| name | neb-irc-activation-energy |
| description | NEB-IRC activation energy pipeline for reaction barriers using GFN2-xTB and pysisyphus. Optimize reactant and product geometries, run CI-NEB path search, optimize the transition state with a Hessian, verify with IRC (one imaginary mode, endpoints matching reactant/product, single NEB maximum), and report the electronic and Gibbs barriers. Use when you need a transition state, reaction barrier, activation energy, minimum energy path, or intrinsic reaction coordinate. Covers reactant/product atom-ordering pitfalls, feasibility sizing for single-core runs, and thermochemistry corrections. Renders an IRC energy-profile plot and an animated TS imaginary-mode HTML viewer. For 2D reaction scheme drawing use rdkit-chemdraw-cdxml. |
| license | CC-BY-4.0 |
NEB-IRC activation energy pipeline
Overview
Computes a reaction activation energy end to end — optimize reactant and product, find the
minimum energy path with climbing-image NEB, refine the transition state with a Hessian, and
confirm it with IRC — using GFN2-xTB through pysisyphus. Outputs a verified TS geometry, the
barrier (ΔE‡; ΔG‡ after thermal corrections), an IRC energy profile (irc_energy_profile.png),
and an animated TS imaginary-mode viewer (ts_imaginary_mode.html). Verification is required,
not optional: a converged TS is meaningless until its single imaginary mode and IRC endpoints
are checked.
When to Use
- Finding the transition state for an elementary reaction step and its activation energy
- Computing a reaction barrier (ΔE‡ or ΔG‡) to rank a series of related reactions
- Running a climbing-image NEB / minimum energy path between a reactant and product
- Verifying a candidate TS with IRC — does it connect the intended reactant and product?
- Screening barriers at a cheap semi-empirical level before committing DFT time
Reach for DFT on a multi-core node instead when you need quantitative agreement with
experiment; GFN2-xTB barriers are semi-quantitative (see references/energetics.md). For a 2D
scheme figure of the reaction, use the rdkit-chemdraw-cdxml skill instead.
Prerequisites
- Tools:
xtb (GFN2-xTB engine), pysisyphus (pysis CLI for the path pipeline)
- Python:
matplotlib for the IRC plot (the TS animation HTML needs no packages)
- Input:
reactant.xyz and product.xyz with identical atom ordering (see Step 1)
- Environment: single core suffices; set
OMP_NUM_THREADS to match physical cores
Work in a local scratch dir (e.g. /tmp/rxn/), not a mounted/networked workspace:
pysisyphus creates and deletes symlinks and throws PermissionError mid-run on s3fs/FUSE.
Copy results out at the end.
Materialize the bundled scripts into the scratch dir first. They can't be run in place from
the skill directory, so use your file tools to read each one and save it into your working dir
before running it. The scripts live in this skill's scripts/ folder (next to this SKILL.md):
scripts/setup_env.sh
scripts/pipeline.yaml
scripts/check_result.py
scripts/plot_irc.py
The TS imaginary-mode animation is not produced here — read the
molecular-visualization-3dmol skill and use its mol_viewer.py (Step 6).
Check for the tools; install only if missing (inside pixi/conda, invoke via pixi run xtb):
cd /tmp/rxn
command -v xtb && command -v pysis || bash setup_env.sh
source "${ROOT:-${HOME:-/tmp}/xtbenv}/env.sh"
Workflow
Step 1: Prepare reactant and product geometries
Most failures originate here, not in the NEB. Build the product by editing a copy of the
reactant so atom ordering is identical — a permuted order gives a path that is geometrically
valid and chemically meaningless. Align non-reacting groups so a spectator conformational
change does not fold into the barrier. For bimolecular reactions use a pre-reaction complex as
the reactant, not separated fragments (NEB converges poorly from infinite separation, and the
reference state changes the reported barrier — record it).
from pathlib import Path
lines = Path("reactant.xyz").read_text().splitlines()
natoms = int(lines[0])
atoms = [ln.split() for ln in lines[2:2 + natoms]]
Path("product.xyz").write_text("\n".join([str(natoms), "product"] + [" ".join(a) for a in atoms]) + "\n")
Step 2: Check the endpoints sit in different basins
If the reacting groups start too close, preoptimization carries the reactant over the barrier
and both endpoints relax to the same structure; the NEB then returns a flat profile and the TS
search aborts. This looks like success in the log until it fails minutes later, so compare the
two pre-optimized endpoints on the key reacting bond.
