AI 中文总结
本研究提出将感官数据存储在导电聚合物树突互连强度中的进化电气系统，以神经启发电子鼻为模型，通过模拟验证其可降低高密度传感阵列制造复杂度，适用于新兴传感技术。
AI 中文摘要
如果电子学仅驱动电子为电极充电，那么自然系统则通过移动物质进行演化。固着生物的形态发生既可视为一种制造过程，也可视为一种运作机制。然而，在电子硬件中整合制造与功能编程并非传统做法。本研究以神经启发的电子鼻为模型，实验性实现了这种进化电气系统的概念，将感官数据的历史存储在传感元件的电气互连物理特性中。仅在挥发性分子暴露时触发，不同传感元件会瞬时且可逆地改变其阻抗，因此脉冲电压可实现导电聚合物树突的电化学生长。不断演化的互连强度与传感材料及所暴露挥发性分子的性质密切相关。树突生长仅在暴露于挥发性样本时发生，暴露中断后立即停止。还通过模拟网络架构评估了这种“被动记忆”的能力，结果表明，这种信息存储方式应能大幅降低高密度传感阵列的制造复杂度，同时切实实现其校准以对用户特定环境暴露进行分类。本研究证明，电子学中的记忆可像在生物体中一样与制造相关联，表明低材料资源和低能量激活可用于未来新兴传感技术的实际电子应用。
英文摘要
If electronics drives only electrons to charge electrodes, natural systems learn by moving matter to evolve. Morphogenesis in sessile organisms can be seen both as a fabrication process and as an operative mechanism. However, intricating manufacturing and programming functionalities in electronic hardware is not conventional. In this study, we experimentally implement such a concept of an evolutionary electrical system using a neuro-inspired electronic nose as a model, to store a history of sensory data in the physical properties of the electrical interconnects of sensing elements. Triggered only by volatile molecule exposures, different sensing elements change instantaneously and reversibly their impedance, so pulse voltages enable the electrochemical growth of conducting polymer dendrites. The strength of the evolving interconnects is specific to the sensing materials and to the nature of volatile molecules to which they are exposed. The dendritic growths occur exclusively when exposed to volatile samples, and stop immediately after interrupting the exposure. The capability of such "passive memory" was also assessed by simulating a network architecture, which showed that this way of storing information should greatly diminish the fabrication complexity of a highly dense sensing array while realistically enabling its calibration to classify user-specific environment exposures. By demonstrating that memory in electronics can be a concept linked to manufacturing like in living organisms, this study shows that low material resources and low energy activation can be exploited for practical electronic applications in future-emerging sensing technologies.
