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Abstract Details

April 27-29

Abstract Details

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Abstracts

Author: Arsene Tema Biwole
Requested Type: Consider for Invited
Submitted: 2026-03-26 14:29:52

Co-authors: J. Candy, E. A. Belli, I. Sfiligoi, N. T. Howard, T. Odstrcil, P. Rodriguez-Fernandez

Contact Info:
MIT Plasma Science and Fusion Center
167 Albany St
Cambridge, MA   02139
USA

Abstract Text:
Controlling heavy impurities in burning plasmas is an absolute requirement for future magnetic-confinement fusion reactors, most of which are expected to operate with tungsten as the primary plasma-facing material. Even trace-level tungsten concentrations can radiate strongly, cool the plasma core, and degrade confinement. Understanding tungsten transport is therefore, central to predicting reactor performance under burning-plasma conditions. Using an approximate quasilinear formulation of electrostatic gyrokinetic theory, we derive an analytic expression for trace-impurity turbulent particle transport in the limit of large charge z and mass m. When z and m are large and comparable, the flux decomposes into separate contributions arising from curvature drift, parallel motion, and density-gradient drive. In the more extreme asymptotic limit m >> z^2, finite-Larmor-radius (FLR) effects dominate and the flux obeys a reduced two-term scaling proportional to z/sqrt(m). These asymptotic limits are unified into a compact expression that captures the transition between limits. The theory is validated against nonlinear CGYRO simulations spanning broad ranges of impurity mass, charge state, and density gradient, with excellent agreement across asymptotic limits. The results demonstrate how impurity mass introduces a systematic FLR-mediated suppression of turbulent impurity transport, explaining recent impurity results in fusion devices, including DIII-D. Importantly, for tungsten, this scaling leads to reduced turbulent diffusivity across reactor-relevant charge states, directly affecting accumulation predictions in burning plasmas, and should be accounted for in reactor modeling.

Characterization: 4.0

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