Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing technologies. The proposal to use nuclear and electronic spins of donor atoms in silicon, introduced by Kane in 1998, sparked a new research field focused on the precise positioning of individual impurity atoms for quantum devices, utilising scanning tunnelling microscopy and ion implantation. This roadmap article reviews the advancements in the 25 years since Kane’s proposal, the current challenges, and the future directions in atomic-scale semiconductor device fabrication and measurement. It covers the quest to create a silicon-based quantum computer and expands to include diverse material systems and fabrication techniques, highlighting the potential for a broad range of semiconductor quantum technological applications. Key developments include phosphorus in silicon devices such as single-atom transistors, arrayed few-donor devices, one- and two-qubit gates, three-dimensional architectures, and the development of a toolbox for future quantum integrated circuits. The roadmap also explores new impurity species like arsenic and antimony for enhanced scalability and higher-dimensional spin systems, new chemistry for dopant precursors and lithographic resists, and the potential for germanium-based devices. Emerging methods, such as photon-based lithography and electron beam manipulation, are discussed for their disruptive potential. This roadmap charts the path toward scalable quantum computing and advanced semiconductor quantum technologies, emphasising the critical intersections of experiment, technological development, and theory.

We investigate the different transport mechanisms that can occur in pn junction devices made using atomic precision advanced manufacturing at temperatures ranging from cryogenic to room temperature. We first elucidate the potential cause of the anomalous behavior observed in the forward-bias response of these devices in recent cryogenic temperature measurements, which deviates from the theoretical response of a silicon Esaki diode. These anomalous behaviors include current suppression at low voltages in the forward-bias response and a much lower valley voltage at cryogenic temperatures than theoretically expected for a silicon diode. To investigate the potential causes of these anomalies, we studied the effects of a few possible transport mechanisms, including band-to-band tunneling, bandgap narrowing, potential impact of non-Ohmic contacts, band quantization, impact of leakage, and inelastic trap-assisted tunneling, through semi-classical simulations. We find that a combination of two sets of band-to-band tunneling (BTBT) parameters can qualitatively approximate the shape of the tunneling current at low bias. This can arise from band quantization and realignment due to the strong potential confinement in δ-layers. We also find that the lower-than-theoretically-expected valley voltage can be attributed to modifications in the electronic band structure within the δ-layer regions, leading to a significant bandgap narrowing induced by the high density of dopants. Finally, we extend our analyses to room temperature operation and predict that trap-assisted tunneling (TAT) facilitated by phonon interactions may become significant, leading to a complex superposition of BTBT and TAT transport mechanisms in the electrical measurements.

Hydrogen Depassivation Lithography has become established as the method for atomic-precision patterning for 2D dopant-based devices, such as qubits and analog quantum simulators. Research thus far in this area has mostly been focused on patterning of n-type dopants, such as P and As. In this work, we describe the process for fabrication of bipolar dopant-based devices, such as p-n junctions and n-p-n bipolar junction transistors, which may have a number of advantages such as improved gain-bandwidth product and low-noise operation. The P-doped parts of the device are created first, and the B-doped parts are created subsequently, requiring atomically-precise alignment to the P-doped parts. To achieve the necessary patterning precision, we have developed various advances to conventional STMs, including corrections for piezo creep and hysteresis, automatic lattice alignment, and spectroscopic imaging methods to give strong contrast of surface and buried dopants. The overall process described here has become known as Atomically Precise Advanced Manufacturing (APAM), which offers far better patterning precision than conventional techniques such as e-beam lithography.

Limited throughput is a shortcoming of the Scanning Tunneling Microscope (STM), particularly when used for atomically precise lithography. To address this issue, we have developed an on-chip STM based on Microelectromechanical-Systems (MEMS) technology. The device reported here has one degree of freedom, replacing the Z axis in a conventional STM. The small footprint of the on-chip STM provides a great opportunity to increase STM throughput by incorporating a number of on-chip STMs in an array to realize parallel STM. The tip methodology adopted for the on-chip STM presented here, which is a batch-fabricated Si tip, makes our design conducive to this goal. In this work, we investigate the capability of this on-chip STM with an integrated Si tip for STM imaging. We integrate the on-chip STM into a commercial ultrahigh-vacuum STM system and perform imaging with atomic resolution on par with conventional STMs but at higher scan speeds due to the higher sensitivity of the MEMS actuator relative to a piezotube. The results attest that it is possible to achieve a parallel and high-throughput STM platform, which is a fully batch-fabricated MEMS STM nanopositioner capable of performing atomic-resolution STM imaging.

Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with applications ranging from theory and materials prediction to high-throughput data analysis. In parallel, the recent successes in applying ML/AI methods for autonomous systems from robotics through self-driving cars to organic and inorganic synthesis are generating enthusiasm for the potential of these techniques to enable automated and autonomous experiment in imaging. In this article, we discuss recent progress in application of machine learning methods in scanning transmission electron microscopy and scanning probe microscopy, from applications such as data compression and exploratory data analysis to physics learning to atomic fabrication.

In this work, atomic-resolution lithography with a Microelectromechanical-System (MEMS) based Scanning Tunneling Microscope (STM) is demonstrated for the first time. The microscope consists of a commercial UltraHigh-Vacuum (UHV) STM whose regular tip is replaced with a 1-Degree-of-Freedom (1-DOF) MEMS nanopositioner. This results in a hybrid STM system where XY-plane motions are provided by the piezotube of the original system and Z-axis motion by the MEMS with a higher bandwidth. Sharp tips made of Pt or W are added to the MEMS devices with postfabrication techniques. With this hybrid system, STM-based lithography is demonstrated on an H-passivated Si (100)-2×1 sample under UHV condition. Results prove the capability of the hybrid STM system for atomic-scale lithography. This capability, paired with the small footprint of the MEMS device, makes this approach a candidate for building a high-throughput parallel STM lithography platform by incorporating an array of 1-DOF MEMS devices that perform lithography in parallel.

Atomically precise ultradoping of silicon is possible with atomic resists, area-selective surface chemistry, and a limited set of hydride and halide precursor molecules, in a process known as atomic precision advanced manufacturing (APAM). It is desirable to expand this set of precursors to include dopants with organic functional groups and here we consider aluminium alkyls, to expand the applicability of APAM. We explore the impurity content and selectivity that results from using trimethyl aluminium and triethyl aluminium precursors on Si(001) to ultradope with aluminium through a hydrogen mask. Comparison of the methylated and ethylated precursors helps us understand the impact of hydrocarbon ligand selection on incorporation surface chemistry. Combining scanning tunneling microscopy and density functional theory calculations, we assess the limitations of both classes of precursor and extract general principles relevant to each.

A materials synthesis method that we call atomic-precision advanced manufacturing (APAM), which is the only known route to tailor silicon nanoelectronics with full 3D atomic precision, is making an impact as a powerful prototyping tool for quantum computing. Quantum computing schemes using atomic (31P) spin qubits are compelling for future scale-up owing to long dephasing times, one- and two-qubit gates nearing high-fidelity thresholds for fault-tolerant quantum error correction, and emerging routes to manufacturing via proven Si foundry techniques. Multiqubit devices are challenging to fabricate by conventional means owing to tight interqubit pitches forced by short-range spin interactions, and APAM offers the required (Å-scale) precision to systematically investigate solutions. However, applying APAM to fabricate circuitry with increasing numbers of qubits will require significant technique development. Here, we provide a tutorial on APAM techniques and materials and highlight its impacts in quantum computing research. Finally, we describe challenges on the path to multiqubit architectures and opportunities for APAM technique development.

A scanning tunneling microscope (STM) combines unique capabilities in imaging and spectroscopy with atomic precision, and it can obtain energy-resolved spectroscopic data with atomic resolution. In this paper, we utilize a recently proposed modification to the STM feedback control loop to acquire high quality d2I/dV2 images. We have developed a constant differential conductance imaging method by closing the STM feedback loop with a high precision dI/dV measurement. In this mode, the tip’s vertical position is adjusted so as to keep the differential conductance constant during raster scanning of the surface. Based on this imaging mode, we propose a new technique to acquire fast and reliable scanning tunneling spectroscopy (STS) data simultaneously with the imaging.

