Achieving Cost-Efficient Superalloy Powder Manufacturing Using Machine Learning

—Technique Efficiently Optimizes Complex Manufacturing Processes and May Reduce Aircraft Engine Component Production Costs—

Accelerating Thin Film Fabrication Processes Using Machine Learning

—Technique May Be Used to Reduce Materials Development Cost by Greatly Shortening the Trial-and-Error Process without Relying on External Data—

Development of a Multivalued Optical Memory Composed of Two-Dimensional Materials

Development of a Small Sensor Capable of Continuously Monitoring the Phytohormone Ethylene

—Technology May Allow Optimal Transportation and Storage of Fruits and Vegetables, Reducing Food Waste—

World's Best Magnetocaloric Material for H₂ Liquefaction discovered via Machine Learning

—A Step Forward for Enabling Efficient Hydrogen Liquefaction, Vital to the Development of a Hydrogen Society—

Chemical Reactions at Specific Molecular Sites under a Microscope

—Technique Enabling High-Precision Graphene Modification May Facilitate the Development of New Electronic Devices—

Formation of Black Rust Accelerates Bacteiral Iron Corrosion

—Discovery of Bacteria’s Ability to Extract Electrons without a Special Enzyme May Promote the Development of New Anti-Corrosion Materials—

Development of a Solid Material Capable of Slowly Releasing H₂S and NO

—Controlled Release Technology Will Facilitate Medical Use of Physiologically Active Gases—