Link Function: information

Tabulated transport coefficients and scattering cross-sections play a vital role in plasma modeling and in enabling transparent, quantitative comparisons across different experimental studies. Over the past decade, the expansion of experimental datasets has also enabled data-driven approaches, most notably deep learning techniques, to infer electron scattering cross-sections from measured transport properties. To date, most databases (including LXCat and NIST) have focused primarily on electron transport in the gas phase. However, recent developments have begun to broaden this scope. For example, LXCat has announced an updated version of its database that will incorporate new states of matter and broader classes of incident particles.

In this dataset, we present data on the electron mobility and diffusion coefficients in LXe and LAr over a range of experimental conditions. The full dataset is also available on GitHub and is structured in a format similar to LXCat. While CSV formats were initially used, we are exploring alternative text-based formats to better support transparency and long-term maintainability. Each dataset includes accompanying files compatible with WebPlotDigitizer v4, making the digitization process reproducible and easy to update.

This dataset contains the results of PIC-MCC simulations of a 2D plasma in a box in 7 test cases with different boundary conditions. The results can be used to verify the correct implementation of PIC and MCC routines. The simulations are performed using the LPPic code, developed at the Laboratoire de Physique des Plasmas (LPP) at École polytechnique, and with Pantera, developed at the von Karman Institute for Fluid Dynamics (VKI).

CrossSections.zip contains the cross-sections used in the simulations in tabulated form. The first column is the collision energy in the center-of-mass frame in [eV]. The second column is the cross-section in [m²]. The cross-section for elastic e−H and electron impact excitation are taken from the Morgan database on LXCat (https://nl.lxcat.net). The cross sections for H+−H elastic and charge exchange collisions are taken from the tabulated data in Schultz et al.. The ionization cross section corresponds to the fit of Janev et al., but the energy has been scaled down by a factor of 10 for practical reasons.

DensityTemporalProfiles_xxx.csv contain the temporal evolution of the mean electron and ion density, normalized to the initial density. The data from VKI also contains the corresponding confidence interval estimates.

DensitySpatialProfiles_xxx.csv contain the spatial profiles along the x-coordinate (x in [0,1]m) of the electron and ion densities at the lat time step (t = 5 μs), spatially avergaed in the interval 0.4 m < y < 0.6 m. The data from VKI also contains the corresponding confidence interval estimates.

ResultsComparison.zip contains the temporal history of many domain-integrated quantities (number of particles, total momentum, energies, ...) for each run of each test case using both codes.

ErrorQuantification.zip contains the results of the same integrated quantities, in addition to a final snapshot of the simulation domain, for each test case at three progressive levels of refinement, obtained using the VKI code. These data has been used to compute the confidence intervals for temporal and spatial quantities.

DensityConvergenceRate.pdf contains plots of the effective convergence rate for the mean density of electrons and ions as a function of time for all test cases, computed using the VKI code.

We present a freely available MATLAB code for the simulation of electron transport in arbitrary gas mixtures in the presence of uniform electric fields. For steady-state electron transport, the program provides the transport coefficients, reaction rates and the electron energy distribution function. The program uses established Monte Carlo techniques and is compatible with the electron scattering cross section files from the open-access Plasma Data Exchange Project LXCat. The code is written in object-oriented design, allowing the tracing and visualization of the spatiotemporal evolution of electron swarms and the temporal development of the mean energy and the electron number due to attachment and/or ionization processes. We benchmark our code with well-known model gases as well as the real gases argon, N2, O2, CF4, SF6 and mixtures of N2 and O2.