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DOE OSTI2024

Wall heating by subcritical energetic electrons generated by the runaway electron avalanche source *

Abstract Subcritical energetic electrons (SEEs) produced by the runaway electron (RE) avalanche source at energies below the runaway threshold are found to be the primary contributor to surface heating of plasma-facing components (PFCs) during final loss events. This finding is supported by theoretical analysis, computational modeling with the Kinetic Orbit Runaway electrons Code (KORC), and qualitative agreement with DIII-D experimental observations. The avalanche source generates significantly more secondary electrons below the runaway threshold, which thermalize rapidly when well-confined. However, during a final loss event, the RE beam impacts the first wall, and SEEs are deconfined before they can thermalize. Additionally, because the energy deposition length decreases faster than energy, the deposited energy density, and thus the maximum PFC surface temperature change, is larger for SEEs than REs. KORC simulations employ an analytic first wall to model particle deconfinement onto a non-axisymmetric wall composed of individual tiles. PFC surface heating is calculated using a 1D model extended to include an energy-dependent deposition length scale. Simulations of DIII-D qualitatively agree with infrared (IR) imaging only when SEEs from the avalanche source are included. These results demonstrate that SEEs are the dominant contributor to PFC surface heating and indicate that the avalanche source plays a critical role in the PFC damage caused during final loss events. The prominence of SEEs also has important implications for interpreting IR imaging, one of the primary diagnostics for RE-wall interaction diagnosis, despite REs dominating the energy and current density. This result improves predictions of wall damage due to post-disruption REs to estimate material lifetime and design RE mitigation systems for ITER and future reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

A physics-constrained deep learning surrogate model of the runaway electron avalanche growth rate

A surrogate model of the runaway electron avalanche growth rate in a magnetic fusion plasma is developed. This is accomplished by employing a physics-informed neural network (PINN) to learn the parametric solution of the adjoint to the relativistic Fokker–Planck equation. The resulting PINN is able to evaluate the runaway probability function across a broad range of parameters in the absence of any synthetic or experimental data. This surrogate of the adjoint relativistic Fokker–Planck equation is then used to infer the avalanche growth rate as a function of the electric field, synchrotron radiation and effective charge. Predictions of the avalanche PINN are compared against first principle calculations of the avalanche growth rate with excellent agreement observed across a broad range of parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

The impact of collisionality on the runaway electron avalanche during a tokamak disruption

The exponential growth (avalanching) of runaway electrons (REs) during a tokamak disruption continues to be a large uncertainty in RE modeling. The present work investigates the impact of tokamak geometry on the efficiency of the avalanche mechanism across a broad range of disruption scenarios. It is found that the parameter ν *,crit ⁠, describing the collisionality at the critical energy to run away, delineates how toroidal geometry impacts RE formation. In particular, utilizing a reduced but self-consistent description of plasma power balance, it is shown that for a high-density deuterium-dominated plasma, ν *,crit is robustly less than one, resulting in a substantial decrease in the efficiency of the RE avalanche compared to predictions from slab geometry. In contrast, for plasmas containing a substantial quantity of neon or argon, ν *,crit ≳1, no reduction of the avalanche is observed due to toroidal geometry. This sharp contrast in the impact of low- vs high-Z material results primarily from the relatively strong radiative cooling from high-Z impurities, enabling the plasma to be radiatively pinned at low temperatures and thus large electric fields, even for modest quantities of high-Z material.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Machine Learning for Multipactor Susceptibility Prediction in Planar RF Gaps

Multipactor discharge is a nonlinear electron avalanche that limits the performance of high-power radio-frequency (RF) and vacuum electronic devices. Predicting multipactor susceptibility traditionally relies on Monte Carlo or particle-in-cell (PIC) simulations, which become computationally expensive for large parametric studies. In this work, we present a supervised machine-learning (ML) framework for prediction of multipactor susceptibility in a two-surface planar geometry. The models are trained using high-fidelity PIC simulation generated susceptibility data and learn the relationship between operational parameters, geometry, and material-dependent secondary electron emission properties. The proposed approach enables rapid reconstruction of susceptibility charts while preserving the physical structure of multipactor growth regions.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Corrigendum: Simulations of stand-off runaway electron beam termination by tungsten particulates for tokamak disruption mitigation (2024 Nucl. Fusion 64 056019)

