💎 Computational Mineralogy  ·  Crystallographic Physics  ·  High-Pressure Phase Dynamics

MINERALCO

Seven-Parameter Crystal Intelligence  ·  Mantle Phase Dynamics  ·  Open-Source EOS Engine

A physically rigorous seven-parameter Crystal Intelligence Septuplet for equation-of-state modelling, lattice thermodynamics, and mantle phase transition prediction across Earth's full pressure-temperature interior.

📊 Live Dashboard 📄 Research Paper pip install meneralco
0.19% RMS ΔV/V · All 47 Minerals
47 Benchmark Minerals · 0–363 GPa
91.5% CSI Phase Prediction Accuracy
7 Crystal Intelligence Parameters

Decoding the Earth's Solid Interior

Every cubic centimetre of mineral material inside the Earth is subject to forces no surface laboratory can sustain indefinitely. MINERALCO integrates all seven governing parameters into a single unified framework.

Pressures reach 363 GPa at the inner-core boundary — 3.6 million Earth atmospheres. Temperatures climb to ~6,000 K at the core. Minerals operating under these conditions control everything from seismic wave speed to mantle viscosity to volcanic eruption dynamics.

MINERALCO provides the first unified seven-parameter framework — the Crystal Intelligence Septuplet (CIS) — that simultaneously encodes all information required to predict a mineral's equation of state, thermal expansion, phase stability, and lattice energy under any P-T condition accessible within Earth.

Validated against 3,200 experimental P-V-T data points from synchrotron diamond anvil cell and multi-anvil press studies, MINERALCO achieves mean RMS volumetric accuracy of 0.19% across the full mantle pressure range.

# Load 47-mineral CIS benchmark from mineralco import EOSFitter, PhaseMapper from mineralco import LatticeAnalyzer # Fit BM3-EOS to bridgmanite P-V data fitter = EOSFitter() result = fitter.fit_bm3( pressure=pvt['P_GPa'], volume=pvt['V_cm3mol'], mode="BM3" ) print(result.K0) # → 260.7 ± 3.8 GPa # Crystal Stability Index mapper = PhaseMapper() csi = mapper.csi( K0=185.1, Vs=39.49, Kp=4.14, Sy="cubic", alpha=2.10e-5, gamma=1.27 ) print(f"CSI = {csi:.2f}") # → CSI = 0.91 ⚠ Transition imminent # PREM comparison at 660 km print(result.Vp_at_depth(660)) # → 10.23 km/s (PREM: 10.27 km/s)

Every dimension of Earth's crystal identity

Seven physically independent parameters, each capturing a distinct aspect of mineral behaviour under extreme pressure and temperature — from the crystallographic unit cell to thermodynamic coupling between lattice vibrations and volume.

01
w₁ = 0.28 · CSI dominant weight
K₀
Bulk Modulus

Zero-pressure incompressibility — the foundational EOS stiffness parameter. Determines seismic velocity and mineral density at depth. Every major mantle phase transition is driven by a K₀ discontinuity between competing phases.

Bridgmanite: K₀ = 261 GPa
02
Crystallographic DNA
a, b, c
Lattice Parameters

The three edge lengths and angles of the crystallographic unit cell — encoding atomic bond lengths, densities, and elastic anisotropy. Measured by synchrotron X-ray diffraction to ±0.001 Å precision above 100 GPa.

Bridgmanite: 4.775 × 4.929 × 6.897 Å
03
w₃ = 0.17 · Sᵧ correlated
K'
Pressure Derivative

First pressure derivative ∂K/∂P at P=0 — the non-linear stiffening rate under compression. Critical for EOS accuracy above ~10 GPa. The MINERALCO Symmetry-Stiffness Paradigm predicts K' from crystal system alone (r = −0.88).

Cubic: K' = 4.01 ± 0.24 universally
04
w₄ = 0.13 · Master variable
Sᵧ
Crystal Symmetry

Space group (1–230) and crystal system (cubic → triclinic). Governs the Madelung constant, elastic anisotropy, and the number of independent elastic constants (3 to 21). Neumann's Principle: all physical properties must exhibit the crystal's symmetry.

7 crystal systems · 230 space groups
05
w₅ = 0.10
α
Thermal Expansion

Volumetric thermal expansion ∂(lnV)/∂T|ₚ (K⁻¹). Governs volume change with temperature — critical for the mantle adiabat and phase boundary Clapeyron slopes. A mineral at 2,500 K in the lower mantle has a volume ~3–5% larger than at 300 K.

Bridgmanite: α = 2.0 × 10⁻⁵ K⁻¹
06
w₆ = 0.09 · α correlated (r=0.79)
γ
Grüneisen Parameter

The most physically fundamental parameter in the CIS. Dimensionless thermodynamic coupling γ = αK₀Vₛ/Cᵥ — the backbone of the Mie-Grüneisen EOS. Links thermal pressure to volume; quantifies how strongly thermal energy contributes to pressure.

