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Sultana N, Edlund U, Guria C, Westman G. Kinetics of Periodate-Mediated Oxidation of Cellulose. Polymers (Basel) 2024; 16:381. [PMID: 38337270 DOI: 10.3390/polym16030381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 01/23/2024] [Accepted: 01/25/2024] [Indexed: 02/12/2024] Open
Abstract
The oxidation of cellulose to dialdehyde cellulose (DAC) is a process that has received increased interest during recent years. Herein, kinetic modeling of the reaction with sodium periodate as an oxidizing agent was performed to quantify rate-limiting steps and overall kinetics of the cellulose oxidation reaction. Considering a pseudo-first-order reaction, a general rate expression was derived to elucidate the impact of pH, periodate concentration, and temperature on the oxidation of cellulose and concurrent formation of cellulose degradation products. Experimental concentration profiles were utilized to determine the rate constants for the formation of DAC (k1), degradation constant of cellulose (k2), and degradation of DAC (k3), confirming that the oxidation follows a pseudo-first-order reaction. Notably, the increase in temperature has a more pronounced effect on k1 compared to the influence of IO4- concentration. In contrast, k2 and k3 display minimal changes in response to IO4- concentration but increase significantly with increasing temperature. The kinetic model developed may help with understanding the rate-limiting steps and overall kinetics of the cellulose oxidation reaction, providing valuable information for optimizing the process toward a faster reaction with higher yield of the target product.
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Affiliation(s)
- Nazmun Sultana
- Fibre and Polymer Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden
- Organic Chemistry, Chemistry, and Chemical Engineering, Chalmers University of Technology, Kemigården 4, SE-412 96 Gothenburg, Sweden
- FibRe-Centre for Lignocellulose-Based Thermoplastics, Department of Fibre and Polymer Technology, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden
| | - Ulrica Edlund
- Fibre and Polymer Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden
- FibRe-Centre for Lignocellulose-Based Thermoplastics, Department of Fibre and Polymer Technology, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden
| | - Chandan Guria
- Department of Petroleum Engineering, Indian Institute of Technology (IIT-Indian School of Mines), Dhanbad 826 004, India
| | - Gunnar Westman
- Organic Chemistry, Chemistry, and Chemical Engineering, Chalmers University of Technology, Kemigården 4, SE-412 96 Gothenburg, Sweden
- FibRe-Centre for Lignocellulose-Based Thermoplastics, Department of Chemistry and Chemical Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
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Lennon G, Dingwall P. Enabling High Throughput Kinetic Experimentation by Using Flow as a Differential Kinetic Technique. Angew Chem Int Ed Engl 2024; 63:e202318146. [PMID: 38078481 PMCID: PMC10952970 DOI: 10.1002/anie.202318146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Indexed: 12/23/2023]
Abstract
Kinetic data is most commonly collected through the generation of time-series data under either batch or flow conditions. Existing methods to generate kinetic data in flow collect integral data (concentration over time) only. Here, we report a method for the rapid and direct collection of differential kinetic data (direct measurement of rate) in flow by performing a series of instantaneous rate measurements on sequential small-scale reactions. This technique decouples the time required to generate a full kinetic profile from the time required for a reaction to reach completion, enabling high throughput kinetic experimentation. In addition, comparison of kinetic profiles constructed at different residence times allows the robustness, or stability, of homogeneously catalysed reactions to be interrogated. This approach makes use of a segmented flow platform which was shown to quantitatively reproduce batch kinetic data. The proline mediated aldol reaction was chosen as a model reaction to perform a high throughput kinetic screen of 216 kinetic profiles in 90 hours, one every 25 minutes, which would have taken an estimated continuous 3500 hours in batch, an almost 40-fold increase in experimental throughput matched by a corresponding reduction in material consumption.
