Enabling Tools and Techniques for Organic Synthesis

Name: Enabling Tools and Techniques for Organic Synthesis | A Practical Guide to Experimentation, Automation, and Computation
Brand: Wiley-ISTE
Price: 151.99 EUR
Availability: OnlineOnly

A Practical Guide to Experimentation, Automation, and Computation

Stephen G. Newman(Herausgeber*in)

Wiley-ISTE (Verlag)

1. Auflage

Erschienen am 4. August 2023

496 Seiten

E-Book

PDF mit Adobe-DRM

Systemvoraussetzungen

978-1-119-85565-1 (ISBN)

151,99 €inkl. 7% MwSt.

Systemvoraussetzungen

für PDF mit Adobe-DRM

E-Book Einzellizenz

Als Download verfügbar

Beschreibung

ENABLING TOOLS AND TECHNIQUES FOR ORGANIC SYNTHESIS

Provides the practical knowledge of how new technologies impact organic synthesis, enabling the reader to understand literature, evaluate different techniques, and solve synthetic challenges

In recent years, new technologies have impacted organic chemistry to the point that they are no longer the sole domain of dedicated specialists. Computational chemistry, for example, can now be used by organic chemists to help predict outcomes, understand selectivity, and decipher mechanisms. To be prepared to solve various synthetic problems, it is increasingly important for chemists to familiarize themselves with a range of current and emerging tools and techniques.

Enabling Tools and Techniques for Organic Synthesis: A Practical Guide to Experimentation, Automation, and Computation provides a broad overview of contemporary research and new technologies applied to organic synthesis. Detailed chapters, written by a team of experts from academia and industry, describe different state-of-the-art techniques such as computer-assisted retrosynthesis, spectroscopy prediction with computational chemistry, high throughput experimentation for reaction screening, and optimization using Design of Experiments (DoE). Emphasizing real-world practicality, the book includes chapters on programming for synthetic chemists, machine learning (ML) in chemical synthesis, concepts and applications of computational chemistry, and more.

* Highlights the most recent methods in organic synthesis and describes how to employ these techniques in a reader's own research

* Familiarizes readers with the application of computational chemistry and automation technology in organic synthesis

* Introduces synthetic chemists to electrochemistry, photochemistry, and flow chemistry

* Helps readers comprehend the literature, assess the strengths and limitations of each technique, and apply those tools to solve synthetic challenges

* Provides case studies and guided examples with graphical illustrations in each chapter

Enabling Tools and Techniques for Organic Synthesis: A Practical Guide to Experimentation, Automation, and Computation is an invaluable reference for scientists needing an up-to-date introduction to new tools, graduate students wanting to expand their organic chemistry skills, and instructors teaching courses in advanced techniques for organic synthesis.

