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arxiv: 2605.02478 · v1 · submitted 2026-05-04 · ❄️ cond-mat.stat-mech · physics.app-ph

Recognition: 3 theorem links

· Lean Theorem

Stochastic first-passage modeling of single-event burnout in SiC power MOSFETs

Feiyi Liu, Min Guo, Mingyang Liu, Shiyang Chen, Yang Wang, Yuhan Jiang

Pith reviewed 2026-05-08 18:10 UTC · model grok-4.3

classification ❄️ cond-mat.stat-mech physics.app-ph
keywords stochastic modelingfirst-passage timesingle-event burnoutSiC MOSFETelectrothermal feedbackprobabilistic failureavalanche multiplicationthermal relaxation
0
0 comments X

The pith

Finite fluctuations broaden the deterministic burnout threshold in SiC power MOSFETs into a probabilistic transition band.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces a stochastic first-passage model for single-event burnout in silicon carbide power MOSFETs. It shows that random variations in carrier generation and heat spread turn the usual sharp recovery-versus-runaway boundary into a region of uncertain outcomes. Some strikes can still trigger failure even when average conditions point to recovery, because rare noise-driven paths allow the system to cross into runaway. The model computes distributions of failure times and survival probabilities to separate fast feedback-driven events from slower stochastic ones. A phase diagram then organizes the conditions into recoverable, transitional, and rapidly unstable regimes.

Core claim

The central claim is that finite fluctuations in a reduced electrothermal feedback-relaxation model with stochastic carrier and thermal terms broaden the deterministic burnout threshold into a probabilistic transition band. Noise-induced subthreshold runaway appears, so that nominally recoverable conditions can still produce failure through rare stochastic excursions. First-passage-time distributions resolve the time scale of burnout while survival probabilities distinguish rapid feedback-dominated runaway from delayed stochastic failure. A feedback-relaxation phase diagram organizes the recoverable, probabilistic, and rapidly unstable regimes.

What carries the argument

A reduced electrothermal feedback-relaxation model with an absorbing boundary and stochastic terms for unresolved carrier and thermal variability.

If this is right

  • Burnout occurs with finite probability under conditions previously viewed as safe.
  • First-passage time distributions give the characteristic time scales for both rapid and delayed failures.
  • Survival probabilities quantify the likelihood of avoiding runaway.
  • The phase diagram maps boundaries between recoverable, transitional, and unstable operating regimes.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar stochastic broadening may appear in avalanche or thermal runaway processes in other semiconductor devices.
  • Device design could target reduced fluctuation amplitudes to shrink the width of the probabilistic failure band.
  • Systematic measurements of failure rates versus strike energy near threshold could map the band width directly.

Load-bearing premise

The reduced electrothermal feedback-relaxation model with its chosen stochastic carrier and thermal terms is sufficient to capture the essential variability near the burnout boundary.

What would settle it

A high-statistics single-event test that finds zero burnout probability below the deterministic threshold and an abrupt step in failure rate would contradict the predicted probabilistic band and noise-induced subthreshold runaway.

Figures

Figures reproduced from arXiv: 2605.02478 by Feiyi Liu, Min Guo, Mingyang Liu, Shiyang Chen, Yang Wang, Yuhan Jiang.

Figure 1
Figure 1. Figure 1: Source and field overlap defining the coarse-grained sensitive region view at source ↗
Figure 2
Figure 2. Figure 2: Reduced electrothermal framework. The upper solid-line part represents the de view at source ↗
Figure 3
Figure 3. Figure 3: Deterministic reference trajectories of the reduced electrothermal model. (a) view at source ↗
Figure 4
Figure 4. Figure 4: Stochastic broadening of the burnout transition. (a) Stochastic temperature view at source ↗
Figure 5
Figure 5. Figure 5: Noise-induced subthreshold electrothermal runaway. (a) Stochastic temperature view at source ↗
Figure 6
Figure 6. Figure 6: First-passage-time statistics of stochastic electrothermal runaway. (a) Distribu view at source ↗
Figure 7
Figure 7. Figure 7: Feedback–relaxation phase diagram. The color map shows view at source ↗
Figure 8
Figure 8. Figure 8: Coarse-grained mapping from SiC power-device SEB physics to the reduced view at source ↗
Figure 9
Figure 9. Figure 9: Numerical convergence of the burnout probability curve under time-step and view at source ↗
read the original abstract

