Fitzgerald Lucy, Lopez Ruiz Luis, Zhu Joe, Lach John, Quinn Daniel
Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA.
Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA.
R Soc Open Sci. 2022 Sep 21;9(9):220895. doi: 10.1098/rsos.220895. eCollection 2022 Sep.
Piezoelectric materials are widely used to generate electric charge from mechanical deformation or vice versa. These strategies are increasingly common in implantable medical devices, where sensing must be done on small scales. In the case of a flow rate sensor, a sensor's energy harvesting rate could be mapped to that flow rate, making it 'self-powered by design (SPD)'. Prior fluids-based SPD work has focused on turbulence-driven resonance and has been largely empirical. Here, we explore the possibility of sub-resonant SPD flow sensing in a human airway. We present a physical model of piezoelectric sensing/harvesting in the airway, which we validated with a benchtop experiment. Our work offers a model-based roadmap for implantable SPD sensing solutions. We also use the model to theorize a new form of SPD sensing that can detect broadband flow information.
压电材料被广泛用于从机械变形中产生电荷,反之亦然。这些策略在可植入医疗设备中越来越普遍,因为在这些设备中必须在小尺度上进行传感。就流量传感器而言,传感器的能量收集速率可以映射到该流量,使其“设计上自供电(SPD)”。先前基于流体的SPD工作主要集中在湍流驱动的共振上,并且在很大程度上是经验性的。在这里,我们探讨了在人类气道中进行亚共振SPD流量传感的可能性。我们提出了气道中压电传感/收集的物理模型,并通过台式实验对其进行了验证。我们的工作为可植入SPD传感解决方案提供了基于模型的路线图。我们还使用该模型对一种能够检测宽带流量信息的新型SPD传感形式进行了理论推导。