Spectral Barcoding of Quantum Dots: Deciphering Structural Motifs from the Excitonic Spectra
Self-assembled semiconductor quantum dots (QDs) show in high-resolution single-dot spectra a multitude of sharp lines, resembling a barcode, due to various neutral and charged exciton complexes. Here we propose the 'spectral barcoding' method that deciphers structural motifs of dots by using such barcode as input to an artificial-intelligence learning system. Thus, we invert the common practice of deducing spectra from structure by deducing structure from spectra. This approach (i) lays the foundation for building a much needed structure-spectra understanding for large nanostructures and (ii) can guide future design of desired optical features of QDs by controlling during growth only those structural motifs that decide given optical features.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 975403
- Journal Information:
- Physical Review. B, Condensed Matter and Materials Physics, Vol. 80, Issue 3, 2009; Related Information: Article No. 035328
- Country of Publication:
- United States
- Language:
- English
Similar Records
Determination of lateral size distribution of type-II ZnTe/ZnSe stacked submonolayer quantum dots via spectral analysis of optical signature of the Aharanov-Bohm excitons
Enhanced Emission from Bright Excitons in Asymmetrically Strained Colloidal CdSe/CdxZn1–xSe Quantum Dots