arXiv subjects

V. King

Publications and source records attributed to V. King.

2 recordsLinked to original sources

arXiv2026

Stacking-Induced Tuning of a Flat-Band Surface State in NbIrTe4

Ternary layered transition metal dichalcogenides (TMDCs) offer high tunability and access to correlated and topological states. However, like the broader family of layered TMDCs, their properties are sensitive to stacking order and interlayer coupling. Here, we investigate the electronic structure and surface states of NbIrTe$_4$, a candidate Weyl semimetal in bulk, and predicted to be a quantum spin Hall insulator in monolayer form. Using scanning tunnelling microscopy (STM), angle-resolved photoemission spectroscopy (ARPES), and density-functional theory (DFT), we attribute the strong resonance in tunnelling spectroscopy located approximately 8 meV below the Fermi level to a surface-derived flat band which shows sensitivity to the local stacking order at the surface. In regions where the top layer is laterally shifted, tunnelling spectroscopy instead shows a gap-like feature with intensity near the Fermi level shifted in energy. Combining DFT and quasiparticle interference (QPI) measurements, we find this dramatic change in the spectroscopy in the vicinity of the quasi-1D flat-band surface state becomes dispersive due to a change in the spatial distribution of the density of states in the top two layers. These findings establish NbIrTe$_4$ as a platform where surface band dispersion can be effectively tuned through local structural manipulation.

cond-mat.mes-hall↗

arXiv2024

Using $k$-means to sort spectra: electronic order mapping from scanning tunneling spectroscopy measurements

Hyperspectral imaging techniques have a unique ability to probe the inhomogeneity of material properties whether driven by compositional variation or other forms of phase segregation. In the doped cuprates, iridates, and related materials, scanning tunneling microscopy/spectroscopy (STM/STS) measurements have found the emergence of pseudogap 'puddles' from the macroscopically Mott insulating phase with increased doping. However, categorizing this hyperspectral data by electronic order is not trivial, and has often been done with ad hoc methods. In this paper we demonstrate the utility of $k$-means, a simple and easy-to-use unsupervised clustering method, as a tool for classifying heterogeneous scanning tunneling spectroscopy data by electronic order for Rh-doped Sr$_2$IrO$_{4}$, a cuprate-like material. Applied to STM data acquired within the Mott phase, $k$-means successfully identified areas of Mott order and of pseudogap order. The unsupervised nature of $k$-means limits avenues for bias, and provides clustered spectral shapes without a priori knowledge of the physics. Additionally, we demonstrate successful use of $k$-means as a preprocessing tool to constrain phenomenological function fitting. Clustering the data allows us to reduce the fitting parameter space, limiting over-fitting. We suggest $k$-means as a fast, simple model for processing hyperspectral data on materials of mixed electronic order.

cond-mat.str-el↗