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Powder X‐ray diffraction (pXRD) experiments are a cornerstone for materials structure characterization. Despite their widespread application, analyzing pXRD diffractograms still presents a significant challenge to automation and a bottleneck in high‐throughput discovery in self‐driving labs. Machine learning promises to resolve this bottleneck by enabling automated powder diffraction analysis. A notable difficulty in applying machine learning to this domain is the lack of sufficiently sized experimental datasets, which has constrained researchers to train primarily on simulated data. However, models trained on simulated pXRD patterns showed limited generalization to experimental patterns, particularly for low‐quality experimental patterns with high noise levels and elevated backgrounds. With the Open Experimental Powder X‐ray Diffraction Database (opXRD), we provide an openly available and easily accessible dataset of labeled and unlabeled experimental powder diffractograms. Labeled opXRD data can be used to evaluate the performance of models on experimental data and unlabeled opXRD data can help improve the performance of models on experimental data, for example, through transfer learning methods. We collected 92,552 diffractograms, 2179 of them labeled, from a wide spectrum of material classes. We hope this ongoing effort can guide machine learning research toward fully automated analysis of pXRD data and thus enable future self‐driving materials labs. 

Abstract Fungi are one of the most diverse groups of organisms with an estimated number of species in the range of 2–3 million. The higher-level ranking of fungi has been discussed in the framework of molecular phylogenetics since Hibbett et al., and the definition and the higher ranks (e.g., phyla) of the ‘true fungi’ have been revised in several subsequent publications. Rapid accumulation of novel genomic data and the advancements in phylogenetics now facilitate a robust and precise foundation for the higher-level classification within the kingdom. This study provides an updated classification of the kingdomFungi, drawing upon a comprehensive phylogenomic analysis ofHolomycota, with which we outline well-supported nodes of the fungal tree and explore more contentious groupings. We accept 19 phyla ofFungi,viz. Aphelidiomycota,Ascomycota,Basidiobolomycota,Basidiomycota,Blastocladiomycota,Calcarisporiellomycota,Chytridiomycota,Entomophthoromycota,Entorrhizomycota,Glomeromycota,Kickxellomycota,Monoblepharomycota,Mortierellomycota,Mucoromycota,Neocallimastigomycota,Olpidiomycota,Rozellomycota,Sanchytriomycota,andZoopagomycota. In the phylogenies,Caulochytriomycotaresides inChytridiomycota; thus, the former is regarded as a synonym of the latter, whileCaulochytriomycetesis viewed as a class inChytridiomycota. We provide a description of each phylum followed by its classes. A new subphylum,SanchytriomycotinaKarpov is introduced as the only subphylum inSanchytriomycota. The subclassPneumocystomycetidaeKirk et al. inPneumocystomycetes,Ascomycotais invalid and thus validated. Placements of fossil fungi in phyla and classes are also discussed, providing examples.