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Agent Skill · 研究检索

pymatgen(pymatgen 搜索)

pymatgen 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。

pymatgen 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 53,170。

总安装 539周安装 22GitHub Stars 公开资料未说明下载 174核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:pymatgen(pymatgen 搜索)
来源仓库:https://github.com/jimmc414/kosmos
仓库路径:skills/pymatgen
安装命令:
npx skills add jimmc414/kosmos --skill "pymatgen"
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add jimmc414/kosmos --skill "pymatgen"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

pymatgen 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。适用于材料科学领域的数据查询与筛选,支持通过关键词匹配相关研究内容或技术文档。

通过 npx skills add jimmc414/kosmos --skill "pymatgen" 命令安装,需确认宿主环境是否支持 GitHub 技能加载。使用前建议核实权限范围、维护状态及是否会触发联网或文件操作,避免误执行系统命令。

可结合原始 README 进一步验证具体功能和使用限制,确保符合实际工作流需求。

来源仓库内路径:skills/pymatgen

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add jimmc414/kosmos --skill "pymatgen";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

pymatgen 怎么安装?

在终端执行 npx skills add jimmc414/kosmos --skill "pymatgen"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pymatgen 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

pymatgen 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

pymatgen 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pymatgen 用的人多吗?

公开数据是累计安装 539 次,近一周安装 22 次,下载 174 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

pymatgen 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
pymatgen

pymatgen 搜索 · 本页

539—接触敏感数据MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Pymatgen - Python Materials Genomics

Overview

Pymatgen is a comprehensive Python library for materials analysis that powers the Materials Project. Create, analyze, and manipulate crystal structures and molecules, compute phase diagrams and thermodynamic properties, analyze electronic structure (band structures, DOS), generate surfaces and interfaces, and access Materials Project's database of computed materials. Supports 100+ file formats from various computational codes.

When to Use This Skill

This skill should be used when:

  • Working with crystal structures or molecular systems in materials science
  • Converting between structure file formats (CIF, POSCAR, XYZ, etc.)
  • Analyzing symmetry, space groups, or coordination environments
  • Computing phase diagrams or assessing thermodynamic stability
  • Analyzing electronic structure data (band gaps, DOS, band structures)
  • Generating surfaces, slabs, or studying interfaces
  • Accessing the Materials Project database programmatically
  • Setting up high-throughput computational workflows
  • Analyzing diffusion, magnetism, or mechanical properties
  • Working with VASP, Gaussian, Quantum ESPRESSO, or other computational codes

Quick Start Guide

Installation

# Core pymatgen
uv pip install pymatgen

# With Materials Project API access
uv pip install pymatgen mp-api

# Optional dependencies for extended functionality
uv pip install pymatgen[analysis]  # Additional analysis tools
uv pip install pymatgen[vis]       # Visualization tools

Basic Structure Operations

from pymatgen.core import Structure, Lattice

# Read structure from file (automatic format detection)
struct = Structure.from_file("POSCAR")

# Create structure from scratch
lattice = Lattice.cubic(3.84)
struct = Structure(lattice, ["Si", "Si"], [[0,0,0], [0.25,0.25,0.25]])

# Write to different format
struct.to(filename="structure.cif")

# Basic properties
print(f"Formula: {struct.composition.reduced_formula}")
print(f"Space group: {struct.get_space_group_info()}")
print(f"Density: {struct.density:.2f} g/cm³")

Materials Project Integration

# Set up API key
export MP_API_KEY="your_api_key_here"
from mp_api.client import MPRester

with MPRester() as mpr:
    # Get structure by material ID
    struct = mpr.get_structure_by_material_id("mp-149")

    # Search for materials
    materials = mpr.materials.summary.search(
        formula="Fe2O3",
        energy_above_hull=(0, 0.05)
    )

Core Capabilities

1. Structure Creation and Manipulation

Create structures using various methods and perform transformations.

