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This article uses data from a natural experiment to address one of the most contentious issues in the on-demand platform economy—whether gig work is compatible with standard employment. We analyze a US-based package delivery platform that shifted a subset of its workers from independent contractors to employees, thereby creating a natural experiment that allowed us to exploit variation over time and across locations. We examine the impact of employment status on work scheduling practices, hours of work and the firm’s ability to match workers’ scheduled hours with the amount of time they were actively engaged in parcel delivery. We find that after the transition to employment, flexibility with respect to how work schedules were determined was maintained, and drivers’ total hours of work increased. We also find that the switch to employee status increased the firm’s ability to match scheduled and actual working time, indicating greater operational efficiency. We conclude, contrary to claims commonly made by platform firms, that employment status can coexist with the platform model.

 

Discovery of novel high-performance materials with earth-abundant and environmentally friendly elements is a key task for civil applications based on advanced thermoelectric technology. Advancements in this area are greatly limited by the traditional trial-and-error method, which is both time-consuming and expensive. The materials genome initiative can provide a powerful strategy to screen for potential novel materials using high-throughput calculations, materials characterization, and synthesis. In this study, we developed a modified diffusion-couple high-throughput synthesis method and an automated histogram analysis technique to quickly screen high-performance copper chalcogenide thermoelectric materials, which has been well demonstrated in the ternary Cu–Sn–S compounds. A new copper chalcogenide with the composition of Cu 7 Sn 3 S 10 was discovered. Studies on crystal structure, band gap, and electrical and thermal transport properties were performed to show that it is a promising thermoelectric material with ultralow lattice thermal conductivity, moderate band gap, and decent electrical conductivity. Via Cl doping, the thermoelectric dimensionless figure of merit zT reaches 0.8 at 750 K, being among the highest values reported in Cu–Sn–S ternary materials. The modified diffusion-couple high-throughput synthesis method and automated histogram analysis technique developed in this study also shed light on the development of other advanced thermoelectric and functional materials. 

Accurate indoor positioning has attracted a lot of attention for a variety of indoor location-based applications, with the rapid development of mobile devices and their onboard sensors. A hybrid indoor localization method is proposed based on single off-the-shelf smartphone, which takes advantage of its various onboard sensors, including camera, gyroscope and accelerometer. The proposed approach integrates three components: visual-inertial odometry (VIO), point-based area mapping, and plane-based area mapping. A simplified RANSAC strategy is employed in plane matching for the sake of processing time. Since Apple's augmented reality platform ARKit has many powerful high-level APIs on world tracking, plane detection and 3D modeling, a practical smartphone app for indoor localization is developed on an iPhone that can run ARKit. Experimental results demonstrate that our plane-based method can achieve an accuracy of about 0.3 meter, which is based on a much more lightweight model, but achieves more accurate results than the point-based model by directly using ARKit's area mapping. The size of the plane-based model is less than 2KB for a closed-loop corridor area of about 45m*15m, comparing to about 10MB of the point-based model. 

The strong and counterproductive interrelationship of thermoelectric parameters remains a bottleneck to improving thermoelectric performance, especially in polymer‐based materials. In this paper, a compositional range is investigated over which there is decoupling of the electrical conductivity and Seebeck coefficient, achieving increases in at least one of these two parameters while the other is maintained or slightly increased as well. This is done using an alkylthio‐substituted polythiophene (PQTS12) as additive in poly(bisdodecylquaterthiophene) (PQT12) with tetrafluorotetracyanoquinodimethane (F4TCNQ) and nitrosyl tetrafluoroborate (NOBF4) as dopants. The power factor increases two orders of magnitude with the PQTS12 additive at constant doping level. Using a second pair of polymers, poly(2,5‐bis(3‐dodecylthiophen‐2‐yl)thieno[3,2‐b]thiophene (PBTTTC12) and poly(2,5‐bis(3‐dodecylthiothiophen‐2‐yl)thieno[3,2‐b]thiophene, (PBTTTSC12), with higher mobilities, decoupling of the Seebeck coefficient and electrical conductivity is also observed and higher power factor is achieved. Distinguished from recently reported works, these two sets of polymers possess very closely offset carrier energy levels (0.05–0.07 eV), and the microstructure, assessed using grazing incidence X‐ray scattering, and mobility evaluated in field‐effect transistors, are not adversely affected by the blending. Experiments, calculations, and simulations are consistent with the idea that blending and doping polymers with closely spaced energy levels and compatible morphologies to promote carrier mobility favors increased power factors.