VASP learning pathways
MODEL · CONVERGE · VALIDATE · INTERPRET
Learn to define a model, control numerical error and interpret a result. Follow the chapters from essential skills and isolated atoms or molecules to periodic bulk models, then choose a property or advanced workflow.
Examples are original educational inputs and schematics, not claimed simulation results. Use a licensed VASP installation and authorized PAW datasets. External tools are identified separately in their workflows.
Choose a calculation question
1 Essential calculation skills
Input anatomy, numerical accuracy and reliable execution.
1.1 Four input files, one physical question
Before asking “What is the energy?”, ask “Energy of which model?” POSCAR defines the periodically repeated cell and positions.
Study the workflow →1.2 A convergence laboratory with an error budget
Convergence is not a badge attached to an INCAR file.
Study the workflow →1.3 Reliable HPC execution, restart validation and reproducible automation
A job ending normally is an operational result; a converged and interpretable trajectory is a scientific result.
Study the workflow →1.4 Access, units and file anatomy
Identify the installation, licensed datasets, input files and output quantities.
Study the workflow →1.5 SCF, cutoff and k-mesh convergence
Separate solver, basis and sampling errors with controlled tests.
Study the workflow →1.6 Slurm, troubleshooting and reproducibility
Adapt the launcher safely and preserve an auditable run lineage.
Study the workflow →2 Atoms and molecules
Learn isolation, spin, bonding and molecular validation before periodic models.
2.1 A spin-polarized isolated atom
Hydrogen has one electron.
Study the workflow →2.2 H₂ binding: an energy difference needs a reference
A negative total energy by itself does not prove a bond exists.
Study the workflow →2.3 Molecular geometry and vibrations in vacuum
A geometry optimizer finds a stationary point by following forces.
Study the workflow →3 Bulk, surfaces and defects
Construct cells, relax structures and define meaningful energy comparisons.
3.1 Silicon: from a finite object to a crystal
In an isolated molecule, vacuum separates copies.
Study the workflow →3.2 Aluminum: why metals need smearing care
Silicon has a gap; a metal has states crossing the Fermi level.
Study the workflow →3.3 Crystal relaxation, stress and Pulay error
Moving atoms and changing a cell are different operations.
Study the workflow →3.4 Slabs, adsorption, dipoles and work functions
A surface calculation retains periodicity parallel to a surface and inserts vacuum normal to it.
Study the workflow →3.5 Neutral and charged defect formation energies
Removing an atom does not simply subtract two comparable total energies: the removed atom must go somewhere.
Study the workflow →3.6 Adsorption energies with consistent references, coverage and dispersion
Subtracting three large numbers can produce a chemically important small difference.
Study the workflow →3.7 First bulk-silicon single point
Understand a two-atom primitive cell and inspect a fixed-geometry SCF run.
Study the workflow →3.8 Atomic and cell relaxation
Distinguish ionic stopping, residual stress and numerical accuracy.
Study the workflow →4 Electronic structure and magnetism
Interpret bands, densities, spin and correlated or relativistic models.
4.1 Competing magnetic states in bcc iron
A magnetic calculation is an optimization on an energy landscape with potentially several self-consistent solutions.
Study the workflow →4.2 Bands and effective masses
A band structure draws electron energies as crystal momentum changes.
Study the workflow →4.3 DOS and PDOS
The density of states answers “how many states occur near this energy?” It deliberately discards the momentum coordinate.
Study the workflow →4.4 Charge density, charge differences, and ELF
Electron density asks where electrons reside.
Study the workflow →4.5 Bader populations and charge conventions
A Bader analysis partitions space into density basins separated by zero-flux boundaries of the density gradient.
Study the workflow →4.6 DFT+U with an explicit model choice
Semilocal DFT can over-delocalize localized d or f electrons.
Study the workflow →4.7 Hybrid band gaps and the correct band workflow
A hybrid functional includes an orbital-dependent exact-exchange contribution.
Study the workflow →4.8 SOC and noncollinear magnetism
Noncollinear magnetism allows a magnetization vector whose direction varies through the system.
Study the workflow →4.9 Bands and density of states
Trace path eigenvalues and DOS back to a compatible parent density.
