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Research area 03

Multiphysics Simulation

Connecting particle transport, energy deposition, electrostatics and transient charge collection.

  • TCAD
  • FLUKA
  • SRIM

Why a multiphysics approach?

A radiation detector cannot be understood from a single simulation alone. Particle transport determines where energy is deposited. Semiconductor electrostatics determines the internal field. Carrier transport determines how generated charge moves. The external circuit observes the current induced by that motion.

  1. Define the material stack and detector geometry
  2. Simulate radiation interaction and secondary-particle transport
  3. Convert energy deposition into spatial carrier generation
  4. Solve semiconductor electrostatics and transport
  5. Calculate transient current, collected charge and timing
  6. Compare designs using physically meaningful metrics

Particle transport and energy deposition

FLUKA is used to study radiation transport, nuclear interactions and reaction-product trajectories in complex detector geometries. SRIM/TRIM provides complementary insight into the range, stopping and energy-loss behaviour of ions in materials.

Semiconductor-device simulation

TCAD is used to solve electrostatics and charge-transport equations in the detector structure.

  • Electric-field, depletion and space-charge distributions
  • Leakage current and breakdown behaviour
  • Radiation-induced carrier generation
  • Transient current and charge collection
  • Influence of contacts, interfaces, traps and recombination models

Linking the models

The crucial step is the interface between simulation domains. Energy-deposition information must be translated into a carrier-generation model with consistent geometry, coordinates, units and time scales.

  • Explicit coordinate and incidence conventions
  • Consistent material definitions and dimensions
  • Careful normalization of fluence, energy and current
  • Documented assumptions when transferring data between tools
  • Validation against limiting cases, analytical expectations or published evidence

Reproducibility

Python-based analysis is used to clean simulation outputs, calculate metrics and generate comparison plots. Public notes identify the assumptions, boundary conditions and processing steps needed to reproduce the interpretation whenever possible.

Simulation is most useful when every curve can be traced back to a physical assumption.