From files:

# Automatic format detection
struct = Structure.from_file("structure.cif")
struct = Structure.from_file("POSCAR")
mol = Molecule.from_file("molecule.xyz")

From scratch:

from pymatgen.core import Structure, Lattice

# Using lattice parameters
lattice = Lattice.from_parameters(a=3.84, b=3.84, c=3.84,
                                  alpha=120, beta=90, gamma=60)
coords = [[0, 0, 0], [0.75, 0.5, 0.75]]
struct = Structure(lattice, ["Si", "Si"], coords)

# From space group
struct = Structure.from_spacegroup(
    "Fm-3m",
    Lattice.cubic(3.5),
    ["Si"],
    [[0, 0, 0]]
)

Transformations:

from pymatgen.transformations.standard_transformations import (
    SupercellTransformation,
    SubstitutionTransformation,
    PrimitiveCellTransformation
)

# Create supercell
trans = SupercellTransformation([[2,0,0],[0,2,0],[0,0,2]])
supercell = trans.apply_transformation(struct)

# Substitute elements
trans = SubstitutionTransformation({"Fe": "Mn"})
new_struct = trans.apply_transformation(struct)

# Get primitive cell
trans = PrimitiveCellTransformation()
primitive = trans.apply_transformation(struct)

Reference: See references/core_classes.md for comprehensive documentation of Structure, Lattice, Molecule, and related classes.

2. File Format Conversion

Convert between 100+ file formats with automatic format detection.

Using convenience methods:

# Read any format
struct = Structure.from_file("input_file")

# Write to any format
struct.to(filename="output.cif")
struct.to(filename="POSCAR")
struct.to(filename="output.xyz")

Using the conversion script:

# Single file conversion
python scripts/structure_converter.py POSCAR structure.cif

# Batch conversion
python scripts/structure_converter.py *.cif --output-dir ./poscar_files --format poscar

Reference: See references/io_formats.md for detailed documentation of all supported formats and code integrations.

3. Structure Analysis and Symmetry

Analyze structures for symmetry, coordination, and other properties.

Symmetry analysis:

from pymatgen.symmetry.analyzer import SpacegroupAnalyzer

sga = SpacegroupAnalyzer(struct)

# Get space group information
print(f"Space group: {sga.get_space_group_symbol()}")
print(f"Number: {sga.get_space_group_number()}")
print(f"Crystal system: {sga.get_crystal_system()}")

# Get conventional/primitive cells
conventional = sga.get_conventional_standard_structure()
primitive = sga.get_primitive_standard_structure()

Coordination environment:

from pymatgen.analysis.local_env import CrystalNN

cnn = CrystalNN()
neighbors = cnn.get_nn_info(struct, n=0)  # Neighbors of site 0

print(f"Coordination number: {len(neighbors)}")
for neighbor in neighbors:
    site = struct[neighbor['site_index']]
    print(f"  {site.species_string} at {neighbor['weight']:.3f} Å")

Using the analysis script:

# Comprehensive analysis
python scripts/structure_analyzer.py POSCAR --symmetry --neighbors

# Export results
python scripts/structure_analyzer.py structure.cif --symmetry --export json

Reference: See references/analysis_modules.md for detailed documentation of all analysis capabilities.

4. Phase Diagrams and Thermodynamics

Construct phase diagrams and analyze thermodynamic stability.

Phase diagram construction:

from mp_api.client import MPRester
from pymatgen.analysis.phase_diagram import PhaseDiagram, PDPlotter

# Get entries from Materials Project
with MPRester() as mpr:
    entries = mpr.get_entries_in_chemsys("Li-Fe-O")

# Build phase diagram
pd = PhaseDiagram(entries)

# Check stability
from pymatgen.core import Composition
comp = Composition("LiFeO2")

# Find entry for composition
for entry in entries:
    if entry.composition.reduced_formula == comp.reduced_formula:
        e_above_hull = pd.get_e_above_hull(entry)
        print(f"Energy above hull: {e_above_hull:.4f} eV/atom")

        if e_above_hull > 0.001:
            # Get decomposition
            decomp = pd.get_decomposition(comp)
            print("Decomposes to:", decomp)

# Plot
plotter = PDPlotter(pd)
plotter.show()

Using the phase diagram script:

# Generate phase diagram
python scripts/phase_diagram_generator.py Li-Fe-O --output li_fe_o.png

# Analyze specific composition
python scripts/phase_diagram_generator.py Li-Fe-O --analyze "LiFeO2" --show

Reference: See references/analysis_modules.md (Phase Diagrams section) and references/transformations_workflows.md (Workflow 2) for detailed examples.

