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Abstract Optical spectroscopy is indispensable for research and development in nanoscience and nanotechnology, microelectronics, energy, and advanced manufacturing. Advanced optical spectroscopy tools often require both specifically designed high-end instrumentation and intricate data analysis techniques. Beyond the common analytical tools, deep learning methods are well suited for interpreting high-dimensional and complicated spectroscopy data. They offer great opportunities to extract subtle and deep information about optical properties of materials with simpler optical setups, which would otherwise require sophisticated instrumentation. In this work, we propose a computational approach based on a conventional tabletop optical microscope and a deep learning model called ReflectoNet . Without any prior knowledge about the multilayer substrates, ReflectoNet can predict the complex refractive indices of thin films and 2D materials on top of these nontrivial substrates from experimentally measured optical reflectance spectra with high accuracies. This task was not feasible previously with traditional reflectometry or ellipsometry methods. Fundamental physical principles, such as the Kramers–Kronig relations, are spontaneously learned by the model without any further training. This approach enables in-operando optical characterization of functional materials and 2D materials within complex photonic structures or optoelectronic devices. 

Technology advancements in history have often been propelled by material innovations. In recent years, two-dimensional (2D) materials have attracted substantial interest as an ideal platform to construct atomic-level material architectures. In this work, we design a reaction pathway steered in a very different energy landscape, in contrast to typical thermal chemical vapor deposition method in high temperature, to enable room-temperature atomic-layer substitution (RT-ALS). First-principle calculations elucidate how the RT-ALS process is overall exothermic in energy and only has a small reaction barrier, facilitating the reaction to occur at room temperature. As a result, a variety of Janus monolayer transition metal dichalcogenides with vertical dipole could be universally realized. In particular, the RT-ALS strategy can be combined with lithography and flip-transfer to enable programmable in-plane multiheterostructures with different out-of-plane crystal symmetry and electric polarization. Various characterizations have confirmed the fidelity of the precise single atomic layer conversion. Our approach for designing an artificial 2D landscape at selective locations of a single layer of atoms can lead to unique electronic, photonic, and mechanical properties previously not found in nature. This opens a new paradigm for future material design, enabling structures and properties for unexplored territories. 

Thin ferroelectric materials hold great promise for compact nonvolatile memory and nonlinear optical and optoelectronic devices. Herein, an ultrathin in‐plane ferroelectric material that exhibits a giant nonlinear optical effect, group‐IV monochalcogenide SnSe, is reported. Nanometer‐scale ferroelectric domains with ≈90°/270° twin boundaries or ≈180° domain walls are revealed in physical‐vapor‐deposited SnSe by lateral piezoresponse force microscopy. Atomic structure characterization reveals both parallel and antiparallel stacking of neighboring van der Waals ferroelectric layers, leading to ferroelectric or antiferroelectric ordering. Ferroelectric domains exhibit giant nonlinear optical activity due to coherent enhancement of second‐harmonic fields and the as‐resulted second‐harmonic generation was observed to be 100 times more intense than monolayer WS₂. This work demonstrates in‐plane ferroelectric ordering and giant nonlinear optical activity in SnSe, which paves the way for applications in on‐chip nonlinear optical components and nonvolatile memory devices.

 

The 2D van der Waals crystals have shown great promise as potential future electronic materials due to their atomically thin and smooth nature, highly tailorable electronic structure, and mass production compatibility through chemical synthesis. Electronic devices, such as field effect transistors (FETs), from these materials require patterning and fabrication into desired structures. Specifically, the scale up and future development of “2D”-based electronics will inevitably require large numbers of fabrication steps in the patterning of 2D semiconductors, such as transition metal dichalcogenides (TMDs). This is currently carried out via multiple steps of lithography, etching, and transfer. As 2D devices become more complex (e.g., numerous 2D materials, more layers, specific shapes, etc.), the patterning steps can become economically costly and time consuming. Here, we developed a method to directly synthesize a 2D semiconductor, monolayer molybdenum disulfide (MoS₂), in arbitrary patterns on insulating SiO₂/Si via seed-promoted chemical vapor deposition (CVD) and substrate engineering. This method shows the potential of using the prepatterned substrates as a master template for the repeated growth of monolayer MoS₂patterns. Our technique currently produces arbitrary monolayer MoS₂patterns at a spatial resolution of 2 μm with excellent homogeneity and transistor performance (room temperature electron mobility of 30 cm²V⁻¹s⁻¹and on–off current ratio of 10⁷). Extending this patterning method to other 2D materials can provide a facile method for the repeatable direct synthesis of 2D materials for future electronics and optoelectronics.

 

Nanoporous graphene (NPG) can exhibit a uniform electronic band gap and rationally‐engineered emergent electronic properties, promising for electronic devices such as field‐effect transistors (FETs), when synthesized with atomic precision. Bottom‐up, on‐surface synthetic approaches developed for graphene nanoribbons (GNRs) now provide the necessary atomic precision in NPG formation to access these desirable properties. However, the potential of bottom‐up synthesized NPG for electronic devices has remained largely unexplored to date. Here, FETs based on bottom‐up synthesized chevron‐type NPG (C‐NPG), consisting of ordered arrays of nanopores defined by laterally connected chevron GNRs, are demonstrated. C‐NPG FETs show excellent switching performance with on–off ratios exceeding 10⁴, which are tightly linked to the structural quality of C‐NPG. The devices operate as p‐type transistors in the air, while n‐type transport is observed when measured under vacuum, which is associated with reversible adsorption of gases or moisture. Theoretical analysis of charge transport in C‐NPG is also performed through electronic structure and transport calculations, which reveal strong conductance anisotropy effects in C‐NPG. The present study provides important insights into the design of high‐performance graphene‐based electronic devices where ballistic conductance and conduction anisotropy are achieved, which could be used in logic applications, and ultra‐sensitive sensors for chemical or biological detection.