Saban M. Hus

Combinatorial magnetron sputtering was used to generate a library of devices with a wide range of Hf:Zr ratios. The electrical properties of these devices were systematically investigated and correlated to the crystal structure. XRD, XRR, XPS, and EDS were used to measure film structure, thickness, bonding, and chemistry across the sample, respectively. Time-resolved PUND measurements were used to confirm ferroelectric behavior in devices ranging from 49 to 22 atomic % Hf. The switching current and polarization were extracted from the PUND measurements. Ferroelectricity is shown to increase from 49 to 38% Hf. Further decreasing Hf decreases the switching polarization, while also generating peak splitting behavior. Device endurance properties were measured and showed consistent switching up to 10⁴ cycles, while enduring cycling out to 10⁵ cycles. Increased cycling of bimodal switching unified the peak splitting, while increasing the overall switching polarization. XRD structural measurements showed high orthorhombic/tetragonal peaks in the regions exhibiting ferroelectricity, suggesting that the primary phase driving the ferroelectric behavior is orthorhombic.

Bi 4 Br 4 is a prototypical quasi-one-dimensional (1D) material in which covalently bonded bismuth bromide chains are arranged in parallel, side-by-side and layer-by-layer, with van der Waals (vdW) gaps in between. So far, two different structures have been reported for this compound, α − Bi 4 Br 4 and β − Bi 4 Br 4 , in both of which neighboring chains are shifted by b / 2 , i.e., half a unit-cell vector in the plane, but which differ in their vertical stacking. While the different layer stacking is known to result in distinct electronic properties—higher-order and weak topological insulators, respectively—the effect of different in-plane arrangements of the atomic chains remains an open question. Here, using scanning tunneling microscopy and spectroscopy (STM/STS), we report an unusual Bi 4 Br 4 (001) structure, with a shift of b / 3 between neighboring chains in the plane and AB layer stacking. We determine shear strain to be the origin of this structure, which can readily result in shifts of neighboring atomic chains because of the weak interchain bonding. For the observed b / 3 structure, the (residual) atomic chain shift corresponds to an in-plane shear strain of γ ≈ 7.5 % . STS reveals a bulk insulating gap and metallic edge states at monolayer surface steps, indicating that, just like for α − Bi 4 Br 4 , monolayers of the b / 3 structure are also quantum spin Hall insulators, in agreement with density functional theory (DFT) calculations. Published by the American Physical Society 2025

Most two-dimensional (2D) materials experimentally studied so far have hexagons as their building blocks. Only a few exceptions, such as PdSe₂, are lower in energy in pentagonal phases and exhibit pentagons as building blocks. Although theory has predicted a large number of pentagonal 2D materials, many of these are metastable and their experimental realization is difficult. Here we report the successful synthesis of a metastable pentagonal 2D material, monolayer pentagonal PdTe₂, by symmetry-driven epitaxy. Scanning tunnelling microscopy and complementary spectroscopy measurements are used to characterize this material, which demonstrates well-ordered low-symmetry atomic arrangements and is stabilized by lattice matching with the underlying Pd(100) substrate. Theoretical calculations, along with angle-resolved photoemission spectroscopy, reveal monolayer pentagonal PdTe₂ to be a semiconductor with an indirect bandgap of 1.05 eV. Our work opens an avenue for the synthesis of pentagon-based 2D materials and gives opportunities to explore their applications such as multifunctional nanoelectronics.

We report an algorithm to identify and correct distorted wavefronts in atomic resolution scanning tunneling microscope images. This algorithm can be used to correct nonlinear in-plane distortions without prior knowledge of the physical scanning parameters, the characteristics of the piezoelectric actuator, or individual atom positions. The 2D image is first defined as a sum of sinusoidal plane waves, where a nonlinear distortion renders a curve for an otherwise ideal linear wavefront. Using the Fourier transforms of local areas of the image, the algorithm generates a wavefront vector field. The identified wavefronts are subsequently linearized for each plane wave without changing lattice orders, giving rise to distortion corrections. Our algorithm is complementary to conventional post-processing algorithms that require prior detection of real space features, which can also be used to correct nonlinear distortions in 2D images acquired by other microscopy techniques.

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.