Enhanced Atomic Precision Fabrication by Adsorption of Phosphine into Engineered Dangling Bonds on H-Si Using STM and DFT

Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics

The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into "Beyond CMOS" and "More than Moore" paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. The outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.

Single-Atom Control of Arsenic Incorporation in Silicon for High-Yield Artificial Lattice Fabrication

Artificial lattices constructed from individual dopant atoms within a semiconductor crystal hold promise to provide novel materials with tailored electronic, magnetic, and optical properties. These custom-engineered lattices are anticipated to enable new, fundamental discoveries in condensed matter physics and lead to the creation of new semiconductor technologies including analog quantum simulators and universal solid-state quantum computers. This work reports precise and repeatable, substitutional incorporation of single arsenic atoms into a silicon lattice. A combination of scanning tunneling microscopy hydrogen resist lithography and a detailed statistical exploration of the chemistry of arsine on the hydrogen-terminated silicon (001) surface are employed to show that single arsenic dopants can be deterministically placed within four silicon lattice sites and incorporated with 97 ± 2% yield. These findings bring closer to the ultimate frontier in semiconductor technology: the deterministic assembly of atomically precise dopant and qubit arrays at arbitrarily large scales.

Surface-Assisted Selective Air Oxidation of Phosphines Adsorbed on Activated Carbon

Trialkyl- and triarylphosphines readily adsorb onto the surface of porous activated carbon (AC) even in the absence of solvents through van der Waals interactions between the lone electron pair and the AC surface. This process has been proven by solid-state NMR techniques. Subsequently, it is demonstrated that the AC enables the fast and selective oxidation of adsorbed phosphines to phosphine oxides at ambient temperature in air. In solution, trialkylphosphines are oxidized to a variety of P(V) species when exposed to the atmosphere, while neat or dissolved triarylphosphines cannot be oxidized with air. When the trialkyl- and triarylphosphines PnBu3 (1), PEt3, (2), PnOct3 (3), PMetBu2 (4), PCy3 (5), and PPh3 (6) are adsorbed in a mono- or submonolayer on the surface of AC, in the absence of a solvent and at ambient temperature, they are quantitatively oxidized to the adsorbed phosphine oxides, 1ox-6ox, once air is admitted. No formation of any unwanted P(V) side products or water adducts is observed. The phosphine oxides can then be recovered in good yields by washing them off of the AC. The oxidation is likely facilitated by a radical activation of molecular oxygen due to delocalized electrons on the aromatic surface coating of AC, as proven by ESR. This easy and inexpensive oxidation method renders hydrogen peroxide or other oxidizers unnecessary and is broadly applicable to sterically hindered and even to air-stable triarylphosphines. Phosphines adsorbed at lower surface coverages on AC oxidize at a faster rate. All oxidation reactions were monitored by solution- and solid-state NMR spectroscopy.

PBr3 adsorption on a chlorinated Si(100) surface with mono- and bivacancies

For the most precise incorporation of single impurities in silicon, which is utilized to create quantum devices, a monolayer of adatoms on the Si(100) surface and a dopant-containing molecule are used. Here, we studied the interaction of phosphorus tribromide with a chlorine monolayer with mono- and bivacancies using a scanning tunneling microscope (STM) at 77 K. The combination of different halogens in the molecule and the adsorbate layer enabled unambiguous identification of the structures after PBr3 dissociation on Si(100)-Cl. A Cl monolayer was exposed to PBr3 in the STM chamber, which allows us to compare the same surface areas before and after PBr3 adsorption. As a result of this comparison, we detected small changes in the chlorine layer and unraveled the molecular fragments filling mono- and bivacancies. Using density functional theory, we found that the phosphorus atom occupies a bridge position after dissociation of the PBr3 molecule, which primarily bonds with silicon in Cl bivacancies. These findings provide insight into the interaction of a dopant-containing molecule with an adsorbate monolayer on Si(100) and can be applied to improve the process of single impurity incorporation into silicon.

Uncovering anisotropic effects of electric high-moment dipoles on the tunneling current in [Formula: see text]-layer tunnel junctions

The precise positioning of dopants in semiconductors using scanning tunneling microscopes has led to the development of planar dopant-based devices, also known as [Formula: see text]layer-based devices, facilitating the exploration of new concepts in classical and quantum computing. Recently, it has been shown that two distinct conductivity regimes (low- and high-bias regimes) exist in [Formula: see text]-layer tunnel junctions due to the presence of quasi-discrete and continuous states in the conduction band of [Formula: see text]-layer systems. Furthermore, discrete charged impurities in the tunnel junction region significantly influence the tunneling rates in [Formula: see text]-layer tunnel junctions. Here we demonstrate that electrical dipoles, i.e. zero-charge defects, present in the tunnel junction region can also significantly alter the tunneling rate, depending, however, on the specific conductivity regime, and orientation and moment of the dipole. In the low-bias regime, with high-resistance tunneling mode, dipoles of nearly all orientations and moments can alter the current, indicating the extreme sensitivity of the tunneling current to the slightest imperfection in the tunnel gap. In the high-bias regime, with low-resistivity, only dipoles with high moments and oriented in the directions perpendicular to the electron tunneling direction can significantly affect the current, thus making this conductivity regime significantly less prone to the influence of dipole defects with low-moments or oriented in the direction parallel to the tunneling.