5. Electronic Structure Analysis

Analyze band structures, density of states, and electronic properties.

Band structure:

from pymatgen.io.vasp import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotter

# Read from VASP calculation
vasprun = Vasprun("vasprun.xml")
bs = vasprun.get_band_structure()

# Analyze
band_gap = bs.get_band_gap()
print(f"Band gap: {band_gap['energy']:.3f} eV")
print(f"Direct: {band_gap['direct']}")
print(f"Is metal: {bs.is_metal()}")

# Plot
plotter = BSPlotter(bs)
plotter.save_plot("band_structure.png")

Density of states:

from pymatgen.electronic_structure.plotter import DosPlotter

dos = vasprun.complete_dos

# Get element-projected DOS
element_dos = dos.get_element_dos()
for element, element_dos_obj in element_dos.items():
    print(f"{element}: {element_dos_obj.get_gap():.3f} eV")

# Plot
plotter = DosPlotter()
plotter.add_dos("Total DOS", dos)
plotter.show()

Reference: See references/analysis_modules.md (Electronic Structure section) and references/io_formats.md (VASP section).

6. Surface and Interface Analysis

Generate slabs, analyze surfaces, and study interfaces.

Slab generation:

from pymatgen.core.surface import SlabGenerator

# Generate slabs for specific Miller index
slabgen = SlabGenerator(
    struct,
    miller_index=(1, 1, 1),
    min_slab_size=10.0,      # Å
    min_vacuum_size=10.0,    # Å
    center_slab=True
)

slabs = slabgen.get_slabs()

# Write slabs
for i, slab in enumerate(slabs):
    slab.to(filename=f"slab_{i}.cif")

Wulff shape construction:

from pymatgen.analysis.wulff import WulffShape

# Define surface energies
surface_energies = {
    (1, 0, 0): 1.0,
    (1, 1, 0): 1.1,
    (1, 1, 1): 0.9,
}

wulff = WulffShape(struct.lattice, surface_energies)
print(f"Surface area: {wulff.surface_area:.2f} Ų")
print(f"Volume: {wulff.volume:.2f} ų")

wulff.show()

Adsorption site finding:

from pymatgen.analysis.adsorption import AdsorbateSiteFinder
from pymatgen.core import Molecule

asf = AdsorbateSiteFinder(slab)

# Find sites
ads_sites = asf.find_adsorption_sites()
print(f"On-top sites: {len(ads_sites['ontop'])}")
print(f"Bridge sites: {len(ads_sites['bridge'])}")
print(f"Hollow sites: {len(ads_sites['hollow'])}")

# Add adsorbate
adsorbate = Molecule("O", [[0, 0, 0]])
ads_struct = asf.add_adsorbate(adsorbate, ads_sites["ontop"][0])

Reference: See references/analysis_modules.md (Surface and Interface section) and references/transformations_workflows.md (Workflows 3 and 9).

7. Materials Project Database Access

Programmatically access the Materials Project database.

Setup:

  1. Get API key from https://next-gen.materialsproject.org/
  2. Set environment variable: export MP_API_KEY="your_key_here"

Search and retrieve:

from mp_api.client import MPRester

with MPRester() as mpr:
    # Search by formula
    materials = mpr.materials.summary.search(formula="Fe2O3")

    # Search by chemical system
    materials = mpr.materials.summary.search(chemsys="Li-Fe-O")

    # Filter by properties
    materials = mpr.materials.summary.search(
        chemsys="Li-Fe-O",
        energy_above_hull=(0, 0.05),  # Stable/metastable
        band_gap=(1.0, 3.0)            # Semiconducting
    )

    # Get structure
    struct = mpr.get_structure_by_material_id("mp-149")

    # Get band structure
    bs = mpr.get_bandstructure_by_material_id("mp-149")

    # Get entries for phase diagram
    entries = mpr.get_entries_in_chemsys("Li-Fe-O")

Reference: See references/materials_project_api.md for comprehensive API documentation and examples.

8. Computational Workflow Setup

Set up calculations for various electronic structure codes.

