dc breakdown conditioning and breakdown rate of metals and metallic alloys under ultrahigh vacuum

Descoeudres, Antoine; Ramsvik, T.; Calatroni, S.; Taborelli, M.; Wuensch, Walter

doi:10.1103/physrevstab.12.032001

Cited by 83 publications

(76 citation statements)

References 18 publications

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“…The experimental setup to be modelled [11] consists of a rounded rod (anode) and a plane sample (cathode), with a typical gap distance of 20 μm ( Fig. 1(a)).…”

Section: Methodsmentioning

confidence: 99%

A One‐Dimensional Particle‐in‐Cell Model of Plasma Build‐Up in Vacuum Arcs

Timkó

Matyash

Schneider

et al. 2011

Contrib. Plasma Phys.

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Understanding the mechanism of plasma build-up in vacuum arcs is essential in many fields of physics. A onedimensional particle-in-cell computer simulation model is presented, which models the plasma developing from a field emitter tip under electrical breakdown conditions, taking into account the relevant physical phenomena. As a starting point, only an external electric field and an initial enhancement factor of the tip are assumed. General requirements for plasma formation have been identified and formulated in terms of the initial local field and a critical neutral density. The dependence of plasma build-up on tip melting current, the evaporation rate of neutrals and external circuit time constant has been investigated for copper and simulations imply that arcing involves melting currents around 0.5 − 1 A/μm 2 , evaporation of neutrals to electron field emission ratios in the regime 0.01 − 0.05, plasma build-up timescales in the order of ∼ 1 − 10 ns and two different regimes depending on initial conditions, one producing an arc plasma, the other one not. Also the influence of the initial field enhancement factor and the external electric field required for ignition has been explored, and results are consistent with the experimentally measured local field value of ∼ 10 GV/m for copper.

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“…The experimental setup to be modelled [11] consists of a rounded rod (anode) and a plane sample (cathode), with a typical gap distance of 20 μm ( Fig. 1(a)).…”

Section: Methodsmentioning

confidence: 99%

A One‐Dimensional Particle‐in‐Cell Model of Plasma Build‐Up in Vacuum Arcs

Timkó

Matyash

Schneider

et al. 2011

Contrib. Plasma Phys.

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“…The field enhancement factor β and the emitting area A can then be found via measurements of the field emission current at multiple field levels E z , by fitting the data to the Fowler-Nordheim equation. Typical measured values for β are in the range 30-60 [23].…”

Section: Experiments To Be Modeledmentioning

confidence: 98%

“…A typical electrode gap distance is 20 μm. With copper electrodes, breakdowns usually occur at an applied voltage of about 4-6 kV [23], or in terms of the surface electric field, around E z = 200-300 MV/m. This is also the typical maximum surface field in the CLIC accelerating cavities [8,24].…”

Section: Experiments To Be Modeledmentioning

confidence: 99%

From Field Emission to Vacuum Arc Ignition: A New Tool for Simulating Copper Vacuum Arcs

Timkó

Sjøbak

Mether

et al. 2015

Contrib. Plasma Phys.

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Understanding plasma initiation in vacuum arc discharges can help to bridge the gap between nano-scale triggering phenomena and the macroscopic surface damage caused by vacuum arcs. We present a new twodimensional particle-in-cell tool to simulate plasma initiation in direct-current (DC) copper vacuum arc discharges starting from a single, strong field emitter at the cathode. Our simulations describe in detail how a sub-micron field emission site can evolve to a macroscopic vacuum arc discharge, and provide a possible explanation for why and how cathode spots can spread on the cathode surface. Furthermore, the model provides us with a prediction for the current and voltage characteristics, as well as for properties of the plasma like densities, fluxes and electric potentials in a simple DC discharge case, which are in agreement with the known experimental values.

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“…A number of analytical models exist to explain the phenomenon of the field ion microscopy [11][12][13], but the gap between experimental observations and the theoretical predictions remains unbridged. It has also been proved that the probability of the vacuum arcs to occur near metal surfaces in ultrahigh vacuum conditions depends on the structural properties of the metals [14]. Thus knowing the actual dynamics of the motion of surface atoms of a certain metal under a high electric field can shed light on the triggering process of vacuum arcs.…”

Section: Introductionmentioning

confidence: 99%

Atomistic modeling of metal surfaces under electric fields: Direct coupling of electric fields to a molecular dynamics algorithm

et al. 2011

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The effect of electric fields on metal surfaces is fairly well studied, resulting in numerous analytical models developed to understand the mechanisms of ionization of surface atoms observed at very high electric fields, as well as the general behavior of a metal surface in this condition. However, the derivation of analytical models does not include explicitly the structural properties of metals, missing the link between the instantaneous effects owing to the applied field and the consequent response observed in the metal surface as a result of an extended application of an electric field. In the present work, we have developed a concurrent electrodynamicmolecular dynamic model for the dynamical simulation of an electric-field effect and subsequent modification of a metal surface in the framework of an atomistic molecular dynamics (MD) approach. The partial charge induced on the surface atoms by the electric field is assessed by applying the classical Gauss law. The electric forces acting on the partially charged surface atoms (Lorentz and Coulomb) are then introduced in the MD algorithm to correct the atomic motion in response to the applied field. The enhancement factor at sharp features on the surface for the electric field and the assessment of atomic charges are discussed. The results obtained by the present model compare well with the experimental and density-functional theory results. Geneva, SwitzerlandFebruary 2011 CLIC -Note -870PHYSICAL REVIEW E 83, 026704 (2011) The effect of electric fields on metal surfaces is fairly well studied, resulting in numerous analytical models developed to understand the mechanisms of ionization of surface atoms observed at very high electric fields, as well as the general behavior of a metal surface in this condition. However, the derivation of analytical models does not include explicitly the structural properties of metals, missing the link between the instantaneous effects owing to the applied field and the consequent response observed in the metal surface as a result of an extended application of an electric field. In the present work, we have developed a concurrent electrodynamicmolecular dynamic model for the dynamical simulation of an electric-field effect and subsequent modification of a metal surface in the framework of an atomistic molecular dynamics (MD) approach. The partial charge induced on the surface atoms by the electric field is assessed by applying the classical Gauss law. The electric forces acting on the partially charged surface atoms (Lorentz and Coulomb) are then introduced in the MD algorithm to correct the atomic motion in response to the applied field. The enhancement factor at sharp features on the surface for the electric field and the assessment of atomic charges are discussed. The results obtained by the present model compare well with the experimental and density-functional theory results.

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dc breakdown conditioning and breakdown rate of metals and metallic alloys under ultrahigh vacuum

Cited by 83 publications

References 18 publications

A One‐Dimensional Particle‐in‐Cell Model of Plasma Build‐Up in Vacuum Arcs

A One‐Dimensional Particle‐in‐Cell Model of Plasma Build‐Up in Vacuum Arcs

From Field Emission to Vacuum Arc Ignition: A New Tool for Simulating Copper Vacuum Arcs

Atomistic modeling of metal surfaces under electric fields: Direct coupling of electric fields to a molecular dynamics algorithm

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