Speaker
Description
The concept of Non-Ionizing Energy Loss (NIEL) is used to compare and quantify the damage caused to semiconductor devices in various radiation environments. However, the current NIEL concept has a limitation in predicting the formation rates of cluster and point defects in silicon (Si) crystals for different particles and particle energies. Experimental observations have revealed differences in radiation damage produced by neutrons and protons with the same displacement energies (i.e., damage parameters normalized to NIEL).
In this study, we introduce a wide theoretical framework that aims to distinguish between clusters and defects from first principles. In the first step Geant4 simulations (using standard electromagnetic physics lists) of high-energy particles (neutrons, protons, electrons and gammas) produce Primary Knocked-on atoms (PKA) spectra. In the second step PKA of various energies and Z=1 to Z=15 are used as a SRIM/TRIM input and subsequent Silicon cascades are produced, stored and analyzed in terms of Non-Ionizing-Energy-Loss. From Step 1 and 2 the classical Damage equivalent curve as defined by RD-48 collaboration is reproduced. Third step, crucial for the novel distinction between clusters and isolated defects consists of two possible approaches. The first approach uses OPTICS (Ordering points to identify the clustering structure) algorithm as a tool to differentiate between isolated and clustered fractions of each event, while the alternative approach is a random-walk simulation encompassing molecular dynamics constants relevant for the actual physical defects creation.
The results are compared to the collection of Deep-Level-Transient-Spectroscopy measurements.
This revised approach allows for a more accurate prediction of damage and estimation of clustered and isolated defects for different incident particle energies.
| Type of presentation (in-person/online) | online presentation (zoom) |
|---|---|
| Type of presentation (scientific results or project proposal) | Presentation on scientific results |
