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lammps-simulation灯模拟

Agent Skill

lammps-simulation 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

636

周安装

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GitHub Stars

3

下载量

206
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:lammps-simulation(灯模拟)
来源仓库:https://github.com/fl-sean03/agentic-science-worker
仓库路径:skills/lammps-simulation
安装命令:
npx skills add https://github.com/fl-sean03/agentic-science-worker --skill lammps-simulation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/fl-sean03/agentic-science-worker --skill lammps-simulation

简介

用于查找、检索和筛选相关信息,支持多宿主环境。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。
  • 可结合来源仓库和原始 README 进一步核验具体用法。
  • 安装前建议确认权限范围和维护状态,避免触发联网或命令执行。
  • 注意区分只读查询与实际操作的风险边界。lammps-simulation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

LAMMPS Molecular Dynamics Simulation

You are executing LAMMPS molecular dynamics simulations on this workstation.

CRITICAL: Finding Your Own Parameters

You must find force field parameters yourself. They are NOT provided.

How to Find Force Field Parameters

Step 1: Identify what you need

  • What material? (argon, water, copper, etc.)
  • What property? (diffusion, structure, thermal conductivity)
  • What conditions? (temperature, pressure)

Step 2: Search literature

Good search queries:
- "[material] lennard-jones parameters molecular dynamics"
- "[material] force field molecular dynamics"
- "[material] interatomic potential parameters"
- "[water model] parameters" (for TIP3P, TIP4P, SPC/E, etc.)
- "[metal] EAM potential"

Step 3: Find authoritative sources

MaterialSeminal PaperKey Values
Liquid ArgonRahman 1964, Phys. Rev. 136, A405ε/kB=119.8 K, σ=3.405 Å
TIP4P WaterJorgensen 1983, J. Chem. Phys. 79, 926See paper Table I
TIP3P WaterJorgensen 1983 (same paper)ε=0.1521 kcal/mol, σ=3.1507 Å
SPC/E WaterBerendsen 1987, J. Phys. Chem. 91, 6269qO=-0.8476e, ε=0.1553 kcal/mol

Step 4: Download supplementary materials if needed Use Playwright or WebFetch to get SI with parameter tables.

Step 5: Convert units

kJ/mol → kcal/mol: divide by 4.184
eV → kcal/mol: multiply by 23.06
K → kcal/mol: multiply by 0.001987 (kB)

Step 6: Document source in input file

# Lennard-Jones parameters for liquid argon
# Source: Rahman, Phys. Rev. 136, A405 (1964)
# ε/kB = 119.8 K = 0.238 kcal/mol, σ = 3.405 Å
pair_coeff 1 1 0.238 3.405

Binary Location

LAMMPS is configured via environment variable (set in .claude/settings.json or shell):

# From environment variable
LMP="${LMP:-lmp}"  # Falls back to 'lmp' in PATH

# Or check your config
echo $LMP

Execution Commands

CPU:

$LMP -in input.lmp

GPU (for large systems):

$LMP -sf gpu -pk gpu 1 neigh yes -in input.lmp

Complete Workflow (Agentic)

Example: Liquid Argon Diffusion

Given only: "Calculate the self-diffusion coefficient of liquid argon"

You do:

  1. Search literature for argon MD parameters

- Find Rahman 1964 as seminal paper - Extract: ε/kB = 119.8 K, σ = 3.405 Å - Note conditions: T = 94.4 K (triple point), ρ = 1.374 g/cm³

  1. Convert parameters

- ε = 119.8 K × 0.001987 kcal/(mol·K) = 0.238 kcal/mol

  1. Calculate system size

- N = 864 atoms (Rahman's choice, or 256-500 for faster) - Box size from density: L = (N × M / (ρ × Nₐ))^(1/3)

  1. Create input file with citations # Liquid Argon MD - Self-diffusion calculation # Parameters from Rahman, Phys. Rev. 136, A405 (1964) units real atom_style atomic boundary p p p # Create FCC lattice, will melt to liquid lattice fcc 5.26 # ~1.374 g/cm³ region box block 0 6 0 6 0 6 create_box 1 box create_atoms 1 box mass 1 39.948 # Argon # LJ potential - Rahman 1964 parameters pair_style lj/cut 10.0 pair_coeff 1 1 0.238 3.405 # ε=0.238 kcal/mol, σ=3.405 Å # Initialize velocities at target temperature velocity all create 94.4 12345 # Equilibration fix 1 all nvt temp 94.4 94.4 100.0 timestep 2.0 thermo 100 run 10000 # Production with trajectory for MSD reset_timestep 0 dump 1 all custom 100 trajectory.lammpstrj id type x y z run 50000
  2. Run simulation $LMP -in input.lmp
  3. Analyze MSD and extract D

- Use LAMMPS compute msd or post-process trajectory - D = lim(t→∞) MSD(t) / (6t)

  1. Compare to literature

- Rahman 1964: D ≈ 2.43 × 10⁻⁵ cm²/s - Your result should be within ~10%


Common Pair Styles and When to Use

Pair StyleUse ForNotes
lj/cutNoble gases, simple fluidsNeed ε, σ from literature
lj/cut/coul/longMolecular systems with chargesCombine with kspace
eamMetalsDownload.eam file from literature
tersoffCovalent (Si, C, etc.)Use published parameter files
reaxffReactive systemsRequires force field file

Finding EAM Potentials for Metals

  1. Search: "[metal] EAM potential LAMMPS"
  2. Check NIST Interatomic Potentials Repository: https://www.ctcms.nist.gov/potentials/
  3. Download the.eam.alloy or.eam.fs file
  4. Reference in input: pair_style eam/alloy pair_coeff * * Cu_Zhou04.eam.alloy Cu

Input File Structure

  1. Units and style - units real for most molecular systems
  2. Structure - read_data or create with lattice/create_atoms
  3. Force field - pair_style and pair_coeff (YOU FIND THESE)
  4. Dynamics - fix nvt/npt/nve, timestep
  5. Output - thermo, dump
  6. Run - minimize or run

Common Issues and Solutions

  1. "Unknown pair style" - Style not compiled in. Check $LMP -h for available.
  2. "Bond atom missing" - Topology error in data file
  3. "Out of range atoms" - Timestep too large or bad parameters
  4. Wrong temperature/energy - Check unit consistency (real vs metal vs lj)

Property Calculations

Diffusion Coefficient

compute         msd all msd
fix             msd_out all ave/time 100 1 100 c_msd[4] file msd.dat

Then: D = slope(MSD vs t) / 6

Radial Distribution Function

compute         rdf all rdf 100
fix             rdf_out all ave/time 100 1 100 c_rdf[*] file rdf.dat mode vector

Temperature/Pressure

Already in thermo output by default.


Key Principle

Don't use placeholder parameters. Every pair_coeff line should have a citation in the comments. If you can't find parameters, search harder or report that the parameters aren't available in literature.

适合场景

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用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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敏感数据

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安装前确认

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