Efficient Synaptic Emulation and Ultralow Power Digital-Analog Conversion in Cellulose-Based Neural Devices through Molecular Polarization

Efficient hardware–cell communication is crucial in understanding cellular states and controlling cells, serving as a crucial pathway in advancing next-generation human–machine interfaces. Here, we propose an energy-efficient neural device based on natural cellulose, addressing limitations in conventional interface communication hardware, particularly concerning material biocompatibility and biological signal matching. The cellulose-based device effectively emulates the plasticity of biological synaptic connections and exhibits learning behavior under biograde voltage as low as 10 mV. Significantly, it demonstrates exceptional digital-to-analog conversion performance with a minimal power consumption of 0.1 nJ, facilitating efficient interface biological signal matching. Furthermore, a molecular-level model is introduced to elucidate the rotation of intramolecular polar bonds in cellulose induced by electrical stimulation. This rotation alters the material's relative dielectric constant, unveiling the digital-to-analog conversion ability and neuro-like behavior. The biocompatible cellulose-based device efficiently emulates synapses with its low-power signal conversion, holding promise for effective biological signal matching in brain–machine interfaces.