Solution-processed ZnO nanoparticle thin films are widely used as the electron transport layers (ETLs) in quantum dot light-emitting diodes (QLEDs). While the ZnO nanoparticle (NP) synthesis process has been thoroughly optimized, very few studies have focused on exploring how the solvents for dispersing the NPs affect the film-forming process, which has profound effects on the film quality and functionality as ETLs. Herein, we present a comprehensive investigation on the impact of the dispersing agent on the materials and carrier transport properties of spin-coated ZnO NP thin films. The first four members of the alkanol family, which show considerably different viscosities and volatilities, were used in this study. ZnO NP thin films deposited with different alcohols were used as the ETLs of the QLED structure, and the optoelectronic performances of the devices are compared. Alcohols with high viscosity are found to cause NP agglomerations, which roughen the film surface and lead to significant leakage current. Nanocracks in the ZnO NP film are observed when a highly volatile solvent is used due to the vigorous bursts of vapor during solvent evaporation. Our results show that a proper solvent can improve the surface roughness and compactness of the solution-processed ZnO films and lead to a 30% difference in the current efficiency of QLEDs. The findings here clearly indicate the important roles of the dispersing agent in the formation of high-quality NP-based thin films, which can be an important guidance for achieving high performances in QLEDs as well as a variety of solution-based devices.
The impact of Automated Vehicles (AVs) on urban geography has been widely speculated, though there is little quantitative evidence in the literature to establish the magnitude of such effects. To quantify the impact of the greater precision of automated driving on the spatial efficiency of off-street parking facilities, we develop a mixed integer nonlinear model (solved via a branch-and-cut approach) and present comparisons against industry-standard requirements for human-driving operation. We demonstrate that gains on the order of 40-50% in spatial efficiency (parking spaces per unit area) are in principle achievable while ensuring that each parked vehicle is independently accessible. We further show that the large majority of these efficiency gains can be obtained under current automotive engineering practice in which only the front two wheels pivot. There is a need for standardized methods that take the parking supply of a city as an input and calculate both the aggregate (citywide) efficiency impacts of automated driving and the spatial distribution of the effects. This study is intended as an initial step towards this objective.
The study evaluates, in the context of freeway segments, the interaction between automated cars' kinematic capabilities and the standard legal requirement for the operator of an automobile to not strike items that are in its path (known as the 'Assured Clear Distance Ahead' criterion). The objective is to characterize the impacts of ACDA-compliant driving behavior on the system-level indicator of roadway-network capacity. We assess the barriers to automated cars operating non-ACDA-compliant driving strategies, develop a straightforward ACDAcompliant automated-driving model to analytically estimate freeway 'pipeline' capacity, compare this behavior to human drivers, and interpret quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty. We demonstrate that automated cars pursuing ACDA-compliant driving strategies would have distinctive ''fundamental diagrams'' (relationships between speed and flow). Our results suggest that such automated-driving strategies (under a baseline set of assumptions) would sustain higher flow rates at free-flow speeds than human drivers, however at higher traffic volumes the rate of degradation in speed due to congestion would be steeper. ACDA-compliant automated cars also would have a higher level of maximum-achievable throughput, though the impact on maximum throughput at free-flow speed depends on the specific interpretation of ACDA. We also present a novel quantification of the tradeoff between freeway-capacity and various degrees of safety (one failure in 100,000 events, one failure in 1,000,000, etc.) that explicitly accounts for the irreducible uncertainty in emergency braking performance, by drawing on empirical distributions of braking distance testing. Finally, we assess the vulnerability of ACDA-compliant automated cars to lateral 'cut-ins' by vehicles making lane changes. The paper concludes with a brief discussion of policy questions and research needs.
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