A fitting algorithm for optimizing ion implantation energies and fluences

TL;DR

This paper presents an automated method to generate optimal ion implantation recipes, minimizing energies needed to achieve desired defect profiles in solids, with applications in quantum sensing using nitrogen-vacancy centers.

Contribution

The authors introduce a novel algorithm that automatically optimizes ion energies and fluences to produce target defect profiles efficiently, reducing the number of energies required.

Findings

Successfully optimized ion implantation recipes for specific defect profiles.

Achieved uniform 1 μm surface layers of nitrogen or vacancies.

Reduced the number of energies needed for precise defect control.

Abstract

We describe a method to automatically generate an ion implantation recipe, a set of energies and fluences, to produce a desired defect density profile in a solid using the fewest required energies. We simulate defect density profiles for a range of ion energies, fit them with an appropriate function, and interpolate to yield defect density profiles at arbitrary ion energies. Given $N$ energies, we then optimize a set of $N$ energy-fluence pairs to match a given target defect density profile. Finally, we find the minimum $N$ such that the error between the target defect density profile and the defect density profile generated by the $N$ energy-fluence pairs is less than a given threshold. Inspired by quantum sensing applications with nitrogen-vacancy centers in diamond, we apply our technique to calculate optimal ion implantation recipes to create uniform-density 1 $\mu$m surface layers of $^{15}$N or vacancies (using $^4$He).