Formulation and Print Process Optimization for Industrial Paints and Inks

The Ever-Evolving Complexity of Paint and Ink Formulation

R&D in paints and inks has never been more demanding. Whether working with organic or inorganic pigments, formulators face the constant challenge of balancing a wide array of properties (stability, color strength, print quality, interlayer adhesion, shear-thinning behavior, and weathering resistance) while simultaneously managing costs and navigating increasingly stringent regulatory requirements.

Every substrate, be it paper, glass, metal, or 3D-printed polymer, interacts uniquely with inks and coatings. Minor variations in porosity, surface energy, or thermal conductivity can disrupt ink leveling, reduce wet-edge retention, or compromise color development due to uneven film formation or premature solvent evaporation.

Emerging application areas, such as flexible electronics and bioactive surfaces, bring new material demands and functional requirements. At the same time, long-standing issues persist: unstable dispersions continue to cause nozzle clogging, and adhesion failure on metalized films remains a common development bottleneck.

Add to this the constraints imposed by various printing processes: inkjet, screen, gravure, and flexographic, as well as compliance with REACH, Prop 65, VOC limitations, and other regulatory frameworks. The result is a formidable R&D landscape where traditional trial-and-error approaches are increasingly unsustainable.

Why Conventional Formulas Optimization Falls Short

Ink formulation is rarely a linear process. A slight change to pigment load, resin, or solvent can cause ripples across material outcomes. Add in process variables like drop volume or curing dose, and the ink formulation problem space quickly becomes too complex to navigate by hand. This complexity is made worse by fragmented workflows. Data lives in spreadsheets, lab notebooks, emails, and disconnected instruments, making it difficult to trace issues, avoid repeating tests, or understand cause and effect. Long iteration cycles often mean valuable insights are lost along the way. Even minor adjustments in shade or gloss can trigger a full reformulation, not just between print platforms, but sometimes even within the same system. This can be due to process limitations or shifts in equipment setup, substrate response, or ink-substrate interaction.

And while Inks and paints performance is increasingly assessed through objective methods like high-resolution optical analysis (e.g., confocal or 3D profilometry), dot gain and mottle indexing, cross-hatch adhesion tests, salt spray corrosion evaluation, and gloss retention tracking, most formulation workflows still struggle to connect these metrics back to formulation and process variables in a meaningful, structured way.

Data-Driven Formulation for Printability and Coating Control

MaterialsZone turns experimental and production data into a foundation for better, faster formulation. It links your lab systems and instruments into a single intelligent environment and uses machine learning to reveal patterns and guide next steps.

All paints and inks data - formulation, print process, and print evaluation, are consolidated in one harmonized system. To facilitate data upload and aggregation, MaterialsZone connects directly to rheometers, drop watchers, printers, ovens, spectrophotometers, LIMS, and more.

Each formula record is enriched with a full properties profile, and when linked with associated performance results, these datasets form a searchable, evolving knowledge base. This foundation gives R&D teams a holistic view of how formulations perform.

With this infrastructure in place, teams can:

• Define targets and constraints, and explore the fastest path to a viable, high-performance formula
• Discover patterns between formulation choices and critical outputs
• Predict how new formulations will behave across substrates and print methods
• Reuse prior results instead of starting from scratch
• Strengthen model accuracy with every pass/fail record or process log

Smarter Ink Development with Smart DoE and AI Modeling

Whether you're optimizing an existing ink system or exploring new territory, MaterialsZone helps you move faster and smarter. Instead of running full-factorial tests across countless formulation and process variables, teams can simulate likely outcomes based on prior experimental history. Transfer learning pulls insights from similar systems, while AI models generate compact, high-value test sets. Active learning algorithms then recommend the most informative next experiment.

You can ask focused questions like:

• How does pigment load affect jetting stability and color strength?
• Can we boost gloss without increasing dry time?
• What’s the best trade-off between flow, adhesion, and VOC content?
• How will this formulation behave on coated vs. uncoated substrates?
• Which variables are driving film defects or print mottle?

Predictions are grounded in your own lab data and enhanced by image-based evaluations, mottle detection, edge sharpness, color uniformity, enabling optimization across both formulation chemistry and visual quality. Once targets like gloss or dry time are defined, the system reveals the best trade-offs to test next.

Quantified Results for Paints and Inks Innovators

 Teams using MaterialsZone report:

• 50–70% fewer experiments
• 5× faster development cycles
• 20–40% time savings on compliance reporting
• Smoother scale-up from lab to production
• Greater use of objective print quality data in decision-making workflows

It’s not just faster—it’s smarter, more resilient R&D.