Type-II Colloidal Quantum Wells: CdSe/CdTe Core/Crown Heteronanoplatelets

Solution-processed quantum wells, also known as colloidal nanoplatelets (NPLs), are emerging as promising materials for colloidal optoelectronics. In this work, we report the synthesis and characterization of CdSe/CdTe core/crown NPLs exhibiting a Type-II electronic structure and Type-II specific optical properties. Here, based on a core-seeded approach, the CdSe/CdTe core/crown NPLs were synthesized with well-controlled CdTe crown coatings. Uniform and epitaxial growth of CdTe crown region was verified by using structural characterization techniques including transmission electron microscopy (TEM) with quantitative EDX analysis and X-ray diffraction (XRD). Also the optical properties were systematically studied in these Type-II NPLs that reveal strongly red-shifted photoluminescence (up to similar to 150 nm) along with 2 orders of magnitude longer fluorescence lifetimes (up to 190 ns) compared to the Type-I NPLs owing to spatially indirect excitons at the Type-II interface between the CdSe core and the CdTe crown regions. Photoluminescence excitation spectroscopy confirms that this strongly red-shifted emission actually arises from the CdSe/CdTe NPLs. In addition, temperature-dependent time-resolved fluorescence spectroscopy was performed to reveal the temperature-dependent fluorescence decay kinetics of the Type-II NPLs exhibiting interesting behavior. Also, water-soluble Type-II NPLs were achieved via ligand exchange of the CdSe/CdTe core/crown NPLs by using 3-mercaptopropionic acid (MPA), which allows for enhanced charge extraction efficiency owing to their shorter chain length and enables high quality film formation by layer-by-layer (LBL) assembly. With all of these appealing properties, the CdSe/CdTe core/crown heterostructures having Type-II electronic structure presented here are highly promising for light-harvesting applications

High Efficiency Colloidal Quantum Dot Infrared Light Emitting Diodes via Engineering at the Supra-Nanocrystalline Level

Colloidal quantum dot (CQD) light-emitting diodes (LEDs) deliver a compelling performance in the visible, yet infrared CQD LEDs underperform their visible-emitting counterparts, largely due to their low photoluminescence quantum efficiency. Here we employ a ternary blend of CQD thin film that comprises a binary host matrix that serves to electronically passivate as well as to cater for an efficient and balanced carrier supply to the emitting quantum dot species. In doing so, we report infrared PbS CQD LEDs with an external quantum efficiency of ~7.9% and a power conversion efficiency of ~9.3%, thanks to their very low density of trap states, on the order of 1014 cm−3, and very high photoluminescence quantum efficiency in electrically conductive quantum dot solids of more than 60%. When these blend devices operate as solar cells they deliver an open circuit voltage that approaches their radiative limit thanks to the synergistic effect of the reduced trap-state density and the density of state modification in the nanocomposite.Peer ReviewedPostprint (author's final draft

Highly flexible, electrically driven, top-emitting, quantum dot light-emitting stickers

Flexible information displays are key elements in future optoelectronic devices. Quantum dot light-emitting diodes (QLEDs) with advantages in color quality, stability, and cost-effectiveness are emerging as a candidate for single-material, full color light sources. Despite the recent advances in QLED technology, making high-performance flexible QLEDs still remains a big challenge due to limited choices of proper materials and device architectures as well as poor mechanical stability. Here, we show highly efficient, large-area QLED tapes emitting in red, green, and blue (RGB) colors with top-emitting design and polyimide tapes as flexible substrates. The brightness and quantum efficiency are 20 000 cd/m2 and 4.03%, respectively, the highest values reported for flexible QLEDs. Besides the excellent electroluminescence performance, these QLED films are highly flexible and mechanically robust to use as electrically driven light-emitting stickers by placing on or removing from any curved surface, facilitating versatile LED applications. Our QLED tapes present a step toward practical quantum dot based platforms for high-performance flexible displays and solid-state lighting. © 2014 American Chemical Society

DNA-Mediated Patterning of Single Quantum Dot Nanoarrays: A Reusable Platform for Single-Molecule Control

D.H. is financially supported by the Chinese Scholarship Council. We further gratefully acknowledge financial support from Queen Mary University of London

Developing an Indigenous cultural safety micro-credential: initial findings from a training designed for public health professionals in southern Ontario

Cultural safety training is a resource that healthcare institutions and staff can rely on to end anti-Indigenous racism in their organisations and to shift service providers’ attitudes, beliefs, and knowledge of Indigenous people. The aim of this study was to understand the initial knowledge and interest about Indigenous Peoples that a southern Ontario public health unit’s (PHU) staff hold. A cultural safety micro-credential project was developed in consultation with the PHU. An online survey was administered from January to March 2021 to those who were starting the micro-credential during this timeframe (n = 31). Thirty-one staff responded. A majority of the participants indicated that they had some knowledge of Indigenous Peoples and that this knowledge was relevant to their work. The number of interactions with Indigenous Peoples varied by role. Common themes for the open-ended responses included culture, relationships, and supports/services. Many of the open-ended responses highlighted feelings of not knowing enough and wanting to learn more about Indigenous Peoples. These results indicate a shift in attitudes, behaviours, and knowledge of Indigenous Peoples among the PHU staff. Cultural safety training can serve to address knowledge gaps and contribute to creating the systemic change needed to end anti-Indigenous racism in healthcare institutions

Fabrication of ZnO Thin Films from Nanocrystal Inks

Zinc oxide nanocrystals were prepared in ethanol and spin-cast to form semiconductor nanocrystal thin films that were thermally annealed at temperatures between 100 and 800 \ub0C. Particle size, monodispersity, and film porosity were determined by X-ray diffraction, ultraviolet-visible absorption spectroscopy, and spectroscopic ellipsometry, respectively. Film porosity rapidly decreased above 400 \ub0C, from 32% to 26%, which coincided with a change in electronic properties. Above 400 \ub0C, the ZnO electron mobility, determined from FET transfer characteristics, increased from 10-3 to 10-1 cm2 V s-1, while the surface resistivity, determined from electrical impedance, decreased from 107 to 103 \u3a9 m over the same temperature range. Below the densification point, nanoparticle core resistivity was found to increase from 104 to 106 \u3a9 m, which is caused by the increasing polydispersity in the quantized energy levels of the nanocrystals. From 100 to 800 \ub0C, crystallite size was found to increase from 5 to 18 nm in diameter. The surface resistance was decreased dramatically by passivation with butane thiol

Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System

BACKGROUND: Seizure prediction can increase independence and allow preventative treatment for patients with epilepsy. We present a proof-of-concept for a seizure prediction system that is accurate, fully automated, patient-specific, and tunable to an individual's needs. METHODS: Intracranial electroencephalography (iEEG) data of ten patients obtained from a seizure advisory system were analyzed as part of a pseudoprospective seizure prediction study. First, a deep learning classifier was trained to distinguish between preictal and interictal signals. Second, classifier performance was tested on held-out iEEG data from all patients and benchmarked against the performance of a random predictor. Third, the prediction system was tuned so sensitivity or time in warning could be prioritized by the patient. Finally, a demonstration of the feasibility of deployment of the prediction system onto an ultra-low power neuromorphic chip for autonomous operation on a wearable device is provided. RESULTS: The prediction system achieved mean sensitivity of 69% and mean time in warning of 27%, significantly surpassing an equivalent random predictor for all patients by 42%. CONCLUSION: This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance