bader-charge-analysis
ResearchUse when the user asks about Bader charge analysis, charge transfer, oxidation states from DFT, or electron density partitioning.
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Bader Charge Analysis
Overview
Bader analysis partitions the continuous electron density from DFT into atomic basins defined by zero-flux surfaces of the density gradient. This gives physically meaningful atomic charges and charge transfer values.
What Bader Charges Tell You
- Charge transfer between adsorbate and surface
- Oxidation states of atoms in a material
- Electron donation/back-donation in catalytic bonds
- Ionic vs covalent character of bonds
VASP Settings for Bader Analysis
Bader analysis requires fine-grid charge density output:
LAECHG = .TRUE. # Write core charge density (AECCAR0, AECCAR2)
LCHARG = .TRUE. # Write valence charge density (CHGCAR)
NGXF, NGYF, NGZF # Fine FFT grid (2x default, e.g., NGXF=2*NGX)
The all-electron charge density is: AECCAR0 + AECCAR2, which is summed with the Bader code to avoid errors from pseudopotential smoothing.
MCP Workflow
Step 1: Single-point with charge output
{"tool": "catgo_workflow_engine", "arguments": {
"action": "add_task", "workflow_id": "wf_bader",
"task_type": "single_point",
"params": {
"software": "vasp",
"ENCUT": 520,
"LAECHG": true,
"LCHARG": true,
"PREC": "Accurate",
"system_name": "charge density"
}
}}
Step 2: Bader analysis post-processing
{"tool": "catgo_workflow_engine", "arguments": {
"action": "add_task", "workflow_id": "wf_bader",
"task_type": "charge_analysis",
"depends_on": "task_sp",
"params": {"method": "bader", "system_name": "Bader charges"}
}}
Step 3: Get results
{"tool": "catgo_workflow_engine", "arguments": {
"action": "get_result", "workflow_id": "wf_bader", "task_id": "task_bader"
}}
{"tool": "catgo_analyze", "arguments": {
"action": "charges", "workflow_id": "wf_bader", "task_id": "task_bader"
}}
Python API
Basic Bader Analysis
from catgo.workflow import Workflow
wf = Workflow("Bader charge - CO on Pt(111)")
inp = wf.add_task("structure_input", structure=co_pt_json)
# Relax first
opt = wf.add_task("geo_opt",
structure=inp.output.structure,
software="vasp", ENCUT=520)
# Single-point with charge density output
sp = wf.add_task("single_point",
structure=opt.output.structure,
software="vasp", ENCUT=520,
LAECHG=True, LCHARG=True, PREC="Accurate")
# Bader post-processing
bader = wf.add_task("charge_analysis",
chgcar=sp.output.chgcar,
aeccar0=sp.output.aeccar0,
aeccar2=sp.output.aeccar2,
method="bader")
wf.submit()
Charge Transfer Analysis
# Compare charges before and after adsorption
wf = Workflow("Charge transfer analysis")
# Clean slab Bader
slab_sp = wf.add_task("single_point",
structure=slab_opt.output.structure,
software="vasp", ENCUT=520, LAECHG=True, LCHARG=True)
slab_bader = wf.add_task("charge_analysis",
chgcar=slab_sp.output.chgcar,
aeccar0=slab_sp.output.aeccar0,
aeccar2=slab_sp.output.aeccar2)
# Slab+adsorbate Bader
ads_sp = wf.add_task("single_point",
structure=ads_opt.output.structure,
software="vasp", ENCUT=520, LAECHG=True, LCHARG=True)
ads_bader = wf.add_task("charge_analysis",
chgcar=ads_sp.output.chgcar,
aeccar0=ads_sp.output.aeccar0,
aeccar2=ads_sp.output.aeccar2)
wf.submit()
# After completion:
# dq = q_ads(atom) - q_clean(atom) for each surface atom
# Positive dq = atom lost electrons; Negative dq = atom gained electrons
DAG Structure
structure --> geo_opt --> single_point(LAECHG) --> charge_analysis
Output Format
Bader analysis returns per-atom data:
| Field | Description |
|---|---|
atom_index | 0-based atom index |
element | Element symbol |
bader_charge | Electrons in Bader basin |
valence_electrons | POTCAR valence electron count |
net_charge | valence_electrons - bader_charge (+ means cation) |
volume | Bader basin volume (A^3) |
Interpreting Results
Common Reference Charges (VASP PAW, valence electrons)
| Element | ZVAL (valence e-) | Typical Net Charge Range |
|---|---|---|
| O | 6 | -0.8 to -1.4 (oxide) |
| Ti | 4 or 10 | +1.5 to +2.5 (TiO2) |
| Pt | 10 | -0.1 to +0.3 (metallic) |
| C | 4 | -0.5 to +1.0 (varies) |
| H | 1 | +0.4 to +0.6 (on O), -0.3 (on metal) |
Charge Transfer Upon Adsorption
dq_adsorbate = sum(net_charge of adsorbate atoms in slab+ads system)
- sum(net_charge of same atoms in isolated adsorbate)
- dq < 0: adsorbate gains electrons (acceptor, e.g., CO on Pt)
- dq > 0: adsorbate loses electrons (donor, e.g., Na on surface)
Common Pitfalls
- Always use LAECHG=.TRUE. to get all-electron charge density. Bader analysis on pseudocharge (CHGCAR alone) gives wrong atomic charges because core electrons are missing.
- PREC=Accurate and a fine FFT grid improve Bader basin boundaries. Coarse grids can misassign charge near atomic boundaries.
- Bader charges are NOT formal oxidation states. They are typically smaller in magnitude (e.g., Ti in TiO2 shows +2.3, not +4).
- For charge transfer analysis, use the SAME computational settings for the reference and adsorbed systems.
- The Bader program (Henkelman group) must be available on the HPC.
CatGo calls it automatically during
charge_analysispost-processing. - For spin-polarized systems, Bader can also partition spin density -- this gives magnetic moments per atom.