Material-specific Deep-learned AI-Driven Engines

For design, optimization & performance prediction of Polymeric Materials

Material Property Prediction
Aging /Degradation

We can predict response of any polymeric material (with unknown compounds) using existing sparse and heterogonous databses Z through regressing Y on Z followed by prediction of new data points Z*.
Our Engines can be used to extend almost any database to new systems, allowing prediction of new data, rapid exploration beyond training databases, and rapid optimization to assure accurate prediction of myriad polymer materials properties for many classes of polymeric materials.

Polymer degradation

Polymer aging prediction

Polymer durability

Polymer life prediction

Polymer performance degradation

Polymer material aging

Polymer part life cycle

Polymer component degradation

Polymer part aging

Polymer part life prediction

Materials discovery & design

Our Deep-learned engines seek to balance exploitation of information contained in existing data through previous polymeric material development efforts and exploration of less-sampled portions of the design space .Using Active learning method, engines can reach the target compound as efficiently as possible by first quickly sampling potential regions of interest, followed by adaptive sampling of the exploitation-exploration tradeoff to move toward a compound with target objective with the fewest number of testing.

Inverse Material Design(Compound Optimization)

Our inverse Design engines are based on generative adversarial networks (GANs) which are particularly designed to map property-compound space to track the compound target features to generate, screen and subsequently discover new stable hydride compounds on-the-fly.

Applications

Considering low computational cost and short development cycle of our Physics-based AI-driven engines, they provide a powerful alternative for processing of existing data with significant cost advantage in analysis, design and optimization of the materials.

Resins

&

Composites

Coatings

Elastomers

Adhesives

&

Thermal Pastes

Insulation

&

Di-electrics

Engine can be used to help designers in selection and maintenance of composite materials by providing input on material degradation over times. Our engine can particularly describe the following behaviors for epoxy, PU, Cyanate and carbon-carbon composites.

- Pyrolysis
-Ablation
-Irradiation

Coatings can be optimized for their anti-reflection, or refractive index matching performances in specific conditions, such as automotive industry or space.
Typical materials are silicon dioxide, tantalum pentoxide, magnesium
fluoride, zinc sulfide and thorium fluoride

Gaskets, seals and O-rings can be specifically designed to achieve certain properties in extreme environments, such as high pressure, high temperature, corrosive, or radiate environments. Fluorinated elastomers can be specifically designed to excellent corrosion resistance, but are not as
good under radiation.

Our engines can accelerate the search process for new formulations to achieve target-specific products that can stand the test of severe environments such as
- Extreme Vibrations
- Intense Heat
-Extreme Cold
- Ionizing Radiation
-Hot & wet conditions

In extreme applications, Cable and wiring insulation are a major concern. Our engine can help the designers to estimate performance of certain insulation materials against projected environment. The engine is specially relevant in space electronics, such as in bus, thruster and antenna deployment areas, or in Nuclear cables and wires.