VASP input generation:

from pymatgen.io.vasp.sets import MPRelaxSet, MPStaticSet, MPNonSCFSet

# Relaxation
relax = MPRelaxSet(struct)
relax.write_input("./relax_calc")

# Static calculation
static = MPStaticSet(struct)
static.write_input("./static_calc")

# Band structure (non-self-consistent)
nscf = MPNonSCFSet(struct, mode="line")
nscf.write_input("./bandstructure_calc")

# Custom parameters
custom = MPRelaxSet(struct, user_incar_settings={"ENCUT": 600})
custom.write_input("./custom_calc")

Other codes:

# Gaussian
from pymatgen.io.gaussian import GaussianInput

gin = GaussianInput(
    mol,
    functional="B3LYP",
    basis_set="6-31G(d)",
    route_parameters={"Opt": None}
)
gin.write_file("input.gjf")

# Quantum ESPRESSO
from pymatgen.io.pwscf import PWInput

pwin = PWInput(struct, control={"calculation": "scf"})
pwin.write_file("pw.in")

Reference: See references/io_formats.md (Electronic Structure Code I/O section) and references/transformations_workflows.md for workflow examples.

9. Advanced Analysis

Diffraction patterns:

from pymatgen.analysis.diffraction.xrd import XRDCalculator

xrd = XRDCalculator()
pattern = xrd.get_pattern(struct)

# Get peaks
for peak in pattern.hkls:
    print(f"2θ = {peak['2theta']:.2f}°, hkl = {peak['hkl']}")

pattern.plot()

Elastic properties:

from pymatgen.analysis.elasticity import ElasticTensor

# From elastic tensor matrix
elastic_tensor = ElasticTensor.from_voigt(matrix)

print(f"Bulk modulus: {elastic_tensor.k_voigt:.1f} GPa")
print(f"Shear modulus: {elastic_tensor.g_voigt:.1f} GPa")
print(f"Young's modulus: {elastic_tensor.y_mod:.1f} GPa")

Magnetic ordering:

from pymatgen.transformations.advanced_transformations import MagOrderingTransformation

# Enumerate magnetic orderings
trans = MagOrderingTransformation({"Fe": 5.0})
mag_structs = trans.apply_transformation(struct, return_ranked_list=True)

# Get lowest energy magnetic structure
lowest_energy_struct = mag_structs[0]['structure']

Reference: See references/analysis_modules.md for comprehensive analysis module documentation.

Bundled Resources

Scripts (scripts/)

Executable Python scripts for common tasks:

  • structure_converter.py: Convert between structure file formats

- Supports batch conversion and automatic format detection - Usage: python scripts/structure_converter.py POSCAR structure.cif

  • structure_analyzer.py: Comprehensive structure analysis

- Symmetry, coordination, lattice parameters, distance matrix - Usage: python scripts/structure_analyzer.py structure.cif --symmetry --neighbors

  • phase_diagram_generator.py: Generate phase diagrams from Materials Project

- Stability analysis and thermodynamic properties - Usage: python scripts/phase_diagram_generator.py Li-Fe-O --analyze "LiFeO2"

All scripts include detailed help: python scripts/script_name.py --help

References (references/)

Comprehensive documentation loaded into context as needed:

  • core_classes.md: Element, Structure, Lattice, Molecule, Composition classes
  • io_formats.md: File format support and code integration (VASP, Gaussian, etc.)
  • analysis_modules.md: Phase diagrams, surfaces, electronic structure, symmetry
  • materials_project_api.md: Complete Materials Project API guide
  • transformations_workflows.md: Transformations framework and common workflows

Load references when detailed information is needed about specific modules or workflows.

Common Workflows

High-Throughput Structure Generation

from pymatgen.transformations.standard_transformations import SubstitutionTransformation
from pymatgen.io.vasp.sets import MPRelaxSet

# Generate doped structures
base_struct = Structure.from_file("POSCAR")
dopants = ["Mn", "Co", "Ni", "Cu"]

for dopant in dopants:
    trans = SubstitutionTransformation({"Fe": dopant})
    doped_struct = trans.apply_transformation(base_struct)

    # Generate VASP inputs
    vasp_input = MPRelaxSet(doped_struct)
    vasp_input.write_input(f"./calcs/Fe_{dopant}")

Band Structure Calculation Workflow

# 1. Relaxation
relax = MPRelaxSet(struct)
relax.write_input("./1_relax")

# 2. Static (after relaxation)
relaxed = Structure.from_file("1_relax/CONTCAR")
static = MPStaticSet(relaxed)
static.write_input("./2_static")

