Combining materials science, artificial intelligence (AI), physical chemistry, and other
disciplines, materials informatics is continuously accelerating the vigorous development of …

Abstract Machine learning holds significant research potential in the field of nanotechnology,
enabling nanomaterial structure and property predictions, facilitating materials design and …

The practical development of Li|| S batteries is hindered by the slow kinetics of polysulfides
conversion reactions during cycling. To circumvent this limitation, researchers suggested the …

Accelerating the discovery of advanced materials is crucial for modern industries,
aerospace, biomedicine, and energy. Nevertheless, only a small fraction of materials are …

Lead-free ferroelectric ceramics are particularly prominent in the energy sector because of
their interesting multi-domain properties. In the present study, three supervised machine …

High-throughput abinitio calculations are the indispensable parts of data-driven discovery of
new materials with desirable properties, as reflected in the establishment of several online …

Spray drying (SD) is a unit operation that efficiently converts solutions or suspensions into
solid products in a simple, versatile, and continuous manner. It is widely used across various …

Despite many accessible AI models that have been developed, it is an open challenge to
fully exploit interpretable insights to enable effective materials design and develop materials …

Ab initio molecular dynamics (AIMD) is an important technique for studying ion transport
within solid electrolyte and interface effects between electrode and electrolyte, which is …

Efficient and precise characterization of material properties is critical in quantum mechanical
modeling. While Density Functional Theory (DFT) remains a foundational method for …