Ba3FeS4Br: A 0D Iron-Based Chalcohalide with Unusual Magnetic Properties

Electronic Configurations of 3d Transition-Metal Compounds Using Local Structure and Neural Networks

Machine learning (ML) methods extract statistical relationships between inputs and results. When the inputs are solid-state crystal structures, structure-property relationships can be obtained. In this work, we investigate whether a simple neural network is able to learn the 3d orbital occupations for the transition-metal (TM) centers in crystalline inorganic solid-state compounds using only the local structure around the transition-metal centers described by rotationally invariant fingerprints based on spherical harmonics and one-hot elemental encoding. A multilayer neural network trained on density functional theory (DFT) results of about 1800 samples was developed and showed good performance in predicting the TM orbital occupations (for both spin channels). We study in detail how the local structure affects the predictions of the local properties and how they provide physical insights for the design of a future machine learning model for materials chemistry. The proposed ML method is illustrated in practical application by predicting local magnetic moments of the transition-metal atoms in a full set of inorganic structures with large unit cells. Although less accurate compared to the experimental data, the ML results compared well with the DFT results, suggesting the feasibility of electronic property prediction based only on structure input.

Pb3SBrI3: The first Pb-based chalcohalide with multiple halogens features unique two-dimensional structure composed of diverse Pb-centered polyhedra

Chalcohalides are attractive multifunctional material candidates due to their diverse crystal structures and the merits fused from chalcogenides and halides. Here, we successfully synthesized a new Pb-based chalcohalide with multiple-halogens,...

Crystal Growth, Structure, Resistivity, Magnetic, and Photoelectric Properties of One-Dimensional Selenometallate Ba2 BiFeSe5

Low-dimensional materials have attracted extensive research interest in recent years owing to their interesting structural chemistry and physical properties, which will greatly deepen our knowledge of these materials and could lead to additional breakthroughs in the future. Herein we have synthesized and characterized Ba₂ BiFeSe₅ , which adopts a quasi-one-dimensional structure and possesses some fascinating physical properties. The sharp divergences between the field-cooled (FC) and the zero-field-cooled (ZFC) data and the rather small magnetic moment per Fe³⁺ (0.07 μ_B ) strongly suggest that the title compound is weakly ferromagnetic with a high magnetic transition temperature above room temperature, which is controlled by competing super-exchange interactions within and between [FeBiSe₅ ]_∞ anionic ladders. Moreover, with its narrow bandgap of 0.95 eV, Ba₂ BiFeSe₅ shows photoelectric properties with a photocurrent density of approximately 30 mA cm² at 5 V. Our study demonstrates that Ba₂ FeBiSe₅ might be a new type of multifunctional material that deserves further investigation.