
AbstractIn a recent article, we described the edxia framework, a user‐friendly framework to analyse the microstructure of cementitious materials using SEM‐EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific questions. However, it is limited for batch analysis and (semi‐)automated treatments. In this article, we show how the framework can be used to customise the analysis to the problem at hand. We first present some possible extensions, and then we provide a simple example of automatic clustering, using the flexible Python scientific libraries which will allow to define more custom workflows in the future.
info:eu-repo/classification/ddc/570, 570, Themed Issue Articles
info:eu-repo/classification/ddc/570, 570, Themed Issue Articles
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
