New study suggests chiral skyrmion flows can be used for logic devices
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Nov-2025 01:11 ET (23-Nov-2025 06:11 GMT/UTC)
Magnetic skyrmions are particle-like objects that can be used as information carriers in memory and computing devices. Researchers from Waseda University recently studied the flow behaviors of many skyrmions in structured magnets and found that skyrmions can behave like chiral fluids. They proposed that fully developed skyrmion flows can be used for fluidics, which significantly reduces complexity of skyrmion logic, as it eliminates the need for deterministic creation, precise control, and detection of individual skyrmions.
A team led by Cleveland Clinic’s Kenneth Merz, PhD, and IBM’s Antonio Mezzacapo, PhD, is developing quantum computing methods to simulate and study supramolecular processes that guide how entire molecules interact with each other.
In their study, published in Nature Communications Physics, researchers focused on molecules’ noncovalent interactions, especially hydrogen bonding and hydrophobic species. These interactions, which involve attraction and repulsive forces between molecules or parts of the same molecule, play an important role in protein folding, membrane assembly and cell signaling.
A research paper by scientists at the City University of Hong Kong proposed a hybrid model-based and online data-driven control method for a tendon-driven continuum robot, which requires no prior dataset collection or training. The method incorporates the Jacobian derived from the piecewise constant curvature model with online Jacobian error compensation using a Kalman filter.
The new research paper, published on Aug. 7 in the journal Cyborg and Bionic Systems, presented an approach eliminates the need for offline dataset collection and training. Experiments conducted on a planar continuum manipulator demonstrate the effectiveness of the proposed method in improving tracking accuracy for both position and attitude. Additionally, the effects of various model parameters are analyzed through comparative experiments.Security researchers have developed the first functional defense mechanism capable of protecting against “cryptanalytic” attacks used to “steal” the model parameters that define how an AI system works.
Bentham Science’s new release, Sustainable Agriculture Applications Using Large Language Models, highlights the transformative impact of AI and LLMs on sustainable agriculture, from precision farming to efficient resource management.