Single-event burnout (SEB) in silicon carbide (SiC) power MOSFETs is often characterized by deterministic threshold quantities. Near the boundary between recovery and runaway, stochastic variability can make this threshold description probabilistic rather than sharp. This work introduces a first-passage perspective for stochastic threshold broadening in burnout. The process is described by a reduced electrothermal feedback-relaxation model with an absorbing boundary. The model combines carrier multiplication, avalanche feedback, localized heating, carrier loss, and thermal relaxation. Stochastic carrier and thermal terms represent unresolved event-level variability. The main finding is that finite fluctuations broaden the deterministic burnout threshold into a probabilistic transition band. Noise-induced subthreshold runaway also emerges, where nominally recoverable conditions can still fail through rare stochastic excursions. First-passage-time distributions resolve the time scale of burnout and survival probabilities further distinguish rapid feedback-dominated runaway from delayed stochastic failure. A feedback-relaxation phase diagram organizes recoverable, probabilistic, and rapidly unstable regimes. This framework provides a statistical-physics interpretation of threshold dispersion in single-event burnout of SiC power MOSFETs by linking coarse-grained electrothermal dynamics to probabilistic and time-resolved failure observables.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. The paper introduces a reduced electrothermal feedback-relaxation model augmented with stochastic carrier and thermal noise terms and an absorbing boundary to analyze single-event burnout (SEB) in SiC power MOSFETs via first-passage statistics. It claims that finite fluctuations convert the deterministic burnout threshold into a probabilistic transition band, that noise-induced subthreshold runaway occurs under nominally recoverable conditions, and that first-passage-time distributions and survival probabilities distinguish rapid feedback-driven failure from delayed stochastic events; a feedback-relaxation phase diagram organizes the regimes.

Significance. If the central construction holds, the work supplies a statistical-physics framework that links coarse-grained electrothermal dynamics to probabilistic failure observables and time scales. This perspective on threshold dispersion is potentially useful for reliability modeling of power devices, where deterministic thresholds are known to be insufficient near the recovery-runaway boundary. The explicit framing as an illustrative coarse-grained model rather than a quantitative predictor is appropriate and strengthens the contribution.

minor comments (3)
  1. [§2] The abstract and introduction refer to 'stochastic carrier and thermal terms' and 'first-passage-time distributions' without specifying the precise form of the noise (additive vs. multiplicative, white vs. colored) or the exact definition of the absorbing boundary; these should be stated explicitly in §2 or §3 with the governing SDEs.
  2. [Figures 3-5] Figure captions and axis labels for the phase diagram and survival-probability plots should include the precise parameter values or ranges used (e.g., noise amplitudes, feedback rates) so that the plotted regimes can be reproduced from the text alone.
  3. [§3] A brief statement on the numerical method used to integrate the stochastic equations and to compute first-passage times (e.g., Euler-Maruyama with fixed step or adaptive scheme) would improve reproducibility.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive and constructive assessment of our manuscript. We are pleased that the statistical-physics framing, the broadening of the burnout threshold into a probabilistic band, and the utility for reliability modeling near the recovery-runaway boundary are viewed favorably. The recommendation for minor revision is appreciated, and we will incorporate any editorial or minor clarifications in the revised version.

Circularity Check

0 steps flagged

No significant circularity; derivation self-contained from model definition

full rationale

The paper constructs a reduced electrothermal feedback-relaxation model by combining explicit physical processes (carrier multiplication, avalanche feedback, localized heating, carrier loss, thermal relaxation) plus added stochastic carrier and thermal noise terms, then applies first-passage analysis with an absorbing boundary to obtain emergent observables such as broadened probabilistic thresholds, first-passage-time distributions, survival probabilities, and a feedback-relaxation phase diagram. These outputs are consequences of the stochastic dynamics rather than inputs, with no evidence of fitted parameters renamed as predictions, self-definitional loops, or load-bearing self-citations that reduce the central claim to its own assumptions. The modeling is explicitly coarse-grained to illustrate statistical-physics effects, keeping the chain independent of the target failure statistics.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The model rests on a reduced set of electrothermal equations whose precise form, stochastic noise spectrum, and boundary conditions are not supplied in the abstract. Several free parameters are expected for carrier multiplication, thermal relaxation rates, and noise amplitudes.

free parameters (2)
  • stochastic carrier and thermal noise amplitudes
    Abstract states that stochastic terms represent unresolved event-level variability; their strength must be chosen or fitted.
  • electrothermal feedback and relaxation rates
    The reduced model combines carrier multiplication, avalanche feedback, localized heating, carrier loss, and thermal relaxation; these coefficients are not derived from first principles in the abstract.
axioms (1)
  • domain assumption The reduced electrothermal feedback-relaxation model with absorbing boundary captures the essential dynamics near the burnout threshold.
    Abstract presents this reduced model as the basis for all subsequent probabilistic results.

pith-pipeline@v0.9.0 · 5514 in / 1345 out tokens · 30992 ms · 2026-05-08T18:10:07.369860+00:00 · methodology

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