Summary Machine learning has been heavily researched and widely used in many disciplines. However, achieving high accuracy requires a large amount of data that is sometimes difficult, expensive, or impractical to obtain. Integrating human knowledge into machine learning can significantly reduce data requirement, increase reliability and robustness of machine learning, and build explainable machine learning systems. This allows leveraging the vast amount of human knowledge and capability of machine learning to achieve functions and performance not available before and will facilitate the interaction between human beings and machine learning systems, making machine learning decisions understandable to humans. This paper gives an overview of the knowledge and its representations that can be integrated into machine learning and the methodology. We cover the fundamentals, current status, and recent progress of the methods, with a focus on popular and new topics. The perspectives on future directions are also discussed.

We show a piezoelectric mechanism that effectively suppresses dendrite growth using a compliant piezoelectric film as a separator or coating. When an electrode surface starts to lose stability upon lithium deposition, any protrusion causes film stretching, generating a local piezoelectric overpotential that suppresses deposition on the protrusion. Lithium ions thus spontaneously deposit to a flat surface. By proposing a theory that couples electrochemistry and piezoelectricity, we quantify the suppression effect and growth morphology. We find that the dendrite-suppression capability is over 5 × 10 5 stronger than the limit of mechanical blocking by any separators or solid-state electrolytes. Surprisingly, the mechanism ensures deposition to form a flat surface even if the initial substrate surface has significant protrusions, suggesting its robustness and effectiveness against manufacturing defects. We show that the mechanism is so strong that even a weak piezoelectric material is highly effective, opening up a wide range of materials.