Atomic Engineering of Molecular Qubits for High-Speed, High-Fidelity Single Qubit Gates

Universal quantum computing requires fast single- and two-qubit gates with individual qubit addressability to minimize decoherence errors during processor operation. Electron spin qubits using individual phosphorus donor atoms in silicon have demonstrated long coherence times with high fidelities, providing an attractive platform for scalable quantum computing. While individual qubit addressability has been demonstrated by controlling the hyperfine interaction between the electron and nuclear wave function in a global magnetic field, the small hyperfine Stark coefficient of 0.34 MHz/MV m-1 achieved to date has limited the speed of single quantum gates to ∼42 μs to avoid rotating neighboring qubits due to power broadening from the antenna. The use of molecular 2P qubits with more than one donor atom has not only demonstrated fast (0.8 ns) two-qubit SWAP gates and long spin relaxation times of ∼30 s but provides an alternate way to achieve high selectivity of the qubit resonance frequency. Here, we show in two different devices that by placing the donors with comparable interatomic spacings (∼0.8 nm) but along different crystallographic axes, either the [110] or [310] orientations using STM lithography, we can engineer the hyperfine Stark shift from 1 MHz/MV m-1 to 11.2 MHz/MV m-1, respectively, a factor of 10 difference. NEMO atomistic calculations show that larger hyperfine Stark coefficients of up to ∼70 MHz/MV m-1 can be achieved within 2P molecules by placing the donors ≥5 nm apart. When combined with Gaussian pulse shaping, we show that fast single qubit gates with 2π rotation times of 10 ns and ∼99% fidelity single qubit operations are feasible without affecting neighboring qubits. By increasing the single qubit gate time to ∼550 ns, two orders of magnitude faster than previously measured, our simulations confirm that >99.99% single qubit control fidelities are achievable.

Lessons Learned from Catalysis to Qubits: General Strategies to Build Accessible and Accurate First-Principles Models of Point Defects

Defects and dopants play critical roles in defining the properties of a material. Achieving a mechanistic understanding of how such properties arise is challenging with current experimental methods, and computational approaches suffer from significant modeling limitations that frequently require a posteriori fitting. Consequently, the pace of dopant discovery as a means of tuning material properties for a particular application has been slow. However, recent advances in computation have enabled researchers to move away from semiempirical schemes to reposition density functional theory as a predictive tool and improve the accessibility of highly accurate first-principles methods to all researchers. This Perspective discusses some of these recent achievements that provide more accurate first-principles geometric, thermodynamic, optical, and electronic properties simultaneously. Advancements related to supercells, basis sets, functionals, and optimization protocols, as well as suggestions for evaluating the quality of a computational model through comparison to experimental data, are discussed. Moreover, recent computational results in the fields of energy materials, heterogeneous catalysis, and quantum informatics are reviewed along with an evaluation of current frontiers and opportunities in the field of computational materials chemistry.

Applying a Deep-Learning-Based Keypoint Detection in Analyzing Surface Nanostructures

Scanning tunneling microscopy (STM) imaging has been routinely applied in studying surface nanostructures owing to its capability of acquiring high-resolution molecule-level images of surface nanostructures. However, the image analysis still heavily relies on manual analysis, which is often laborious and lacks uniform criteria. Recently, machine learning has emerged as a powerful tool in material science research for the automatic analysis and processing of image data. In this paper, we propose a method for analyzing molecular STM images using computer vision techniques. We develop a lightweight deep learning framework based on the YOLO algorithm by labeling molecules with its keypoints. Our framework achieves high efficiency while maintaining accuracy, enabling the recognitions of molecules and further statistical analysis. In addition, the usefulness of this model is exemplified by exploring the length of polyphenylene chains fabricated from on-surface synthesis. We foresee that computer vision methods will be frequently used in analyzing image data in the field of surface chemistry.

Probing the Atomic Arrangement of Subsurface Dopants in a Silicon Quantum Device Platform

High-density structures of subsurface phosphorus dopants in silicon continue to garner interest as a silicon-based quantum computer platform; however, a much-needed confirmation of their dopant arrangement has been lacking. In this work, we take advantage of the chemical specificity of X-ray photoelectron diffraction to obtain the precise structural configuration of P dopants in subsurface Si:P δ-layers. The growth of δ-layer systems with different levels of doping is carefully studied and verified using X-ray photoelectron spectroscopy and low-energy electron diffraction. Subsequent diffraction measurements reveal that in all cases, the subsurface dopants primarily substitute with Si atoms from the host material. Furthermore, no signs of carrier-inhibiting P-P dimerization can be observed. Our observations not only settle a nearly decade-long debate about the dopant arrangement but also demonstrate how X-ray photoelectron diffraction is surprisingly well suited for studying subsurface dopant structure. This work thus provides valuable input for an updated understanding of the behavior of Si:P δ-layers and the modeling of their derived quantum devices.

Experimental realization of an extended Fermi-Hubbard model using a 2D lattice of dopant-based quantum dots

The Hubbard model is an essential tool for understanding many-body physics in condensed matter systems. Artificial lattices of dopants in silicon are a promising method for the analog quantum simulation of extended Fermi-Hubbard Hamiltonians in the strong interaction regime. However, complex atom-based device fabrication requirements have meant emulating a tunable two-dimensional Fermi-Hubbard Hamiltonian in silicon has not been achieved. Here, we fabricate 3 × 3 arrays of single/few-dopant quantum dots with finite disorder and demonstrate tuning of the electron ensemble using gates and probe the many-body states using quantum transport measurements. By controlling the lattice constants, we tune the hopping amplitude and long-range interactions and observe the finite-size analogue of a transition from metallic to Mott insulating behavior. We simulate thermally activated hopping and Hubbard band formation using increased temperatures. As atomically precise fabrication continues to improve, these results enable a new class of engineered artificial lattices to simulate interactive fermionic models.

Atomically precise artificial lattices of dopant-based quantum dots offer a tunable platform for simulations of interacting fermionic models. By leveraging advances in fabrication and atomic-state control, Wang et al. report quantum simulations of the 2D Fermi-Hubbard model on a 3 × 3 few-dopant quantum dot array.