We propose a framework to analyze mm-wave baluns directly from physical parameters by adding a dimension of Machine Learning (ML) to existing electromagnetic (EM) methods. From a generalized physical model of mm-wave baluns, we train physical-electrical Machine Learning models that both accurately and quickly compute the electrical parameters of mm-wave baluns from physical parameters, reducing the need for full-wave simulations and advancing several aspects of mm-wave designs. One of the advancements is a fully automated design process that accurately generates full EM designs of mm-wave baluns when given an electrical specification and a metal option. The automated technique only takes several seconds to complete, compared to hours-weeks of the current trial-and-error methods, and notably the approach can optimize mm-wave baluns directly for the lowest metal loss. Another advancement is the theoretical interpretation of several high-level and abstract questions concerning mm-wave designs, in which we quantify the optimum transistor sizes for the last stage of a class-AB differential power amplifier on an on-chip process and derive the rule of thumb describing the inverse relationship between the optimum device sizes and mm-wave frequencies.

A review of the current status of integral equation and finite element (FEM) (including time domain) modeling as applied particularly to penetrable bodies is provided. The direct numerical solution of the appropriate frequency-domain partial differential equations is an alternative that has recently been the focus of much effort by the research community and appears to offer computational advantages over the integral equation formulations. These frequency-domain approaches require the solution of a matrix equation; the direct time-domain solution of partial differential equations offers a third formulation that does not require a matrix solution and may be more efficient for electrically large structures. The author summarizes the development of these modeling procedures and attempts to identify some of the unresolved issues associated with their development.>