import numpy as np
def load_xyz(fn):
lines = open(fn).read().splitlines()
return np.array([[float(v) for v in ln.split()[1:4]] for ln in lines[2:2 + int(lines[0])]])
r, p = load_xyz("first_pre_opt.xyz"), load_xyz("last_pre_opt.xyz")
i, j = 0, 5
dr, dp = np.linalg.norm(r[i] - r[j]), np.linalg.norm(p[i] - p[j])
assert abs(dr - dp) > 0.3, "endpoints nearly identical: move the reacting fragment further out"
Step 3: Run the pipeline
The template chains preopt → IDPP interpolation → CI-NEB → RS-I-RFO TS optimization with
Hessian → IRC both directions → endpoint reoptimization. Set charge and mult in
pipeline.yaml before running — the default charge: 0 is wrong for any ion and converges
silently to a meaningless TS. Add alpb: <solvent> for solution reactions. Whatever you set
here must match every standalone xtb call in Step 5. Raise max_cycles to 150–200 above
~50 atoms.
pysis pipeline.yaml > pipeline.log 2>&1
tail -40 pipeline.log
ΔE‡ and the reaction energy come from the pipeline's | BARRIERS | block, referenced to the
reactant endpoint (check_result.py in Step 4 reports the same numbers):
Left: 0.00 kJ mol-1 # reactant endpoint
TS: 107.84 kJ mol-1 # dE‡ = TS - Left = 107.84 kJ/mol
Right: 10.19 kJ mol-1 # dE_rxn = Right - Left = 10.19 kJ/mol
Step 4: Verify the transition state
Never report a barrier before this passes. The checker applies all three gates (see Key
Concepts) and exits 0 only if every one passes.
python3 check_result.py pipeline.log
Step 5: Compute thermochemistry and report the barrier
Report ΔE‡ and the level of theory; for comparison against experimental rates, report ΔG‡,
which needs Hessians on the TS and reactant. Every standalone xtb call must use the same
--chrg, --uhf, and solvent as pipeline.yaml, on the pipeline's optimized geometries — not
the raw input. A gas-phase Hessian against a solvated barrier, or a missing --chrg, yields
a nonsensical (often negative) ΔG‡.
xtb forward_end_final_geometry.xyz --hess --gfn 2 --alpb water --chrg -1 --uhf 0 > r_hess.log 2>&1
xtb ts_final_geometry.xyz --hess --gfn 2 --alpb water --chrg -1 --uhf 0 > ts_hess.log 2>&1
grep -i "TOTAL FREE ENERGY" r_hess.log ts_hess.log
Step 6: Deliver the two visuals
IRC energy profile — plot_irc.py reads gfn/charge/mult/solvent from pipeline.yaml and
recomputes each IRC frame's energy at that exact level (the *_irc.trj comment lines carry
none). Override with --charge/--mult/--alpb/--gfn only if you edited the pipeline after running.
python3 plot_irc.py
TS imaginary-mode animation — produced by the molecular-visualization-3dmol skill, not
here. Read that skill and run its mol_viewer.py on the ts_imaginary_mode_000.trj that
tsopt: do_hess: True wrote (grab the frequency from check_result.py for the label):
python3 mol_viewer.py ts_imaginary_mode_000.trj --mode trajectory \
--title "Transition-state mode" --subtitle "imaginary mode -621.8 cm-1" --out ts_imaginary_mode.html
Key Parameters
Set in pipeline.yaml unless noted.
| Parameter | Section | Default | Range / Options | Effect |
|---|
gfn | calc | 2 | 0, 1, 2 | GFN parametrization; 2 is the standard choice |
charge / mult | calc | 0 / 1 | integers | Set explicitly; wrong values silently give a wrong TS |
alpb | calc | off | solvent name (water, ...) | Implicit solvation; changes the barrier |
pal | calc | 1 | physical cores | Threads; xTB parallel efficiency is modest |
between | interpol | 8 | 6–12 | Intermediate NEB images (between+2 total) |
climb | cos | True | True/False | Climbing image; gives a usable TS guess |
max_cycles | opt | 80 | 80–200 | Raise above ~50 atoms |
do_hess | tsopt | True | True/False | Required — the imaginary-frequency gate depends on it |
Key Concepts
The three verification gates and what a failure means:
| Gate | Failure | Meaning and fix |
|---|
| Imaginary frequencies | 0 found | Optimizer fell into a minimum; perturb along the NEB tangent and rerun tsopt |
| Imaginary frequencies | ≥2 found | Higher-order saddle; displace along the lowest non-reactive mode and reoptimize |
| Imaginary frequencies | 1, wrong mode | Confirm it is the bonds breaking/forming — a methyl rotation also shows exactly one |
| IRC endpoints | mismatch | TS connects other species; may be a real TS for a different reaction — do not report |
| NEB profile | multiple maxima | Not an elementary step; split at the intervening minimum and run each segment |
Barrier definitions differ by reference and corrections: ΔE‡ (electronic), ΔE‡+ZPE, ΔH‡,
ΔG‡ (for kinetics). For bimolecular reactions the reference state (separated reactants vs
pre-reaction complex) shifts the number — record which was used. Full table in
references/energetics.md.
Submerged barriers. For an ion + neutral in the gas phase (e.g. anionic SN2) the TS can
sit below the separated reactants — a negative barrier against separated reactants is real,
not a bug. Reference to the pre-reaction complex (the pipeline's endpoint) and/or add alpb
solvation, which lifts it to a positive, experiment-comparable value.
