In addition, there has been a huge demand for the collection and processing of the massive data generated in daily life due to various personalized portable devices.

The 4th industrial age, characterized by the Internet of Things and artificial intelligence (AI), has led to a substantial increase in data generation across electronic devices with a projected 170 (zettabyte) to be generated in 2025. These results are promising for the development of personalized wearable artificial neural systems in the future. Thus, a high classification accuracy of 95% is achieved without any noticeable performance degradation in the Modified National Institute of Standards and Technology. Based on the excellent flexibility of colorless polyimide substrates and thin-layered structures, the fabricated flexible neuromorphic synaptic devices exhibit superior long-term potentiation and long-term depression cyclic endurance performance, even when bent over 700 times or on curved surfaces with a diameter of 10 mm. Enabled by the sequential fabrication process of all layers, by excluding the transfer process, artificial van der Waals devices combined with the 2D-MoS 2 channel and LiSiO x solid electrolyte exhibit excellent neuromorphic synaptic characteristics with a nonlinearity of 0.55 and asymmetry ratio of 0.22. Herein, the development of an ultraflexible artificial-synaptic array device with concrete-mechanical cyclic endurance consisting of a novel heterostructure with an all-solid-state 2D MoS 2 channel and LiSiO x (lithium silicate) is demonstrated. Hardware systems enabling artificial neural networks while consuming low power and processing massive in situ personal data are essential for adaptive wearable neuromorphic edging computing.

Wearable electronic devices with next-generation biocompatible, mechanical, ultraflexible, and portable sensors are a fast-growing technology.

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