Inverse materials design

State the properties you need — bulk modulus, shear, anisotropy, Poisson ratio — and get the exact stiffness tensor that realizes them, the nearest real material, or a printable metamaterial when none exists yet. Certified complete, validated blind on 11,265 materials.

📜 Patent OMNI-2026-007 — reduced to practice
11,265
materials validated
9 / 9
blind recovery, rank 1
1 solution
certified, or a proof of none
seconds
full pipeline, on a laptop

Flat vectors get materials wrong

Stiffness tensors are symmetric positive-definite matrices on a curved manifold — not points in flat space. Treating them as 21-vectors introduces bias worth orders of magnitude.

The representation trap

A material is described equally by its stiffness C or its compliance S = C⁻¹. Under Euclidean distance the same pair of materials can look five orders of magnitude closer or farther apart depending on which one you picked — an arbitrary choice silently reorders your whole database.

The fix is exact

The affine-invariant Riemannian metric makes stiffness and compliance exactly isometric — distance ratio 1.000 for every pair. Similarity search, clustering, and inverse design stop depending on representation. The geometry costs nothing where curvature doesn’t matter, and everything where it does.

Property spec → certified tensor → real material

Real math, running in your browser. Set the targets; the exact realizing tensor, its nearest real material by geodesic distance, and — for auxetic / white-space targets — a printable re-entrant lattice are all computed live. Try the Diamond-stiff auxetic preset.

From a tensor to a thing you can make

The target is a tensor; the deliverable is a material. Three bridges cover the gap — and the tool already runs the first two.

01 · RetrievalLIVE

Nearest real material

If a catalogued compound sits near your target, we return it — ranked by affine-invariant geodesic distance across the full database. Blind tests recover held-out materials from their properties alone, 9 of 9.

02 · MetamaterialsLIVE

Printable lattice

When your target is auxetic and no atomic solid applies, we solve the re-entrant lattice geometry that realizes the negative Poisson ratio — with an honest read on the stiffness a real base material and print density can deliver, plus an SVG unit cell.

03 · GenerativeRESEARCH

Candidate compounds

For targets beyond both, generative crystal models conditioned on the tensor propose new compositions for DFT validation — the research frontier, and the natural home for a Materials-Project–scale collaboration.

Completeness, and a map of the unmade

Every solution, or a proof of none

Cubic targets solve in closed form; orthorhombic by homotopy continuation with a posteriori certification — provably exactly one realizing tensor, not one lucky local optimum. For cubic symmetry we prove every positive spec (K, G, A) is realized by exactly one tensor.

The white-space atlas

Because feasibility is never the obstruction, what remains is occupancy. The atlas maps certified-feasible specs no material occupies — like a diamond-stiff auxetic (K=218, G=600 GPa, ν=−0.22), realized uniquely by (c₁₁, c₁₂, c₄₄) = (564, 45, 1039) GPa. A ranked list of synthesis targets elasticity itself does not forbid.

Grounded, not asserted

Peer-reviewed method

“Certified-complete inverse design of elastic stiffness tensors” — affine-invariant geometry + numerical algebraic geometry, submitted to Physical Review Materials.

Reduced to practice

Working engine across six domains, 117 tests. Patent OMNI-2026-007. Cubic at ~10⁵ solves/s; certified homotopy for higher symmetry.

Database-scale

Validated on the 11,265-material Materials Project elasticity set; the same geometry audits data quality (2,018 non-physical tensors flagged).

Have a property target in mind?

API access, a database audit, or a certified inverse-design collaboration — including SBIR / DOE partnerships on the metamaterial track.