Given its interdisciplinary nature, nanomaterials research is conducted in a virtuous cycle. In this cycle, new materials are first synthesized, then characterized, and fit into and evaluated for appropriate applications, which in turn inform what type of new materials should be synthesized. Recently, with the advent of big data and machine learning, researchers are utilizing computational methods to aid in all aspects of this cycle. While covering all four aspects of the nanomaterials research cycle, my PhD work focuses specifically on kinked silicon nanowires with the aim of developing probes for bio-nano interfaces. Prior to introducing my PhD work, to give context and motivations, I outline how nanomaterials are used to sense and modulate biological interfaces, such as to read the signals from neuronal cells and to pace cardiac cells. While focusing on semiconducting nanomaterials’ applications in photo-induced bio-modulations, I point out the unique properties of nanomaterials, which make them suitable for such applications. In the remaining part of the thesis, I introduce my two main projects, in which I (1) synthesized multinucleated kinked silicon nanowires, and (2) developed a method of tracking the longitudinal rotation of a kinked silicon nanowire. In my synthesis project, I devise a way to grow ultra thin silicon nanowire branches by inducing the main nanowire catalysts to diffuse down the nanowire sidewall. More interestingly, I demonstrate how these thin nanowire branches are restructured to spheroids via an Ostwald ripening-like process. This new synthetic strategy will allow one to synthesize semiconducting nanowires with multiple regions of increased surface area along the nanowire long axis, opening the door to a variety of applications. In my tracking method development project, I first introduce the idea of utilizing the arm of the kinked nanowire to track the nanowire’s longitudinal orientation, and thus rotational motion along its long axis (i.e. rolling). Then, I explain the newly developed image analysis algorithms that can accurately and efficiently track the longitudinal orientation of the nanowire undergoing rolling. Finally, I demonstrate the use of the method in studying the nanowire interacting with a mammalian cell, suggesting the method’s ability to reflect different types of biological behavior. Collectively, these projects highlight all aspects of the cycle of nanomaterials research. I suggest how the multinucleated nanowire can serve as a more “complete” probe for tracking longitudinal rotation tracking.