Quamtum chemistry

Quantum chemistry is a sub-discipline of chemistry that focuses on the application of quantum mechanics and quantum field theory to understand the behavior of atoms, molecules, and chemical systems at the quantum level. It seeks to explain the electronic structure of molecules, their energy levels, and the forces between them, which ultimately determine chemical reactivity, bonding, and other chemical properties.

Quantum chemistry combines the principles of quantum mechanics with computational methods to study chemical systems, using mathematical models and algorithms to predict and explain the outcomes of chemical reactions and the properties of molecules. Some of the key aspects of quantum chemistry include:

1. Electronic structure theory: This is concerned with the determination of the wavefunctions and energy levels of molecules, which describe the spatial distribution and behavior of electrons in the system.
2. Molecular dynamics: This involves the simulation of the motions of atomic nuclei and electrons in a molecule or a collection of molecules, based on the forces derived from electronic structure calculations.
3. Quantum reaction dynamics: This area focuses on studying the quantum mechanical aspects of chemical reactions, including reaction mechanisms, transition states, and reaction rates.
4. Spectroscopy: Quantum chemistry helps explain and predict the interaction of molecules with electromagnetic radiation, which is central to various spectroscopic techniques used to study molecular structure and dynamics.

Quantum chemistry has applications in various fields, including materials science, drug design, environmental chemistry, and nanotechnology. It is an interdisciplinary field that requires a solid understanding of both chemistry and quantum mechanics, as well as computational techniques for solving complex mathematical problems.

The Materials Project

https://materialsproject.org/

Periodic table https://materialsproject.org/materials

The database contains over 1M computed properties based on DFT and HPC. But most of them are calculated by cheap and not very accurate methods

Introduction: Harnessing the power of supercomputing and state-of-the-art methods, the Materials Project provides open web-based access to computed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials.

Hartree-Fock-theory-for-Hydrogen

Why started from hydrogen atom?

Hydrogen is the most abundant element in the universe. From outer space to stars, and to many substances on Earth, hydrogen is ubiquitous. Hydrogen is the first element in the periodic table, and its single atom is also the simplest of all elements, with only one proton and one electricity, which makes hydrogen a starting point for constructing and testing theories like hydrogen spectral series in quantum mechanics history.

Replaced the exact N-body wave function of the system with a single Slater determinant in time-independent Schrödinger equation. Used Hartree-Fock theory to build a numerical model for hydrogen with 6-31G basis from Basis Set Exchange and solved the equation using a nonlinear method and self-consistent field method. Solved the physical quantities matrix model with Born-Oppenheimer Approximation, and the quantitive relation of total energy and bond distance of a single molecule.

Please find more details in jupyter notebook.

Useful link: http://butane.chem.illinois.edu/sohirata/

DFT workflow

Although the DFT model is often a simplification of the true electronic structure of materials, it is computationally efficient and provides valuable insights into the essential physics.

Please see the jupyter notebook for more details

Computational chemistry packages. Widen the scope of quantum simulation applications

Kwant:

https://kwant-project.org/

https://pypi.org/project/kwant/

Gaussian:

https://gaussian.com/

https://emleddin.github.io/comp-chem-website/Otherguide-gaussian-overview.html

https://sites.google.com/site/rangsiman1993/comp-chem/techniques/learn-comp-chem-with-gaussian

Orca:

https://www.faccts.de/orca/

https://hpc.hku.hk/hpc/software/orca/

https://www.orcasoftware.de/tutorials_orca/

Quantum Espresso

https://www.quantum-espresso.org/

https://github.com/QEF

https://docs.pace.gatech.edu/software/quantumEspresso/

Python + Quantum sciencce & engineering

The realm of spectroscopy and quantum mechanics is vast, and there are several Python packages that cater to various aspects of these fields. Here are some popular Python packages used in these domains:

1. QuTiP (Quantum Toolbox in Python):

   • Focus: Quantum mechanics and quantum information systems.
   • Features: Enables computations related to open quantum systems, quantum optics, qubits, and more.

2. PySCF (Python for Strongly Correlated Electron Systems):

   • Focus: Quantum chemistry.
   • Features: Provides a suite of programs for electronic structure calculations, including Hartree-Fock and various post-Hartree-Fock methods.

3. Psi4:

   • Focus: Quantum chemistry.
   • Features: An open-source suite for ab initio quantum chemistry computations.

4. ASE (Atomic Simulation Environment):

   • Focus: Atomic scale simulations.
   • Features: Allows atomistic simulations of solid-state systems, molecules, chemical reactions, etc., and interfaces with various other simulation engines.

5. Spectral Python (SPy):

   • Focus: Spectroscopy, especially hyperspectral image processing.
   • Features: Offers functions for visualizing, classifying, and analyzing hyperspectral data.

6. QMTools:

   • Focus: Quantum mechanics and quantum chemistry.
   • Features: Provides utilities for data extraction, transformation, and visualization from quantum mechanics simulations.

7. GPkit:

   • Focus: Spectroscopy.
   • Features: A package for defining and manipulating geometric programming (GP) models, which can be useful in certain spectroscopy applications.

8. pyspectools:

   • Focus: Spectroscopy data handling and analysis.
   • Features: Allows for assignments, simulations, and plotting of spectra, particularly useful for rotational spectroscopy.

9. libra-python:

   • Focus: Quantum dynamics simulations.
   • Features: Useful for studying molecular and electronic dynamics in various systems.