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Tohoku University


New method puts a twist on creating efficient micromixers

Researchers at Tohoku University have developed a new method for creating efficient micromixers inside polymer fibers, enabling rapid mixing of minute amounts of liquid. The twisted microchannels fabricated using this method promote mixing even at low Reynolds numbers, making it suitable for various applications.

SourceTohoku University·JournalACS Applied Materials & Interfaces·DateSep 1, 2026

Six-legged robot learns to walk from a stick insect

Researchers trained AI on stick insect walking cycle to find optimal walking strategy, resulting in a six-legged robot that can navigate treacherous terrain and adapt to missing limbs. The approach allows for cheaper and faster robot production, enabling potential disaster response applications.

SourceTohoku University·JournalBioinspiration & Biomimetics·DateAug 27, 2026

Scientists repair damaged plastics at the molecular level, boosting recycling potential

Researchers at Tohoku University developed a method to restore the mechanical strength of degraded polybutylene terephthalate by repairing molecular chains with a chain extender. The technique recovers plastic tensile strength to nearly that of virgin material, enabling high-performance plastics to be reused instead of discarded.

SourceTohoku University·JournalComposites Part A Applied Science and Manufacturing·DateJul 28, 2026

Dreams drain energy: the REM sleep paradox

Researchers at Tohoku University discovered a paradox in REM sleep where the brain's energy molecule decreases despite an increase in fuel supply. This finding suggests that the brain dynamically adjusts its energy economy to support complex internal processing, revealing new insights into biological computation and sleep function.

SourceTohoku University·JournalCommunications Biology·DateJul 27, 2026

Rice grown on the Moon?

Researchers have developed a plasma technology that can produce nitrogen fertilizer suitable for cultivating rice seedlings under lunar conditions. The technology successfully neutralizes highly alkaline regolith and releases critical mineral nutrients, allowing plants to absorb them more readily.

SourceTohoku University·Journalnpj Microgravity·DateJun 29, 2026

Extending cryo-electron microscopy beyond water

Scientists at Tohoku University have developed a new sample-preparation technique called gradient blotting, allowing for the observation of materials in their native liquid environments. This breakthrough extends cryo-electron microscopy beyond water-based systems, enabling the study of materials under realistic processing conditions.

Spintronics p-computer ready for scale-up

A Japan-US collaborative team has developed the world's first integrated spintronic probabilistic bit on a silicon chip, paving the way for large-scale spintronic p-computers. The innovation addresses computational problems requiring parallel processing of enormous numbers of possible states.

SourceTohoku University·JournalIEEE Electron Device Letters·DateJun 2, 2026

Gold nanoparticles that behave like a liquid

A research team found that small changes in organic molecules on nanoparticle surfaces can trigger large-scale structural transformations. This discovery could provide a powerful method for tuning material properties and enable the development of smart and adaptive materials.

SourceTohoku University·JournalJournal of the American Chemical Society·DateMay 13, 2026

Nanoparticles overcome drug-resistant cancer via sequential drug release and photothermal therapy

Researchers have developed nanoparticles that sequentially disable the cancer cell's drug-expulsion mechanism and then release anticancer drugs, combined with photothermal therapy. This approach overcomes multidrug resistance and achieves complete tumor elimination in a mouse model, with no detectable toxicity to normal tissues.

SourceTohoku University·JournalJournal of Controlled Release·DateMay 8, 2026

Living brain cells enable machine learning computations

Researchers at Tohoku University demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task. The study integrates cultured neuronal networks into a machine learning framework, generating complex time-series signals comparable to those involved in motor control.

SourceTohoku University·JournalProceedings of the National Academy of Sciences·DateApr 2, 2026