Mantle minerals: γ ≈ 1.0–2.0 typical
07
w₂ = 0.19 · Primary observable
Vₛ
Specific Volume

Molar volume Vₛ = M/ρ (cm³/mol) — the primary observable in synchrotron P-V diffraction experiments and the dependent variable in all EOS curve-fitting procedures. The net volumetric outcome of all competing pressure and thermal forces.

Bridgmanite: 24.45 cm³/mol (ambient)
BM3-EOS · Mie-Grüneisen · CSI
CIS
The Complete Framework

Together, these seven parameters fully parameterise the third-order Birch-Murnaghan EOS and the Mie-Grüneisen thermal correction — providing a complete thermodynamic description of any mineral across Earth's full P-T interior.

0–363 GPa · 300–6,000 K

From 0.86 to 0.93 — predicting the deep Earth

The CSI has been calibrated against all four major seismic discontinuity-producing transitions in Earth's mantle. A mineral whose CSI reaches 0.85 is within ±2 GPa of a phase transition in 87% of benchmark cases.

Phase Transition P_exp (GPa) P_MINERALCO (GPa) CSI Seismic Feature
Olivine → Wadsleyite 13.5 ± 0.3 13.8
0.86
410 km discontinuity
Wadsleyite → Ringwoodite 18.0 ± 0.5 18.3
0.88
520 km discontinuity
Ringwoodite → Bridgmanite + FP 23.5 ± 0.4 23.2
0.91
660 km — most precise test
Bridgmanite → Post-perovskite 125 ± 2 124
0.87
D'' layer · ~2,600 km
ε-Fe → Liquid Iron (melting) 330 ± 5 327
0.93
Inner Core Boundary · ~5,150 km

Crystal symmetry predicts K' — Pearson r = −0.88

Crystal System K' Mean Std Dev N Minerals Key Minerals
Cubic (highest symmetry) 4.01 ± 0.24 11 MgO, FeO, garnet, spinel, diamond
Tetragonal 4.18 ± 0.31 4 Rutile TiO₂, stishovite, scheelite
Hexagonal / Trigonal 4.29 ± 0.38 8 ε-Fe, corundum, calcite, quartz
Orthorhombic 4.44 ± 0.41 15 Bridgmanite, forsterite, enstatite
Monoclinic 4.67 ± 0.52 6 Wadsleyite, diopside, jadeite
Triclinic (lowest symmetry) 4.91 ± 0.61 3 Feldspars, kyanite, rhodonite

Three pillars of the Crystal Intelligence framework

Key results from the 47-mineral benchmark validate the CIS framework and establish findings with profound implications for planetary interior modelling.

🔷
0.19% RMS ΔV/V · All 47 Minerals · 3,200 Points
EOS Precision

Mean volumetric prediction error of 0.19% across 3,200 experimental P-V-T data points at pressures from 0 to 363 GPa and temperatures from 300 to 5,000 K. Best-in-class: periclase MgO achieves 0.07% — near-experimental accuracy from seven crystallographic numbers alone.

91.5% Phase Transition Accuracy · 43 of 47 Minerals
Phase Prediction

The Crystal Stability Index correctly predicts phase transition onset within ±1.5 GPa for 43 of 47 benchmark minerals, including the 660 km discontinuity (ringwoodite → bridgmanite + ferropericlase) at 23.2 GPa vs 23.5 ± 0.4 GPa experimental. Mean CSI at transition: 0.88 ± 0.03.

🌐
r²=0.971 Thermodynamic vs. Phonon Grüneisen · 28 Minerals
Grüneisen Self-Consistency

Thermodynamic and phonon Grüneisen parameters agree to r² = 0.971 across 28 minerals with both data types — confirming that MINERALCO CIS is thermodynamically internally consistent rather than empirically over-parameterised. Mean discrepancy: |Δγ| = 0.063.

"The bridgmanite seven-parameter CIS predicts PREM seismic velocities at 660 km depth to within 0.4% for Vₚ and < 0.1% for Vₛ — without any empirical adjustment."

— MINERALCO, Section 6.4 · Bridgmanite PREM Comparison

Open science, open source

All code, datasets, CIS parameter databases, and 15 Jupyter notebooks reproducing manuscript figures are fully open-access and reproducible from the archived repository.

2026 Physics and Chemistry of Minerals · Springer · Submitted
MINERALCO: A Seven-Parameter Atomic Architecture Framework for Mineral Phase Intelligence — Equation of State Modelling, Lattice Thermodynamics & Mantle Phase Transition Prediction
DOI: 10.5281/zenodo.19009597 ↗
PyPI Python Package Index · Open Source
meneralco — Seven-parameter Crystal Intelligence Septuplet framework for high-pressure mineral phase dynamics
pip install meneralco ↗
Data Zenodo · CERN Data Centre · Open Access
MINERALCO Dataset: 47-mineral CIS parameter archive + 3,200 P-V-T experimental data points (0–363 GPa, 300–5,000 K)
Zenodo Archive ↗

"Seven parameters to decode the Earth's solid core."

— Samir Baladi, March 2026

Access the full framework, live data,
and open code

All 15 Jupyter notebooks reproduce manuscript figures and statistical outputs without external dependencies beyond the archived data. Fully reproducible mineral physics.