lammps

name	lammps
description	LAMMPS molecular dynamics with DeepMD/DPA machine-learning potentials ONLY. This skill generates LAMMPS input files (in.lammps) using pair_style deepmd. Classical force fields (Stillinger-Weber, Tersoff, EAM, etc.) are NOT supported and must NEVER be suggested. The default model is the DPA3 pretrained checkpoint frozen with the Omat24 head (from DEEPMD_MODEL_PATH env var), identical to the ase skill. A model file is always required — do NOT ask the user whether they want to use a classical potential instead. Bohrium's default DeepMD image (registry.dp.tech/dptech/deepmd-kit) already includes LAMMPS — no separate LAMMPS installation is needed. Covers structure conversion, input generation, Bohrium submission via bohrium skill, and result collection.
metadata	{"tools":["run_bash","run_python_file","load_skill_resource"],"dependent_skills":["bohrium"],"tags":["lammps","deepmd","dpa","dpa3","deep-potential","machine-learning-potential","md","molecular-dynamics","npt","nve","bohrium"]}

LAMMPS / DeepMD Skill

CRITICAL CONSTRAINTS — READ FIRST

1. This skill ONLY supports pair_style deepmd. Do NOT suggest, mention, or offer classical force fields (Stillinger-Weber, Tersoff, EAM, ReaxFF, etc.) as alternatives. There is no "choice" — DeepMD is the only option.

2. A model is always available. The environment variable DEEPMD_MODEL_PATH points to a pretrained DPA3 model. The tool automatically freezes it with the Omat24 head (dp --pt freeze --head Omat24). You do NOT need to ask the user for a model file — just run generate_input and it will resolve the model automatically. Only ask if DEEPMD_MODEL_PATH is unset AND the user did not pass --model_path.

3. LAMMPS is already installed in the Bohrium DeepMD image. The default image registry.dp.tech/dptech/deepmd-kit provides both LAMMPS and DeePMD-kit. Do NOT ask whether LAMMPS is installed — it is. Use BOHRIUM_DEEPMD_IMAGE (the same env var as the deepmd skill) as the container image.

4. Never present this as a plan to be confirmed. If the user asks for a LAMMPS MD simulation, execute immediately: generate input → submit → collect.

---

How it works

Component	Role
lammps_tools.py	Generate in.lammps + conf.lmp; collect results
bohrium skill	Submit job directories to Bohrium

Every command prints JSON to stdout and exits 0 on success, 1 on error.

---

Mandatory workflow sequence

1. Obtain a structure — supply an extxyz, POSCAR, CIF, or any ASE-readable file. If the user has no structure, generate one first using the atomic-structure skill.
2. Prepare job directory — run lammps_tools.py generate_input. The model is resolved automatically from DEEPMD_MODEL_PATH and frozen with Omat24 head.
3. Submit jobs — use the bohrium skill for Bohrium platform submission. For full submission details, see:

   load_skill_resource(skill_name="lammps", path="references/bohrium-submission.md")
   

4. Collect results — run collect_results after jobs finish.

---

1. Generate LAMMPS input

Simplest usage (model resolved from DEEPMD_MODEL_PATH automatically)

python lammps_tools.py generate_input --structures POSCAR

This uses all defaults: DPA3 model, Omat24 head, NPT, 300 K, 1 bar, 1M steps.

NVE ensemble at 600 K

python lammps_tools.py generate_input \
    --structures structures.extxyz \
    --ensemble nve --temperature 600 --runtime_steps 500000

NPT at zero pressure

python lammps_tools.py generate_input \
    --structures POSCAR \
    --temperature 300 --pressure 0.0

All frames from a multi-frame file (one job per frame)

python lammps_tools.py generate_input \
    --structures traj.extxyz --frame -1

Key flags

Flag	Default	Description
--structures	required	Any ASE-readable structure file (extxyz, POSCAR, CIF, …)
--model_path	DEEPMD_MODEL_PATH	DeePMD model file. Auto-resolved from env var — usually不需要指定.
--head	Omat24	Multi-task head to freeze. Pass none to skip freezing.
--frame	0	Frame index. -1 = all frames.
--ensemble	npt	npt or nve
--temperature	300.0	Target temperature (K)
--pressure	1	Target pressure in bar (NPT only). LAMMPS units metal uses bar.
--timestep	0.001	Timestep in ps
--runtime_steps	1000000	Number of MD steps
--dump_interval	10000	Trajectory write frequency (steps)
--thermo_interval	100	Thermo output frequency (steps)

Model handling (same as ase)

The pretrained DPA3 model (from DEEPMD_MODEL_PATH) is frozen with dp --pt freeze --head Omat24 before being copied into the job directory. The frozen single-task model is used as pair_style deepmd frozen_model.pth. Pass --head none to skip freezing.

Generated in.lammps example

units           metal
boundary        p p p
atom_style      atomic

neighbor        1.0 bin

read_data       conf.lmp

pair_style      deepmd frozen_model.pth
pair_coeff      * * Si                    # elements sorted alphabetically

velocity        all create 300.0 23456789
timestep        0.001
thermo          100
thermo_style    custom step pe ke etotal temp press vol

fix             1 all npt temp 300.0 300.0 0.1 aniso 1.0 1.0 0.5   # pressure in bar
dump            1 all custom 10000 traj.dump id type xu yu zu
dump_modify     1 sort id

run             1000000

undump          1
unfix           1

---

2. Collect results

python lammps_tools.py collect_results \
    --calc_dirs /tmp/lammps_jobs/lammps_npt_001 /tmp/lammps_jobs/lammps_npt_002

Returns per-job summary: average temperature, pressure, potential energy, volume.

---

3. Submit to Bohrium

For Bohrium platform submission, use the bohrium skill. Full submission details including environment variables, JSON template, and submission commands are in:

load_skill_resource(skill_name="lammps", path="references/bohrium-submission.md")

---

config.yaml

work_dir: lammps