q2D-Materials: Stacking-first perovskite architecture

q2D-Materials is a template-driven library for stacking quasi-2D and bulk perovskites. Instead of shipping a single geometry, we provide a set of hackable layer types (L1, RP1, M1, …) that you can arrange however you want—much like an architecture studio that swaps floor plates. Our tooling then handles ion assignment, molecular alignment, Glazer tilts, spacer orientation, and export. Because everything is encoded as JSON templates you can version-control, you are free to invent new stack types without editing the core library. Our framework providing a fully hackable, layer-sequence-driven approach that decouples geometry from composition.

Reproducible hacking (Nix encouraged)

# Recommended: one command, pinned dependencies
nix develop

# Or the classic pip workflow
pip install ase numpy rdkit

Why Nix? Repeatable builds. No “works on my machine”. You still get the same hackable Python environment—just deterministic.

Stacking storyboard

Our entire philosophy boils down to stacking. Pick a template, choose a layer_sequence, repeat along c. The three frames below (generated by Examples/plot.py) show the same cubic template rendered after placing only L1, then L1-L2, then L1-L2-L1.

Every other tour (Glazer tilts, DJ spacers, RP steps) is just this storyboard with different layers and surface metadata.

Build your own templates

Templates live in q2D_Materials/builders/data/*.json. Each template defines named_layers with [site, x_frac, y_frac] entries. You can add S# sites for spacers, Ap for surface cations, additional B offsets, or whatever else fits your chemistry. Examples/2_Templates.md walks through two canonical examples (cubic and Jagodzinski), and you can expand that pattern to reduced cells, Glazer-ready primitives, or your own experimental stacking faults.

Because the templates are just JSON, you can script their creation, lint them in CI, and share them like any other data asset. Provide either a Python list (["L2", "M1", "RP1", "RP2"]) or a hyphenated string ("L2-M1-RP1-RP2") as layer_sequence—we normalize both.

Stacking archetypes: DJ & RP

Templates carry more than A/B/X positions—they also mark spacer anchors. In q2D_Materials/builders/data/reduced.json, for example, the M1 layer contains:

"M1": [
  ["S1", 0.25, 0.75],
  ["S2", 0.75, 0.25],
  ["X", 0.25, 0.25],
  ["X", 0.75, 0.75]
]

Those S# tags define ground anchor points. Any layer that follows and reuses the same labels becomes the sky for that pair. We reuse this simple idea for two families:

• Dion–Jacobson (DJ) stacks place two spacer-bearing layers back-to-back (think M1 followed immediately by another M1). Double-NH₃ molecules connect matching labels, so one end binds to the ground, the other to the sky. It feels like drawing a section: one bridge per S#. See Examples/images/dj_bulk.png for the reduced-template render.
• Ruddlesden–Popper (RP) alternates a perovskite slab, then two surface layers (RP1/RP2) that expose S# only on one side. The following layer exposes the matching labels, so you always know which side is the spacer “ceiling.” We show the same RP block in plan (Examples/images/rp_glazer_top.png), elevation (Examples/images/rp_base_side.png), and an isometric cut (Examples/images/rp_atomic_side.png). Because every layer is typed (L1, M1, RP1, …), you can remix DJ and RP logic in one template without touching the core code.

Whenever you edit a template or layer_sequence, run Examples/plot.py to refresh every figure used throughout the docs.

Quick usage

from q2D_Materials.core.creator import q2D_creator
from ase.io import write

q2d = q2D_creator()

bulk = q2d.create_perovskite(
    structure_type="bulk",
    A_ions="MA",
    B_ions="Pb",
    X_ions="I",
    xy_expansion=(1, 1),
    template="cubic",
    glazer_angles=[0, 0, 5],
    glazer_pattern=["0", "0", "+"],
)
write("bulk.vasp", bulk, sort=True)

Supported Structure Types

• Bulk: 3D perovskites (tiling via xy_expansion, optional Bp, Glazer tilts)
• Monolayer: 2D slabs with thickness, vacuum, spacer, penetration
• Twist: Build twisted stacks from monolayers via twist(...)

Ion recommender

Get recommendations for compatible ions based on database occurrence:

q2d = q2D_creator()

# Get recommendations based on X = Cl
recommendations = q2d.recommend(X='Cl', top_n=5)
print(recommendations['B'])  # Top 5 B-site cations
print(recommendations['A'])  # Top 5 A-site cations
print(recommendations['spacer'])  # Top 5 spacers

Documentation index

Regenerate every figure with nix develop -c python3 Examples/plot.py and browse the Markdown references:

• Examples/1_Creator.md
• Examples/2_Templates.md
• Examples/3_Glazer.md
• Examples/4_Jagodzinski.md
• Examples/5_Monolayer.md
• Examples/6_Twist.md
• Examples/7_DionJacobson.md
• Examples/8_Ruddlessden_Popper.md

Gallery — program capabilities

Image	What it demonstrates
	Layer stacking flexibility – Shows how changing just the layer_sequence parameter builds increasingly complex structures from the same template, demonstrating automated layer assembly and ion population.
	Automated octahedral tilting – Illustrates how the framework automatically applies Glazer tilt patterns to break cubic symmetry, enabling systematic exploration of perovskite distortions.
	Hybrid organic-inorganic assembly – Demonstrates automated molecular spacer attachment between perovskite layers, with precise control over spacer orientation and penetration depth.
	Multi-view structural analysis – Shows different Ruddlesden-Popper structure from plan, elevation, and isometric perspectives, highlighting stepped layer architectures and surface termination.
	Twisted interface engineering – Demonstrates the creation of twisted bilayer perovskites with controlled interlayer distances and arbitrary twist angles, enabling moiré pattern studies.

References

[1] Kunz, S. L., Haefner, M., & Clemens, O. "``hexagonal'' perovskites: From stacking sequence to space group symmetry and new opportunities." Chem. Mater. 36, 23 (2024).

[2] Stanton, R., & Trivedi, D. J. "Pyrovskite: A software package for the high-throughput construction, analysis, and featurization of two- and three-dimensional perovskite systems." J. Chem. Phys. 159, 6 (2023).

License

MIT License