In the original article, we inadvertently omitted a reference which previously introduced the concept of tungsten injection for 'Disruption Mitigation in Tokamak Reactor via Reducing the Seed Electrons of Avalanche.' In that reference, the authors have proposed injection of a tungsten cylinder of 80 mm by 8 mm dimensions, by rail guns, to absorb the runaway seed population. This can be contrasted with another interesting idea of using small tungsten pellets coated with a low Z material for depleting the runaway seeds as an option for upgrade of the ITER Disruption Mitigation System. Interested readers are referred to those two papers on the tungsten injection for runaway seed removal/reduction, and the related issue of not shortening the current quench excessively. The application focus of was not on reducing the runaway seeds in the initial Ohmic-to-runaway current conversion phase, but on safe termination of a fully formed and likely decaying runaway beam that is about to scrape off against the first wall, which can be accelerated by vertical displacement events. This scheme thus serves as a last line of defense against potential wall damage. The choice here is locally released tungsten particulates, similar to the previous idea of using tungsten particulates as a dust shield for the divertor. The most significant finding of is that strong pitch angle scattering, in addition to energy attenuation and absorption, of high-energy runaways by tungsten particulates, provides a transport mechanism by which runaways damage of the first wall can be mitigated by reducing and spreading the runaway wall load. We regret the omission in the original article, and thank the authors of the cited article for bringing this matter to our attention. We also find the possibility of using the injected tungsten rod from to terminate the runaways, as opposed to the cloud of tungsten particulates in intriguing. In that context, it is of interest to mention another possibility of a retractable tungsten metal arm that can be swung out for deployment in runaway termination, which would remove the need for post-mitigation recovery of tungsten debris in injection schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Characterization of a SiPM-based monolithic neutron scatter camera using dark counts

The Single Volume Scatter Camera (SVSC) Collaboration aims to develop portable neutron imaging systems for a variety of applications in nuclear non-proliferation. Conventional double-scatter neutron imagers are composed of several separate detector volumes organized in at least two planes. A neutron must scatter in two of these detector volumes for its initial trajectory to be reconstructed. As such, these systems typically have a large footprint and poor geometric efficiency. We report on the design and characterization of a prototype monolithic neutron scatter camera that is intended to significantly improve upon the geometrical shortcomings of conventional neutron cameras. The detector consists of a 50 mm×56 mm× 60 mm monolithic block of EJ-204 plastic scintillator instrumented on two faces with arrays of 64 Hamamatsu S13360-6075PE silicon photomultipliers (SiPMs). The electronic crosstalk is limited to < 5% between adjacent channels and < 0.1% between all other channel pairs. SiPMs introduce a significantly elevated dark count rate over PMTs, as well as correlated noise from after-pulsing and optical crosstalk. In this article, we characterize the dark count rate and optical crosstalk and present a modified event reconstruction likelihood function that accounts for them. We find that the average dark count rate per SiPM is 4.3 MHz with a standard deviation of 1.5 MHz among devices. The analysis method we employ to measure internal optical crosstalk also naturally yields the mean and width of the single-electron pulse height. Here, we calculate separate contributions to the width of the single-electron pulse-height from electronic noise and avalanche fluctuations. We demonstrate a timing resolution for a single-photon pulse to be (128 ± 4) ps. Finally, coincidence analysis is employed to measure external (pixel-to-pixel) optical crosstalk. We present a map of the average external crosstalk probability between 2×4 groups of SiPMs, as well as the in-situ timing characteristics extracted from the coincidence analysis. Further work is needed to characterize the performance of the camera at reconstructing single- and double-site interactions, as well as image reconstruction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Simulation of DIII-D disruption with argon pellet injection and runaway electron beam

Abstract The next generation of large tokamaks, including ITER, will be equipped with a disruption mitigation system (DMS) that can be activated if a disruption is deemed to be imminent. Introducing impurities by pellet (large or shattered) or massive gas injection has been shown to be an effective mitigation mechanism on many tokamaks. The goal of the mitigation is to lessen the thermal and electromagnetic loads from the disruption without generating enough high-energy (runaway) electrons to damage the device. Variations of this mitigation process with impurity injection are presently being tested on many experiments. We have modeled one such impurity injection experiment on DIII-D using the M3D-C1 nonlinear 3D extended MHD code (Jardin et al 2012 Comput. Sci. Discovery 6 014002), The model includes an argon large pellet injection and ablation model, impurity ionization, recombination, and radiation, and runaway electron formation and subsequent evolution, including both Dreicer and avalanche sources. We obtain reasonable agreement with the experimental results for the timescale of the thermal and current quench and for the magnitude of the runaway electron plateau formed during the mitigation. This is the first 3D full MHD simulation with pellets and REs to simulate the disruption process and it also provides a partial validation of the M3D-C1 DMS model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Undulator radiation of single electrons: coherence length and quantum-optical properties

