“DFT offers a practical route to understanding and predicting the properties of real materials.” -John P. Perdew

 

 

Our research group has expertise in Density Functional Theory (DFT) calculations for investigating the electronic and optical properties of materials. We simulate and interpret experimental chiroptical properties using theoretical approaches, including Circular Dichroism (CD) and Circularly Polarized Luminescence (CPL), to better understand the optical and electronic properties of chiral molecules and materials.

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Density Functional Theory (DFT)

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Density Functional Theory (DFT) is one of the most important theoretical and computational tools in modern chemistry, physics, and materials science. It is widely used to study the electronic structure of atoms, molecules, and solids with relatively high accuracy and manageable computational cost. 

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1. Understanding Electronic Structure

DFT allows scientists to calculate the electronic structure of materials by focusing on the electron density rather than complex many-electron wavefunctions. This makes it possible to predict properties such as:

• Energy levels

• Charge distribution

• Bonding interactions

• Magnetic properties

 

2. Predicting Material Properties

DFT helps researchers predict physical and chemical properties before experimental synthesis. Important properties that can be calculated include:

• Band structure of semiconductors

• Optical properties

• Magnetic behavior

• Mechanical stability

• Conductivity and catalytic activity

This predictive capability accelerates materials discovery and design.

 

3. Reducing Experimental Cost and Time

Many experiments are expensive, time-consuming, or difficult to perform. DFT simulations allow researchers to:

• Screen potential materials

• Test hypotheses theoretically

• Optimize structures before laboratory experiments

Thus, it significantly reduces research costs and development time.

 

4. Applications in Various Fields

DFT has applications across many scientific disciplines:

Chemistry

• Reaction mechanisms

• Catalysis studies

• Molecular structure and bonding

Materials Science

• Semiconductor design

• Battery materials

• Nanomaterials and 2D materials

Physics

• Electronic and magnetic properties of solids

• Superconductivity studies

Biochemistry

• Drug interactions

• Enzyme mechanisms

 

5. Widely Used Computational Method

Density Functional Theory has become a standard computational approach for investigating the electronic structure and properties of molecules and materials. Many computational packages use DFT to simulate materials, such as:

• Gaussian – Popular software for molecular DFT and quantum chemistry calculations. 

• VASP – Widely used plane-wave DFT code for solid-state materials and surfaces.

• Quantum ESPRESSO – Open-source package for electronic structure calculations using plane waves and pseudopotentials.

• Octopus – Real-space DFT code widely used for time-dependent DFT and nanoscale simulations.

• ABINIT – Open-source program for electronic structure calculations and materials properties.

• CASTEP – Plane-wave DFT program mainly used for solid-state materials simulations.

• WIEN2k – Accurate DFT package for crystalline solids using the full-potential linearized augmented plane wave (FP-LAPW) method.

• SIESTA – Efficient DFT program using localized basis sets suitable for large systems.

• ORCA – Free academic quantum chemistry package widely used for molecular DFT calculations.

• NWChem – High-performance computational chemistry software designed for large-scale parallel computing.

• CP2K – Software for simulations of solid-state, liquid, molecular, and biological systems using DFT and molecular dynamics.

• Amsterdam Density Functional (ADF) – A quantum chemistry software package based on Density Functional Theory is widely used for studying molecular systems, transition-metal complexes, catalysis, and spectroscopic properties. 

• ABACUS – An open-source electronic structure simulation package based on Density Functional Theory used for studying molecules, solids, and materials properties using atomic-orbital and plane-wave basis sets. 

• TURBOMOLE – Efficient quantum chemistry package for DFT and ab initio molecular calculations. 

• CRYSTAL – Periodic quantum chemistry program used for DFT studies of crystalline materials. 

• Molpro – Advanced quantum chemistry program supporting DFT and highly accurate wavefunction methods. 

• DALTON – Molecular electronic structure program used for DFT and spectroscopic property calculations.

• Q-Chem – Modern quantum chemistry software package widely used for DFT and excited-state calculations.

• FLEUR – Full-potential linearized augmented plane wave code used for electronic structure studies of solids.

• Yambo – Code for many-body perturbation theory and excited-state calculations based on DFT results.

• SCALE-UP – Linear-scaling DFT software designed for simulations of very large systems.

• Conquest – Large-scale linear-scaling DFT code capable of handling millions of atoms.

