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Simpal
A Virtual Lab
Core Architecture

Workflow

How we translate a material question into a digital workflow.

We build the Simpal architecture to convert material structure, formulation context, simulation outputs, and selected experimental data into interpretable property maps and decision support. We structure material knowledge in a traceable way.

Molecular Input

Positions, velocities, topology, and morphology.

Virtual Test

Equilibrium, RNEMD, shear, and deformation.

OTFC Engine

Extraction of stress, relaxation, and descriptors.

Estimators

Constitutive mapping (viscosity, G', G'').

Decision Output

Property curves, uncertainty flags.

Figure: Workflow Architecture. Material and formulation inputs are translated into virtual test protocols, property indicators, validation assumptions, and decision-oriented outputs.

1. Molecular & Coarse-Grain Input

We begin by defining the digital sample. We represent materials from atomistic details to coarse-grained (mesoscopic) models, tracking atomic positions, velocities, topology, morphology, tacticity, chain length, and blend ratios.

2. Virtual Test

Next, we subject the digital sample to virtual tests, the digital equivalent of laboratory tests. We apply thermodynamic equilibration, Reverse Nonequilibrium Molecular Dynamics (RNEMD), SLLOD algorithms for shear flow, and various deformation processes.

3. OTFC Property Engine

During simulation, we extract critical descriptors in real time using our On-The-Fly Calculation (OTFC) engine. We track stress tensors, relaxation spectra, mobility patterns, morphology changes, and molecular interaction parameters.

4. Property Estimators

We then map the raw simulation data to physical properties through constitutive mapping. We connect abstract molecular descriptors to engineering metrics, such as Carreau–Yasuda viscosity curves, oscillatory shear response (G', G'', tan δ), and deformation-response indicators.

5. Decision Output

Finally, we generate a practical decision support map. We provide full property curves, processing-window indicators, uncertainty flags, and highly targeted validation plans to guide your next physical lab experiment.