The H- and T-phases of MA ₂ Z ₄ structures, elemental composition and high-throughput screening process.

This study proposes ConditionCDVAE+, a crystal diffusion variational autoencoder (CDVAE) based deep generative model for inverse design of van der Waals (vdW) heterostructures. To address the challenges of traditional experimental methods relying on trial-and-error and existing models struggling to incorporate target property constraints, this work achieves breakthroughs through three innovative stages: (1) introduce the SE(3)-equivariant graph neural network EquiformerV2 as the encoder-decoder within the CDVAE framework to enhance the generation quality of the model; (2) design a module integrating Low-rank Multimodal Fusion and Generative Adversarial Networks to map properties and structures into a joint latent space; and (3) for the first time propose a generative model for the vdW heterostructures, by conducting experimental validation on the dataset constructed from Janus III–VI vdW heterostructures. Experiments demonstrate that ConditionCDVAE+ achieves optimal root mean square error for crystal reconstruction, with improved generation quality. Density Functional Theory calculations confirms 99.51% of generated samples converge to energy minima, indicating superior ground-state convergence. The effectiveness of the model under conditional guidance has also been extensively validated. This framework provides an efficient solution for target-oriented design of vdW heterostructures and holds promise for accelerating the development of novel optoelectronic devices.

We systematically investigated the morphology-controlled synthesis of Cu₂O micro-nano crystals, especially under surfactant-free conditions, targeting a simple, rapid, and morphologically controllable preparation strategy for polyhedral Cu₂O micro-nano crystals. By systematically investigating the effects of NaOH concentration, types of reducing agents, and copper salt precursors on crystal growth, precise control over the morphology of Cu₂O crystals under surfactant-free conditions was achieved. This method can rapidly prepare variously faceted Cu₂O crystals under mild conditions (70 °C, 7 min), including regular polyhedra with low-index facets exposure including cubes, octahedra and rhombic dodecahedra, as well as more complex polyhedra with high-index facets exposure such as 18-faceted, 26-faceted, 50-faceted and 74-faceted crystals. NaOH concentration is found to be the key factor in controlling Cu₂O crystal morphology: as the concentration of NaOH increases, the morphology of Cu₂O crystals gradually transforms from cubes that fully expose the {100} faces to regular polyhedra that expose the {110}, {111} faces, and even other high-index faces, ultimately presenting octahedra that fully expose the {111} faces. Additionally, Cu₂O crystals with unique morphologies such as hollow cubes and 18-faceted with {110} face etched can be obtained by introducing surfactants or prolonging reaction durations. This work provides new insights into the morphology control of Cu₂O crystals and establishes foundation in acquiring distinct Cu₂O polyhedra in a facile manner for their application in catalysis, optoelectronics, sensing, and energy conversion fields.