Fe dopant in ZnO: 2+ vs 3+ valency and ion-carrier s,p-d exchange interaction
J. Papierska, A. Ciechan, P. Bogus{\l}awski, M. Boshta, M. M. Gomaa,, E. Chikoidze, Y. Dumont, A. Drabi\'nska, H. Przybyli\'nska, A. Gardias, J., Szczytko, A. Twardowski, M. Tokarczyk, G. Kowalski, B. Witkowski, K. Sawicki,, W. Pacuski, M. Nawrocki, and J. Suffczy\'nski

TL;DR
This study combines theoretical calculations and experimental techniques to clarify the valency of Fe in ZnO, revealing Fe predominantly exists as Fe3+ in doped films and exhibits significant s,p-d exchange interactions.
Contribution
It provides a comprehensive analysis of Fe valency in ZnO, reconciling previous contradictions and demonstrating the presence of Fe3+ ions and their magnetic interactions.
Findings
Fe acts as a shallow donor with Fe2+ as the stable charge state in ideal ZnO.
Fe doping increases n-type conductivity with a donor ionization energy of 0.25 eV.
Magneto-optical measurements confirm s,p-d exchange interactions between carriers and Fe3+ ions.
Abstract
Dopants of transition metal ions in II-VI semiconductors exhibit native 2+ valency. Despite this, 3+ or mixed 3+/2+ valency of iron ions in ZnO was reported previously. Several contradictory mechanisms have been put forward for explanation of this fact so far. Here, we analyze Fe valency in ZnO by complementary theoretical and experimental studies. Our calculations within the generalized gradient approximation (GGA+U) indicate that the Fe ion is a relatively shallow donor. Its stable charge state is Fe2+ in ideal ZnO, however, the high energy of the (+/0) transition level enhances the compensation of Fe2+ to Fe3+ by non-intentional acceptors in real samples. Using several experimental methods like electron paramagnetic resonance, magnetometry, conductivity, excitonic magnetic circular dichroism and magneto-photoluminescence we confirm the 3+ valency of the iron ions in polycrystalline…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
