Individual Differences and Contribution Sequences in Threshold Public Goods

Following the notion that organizations often face public good dilemmas when collective action is needed, we use a real-time provision-point mechanism to experimentally explore the process of achieving cooperative equilibria. Specifically, besides exploring group outcomes, we identify individual antecedents for the timing of the contribution to the public good. In addition, we study the role of different situational factors for sustaining high rates of cooperation: information about others' actions and the number of individuals necessary for public good provision. We find that contribution and implementation rates are relatively high, with only a moderate decline over time, and that social value orientation as well as several personality traits help to explain the observed contribution sequences

Professionalisierung von Grundschullehrkräften für das Unterrichtsfach Sport

Die Autoren arbeiten die Anforderungen an eine Professionalisierung von Grundschullehrkräften im Unterrichtsfach Sport heraus. Zur Konturierung dieser Anforderungen wird zum einen auf der Grundlage empirischer Befunde das Bewegungs-, Spiel- und Sportverhalten von Grundschulkindern näher beschrieben. Zum anderen wird das Konzept des Schulsports umrissen und die didaktischen Konzepte für den Sportunterricht in der Grundschule werden mit Blick auf daraus resultierende Anforderungen reflektiert. Auch die Biografie von Sportlehrkräften wird hinsichtlich der Bedeutung für Professionalisierungsprozesse in den Blick genommen. (DIPF/Orig.

Heterogeneity of Graphite Lithiation in State‐of‐the‐Art Cylinder‐Type Li‐Ion Cells

The two‐dimensional lithium distribution in the graphite anode was non‐destructively probed by spatially resolved neutron diffraction for a batch consisting of 34 different cylinder‐type (18650) Li‐ion batteries in fully charged state. The uniformity of the lithium distribution was quantified and correlated to the cell specifications/electrochemistry and to intrinsic cell parameters like electrode thickness, position of current collectors, etc. which were obtained by X‐ray micro‐computed tomography. Non‐uniformities in the lithiation state of the anode from a constant plateau have been observed for the majority of the studied cells. Their location corresponds to the positions of current tabs connecting the electrode stripes and areas of incomplete electrode coating at the beginning and the end of the electrode stripes. Four commonly used schemes of current lid connection were identified. Each of them displays its own effect on the uniformity of the lithiation at the anode and, therefore, variation of the intrinsic state‐of‐charge distribution and, most probably, the ageing behavior of the electrodes

Powder diffraction computed tomography: A combined synchrotron and neutron study

Diffraction and imaging using x-rays and neutrons are widely utilized in different fields of engineering, biology, chemistry and/or materials science. The additional information gained from the diffraction signal by x-ray diffraction and computed tomography (XRD-CT) can give this method a distinct advantage in materials science applications compared to classical tomography. Its active development over the last decade revealed structural details in a non-destructive way with unprecedented sensitivity. In the current contribution an attempt to adopt the well-established XRD-CT technique for neutron diffraction computed tomography (ND-CT) is reported. A specially designed \u27phantom\u27, an object displaying adaptable contrast sufficient for both XRD-CT and ND-CT, was used for method validation. The feasibility of ND-CT is demonstrated, and it is also shown that the ND-CT technique is capable to provide a non-destructive view into the interior of the \u27phantom\u27 delivering structural information consistent with a reference XRD-CT experiment

Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation

Accurate capacity estimation is crucial for the reliable and safe operation of lithium-ion batteries. In particular, exploiting the relaxation voltage curve features could enable battery capacity estimation without additional cycling information. Here, we report the study of three datasets comprising 130 commercial lithium-ion cells cycled under various conditions to evaluate the capacity estimation approach. One dataset is collected for model building from batteries with LiNi$_{0.86}$Co$_{0.11}$Al$_{0.03}$O$_{2}$-based positive electrodes. The other two datasets, used for validation, are obtained from batteries with LiNi$_{0.83}$Co$_{0.11}$Mn$_{0.07}$O$_{2}$-based positive electrodes and batteries with the blend of Li(NiCoMn)O$_{2}$ - Li(NiCoAl)O$_{2}$ positive electrodes. Base models that use machine learning methods are employed to estimate the battery capacity using features derived from the relaxation voltage profiles. The best model achieves a root-mean-square error of 1.1% for the dataset used for the model building. A transfer learning model is then developed by adding a featured linear transformation to the base model. This extended model achieves a root-mean-square error of less than 1.7% on the datasets used for the model validation, indicating the successful applicability of the capacity estimation approach utilizing cell voltage relaxation