EXTENDED ABSTRACT: Invar alloy, known for its extremely low coefficient of thermal expansion, has significant demand and applications in fields such as precision instruments and precision molds. To effectively optimize and customize the performance of additively manufactured Invar alloy and its components, under the guidance of the materials genome engineering concept, we have developed a highthroughput intelligent research platform that integrates a forward product development system, automated experimental platform, and artificial intelligence data mining technology. The high-throughput experimental platform (including multi-material high-throughput preparation, high-throughput mechanical testing, highthroughput hardness testing, high-throughput densification testing, and high-throughput 3D scanning modules)
efficiently generates material big data (composition, process, densification, mechanics, hardness, printing accuracy, etc.). Using machine learning algorithms, the platform establishes composition-process-structure-performance mapping relationships. Through the high-throughput intelligent research platform, we successfully optimized the selective laser melting (SLM) process, developed high-performance Invar alloy composite materials, and established a structureperformance relationship model for Invar alloy superstructures. Based on this, we successfully fabricated lightweight Invar alloy molds, achieving a 60% weight reduction. This study significantly shortened the research and development cycle, reduced costs.

Keywords：high throughput testing; intelligent Lab;additive manufacturing; invar alloys;Metasturcture