Topological Landscape of Competing Charge Density Waves in 2H-NbSe2

Despite decades of studies of the charge density wave (CDW) of 2H-NbSe2, the origin of its incommensurate CDW ground state has not been understood. We discover that the CDW of 2H-NbSe2 is composed of two different, energetically competing, structures. The lateral heterostructures of two CDWs are entangled as topological excitations, which give rise to a CDW phase shift and the incommensuration without a conventional domain wall. A partially melted network of topological excitations and their vertices explain an unusual landscape of domains. The unconventional topological role of competing phases disclosed here can be widely applied to various incommensuration or phase coexistence phenomena in materials. © 2019 American Physical Societ

Realizing a Superconducting Square-Lattice Bismuth Monolayer

Interplay of crystal symmetry, strong spin$-$orbit coupling (SOC), and many-body interactions in low dimensional materials provides a fertile ground for the discovery of unconventional electronic and magnetic properties and versatile functionalities. Two-dimensional (2D) allotropes of group 15 elements are appealing due to their structures and controllability over symmetries and topology under strong SOC. Here, we report the heteroepitaxial growth of a proximity-induced superconducting 2D square-lattice bismuth monolayer on superconducting Pb films. The square lattice of monolayer bismuth films in a $C_4$ symmetry together with a stripey moir\'e structure is clearly resolved by our scanning tunneling microscopy and its atomic structure is revealed by density functional theory (DFT) calculations. A Rashba-type spin-split Dirac band is predicted by DFT calculations to exist at the Fermi level and becomes superconducting through the proximity effect from the Pb substrate. We suggest the possibility of a topological superconducting state in this system with magnetic dopants/field. This work introduces an intriguing material platform with 2D Dirac bands, strong SOC, topological superconductivity, and the moir\'e superstructure.Comment: 21 pages, 4 figure

Defect-Selective Charge-Density-Wave Condensation in 2H-NbSe_{2}

© 2020 American Physical Society. Defects have been known to substantially affect quantum states of materials including charge density wave (CDW). However, the microscopic mechanism of the influence of defects is often elusive due partly to the lack of atomic scale characterization of defects themselves. We investigate native defects of a prototypical CDW material 2H-NbSe_{2} and their microscopic interaction with CDW. Three prevailing types of atomic scale defects are classified by scanning tunneling microscope, and their atomic structures are identified by density functional theory calculations as Se vacancies and Nb intercalants. Above the transition temperature, two distinct CDW structures are found to be induced selectively by different types of defects. This intriguing phenomenon is explained by competing CDW ground states and local lattice strain fields induced by defects, providing a clear microscopic mechanism of the defect-CDW interaction11sci

Realizing a Superconducting Square-Lattice Bismuth Monolayer

Interplay of crystal symmetry, strong spin-orbit coupling (SOC), and many-body interactions in low-dimensional materials provides a fertile ground for the discovery of unconventional electronic and magnetic properties and versatile functionalities. Two-dimensional (2D) allotropes of group 15 elements are appealing due to their structures and controllability over symmetries and topology under strong SOC. Here, we report the heteroepitaxial growth of a proximity-induced superconducting 2D square-lattice bismuth monolayer on superconducting Pb films. The square lattice of monolayer bismuth films in a C4 symmetry together with a stripey moiré structure is clearly resolved by our scanning tunneling microscopy, and its atomic structure is revealed by density functional theory (DFT) calculations. A Rashba-type spin-split Dirac band is predicted by DFT calculations to exist at the Fermi level and becomes superconducting through the proximity effect from the Pb substrate. We suggest the possibility of a topological superconducting state in this system with magnetic dopants/field. This work introduces an intriguing material platform with 2D Dirac bands, strong SOC, topological superconductivity, and the moiré superstructure.11Nsciescopu

Unveiling the hidden charge density wave spectral signature in 2H- NbSe2

Although 2H-NbSe2 has been discussed as a prototypical charge density wave (CDW) material with strong electron-phonon coupling, its energy gap structure, such as its position and size, has been elusive in spectroscopic measurements. We carefully reinvestigate the spectral change in the scanning tunneling microscopy and spectroscopy (STM/STS) when crossing the CDW transition in temperature and space. In contradiction to previous assignments, our spectroscopy measurements exhibit no significant spectral change across the CDW transition. Density functional theory calculations attribute the absence of the spectral signature to the CDW gap opening at the M point and the Γ-point-sensitive tunneling in the STS measurement. As an alternative CDW signature, we identify a strong bias-dependent modulation of local charge density across the Fermi energy which originates from the bonding/antibonding character of bands involved in the CDW gap at the M point. Our findings provide important insights for understanding partially gapped mutliband CDW materials.11Nsciescopu

Methodology to Predict Random Telegraph Noise Induced Threshold Voltage Shift Using Machine Learning

We suggest the methodology to predict the distribution of threshold voltage (V-t) shift caused by random telegraph noise (RTN). Poly-silicon channels were randomized with a single trap and the neural network was modeled to predict RTN trap-induced Vt fluctuation in 3D NAND Flash Memory. 3D Technology Computer-Aided Design (TCAD) simulations were performed in a unit cell to calculate the Vt shift in a 3D vertical channel. Finally, we extract the distribution of Vt fluctuation using machine learning.N