The scanning tunneling microscope (STM) has enabled manipulation and interrogation of surfaces with atomic-scale resolution. Electronic information about a surface is obtained by combining the imaging capability of the STM with scanning tunneling spectroscopy, i.e., measurement of current-voltage (I/V) characteristics of the surface. We propose a change in the STM feedback loop that enables capturing a higher quality dI/dV image. A high frequency dither voltage is added to the bias voltage of the sample, and the fundamental frequency component of the resulting current is demodulated. The in-phase component of this signal is then plotted along with the X and Y position data, constructing the dI/dV image. We show that by incorporating notch filters in the STM feedback loop, we may utilize a high-amplitude dither voltage to significantly improve the quality of the obtained dI/dV image.

A fundamental understanding and advancement of nanopatterning and nanometrology are essential in the future development of nanotechnology, atomic scale manipulation, and quantum technology industries. Scanning probe-based patterning/imaging techniques have been attractive for many research groups to conduct their research in nanoscale device fabrication and nanotechnology mainly due to its cost-effective process; however, the current tip materials in these techniques suffer from poor durability, limited resolution, and relatively high fabrication costs. Here, we report on employing GaN nanowires as a robust semiconductor material in scanning probe lithography (SPL) and microscopy (SPM) with a relatively low-cost fabrication process and the capability to provide sub-10 nm lithography and atomic scale (<1 nm) patterning resolution in field-emission scanning probe lithography (FE-SPL) and scanning tunneling microscopy (STM), respectively. We demonstrate that GaN NWs are great candidates for advanced SPL and imaging that can provide atomic resolution imaging and sub-10 nm nanopatterning on different materials in both vacuum and ambient operations.

In this article, we replace the Z axis of the piezotube of a conventional Ultrahigh-Vacuum (UHV) Scanning Tunneling Microscope (STM) with a one-degree-of-freedom Microelectromechanical-System (MEMS) nanopositioner. As a result, a hybrid system is realized in which motions in the XY plane are carried out by the piezotube, while the MEMS device performs the Z-axis positioning with a smaller footprint and higher sensitivity. With the proposed system and a feedback loop, STM imaging is conducted on an H-passivated Si (100)-2×1 sample in a UHV condition, demonstrating that this on-chip STM is conducive to atomic precision scanning tunneling microscopy.

Current lithographic techniques are limited to a resolution of a few nm with poor relative precision. Scanning Tunneling Microscope (STM) based lithography[1], removes H from H-passivated Si 2x1 (100) by a mode distinct from usual imaging. This technique is generally called Hydrogen Depassivation Lithography (HDL) and since it scans a beam of electrons around on a surface exposing a resist, it is a form of E-beam Lithography. The HDL approach is not effective with standard resists and, at present, has only a limited number of pattern transfer methods. The two primary ones are patterning 2D delta doped Si devices for solid state quantum devices and selective Atomic Layer Deposition metal oxides that can be used as hard etch masks. However, electron stimulated desorption of atoms and molecules is a fairly generic process and its use can be anticipated on a wide variety of substrates. Sub-nm resolution (0.768 nm) has been demonstrated and used for numerous research purposes, such as dopant positioning for quantum devices[2]. While sub-nm resolution is easily obtainable with standard Ultra-High Vacuum (UHV) STMs, the repeatability and accuracy of the patterning has limited its applications. In this paper we report on progress to dramatically scale HDL’s throughput while maintaining sub-nm resolution.

of hydrocarbon ligand selection on incorporation surface chemistry. Combining scanning tunneling microscopy and density functional theory calculations, we assess the limitations of both classes of precursor and extract general principles relevant to each.

The nature of the atomic defects on the hydrogen passivated Si (100) surface is analyzed using deep learning and scanning tunneling microscopy (STM). A robust deep learning framework capable of identifying atomic species, defects, in the presence of non-resolved contaminates, step edges, and noise is developed. The automated workflow, based on the combination of several networks for image assessment, atom-finding and defect finding, is developed to perform the analysis at different levels of description and is deployed on an operational STM platform. This is further extended to unsupervised classification of the extracted defects using the mean-shift clustering algorithm, which utilizes features automatically engineered from the combined output of neural networks. This combined approach allows the identification of localized and extended defects on the topographically non-uniform surfaces or real materials. Our approach is universal in nature and can be applied to other surfaces for building comprehensive libraries of atomic defects in quantum materials.

