Abstract
Quasi-random nanostructured material systems (NMSs) are emerging engineered material systems via cost-effective, scalable bottom-up processes, such as the phase separation of polymer mixtures or the mechanical self-assembly based on thin-film wrinkling. Current development of functional quasi-random NMSs mainly follows a sequential strategy without considering the fabrication conditions in nanostructure optimization, which limits the feasibility of the optimized design for large-scale, parallel nanomanufacturing using bottom-up processes. We propose a novel design methodology for designing quasi-random NMSs that employs spectral density function (SDF) to concurrently optimize the nanostructure and design the corresponding nanomanufacturing conditions of a bottom-up process. Alternative to the well-known correlation functions for characterizing the structural correlation of NMSs, the SDF provides a convenient and informative design representation to bridge the gap between processing-structure and structure-performance relationships, to enable fast explorations of optimal fabricable nanostructures, and to exploit the stochastic nature of manufacturing processes. In this paper, we first introduce the SDF as a non-deterministic design representation for quasi-random NMSs, compared with the two-point correlation function. Efficient reconstruction methods for quasi-random NMSs are developed for handling different morphologies, such as the channeltype and particle-type, in simulation-based design. The SDF based computational design methodology is illustrated by the optimization of quasi-random light-trapping nanostructures in thin-film solar cells for both channel-type and particle-type NMSs. Finally, the concurrent design strategy is employed to optimize the quasi-random light-trapping structure manufactured via scalable wrinkle nanolithography process.
| Original language | English |
|---|---|
| Title of host publication | 42nd Design Automation Conference |
| Publisher | American Society of Mechanical Engineers (ASME) |
| Volume | 2B-2016 |
| ISBN (Electronic) | 9780791850114 |
| DOIs | |
| Publication status | Published - 2016 |
| Event | ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016 - Charlotte, United States Duration: Aug 21 2016 → Aug 24 2016 |
Other
| Other | ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016 |
|---|---|
| Country | United States |
| City | Charlotte |
| Period | 8/21/16 → 8/24/16 |
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ASJC Scopus subject areas
- Mechanical Engineering
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Modelling and Simulation
Cite this
Characterization and design of functional Quasi-random nanostructured materials using spectral density function. / Yu, Shuangcheng; Zhang, Yichi; Wang, Chen; Lee, Won Kyu; Dong, Biqin; Odom, Teri W; Sun, Cheng; Chen, Wei.
42nd Design Automation Conference. Vol. 2B-2016 American Society of Mechanical Engineers (ASME), 2016.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Characterization and design of functional Quasi-random nanostructured materials using spectral density function
AU - Yu, Shuangcheng
AU - Zhang, Yichi
AU - Wang, Chen
AU - Lee, Won Kyu
AU - Dong, Biqin
AU - Odom, Teri W
AU - Sun, Cheng
AU - Chen, Wei
PY - 2016
Y1 - 2016
N2 - Quasi-random nanostructured material systems (NMSs) are emerging engineered material systems via cost-effective, scalable bottom-up processes, such as the phase separation of polymer mixtures or the mechanical self-assembly based on thin-film wrinkling. Current development of functional quasi-random NMSs mainly follows a sequential strategy without considering the fabrication conditions in nanostructure optimization, which limits the feasibility of the optimized design for large-scale, parallel nanomanufacturing using bottom-up processes. We propose a novel design methodology for designing quasi-random NMSs that employs spectral density function (SDF) to concurrently optimize the nanostructure and design the corresponding nanomanufacturing conditions of a bottom-up process. Alternative to the well-known correlation functions for characterizing the structural correlation of NMSs, the SDF provides a convenient and informative design representation to bridge the gap between processing-structure and structure-performance relationships, to enable fast explorations of optimal fabricable nanostructures, and to exploit the stochastic nature of manufacturing processes. In this paper, we first introduce the SDF as a non-deterministic design representation for quasi-random NMSs, compared with the two-point correlation function. Efficient reconstruction methods for quasi-random NMSs are developed for handling different morphologies, such as the channeltype and particle-type, in simulation-based design. The SDF based computational design methodology is illustrated by the optimization of quasi-random light-trapping nanostructures in thin-film solar cells for both channel-type and particle-type NMSs. Finally, the concurrent design strategy is employed to optimize the quasi-random light-trapping structure manufactured via scalable wrinkle nanolithography process.
AB - Quasi-random nanostructured material systems (NMSs) are emerging engineered material systems via cost-effective, scalable bottom-up processes, such as the phase separation of polymer mixtures or the mechanical self-assembly based on thin-film wrinkling. Current development of functional quasi-random NMSs mainly follows a sequential strategy without considering the fabrication conditions in nanostructure optimization, which limits the feasibility of the optimized design for large-scale, parallel nanomanufacturing using bottom-up processes. We propose a novel design methodology for designing quasi-random NMSs that employs spectral density function (SDF) to concurrently optimize the nanostructure and design the corresponding nanomanufacturing conditions of a bottom-up process. Alternative to the well-known correlation functions for characterizing the structural correlation of NMSs, the SDF provides a convenient and informative design representation to bridge the gap between processing-structure and structure-performance relationships, to enable fast explorations of optimal fabricable nanostructures, and to exploit the stochastic nature of manufacturing processes. In this paper, we first introduce the SDF as a non-deterministic design representation for quasi-random NMSs, compared with the two-point correlation function. Efficient reconstruction methods for quasi-random NMSs are developed for handling different morphologies, such as the channeltype and particle-type, in simulation-based design. The SDF based computational design methodology is illustrated by the optimization of quasi-random light-trapping nanostructures in thin-film solar cells for both channel-type and particle-type NMSs. Finally, the concurrent design strategy is employed to optimize the quasi-random light-trapping structure manufactured via scalable wrinkle nanolithography process.
UR - http://www.scopus.com/inward/record.url?scp=85007593558&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85007593558&partnerID=8YFLogxK
U2 - 10.1115/DETC2016-60118
DO - 10.1115/DETC2016-60118
M3 - Conference contribution
AN - SCOPUS:85007593558
VL - 2B-2016
BT - 42nd Design Automation Conference
PB - American Society of Mechanical Engineers (ASME)
ER -