Introduction

Today, nanoscience promises to provide an overwhelmingly large number of experimentally accessible ways to configure the spatial position of atoms, molecules, and other nanoscale components to form devices. The central challenge of nano-technology is to find the best, most practical, configuration that yields a useful device function. In the presence of what will typically be an enormous non-convex search space, it is reasonable to assume that traditional ad hoc design methods will miss many possible solutions. One approach to solving this difficult problem is to employ machine-based searches of configuration space that discover user-defined objective functions. Such an optimal design methodology aims to identify the best broken-symmetry spatial configuration of metal, semiconductor, and dielectric that produces a desired response. Hence, by harnessing a combination of modern computer power, adaptive algorithms, and realistic physical models, it should be possible to seek robust, manufacturable designs that meet previously unobtainable system specifications. Ultimately one can envision a design process that simultaneously is capable of basic scientific discovery and engineering for technological applications.

This is the frontier of device engineering we wish to explore.

The past success of ad hoc design

For many years an ad hoc approach to device design has successfully contributed to the development of technology. For example, after identifying the cause of poor device performance one typically tries to create a solution by modifying a process or fabrication step. The result is usually a series of innovations heavily weighted towards incremental, and hence small, changes in previous practice.

Introduction

The theme of this book is driven by an attempt to exploit system-level complexity that can exist in small devices and quantum systems. The approach adopted involves development of realistic physical models with enough richness in the solutions to allow for discovery of nonintuitive designs. The methodology utilizes a systematic numerical search of solution space to find unexpected behavior. This might include exponential sensitivity, super linearity, polynomial response, or some other desired objective. Obviously, possible future directions of this strategy could be very broad in scope. To narrow the options and help identify a productive path forward it serves to consider some examples that help illustrate the concepts. One way this can be done is by addressing the question of device scaling. That is, what happens when a device is reduced in size.

When electronic and photonic systems are made very small they behave differently. Because we now have access to vast amounts of inexpensive computing power it is possible to find out how these small, but fundamentally complex, systems work, explore differences compared to larger scale systems, and possibly identify opportunities for innovation in the way small systems are designed.

Future directions for research can be guided in part by understanding how small devices and small physical systems differ in their behavior compared to larger systems. One theme that emerges is the increased role fluctuations play in determining the behavior of small complex systems comprising multiple interacting elements. The example of complexity in a small laser diode is discussed in Section 8.2. Another theme is the increased sensitivity scaled devices have to defects and small changes in configuration.