The controlled formation of dangling bond structures on a H-terminated silicon surface is the first step in an atomically precise method of fabrication of silicon quantum electronic devices. An ultrahigh vacuum scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from a Si(100)-2×1:H surface by injecting electrons with the sample held at a positive bias voltage. The authors propose a lithography method that allows the STM to operate under negative bias imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative bias voltage to deliver the required energy for hydrogen removal. The resulting current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM’s feedback control loop. The authors show that the chance of tip-sample crash during the lithography process is reduced by employing this method. They also demonstrate that this approach offers a significant potential for controlled and precise removal of H atoms from a H-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

In top down nanofabrication research facilities around the world, the direct-write high-resolution patterning tool of choice is overwhelmingly electron beam lithography. Remarkably small features can be written in a variety of polymeric resists [V. R. Manfrinato et al., Nano Lett. 14, 4406 (2014); V. R. Manfrinato, A. Stein, L. Zhang, Y. Nam, K. G. Yager, E. A. Stach, and C. T. Black, Nano Lett. 17, 4562 (2017)]. However, this technology, which in this article the authors will refer to as conventional electron beam lithography (CEBL), is reaching its practical resolution and precision limits [V. R. Manfrinato et al., Nano Lett. 14, 4406 (2014)]. Hydrogen depassivation lithography (HDL) [J. N. Randall, J. W. Lyding, S. Schmucker, J. R. Von Ehr, J. Ballard, R. Saini, and Y. Ding, J. Vac. Sci. Technol. B 27, 2764 (2009); J. N. Randall, J. B. Ballard, J. W. Lyding, S. Schmucker, J. R. Von Ehr, R. Saini, H. Xu, and Y. Ding, Microelectron. Eng. 87, 955 (2010)] is a different version of electron beam lithography that is not limited in resolution and precision in the way that CEBL is. It uses a cold field emitter, a scanning tunneling microscope (STM) tip, to deliver a small spot of electrons on a Si (100) 2 × 1 H-passivated surface to expose a self-developing resist that is a monolayer of H adsorbed to the Si surface. Subnanometer features [S. Chen, H. Xu, K. E. J. Goh, L. Liu, and J. N. Randall, Nanotechnology 23, 275301 (2012)], and even the removal of single H atoms can be routinely accomplished [M. A. Walsh and M. C. Hersam, Annu. Rev. Phys. Chem. 60, 193 (2009)]. It is known that the H desorption process at low biases is a multielectron process [E. Foley, A. Kam, J. Lyding, and P. Avouris, Phys. Rev. Lett. 80, 1336 (1998)], but the tunneling distribution of the electrons from the STM tip to the Si surface lattice is not known. The authors have developed a simple model that demonstrates that the combination of two highly nonlinear processes creates a much higher contrast exposure mechanism than CEBL. Currently, HDL has been used almost exclusively on the Si (100) surface and has a limited number of pattern transfer techniques including Si and Ge patterned epitaxy, selective atomic layer deposition of TiO2 followed by reactive ion etching [J. B. Ballard, T. W. Sisson, J. H. G. Owen, W. R. Owen, E. Fuchs, J. Alexander, J. N. Randall, and J. R. Von Ehr, J. Vac. Sci. Technol. B 31, 06FC01 (2013)], and selective deposition of dopant atoms for quantum devices and materials [Workshop on 2D Quantum MetaMaterials held at NIST, Gaithersburg, MD, April 25–26, 2018, edited by J. Owen and W. P. Kirk]. While the throughput of HDL is very low, going parallel in a big way appears promising [J. N. Randall, J. H. G. Owen, J. Lake, R. Saini, E. Fuchs, M. Mahdavi, S. O. R. Moheimani, and B. C. Schaefer, J. Vac. Sci. Technol. B 36, 6 (2018)]. However, the most exciting aspect of HDL is its atomic-scale resolution and precision, which is key to nanoscale research. The authors see HDL emerging as the ultimate high-resolution patterning tool in top down nanofabrication research facilities.