• RESCU – Real-space electronic structure calculator used for DFT simulations of molecules and materials.

• JDFTx – Open-source DFT software designed for joint density functional theory and electrochemical simulations.

• GPAW – Grid-based projector augmented wave method code used for electronic structure calculations.

• PySCF – Python-based framework for quantum chemistry simulations including DFT calculations.

 

These tools are essential for modern theoretical and computational research.

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6. Methodological Notes

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a. Creating UV/Visible Plots from the Results of Excited States Calculations – Demonstrates how to generate UV–Visible absorption spectra from excited-state computational results using Gaussian.

 

b. Modeling Antiferromagnetic Coupling in Gaussian – Explains how to simulate and analyze antiferromagnetic interactions in molecular systems.

 

c. Transition State Optimizations with Opt=QST2 – Describes the procedure for locating transition states using the QST2 optimization method.

 

d. Using Gaussian to Teach Physical Chemistry – Shows how Gaussian can be used as a teaching tool to explain important physical chemistry concepts.

 

e. Comparing NMR Methods in ChemDraw and Gaussian – Discusses the comparison of NMR prediction methods between ChemDraw and Gaussian.

 

f. Vibrational Analysis in Gaussian – Explains how to calculate and interpret vibrational frequencies and infrared (IR) spectra.

 

g. Thermochemistry in Gaussian – Describes the calculation of thermodynamic properties such as enthalpy, entropy, and Gibbs free energy.

 

h. Visualizing Results when Gaussian and GaussView are on Different Machines – Provides guidance for visualizing computational results using GaussView when programs are installed on separate computers.

 

i. Studying Chirality with Vibrational Circular Dichroism – Demonstrates how vibrational circular dichroism (VCD) calculations can be used to study molecular chirality.

 

j. Investigating the Reactivity and Spectra of Large Molecules with ONIOM – Explains how the ONIOM method is applied to investigate the reactivity and spectroscopic properties of large molecular systems.

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7. Modeling Spectroscopy

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Gaussian 16 can predict several types of spectra, including:

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a. Infrared (IR) and Raman spectra – Used to study molecular vibrations and bonding.

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b. NMR spectra and spin–spin coupling constants – Provides information about molecular structure and chemical environments of nuclei.

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c. Vibrational Circular Dichroism (VCD) – Useful for determining molecular chirality and stereochemistry.

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d. Raman Optical Activity (ROA) – Provides chiral information through Raman scattering.

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e. Resonance Raman spectroscopy – Enhances Raman signals associated with electronic transitions.

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f. UV–Visible spectroscopy – Used to study electronic transitions in molecules.

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g. Vibronic absorption and emission spectra for excited states – Calculated using Franck–Condon and/or Herzberg–Teller analysis.

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h. Electronic Circular Dichroism (ECD) and Circularly Polarized Luminescence (CPL) – Important techniques for studying chiral electronic transitions.

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i. Optical Rotatory Dispersion (ORD) – Measures optical activity as a function of wavelength.

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j. Hyperfine interactions (microwave spectroscopy) – Provides detailed information about molecular rotational transitions.

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8. Books to learn Density Functional Theory (DFT)

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1. Exploring Chemistry with Electronic Structure Methods — James B. Foresman & Æleen Frisch 

 

2. Density Functional Theory: A Practical Introduction — David S. Sholl & Janice A. Steckel

 

3. Introduction to Computational Chemistry — Frank Jensen

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4. A Chemist’s Guide to Density Functional Theory — Wolfram Koch & Max C. Holthausen

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5. Molecular Electronic Structure Theory — Trygve Helgaker, Poul Jørgensen & Jeppe Olsen

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6. Density Functionals: Theory and Applications — Daniel Joubert

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9. Basis set database

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A basis set is a collection of mathematical functions used to describe the electron wavefunctions in a molecule. These functions approximate how electrons are distributed around atoms when solving the Schrödinger equation for molecular systems. In quantum chemistry, electrons are described by orbitals. Instead of solving the Schrödinger equation exactly (which is impossible for most molecules), we approximate orbitals as a linear combination of basis functions. This approach is called Linear Combination of Atomic Orbitals (LCAO).

Mathematically: 𝜓 = 𝑐 1 𝜙 1 + 𝑐 2 𝜙 2 + 𝑐 3 𝜙 3 + . . .

