In this paper, polyethylenimine (PEI) and Chitosan were simultaneously one-step doped into silicon dioxide (SiO 2 ) nanoparticles to synthesize PEI/Chitosan/SiO 2 composite nanoparticles. The polymer PEI contained a large amount of amino groups, which can realize the amino functionalized SiO 2 nanoparticles. And, the good pore forming effect of Chitosan was introduced into SiO 2 nanoparticles, and the resulting composite nanoparticles also had a porous structure. In pH 7.4 phosphate buffer solution (PBS), the amino groups of PEI had positive charges, and therefore the fluorescein sodium dye molecule can be loaded into the channels of PEI/Chitosan/SiO 2 composite nanoparticles by electrostatic adsorption. Furthermore, utilizing the diversity of DNA molecular conformation, we designed a high sensitive controllable assembly of DNA gated fluorescent sensor based on PEI/Chitosan/SiO 2 composite nanoparticles as loading materials. The factors affecting the sensing performance of the sensor were investigated, and the sensing mechanism was also further studied.
Embodied intelligent tactile systems represent a groundbreaking paradigm for autonomous agents, facilitating dynamic perception and adaptation in unstructured environments. Traditional von Neumann architectures suffer from inefficiencies due to the separation of sensing and memory units, where mechanical relaxation is often overlooked as non-informative noise rather than utilized as a computational resource. The transition dynamics from mechanical stimulation to memory encoding and their potential in neuromorphic interactions remain largely unexplored. Here, we present a transformative breakthrough in the seamless integration of sensing and memory (SMI) within a single device through programmable tactile memory. Utilizing polyborosiloxane (PBS) filament networks with dynamically reversible boron-oxygen and hydrogen bonds, the design enhances adhesion and energy dissipation. It enables pressure-induced electrically readable memory states with tunable retention times (260 ms to 63.9 s) and 99.6% linearity, supporting applications, such as threshold triggering, biomimetic pain perception, and motion recognition. The SMI sensor's in-sensor memory and logic functions facilitate intelligent control, while its memory retention capabilities enable pain visualization and action-driven modulation. Additionally, the spatiotemporal tactile memory achieves high-precision motion recognition (98.33%) without relying on continuous time-series data. This work introduces a novel mechanism for constructing SMI devices, advancing the development of intelligent neuromorphic tactile systems.
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