Quantum dots are semiconductor nanoparticles with their sizes much smaller than the bulk exciton Bohr radii of these materials. This brings the physical confinement of electronics into a quantum dot which can alter the energy levels of the quantum dot and tune its electronic bandgap. CQDs are solution-processed quantum dots that can be large-scale, low-temperature manufactured on lightweight flexible substrates, and CQDs have the potential for next-generation optoelectronics, including solar cells, photodetectors, LEDs, and lasers. In this field, we have obtained high quality CQD inks and applied them for printed CQD devices [Publication #42]. We have explored novel p-type PbS CQD based homojunction solar cells [Publication #47] and CQD materials for luminescent solar concentrators [Publication #53]. We also studied CQD photodetectors [Publication #37, 41, 47], and integrated CQDs on silicon for on-chip near-infrared light detection [Publication #49, 55, 58, 60]. We also contributed to two review papers [Publication #57, 61] in the field.
Micro-/photonics control the behavior of light using metallic and dielectric micro-/nanostructures, which can be applied in a wide variety of applications. In this area, we have produced cellulose nanocrystal:polymer hybrid optical diffusers achieving high haze and high transparent simultaneously. These optical diffusers have been proposed to improve the performance of Si solar cells [Publication #43] and the performance of white LEDs [Publication #46, 51]. Here our works enable integration of widely available materials and cost-effective fabrication for light management in photonic applications.
My expertise in micro-/nanophotonics also lead to great collaborations in developing various photonic devices. In a collaboration with our industrial partner, we first proposed to use an important property, volatility of chemicals, for hydrocarbon identification and analysis of each component in hydrocarbon mixtures, and successfully differentiated hydrocarbon mixtures consisting of up to three volatile components with only one carbon content difference and with volume percentage difference of less than 1% [Publication #38]. In another collaboration with Prof. Zhang in the Department of Chemical and Materials Engineering at the University of Alberta, we studied extraordinary focusing effect exhibited by a surface nanolens in an evanescent field [Publication #39], achieved tunable optical properties for surface microlens [Publication #44], and explored its application in water treatment [Publication #56].
Plastics are common materials in a wide range of applications in everyday life and are found everywhere. Although plastic waste can be recycled to reduce environmental impact and bring economic benefits to our life, plastic pollution becomes a serious issue that affects wildlife, wildlife habitat, and humans. Advances in technology can help to reduce plastic pollution by providing substitute materials – eco-friendly biodegradable polymers which are produced from natural products. Therefore, cellulose nanocrystal (CNCs) and lignin, wood-derived eco-friendly materials, start to attract a great attention in academia and industry for their properties of high tensile strength, low density, low thermal expansion, and non-toxicity. Recently, we demonstrated the CNC-quantum dot luminescent films [Publication #53] for solar energy harvesting. Lignin can be used to produce graphene, and we have demonstrated the laser-induced graphene from lignin and applied it for pressure sensors [Publication #50]. CNC and lignin have strong emissivity in the wavelength region between 8 and 13 mm (the transparent window on Earth’s atmosphere, thus we have applied them for radiative cooling applications [Publication #52, 54].
The sensor is a device that detects events or changes in its environment, and send the information to other electronics for analysis. Over the past six years, we have developed various types of sensors for detecting physical input (i.e. pressure, strain, touch), light, and biological species using micro-/nanostructures and nanomaterials.
For physical sensors, we have showed methods to integrate micro-/nanostructured sensors for robotic applications [Publication #40]. We also applied nanomaterials (i.e. graphene, carbon nanotube) to make touch and pressure sensors [Publication #45, 50]. As shown in Contribution 1, we have demonstrated various CQD-based optical sensors including CQD-based photodiodes, on-chip near-infrared light sensors, and filter-free narrow-band photodetectors. These works are published in prestigious optics and/or nanotechnology journals, such as ACS Nano, ACS Photonics, Optics Letters, IEEE Journal of Selected Topics in Quantum Electronics. I have been working on biosensors since my PhD study with the thesis titled “Nano-electronic and nano-optic biosensing”. I co-supervised PhD students with Prof. Jie Chen, and works on biomolecular detection and cell manipulation using micro-/nanostructured devices [Publication #62, 65, 66].
Recently, deep learning has been applied in many photonic applications. Here, we focus on applying machine learning to improve the photonic design in white light-emitting diodes (LEDs). In our recent work [Publication #59], the developed forward neural network successfully predicts the two figure-of-merits (angular color uniformity and luminous flux) of white LEDs with high accuracy (percentage error < 1 %), and the inverse predicting model can rapidly design the structural parameters of the coating film according to the required figure-of-merits. Further explorations taking advantages of both the forward neutral network and the inverse predicting mode can effectively construct the coating layer for white LED modules to reach the best performance, and the results are verified with simulations. We also submitted two journal papers [TBD] about three-dimensional control of light in LEDs and apply it for applications in street lighting.