2020.09.25 Press Release A Clearer View of What Makes Glass Rigid A team of scientists led by the University of Tokyo uses computer simulations to study the rigidity of amorphous solids like glass
2020.09.22 Press Release Having a Ball: Crystallization in a Sphere Researchers from The University of Tokyo and Fudan University observe the crystallization process in a droplet
2020.09.17 Press Release 0.5°C of additional warming has a huge effect on global aridity Based on models specifically designed to examine the difference between 1.5°C and 2°C of global warming, UTokyo researchers reveal major effects of the additional warming on drought in many regions of the world
2020.09.16 Events [NOTICE] Komaba Research Campus Japanese Language Course 2020 Winter(Course Period: October 12 - January 15)
2020.09.14 Press Release Painless paper patch test for glucose levels uses microneedles A patch of microneedles, each less than 1 mm in length, painlessly samples fluid from the skin and quickly reports glucose levels using a paper sensor with a color scale
2020.09.03 Events [EVENT] The 8th CMI Symposium "Aiming for Innovation in Aircraft Manufacturing Technology" will be held on Oct. 23, 2020
2020.07.02 Press Release Crystal Wars Researchers at The University of Tokyo and Fudan University use confocal microscopy to observe polymorphic crystallization in unprecedented detail
2020.06.17 Press Release Diabetic Mice Improve With Retrievable Millimeter-thick Cell-laden Hydrogel Fiber Researchers from The University of Tokyo discover that the diameter of fiber-shaped cell-laden hydrogel transplants determines their success in the treatment of type 1 diabetes mellitus
2020.06.14 Press Release Circular Reasoning: Spiraling Circuits for More Efficient AI Researchers from The University of Tokyo create a new integrated 3D-circuit architecture for AI applications with spiraling stacks of memory modules, which may help lead to specialized machine-learning hardware that uses much less electricity
2020.06.03 Press Release Get Excited by Neural Networks Scientists at The University of Tokyo use machine learning to predict the excited electronic states of materials—research that can accelerate both the characterization of materials as well as the formulation of new useful compounds