Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles
Summary
Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles is a scholarly article[1].
Key Facts
Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles. Retrieved May 24, 2026, from https://4ort.xyz/entity/machine-learning-to-tame-divergent-density-functional-approximations-a-new-path-to-consensus-materials-design-principles
MLA“Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/machine-learning-to-tame-divergent-density-functional-approximations-a-new-path-to-consensus-materials-design-principles.
BibTeX@misc{4ortxyz_machine-learning-to-tame-divergent-density-functional-approximations-a-new-path-to-consensus-materials-design-principles_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles}}, year = {2026}, url = {https://4ort.xyz/entity/machine-learning-to-tame-divergent-density-functional-approximations-a-new-path-to-consensus-materials-design-principles}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles — https://4ort.xyz/entity/machine-learning-to-tame-divergent-density-functional-approximations-a-new-path-to-consensus-materials-design-principles (retrieved 2026-05-24)
