Optical Fingerprints of Upconversion Nanoparticles for Super-Capacity Multiplexing
- Publication Type:
- Thesis
- Issue Date:
- 2020
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This thesis includes six chapters.
Chapter 1 outlines the background knowledge and motivation relevant to the development of luminescence materials for optical multiplexing. The materials include fluorescence dyes, quantum dots, metal particles and upconversion nanoparticles (UCNPs). This thesis introduces different optical dimensions of UCNPs. The challenges associated with luminescence materials for multiplexing are approached. These sections detail the motivation for and the specific aims of the current study—that is, to tune the energy-transfer process in the core-shell UCNPs and to achieve the optical multiplexing of UCNPs in the spectral and lifetime orthogonal dimensions.
Chapter 2 provides detailed information on the materials, instruments and equipment, preparation and characterization methods.
Chapter 3 is the first research chapter, and it investigates the peak tuning of the excited state population of powder samples in Nd-Yb-Tm core-shell UCNPs. For the take-off of upconversion emissions, the duration can be extended from 100 μs to 900 μs after the 808 nm excitation is switched off. This strategy creates a set of time-resolved emission profiles over a large dynamic range, where they can be tuned from either the time of rising or decay.
Chapter 4 synthesizes two groups of UCNPs: Yb³⁺-Nd³⁺-Er³⁺ and Yb³⁺-Tm³⁺ core-shell UCNPs. This chapter outlines the systematic analysis (via the confocal microscope system) of the emission intensity/spectra and lifetimes of single UCNPs. Strategies to control the energy migration process and to arbitrarily tune the rising and decay times and the plateau moment are presented, where it is suggested a unique time-domain optical fingerprint can be assigned to each type of nanoparticles.
Chapter 5 outlines the finding that the nanoparticles show a unique lifetime signature under wide-field systems upon 976 nm (Yb³⁺-Tm³⁺ doped UCNPs) and 808 nm (Yb³⁺-Nd³⁺-Er³⁺ doped UCNPs) excitation. To achieve high-throughput multiplexing, the lifetime profiles can be detected under a wide-field microscope system. A novel method is also introduced here (i.e., deep learning) to decode the lifetime fingerprints of 14 batches of UCNPs. Through deep learning, the large amount of optical data from different batches of UCNPs allows the classification of each single UCNPs for the untapped opportunity to decode these nanoscale lifetime barcodes. The classification capability associated with deep learning allows all 14 kinds of UCNPs to achieve accuracies of over 90%.
Finally, the research results of this thesis are summarised in Chapter 6. Potential future developments and prospects regarding the multidimensional optical properties of UCNPs are discussed.
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