  Interest in the thermodynamics of computation has revived in recent years,
driven by developments in science, economics and technology. Given the
consequences of the growing demand for computational power, the idea of
reducing the energy cost of computations has gained new importance.
Simultaneously, many biological networks are now interpreted as
information-processing or computational systems constrained by their underlying
thermodynamics. Indeed, some suggest that low-cost, high-density biological
systems may help to mitigate the rising demand for computational power and the
"end" of Moore's law of exponential growth in the density of transistors.
  In this chapter we address widespread misconceptions about thermodynamics and
the thermodynamics of computation. In particular, we will argue against the
general perception that a measurement or copy operation can be performed at no
cost, against the emphasis placed on the significance of erasure operations,
and against the careless discussion of heat and work. While not universal,
these misconceptions are sufficiently prevalent (particularly within
interdisciplinary contexts) to warrant a detailed discussion. In the process,
we will argue that explicitly representing fundamental processes is a useful
tool, serving to demystify key concepts.
  We first give a brief overview of thermodynamics, then the history of the
thermodynamics of computation - particularly in terms of copy and measurement
operations inherent to classic thought experiments. Subsequently, we analyse
these ideas via an explicit biochemical representation of the entire cycle of
Szilard's engine. In doing so we show that molecular computation is both a
promising engineering paradigm, and a valuable tool in providing fundamental
understanding.
