Growth, Structure, Electronic and Transport Properties of Yttrium Disilicide Nanowires

The electronic properties of low-dimensional materials deviate significantly from their bulk counterparts. Especially in quasi one-dimensional (1D) materials, a small number of structural defects can lead to strong electron localization. Electrons may also display unusual collective behavior in 1D. As integrated circuits continue to shrink in size, there is an increasing need for understanding and possibly manipulating electronic transport in quasi 1D materials. Here, we focus on electrical transport in self-assembled YSi2 [yttrium disilicide] nanowires on Si(001). Being just a few atoms wide, these nanowires are one of the closest experimental realizations of a 1D conductor. YSi2 nanowires are particularly attractive because they can be integrated into silicon based electronic circuits. Little is known about their electrical transport properties, however, because it is extremely difficult to connect these atomically thin wires to macroscopic measurement contacts. This technical obstacle was overcome by developing an in-situ method for contacting these atomically thin nanowires in ultrahigh vacuum. Here, one wire end is contacted to a macroscopic contact pad via shadow mask deposition, while the other end is contacted with the tip of a scanning tunneling microscope. The nanowires turn out to be very resistive and the relation between the measured resistance and wire length is highly non-linear. From the resistance measurements, we infer a localization length that is comparable to the atomic defect spacing in the wire, thus confirming the 1D nature of the transport and highlighting the importance of charge trapping by defects. Whereas the nanowires on Si(001) grow into orthogonal directions, nanowires on Si(110) all grow in the same direction. They exhibit a clear preference of nucleating at step edges when these edges are aligned along the [1-10] growth direction. This suggests a promising avenue for the fabrication of regular nanowire arrays with controlled wire separation, by varying the miscut angle of the Si wafer. We have demonstrated the feasibility of controlling nanowire growth, including their orientation, and related the nanowire resistance with the atomic dimensions and atomic-scale features of the wires. These insights will be increasingly relevant as nanoscale interconnects will ultimately approach the atomic limit

Taming Atomic Defects for Quantum Functions

Single atoms provide an ideal system for utilizing fundamental quantum functions. Their electrons have well-defined energy levels and spin properties. Even more importantly, for a given isotope -- say, $^{12}$C -- all the atoms are identical. This creates a perfect uniformity that is impossible to achieve in macroscopic-size quantum systems. However, herding individual atoms is a very difficult task that requires trapping them with magnetic or optical means and cooling them down to temperatures in the nanokelvin range. On the other hand, the counterpart of single atoms -- the single defects -- may be as good as atom-based quantum systems if not better. These defects, also referred as quantum defects, possess the favorable energy, spin, and uniformity properties of single atoms and remain in their place without the help of precisely tuned lasers. While the number of usable isotopes is set, the combinations of defects and their host material are practically limitless, giving us the flexibility to create precisely designed and controlled quantum systems. Furthermore, as we tame these defects for the quantum world, we bring about transformative opportunities to the classical world in forms such as ultradense electronic devices and precise manufacturing. In this research insight, we introduce some of our recent work on precisely controlled creation and manipulation of individual defects with a scanning tunneling microscope (STM). We also discuss possible pathways for utilizing these capabilities for the development of novel systems for Quantum Information Science (QIS) applications such as quantum information processing and ultrasensitive sensors

Autonomous convergence of STM control parameters using Bayesian Optimization

Scanning Tunneling microscopy (STM) is a widely used tool for atomic imaging of novel materials and its surface energetics. However, the optimization of the imaging conditions is a tedious process due to the extremely sensitive tip-surface interaction, and thus limits the throughput efficiency. Here we deploy a machine learning (ML) based framework to achieve optimal-atomically resolved imaging conditions in real time. The experimental workflow leverages Bayesian optimization (BO) method to rapidly improve the image quality, defined by the peak intensity in the Fourier space. The outcome of the BO prediction is incorporated into the microscope controls, i.e., the current setpoint and the tip bias, to dynamically improve the STM scan conditions. We present strategies to either selectively explore or exploit across the parameter space. As a result, suitable policies are developed for autonomous convergence of the control-parameters. The ML-based framework serves as a general workflow methodology across a wide range of materials.Comment: 31 pages, 5 figures and Supplementary Informatio