Study the workflow →5 Mechanical properties
Connect controlled strains, stresses and elastic stability.
5.1 Equation of state and bulk modulus
How difficult is it to compress a crystal uniformly?
Study the workflow →5.2 Elastic tensor from finite strains
A bulk modulus describes uniform compression.
Study the workflow →5.3 Stress–strain and ideal strength
Elastic constants describe the initial slope near zero strain.
Study the workflow →6 Phonons and thermal properties
Separate harmonic, quasiharmonic and transport workflows.
6.1 Finite-displacement phonons with Phonopy
At equilibrium every force is nearly zero, but that does not tell us how strongly atoms resist motion.
Study the workflow →6.2 DFPT phonons
Finite differences push atoms a small but finite distance.
Study the workflow →6.3 Harmonic free energy, heat capacity, and entropy
A phonon spectrum is a catalogue of collective quantum oscillators.
Study the workflow →6.4 Quasiharmonic thermal expansion
A strictly harmonic calculation at one volume has no volume degree of freedom and cannot predict thermal expansion by itself.
Study the workflow →6.5 Lattice thermal conductivity: external third-order tools
Heat capacity measures how much vibrational energy a crystal stores.
Study the workflow →7 Optical response and excitations
Understand response approximations, energy references and convergence.
7.1 Dielectric tensors, Born effective charges, and LO–TO splitting
An electric field can distort the electron cloud while nuclei remain fixed, and it can also move the nuclei.
Study the workflow →7.2 Independent-particle optical spectra with LOPTICS
Light can induce vertical transitions between occupied and empty states.
Study the workflow →7.3 GW and BSE: a staged advanced workflow
A quasiparticle energy describes adding or removing an electron while the other electrons respond.
Study the workflow →8 AIMD and reaction pathways
Validate time evolution, sampling and transition-state evidence.
8.1 NEB diffusion barriers
Two stable sites can have similar energies but a large barrier between them.
Study the workflow →8.2 Prepare an AIMD calculation and decide when equilibration ends
A relaxation asks, “where is a nearby minimum?” AIMD asks, “what configurations does the system visit while moving?” A relaxed structure with no velocities is not yet a thermal…
Study the workflow →8.3 Validate NVE timestep and energy conservation
In a fixed-cell, isolated classical system, potential and kinetic energy continually exchange.
Study the workflow →8.4 Choose an NVT thermostat without confusing sampling and dynamics
A thermostat exchanges energy with an imagined heat bath.
Study the workflow →8.5 NpT dynamics, pressure units and a stable simulation cell
NVT fixes the container; NpT lets the container respond.
Study the workflow →8.6 Read trajectories and build a defensible radial distribution function
A snapshot can show a neighbour; an RDF answers whether neighbours occur more often at a distance than in a chosen uniform reference.
Study the workflow →8.7 MSD, diffusion, unwrapping and honest error bars
A particle can cross a periodic boundary while moving only a short distance.
Study the workflow →8.8 Finite-temperature surfaces and liquids: sampling before storytelling
At finite temperature, the system visits a distribution of adsorption geometries, orientations, coordination environments and solvent arrangements.
Study the workflow →8.9 Train, validate and deploy VASP-native machine-learned force fields
A force field is a model of an energy landscape.
Study the workflow →Core reference guides
- 1.4 Access, units and file anatomy — Identify the installation, licensed datasets, input files and output quantities.
- 3.7 First bulk-silicon single point — Understand a two-atom primitive cell and inspect a fixed-geometry SCF run.
- 1.5 SCF, cutoff and k-mesh convergence — Separate solver, basis and sampling errors with controlled tests.
- 3.8 Atomic and cell relaxation — Distinguish ionic stopping, residual stress and numerical accuracy.
- 4.9 Bands and density of states — Trace path eigenvalues and DOS back to a compatible parent density.
- 1.6 Slurm, troubleshooting and reproducibility — Adapt the launcher safely and preserve an auditable run lineage.
What counts as a completed case?
Be able to explain the physical model and units, input choices, parent/restart data, convergence of the target observable, acceptance checks and limitations. Keep raw inputs and outputs with version and dataset provenance. Process completion, electronic convergence and scientific validity are separate judgments.