Home ›
Entities
› academia
› Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study
Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study
Research article (Journal of Chromatography A, 2022) · cited 22× · AI/ML
Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study
Summary
Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study is a scholarly article[1].
Key Facts
Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study. Retrieved May 24, 2026, from https://4ort.xyz/entity/optimization-of-enantiomer-separation-in-flow-modulated-comprehensive-two-dimensional-gas-chromatography-by-response-sur
MLA“Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/optimization-of-enantiomer-separation-in-flow-modulated-comprehensive-two-dimensional-gas-chromatography-by-response-sur.
BibTeX@misc{4ortxyz_optimization-of-enantiomer-separation-in-flow-modulated-comprehensive-two-dimensional-gas-chromatography-by-response-sur_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study}}, year = {2026}, url = {https://4ort.xyz/entity/optimization-of-enantiomer-separation-in-flow-modulated-comprehensive-two-dimensional-gas-chromatography-by-response-sur}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study — https://4ort.xyz/entity/optimization-of-enantiomer-separation-in-flow-modulated-comprehensive-two-dimensional-gas-chromatography-by-response-sur (retrieved 2026-05-24)
