The developed highly sensitive micro-strain sensing technique differs from the existing strain mapping techniques, such as digital image correlation (DIC)/micro-Moiré techniques, in terms of working mechanism, by filling a technology gap that requires high spatial resolution while simultaneously maintaining a large field-of-view. The strain sensing mechanism relies on the scanning of a tightly focused laser beam onto the grating that is on the sample surface to detect the change in the diffracted beam angle as a result of the strain. Gratings are fabricated on the target substrates to serve as strain sensors, which carries the strain information in the form of variations in the grating period. The geometric structure of the optical system inherently ensures the high sensitivity for the strain sensing, where the nanoscale change of the grating period is amplified by almost six orders into a diffraction peak shift on the order of several hundred micrometers. It significantly amplifies the small signal measurements so that the desired sensitivity and accuracy can be achieved.
The important features, such as strain sensitivity and spatial resolution, for the strain sensing technique are investigated to evaluate the technique. The strain sensitivity has been validated by measurements on homogenous materials with well known reference values of CTE (coefficient of thermal expansion). 10 micro-strain has been successfully resolved from the silicon CTE extraction measurements. Furthermore, the spatial resolution has been studied on predefined grating patterns, which are assembled to mimic the uneven strain distribution across the sample surface. A resolvable feature size of 10 µm has been achieved with an incident laser spot size of 50 µm in diameter.
In addition, the strain sensing technique has been applied to a composite sample made of SU8 and silicon, as well as the microelectronic packages for thermal strain mappings.
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.