Skip to main content
Duke University Libraries
DukeSpace Scholarship by Duke Authors
  • Login
  • Ask
  • Menu
  • Login
  • Ask a Librarian
  • Search & Find
  • Using the Library
  • Research Support
  • Course Support
  • Libraries
  • About
View Item 
  •   DukeSpace
  • Theses and Dissertations
  • Duke Dissertations
  • View Item
  •   DukeSpace
  • Theses and Dissertations
  • Duke Dissertations
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Multiplexing Techniques and Design-Automation Tools for FRET-Enabled Optical Computing

Thumbnail
View / Download
3.2 Mb
Date
2014
Author
Mottaghi, Mohammad
Advisor
Dwyer, Christopher L
Repository Usage Stats
304
views
230
downloads
Abstract

FRET-enabled optical computing is a new computing paradigm that uses the energy of incident photons to perform computation in molecular-scale circuits composed of inter-communicating photoactive molecules. Unlike conventional computing approaches, computation in these circuits does not require any electric current; instead, it relies on the controlled-migration of energy in the circuit through a phenomenon called Förster Resonance Energy Transfer (FRET). This, coupled with other unique features of FRET circuits can enable computing in new domains that are unachievable by the conventional semiconductor-based computing, such as in-cell computing or targeted drug delivery. In this thesis, we explore novel FRET-based multiplexing techniques to significantly increase the storage density of optical storage media. Further, we develop analysis algorithms, and computer-aided design tools for FRET circuits.

Existing computer-aided design tools for FRET circuits are predominantly ad hoc and specific to particular functionalities. We develop a generic design-automation framework for FRET-circuit optimization that is not limited to any particular functionality. We also show that within a fixed time-budget, the low-speed of Monte-Carlo-based FRET-simulation (MCS) algorithms can have a potentially-significant negative impact on the quality of the design process, and to address this issue, we design and implement a fast FRET-simulation algorithm which is up to several million times faster than existing MCS algorithms. We finally exploit the unique features of FRET-enabled optical computing to develop novel multiplexing techniques that enable orders of magnitude higher storage density compared to conventional optical storage media, such as DVD or Blu-Ray.

Type
Dissertation
Department
Computer Science
Subject
Computer science
Computer engineering
computer-aided design
data multiplexing
FRET-enabled optical computing
FRET network
FRET simulation algorithm
Optical storage density
Permalink
https://hdl.handle.net/10161/8658
Citation
Mottaghi, Mohammad (2014). Multiplexing Techniques and Design-Automation Tools for FRET-Enabled Optical Computing. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/8658.
Collections
  • Duke Dissertations
More Info
Show full item record
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

Rights for Collection: Duke Dissertations


Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info

Related items

Showing items related by title, author, creator, and subject.

  • Thumbnail

    Design Strategies for Efficient and Secure Memory 

    Lehman, Tamara Silbergleit (2019)
    Recent computing trends force users to relinquish physical control to unknown parties, making the system vulnerable to physical attacks. Software alone is not well equipped to protect against physical attacks. Instead software ...
  • Thumbnail

    A positioning QA procedure for 2D/2D (kV/MV) and 3D/3D (CT/CBCT) image matching for radiotherapy patient setup. 

    Guan, Huaiqun; Hammoud, Rabih; Yin, Fang-Fang (Journal of applied clinical medical physics, 2009-10-06)
    A positioning QA procedure for Varian's 2D/2D (kV/MV) and 3D/3D (planCT/CBCT) matching was developed. The procedure was to check: (1) the coincidence of on-board imager (OBI), portal imager (PI), and cone beam CT (CBCT)'s ...
  • Thumbnail

    Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images. 

    Prince, Eric W; Whelan, Ros; Mirsky, David M; Stence, Nicholas; Staulcup, Susan; Klimo, Paul; Anderson, Richard CE; ... (27 authors) (Scientific reports, 2020-10)
    Deep learning (DL) is a widely applied mathematical modeling technique. Classically, DL models utilize large volumes of training data, which are not available in many healthcare contexts. For patients with brain tumors, ...

Make Your Work Available Here

How to Deposit

Browse

All of DukeSpaceCommunities & CollectionsAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit DateThis CollectionAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit Date

My Account

LoginRegister

Statistics

View Usage Statistics
Duke University Libraries

Contact Us

411 Chapel Drive
Durham, NC 27708
(919) 660-5870
Perkins Library Service Desk

Digital Repositories at Duke

  • Report a problem with the repositories
  • About digital repositories at Duke
  • Accessibility Policy
  • Deaccession and DMCA Takedown Policy

TwitterFacebookYouTubeFlickrInstagramBlogs

Sign Up for Our Newsletter
  • Re-use & Attribution / Privacy
  • Harmful Language Statement
  • Support the Libraries
Duke University