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Affiliation(s)
- Gavin Lennon
- School of Chemistry and Chemical EngineeringQueen's University BelfastDavid Keir Building, Stranmillis RoadBelfastBT9 5AGUK
| | - Paul Dingwall
- School of Chemistry and Chemical EngineeringQueen's University BelfastDavid Keir Building, Stranmillis RoadBelfastBT9 5AGUK
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Wigh DS, Tissot M, Pasau P, Goodman JM, Lapkin AA. Quantitative In Silico Prediction of the Rate of Protodeboronation by a Mechanistic Density Functional Theory-Aided Algorithm. J Phys Chem A 2023; 127:2628-2636. [PMID: 36916916 PMCID: PMC10041635 DOI: 10.1021/acs.jpca.2c08250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/15/2023]
Abstract
Computational reaction prediction has become a ubiquitous task in chemistry due to the potential value accurate predictions can bring to chemists. Boronic acids are widely used in industry; however, understanding how to avoid the protodeboronation side reaction remains a challenge. We have developed an algorithm for in silico prediction of the rate of protodeboronation of boronic acids. A general mechanistic model devised through kinetic studies of protodeboronation was found in the literature and forms the foundation on which the algorithm presented in this work is built. Protodeboronation proceeds through 7 distinct pathways, though for any particular boronic acid, only a subset of mechanistic pathways are active. The rate of each active mechanistic pathway is linearly correlated with its characteristic energy difference, which in turn can be determined using Density Functional Theory. We validated the algorithm using leave-one-out cross-validation on a data set of 50 boronic acids and made a further 50 rate predictions on academically and industrially important boronic acids out of sample. We believe this work will provide great assistance to chemists performing reactions that feature boronic acids, such as Suzuki-Miyaura and Chan-Evans-Lam couplings.
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Affiliation(s)
- Daniel S Wigh
- Department of Chemical Engineering and Biotechnology, University of Cambridge, CB3 0AS Cambridge, U.K
| | | | | | - Jonathan M Goodman
- Yusuf Hamied Department of Chemistry, University of Cambridge, CB2 1EW Cambridge, U.K
| | - Alexei A Lapkin
- Department of Chemical Engineering and Biotechnology, University of Cambridge, CB3 0AS Cambridge, U.K
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Taylor CJ, Pomberger A, Felton KC, Grainger R, Barecka M, Chamberlain TW, Bourne RA, Johnson CN, Lapkin AA. A Brief Introduction to Chemical Reaction Optimization. Chem Rev 2023; 123:3089-3126. [PMID: 36820880 PMCID: PMC10037254 DOI: 10.1021/acs.chemrev.2c00798] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.
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Affiliation(s)
- Connor J Taylor
- Astex Pharmaceuticals, 436 Cambridge Science Park, Milton Road, Cambridge CB4 0QA, U.K
- Innovation Centre in Digital Molecular Technologies, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K
| | - Alexander Pomberger
- Innovation Centre in Digital Molecular Technologies, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K
| | - Kobi C Felton
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, U.K
| | - Rachel Grainger
- Astex Pharmaceuticals, 436 Cambridge Science Park, Milton Road, Cambridge CB4 0QA, U.K
| | - Magda Barecka
- Chemical Engineering Department, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
- Chemistry and Chemical Biology Department, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
- Cambridge Centre for Advanced Research and Education in Singapore, 1 Create Way, 138602 Singapore
| | - Thomas W Chamberlain
- Institute of Process Research and Development, School of Chemistry and School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, U.K
| | - Richard A Bourne
- Institute of Process Research and Development, School of Chemistry and School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, U.K
| | - Christopher N Johnson
- Astex Pharmaceuticals, 436 Cambridge Science Park, Milton Road, Cambridge CB4 0QA, U.K
| | - Alexei A Lapkin
- Innovation Centre in Digital Molecular Technologies, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K
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Saltão VAC, Thybaut JW, Pirro L, Freire FG, Mendes PSF. Automation of Data-Driven Rate Equation Screening for Heterogeneously Catalyzed Reactions. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c01920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Vasco A. C. Saltão
- Laboratory for Chemical Technology, Department of Materials, Textiles and Chemical Engineering, Ghent University, Technologiepark 125, 9052 Ghent, Belgium
- Chemical Engineering Department, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
| | - Joris W. Thybaut
- Laboratory for Chemical Technology, Department of Materials, Textiles and Chemical Engineering, Ghent University, Technologiepark 125, 9052 Ghent, Belgium
| | - Laura Pirro
- Laboratory for Chemical Technology, Department of Materials, Textiles and Chemical Engineering, Ghent University, Technologiepark 125, 9052 Ghent, Belgium
| | - Filipe G. Freire
- Chemical Engineering Department, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
| | - Pedro S. F. Mendes
- Laboratory for Chemical Technology, Department of Materials, Textiles and Chemical Engineering, Ghent University, Technologiepark 125, 9052 Ghent, Belgium
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Sagmeister P, Ort FF, Jusner CE, Hebrault D, Tampone T, Buono FG, Williams JD, Kappe CO. Autonomous Multi-Step and Multi-Objective Optimization Facilitated by Real-Time Process Analytics. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2105547. [PMID: 35106974 PMCID: PMC8981902 DOI: 10.1002/advs.202105547] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/12/2022] [Indexed: 05/04/2023]
Abstract
Autonomous flow reactors are becoming increasingly utilized in the synthesis of organic compounds, yet the complexity of the chemical reactions and analytical methods remains limited. The development of a modular platform which uses rapid flow NMR and FTIR measurements, combined with chemometric modeling, is presented for efficient and timely analysis of reaction outcomes. This platform is tested with a four variable single-step reaction (nucleophilic aromatic substitution), to determine the most effective optimization methodology. The self-optimization approach with minimal background knowledge proves to provide the optimal reaction parameters within the shortest operational time. The chosen approach is then applied to a seven variable two-step optimization problem (imine formation and cyclization), for the synthesis of the active pharmaceutical ingredient edaravone. Despite the exponentially increased complexity of this optimization problem, the platform achieves excellent results in a relatively small number of iterations, leading to >95% solution yield of the intermediate and up to 5.42 kg L-1 h-1 space-time yield for this pharmaceutically relevant product.