The aims of the CLARA experiment at the Fermilab Integrable Optics Test Accelerator (IOTA) were to directly measure the coherence length of undulator radiation emitted by a single electron and to test whether the radiation is in a pure classical Glauber coherent state or in a quantum mixture of coherent and Fock states. We used a Mach-Zehnder interferometer (MZI) to study visible radiation generated by 150-MeV electrons circulating in the ring. The relative delay between the two arms of the MZI was adjusted by varying the length of one of them with a resolution of 10 nm. The intensity of the circulating beam spanned several orders of magnitude, down to single electrons. A pair of single-photon avalanche diodes (SPADs) was placed at the output of the MZI arms to detect photocounts with high efficiency and timing resolution. We describe the observed interference patterns and photocount rates as a function of interferometer delay and discuss their implications.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Undulator Radiation of Single Electrons: Coherence Length and Quantum-Optical Properties

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

AC-LGADs Fermilab front-end electronics characterization

Here, we characterized the front-end electronics used to process high-frequency signals from low-gain avalanche diodes (LGADs) at the Fermilab Test Beam Facility. LGADs are silicon detectors employed for charged particle tracking, offering exceptional spatial and temporal resolution. The purpose of this characterization was to understand how the time resolution is influenced by the front-end electronics. To achieve this, we developed a setup capable of generating input signals with varying amplitudes. The output results demonstrated that signal processing by the front-end electronics plays a crucial role in enhancing time resolution. We showed that the time resolution achieved by the FEE board is better than 2 p s at the 1 σ level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Time projection chamber for GADGET II

The established Gaseous Detector with Germanium Tagging (GADGET) detection system is used to measure weak, low-energy 𝛽-delayed proton decays. It consists of the Gaseous Proton Detector equipped with a MICROMEGAS (MM) readout to detect protons and other charged particles calorimetrically, surrounded by the Segmented Germanium Array (SeGA) for high-resolution detection of prompt 𝛾 rays. To upgrade GADGET's Proton Detector to operate as a compact time projection chamber (TPC) for the detection, three-dimensional imaging and identification of low-energy 𝛽-delayed single- and multiparticle emissions mainly of interest to astrophysical studies. A new high granularity MM board with 1024 pads has been designed, fabricated, installed, and tested. A high-density data acquisition system based on generic electronics for TPCs (GET) has been installed and optimized to record and process the gas avalanche signals collected on the readout pads. The TPC's performance has been tested using a 220 Rn 𝛼-particle source and cosmic-ray muons. In addition, decay events in the TPC have been simulated by adapting the attpcroot data analysis framework. Furthermore, a novel application of two-dimensional convolutional neural networks for GADGET II event classification is introduced. The optimization of data throughput is also addressed. The GADGET II TPC is capable of detecting and identifying 𝛼 particles as well as measuring their track direction, range, and energy. The extracted energy resolution of the GADGET II TPC using P10 gas is about 5.4% at 6.288 MeV ( 220 Rn 𝛼 events), computed using charge integration. Based on a systematic simulation study, we estimated the detection efficiency of the GADGET II TPC for protons and 𝛼 particles, respectively. It has also been demonstrated that the GADGET II TPC is capable of tracking minimum-ionizing particles (i.e., cosmic-ray muons). From these measurements, the electron drift velocity was measured under typical operating conditions. In addition to being one of the first generation of micropattern gaseous detectors (MPGDs) to utilize a resistive anode applied to low-energy nuclear physics, the GADGET II TPC will also be the first TPC surrounded by a high-efficiency array of high-purity germanium 𝛾-ray detectors. As a result, the TPC of GADGET II has been designed, fabricated, and tested and is ready for operation at the Facility for Rare Isotope Beams for radioactive-beam-line experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

An efficient surrogate model of secondary electron formation and evolution

This work extends the adjoint-deep learning framework for runaway electron (RE) evolution, developed by McDevitt et al. [Phys. Plasmas 32, 042503 (2025)], to account for large-angle collisions. By incorporating large-angle collisions, the framework allows the avalanche of REs to be captured, an essential component of RE dynamics. This extension is accomplished by using a Rosenbluth–Putvinski approximation to estimate the distribution of secondary electrons generated by large-angle collisions. By evolving both the primary and multiple generations of secondary electrons, the present formulation can capture both the detailed temporal evolution of a RE population beginning from an arbitrary initial momentum space distribution, along with providing approximations to the saturated growth and decay rates of the RE population. Predictions of the adjoint-deep learning framework are verified against a traditional RE solver, with good agreement present across a broad range of parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Testing strong-field QED with the avalanche precursor

