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Within the last years, Q CELLS has developed a silicon solar cell structure yielding an energy conversion efficiency exceeding 24%. The cell structure features a so-called passivating contact consisting of an interfacial oxide and an n-type polysilicon layer on the rear side, double-sided screen-printed metal contacts, a module-optimized anti-reflective coating, a homogeneous front-side emitter, and an n-type silicon substrate. For the fabrication of this type of solar cell, a lean processing sequence has been applied by using exclusively mass-production processes in Q CELLS’ pilot R&D line in Thalheim, Germany. For module integration, state-of-the-art technology, such as half-cells, multi-wire interconnection, standard encapsulants, and zero-gap technology, can be applied. Hence, this solar cell structure has the potential to fully close the small remaining gap to the highest efficiency cell technologies, such as heterojunction and rear-contact solar cells at very competitive manufacturing cost. In analogy to Q CELLS' PERC-like Q.ANTUM technology, and in contrast to conventional passivated emitter and rear cells (PERC), this novel solar cell is shown to reliably suppress light-induced degradation.

Sparked by reports of insect declines of unexpected extent, there has been a surge in the compilation and analysis of insect time series data. While this effort has led to valuable databases, disagreement remains as to whether, where and why insects are declining. The ‘why’ question is particularly important because successful insect conservation will need to address the most important drivers of decline. Despite repeated calls for more long-term data, new time series will have to run for decades to quantitatively surpass those currently available. Here we argue that experimentation in addition to quantitative analysis of existing data is needed to identify the most important drivers of insect decline. While most potential drivers of insect population change are likely to have already been identified, their relative importance is largely unknown. Researchers should thus unite and use statistical insight to set up suitable experiments to be able to rank drivers by their importance. Such a coordinated effort is needed to produce the knowledge necessary for conservation action and will also result in increased monitoring and new time series.

This article outlines the theoretical foundations of the research contributions of this edited collection about "Diversity and Discrimination in Research Organizations." First, the sociological understanding of the basic concepts of diversity and discrimination is described and the current state of research is introduced. Second, national and organizational contextual conditions and risk factors that shape discrimination experiences and the management of diversity in research teams and organizations are presented. Third, the questions and research approaches of the individual contributions to this edited collection are presented.