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1
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McHale C, Soliven A, Schuster S. A simple approach for reversed phase column comparisons via the Tanaka test. Microchem J 2021. [DOI: 10.1016/j.microc.2020.105793] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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2
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Data processing strategies for non-targeted analysis of foods using liquid chromatography/high-resolution mass spectrometry. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116188] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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3
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A Thioether-Embedded Mixed-Mode Cyano-Bonded Chromatographic Stationary Phase: Preparation, Characterization and Retention Mechanism. Chromatographia 2018. [DOI: 10.1007/s10337-018-3630-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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4
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Applications of the solvation parameter model in reversed-phase liquid chromatography. J Chromatogr A 2017; 1486:2-19. [DOI: 10.1016/j.chroma.2016.05.099] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Revised: 05/26/2016] [Accepted: 05/30/2016] [Indexed: 11/20/2022]
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5
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Barron LP, McEneff GL. Gradient liquid chromatographic retention time prediction for suspect screening applications: A critical assessment of a generalised artificial neural network-based approach across 10 multi-residue reversed-phase analytical methods. Talanta 2016; 147:261-70. [DOI: 10.1016/j.talanta.2015.09.065] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2015] [Revised: 09/22/2015] [Accepted: 09/27/2015] [Indexed: 12/01/2022]
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6
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Munro K, Miller TH, Martins CP, Edge AM, Cowan DA, Barron LP. Artificial neural network modelling of pharmaceutical residue retention times in wastewater extracts using gradient liquid chromatography-high resolution mass spectrometry data. J Chromatogr A 2015; 1396:34-44. [DOI: 10.1016/j.chroma.2015.03.063] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2014] [Revised: 02/27/2015] [Accepted: 03/23/2015] [Indexed: 02/07/2023]
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7
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Lu J, Ni X, Cao Y, Ma X, Cao G. Electrokinetic chromatographic characterization of novel catanionic surfactants vesicle as pseudostationary phase. Electrophoresis 2014; 36:312-8. [DOI: 10.1002/elps.201400375] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Revised: 10/08/2014] [Accepted: 10/14/2014] [Indexed: 11/11/2022]
Affiliation(s)
- Jie Lu
- School of Chemical and Material Engineering; Jiangnan University; Wuxi China
| | - Xinjiong Ni
- School of Chemical and Material Engineering; Jiangnan University; Wuxi China
| | - Yuhua Cao
- School of Chemical and Material Engineering; Jiangnan University; Wuxi China
- The Key Laboratory of Food Colloids and Biotechnology; Ministry of Education; Wuxi China
| | - Xinyu Ma
- School of Chemical and Material Engineering; Jiangnan University; Wuxi China
| | - Guangqun Cao
- School of Chemical and Material Engineering; Jiangnan University; Wuxi China
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8
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Artificial neural network prediction of multilinear gradient retention in reversed-phase HPLC: comprehensive QSRR-based models combining categorical or structural solute descriptors and gradient profile parameters. Anal Bioanal Chem 2014; 407:1181-90. [DOI: 10.1007/s00216-014-8317-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2014] [Revised: 10/30/2014] [Accepted: 11/03/2014] [Indexed: 11/26/2022]
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9
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D'Archivio AA, Maggi MA, Ruggieri F. Prediction of the retention ofs-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditions. J Sep Sci 2014; 37:1930-6. [DOI: 10.1002/jssc.201400346] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Revised: 04/29/2014] [Accepted: 05/05/2014] [Indexed: 11/05/2022]
Affiliation(s)
| | | | - Fabrizio Ruggieri
- Dipartimento di Scienze Fisiche e Chimiche; Università degli Studi dell'Aquila; L'Aquila Italy
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Miller TH, Musenga A, Cowan DA, Barron LP. Prediction of Chromatographic Retention Time in High-Resolution Anti-Doping Screening Data Using Artificial Neural Networks. Anal Chem 2013; 85:10330-7. [DOI: 10.1021/ac4024878] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Thomas H. Miller
- Analytical & Environmental Sciences Division, School of Biomedical Sciences, King’s College London, 150 Stamford Street, London SE1 9NH, United Kingdom
| | - Alessandro Musenga
- Analytical & Environmental Sciences Division, School of Biomedical Sciences, King’s College London, 150 Stamford Street, London SE1 9NH, United Kingdom
| | - David A. Cowan
- Analytical & Environmental Sciences Division, School of Biomedical Sciences, King’s College London, 150 Stamford Street, London SE1 9NH, United Kingdom
| | - Leon P. Barron
- Analytical & Environmental Sciences Division, School of Biomedical Sciences, King’s College London, 150 Stamford Street, London SE1 9NH, United Kingdom
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Cela R, Ordoñez E, Quintana J, Rodil R. Chemometric-assisted method development in reversed-phase liquid chromatography. J Chromatogr A 2013; 1287:2-22. [DOI: 10.1016/j.chroma.2012.07.081] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2012] [Revised: 07/25/2012] [Accepted: 07/26/2012] [Indexed: 11/16/2022]
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12
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D’Archivio AA, Maggi MA, Ruggieri F. Quantitative structure/eluent–retention relationships in reversed-phase high-performance liquid chromatography based on the solvatochromic method. Anal Bioanal Chem 2012; 405:755-66. [DOI: 10.1007/s00216-012-6191-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2012] [Revised: 06/08/2012] [Accepted: 06/11/2012] [Indexed: 11/24/2022]
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13
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D’Archivio AA, Giannitto A, Maggi MA, Ruggieri F. Cross-column retention prediction in reversed-phase high-performance liquid chromatography by artificial neural network modelling. Anal Chim Acta 2012; 717:52-60. [DOI: 10.1016/j.aca.2011.12.047] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2011] [Revised: 12/18/2011] [Accepted: 12/21/2011] [Indexed: 11/16/2022]
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