Deterministic Detection of Single Ion Implantation

TL;DR

This work demonstrates that single-ion implantation can be made deterministic across a broad set of ion species and substrate materials by leveraging surface secondary-electron detection with high-bandwidth readout. The authors formalize the implantation-detection relationship with $\nu = -\ln \left( \dfrac{M-p}{M} \right) = \eta \lambda$ and $\lambda = \dfrac{It}{q}$, and implement both linear-regression and direct-peak-counting strategies to quantify $\eta$ in real experiments. They show that detection efficiencies exceed $90\%$ for many ion/substrate combinations, with several cases attaining $100\%$ (e.g., Sb clusters in Si), and identify oxide substrates as particularly favorable. The results support scalable, electrode-free deterministic implantation for solid-state qubits and color centers, enabling large-area, high-precision dopant placement and real-time verification via high-bandwidth SEDs and potential STEM integration. Overall, the approach provides a practical pathway to fabricating large qubit arrays with controlled single-ion occupancy, essential for quantum error correction and scalable quantum technologies.

Abstract

Single ion implantation using focused ion beam systems enables high spatial resolution and maskless doping for rapid and scalable engineering of materials for quantum technologies, particularly qubits and colour centres in solid-state hosts. In such applications, the confidence with which a single ion can be deterministically implanted is crucial, and so the efficiency of the detection mechanism is a vital parameter. Here, we present a study of the single-ion detection efficiency for a variety of ion species (Si, P, Mn, Co, Ge, Sb, Au and Bi) into various hosts (Si, SiO2, Al2O3, GaAs, diamond and SiC). The effect of varying ion mass, charge and kinetic energy are studied, in addition to the cluster implantation of Sb, Au and Bi. We demonstrate that it is possible to achieve detection efficiencies >90% for a wide range of ion species and substrate combination through selection of the implantation parameters. Furthermore, detection efficiencies of 100% are found for the doping of Sb clusters which is of direct relevance for the future fabrication of quantum devices.

Figures (8)

• Figure 1: \ref{['fig:peakCount:combo']} Example SED traces showing single and double ion implantation events within a single pulse. The inset is a highlights the 'detection window' which is the time within which a signal must be detected in order to register as a successful implantation event. \ref{['fig:peakCount:array']} Map of the number of ion implantation events detected at each point within a 50x50 point array during deterministic doping of 50 keV P into silicon.
• Figure 2: Detection efficiency measurements for various ion species into undoped silicon (through a native oxide layer). The anode voltage and charge state of the ions was varied to obtain different implantation energies \ref{['fig:si:energyVar']} and the same implantation energy \ref{['fig:si:chargeVar']}. Hashed bars represent data that was previously reported adshead2025isotopically.
• Figure 3: Detection efficiency measurements for various ion species into SiO$_2$. The anode voltage and charge state of the ions was varied to obtain different implantation energies \ref{['fig:sio2:energyVar']} and the same implantation energy \ref{['fig:sio2:chargeVar']}.
• Figure 4: Detection efficiency measurements for various ion species implanted into Al2O3. The anode voltage and charge state of the ions was varied to obtain different implantation energies \ref{['fig:al2o3:energyVar']} and the same implantation energy \ref{['fig:al2o3:chargeVar']}.
• Figure 5: Detection efficiency measurements for various ion species implanted into GaAs. The anode voltage and charge state of the ions was varied to obtain different implantation energies \ref{['fig:gaas:energyVar']} and the same implantation energy \ref{['fig:gaas:chargeVar']}.