Computational Chemistry with Python : A Practical Introduction to Molecular Orbitals, Quantum Methods, Geometry Optimization, and Energy Calculations
Language: English
Published by Amazon Digital Services LLC - Kdp Mai 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 64.61
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Add to basketItem description from seller
Neuware - Reactive PublishingComputational chemistry allows researchers, students, and technical professionals to explore molecular structure, bonding, energy, and reactivity through mathematical models and programmable workflows. Computational Chemistry with Python provides a practical introduction to the core ideas behind molecular modeling while showing how Python can be used to support calculations, visualization, and conceptual understanding.This book introduces molecular orbitals, quantum chemistry foundations, Hartree-Fock theory, density functional theory concepts, geometry optimization, and molecular energy calculations in a clear, applied format. Rather than treating computational chemistry as a purely theoretical subject, it connects the underlying mathematics and physical chemistry to practical coding workflows that help readers understand how molecules can be represented, approximated, and analyzed.Inside, readers will explore how computational models describe electrons, orbitals, molecular geometry, basis sets, energy surfaces, and approximation methods. The book also explains where common methods are useful, where they are limited, and how Python-based workflows can help make abstract chemical concepts more concrete.Designed for students, self-learners, chemists, data scientists, and technically minded readers, this guide offers a structured entry point into computational chemistry without assuming advanced prior experience in quantum mechanics.Topics include: Molecular structure and coordinate representationMolecular orbitals and electronic structure conceptsQuantum chemistry foundations for applied modelingHartree-Fock theory and self-consistent field ideasDensity functional theory concepts and practical interpretationGeometry optimization and potential energy surfacesMolecular energy calculations and result interpretationPython-based approaches for chemical computation and analysisComputational Chemistry with Python is for readers who want to understand how modern molecular modeling works and how Python can be used as a practical tool for learning, experimentation, and applied chemical analysis. …
Seller Inventory # 9798196708305
- Title
- Computational Chemistry with Python : A Practical Introduction to Molecular Orbitals, Quantum Methods, Geometry Optimization, and Energy Calculations
- Author
- Livia Arden
- Publisher
- Amazon Digital Services LLC - Kdp Mai 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798196708305
- Item weight
- 658 grams
- Dimensions
- 225x150x27 mm
Computational chemistry allows researchers, students, and technical professionals to explore molecular structure, bonding, energy, and reactivity through mathematical models and programmable workflows. Computational Chemistry with Python provides a practical introduction to the core ideas behind molecular modeling while showing how Python can be used to support calculations, visualization, and conceptual understanding.
This book introduces molecular orbitals, quantum chemistry foundations, Hartree-Fock theory, density functional theory concepts, geometry optimization, and molecular energy calculations in a clear, applied format. Rather than treating computational chemistry as a purely theoretical subject, it connects the underlying mathematics and physical chemistry to practical coding workflows that help readers understand how molecules can be represented, approximated, and analyzed.
Inside, readers will explore how computational models describe electrons, orbitals, molecular geometry, basis sets, energy surfaces, and approximation methods. The book also explains where common methods are useful, where they are limited, and how Python-based workflows can help make abstract chemical concepts more concrete.
Designed for students, self-learners, chemists, data scientists, and technically minded readers, this guide offers a structured entry point into computational chemistry without assuming advanced prior experience in quantum mechanics.
Topics include:
Molecular structure and coordinate representation
Molecular orbitals and electronic structure concepts
Quantum chemistry foundations for applied modeling
Hartree-Fock theory and self-consistent field ideas
Density functional theory concepts and practical interpretation
Geometry optimization and potential energy surfaces
Molecular energy calculations and result interpretation
Python-based approaches for chemical computation and analysis
Computational Chemistry with Python is for readers who want to understand how modern molecular modeling works and how Python can be used as a practical tool for learning, experimentation, and applied chemical analysis.
"Synopsis" may belong to another edition of this title.
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