ψ = molecular orbital

φ = basis functions

c = coefficients optimized during the calculation

So the basis set = the set of φ functions used to build orbitals.

 

Most Gaussian calculations use Gaussian-type orbital (GTO) functions because they are computationally efficient. They approximate atomic orbitals using Gaussian mathematical functions.

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   In Gaussian calculations, several basis sets are commonly used depending on the accuracy required and the type of system studied. Examples include STO-3G, which is a minimal basis set used mainly for quick preliminary calculations, and 6-31G, a split-valence basis set that provides a better description of valence electrons. More advanced basis sets such as 6-31+G(d,p) include diffuse and polarization functions that improve the treatment of electron distribution and bonding. Larger and more flexible basis sets like 6-311G, def2-SVP, def2-TZVP, and cc-pVDZ are used for more accurate calculations. A typical Gaussian input line may look like # B3LYP/6-31G(d), where B3LYP represents the computational method and the basis set defines how the atomic orbitals are mathematically described.

 

   The notation of basis sets also provides important information about their structure. For example, in 6-31G(d,p), the number 6 indicates that core orbitals are described by six Gaussian functions, while 31 shows that the valence orbitals are split into two groups (three and one Gaussian functions), allowing greater flexibility. The symbols d and p represent polarization functions added to heavy atoms and hydrogen atoms, respectively, which allow orbitals to change shape during bonding. Additional symbols such as + or ++ indicate diffuse functions that extend the electron cloud farther from the nucleus. These diffuse functions are particularly important for systems such as anions, hydrogen-bonded complexes, and molecules with weak intermolecular interactions.

 

   The choice of basis set is important because it significantly affects both the accuracy and computational cost of the calculation. Larger basis sets provide more accurate predictions of molecular properties such as geometry, total energy, dipole moments, reaction barriers, and spectroscopic properties. They also describe electron density, bonding, and polarization effects more accurately. However, larger basis sets require more computational resources. Minimal basis sets like STO-3G are very fast but less accurate, while split-valence sets like 6-31G offer a good balance between speed and accuracy. More advanced triple-zeta basis sets provide higher accuracy but require longer computation times.

 

   Increasing the size of the basis set generally improves accuracy, following a hierarchy such as STO-3G → 6-31G → 6-31G(d) → 6-311G(d,p) → larger correlation-consistent sets. In practical Gaussian calculations, a typical input such as # B3LYP/6-31+G(d,p) opt freq indicates a density functional theory calculation with a medium-to-high accuracy basis set, including geometry optimization and frequency analysis. For quick tests, STO-3G may be used, while geometry optimizations often employ 6-31G(d). For more accurate energies, 6-311+G(d,p) or larger basis sets are preferred. For systems containing heavy or transition metal atoms, basis sets combined with Effective Core Potentials, such as LANL2DZ or SDD, are commonly used to reduce computational cost while maintaining reasonable accuracy.

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a. Basis Sets (Gaussian)

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b. Basis Set Exchange (BSE)

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c. Energy-consistent Pseudopotentials of the Stuttgart/Cologne Group

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d. Mixed Basis Sets in Gaussian

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e. Basis Set Database of Gaussian 09/16 calculation

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10. GaussSum

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​GaussSum is a free program developed by Noel O'Boyle and distributed under the GNU Public License. It analyzes output files from many quantum chemistry packages such as Gaussian, ORCA, NWChem, Q-Chem, GAMESS, and ADF to extract useful chemical information.

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Main Features

a. Displays all lines containing a specific phrase in output files.

b. Tracks SCF convergence and geometry optimization progress.

c. Extracts molecular orbital information, including contributions from groups of atoms.

d. Plots Density of States (DOS) and Partial Density of States (PDOS) spectra.

e. Plots Crystal Orbital Overlap Population (COOP) to analyze bonding and antibonding interactions.

f. Extracts and plots UV–Vis and Circular Dichroism (CD) spectra.

g. Analyzes IR and Raman vibrational data and plots their spectra (with scaling factors).

h. Supports compressed output files such as .zip, .gz, and .bz2.

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11. Gaussian & GaussView Tutorial Videos

a. Building Molecules

b. Running Jobs

c. Visualizing Results

d. 3D Results Visualization

f. Working with Spectra

g. Selecting Atoms in GV6

h. Gaussian Calculation Setup

i. Calculation Defaults & Schemes​​