Atomic Hydrogen Cleaning of Polarized GaAs Photocathodes

Atomic hydrogen cleaning followed by heat cleaning at 450$^\circ$C was used to prepare negative-electron-affinity GaAs photocathodes. When hydrogen ions were eliminated, quantum efficiencies of 15% were obtained for bulk GaAs cathodes, higher than the results obtained using conventional 600$^\circ$C heat cleaning. The low-temperature cleaning technique was successfully applied to thin, strained GaAs cathodes used for producing highly polarized electrons. No depolarization was observed even when the optimum cleaning time of about 30 seconds was extended by a factor of 100

Diffusive transport in networks built of containers and tubes

We developed analytical and numerical methods to study a transport of non-interacting particles in large networks consisting of M d-dimensional containers C_1,...,C_M with radii R_i linked together by tubes of length l_{ij} and radii a_{ij} where i,j=1,2,...,M. Tubes may join directly with each other forming junctions. It is possible that some links are absent. Instead of solving the diffusion equation for the full problem we formulated an approach that is computationally more efficient. We derived a set of rate equations that govern the time dependence of the number of particles in each container N_1(t),N_2(t),...,N_M(t). In such a way the complicated transport problem is reduced to a set of M first order integro-differential equations in time, which can be solved efficiently by the algorithm presented here. The workings of the method have been demonstrated on a couple of examples: networks involving three, four and seven containers, and one network with a three-point junction. Already simple networks with relatively few containers exhibit interesting transport behavior. For example, we showed that it is possible to adjust the geometry of the networks so that the particle concentration varies in time in a wave-like manner. Such behavior deviates from simple exponential growth and decay occurring in the two container system.Comment: 21 pages, 18 figures, REVTEX4; new figure added, reduced emphasis on graph theory, additional discussion added (computational cost, one dimensional tubes

In-depth description of Electrohydrodynamic conduction pumping of dielectric liquids: physical model and regime analysis

In this work, we discuss the fundamental aspects of Electrohydrodynamic (EHD) conduction pumping of dielectric liquids. We build a mathematical model of conduction pumping that can be applied to all sizes, down to microsized pumps. In order to do this, we discuss the relevance of the Electrical Double Layer (EDL) that appears naturally on nonmetallic substrates. In the process, we identify a new dimensionless parameter related to the value of the zeta potential of the substrate-liquid pair, which quantifies the influence of these EDLs on the performance of the pump. This parameter also describes the transition from EHD conduction pumping to electro-osmosis. We also discuss in detail the two limiting working regimes in EHD conduction pumping: ohmic and saturation. We introduce a new dimensionless parameter, accounting for the electric field enhanced dissociation that, along with the conduction number, allows us to identify in which regime the pump operates.Ministerio de Ciencia, Innovación y Universidades PGC2018-099217-B-I0

Class Attendance and Students’ Evaluations of Teaching: Do No-Shows Bias Course Ratings and Rankings?

Background: Many university departments use students’ evaluations of teaching (SET) to compare and rank courses. However, absenteeism from class is often nonrandom and, therefore, SET for different courses might not be comparable. Objective: The present study aims to answer two questions. Are SET positively biased due to absenteeism? Do procedures, which adjust for absenteeism, change course rankings? Research Design: The author discusses the problem from a missing data perspective and present empirical results from regression models to determine which factors are simultaneously associated with students’ class attendance and course ratings. In order to determine the extent of these biases, the author then corrects average ratings for students’ absenteeism and inspect changes in course rankings resulting from this adjustment. Subjects: The author analyzes SET data on the individual level. One or more course ratings are available for each student. Measures: Individual course ratings and absenteeism served as the key outcomes. Results: Absenteeism decreases with rising teaching quality. Furthermore, both factors are systematically related to student and course attributes. Weighting students’ ratings by actual absenteeism leads to mostly small changes in ranks, which follow a power law. Only a few, average courses are disproportionally influenced by the adjustment. Weighting by predicted absenteeism leads to very small changes in ranks. Again, average courses are more strongly affected than courses of very high or low in quality. Conclusions: No-shows bias course ratings and rankings. SET are more appropriate to identify high- and low-quality courses than to determine the exact ranks of average courses