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FeTe1-xSex, a promising layered material used to realize Majorana zero modes, has attracted enormous attention in recent years. Pulsed laser deposition (PLD) and molecular-beam epitaxy (MBE) are the routine growth methods used to prepare FeTe1-xSex thin films. However, both methods require high-vacuum conditions and polished crystalline substrates, which hinder the exploration of the topological superconductivity and related nanodevices of this material. Here we demonstrate the growth of the ultrathin FeTe1-xSex superconductor by a facile, atmospheric pressure chemical vapor deposition (CVD) method. The composition and thickness of the two-dimensional (2D) FeTe1-xSex nanosheets are well controlled by tuning the experimental conditions. The as-prepared FeTe0.8Se0.2 nanosheet exhibits an onset superconducting transition temperature of 12.4 K, proving its high quality. Our work offers an effective strategy for preparing the ultrathin FeTe1-xSex superconductor, which could become a promising platform for further study of the unconventional superconductivity in the FeTe1-xSex system. © 2021 American Chemical Society.

Two-dimensional (2D) materials1–5 offer a unique platform from which to explore the physics of topology and many-body phenomena. New properties can be generated by filling the van der Waals gap of 2D materials with intercalants6,7; however, post-growth intercalation has usually been limited to alkali metals8–10. Here we show that the self-intercalation of native atoms11,12 into bilayer transition metal dichalcogenides during growth generates a class of ultrathin, covalently bonded materials, which we name ic-2D. The stoichiometry of these materials is defined by periodic occupancy patterns of the octahedral vacancy sites in the van der Waals gap, and their properties can be tuned by varying the coverage and the spatial arrangement of the filled sites7,13. By performing growth under high metal chemical potential14,15 we can access a range of tantalum-intercalated TaS(Se)y, including 25% Ta-intercalated Ta9S16, 33.3% Ta-intercalated Ta7S12, 50% Ta-intercalated Ta10S16, 66.7% Ta-intercalated Ta8Se12 (which forms a Kagome lattice) and 100% Ta-intercalated Ta9Se12. Ferromagnetic order was detected in some of these intercalated phases. We also demonstrate that self-intercalated V11S16, In11Se16 and FexTey can be grown under metal-rich conditions. Our work establishes self-intercalation as an approach through which to grow a new class of 2D materials with stoichiometry- or composition-dependent properties.

Reducing the lateral scale of two-dimensional (2D) materials to one-dimensional (1D) has attracted substantial research interest not only to achieve competitive electronic device applications but also for the exploration of fundamental physical properties. Controllable synthesis of high-quality 1D nanoribbons (NRs) is thus highly desirable and essential for the further study. Traditional exploration of the optimal synthesis conditions of novel materials is based on the trial-and-error approach, which is time consuming, costly and laborious. Recently, machine learning (ML) has demonstrated promising capability in guiding material synthesis through effectively learning from the past data and then making recommendations. Here, we report the implementation of supervised ML for the chemical vapor deposition (CVD) synthesis of high-quality 1D few-layered WTe2 nanoribbons (NRs). The synthesis parameters of the WTe2 NRs are optimized by the trained ML model. On top of that, the growth mechanism of as-synthesized 1T' few-layered WTe2 NRs is further proposed, which may inspire the growth strategies for other 1D nanostructures. Our findings suggest that ML is a powerful and efficient approach to aid the synthesis of 1D nanostructures, opening up new opportunities for intelligent material development.