Stochastic Model of Breakdown Nucleation under Intense Electric Fields

Engelberg, Eliyahu Zvi; Ashkenazy, Yinon; Assaf, Michael

doi:10.1103/physrevlett.120.124801

Cited by 30 publications

(12 citation statements)

References 44 publications

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“…Theoretical and computational studies in recent years have advanced the hypothesis that movement of dislocations is a key part of the microprocess that leads up to breakdown [37][38][39][40][41]. This result supports that hypothesis.…”

Section: Discussionsupporting

confidence: 71%

Vacuum electrical breakdown conditioning study in a parallel plate electrode pulsed dc system

Korsbäck

Djurabekova

Mercadé

et al. 2020

Phys. Rev. Accel. Beams

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Conditioning of a metal structure in a high-voltage system is the progressive development of resistance to vacuum arcing over the operational life of the system. This is, for instance, seen during the initial operation of radio frequency (rf) cavities in particle accelerators. It is a relevant topic for any technology where breakdown limits performance, and where conditioning continues for a significant duration of system runtime. Projected future linear accelerators require structures with accelerating gradients of up to 100 MV/m. Currently, this performance level is only achievable after a multi-month conditioning period. In this work, a pulsed DC system applying voltage pulses over parallel disk electrodes was used to study the conditioning process, with the objective of obtaining insight into its underlying mechanics, and ultimately, to find ways to shorten the conditioning process. Two kinds of copper electrodes were tested: As-prepared machine-turned electrodes ("hard" copper), and electrodes that additionally had been subjected to high temperature treatments ("soft" copper). The conditioning behaviour of the soft electrodes was found to be similar to that of comparably treated accelerating structures, indicating a similar conditioning process. The hard electrodes reached the same ultimate performance as the soft electrodes much faster, with a difference of more than an order of magnitude in the number of applied voltage pulses. Two distinctly different distributions of breakdown locations were observed on the two types of electrodes. Considered together, our results support the crystal structure dislocation theory of breakdown, and suggest that the conditioning of copper in high field systems such as rf accelerating structures is dominated by material hardening.

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Section: Discussionsupporting

confidence: 71%

Vacuum electrical breakdown conditioning study in a parallel plate electrode pulsed dc system

Korsbäck

Djurabekova

Mercadé

et al. 2020

Phys. Rev. Accel. Beams

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“…30 However, the formation process of such protrusions in a metal subject to an electric field has not yet been adequately described theoretically or observed experimentally. 19,25,28,29 Our model, based on mobile dislocation density fluc- tuations (MDDF), 16 complements these previous models by proposing that surface features appear as a result of a critical increase in the mobile dislocation density ρ. According to this model, prior to breakdown, the mobile dislocation density is in a long-lived metastable state, fluctuating around a deterministically stable value ρ * .…”

Section: Introductionmentioning

confidence: 55%

“…9 The probability distribution of such events was measured 10 and shown to match simulations, 11 and mean field theories were developed which were able to reproduce the stress-strain behavior of the micropillars. [12][13][14][15] In a previous study 16 we proposed that stochastic fluctuations of the mobile dislocation density ρ control a critical process in metallic surfaces subjected to an extreme electric field. This critical process leads to plasma formation between electrodes in vacuum, and to subsequent arcing of current between the electrodes, serving as a major failure mechanism in numerous applications.…”

Section: Introductionmentioning

confidence: 99%

Theory of electric field breakdown nucleation due to mobile dislocations

Engelberg

Yashar

Ashkenazy

et al. 2019

Phys. Rev. Accel. Beams

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A model is described, in which electrical breakdown in high-voltage systems is caused by stochastic fluctuations of the mobile dislocation population in the cathode. In this model, the mobile dislocation density normally fluctuates, with a finite probability to undergo a critical transition due to the effects of the external field. It is suggested that once such a transition occurs, the mobile dislocation density will increase deterministically, leading to electrical breakdown. Model parametrization is achieved via microscopic analysis of OFHC Cu cathode samples from the CERN CLIC project, allowing the creation and depletion rates of mobile dislocations to be estimated as a function of the initial physical condition of the material and the applied electric field. We find analytical expressions for the mean breakdown time and quasistationary probability distribution of the mobile dislocation density, and verify these results by using a Gillespie algorithm. A least-squares algorithm is used to fit these results with available experimental data of the dependence of the breakdown rate on the applied strength of the electric field and on temperature. The effects of the variation of some of the assumptions of the physical model are considered, and a number of additional experiments to validate the model are proposed, which include examining the effects of the temperature and pulse length, as well as of a time-dependent electric field, on the breakdown rate. Finally, applications of the model are discussed, including the usage of the quasistatic probability distribution to predict breakdowns, and applying the predictions of the model to improve the conditioning process of the cathode material.

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“…One potential explanation is that the phenomenon may be related to plastic behavior of metal under high fields. In recent years it has been proposed that the movement of glissile dislocations which is a mobile dislocation within the metal, may nucleate breakdowns if they evolve into a surface protrusion [71]. If such dislocations migrate to the surface, then the previously unexposed copper may act as a source for outgassing.…”

Section: B Explainable-aimentioning

confidence: 99%

Explainable Machine Learning for Breakdown Prediction in High Gradient RF Cavities

Obermair¹,

Cartier-Michaud²,

Apollonio³

et al. 2022

Preprint

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Radio Frequency (RF) breakdowns are one of the most prevalent limiting factors in RF cavities for particle accelerators. During a breakdown, field enhancement associated with small deformations on the cavity surface results in electrical arcs. Such arcs lead to beam aborts, reduce machine availability and can cause irreparable damage on the RF cavity surface. In this paper, we propose a machine learning strategy to discover breakdown precursors in CERN's Compact Linear Collider (CLIC) accelerating structures. By interpreting the parameters of the learned models with explainable Artificial Intelligence (AI), we reverse-engineer physical properties for deriving fast, reliable, and simple rule based models. Based on 6 months of historical data and dedicated experiments, our models show fractions of data with high influence on the occurrence of breakdowns. Specifically, it is shown that in many cases a rise of the vacuum pressure is observed before a breakdown is detected with the current interlock sensors.

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Stochastic Model of Breakdown Nucleation under Intense Electric Fields

Cited by 30 publications

References 44 publications

Vacuum electrical breakdown conditioning study in a parallel plate electrode pulsed dc system

Vacuum electrical breakdown conditioning study in a parallel plate electrode pulsed dc system

Theory of electric field breakdown nucleation due to mobile dislocations

Explainable Machine Learning for Breakdown Prediction in High Gradient RF Cavities

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