Microsystems for Bioelectronics

Design secrets of an in carbo system ......................................................................................179

Heavier mass of information carrier ........................................................................................... 179

Utilization of ambient thermal energy ........................................................................................ 180

Flexible/on-demand 3D connections/routing .............................................................................. 180

Summary ............................................................................................................................................ 180

Appendix: Choice of probability values to maximize the entropy function ............................................... 181

List of symbols.................................................................................................................................... 182

References ......................................................................................................................................... 183

6.1 INTRODUCTION

In Chapters 2–5, scaling properties of essential units of autonomous electronic systems have been

investigated: energy sources, information processing (logic and memory), sensing, and communication.

The reader is now equipped with the quantitative estimates of performance parameters for each of the

above units, when the size of the unit is ~10

m

m. The next task is to assemble all units into an integrated

system and to analyze the performance of this in silico system, assuming a best case scenario.

It is intriguing to compare the ultimately scaled in silico systems with natural in carbo systems, i.e.

living cells. In fact, the living cell is an excellent example of a functioning micron-sized information-

processing system and it will be used as a benchmark for comparison with operation of a nanomorphic

cell, a micron-sized electronic system. Therefore, a goal of this chapter is to develop a framework for

estimating the information-processing capabilities both of a living cell and a nanomorphic cell.

As prerequisites for quantitative assessments of the in silico and the in carbo functional micro-

systems, theoretical models for information and information processors are introduced in this chapter.

Then the living cell is characterized as an information-processing system in the context of the theo-

retical framework of a Turing Machine and a von Neumann Universal Constructor.

The study of the living cell as a functional microsystem may help engineers understand the limits of

scaling for functional electronic systems and offer new insights that avoid some of the restrictions of

classical approaches to information-processing devices and architectures. Conversely, lessons from the

extremely scaled electronic systems may help biologists gain new insights on how cells function.

6.2 INFORMATION: A QUANTITATIVE TREATMENT

The concept of information has been discussed qualitati vely in Chapter 3, with respect to different infor-

mation carriers. In this section, a quantitative definition of information is introduced. The simplest special

BOX 6.1 IN SILICO AND IN CARBO SYSTEMS

In silico, in its original meaning, is a phrase used to mean ‘performed on computer’ in analogy to in vivo, which is

commonly used in biology and refers to processes occurring within living organisms. In this text, the expression in

silico is used in a broader sense, referring to different processes occurring in an electronic microsystem (which is to

a large extent made from silicon). This is in contrast to similar processes in living cells, which are to a large extent

made of carbon, thus being in carbo systems.

154 CHAPTER 6 Micron-sized systems: In carbo vs. in silico