Biomedical Engineering Reference
In-Depth Information
and dry processes (attrition, thermolysis, laser ablation, vapor deposition,
pyrolysis, and plasma arc discharge).
53
Table 11.7 provides an overview of
the manufacturing methods for nanomaterials, based on Steinfeldt et al.
30
This implies that rather than having product-specific life cycle inventories, it
would be more efficient and consistent to have production-pathway-specific
inventories for the manufacturing stage, similar to current energy or raw
material production inventories. The inventory of the final product manu-
facture would then be composed of the inventory for the particle production
and possible enhancements via surface activation or functionalization plus
the integration into the final product.
To achieve this goal for nanomaterial production processes, one promis-
ing approach could be to generate gate-to-gate LCI modules following the
method described for chemical engineering processes by Jimenez-Gonzalez
et al.
91
and Ponder and Overcash.
92
The method consists of (i) selecting the
process with consideration of the industrial importance and the access to
representative, up-to-date data; (ii) defining the process by its mass flow, the
substances it uses, the reactions it involves, and the conditions under which it
operates; (iii) determining the mass balance of the system, that is, calculating
the inputs and outputs (including losses) for the process; and (iv) identifying
the energy requirements and losses of the process. Eventually, the analysis
of the system can lead to building a parameterized module, in which inputs
and outputs are made dependent on the conditions of operations, for exam-
ple, the energy-related emissions being correlated to the temperature set in
the reaction chamber.
If applied to nanomaterial production, for example, to the techniques dis-
played in Table 11.7, such approach would bring a number of benefits as it
would enable to investigate what process changes could have the greatest
impact on raw materials, energy consumption, and emissions. Dealing with
immature technologies, this can help to quickly move to more optimized
processes. The parameterization of the module would also allow for defining
life cycle inventories that are specific to the properties of the manufactured
nanomaterials. For example, it could link the energy requirements and pro-
cess emissions to the grade of the produced nanomaterial, that is, its degree
of purity, which is typically imposed by its type of application and very often
turn out to be the source of highly increased energy requirements if a high
degree is needed (e.g., fullerenes used in organic solar cells
21
). Finally, until
reliable measurements can be used, a qualitative or semiqualitative assess-
ment of the potential releases of nanoparticles could be linked to the produc-
tion intensity within each module, for example, increased risks of releases as
a consequence of increased replacements of air filters when the productivity
of the process is increased and leads to more waste generation. In their quali-
tative discussion of the potential for nanoparticle emissions during each of
the seven manufacturing pathways, Steinfeldt et al.
30
pointed out that pro-
duction methods taking place in gaseous media induce a higher potential of
nanoparticle releases—see Table 11.7.
