hello-qm/catgo-lrg/charge

Name: charge
Author: hello-qm

Claude Code and agent skill by hello-qm/catgo-lrg

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By hello-qm
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hello-qm/catgo-lrg
server/catgo/workflow/skills/analysis/charge/SKILL.md
Updated 25 Sep 2026
Version 1.0.01 version recorded

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Use when the user asks about Bader charge analysis, charge transfer, oxidation states from DFT, or electron density partitioning.

Install

npx vskill@latest install hello-qm/catgo-lrg/charge

SKILL.md

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

json

{"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

json

{"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

json

{"tool": "catgo_workflow_engine", "arguments": {
  "action": "get_result", "workflow_id": "wf_bader", "task_id": "task_bader"
}}

json

{"tool": "catgo_analyze", "arguments": {
  "action": "charges", "workflow_id": "wf_bader", "task_id": "task_bader"
}}

Python API

Basic Bader Analysis

python

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

python

# 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_analysis post-processing.

For spin-polarized systems, Bader can also partition spin density --

this gives magnetic moments per atom.

Security

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Source

SKILL.md in the repositoryCheckingserver/catgo/workflow/skills/analysis/charge/SKILL.md

Popularity

Repository stars: 172
Repository forks: 18
7-day trend score: 26

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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