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Polymer topology from rheology – the inverse problem, solved


- Topology · Mw · T° → G'(ω), G”(ω), η* in a few seconds. API-driven solution
- Forward (ultra-fast) enables inverse

Your data stays yours
No online access — your data stays yours. Enter your polymer structure, in a few millisecond get storage modulus G’, loss modulus G ” and viscosity. Designed for field decisions, not academic papers.
The upside is enormous
a 10 000× speedup is not incremental; it changes what is possible (real‑timeprocess control, massive parametric sweeps, inverse design)
Preservation of the Milner‑McLeish Structure
Rather than reproducing full tube-theory dynamics, the engine preserves the hierarchical temporal organization characteristic of branched polymer relaxation, enabling fast reduced-order rheological prediction
Stability Against Physical Perturbations
The implementation of fine‑tuned physical corrections such as adjusting relaxation times does not destabilize the algorithm.The solution space remains “smooth,” allowing standard optimizers.
Integrity of the Error Landscape
Where competing models generate chaotic optimization landscapes due to the discretization of topologies, RheoxInverse operates on a physical continuum. Convergence is preserved because the error landscape remains anchored in the thermodynamic reality of time‑scale separation.
RheoxInverse does more than just “fit” curves
It leverages the mathematical stability of Hopf factorization totransform an inverse problem once deemed unsolvable into a fast, reliable, and physically consistentoptimization task.
Built for both R&D and QC
Deployable as an advanced research tool or as an automated, API-driven quality control metric on the factory floor.
The science is proven
Not a vague analogy, but an exact mathematical identity validated againstnumerics.
“Rheox is a proprietary simulation engine (No data leaves your machine) – No AI, just Mathematics – Graph Theory – Complexity reduction O(n).”

Buisson Christophe
RESEARCH PHYSICIST ENGINEER, MeltAlice

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