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Alkali antimonide semiconductor photocathodes provide a promising platform for the generation of high-brightness electron beams, which are necessary for the development of cutting-edge probes, including x-ray free electron lasers and ultrafast electron diffraction. Nonetheless, to harness the intrinsic brightness limits in these compounds, extrinsic degrading factors, including surface roughness and contamination, must be overcome. By exploring the growth of CsxSb thin films monitored by in situ electron diffraction, the conditions to reproducibly synthesize atomically smooth films of CsSb on 3C–SiC (100) and graphene-coated TiO2 (110) substrates are identified, and detailed structural, morphological, and electronic characterization is presented. These films combine high quantum efficiency in the visible (up to 1.2% at 400 nm), an easily accessible photoemission threshold of 566 nm, low surface roughness (down to 600 pm on a 1 μm scale), and a robustness against oxidation up to 15 times greater than Cs3Sb. These properties lead us to suggest that CsSb has the potential to operate as an alternative to Cs3Sb in electron source applications where the demands of the vacuum environment might otherwise preclude the use of traditional alkali antimonides.

A primary goal of collective population behavior studies is to determine the rules governing crowd distributions in order to predict future behaviors in new environments. Current top-down modeling approaches describe, instead of predict, specific emergent behaviors, whereas bottom-up approaches must postulate, instead of directly determine, rules for individual behaviors. Here, we employ classical density functional theory (DFT) to quantify, directly from observations of local crowd density, the rules that predict mass behaviors under new circumstances. To demonstrate our theory-based, data-driven approach, we use a model crowd consisting of walking fruit flies and extract two functions that separately describe spatial and social preferences. The resulting theory accurately predicts experimental fly distributions in new environments and provides quantification of the crowd “mood”. Should this approach generalize beyond milling crowds, it may find powerful applications in fields ranging from spatial ecology and active matter to demography and economics.