Place and Time - Sustainable Design: The Science of Sustainability and Green Engineering - page 178

Table 4.3 Principles of Green Programs ( Continued )

Computational and Other

Principle Description Example Engineering Tools

Avoiding
chemical
derivatives

Avoid using blocking or
protecting groups or any
temporary modifications if
possible. Derivatives use
additional reagents and
generate waste.

Derivativization is a common analytical
method in environmental chemistry
(i.e., forming new compounds that
can be detected by chromatography).
However, chemists must be aware of
possible toxic compounds formed,
including leftover reagents that are
inherently dangerous.

Computational methods and natural
products chemistry can help scientists
start with a better synthetic framework.

Atom
economy

Design syntheses so that the
final product contains the
maximum proportion of
the starting materials.
There should be few, if
any, wasted atoms.

Single atomic- and molecular-scale logic
used to develop electronic devices
that incorporate design for
disassembly, design for recycling, and
design for safe and environmentally
optimized use.

The same amount of value (e.g.,
information storage and application) is
available on a much smaller scale. Thus,
devices are smarter and smaller, and
more economical in the long term.
Computational toxicology enhances the
ability to make product decisions with
better predictions of possible adverse
effects, based on logic.

Nanomaterials Tailor-make materials and
processes for specific
designs and intent at
the nanometer scale
( ≤ 100 nm).

Provide emissions, effluent, and other
environmental controls; design for
extremely long life cycles. Limits and
provides better control of production
and avoids overproduction (i.e., a
“throwaway economy”).

Use improved, systematic catalysis in
emission reductions (e.g., large sources
like power plants and small sources like
automobile exhaust systems). Zeolite
and other sorbing materials used in
hazardous waste and emergency response
situations can be better designed by
taking advantage of surface effects; this
decreases the volume of material used.

Selection of
safer
solvents and
reaction
conditions

Avoid using solvents,
separation agents, or other
auxiliary chemicals. If
these chemicals are
necessary, use innocuous
chemicals.

Supercritical chemistry and physics,
especially that of carbon dioxide and
other safer alternatives to halogenated
solvents are finding their way into the
more mainstream processes, most
notably dry cleaning.

To date, most of the progress as been the
result of wet chemistry and bench
research. Computational methods will
streamline the process, including quicker
scale-up.

Improved
energy
efficiencies

Run chemical reactions and
other processes at ambient
temperature and pressure
whenever possible.

To date, chemical engineering and other
reactor-based systems have relied on
“cheap” fuels and, thus have
optimized on the basis of
thermodynamics. Other factors (e.g.,
pressure, catalysis, photovoltaics,
fusion) should also be emphasized in
reactor optimization protocols.

Heat will always be important in reactions,
but computational methods can help
with relative economies of scale.
Computational models can test the
feasibility of new energy-efficient
systems, including intrinsic and extrinsic
hazards (e.g., to test certain scale-ups of
hydrogen and other economies). Energy
behaviors are scale-dependent. For
example, recent measurements of H 2 SO 4
bubbles when reacting with water have
temperatures in range of those found the
surface of the sun. b

( Continued )