The objective of this award is to optimize the growth process of semiconductor nanowires (NWs) by modeling the interrelationship between their growth process variables, structural defects, and mechanical properties, so that reliable NW-based devices with fewer defects can be produced. A double-loop framework will be investigated in this research, which links NW defects and the reliability of NW-based devices for the first time. The fundamental questions to be answered are: (1) How to systematically establish the relationship between the process variables, the generation rates of different NW defects, and the reliability of NW-based devices? (2) How to expedite the reliability prediction for NW-based devices and use the achieved reliability information to perform the application-centric defect reduction through the manipulation of the NW growth process? Specifically, we will (1) model the stochastic generation process of NW defects that link the generation of different types of defects to the NW growth-process variables; (2) develop a statistical fracture model for NWs with various defects under mechanical loading; (3) explore an advanced accelerated testing methodology and optimize the NW growth process by the optimal experimental design methods; and (4) conduct validation studies based on the proposed methodology by developing benchmark NW-based nanodevices, and demonstrate their desired reliability performance.

If successful, this research will facilitate today's fast-paced technological advancements that are continually faced with increasing needs for cost-effective product-development technologies. It will result in an appealing practice that helps resolve common fabrication problems in a wide spectrum of nanomaterials/device development processes. It is expected that a systematic process optimization approach for the development of highly reliable NW-based devices, instead of trial-and-error approaches that are currently used in the field of nanomanufacturing, will be achieved. Moreover, the educational initiatives will strengthen the related programs at the two collaborative institutions, which will impact a large number of on-campus and nationwide distance students. The research result will also be broadly disseminated through technical publications, workshops, short courses, and K-12 outreach program.

Project Start
Project End
Budget Start
2012-01-06
Budget End
2015-08-31
Support Year
Fiscal Year
2012
Total Cost
$168,000
Indirect Cost
Name
University of Arizona
Department
Type
DUNS #
City
Tucson
State
AZ
Country
United States
Zip Code
85719