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Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys
Research article (Journal of Physics Condensed Matter, 2021) · cited 35× · AI/ML
Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys
Summary
Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys is a scholarly article[1].
Key Facts
Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys. Retrieved May 24, 2026, from https://4ort.xyz/entity/correlation-analysis-of-materials-properties-by-machine-learning-illustrated-with-stacking-fault-energy-from-first-princ
MLA“Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/correlation-analysis-of-materials-properties-by-machine-learning-illustrated-with-stacking-fault-energy-from-first-princ.
BibTeX@misc{4ortxyz_correlation-analysis-of-materials-properties-by-machine-learning-illustrated-with-stacking-fault-energy-from-first-princ_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys}}, year = {2026}, url = {https://4ort.xyz/entity/correlation-analysis-of-materials-properties-by-machine-learning-illustrated-with-stacking-fault-energy-from-first-princ}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys — https://4ort.xyz/entity/correlation-analysis-of-materials-properties-by-machine-learning-illustrated-with-stacking-fault-energy-from-first-princ (retrieved 2026-05-24)
