A fundamental link between two counterintuitive phenomena in spin glasses— reentrance and temperature chaos—has been mathematically proven for the first time. By extending the Edwards–Anderson model to include correlated disorder, researchers at Science Tokyo and Tohoku University provided the first rigorous proof that reentrance implies temperature chaos. The breakthrough enhances understanding of disordered systems and could advance applications in machine learning and quantum technologies, where controlling disorder and errors is crucial.

A review article published by the Fudan University presented the most recent progress for these purposes, with an emphasis on material properties such as foreign body response, on integration schemes with biological tissues, and on their use as bioelectronic platforms.

The new review paper, published on Apr. 29 in the journal Cyborg and Bionic Systems, summarized an envisioned applications involve advanced implants for brain, cardiac, and other organ systems, with capabilities of bioactive materials that offer stability for human subjects and live animal models.

A research paper by scientists at Tianjin University introduces background electroencephalogram (EEG) mixing (BGMix), a novel data augmentation technique grounded in neural principles that enhances training samples by replacing background noise between different classes.

The new research paper, published on Oct. 07, 2025 in the journal Cyborg and Bionic Systems, introduced a novel EEG augmentation method and a new approach to designing deep learning models informed by the neural processes of EEG.

A research paper by scientists at the Beijing Institute of Technology proposed a SnS₂-based in-sensor reservoir that offers an effective solution for detecting a variety of motion types at sensory terminals. By leveraging in-sensor reservoir computing, the device excels at classifying different motions across a wide velocity spectrum, providing a novel and promising method for motion recognition.

The new research paper, published on Sep. 30 in the journal Cyborg and Bionic Systems, presented an optoelectronic in-sensor RC device based on monolayer SnS₂ synthesized via the chemical vapor deposition (CVD) technique. This device demonstrates a notable correlation between its optic response and the duration of illumination, exhibiting excellent optical detection performance under short light illumination. Under long illumination, the sustained optic response can be used to simulate synaptic plasticity.