Formulation Deterministic: Property math, surface-energy proxies, and cure-kinetics modeling Adhesive and sealant formulators, bonding engineers, and R&D chemists
Use data analysis to develop stronger adhesives — screen bond strength across substrates, surface treatments, and cure conditions before you cut coupons.When it applies: an adhesive or sealant must meet a bond-strength or durability target on specific substrates and trial-and-error lap-shear testing is too costly.

Scenario

An adhesive must reach a bond-strength and durability target on one or more specific substrates (metal, plastic, composite, glass), often across different surface treatments and cure conditions. Physically testing every chemistry × substrate × treatment × cure combination is slow and expensive.

Worked example. A structural adhesive must bond an aluminum panel to a low-surface-energy polypropylene bracket and survive thermal cycling.

Agent workflow

  1. Read the adhesive chemistry, the target substrates, and the required bond-strength / durability spec.
  2. Substrate adhesion screen — compare surface energies / polarities of the adhesive versus each substrate to flag wetting and adhesion risk, and suggest priming or surface treatment where the mismatch is large.
  3. Adhesive bond-strength screen — predict lap-shear / peel strength for the candidate formulations on each substrate.
  4. Cure-kinetics screen — model the time / temperature cure window so the proposed formulation actually reaches full strength in the process.
  5. Mechanical property screen — estimate modulus / elongation of the cured adhesive to check toughness against thermal-cycling stress.

Demo output

A matrix of candidate formulations × substrates with predicted bond strength, an adhesion-risk flag per substrate (with a priming/treatment suggestion where needed), and a viable cure window. The magic moment: the agent flags the low-surface-energy substrate early and recommends the treatment that unlocks the bond — before any coupons are made.

Deterministic vs LLM

  • Deterministic — property predictions, surface-energy proxies, and the cure-kinetics math.
  • LLM — the bonding-strategy narrative and the substrate/treatment rationale.

Every strength number and adhesion flag is a validated calculation, never an LLM guess. The agent reads and routes; the engine decides.

Data sources

  • Native (offline): RDKit descriptors and surface-energy / polarity proxies; mechanical-property prediction; cure-kinetics modeling; DOE screening designs.
  • Public reference layer: substrate surface-energy references; polymer and additive property data.

Limits

Screening-level guidance, not a substitute for standardized lap-shear / peel testing, environmental aging, or joint-design validation. It ranks the promising chemistry × substrate combinations; the lab confirms the strength.