Machine Learning & Data Science – Page 2

85. Dataset Design for Building Models of Chemical Reactivity

"Dataset Design for Building Models of Chemical Reactivity" Raghavan, P; Haas, B. C.; Ruos, M. E.; Schleinitz, J; Doyle, A. G.; Reisman, S. E.; Sigman, M. S.; Coley, C. W. J. Am. Chem. Soc. 2023, 145, 24175-24183. [DOI: 10.1021/jacs.3c08301] Link PDF

85. Dataset Design for Building Models of Chemical ReactivityFlora Fan2024-05-27T18:32:22-07:00

81. Continuous flow synthesis of pyridinium salts accelerated by multi-objective Bayesian optimization with active learning

"Continuous flow synthesis of pyridinium salts accelerated by multi-objective Bayesian optimization with active learning" Dunlap, J. H.; Ethier, J. G.; Putnam-Neeb, A. A.; Iyer, S.; Luo, S.-X. L.; Feng, H.; Torres, J. A. G.; Doyle, A. G.; Swager, T. M.; Vaia, R. A.; Mirau, P.; Crouse, C. A.; Baldwin, L. A. Chem. Sci. 2023, 14, 8061-8069.

81. Continuous flow synthesis of pyridinium salts accelerated by multi-objective Bayesian optimization with active learningDaniel Min2024-05-27T18:31:12-07:00

80. Comparison of Monophosphine and Bisphosphine Precatalysts for Ni-Catalyzed Suzuki–Miyaura Cross-Coupling: Understanding the Role of the Ligation State in Catalysis

Borowski, J. E.; Newman-Stonebraker, S. H.; Doyle, A. G. ACS. Catal. 2023, 13, 7966-7977. [DOI: 10.1021/acscatal.3c01331] Link PDF

80. Comparison of Monophosphine and Bisphosphine Precatalysts for Ni-Catalyzed Suzuki–Miyaura Cross-Coupling: Understanding the Role of the Ligation State in CatalysisFlora Fan2023-06-05T13:39:19-07:00

78. Interrogating the Mechanistic Features of Ni(I)-Mediated Aryl Iodide Oxidative Addition Using Electroanalytical and Statistical Modeling Techniques

Tang, T.; Hazra, A.; Min, D. S.; Williams, W. L.; Doyle, A. G.; Sigman M. S. J. Am. Chem. Soc. 2023, 145, 8689-8699. [DOI: 10.1021/jacs.3c01726] Link PDF

78. Interrogating the Mechanistic Features of Ni(I)-Mediated Aryl Iodide Oxidative Addition Using Electroanalytical and Statistical Modeling TechniquesDaniel Min2023-04-25T09:16:29-07:00

77. A Machine Learning Approach to Model Interaction Effects: Development and Application to Alcohol Deoxyfluorination

Żurański, A. M.; Gandhi, S. S.; Doyle, A. G. J. Am. Chem. Soc. 2023, 145, 7898–7909. [DOI: 10.1021/jacs.2c13093] Link PDF

77. A Machine Learning Approach to Model Interaction Effects: Development and Application to Alcohol DeoxyfluorinationFlora Fan2023-04-13T09:16:02-07:00

76. On the Use of Real-World Datasets for Reaction Yield Prediction

Saebi, M.; Nan, B.; Herr, J. E.; Wahlers, J.; Guo, Z.; Zurański, A. M.; Kogej, T.; Norrby, P.-O.; Doyle, A. G.; Wiest, O.; Chawla, N. V. Chem. Sci. 2023. [DOI: 10.1039/d2sc06041h] Link PDF

76. On the Use of Real-World Datasets for Reaction Yield PredictionFlora Fan2023-03-29T12:37:42-07:00

74. A Multi-Objective Active Learning Platform and Web App for Reaction Optimization

Torres, J. A. G.; Lau, S. H.; Anchuri, P.; Stevens, J. M.; Tabora, J. E.; Li, J.; Borovika, A.; Adams, R. P.; Doyle, A. G. J. Am. Chem. Soc. 2022, 144, 19999-20007. [DOI: 10.1021/jacs.2c08592] Link PDF Link EDBO+ web app.

74. A Multi-Objective Active Learning Platform and Web App for Reaction OptimizationWill Lau2022-12-30T17:36:45-08:00

69. Auto-QChem: an automated workflow for the generation and storage of DFT calculations for organic molecules

Żurański, A. M.; Wang, J. Y.; Shields, B. J.; Doyle, A. G. React. Chem. Eng. 2022, 7, 1276-1284. [DOI: 10.1039/D2RE00030J] Link PDF

69. Auto-QChem: an automated workflow for the generation and storage of DFT calculations for organic moleculesWill Lau2022-12-30T17:12:18-08:00

68. Using Data Science to Guide Aryl Bromide Substrate Scope Analysis in a Ni/Photoredox-Catalyzed Cross-Coupling with Acetals as Alcohol-Derived Radical Sources

Kariofillis, S. K.; Jiang, S.; Żurański, A. M.; Gandhi, S. S.; Martinez Alvarado, J. I.; Doyle, A. G. J. Am. Chem. Soc. 2022, 144, 1045-1055. [DOI: 10.1021/jacs.1c12203] Link PDF

68. Using Data Science to Guide Aryl Bromide Substrate Scope Analysis in a Ni/Photoredox-Catalyzed Cross-Coupling with Acetals as Alcohol-Derived Radical SourcesWill Lau2022-12-30T17:04:00-08:00

65. The Open Reaction Database

Kearnes, S. M.; Maser, M. R.; Wleklinski, M.; Kast, A.; Doyle, A. G.; Dreher, S. D.; Hawkins, J. M.; Jensen, K. F.; Coley, C. W. J. Am. Chem. Soc. 2021, 143, 18820-18826. [DOI: 10.1021/jacs.1c09820] Link PDF

65. The Open Reaction DatabaseWill Lau2022-12-30T20:29:25-08:00