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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 andmore »Free, publicly-accessible full text available May 10, 2023
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How does the physical and chemical structure of the Critical Zone (CZ), defined as the zone from treetops to the bottom of groundwater, govern its hydro-biogeochemical functioning? Multiple lines of evidence from past and newly emerging research have prompted the shallow and deep partitioning concentration-discharge (C-Q) hypothesis. The hypothesis states that in-stream C-Q relationships are shaped by distinct source waters from flow paths at different depths. Base flows are often dominated by deep groundwater and mostly reflect groundwater chemistry, whereas high flows are often dominated by shallow soil water and thus mostly reflect soil water chemistry. The contrasts between shallowmore »Free, publicly-accessible full text available December 17, 2022
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