Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). DeePore: A deep learning workflow for rapid and comprehensive characterization of porous materials. Retrieved May 24, 2026, from https://4ort.xyz/entity/deepore-a-deep-learning-workflow-for-rapid-and-comprehensive-characterization-of-porous-materials
MLA“DeePore: A deep learning workflow for rapid and comprehensive characterization of porous materials.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deepore-a-deep-learning-workflow-for-rapid-and-comprehensive-characterization-of-porous-materials.
BibTeX@misc{4ortxyz_deepore-a-deep-learning-workflow-for-rapid-and-comprehensive-characterization-of-porous-materials_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{DeePore: A deep learning workflow for rapid and comprehensive characterization of porous materials}}, year = {2026}, url = {https://4ort.xyz/entity/deepore-a-deep-learning-workflow-for-rapid-and-comprehensive-characterization-of-porous-materials}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): DeePore: A deep learning workflow for rapid and comprehensive characterization of porous materials — https://4ort.xyz/entity/deepore-a-deep-learning-workflow-for-rapid-and-comprehensive-characterization-of-porous-materials (retrieved 2026-05-24)
