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Multi-principal element alloys (MPEAs) with remarkable performances possess great potential as structural, functional, and smart materials. However, their efficient performance-orientated design in a wide range of compositions and types is an extremely challenging issue, because of properties strongly dependent upon the composition and composition-dominated microstructure. Here, we propose a multistage-design approach integrating machine learning, physical laws and a mathematical model for developing the desired-property MPEAs in a very time-efficient way. Compared to the existing physical model- or machine-learning-assisted material development, the forward-and-inverse problems, including identifying the target property and unearthing the optimal composition, can be tackled with better efficiency and higher accuracy using our proposed avenue, which defeats the one-step component-performance design strategy by multistage-design coupling constraints. Furthermore, we developed a new multi-phase MPEA at the minimal time and cost, whose high strength-ductility synergy exceeded those of its system and subsystem reported so far by searching for the optimal combination of phase fraction and composition. The present work suggests that the property-guided composition and microstructure are precisely tailored through the newly built approach with significant reductions of the development period and cost, which is readily extendable to other multi-principal element materials.
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Abstract Background Candidatus Nanohaloarchaeota, an archaeal phylum within the DPANN superphylum, is characterized by limited metabolic capabilities and limited phylogenetic diversity and until recently has been considered to exclusively inhabit hypersaline environments due to an obligate association withHalobacteria . Aside from hypersaline environments,Ca. Nanohaloarchaeota can also have been discovered from deep-subsurface marine sediments.Results Three metagenome-assembled genomes (MAGs) representing a new order within the
Ca. Nanohaloarchaeota were reconstructed from a stratified salt crust and proposed to represent a novel order,Nucleotidisoterales . Genomic features reveal them to be anaerobes capable of catabolizing nucleotides by coupling nucleotide salvage pathways with lower glycolysis to yield free energy. Comparative genomics demonstrated that these and otherCa. Nanohaloarchaeota inhabiting saline habitats use a “salt-in” strategy to maintain osmotic pressure based on the high proportion of acidic amino acids. In contrast, previously describedCa. Nanohaloarchaeota MAGs from geothermal environments were enriched with basic amino acids to counter heat stress. Evolutionary history reconstruction revealed that functional differentiation of energy conservation strategies drove diversification withinCa. Nanohaloarchaeota, further leading to shifts in the catabolic strategy from nucleotide degradation within deeper lineages to polysaccharide degradation within shallow lineages.Conclusions This study provides deeper insight into the ecological functions and evolution of the expanded phylum
Ca. Nanohaloarchaeota and further advances our understanding on the functional and geneticmore »