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Affiliation(s)
- Peter Sagmeister
- Institute of ChemistryUniversity of GrazNAWI Graz, Heinrichstrasse 28Graz8010Austria
- Center for Continuous Flow Synthesis and Processing (CCFLOW)Research Center Pharmaceutical Engineering GmbH (RCPE)Inffeldgasse 13Graz8010Austria
| | - Florian F. Ort
- Institute of ChemistryUniversity of GrazNAWI Graz, Heinrichstrasse 28Graz8010Austria
| | - Clemens E. Jusner
- Institute of ChemistryUniversity of GrazNAWI Graz, Heinrichstrasse 28Graz8010Austria
- Center for Continuous Flow Synthesis and Processing (CCFLOW)Research Center Pharmaceutical Engineering GmbH (RCPE)Inffeldgasse 13Graz8010Austria
| | - Dominique Hebrault
- Chemical Development USBoehringer Ingelheim Pharmaceuticals, Inc.900 Ridgebury RoadRidgefieldConnecticut06877USA
| | - Thomas Tampone
- Chemical Development USBoehringer Ingelheim Pharmaceuticals, Inc.900 Ridgebury RoadRidgefieldConnecticut06877USA
| | - Frederic G. Buono
- Chemical Development USBoehringer Ingelheim Pharmaceuticals, Inc.900 Ridgebury RoadRidgefieldConnecticut06877USA
| | - Jason D. Williams
- Institute of ChemistryUniversity of GrazNAWI Graz, Heinrichstrasse 28Graz8010Austria
- Center for Continuous Flow Synthesis and Processing (CCFLOW)Research Center Pharmaceutical Engineering GmbH (RCPE)Inffeldgasse 13Graz8010Austria
| | - C. Oliver Kappe
- Institute of ChemistryUniversity of GrazNAWI Graz, Heinrichstrasse 28Graz8010Austria
- Center for Continuous Flow Synthesis and Processing (CCFLOW)Research Center Pharmaceutical Engineering GmbH (RCPE)Inffeldgasse 13Graz8010Austria
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Taylor CJ, Manson JA, Clemens G, Taylor BA, Chamberlain TW, Bourne RA. Modern advancements in continuous-flow aided kinetic analysis. REACT CHEM ENG 2022. [DOI: 10.1039/d1re00467k] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Although kinetic analysis has traditionally been conducted in a batch vessel, continuous-flow aided kinetic analysis continues to swell in popularity.
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Affiliation(s)
- Connor J. Taylor
- Institute of Process Research and Development, School of Chemistry and School of Chemical and Process Engineering, University of Leeds, Leeds, LS2 9JT, UK
| | - Jamie A. Manson
- Institute of Process Research and Development, School of Chemistry and School of Chemical and Process Engineering, University of Leeds, Leeds, LS2 9JT, UK
| | - Graeme Clemens
- Chemical Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Macclesfield, UK
| | - Brian A. Taylor
- Chemical Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Macclesfield, UK
| | - Thomas W. Chamberlain
- Institute of Process Research and Development, School of Chemistry and School of Chemical and Process Engineering, University of Leeds, Leeds, LS2 9JT, UK
| | - Richard A. Bourne
- Institute of Process Research and Development, School of Chemistry and School of Chemical and Process Engineering, University of Leeds, Leeds, LS2 9JT, UK
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