Modeling for COVID-19 college reopening decisions: Cornell, a case study.

We consider epidemiological modeling for the design of COVID-19 interventions in university populations, which have seen significant outbreaks during the pandemic. A central challenge is sensitivity of predictions to input parameters coupled with uncertainty about these parameters. Nearly 2 y into the pandemic, parameter uncertainty remains because of changes in vaccination efficacy, viral variants, and mask mandates, and because universities' unique characteristics hinder translation from the general population: a high fraction of young people, who have higher rates of asymptomatic infection and social contact, as well as an enhanced ability to implement behavioral and testing interventions. We describe an epidemiological model that formed the basis for Cornell University's decision to reopen for in-person instruction in fall 2020 and supported the design of an asymptomatic screening program instituted concurrently to prevent viral spread. We demonstrate how the structure of these decisions allowed risk to be minimized despite parameter uncertainty leading to an inability to make accurate point estimates and how this generalizes to other university settings. We find that once-per-week asymptomatic screening of vaccinated undergraduate students provides substantial value against the Delta variant, even if all students are vaccinated, and that more targeted testing of the most social vaccinated students provides further value.

Optimizing a Drone Network to Deliver Automated External Defibrillators.

BACKGROUND: Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest, but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an out-of-hospital cardiac arrest for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. METHODS: We applied our model to 53 702 out-of-hospital cardiac arrests that occurred in the 8 regions of the Toronto Regional RescuNET between January 1, 2006, and December 31, 2014. Our primary analysis quantified the drone network size required to deliver an AED 1, 2, or 3 minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as a large coordinated region. RESULTS: The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by 3 minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. CONCLUSIONS: An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an out-of-hospital cardiac arrest event.

Homogeneously dispersed multimetal oxygen-evolving catalysts.

Earth-abundant first-row (3d) transition metal-based catalysts have been developed for the oxygen-evolution reaction (OER); however, they operate at overpotentials substantially above thermodynamic requirements. Density functional theory suggested that non-3d high-valency metals such as tungsten can modulate 3d metal oxides, providing near-optimal adsorption energies for OER intermediates. We developed a room-temperature synthesis to produce gelled oxyhydroxides materials with an atomically homogeneous metal distribution. These gelled FeCoW oxyhydroxides exhibit the lowest overpotential (191 millivolts) reported at 10 milliamperes per square centimeter in alkaline electrolyte. The catalyst shows no evidence of degradation after more than 500 hours of operation. X-ray absorption and computational studies reveal a synergistic interplay between tungsten, iron, and cobalt in producing a favorable local coordination environment and electronic structure that enhance the energetics for OER.

Self-Assembled PbSe Nanowire:Perovskite Hybrids.

Inorganic semiconductor nanowires are of interest in nano- and microscale photonic and electronic applications. Here we report the formation of PbSe nanowires based on directional quantum dot alignment and fusion regulated by hybrid organic-inorganic perovskite surface ligands. All material synthesis is carried out at mild temperatures. Passivation of PbSe quantum dots was achieved via a new perovskite ligand exchange. Subsequent in situ ammonium/amine substitution by butylamine enables quantum dots to be capped by butylammonium lead iodide, and this further drives the formation of a PbSe nanowire superlattice in a two-dimensional (2D) perovskite matrix. The average spacing between two adjacent nanowires agrees well with the thickness of single atomic layer of 2D perovskite, consistent with the formation of a new self-assembled semiconductor nanowire:perovskite heterocrystal hybrid.

Colloidal Quantum Dot Photovoltaics Enhanced by Perovskite Shelling.

Solution-processed quantum dots are a promising material for large-scale, low-cost solar cell applications. New device architectures and improved passivation have been instrumental in increasing the performance of quantum dot photovoltaic devices. Here we report photovoltaic devices based on inks of quantum dot on which we grow thin perovskite shells in solid-state films. Passivation using the perovskite was achieved using a facile solution ligand exchange followed by postannealing. The resulting hybrid nanostructure created a more intrinsic CQD film, which, when incorporated into a photovoltaic device with graded bandstructure, achieved a record solar cell performance for single-step-deposited CQD films, exhibiting an AM1.5 solar power conversion efficiency of 8.95%.