Two-dimensional (2D) layered materials have attracted the interest of the scientific community following the discovery of graphene and its extraordinary properties. Of particular interest is a class of materials called transition metal dichalcogenides (TMDs). The materials within this class were discovered to show similarly intriguing optical and electronic properties, when compared to graphene. Moreover, research indicated that these properties are also highly sensitive to the TMDs' underlying atomic structure. Gaining control over these structural properties would enable the tuning of the physical and chemical properties, and hence allow for the fabrication of novel TMD nanostructures with tailored functionalities. Driven by this potential, we strive to gain a comprehensive understanding of the relationship between the structural, chemical, and local electronic properties of nanostructures based on one such TMD material: tungsten disulfide (WS₂). This in order to aid us in the exploitation of the tunability of these physical properties through the fabrication of novel WS₂ nanostructures. …

Achieving nanoscale strain fields mapping in intricate van der Waals (vdW) nanostructures, like twisted flakes and nanorods, presents several challenges due to their complex geometry, small size, and sensitivity limitations. Understanding these strain fields is pivotal as they significantly influence the optoelectronic properties of vdW materials, playing a crucial role in a plethora of applications ranging from nanoelectronics to nanophotonics. Here, a novel approach for achieving a nanoscale-resolved mapping of strain fields across entire micron-sized vdW nanostructures using four-dimensional (4D) scanning transmission electron microscopy (STEM) imaging equipped with an electron microscope pixel array detector (EMPAD) is presented. This technique extends the capabilities of STEM-based strain mapping by means of the exit-wave power cepstrum method incorporating automated peak tracking and K-means clustering algorithms. This approach is validated on two representative vdW nanostructures: a two-dimensional (2D) MoS₂ thin twisted flakes and a one-dimensional (1D) MoO₃/MoS₂ nanorod heterostructure. Beyond just vdW materials, the versatile methodology offers broader applicability for strain-field analysis in various low-dimensional nanostructured materials. This advances the understanding of the intricate relationship between nanoscale strain patterns and their consequent optoelectronic properties.

Twisted 2D materials present an enticing platform for exploring diverse electronic properties owning to the tunability of their bandgap energy. However, the intricate relationship between local heterostrain fields, thickness, and bandgap energy remains insufficiently understood, particularly at the nanoscale. Here, it presents a comprehensive nanoscale study elucidating the remarkable sensitivity of the bandgap energy to both thickness and heterostrain fields within twisted WS₂ nanostructures. This approach integrates electron energy-loss spectroscopy (EELS) enhanced by machine learning with 4D scanning transmission electron microscopy (STEM). Through this synergistic methodology, enhancements up to 20% in the bandgap energy is unveiled depending on the specimen thickness. This phenomenon is traced back to sizable deformation angles present within individual layers, which can be directly linked to distinct variations in local heterostrain fields. The findings represent a significant advancement in comprehending the electronic behavior of twisted 2D materials and introduce a novel methodological framework with far-reaching implications for twistronics and the investigation of other materials within the nanoscience domain.

The phenomenon of polytypism, namely unconventional crystal phases displaying a mixture of stacking sequences, represents a powerful handle to design and engineer novel physical properties in two-dimensional (2D) materials. In this work, we characterize from first-principles the optoelectronic properties associated with the 2H/3R polytypism occurring in WS₂ nanomaterials by means of density functional theory (DFT) calculations. We evaluate the band gap, optical response, and energy-loss function associated with 2H/3R WS₂ nanomaterials and compare our predictions with experimental measurements of electron energy-loss spectroscopy (EELS) carried out in nanostructures exhibiting the same polytypism. Our results provide further input to the ongoing efforts toward the integration of polytypic 2D materials into functional devices.

The electronic properties of two-dimensional (2D) materials depend sensitively on the underlying atomic arrangement down to the monolayer level. Here we present a novel strategy for the determination of the band gap and complex dielectric function in 2D materials achieving a spatial resolution down to a few nanometers. This approach is based on machine learning techniques developed in particle physics and makes possible the automated processing and interpretation of spectral images from electron energy loss spectroscopy (EELS). Individual spectra are classified as a function of the thickness with K-means clustering, and then used to train a deep-learning model of the zero-loss peak background. As a proof of concept we assess the band gap and dielectric function of InSe flakes and polytypic WS2 nanoflowers and correlate these electrical properties with the local thickness. Our flexible approach is generalizable to other nanostructured materials and to higher-dimensional spectroscopies and is made available as a new release of the open-source EELSfitter framework.

Two-dimensional Transition Metal Dichalcogenites (2D TMDs) have recently attracted enormous scientific attention for their unique optical properties. 2D TMDs are semiconductors with a direct bandgap in the visible wavelength range. In their valleys, stable excitons are formed even at room-temperature. A valley pseudospin can be attributed to each valley, making it possible to address each valley individually with circularly polarized light.

Due to their intriguing optical properties, including stable and chiral excitons, two-dimensional transition metal dichalcogenides (2D-TMDs) hold the promise of applications in nanophotonics. Chemical vapor deposition (CVD) techniques offer a platform to fabricate and design nanostructures with diverse geometries. However, the more exotic the grown nanogeometry, the less is known about its optical response. WS₂nanostructures with geometries ranging from monolayers to hollow pyramids have been created. The hollow pyramids exhibit a strongly reduced photoluminescence with respect to horizontally layered tungsten disulphide, facilitating the study of their clear Raman signal in more detail. Excited resonantly, the hollow pyramids exhibit a great number of higher-order phononic resonances. In contrast to monolayers, the spectral features of the optical response of the pyramids are position dependent. Differences in peak intensity, peak ratio and spectral peak positions reveal local variations in the atomic arrangement of the hollow pyramid crater and sides. The position-dependent optical response of hollow WS₂pyramids is characterized and attributed to growth-induced nanogeometry. Thereby the first steps are taken towards producing tunable nanophotonic devices with applications ranging from opto-electronics to non-linear optics.

Exploiting the information provided by electron energy-loss spectroscopy (EELS) requires reliable access to the low-loss region where the zero-loss peak (ZLP) often overwhelms the contributions associated to inelastic scatterings off the specimen. Here we deploy machine learning techniques developed in particle physics to realise a model-independent, multidimensional determination of the ZLP with a faithful uncertainty estimate. This novel method is then applied to subtract the ZLP for EEL spectra acquired in flower-like WS₂ nanostructures characterised by a 2H/3R mixed polytypism. From the resulting subtracted spectra we determine the nature and value of the bandgap of polytypic WS₂, finding E_BG=1.6_−0.2^+0.3eV with a clear preference for an indirect bandgap. Further, we demonstrate how this method enables us to robustly identify excitonic transitions down to very small energy losses. Our approach has been implemented and made available in an open source PYTHON package dubbed EELSfitter.

Tailoring the specific stacking sequence (polytypes) of layered materials represents a powerful strategy to identify and design novel physical properties. While nanostructures built upon transition-metal dichalcogenides (TMDs) with either the 2H or 3R crystalline phases have been routinely studied, knowledge of TMD nanomaterials based on mixed 2H/3R polytypes is far more limited. In this work, mixed 2H/3R free-standing WS₂ nanostructures displaying a flower-like configuration are fingerprinted by means of state-of-the-art transmission electron microscopy. Their rich variety of shape-morphology configurations is correlated with relevant local electronic properties such as edge, surface, and bulk plasmons. Machine learning is deployed to establish that the 2H/3R polytype displays an indirect band gap of (Formula presented.). Further, high resolution electron energy-loss spectroscopy reveals energy-gain peaks exhibiting a gain-to-loss ratio greater than unity, a property that can be exploited for cooling strategies of atomically-thin TMD nanostructures and devices built upon them. The findings of this work represent a stepping stone towards an improved understanding of TMD nanomaterials based on mixed crystalline phases.

Transition metal dichalcogenides such as MoS2 represent promising candidates for building blocks of ultra-thin nanophotonic devices. For such applications, vertically-oriented MoS2 (v-MoS2) nanosheets could be advantageous as compared to conventional horizontal MoS2 (h-MoS2) given that their inherent broken symmetry would favor an enhanced nonlinear response. However, the current lack of a controllable and reproducible fabrication strategy for v-MoS2 limits the exploration of this potential. Here we present a systematic study of the growth of v-MoS2 nanosheets based on the sulfurization of a pre-deposited Mo-metal seed layer. We demonstrate that the sulfurization process at high temperatures is driven by the diffusion of sulfur from the vapor-solid interface to the Mo seed layer. Furthermore, we verify an enhanced nonlinear response in the resulting v-MoS2 nanostructures as compared to their horizontal counterparts. Our results represent a stepping stone towards the fabrication of low-dimensional TMD-based nanostructures for versatile nonlinear nanophotonic devices.

Layered materials (LMs) such as graphene or MoS2 have attracted a great deal of interest recently. These materials offer unique functionalities due to their structural anisotropy characterized by weak van der Waals bonds along the out-of-plane axis and covalent bonds in the in-plane direction. A central requirement to access the structural information on complex nanostructures built upon LMs is to control the relative orientation of each sample prior to their inspection, e.g., with transmission electron microscopy (TEM). However, developing sample preparation methods that result in large inspection areas and ensure full control over the sample orientation while avoiding damage during the transfer to the TEM grid is challenging. Here, we demonstrate the feasibility of deploying ultramicrotomy for the preparation of LM samples in TEM analyses. We show how ultramicrotomy leads to the reproducible large-scale production of both in-plane and out-of-plane cross sections, with bulk vertically oriented MoS2 and WS2 nanosheets as a proof of concept. The robustness of the prepared samples is subsequently verified by their characterization by means of both high-resolution TEM and Raman spectroscopy measurements. Our approach is fully general and should find applications for a wide range of materials as well as of techniques beyond TEM, thus paving the way to the systematic large-area mass-production of cross-sectional specimens for structural and compositional studies.