English

A fitting algorithm for optimizing ion implantation energies and fluences

Materials Science 2021-05-28 v2 Accelerator Physics

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 NN energies, we then optimize a set of NN energy-fluence pairs to match a given target defect density profile. Finally, we find the minimum NN such that the error between the target defect density profile and the defect density profile generated by the NN 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 μ\mum surface layers of 15^{15}N or vacancies (using 4^4He).

Keywords

Cite

@article{arxiv.2103.02525,
  title  = {A fitting algorithm for optimizing ion implantation energies and fluences},
  author = {Pauli Kehayias and Jacob Henshaw and Maziar Saleh Ziabari and Michael Titze and Edward Bielejec and Michael P. Lilly and Andrew M. Mounce},
  journal= {arXiv preprint arXiv:2103.02525},
  year   = {2021}
}

Comments

5 pages, 3 figures

R2 v1 2026-06-23T23:43:08.520Z