A two-beam high-power laser facility is essential for the study of one of the most captivating phenomena predicted by strong-field quantum electrodynamics (QED) and yet unobserved experimentally: the avalanche-type cascade. In such a cascade, the energy of intense laser light can be efficiently transformed into high-energy radiation and electron–positron pairs. The future 50-petawatt-scale laser facility NSF OPAL will provide unique opportunities for studying such strong-field QED effects, as it is designed to deliver two ultra-intense, tightly focused laser pulses onto the interaction point. In this work, we investigate the potential of such a facility for studying elementary particle and plasma dynamics deeply in the quantum radiation-dominated (RD) regime, and the generation of QED avalanches. With three-dimensional particle-in-cell simulations, we demonstrate that QED avalanche precursors can be reliably triggered under realistic laser parameters and layout (namely, focusing f/2, tilted optical axes, and non-ideal co-pointing) with the anticipated capabilities of NSF OPAL. We demonstrate that seed electrons can be efficiently injected into the laser focus by using targets of three types: a gas of heavy atoms, an overcritical plasma, and a thin foil. A strong positron and high-energy photon signal is generated in all cases. The cascade properties can be identified from the final particle distributions, which have a clear directional pattern. At increasing laser field intensity, such distributions provide signatures of the transition, first, to the RD interaction regime, and then to a QED avalanche. Our findings can also be used for designing related future experiments.

Lasers↗

DOE OSTI2025

Gain characterization of LGAD sensors with beta particles and 28-MeV protons

Low Gain Avalanche Diodes, also known as LGADs, are widely considered for fast-timing applications in high energy physics, nuclear physics, space science, medical imaging, and precision measurements of rare processes. Such devices are silicon-based and feature an intrinsic gain due to a p + -doped layer that allows the production of a controlled avalanche of carriers, with multiplication on the order of 10–100. This technology can provide time resolution on the order of 20–30 ps, and variants of this technology can provide precision tracking too. The characterization of LGAD performance has so far primarily been focused on the interaction of minimum ionizing particles for high energy and nuclear physics applications. This article expands the study of LGAD performance to highly-ionizing particles, such as 28-MeV protons, which are relevant for several future scientific applications, e.g. in biology and medical physics, among others. These studies were performed with a beam of 28-MeV protons from a tandem Van de Graaff accelerator at Brookhaven National Laboratory and beta particles from a ^90Sr source; these were used to characterize the response and the gain of an LGAD as a function of bias voltage and collected charge. Here, the experimental results are also compared to TCAD simulations.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Fast photodiode arrays for high frequency fluctuation measurements of reconnecting flux ropes

An array of compact, high-bandwidth (>200 MHz) and low-cost optical photodiodes has been developed and implemented on the PHASe MApping (PHASMA) experiment. Using purpose-built electronics, an array of 16 photodetectors was constructed and used to monitor broadband (1–5 MHz) fluctuations in light intensity emitted by flux ropes undergoing electron-only magnetic reconnection. These measurements reveal a swath of oscillatory behavior, including wave propagation inward toward the diffusion region at approximately the local electron Alfvén speed. Custom 3D-printed collection optics and mounting hardware allow quick reconfiguration of the array for radial or axial measurements. The electronics design is flexible enough to be used with other current-sourcing transducers, such as avalanche photodiodes; silicon photomultipliers; and infrared, x-ray, and UV photodiodes. A noise-rejecting electrical layout allows for low-noise operation close to pulsed plasma discharges. A 16-channel, 64-pixel tomographic array was constructed and initial reconstructions are presented.

Instruments & Instrumentation↗

DOE OSTI2025

Robust Avalanche (1.5 kV, 2 kA/cm²) in Vertical GaN Diodes on Patterned Sapphire Substrate

The lack of avalanche capability is a key limitation of current lateral GaN devices. Despite the report of avalanche in vertical GaN-on-GaN devices, the high wafer cost hinders device commercialization. Here, in this work, we demonstrate a circuit-level avalanche in vertical GaN diodes on low-cost patterned sapphire substrate (PSS), with the avalanche voltage (1.57 kV) and avalanche current density (>2 kA/cm 2 ) both being the highest reported in GaN devices on foreign substrates. The PSS enables a lower dislocation density than conventional sapphire substrate and is employed in high-voltage GaN devices for the first time. The avalanche voltage in the circuit test reaches 98% of the parallel-plane limit, further affirming that near-ideal avalanche breakdown can be realized on GaN devices on foreign substrates. These results show the promise of the GaN-on-PSS platform for low-cost, robust power devices.

42 ENGINEERING↗