Matches in SemOpenAlex for { <https://semopenalex.org/work/W4383198845> ?p ?o ?g. }
Showing items 1 to 81 of
81
with 100 items per page.
- W4383198845 abstract "Nickel- and cobalt-based superalloys are commonly used as turbine materials for high-temperature applications. However, their maximum operating temperature is limited to about 1100 °C. Therefore, to improve turbine efficiency, current research is focused on designing materials that can withstand higher temperatures. Niobium-based alloys can be considered as promising candidates because of their exceptional properties at elevated temperatures. The conventional approach to alloy design relies on phase diagrams and structure–property data of limited alloys and extrapolates this information into unexplored compositional space. In this work, we harness machine learning and provide an efficient design strategy for finding promising niobium-based alloy compositions with high yield and ultimate tensile strength. Unlike standard composition-based features, we use domain knowledge-based custom features and achieve higher prediction accuracy. We apply Bayesian optimization to screen out novel Nb-based quaternary and quinary alloy compositions and find these compositions have superior predicted strength over a range of temperatures. We develop a detailed design flow and include Python programming code, which could be helpful for accelerating alloy design in a limited alloy data regime." @default.
- W4383198845 created "2023-07-06" @default.
- W4383198845 creator A5003301534 @default.
- W4383198845 creator A5030788785 @default.
- W4383198845 creator A5060794659 @default.
- W4383198845 date "2023-07-05" @default.
- W4383198845 modified "2023-10-07" @default.
- W4383198845 title "Machine learning guided optimal composition selection of niobium alloys for high temperature applications" @default.
- W4383198845 cites W1518558473 @default.
- W4383198845 cites W2008269492 @default.
- W4383198845 cites W2041054706 @default.
- W4383198845 cites W2079147787 @default.
- W4383198845 cites W2278970271 @default.
- W4383198845 cites W2883578585 @default.
- W4383198845 cites W2902452488 @default.
- W4383198845 cites W2921873493 @default.
- W4383198845 cites W2968923792 @default.
- W4383198845 cites W2970765526 @default.
- W4383198845 cites W2974252728 @default.
- W4383198845 cites W2978707075 @default.
- W4383198845 cites W3026094172 @default.
- W4383198845 cites W3082902407 @default.
- W4383198845 cites W3095750175 @default.
- W4383198845 cites W3116783766 @default.
- W4383198845 cites W4283263325 @default.
- W4383198845 doi "https://doi.org/10.1063/5.0129528" @default.
- W4383198845 hasPublicationYear "2023" @default.
- W4383198845 type Work @default.
- W4383198845 citedByCount "0" @default.
- W4383198845 crossrefType "journal-article" @default.
- W4383198845 hasAuthorship W4383198845A5003301534 @default.
- W4383198845 hasAuthorship W4383198845A5030788785 @default.
- W4383198845 hasAuthorship W4383198845A5060794659 @default.
- W4383198845 hasBestOaLocation W43831988451 @default.
- W4383198845 hasConcept C111919701 @default.
- W4383198845 hasConcept C112950240 @default.
- W4383198845 hasConcept C119857082 @default.
- W4383198845 hasConcept C127413603 @default.
- W4383198845 hasConcept C191897082 @default.
- W4383198845 hasConcept C192562407 @default.
- W4383198845 hasConcept C207055975 @default.
- W4383198845 hasConcept C2778049539 @default.
- W4383198845 hasConcept C2780026712 @default.
- W4383198845 hasConcept C2781139463 @default.
- W4383198845 hasConcept C41008148 @default.
- W4383198845 hasConcept C507968137 @default.
- W4383198845 hasConcept C519991488 @default.
- W4383198845 hasConcept C78519656 @default.
- W4383198845 hasConceptScore W4383198845C111919701 @default.
- W4383198845 hasConceptScore W4383198845C112950240 @default.
- W4383198845 hasConceptScore W4383198845C119857082 @default.
- W4383198845 hasConceptScore W4383198845C127413603 @default.
- W4383198845 hasConceptScore W4383198845C191897082 @default.
- W4383198845 hasConceptScore W4383198845C192562407 @default.
- W4383198845 hasConceptScore W4383198845C207055975 @default.
- W4383198845 hasConceptScore W4383198845C2778049539 @default.
- W4383198845 hasConceptScore W4383198845C2780026712 @default.
- W4383198845 hasConceptScore W4383198845C2781139463 @default.
- W4383198845 hasConceptScore W4383198845C41008148 @default.
- W4383198845 hasConceptScore W4383198845C507968137 @default.
- W4383198845 hasConceptScore W4383198845C519991488 @default.
- W4383198845 hasConceptScore W4383198845C78519656 @default.
- W4383198845 hasFunder F4320332276 @default.
- W4383198845 hasIssue "3" @default.
- W4383198845 hasLocation W43831988451 @default.
- W4383198845 hasOpenAccess W4383198845 @default.
- W4383198845 hasPrimaryLocation W43831988451 @default.
- W4383198845 hasRelatedWork W1987487801 @default.
- W4383198845 hasRelatedWork W2035140895 @default.
- W4383198845 hasRelatedWork W2766515653 @default.
- W4383198845 hasRelatedWork W2783283445 @default.
- W4383198845 hasRelatedWork W2979108889 @default.
- W4383198845 hasRelatedWork W3197724773 @default.
- W4383198845 hasRelatedWork W4206568719 @default.
- W4383198845 hasRelatedWork W4282039964 @default.
- W4383198845 hasRelatedWork W4293057233 @default.
- W4383198845 hasRelatedWork W4297902612 @default.
- W4383198845 hasVolume "1" @default.
- W4383198845 isParatext "false" @default.
- W4383198845 isRetracted "false" @default.
- W4383198845 workType "article" @default.