# 3. Band structure (non-self-consistent)
nscf = MPNonSCFSet(relaxed, mode="line")
nscf.write_input("./3_bandstructure")

# 4. Analysis
from pymatgen.io.vasp import Vasprun
vasprun = Vasprun("3_bandstructure/vasprun.xml")
bs = vasprun.get_band_structure()
bs.get_band_gap()

Surface Energy Calculation

# 1. Get bulk energy
bulk_vasprun = Vasprun("bulk/vasprun.xml")
bulk_E_per_atom = bulk_vasprun.final_energy / len(bulk)

# 2. Generate and calculate slabs
slabgen = SlabGenerator(bulk, (1,1,1), 10, 15)
slab = slabgen.get_slabs()[0]

MPRelaxSet(slab).write_input("./slab_calc")

# 3. Calculate surface energy (after calculation)
slab_vasprun = Vasprun("slab_calc/vasprun.xml")
E_surf = (slab_vasprun.final_energy - len(slab) * bulk_E_per_atom) / (2 * slab.surface_area)
E_surf *= 16.021766  # Convert eV/Ų to J/m²

More workflows: See references/transformations_workflows.md for 10 detailed workflow examples.

Best Practices

Structure Handling

  1. Use automatic format detection: Structure.from_file() handles most formats
  2. Prefer immutable structures: Use IStructure when structure shouldn't change
  3. Check symmetry: Use SpacegroupAnalyzer to reduce to primitive cell
  4. Validate structures: Check for overlapping atoms or unreasonable bond lengths

File I/O

  1. Use convenience methods: from_file() and to() are preferred
  2. Specify formats explicitly: When automatic detection fails
  3. Handle exceptions: Wrap file I/O in try-except blocks
  4. Use serialization: as_dict()/from_dict() for version-safe storage

Materials Project API

  1. Use context manager: Always use with MPRester() as mpr:
  2. Batch queries: Request multiple items at once
  3. Cache results: Save frequently used data locally
  4. Filter effectively: Use property filters to reduce data transfer

Computational Workflows

  1. Use input sets: Prefer MPRelaxSet, MPStaticSet over manual INCAR
  2. Check convergence: Always verify calculations converged
  3. Track transformations: Use TransformedStructure for provenance
  4. Organize calculations: Use clear directory structures

Performance

  1. Reduce symmetry: Use primitive cells when possible
  2. Limit neighbor searches: Specify reasonable cutoff radii
  3. Use appropriate methods: Different analysis tools have different speed/accuracy tradeoffs
  4. Parallelize when possible: Many operations can be parallelized

Units and Conventions

Pymatgen uses atomic units throughout:

  • Lengths: Angstroms (Å)
  • Energies: Electronvolts (eV)
  • Angles: Degrees (°)
  • Magnetic moments: Bohr magnetons (μB)
  • Time: Femtoseconds (fs)

Convert units using pymatgen.core.units when needed.

Integration with Other Tools

Pymatgen integrates seamlessly with:

  • ASE (Atomic Simulation Environment)
  • Phonopy (phonon calculations)
  • BoltzTraP (transport properties)
  • Atomate/Fireworks (workflow management)
  • AiiDA (provenance tracking)
  • Zeo++ (pore analysis)
  • OpenBabel (molecule conversion)

Troubleshooting

Import errors: Install missing dependencies

uv pip install pymatgen[analysis,vis]

API key not found: Set MP_API_KEY environment variable

export MP_API_KEY="your_key_here"

Structure read failures: Check file format and syntax

# Try explicit format specification
struct = Structure.from_file("file.txt", fmt="cif")

Symmetry analysis fails: Structure may have numerical precision issues

# Increase tolerance
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
sga = SpacegroupAnalyzer(struct, symprec=0.1)

Additional Resources

Version Notes

This skill is designed for pymatgen 2024.x and later. For the Materials Project API, use the mp-api package (separate from legacy pymatgen.ext.matproj).

Requirements:

  • Python 3.10 or higher
  • pymatgen >= 2023.x
  • mp-api (for Materials Project access)

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