Overcoming Variability in Printed RF: A Statistical Method to Designing for Unpredictable Dimensionality

Abstract

As additively manufactured radio frequency (RF) design expands towards higher frequencies, performance becomes ever more sensitive to print-induced dimensional variations. These slight deviations from design dimensions typically skew RF performance, resulting in low yields or poor device performance. In order to overcome this limitation, RF design paradigms must be developed for non-uniform process and material-specific variations. Therefore, a new generalized approach is developed to explore variation-tolerant designs for printed RF structures. This method evaluates the feature fidelity and S11 performance of micro-dispensed, X-band (8–12 GHz) patch antennas by evaluating the standard deviation in as-printed features, surface roughness, and thickness. It was found that the traditional designs based on optimal impedance matching values did not result in the most robust performance over multiple printing sessions. Rather, performance bounds determined by print deviation could be utilized to improve large-batch S11 results by up to 7dB. This work demonstrates that establishing the average standard deviation of printed dimensions in any RF printing system and following the formulated design procedure could greatly improve performance over large datasets. As such, the method defined here can be applied to improve large-scale, printed RF yields and enable predictive performance metrics for any given printing method.