties using CCPs, is challenging. In this paper, results from a computational investigation for the growth of silicon NPs in flowing inductively coupled plasmas (ICPs) using Ar/SiH4 gas mixtures of up to a few Torr are discussed.

Non-thermal plasma systems offer unique opportunities in the fields of bioimaging, drug delivery, photovoltaics, microelectronics manufacturing. Such interests are largely inspired by the fact that hot plasma electrons coexist with neutral species and ions close to room-temperature under non-thermal plasma conditions. A key parameter for determining the contribution of a certain radical/ion species to the nanoparticle surface growth, called sticking coefficient, is computed as a weighted sum from the simulated sticking outcomes with different collision velocities drawn from a Maxwell-Boltzmann distribution at certain temperatures.

On the growth of Si nanoparticles in non-thermal plasma: physisorption to chemisorption conversion

REF Xuetao Shi, Paolo Elvati, Angela Violi

In this work, the collisions of SiHx(x=1-4) fragments and silicon cluster (Si4, Si2H6, and Si29H36) surfaces, responsible for the sticking coefficients, are simulated by molecular dynamics (MD) with a reactive force field. The dependence of sticking coefficients on temperature, H coverage of both silane fragments and cluster surfaces, and the size of the cluster, are systematically examined. A detailed and multi-parameter model of sticking coefficients, accompanied by the mechanism study of physisorption to chemisorption conversion, provides a more accurate and robust approximation of surface growth rate using sticking coefficients, and a deeper understanding of surface growth processes, for the wider non-thermal plasma simulation community.

An important step in predicting the growth of soot nanoparticles is understanding how gas phase variations affect the formation of their aromatic precursors. Once formed, these aromatic structures begin to assemble into nanoparticles and, regardless of the clustering process, the molecular properties of the aromatic precursors play an important role. Leveraging existing experimental data collected from a coflow Jet A-1 surrogate diffusion flame,

Stochastic and network analysis of polycyclic aromatic growth in a coflow diffusion flame

REF Jacob C. Saldinger, Paolo Elvati, Angela Violi

in this paper we report on a detailed study of the spatial evolution of molecular structures of polycyclic aromatic compounds (PACs) and their corresponding formation pathways, using SNapS2 kinetic Monte Carlo software to simulate the chemical evolution of PACs along multiple streamlines. The results show that growth only occurs along streamlines that traverse regions of high acetylene concentrations in the center of the flame.

One of the key parameters required to identify effective drugs is membrane permeability, as a compound intended for an intracellular target with poor permeability will have low efficacy. In this paper, we leverage a computational approach recently developed by our group, combined with all-atom molecular dynamic simulations, to study the interactions between nanoparticles and mammalian membranes to study the time of entry of a 79 of drugs into the viral envelope of coronavirus as well as cellular organelles.

On Drug-Membrane Permeability of Antivirals for SARS-CoV‐2

REF Changjiang Liu, Paolo Elvati, Angela Violi


The results highlight important trends that can be exploited for drug design, from the relatively high permeability of the viral envelope and the effect of transmembrane proteins, to the differences in permeability between organelles.

Here, we present a Symposia Review, summarizing the scientific contributions and events of those who attended the 16th International Congress on Combustion By-Products and Their Health Effects.

Combustion by-products and their health effects: Summary of the 16th international congress

REF Angela Violi, Stephania Cormier, Brian Gullett, Stina Jansson, Slawo Lomnicki, Chloe Luyet, Andreas Mayer, Ralf Zimmermann