Weitere Details

Weitere Ausgaben

Person

Inhalt

Cover
Title Page
Copyright Page
Contents
List of Contributors
Preface
Chapter 1 Biocatalysis 101 - A Chemist's Guide to Starting Biocatalysis
1.1 Introduction
1.1.1 Enzymes - the Green and Sustainable Way of the Future
1.1.2 Enzymatic and Organic Catalysis Are Not too Different from Each Other
1.1.3 Enzymes 101
1.2 When Should I Choose an Enzyme over a Chemical Catalyst?
1.3 Key Considerations for Running Biocatalytic Reactions
1.3.1 Dispelling Myths
1.3.2 Challenges of Using Enzymes: the Need for Strict Reaction Conditions
1.3.3 What Do I Need to Start Biocatalytic Experiments in My Lab?
1.3.4 Additional Considerations
1.4 Transformations Catalyzed by Enzymes
1.4.1 EC - The Enzyme Commission Number
1.4.2 Some Applications of Selected Commercially Available Enzymes
1.4.3 Engineered (Unnatural) Reactions
1.5 New Trends and Technologies in Biocatalysis
1.5.1 Flow Biocatalysis and New Technologies
1.5.2 Enzyme Engineering
1.5.3 Photobiocatalysis
1.6 Flow Chart to Biocatalysis
1.8 Concluding Remarks
Additional Resources
References
Chapter 2 Introduction to Photochemistry for the Synthetic Chemist
2.1 Introduction
2.1.1 Light to Make Your Synthesis Greener
2.1.2 A Way to Overcome HOMO/LUMO Interactions
2.2 How to Plan a Photochemical Synthesis
2.2.1 The Choice of the Solvent
2.2.2 Concentration of the Absorbing Species
2.2.3 The Reaction Vessel
2.2.4 Light Sources
2.2.5 From Batch to Flow Conditions
2.2.6 Preparation of the Sample
2.2.7 Safety Equipment
2.3 Selected Applications of Photochemical/Photocatalyzed Reactions
2.3.1 Reactions Involving the CC Double Bond
2.3.2 Reactions Involving the CO Double Bond
2.3.3 Reactions Involving a Photoinduced Homolysis
2.3.4 Reactions Involving Singlet Oxygen
2.3.5 Reactions Involving a Photocatalytic Step
2.4 Conclusions
Acknowledgment
References
Chapter 3 How to Confidently Become an Electrosynthetic Practitioner
3.1 Introduction
3.2 General Definition of Organic Electrosynthesis
3.3 Why is Organic Electrosynthesis Used?
3.4 How is Organic Electrosynthesis Performed?
3.5 Where to Start with Electrosynthesis?
Selected General Reviews
Selected General Guides
3.6 Electrasyn 2.0
3.6.1 Machine and Consumables
3.6.2 Interface
3.6.3 How to Set Up the Cell
3.6.4 How to Start an Experiment
3.6.5 During the Reaction
3.6.6 After the Reaction
3.7 Case Study
3.7.1 Project Overview
3.7.2 Optimization of Parameters
3.7.3 Proof of Concept
3.8 Conclusion
References
Chapter 4 Flow Chemistry
4.1 Introduction
4.1.1 What is Flow Microchemistry
4.1.2 Reactions Enabled by Flow Microreactors
4.1.3 Further Applicability of Flow Microsynthesis
4.2 General Information for Flow Microreactors
4.2.1 Tools and Equipment for Flow Chemistry
4.2.2 How to Perform Experiments
4.3 Case Studies
4.3.1 Competitive Sequential Reaction (General Procedure)
4.3.2 Reactions Mediated by Short-Lived Intermediates
4.3.3 Reaction Integration
4.4 Further Expertise
4.4.1 Reaction Integration
4.4.2 Chemoselective Reactions
4.4.3 Heterogeneous Catalytic Reactions
4.5 Summary and Outlook
References
Chapter 5 Reaction Optimization Using Design of Experiments
5.1 Introduction
5.1.1 How Do We Experiment and DoE Terminology
5.1.2 OVAT vs. DoE
5.1.3 A Note on Error, Accuracy, and Precision
5.2 When and How Can DoE Be Used?
5.3 What Information Can I Get from a DoE and How Is It Obtained?
5.3.1 Which Factors Are Important?
5.3.2 How Are the Models Generated?
5.4 What Types of Design Are Available?
5.4.1 Screening Designs
5.4.2 Designs for Optimizing Reactions
5.4.3 Response Surface Designs
5.5 The DoE Process
5.5.1 Aim and Objective
5.5.2 Selecting Factors and Ranges
5.5.3 Selecting Responses
5.5.4 Select a Design to Answer the Objective
5.5.5 Carry Out Design and Analyze Samples
5.5.6 Check Results
5.5.7 Model Data
5.5.8 Validate Predictions
5.6 Combining DoE with Other Screening and Optimization Techniques
5.7 Software
5.8 "I Tried Experimental Design But It Did Not Work"
5.9 Conclusion
References
Chapter 6 Introduction to High-Throughput Experimentation (HTE) for the Synthetic Chemist
6.1 What Is HTE?
6.2 Why HTE and What Can It Achieve?
6.2.1 Commonly Perceived Barriers to Employing HTE in Synthetic Chemistry
6.2.2 Advantages of HTE Workflows vs. Traditional Reaction Setup
6.3 Practical Considerations and Tools for HTE
6.3.1 Outline of a Typical HTE Workflow
6.3.2 Types of HTE Designs
6.3.3 HTE Design Software: Tools for Building Arrays
6.3.4 HTE Reactors and Consumables
6.3.5 Considerations for Experimental Setup
6.3.6 Analysis of HTE Screens
6.3.7 The Role of Automation and Robotics in HTE
6.4 Section Summary and Outlook
6.5.1 Motivation
6.5.2 Design of Test Reaction and Initial Ligand Screen
6.5.3 Second Round of Ligand/Base/Solvent Screens
6.5.4 Final Platform Design
6.5.5 Validation of Platform Design
6.6.1 Motivation
6.6.2 Reaction Discovery Plate Design
6.6.3 Ligand Screen
6.6.4 Parallel Optimization of Three Reagents
6.6.5 Base Screen