Common Recipes
Recipe: Split a multi-step reaction into elementary steps
When to use: check_result.py reports multiple NEB maxima — it names the intermediate image
index(es). Extract that image from the NEB path and run the pipeline on each half.
from pathlib import Path
N = 5
lines = Path("final_geometries.trj").read_text().splitlines()
n = int(lines[0].split()[0])
Path("intermediate.xyz").write_text("\n".join(lines[N * (n + 2):(N + 1) * (n + 2)]) + "\n")
Recipe: Refine the electronic energy with a DFT single point
When to use: the xTB geometry is fine but you need a better barrier. Keep the xTB geometry and
thermal corrections; replace only the electronic energy on 3 structures (≤30 atoms).
from pyscf import gto, dft
def electronic_energy(xyz_fn, basis="def2-svp", xc="b3lyp"):
mol = gto.M(atom=xyz_fn, basis=basis)
mf = dft.RKS(mol); mf.xc = xc
return mf.kernel()
dE = (electronic_energy("ts_final_geometry.xyz") - electronic_energy("reactant.xyz")) * 2625.4996
print(f"DFT dE‡ = {dE:.1f} kJ/mol (add xTB G_corr for dG‡)")
Expected Outputs
pipeline.log — full run log; parsed by check_result.py
ts_final_geometry.xyz — the optimized transition state
final_geometries.trj — the converged NEB path (per-image energies in comment lines)
ts_imaginary_mode_000.trj — TS displaced along the imaginary mode (input to the animation)
irc_energy_profile.png — from plot_irc.py; ts_imaginary_mode.html — from the molecular-visualization-3dmol skill (Step 6)
- A barrier: ΔE‡ from the BARRIERS block, ΔG‡ after Hessian thermal corrections
Troubleshooting
| Problem | Cause | Solution |
|---|
xtb: command not found | Env not sourced | source "${ROOT:-${HOME:-/tmp}/xtbenv}/env.sh" in every new shell |
scripts/…: No such file / GitHub 404 | Bundled scripts not copied into the workdir | Read them from this skill's scripts/ folder with your file tools and save locally (Prerequisites); not on GitHub |
setup_env.sh: HOME: unbound variable | HOME unset under set -u | Fixed in the shipped script; if patching, export HOME="${HOME:-/tmp}" first |
PermissionError on a symlink mid-run | pysisyphus symlinks on a mounted/s3fs dir | Run in a local dir (/tmp/rxn/), copy results back |
| ΔG‡ negative or absurd | Hessian charge/solvent ≠ pipeline, or raw input geometry used | Match --chrg/--uhf/alpb to pipeline.yaml; use the optimized endpoint geometry (Step 5) |
| Barrier below separated reactants | Submerged barrier for ion + neutral | Expected in gas phase; reference the pre-reaction complex and/or add alpb |
| NEB profile nearly flat, TS aborts | Endpoints in the same basin | Move the reacting fragment further out (Step 2) |
| Path is chemically nonsensical | Permuted atom order between endpoints | Rebuild product from a copy of the reactant (Step 1) |
| Job killed / never finishes | System too large for the budget | Check references/feasibility.md; split stages or shrink the model |
qm optimizer crashes on cycle 1 | QuickMin instability | Use type: lbfgs under opt (the template default) |
No imaginary-mode trajectory found | ts_imaginary_mode_000.trj absent | Ensure tsopt: do_hess: True ran; re-run tsopt |
| Animation HTML blank |
Bundled Resources
scripts/setup_env.sh — installs xtb (GitHub release) + pysisyphus (PyPI), writes env.sh
scripts/pipeline.yaml — full preopt→NEB→TSopt→IRC→endopt template with inline comments
scripts/check_result.py — verification of the three gates (exit 0 = all pass); prints ΔE‡
scripts/plot_irc.py — builds irc_energy_profile.png (recomputes IRC-frame energies at the pipeline level)
references/feasibility.md — measured timings, atom-count sizing, what DFT can/can't do here
references/energetics.md — ΔE‡/ΔH‡/ΔG‡ definitions, thermochemistry, reporting conventions
Related Skills
- molecular-visualization-3dmol — supplies
mol_viewer.py, which renders the TS imaginary-mode animation and can play back the IRC/NEB path; materialize it alongside this skill's scripts
- rdkit-chemdraw-cdxml — draw the reaction as a 2D scheme figure
References
- xtb documentation — GFN2-xTB methods and CLI
- pysisyphus documentation — COS/NEB, TS optimizers, IRC
- Bannwarth, Ehlert, Grimme, J. Chem. Theory Comput. 2019, 15, 1652 — GFN2-xTB method paper
- Steinmetzer, Kupfer, Gräfe, Int. J. Quantum Chem. 2021, 121, e26550 — pysisyphus paper
- ASE / PySCF — geometry I/O and DFT single points