Lifshitz Transition and Band Structure Evolution in Alkali Metal Intercalated 1Tprime-MoTe2

MoTe2 is a paradigmatic van der Waals layered semimetal with two energetically close electronic phases, the topologically trivial 1Tprime and the low-temperature Td type-II Weyl semimetal phase. The ability to manipulate this phase transition, perhaps towards occurring near room temperature, would open new avenues for harnessing the full potential of Weyl semimetals for high-efficiency electronic and spintronic applications. Here, we show that potassium dosing on 1Tprime-MoTe2 induces a Lifshitz transition by a combination of angle-resolved photoemission spectroscopy, scanning tunneling microscopy, x-ray spectroscopy and density functional theory. While the electronic structure shifts rigidly for small concentrations of K, MoTe2 undergoes significant band structure renormalization for larger concentrations. Our results demonstrate that the origin of this electronic structure change stems from alkali metal intercalation. We show that these profound changes are caused by effectively decoupling the 2D sheets, bringing K-intercalated 1Tprime-MoTe2 to the quasi-2D limit, but do not cause a topological phase transition

Autonomous convergence of STM control parameters using Bayesian optimization

Scanning tunneling microscopy (STM) is a widely used tool for atomic imaging of novel materials and their surface energetics. However, the optimization of the imaging conditions is a tedious process due to the extremely sensitive tip–surface interaction, thus limiting the throughput efficiency. In this paper, we deploy a machine learning (ML)-based framework to achieve optimal atomically resolved imaging conditions in real time. The experimental workflow leverages the Bayesian optimization (BO) method to rapidly improve the image quality, defined by the peak intensity in the Fourier space. The outcome of the BO prediction is incorporated into the microscope controls, i.e., the current setpoint and the tip bias, to dynamically improve the STM scan conditions. We present strategies to either selectively explore or exploit across the parameter space. As a result, suitable policies are developed for autonomous convergence of the control parameters. The ML-based framework serves as a general workflow methodology across a wide range of materials

Resistivity of Surface Steps in Bulk-Insulating Topological Insulators

Electron transport in topological insulators usually involves both topologically protected surface states and trivial electronic states in the bulk material. The surface transport is particularly interesting; however, it is also susceptible to atomic defects on the surfaces, such as vacancies, impurities, and step edges. Experimental determination of scattering effects of these surface defects requires both nanoscale spatial resolution and the ability to decipher surface transport from bulk transport. Here we directly measure the resistivity of individual surface steps in the surface dominating transport process of topological insulator Bi2Te2Se. A variable probe-spacing transport spectroscopy with a multiprobe scanning tunneling microscope is used to differentiate the surface conductance from bulk conductance, allowing the identification of a surface dominant transport regime. The technique also reveals a deviation from ideal 2D transport at atomic steps. Then, a multi-probe scanning tunneling potentiometry is employed to visualize the electrochemical potentials across individual step edges. A quantitative analysis of the potential distributions enables us to acquire a resistivity of 0.530 m omega center dot cm for the one quintuple-layer atomic step. The result indicates that atomic defects, despite preserving the time-reversal symmetry, can still significantly affect the transport in topological insulators.11Nsciescopu

High-throughput electrical measurement and microfluidic sorting of semiconductor nanowires

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Differentiation of Surface and Bulk Conductivities via Four-probe Spectroscopy

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Differentiation of Surface and Bulk Conductivities in Topological Insulators via Four-Probe Spectroscopy

International audienceWe show a new method to differentiate conductivities from the surface states and the coexisting bulk states in topological insulators using a four-probe transport spectroscopy in a multiprobe scanning tunneling microscopy system. We derive a scaling relation of measured resistance with respect to varying interprobe spacing for two interconnected conduction channels to allow quantitative determination of conductivities from both channels. Using this method, we demonstrate the separation of 2D and 3D conduction in topological insulators by comparing the conductance scaling of Bi2Se3, Bi2Te2Se, and Sb-doped Bi2Se3 against a pure 2D conductance of graphene on SiC substrate. We also quantitatively show the effect of surface doping carriers on the 2D conductance enhancement in topological insulators. The method offers a means to understanding not just the topological insulators but also the 2D to 3D crossover of conductance in other complex systems