Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe.

Funder: European and Developing Countries Clinical Trials Partnership (EDCTP); doi: https://doi.org/10.13039/501100001713Funder: MRC Centre for Global Infectious Disease Analysis (MR/R015600/1), jointly funded by the U.K. Medical Research Council (MRC) and the U.K. Foreign, Commonwealth and Development Office (FCDO), under the MRC/FCDO Concordat agreement. Community Jameel. The UK Research and Innovation (MR/V038109/1), the Academy of Medical Sciences Springboard Award (SBF004/1080), The MRC (MR/R015600/1), The BMGF (OPP1197730), Imperial College Healthcare NHS Trust- BRC Funding (RDA02), The Novo Nordisk Young Investigator Award (NNF20OC0059309) and The NIHR Health Protection Research Unit in Modelling Methodology. S. Bhatt thanks Microsoft AI for Health and Amazon AWS for computational credits.Funder: EA FundsFunder: University of Oxford (Oxford University); doi: https://doi.org/10.13039/501100000769Funder: DeepMindFunder: OpenPhilanthropyFunder: UKRI Centre for Doctoral Training in Interactive Artificial Intelligence (EP/S022937/1)Funder: Augustinus Fonden (Augustinus Foundation); doi: https://doi.org/10.13039/501100004954Funder: Knud Højgaards Fond (Knud Højgaard Fund); doi: https://doi.org/10.13039/501100009938Funder: Kai Lange og Gunhild Kai Langes Fond (Kai Lange and Gunhild Kai Lange Foundation); doi: https://doi.org/10.13039/501100008206Funder: Aage og Johanne Louis-Hansens Fond (Aage and Johanne Louis-Hansen Foundation); doi: https://doi.org/10.13039/501100010344Funder: William Demant FoundationFunder: Boehringer Ingelheim Fonds (Stiftung für medizinische Grundlagenforschung); doi: https://doi.org/10.13039/501100001645Funder: Imperial College COVID-19 Research FundFunder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289European governments use non-pharmaceutical interventions (NPIs) to control resurging waves of COVID-19. However, they only have outdated estimates for how effective individual NPIs were in the first wave. We estimate the effectiveness of 17 NPIs in Europe's second wave from subnational case and death data by introducing a flexible hierarchical Bayesian transmission model and collecting the largest dataset of NPI implementation dates across Europe. Business closures, educational institution closures, and gathering bans reduced transmission, but reduced it less than they did in the first wave. This difference is likely due to organisational safety measures and individual protective behaviours-such as distancing-which made various areas of public life safer and thereby reduced the effect of closing them. Specifically, we find smaller effects for closing educational institutions, suggesting that stringent safety measures made schools safer compared to the first wave. Second-wave estimates outperform previous estimates at predicting transmission in Europe's third wave

Ultra-Thick Cathodes for High-Energy Lithium-Ion Batteries Based on Aluminium Foams—Microstructural Evolution during Densification and Its Impact on the Electrochemical Properties

Using three-dimensional (3D) metal foams as current collectors is considered to be a promising approach to improve the areal specific capacity and meet the demand for increased energy density of lithium-ion batteries. Electrodes with an open-porous metal foam as current collector exhibit a 3D connected electronic network within the active mass, shortening the electron transport pathways and lowering the electrodes’ intrinsic electronic resistance. In this study, NMC622 cathodes using an aluminium foam as current collector with a measured areal capacity of up to 7.6 mAh cm−2 were investigated. To this end, the infiltrated foams were densified to various thicknesses between 200 µm and 400 µm corresponding to an electrode porosity between 65% and 30%. The microstructural analysis reveals (i) the elimination of shrinking cavities and a decrease in the porosity of the infiltrated active mass, (ii) an improved contact of active mass to the current collector structure and (iii) a pronounced clogging of the surface pores. The electrochemical properties such as capacity and rate capability are correlated to the electrode’s microstructure, demonstrating that densification is necessary to improve active material utilization and volumetric capacity. However, strong densification impairs the rate capability caused by increased pore resistance and hindered electrolyte accessibility

Swift Prediction of Battery Performance

In this study, we investigate the use of artificial neural networks as a potentially efficient method to determine the rate capability of electrodes for lithium-ion batteries with different porosities. The performance of a lithium-ion battery is, to a large extent, determined by the microstructure (i.e., layer thickness and porosity) of its electrodes. Tailoring the microstructure to a specific application is a crucial process in battery development. However, unravelling the complex correlations between microstructure and rate performance using either experiments or simulations is time-consuming and costly. Our approach provides a swift method for predicting the rate capability of battery electrodes by using machine learning on microstructural images of electrode cross-sections. We train multiple models in order to predict the specific capacity based on the batteries’ microstructure and investigate the decisive parts of the microstructure through the use of explainable artificial intelligence (XAI) methods. Our study shows that even comparably small neural network architectures are capable of providing state-of-the-art prediction results. In addition to this, our XAI studies demonstrate that the models are using understandable human features while ignoring present artefacts

The external surface area of carbon additives as key to enhance the dynamic charge acceptance of lead-carbon electrodes

The dynamic charge acceptance (DCA) of modern lead-carbon batteries is one of the key parameters for their future application in micro- and mild-hybrid cars. This work elucidates the impact of the external surface area of carbon additives on the electrochemical performance of lead-carbon electrodes with respect to the DCA. Five specially synthesized amorphous hard carbon powders with different specific external surface area ranging from 13 m2 g−1 to 192 m2 g−1 were added to the negative active material of laboratory lead-carbon test cells. Results from cyclic voltammetry reveal that the specific external surface area of amorphous carbons exhibits a clear correlation to the electrochemical activity of lead-carbon electrodes. Firstly, an almost linear increase of the activity of the hydrogen evolution reaction with increasing specific external surface area of the carbon additive can be found. Secondly, the specific double-layer capacity of the negative active material is directly linked to the specific external surface area of the additive, as well. Thirdly, a clear correlation to the DCA can be established. In conclusion, a high specific external carbon surface in the negative active material seems to be a key to improve the dynamic charge acceptance of modern lead-carbon batteries

A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe.

During the second half of 2020, many European governments responded to the resurging transmission of SARS-CoV-2 with wide-ranging non-pharmaceutical interventions (NPIs). These efforts were often highly targeted at the regional level and included fine-grained NPIs. This paper describes a new dataset designed for the accurate recording of NPIs in Europe's second wave to allow precise modelling of NPI effectiveness. The dataset includes interventions from 114 regions in 7 European countries during the period from the 1st August 2020 to the 9th January 2021. The paper includes NPI definitions tailored to the second wave following an exploratory data collection. Each entry has been extensively validated by semi-independent double entry, comparison with existing datasets, and, when necessary, discussion with local epidemiologists. The dataset has considerable potential for use in disentangling the effectiveness of NPIs and comparing the impact of interventions across different phases of the pandemic