Anticipatory LCA seeks to overcome the paucity of data through scenario development and thermodynamic bounding analyses. Critical components of anticipatory LCA include:
1) Laboratory-scale inventory data collection for nano-manufacturing processes and
preliminary performance evaluation.
2) Thermodynamic modeling of manufacturing processes and developing scenarios of
efficiency gains informed by analogous material processing industries.
3) Use-phase bounding to report inventory data in a functional unit descriptive of
performance.
Together, these analyses may call attention to environmentally problematic processes or nanotechnologies before significant investments in R&D and infrastructure contribute to technology lock in. The following case study applies these components of anticipatory LCA to single wall carbon nanotube (SWCNT) manufacturing processes, compares the rapid improvements in SWCNT manufacturing to historic reductions in the embodied energy of aluminum, and discusses the use of SWCNTs as free-standing anodes in advanced lithium ion batteries.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.