6.7 Current Challenges and the Future of HTE
6.7.1 Summary and Conclusions
6.7.2 Remaining Challenges: The Next Frontiers
6.7.2.2 Flow Chemistry and HTE
6.7.2.3 Reaction Profiling
6.7.2.4 Building Machine Learning Models to Predict Reactivity
6.7.2.5 Addressing Future Challenges
Acknowledgments
Further Recommended Reading
References
Chapter 7 Concepts and Practical Aspects of Computational Chemistry
7.1 Introduction
7.2 Hardware and Software Requirements for Computational Investigations
7.3 Typical Methods in Computational Organic Chemistry
7.3.1 General Aspects
7.3.2 Molecular Mechanics and Force Fields
7.3.3 Wave-Function Methods I - Hartree-Fock Theory
7.3.4 Wave-Function Methods II - Post-Hartree-Fock Theory
7.3.5 Semiempirical Methods
7.3.6 Density Functional Theory
7.3.7 Dispersion-Corrected Density Functional Theory
7.3.8 Typical Computational Times
7.4 Basis Sets Used in Computational Organic Chemistry
7.4.1 General Aspects of Basis Sets
7.4.2 Introduction to the Mathematical Formalism in Basis Sets
7.4.3 Polarization and Diffuse Functions
7.4.4 Basis Set Families
7.4.5 Effective Core Potentials (Pseudopotentials)
7.4.6 The Basis Set Superposition Error (BSSE)
7.5 Typical Computational Tasks in Organic Chemistry
7.5.1 Preliminary Remarks
7.5.2 Single-Point Calculations
7.5.3 Geometry Optimizations
7.5.4 Frequency Calculations
7.5.5 Intrinsic Reaction Coordinate (IRC) Calculations
7.5.6 Conformational Analysis
7.6 Notation of the Model Chemistry
7.7 The Diels-Alder Reaction as a Tutorial Case Study
7.7.1 General Aspects and Requirements
7.7.2 Preparing Input Files
7.7.3 Conformational Sampling - Generation of Initial Geometries
7.7.4 Geometry Optimizations of Starting Materials and Products
7.7.5 Locating the Transition States
7.7.6 Verifying the Nature of the Transition State
7.8 More Advanced Aspects
7.8.1 General Comments
7.8.2 Influence of Solvation
7.8.3 Integration Grid
7.8.4 Standard States
7.8.5 Treating Unpaired Electrons
7.9 Important and Frequently Used Keywords
7.10 Practical Considerations
7.11 Conclusions
References
Chapter 8 NMR Prediction with Computational Chemistry
8.1 Introduction
8.2 Quantum-Chemistry-Based Computational NMR
8.2.1 Methods
8.2.2 Confidence Analysis
8.2.3 Computer-Aided Automated Approaches
8.2.4 A Case Study
8.2.5 Practicing 1H and 13C Chemical Shift Prediction
8.3 Summary and Outlook
Key References
References
Chapter 9 Introduction to Programming for the Organic Chemist
9.1 Introduction
9.2 Better Visualizations: Communicating Structure-Data Relationships
9.3 Text Extraction: Automating Density Functional Theory Calculations
9.4 Statistical Analysis: Deriving Insight from Historical Data
9.5 Machine Learning: A Predictive Model for Deoxyfluorination
9.6 Working with Public Datasets: Identifying Reactivity Cliffs
9.7 Running Simulations: Process Greenness
9.8 Application Development: Process Mass Intensity Predictor
9.9 Machine Learning for Reaction Optimization
9.10 Executing Robotic Tasks
9.11 Autonomous Reaction Optimization
9.12 Conclusion
References
Chapter 10 Machine Learning for the Optimization of Chemical Reaction Conditions
10.1 Introduction
10.2 Prior Art and Alternative Methods for Rational Reaction Optimization
10.3 Reaction Optimization Using LabMate.ML
10.3.1 Step One: Accessing the LabMate.ML Code and Installation
10.3.2 Step Two: Initializing the Optimization Routine in LabMate.ML
10.3.3 Step Three: Iterative Optimization Routine
10.3.4 Examples
10.4 Primer on Evaluation Guidelines
10.4.1 Code and Dataset Availability
10.4.2 Retrospective Evaluation
10.4.3 Baselines and Comparing Tools
10.4.4 Prospective Evaluation
10.5 Outlook
References
Chapter 11 Computer-Assisted Synthesis Planning
11.1 Introduction to Computer-Aided Synthesis Planning
11.1.1 Defining the Tasks and Use Cases
11.1.2 Historical Approaches to Computer-Aided Synthesis Planning
11.1.3 The Inflection Point of CASP Methods
11.1.4 Preliminaries on Molecular Representation and Cheminformatics
11.1.5 Outline of the Rest of the Chapter
11.2 Approaches and Algorithms for Retrosynthesis
11.2.1 Data-driven v. Expert-Driven Programs
11.2.2 Template-Based Approaches
11.2.3 Template-free Approaches with Graphs and Sequences
11.2.4 Multistep Planning Algorithms
11.3 Approaches and Algorithms for Condition Recommendation and Forward Synthesis
11.3.1 Condition Recommendation Approaches
11.3.2 Forward Synthesis Approaches
11.4 Select Examples of Software Tools for CASP
11.4.1 Open-Source Tools
11.4.2 Closed-Source Tools
11.4.3 CASP Tools for Enzymatic Catalysis
11.4.4 Practical Considerations for CASP Programs
11.5 Case Studies
11.5.1 Segler et al.'s Data-driven Program and A/B Testing Success
11.5.2 MIT's ASKCOS Program and Robotic Synthesis Demonstration
11.5.3 Grzybowski's Chematica/Synthia Program's Experimental Validations and Acquisition
11.6 Conclusion
Key References
References
Index
EULA

Systemvoraussetzungen

Als PDF speichern Als Link merken