Computational Chemistry for Experimentalists
A Nonspecialist's Guide to Practical and Predictive Simulations
- 1st Edition - January 29, 2026
- Latest edition
- Author: Benjamin G. Janesko
- Language: English
Computational Chemistry for Experimentalists: A Nonspecialist's Guide to Practical and Predictive Simulations empowers chemists—especially those at emerging institutions… Read more
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Description
Description
Computational Chemistry for Experimentalists: A Nonspecialist's Guide to Practical and Predictive Simulations empowers chemists—especially those at emerging institutions or in small and medium enterprises—by transforming foundational chemical concepts into practical computational skills. A modular approach, paired with hands-on video tutorials, ensures that even nonspecialists can confidently apply simulations to their research, regardless of career stage or specialization. Beyond its accessible structure, the book features six modules covering core topics such as electronic structure theory and molecular dynamics. Ten experimental modules focus on simulating specific laboratory techniques—reaction mechanisms, NMR, UV/vis, band structures, XPS, and organometallic chemistry.
Regularly updated online tutorials complement the material, providing project-based, real-world training. By bridging theory and practice, this guide serves mid-career professionals, undergraduate and graduate students, and early-career researchers, making computational chemistry approachable and practical for all experimental chemists.
Ben's free online course complimenting this book is available on GitHub:
https://github.com/bjanesko/ComputationalChemistryForExperimentalists
Regularly updated online tutorials complement the material, providing project-based, real-world training. By bridging theory and practice, this guide serves mid-career professionals, undergraduate and graduate students, and early-career researchers, making computational chemistry approachable and practical for all experimental chemists.
Ben's free online course complimenting this book is available on GitHub:
https://github.com/bjanesko/ComputationalChemistryForExperimentalists
Key features
Key features
- Provides experimentalists with a simple and accessible on-ramp to computation for non-specialists
- Highlights the idea that computational chemistry’s core ideas, including chemical bonding, hybridization, and molecular structure are part of core chemical knowledge
- Includes relevant equations and algorithmic details
- Enables readers to rapidly acquire the most relevant knowledge
- Includes modules that are paired with online video tutorials, providing real-world-hands-on training using different software packages
Readership
Readership
Chemists at emerging research institutions and small and medium-sized businesses, who seek to incorporate computation into their research but are not primarily computational chemists; mid-career chemistry professionals, as well as research teams including undergraduate, graduate, and early-career chemists
Table of contents
Table of contents
1. Introduction and Motivation
Section I: Core Modules
2. Molecular Orbitals and Basis Sets
3. Geometry Optimization
4. Orbitals and Densities
5. Dynamics and Conformational Sampling
6. Atomic Charges, Electrostatic Potentials, and Multipole Moments
7. Mean-Field Electronic Structure Approximations
8. Data Processing
Section II: Shared Modules
9. Free Energies of Formation
10. Transition States and Reaction Rates
11. Continuum Solvent
12. Ab Initio Wavefunctions
13. Databases and Machine Learning
Section III: Specific Experiments
14. Ionization Potentials, Electron Affinities, and Redox Potentials
15. Infrared and Raman Spectra
16. NMR Spectra
17. Band Structures
18. pKa
19. Absorption and Emission Spectroscopy
Section IV: Summary Examples
20. Transition Metal Catalysis
21. Drug Design
Section I: Core Modules
2. Molecular Orbitals and Basis Sets
3. Geometry Optimization
4. Orbitals and Densities
5. Dynamics and Conformational Sampling
6. Atomic Charges, Electrostatic Potentials, and Multipole Moments
7. Mean-Field Electronic Structure Approximations
8. Data Processing
Section II: Shared Modules
9. Free Energies of Formation
10. Transition States and Reaction Rates
11. Continuum Solvent
12. Ab Initio Wavefunctions
13. Databases and Machine Learning
Section III: Specific Experiments
14. Ionization Potentials, Electron Affinities, and Redox Potentials
15. Infrared and Raman Spectra
16. NMR Spectra
17. Band Structures
18. pKa
19. Absorption and Emission Spectroscopy
Section IV: Summary Examples
20. Transition Metal Catalysis
21. Drug Design
Product details
Product details
- Edition: 1
- Latest edition
- Published: January 29, 2026
- Language: English
About the author
About the author
BJ
Benjamin G. Janesko
Ben Janesko received a BS in Chemistry from Allegheny College (1999) and a PhD in Chemistry from Carnegie Mellon University, USA (2004). He completed postdoctoral research at Rice University, USA. Since 2009, he has been on the faculty of Texas Christian University (TCU), USA. His research group develops methods at the interface of density functional theory and ab initio wavefunction theory, including beyond-zero-sum and rung-3.5 density functionals, and applies these methods alongside experimentalists. The Janesko Group’s methods are released in the Gaussian 16 electronic structure package, the Multiwfn interpretive package, and as an add-on to the open PySCF package. Dr. Janesko has over 150 indexed publications and an H-index of 29. Since 2015, his course “Computational Chemistry for Experimentalists” has provided a broad cohort of TCU undergraduate and graduate students with real-world hands-on training in computational chemistry. Modular video tutorials are freely available online at the Janesko group webpage.
Affiliations and expertise
Professor and Chair, Department of Chemistry & Biochemistry; Faculty Fellow, Ralph Lowe Energy Institute, Neeley School of Business, Texas Christian University, USAView book on ScienceDirect
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