### Abstract

In this work we investigate electron transport, transition from an electron avalanche into a negative streamer, and propagation of negative streamers in liquid xenon. Our standard Monte Carlo code, initially developed for dilute neutral gases, is generalized and extended to consider the transport processes of electrons in liquids by accounting for the coherent and other liquid scattering effects. The code is validated through a series of benchmark calculations for the

Percus–Yevick model, and the results of the simulations agree very well with those predicted by a multi term solution of Boltzmann’s equation and other Monte Carlo simulations. Electron transport coefficients, including mean energy, drift velocity, diffusion tensor, and the first Townsend coefficient, are calculated for liquid xenon and compared to the available measurements. It is found that our Monte Carlo method reproduces both the experimental and theoretical drift velocities and characteristic energies very well. In particular, we discuss the

occurrence of negative differential conductivity in the E/n0 profile of the drift velocity by considering the spatially-resolved swarm data and energy distribution functions. Calculated transport coefficients are then used as an input in fluid simulations of negative streamers, which are realized in a 1.5 dimensional setup. Various scenarios of representing the inelastic energy

losses in liquid xenon, ranging from the case where the energy losses to electronic excitations are neglected, to the case where some particular excitations are taken into account, and to the case where all electronic excitations are included, are discussed in light of the available spectroscopy

and photoconductivity experiments. We focus on the way in which electron transport coefficients and streamer properties are influenced by representation of the inelastic energy losses, highlighting the need for the correct representation of the elementary scattering processes in the modeling of liquid discharges.

Percus–Yevick model, and the results of the simulations agree very well with those predicted by a multi term solution of Boltzmann’s equation and other Monte Carlo simulations. Electron transport coefficients, including mean energy, drift velocity, diffusion tensor, and the first Townsend coefficient, are calculated for liquid xenon and compared to the available measurements. It is found that our Monte Carlo method reproduces both the experimental and theoretical drift velocities and characteristic energies very well. In particular, we discuss the

occurrence of negative differential conductivity in the E/n0 profile of the drift velocity by considering the spatially-resolved swarm data and energy distribution functions. Calculated transport coefficients are then used as an input in fluid simulations of negative streamers, which are realized in a 1.5 dimensional setup. Various scenarios of representing the inelastic energy

losses in liquid xenon, ranging from the case where the energy losses to electronic excitations are neglected, to the case where some particular excitations are taken into account, and to the case where all electronic excitations are included, are discussed in light of the available spectroscopy

and photoconductivity experiments. We focus on the way in which electron transport coefficients and streamer properties are influenced by representation of the inelastic energy losses, highlighting the need for the correct representation of the elementary scattering processes in the modeling of liquid discharges.

Original language | English |
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Article number | 015006 |

Number of pages | 19 |

Journal | Plasma Sources Science and Technology |

Volume | 28 |

DOIs | |

Publication status | Published - 28 Jan 2019 |

### Keywords

- negative streamers
- inelastic collisions
- Monte Carlo
- electron transport
- liquid xenon

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## Cite this

Simonović, I., Garland, N., Bošnjaković, D., Petrović, Z., White, R., & Dujko, S. (2019). Electron transport and negative streamers in liquid xenon.

*Plasma Sources Science and Technology*,*28*, [015006]. https://doi.org/10.1088/1361-6595/aaf968