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Abstract Electrical scanning probe microscopies (SPM) use ultrasharp metallic tips to obtain nanometer spatial resolution and are a key tool for characterizing nanoscale semiconducting materials and systems. However, these tips are not passive probes; their high work functions can induce local band bending whose effects depend sensitively on the local geometry and material properties and thus are inherently difficult to quantify. We use sequential finite element simulations to first explore the magnitude and spatial distribution of charge reorganization due to tip-induced band bending (TIBB) for planar and nanostructured geometries. We demonstrate that tip-induced depletion and accumulation of carriers can be significantly modified in confined geometries such as nanowires compared to a bulk planar response. This charge reorganization is due to finite size effects that arise as the nanostructure size approaches the Debye length, with significant implications for a range of SPM techniques. We then use the reorganized charge distribution from our model to describe experimentally measured quantities, usingin operandoscanning microwave impedance microscopy measurements on axial p-i-n silicon nanowire devices as a specific example. By incorporating TIBB, we reveal that our experimentally observed enhancement (absence) of contrast at the p-i (i-n) junction is explained by the tip-induced accumulation (depletion) of carriers at the interface. Our results demonstrate that the inclusion of TIBB is critical for an accurate interpretation of electrical SPM measurements, and is especially important for weakly screening or low-doped materials, as well as the complex doping patterns and confined geometries commonly encountered in nanoscale systems. 

Surface functionalization of low-dimensional nanomaterials offers a means to tailor their optoelectronic and chemical characteristics. However, functionalization reactions are sensitive to the inherent surface features of nanomaterials, such as defects, grain boundaries, and edges. Conventional optical characterization methods, such as Raman spectroscopy, have limited sensitivity and spatial resolution and, therefore, struggle to visualize reaction sites and chemical species. Here, we demonstrate the capability of spatially and chemically sensitive tip-enhanced Raman spectroscopy imaging to map the distribution of molecules in covalently functionalized graphene. Hyperspectral vertex component analysis and density functional theory are necessary to interpret the nature of binding sites and extract information from the spatially and spectrally heterogeneous datasets. Our results clarify the origin of heterogeneous surface functionalization, resolving preferential binding at edges and defects. This work demonstrates the potential of nanospectroscopic tools combined with unsupervised learning to characterize complex, partially ordered optoelectronic nanomaterials. 

The nanoscale spectral heterogeneity of graphene oxide provides insight into the mechanism of self-reduction. 

As scattering-scanning near-field optical microscopy (s-SNOM) continues to grow in prominence, there has been great interest in modeling the near-field light-matter interaction to better predict experimental results. Both analytical and numerical models have been developed to describe the near-field response, but thus far models have not incorporated the full range of phenomena accessible. Here, we present a finite element model (FEM), capable of incorporating the complex physical and spatial phenomena that s-SNOM has proved able to probe. First, we use electromagnetic FEM to simulate the multipolar response of the tip and illustrate the impact of strong coupling on signal demodulation. We then leverage the multiphysics advantage of FEM to study the electrostatic effect of metallic tips on semiconductors, finding that THz s-SNOM studies are most impacted by this tip-induced band-bending. Our model is computationally inexpensive and can be tailored to specific nanostructured systems and geometries of interest.