Tag: Plasma Modeling

Seminar notes: Plasma Design of 2D Nanostructures and Beyond Graphene

Online LTP Seminar – 2020 Bi-weekly, Tuesday, 9:00 AM EST ProgramProf. Uroš Cvelbar discussed their work on plasma assisted graphene nanowall growth on plasma treated substrates in changing conditions of pressure and temperature as well as different gas mixtures. His group and collaborators worked on a computational model of large scale production. The model confirmed that lateral surface diffusion through nanoflakes are the main mechanism in catalysis rather than vertical particle transfer because of the ion bombardment causing surface defects and resulting an increase in surface adsorption energy. This was the key takeaway for my future research on understanding of the mechanisms of plasma sintering.

https://mipse.umich.edu/ltp_seminars.php

Models and Representation

Models and Representation, I. G. Hughes

  • the most important distinction:

“The requirement of empirical adequacy is thus the requirement that interpretation is the inverse of denotation.” pg. 333.

Overall, I’m impressed by this simple sentence because I can correlate this with the constructive empiricism of Van Fraassen, asserting the acceptance of a theory with the belief that it is empirically adequate. In my view, interpretation (in the sense of this reading) is mapping of a broader theory, which is postulated in the earlier stages of research by denotations. Demonstration step is related to the mathematical or material model, providing empirical adequacy as a bridge between denotation and interpretation.

  • a clarification question/criticism:

“Galileo’s strategy is to take a problem in physics and represent it geometrically. The solution to the problem is then read off from the geometrical representation. In brief, he reaches his answer by changing the question; a problem in kinematics becomes a problem in geometry. This simple example suggests a very general account of theoretical representation. I call it the DDI account.” pg. 327.

I don’t think this example is a good start point to introduce a new account because it’s focusing on representation/denotation step mostly. For demonstration, he would mention the mathematical expression of this motion (x=1/2*a*t^2) or would show a result of an experiment (e.g. a car is moving from the city A to the city B).

Models and Fiction, Roman Frigg

  • the most important distinction:

“What is missing in the structuralist conception is an analysis of the physical character of model systems. (…) If the Newtonian model system of sun and earth were real, it would consist of two spherical bodies with mass and other concrete properties such as hardness and color, properties that structures do not have; (…) “ pg.253.

I appreciate his distinction for the model systems to be real or hypothetical entities. It sounds a bit cheesy that the Newtonian model system should consist of real spherical bodies with hardness and color (?!). If the model system is designed to show the gravitational force between two celestial objects, then why do we care about their hardness or color? The model describes the force, not the solid objects.

  • a clarification question/criticism:

“Hence, the essential difference between a fictional and non-fictional text lies in what we are supposed to do with it: a text of fiction invites us to imagine certain things while a report of fact leads us to believe what it says.” pg. 260.

So, what if we read a text from an unknown author on the weather predictions for the next 20 years? Let’s say he/she writes about the expected climate changes in South Bend area, and saying, ‘the Lake Michigan will evaporate quickly and will trigger tornados almost every week during spring and summer.’ How can you decide if this is a part of a horror novel or scientific fact? I think there should be more distinctive features in scientific texts, such as reliability, testability, fallibility, the power of its predictions, applicability etc. (Thanks Sir Karl, again!)

Notes from iPlasmaNano 2018

It was a really dense conference. Mostly, the professors gave talks about the latest updates of their research. The discussions were at high level. I tried to keep my eyes open to follow almost every talk 🙂 But, it’s worth it 🙂 Here are the topics attracting my attention.

 

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Review: UNIQUE SOLUTIONS TO BOUNDARY VALUE PROBLEMS IN THE COLD PLASMA MODEL

In this article, Otway provides a solution to the closed Dirichlet problem which is a mixed eliptic-hyperbolic equation. This type of equations are encountered in electromagnetic wave propagation in cold plasmas.

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Summary: EEDF FOR MODELLING THE PLASMA KINETICS IN DIELECTRIC BARRIER DISCHARGES

In this article, different electron energy distribution functions (EEDF) for plasma conditions in xenon dielectric barrier discharge (DBD) are explored in plasma modelling. At the beginning, ionization and excitation rates resulting from electron-neutral collisions are discussed. Generally, local-field approximation (LFA) is used for those collisions by assuming electrons gain energy in nanoseconds and reaches equilibrium. For the LFA models, electron energy distribution function is governed by the Boltzmann equation for the primary elastic and inelastic collisions. Although LFA is useful to calculate the primary ionization and excitation rates, diffusion and mobility coefficients, the secondary processes are omitted. These processes can be superelastic collisions, stepwise ionization, electron-ion recombination etc. The models using LFA neglect the secondary processes to reduce the computational cost.

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Summary: PARTICLE AND FLUID SIMULATIONS OF LOW-TEMPERATURE PLASMA DISCHARGES: BENCHMARKS AND KINETIC EFFECTS

The review article has evaluated three different particle and fluid simulations for low-temperature plasma discharges. The investigated methods are fluid, particle-in-cell and hybrid simulations. The plasma discharge includes complexities in itself but the disciplined models can offer research guidelines, better design alternatives and better operation conditions. The selected model is adapted to the specific plasma conditions. The weakness of the simulations results from the uncertainties of the input parameters and the assumptions. For plasma simulations, cross sections, secondary electron emission coefficients and rate constants cannot be identified strictly.

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