Atomistic Probing of Defect-Engineered 2H-MoTe2 Monolayers.

Point defects dictate various physical, chemical, and optoelectronic properties of two-dimensional (2D) materials, and therefore, a rudimentary understanding of the formation and spatial distribution of point defects is a key to advancement in 2D material-based nanotechnology. In this work, we performed the demonstration to directly probe the point defects in 2H-MoTe2 monolayers that are tactically exposed to (i) 200 °C-vacuum-annealing and (ii) 532 nm-laser-illumination; and accordingly, we utilize a deep learning algorithm to classify and quantify the generated point defects. We discovered that tellurium-related defects are mainly generated in both 2H-MoTe2 samples; but interestingly, 200 °C-vacuum-annealing and 532 nm-laser-illumination modulate a strong n-type and strong p-type 2H-MoTe2, respectively. While 200 °C-vacuum-annealing generates tellurium vacancies or tellurium adatoms, 532 nm-laser-illumination prompts oxygen atoms to be adsorbed/chemisorbed at tellurium vacancies, giving rise to the p-type characteristic. This work significantly advances the current understanding of point defect engineering in 2H-MoTe2 monolayers and other 2D materials, which is critical for developing nanoscale devices with desired functionality.

Full automation of point defect detection in transition metal dichalcogenides through a dual mode deep learning algorithm.

Point defects often appear in two-dimensional (2D) materials and are mostly correlated with physical phenomena. The direct visualisation of point defects, followed by statistical inspection, is the most promising way to harness structure-modulated 2D materials. Here, we introduce a deep learning-based platform to identify the point defects in 2H-MoTe2: synergy of unit cell detection and defect classification. These processes demonstrate that segmenting the detected hexagonal cell into two unit cells elaborately cropped the unit cells: further separating a unit cell input into the Te2/Mo column part remarkably increased the defect classification accuracies. The concentrations of identified point defects were 7.16 × 1020 cm2 of Te monovacancies, 4.38 × 1019 cm2 of Te divacancies and 1.46 × 1019 cm2 of Mo monovacancies generated during an exfoliation process for TEM sample-preparation. These revealed defects correspond to the n-type character mainly originating from Te monovacancies, statistically. Our deep learning-oriented platform combined with atomic structural imaging provides the most intuitive and precise way to analyse point defects and, consequently, insight into the defect-property correlation based on deep learning in 2D materials.

Type-Independent 3D Writing and Nano-Patterning of Confined Biopolymers.

Biopolymers are essential building blocks that constitute cells and tissues with well-defined molecular structures and diverse biological functions. Their three-dimensional (3D) complex architectures are used to analyze, control, and mimic various cells and their ensembles. However, the free-form and high-resolution structuring of various biopolymers remain challenging because their structural and rheological control depend critically on their polymeric types at the submicron scale. Here, direct 3D writing of intact biopolymers is demonstrated using a systemic combination of nanoscale confinement, evaporation, and solidification of a biopolymer-containing solution. A femtoliter solution is confined in an ultra-shallow liquid interface between a fine-tuned nanopipette and a chosen substrate surface to achieve directional growth of biopolymer nanowires via solvent-exclusive evaporation and concurrent solution supply. The evaporation-dependent printing is biopolymer type-independent, therefore, the 3D motor-operated precise nanopipette positioning allows in situ printing of nucleic acids, polysaccharides, and proteins with submicron resolution. By controlling concentrations and molecular weights, several different biopolymers are reproducibly patterned with desired size and geometry, and their 3D architectures are biologically active in various solvents with no structural deformation. Notably, protein-based nanowire patterns exhibit pin-point localization of spatiotemporal biofunctions, including target recognition and catalytic peroxidation, indicating their application potential in organ-on-chips and micro-tissue engineering.

Spin-Orbit Torque Switching in an All-Van der Waals Heterostructure.

Current-induced control of magnetization in ferromagnets using spin-orbit torque (SOT) has drawn attention as a new mechanism for fast and energy efficient magnetic memory devices. Energy-efficient spintronic devices require a spin-current source with a large SOT efficiency (ξ) and electrical conductivity (σ), and an efficient spin injection across a transparent interface. Herein, single crystals of the van der Waals (vdW) topological semimetal WTe2  and vdW ferromagnet Fe3 GeTe2 are used to satisfy the requirements in their all-vdW-heterostructure with an atomically sharp interface. The results exhibit values of ξ ≈ 4.6 and σ ≈ 2.25 × 105  Ω-1 m-1 for WTe2 . Moreover, the significantly reduced switching current density of 3.90 × 106 A cm-2 at 150 K is obtained, which is an order of magnitude smaller than those of conventional heavy-metal/ferromagnet thin films. These findings highlight that engineering vdW-type topological materials and magnets offers a promising route to energy-efficient magnetization control in SOT-based spintronics.

Heteroepitaxial van der Waals semiconductor superlattices.

A broad range of transition metal dichalcogenide (TMDC) semiconductors are available as monolayer (ML) crystals, so the precise integration of each kind into van der Waals (vdW) superlattices (SLs) could enable the realization of novel structures with previously unexplored functionalities. Here we report the atomic layer-by-layer epitaxial growth of vdW SLs with programmable stacking periodicities, composed of more than two kinds of dissimilar TMDC MLs, such as MoS2, WS2 and WSe2. Using kinetics-controlled vdW epitaxy in the near-equilibrium limit by metal-organic chemical vapour depositions, we achieved precise ML-by-ML stacking, free of interlayer atomic mixing, which resulted in tunable two-dimensional vdW electronic systems. As an example, by exploiting the series of type II band alignments at coherent two-dimensional vdW heterointerfaces, we demonstrated valley-polarized carrier excitations-one of the most distinctive electronic features in vdW ML semiconductors-which scale with the stack numbers n in our (MoS2/WS2)n SLs on optical excitations.

Identification of Point Defects in Atomically Thin Transition-Metal Dichalcogenide Semiconductors as Active Dopants.

Selective doping in semiconductors is essential not only for monolithic integrated circuity fabrications but also for tailoring their properties including electronic, optical, and catalytic activities. Such active dopants are essentially point defects in the host lattice. In atomically thin two-dimensional (2D) transition-metal dichalcogenides (TMDCs), the roles of such point defects are particularly critical in addition to their large surface-to-volume ratio, because their bond dissociation energy is relatively weaker, compared to elemental semiconductors. In this Mini Review, we review recent advances in the identifications of diverse point defects in 2D TMDC semiconductors, as active dopants, toward the tunable doping processes, along with the doping methods and mechanisms in literature. In particular, we discuss key issues in identifying such dopants both at the atomic scales and the device scales with selective examples. Fundamental understanding of these point defects can hold promise for tunability doping of atomically thin 2D semiconductor platforms.

Comparative Effectiveness of Surface Functionalized Poly-ε-Caprolactone Scaffold and ß-TCP Mixed PCL Scaffold for Bone Regeneration.

Physio-chemical surface properties to biomaterial has been attention in tissue engineering due to their properties on cell adhesion, proliferation, and differentiation. The object of this study is to evaluate the preosteoblast biological response on physio-chemical surface-layered 3D PCL scaffold and 3D PCL/ß-TCP scaffold. 3D scaffolds were fabricated by FDM 3D printing. Physio-chemical surface of 3D scaffolds were prepared by oxygen plasma and amine plasma-polymerization, respectively. The results of this study demonstrated that amine plasma-treated 3D scaffold on adhesion, proliferation, and osteogenic differentiation of the MC3T3-E1 was significantly increased compared to the other scaffolds.