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Register a new userStructural phase transition in monolayer gold(I) telluride: From a room-temperature topologicalinsulator to an auxetic semiconductor
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Structural phase transitions between semiconductors and topological insulators have rich applications in nanoelectronics but are rarely found in two-dimensional (2D) materials. In this work, by combining ab initio computations and evolutionary structure search, we investigate two stable 2D forms of gold(I) telluride (Au$_{2}$Te) with square symmetry, noted as s(I)- and s(II)-Au$_{2}$Te. s(II)-Au$_{2}$Te is the global minimum structure and is a room-temperature topological insulator. s(I)-Au$_{2}$Te is a direct-gap semiconductor with high carrier mobilities and unusual in-plane negative Poissons ratio. Both s(I) and s(II) phases have ultra-low Youngs modulus, implying high flexibility. By applying a small tensile strain, s(II)-Au$_{2}$Te can be transformed into s(I)-Au$_{2}$Te. Hence, a structural phase transition from a room-temperature topological insulator to an auxetic semiconductor is found in the 2D forms of Au$_{2}$Te, which enables potential applications in phase-change electronic devices. Moreover, we elucidate the mechanism of the phase transition with the help of phonon spectra and group theory analysis.
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Diluted magnetic semiconductors including Mn-doped GaAs are attractive for gate-controlled spintronics but Curie transition at room temperature with long-range ferromagnetic order is still debatable to date. Here, we report the room-temperature ferromagnetic domains with long-range order in semiconducting V-doped WSe2 monolayer synthesized by chemical vapor deposition. Ferromagnetic order is manifested using magnetic force microscopy up to 360K, while retaining high on/off current ratio of ~105 at 0.1% V-doping concentration. The V-substitution to W sites keep a V-V separation distance of 5 nm without V-V aggregation, scrutinized by high-resolution scanning transmission-electron microscopy, which implies the possibility of the Ruderman-Kittel-Kasuya-Yoshida interaction (or Zener model) by establishing the long-range ferromagnetic order in V-doped WSe2 monolayer through free hole carriers. More importantly, the ferromagnetic order is clearly modulated by applying a back gate. Our findings open new opportunities for using two-dimensional transition metal dichalcogenides for future spintronics.
Dilute magnetic semiconductors, achieved through substitutional doping of spin-polarized transition metals into semiconducting systems, enable experimental modulation of spin dynamics in ways that hold great promise for novel magneto-electric or magneto-optical devices, especially for two-dimensional systems such as transition metal dichalcogenides that accentuate interactions and activate valley degrees of freedom. Practical applications of 2D magnetism will likely require room-temperature operation, air stability, and (for magnetic semiconductors) the ability to achieve optimal doping levels without dopant aggregation. Here we describe room-temperature ferromagnetic order obtained in semiconducting vanadium-doped tungsten disulfide monolayers produced by a reliable single-step film sulfidation method across an exceptionally wide range of vanadium concentrations, up to 12 at% with minimal dopant aggregation. These monolayers develop p-type transport as a function of vanadium incorporation and rapidly reach ambipolarity. Ferromagnetism peaks at an intermediate vanadium concentration of a few atomic percent and decreases for higher concentrations, which is consistent with quenching due to orbital hybridization at closer vanadium-vanadium spacings, as supported by transmission electron microscopy, magnetometry and first-principles calculations. Room-temperature two-dimensional dilute magnetic semiconductors provide a new component to expand the functional scope of van der Waals heterostructures and bring semiconducting magnetic 2D heterostructures them into the realm of practical application.
Quasi-one-dimensional (1D) materials provide a superior platform for characterizing and tuning topological phases for two reasons: i) existence for multiple cleavable surfaces that enables better experimental identification of topological classification, and ii) stronger response to perturbations such as strain for tuning topological phases compared to higher dimensional crystal structures. In this paper, we present experimental evidence for a room-temperature topological phase transition in the quasi-1D material Bi$_4$I$_4$, mediated via a first order structural transition between two distinct stacking orders of the weakly-coupled chains. Using high resolution angle-resolved photoemission spectroscopy on the two natural cleavable surfaces, we identify the high temperature $beta$ phase to be the first weak topological insulator with gapless Dirac cones on the (100) surface and no Dirac crossing on the (001) surface, while in the low temperature $alpha$ phase, the topological surface state on the (100) surface opens a gap, consistent with a recent theoretical prediction of a higher-order topological insulator beyond the scope of the established topological materials databases that hosts gapless hinge states. Our results not only identify a rare topological phase transition between first-order and second-order topological insulators but also establish a novel quasi-1D material platform for exploring unprecedented physics.
In multiferroic BiFeO3 thin films grown on highly mismatched LaAlO3 substrates, we reveal the coexistence of two differently distorted polymorphs that leads to striking features in the temperature dependence of the structural and multiferroic properties. Notably, the highly distorted phase quasi-concomitantly presents an abrupt structural change, transforms from a hard to a soft ferroelectric and transitions from antiferromagnetic to paramagnetic at 360+/-20 K. These coupled ferroic transitions just above room temperature hold promises of giant piezoelectric, magnetoelectric and piezomagnetic responses, with potential in many applications fields.
As machine learning becomes increasingly important in engineering and science, it is inevitable that machine learning techniques will be applied to the investigation of materials, and in particular the structural phase transitions common in ferroelectric materials. Here, we build and train an artificial neural network to accurately predict the energy change associated with atom displacements and use the trained artificial neural network in Monte-Carlo simulations on ferroelectric materials to investigate their phase transitions. We apply this approach to two-dimensional monolayer SnTe and show that it can indeed be used to simulate the phase transitions and predict the transition temperature. The artificial neural network, when viewed as a universal mathematical structure, can be readily transferred to the investigation of other ferroelectric materials when training data generated with ab initio methods are available.
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