The quest for new 2D ferroelectric materials continues to arouse interest. Based on first‐principles calculations, here, 2D ferroelectric properties in lead chalcogenides PbXs (X = S, Se, and Te) with a thickness of two atomic layers via strain engineering is demonstrated. Although these materials are stable in a rocksalt‐type cubic structure and are intrinsically nonferroelectric materials, an appropriate mechanical strain can readily activate a paraelectric to ferroelectric phase transition and induce in‐plane electric polarization in these atomic layers. The induced polarization magnitude can be as large as 1.90 × 10−10 C m−1 at a biaxial strain of ε = 4.0%, which is comparable in magnitude to that of ultrathin ferroelectric SnTe. The Curie temperature Tc of the materials is also estimated using effective Hamiltonian simulations. The origin of the emerged ferroelectric phase is attributed to softening of the polar mode with applied strain. In addition, the band gaps of the crystals are found to be tunable with applied strain, which can be adjusted to the ideal value of 1.3 eV for photovoltaic applications. The results not only provide a new route to explore ferroelectricity in 2D materials but also suggest promising semiconducting ferroelectrics for solar applications.

The optimal design of shape memory alloys (SMAs) with specific properties is crucial for the innovative application in advanced technologies. Herein, inspired by the recently proposed design concept of concentration modulation, we explore martensitic transformation (MT) in and design the mechanical properties of Ti-Nb nanocomposites by combining high-throughput phase-field simulations and machine learning (ML) approaches. Systematic phase-field simulations generate data of the mechanical properties for various nanocomposites constructed by four macroscopic degrees of freedom. An ML-assisted strategy is adopted to perform multiobjective optimization of the mechanical properties, through which promising nanocomposite configurations are prescreened for the next set of phase-field simulations. The ML-guided simulations discover an optimized nanocomposite, composed of Nb-rich matrix and Nb-lean nanofillers, that exhibits a combination of mechanical properties, including ultralow modulus, linear super-elasticity, and near-hysteresis-free in a loading-unloading cycle. The exceptional mechanical properties in the nanocomposite originate from optimized continuous MT rather than a sharp first-order transition, which is common in typical SMAs. This work demonstrates the great potential of ML-guided phase-field simulations in the design of advanced materials with extraordinary properties.

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This article is concerned with an initial‐boundary value problem (IBVP) for a new phase‐field model describing the evolution of structural phase transition in elastically deformable solid materials. The model consists of an elliptic‐parabolic system in which the displacement field and the order parameter both satisfy periodic boundary conditions. We prove the existence of global solutions to this IBVP by applying the method of continuation of local solutions and perform numerical simulations to investigate the microstructure evolution of MnNi alloys by using this new phase‐field model.