Quick Navigation

Topics

Quantum Chemistry Spin Qubits Silicon Quantum Computing

Theoretical analysis on retention behavior of pigments in reversed-phase high-performance liquid chromatographic (HPLC).

PubMed
Authors: Song Y, Zhou J, Song Y, Xie J, Ye Y

Year

2007

Paper ID

12743

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

71

Citations

5

Abstract

Quantitative structure-retention relationship (QSRR) models have been used successfully to predict and explain retention behavior of pigments in reversed-phase high-performance liquid chromatography (HPLC). The semi-empirical quantum chemical method (PM3) in Gaussian98 was employed to calculate a set of molecular descriptors of pigments. Using multiple linear regression (MLR), we obtained empirical functions with high correlation coefficient between retention times and quantum-chemical descriptors. This analysis indicated that the proposed QSRR models were satisfactory.

Why This Paper Matters

  • This paper contributes to the Quantum Chemistry research area in the Quantum Articles archive.
  • It adds a 2007 reference point for readers tracking recent quantum research.
  • Quantitative structure-retention relationship (QSRR) models have been used successfully to predict and explain retention behavior of pigments in reversed-phase high-performance...

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #12743 #78837 TLS loss in superconducting res... #78797 Local polarization control of o... #78792 Demonstration of subspace-searc...

External citation index: OpenAlex citation signal • updated 2026-10-22 02:58:48

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.