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Sustainability: “A system engineered to last twice as long may represent a fraction of the lifecycle carbon footprint”
Kaan Aksoy, R&D Manager at Betek Boya, shares insights into how sustainability is driving innovations in the coatings industry. He explains how molecular complexity is being engineered for application simplicity, and how AI tools, bio-based technologies, and regulatory pressures are reshaping formulations to meet performance and compliance goals. Interview by Bettina Hoffmann
Do you observe a trend towards increasing formulation complexity (e.g. multifunctional additives, hybrid systems) or towards simplification (e.g. fewer components, higher robustness) in sustainable coating systems – and what are the technical drivers behind this development?
Kaan Aksoy: The framing of this question as a binary choice complexity versus simplification reflects a tension that is, in our view, a productive false dichotomy. What the industry is actually witnessing is something more intellectually compelling: a convergence in which molecular sophistication at the design level is being deliberately engineered to produce systemic simplicity at the application level.
The underlying chemistry is, without question, growing more complex. Hybrid binder architectures waterborne polyurethane-acrylic interpenetrating networks, silane-functional dispersions, and alkyd-acrylic co-emulsions are consolidating functions that once demanded entirely separate additive packages; multifunctional additives that simultaneously deliver defoaming and wetting performance within a single molecule are gaining significant traction precisely because they reduce formulation component count while increasing process efficiency.
The formulator’s toolbox is expanding, but the goal is always fewer levers for the applicator to manage. What is accelerating this convergence dramatically is the arrival of high-throughput experimentation (HTE) coupled with design of experiment (DoE) methodologies: robotic HTE platforms now enable the rapid, reproducible formulation of paints and their evaluation across substrates at a scale and depth of variable interaction that was simply not achievable with traditional sequential laboratory methods, compressing into days a screening campaign that would formerly have taken months.
The primary strategic driver, however, remains climate urgency. Durability, service life, and repaint frequency now routinely dominate cradle-to-grave environmental impact calculations for coating systems which means that a coating’s performance profile has become inseparable from its sustainability profile. A system engineered to last twice as long, even if it demands a more intricate binder architecture, may represent a fraction of the lifecycle carbon footprint of a simpler but shorter-lived alternative.
At the research frontier, entirely new bio-based binder platforms are emerging such as aqueous poly-butenolide dispersions specifically designed to replace petrochemical acrylates while offering the theoretical possibility of negative CO₂ emissions in the polymeric binder constituent itself. Bio-based vitrimers built on dynamic covalent networks are also entering the coatings research agenda, combining intrinsic self-healing capability with full thermoset recyclability through thermally triggered bond exchange reactions. This is molecular complexity that erases itself from the user’s experience. Perhaps the most transformative development, however, is that machine learning is now being applied directly to formulation optimisation: AI and machine learning are helping companies optimise complex multi-component formulations, meet regulatory demands such as PFAS substitution, and dramatically accelerate R&D cycles while supporting the transfer of critical formulation knowledge to a new generation of scientists.
Concrete industrial cases already demonstrate this shift: AI-driven platforms have compressed new sustainable coating development timelines from six months to one month, a productivity gain that fundamentally redefines the economics of sustainable innovation. In summary, the technical driver is not complexity for its own sake, but intelligent molecular consolidation fewer hazardous substance declarations, fewer application steps, longer service intervals made possible by deeper chemistry, navigated at speed by smarter computational tools.
Event Tip:
The Sustainable Coatings Conference, which takes please November 3 and 4 in Amsterdam, Netherlands, will provide practical insights into low‑carbon technologies, circular economy approaches, bio‑based and water‑based systems, and robust assessment methods such as LCA and mass balance. Learn how the industry is responding to regulatory pressure, customer expectations, and material constraints – and how sustainability can become a measurable business advantage rather than a compliance burden.
How are current and upcoming regulatory restrictions (e.g. on VOCs, hazardous substances or fluorinated chemistries) influencing the design of binders and crosslinking systems, and which new chemistries or approaches do you consider most promising to meet both compliance and high-performance requirements?
Aksoy: The regulatory transformation currently reshaping binder and crosslinker design is arguably the most structurally consequential, the coatings industry has faced since the phaseout of lead-based pigments and its pace is considerably faster. The defining regulatory actions of the past two years have centered on the intensification of PFAS restrictions under EU REACH and the continued tightening of VOC emission standards, forcing systematic and immediate action across the entire raw material supply chain.
The sweeping EU restriction proposal now covers virtually all fluorinated substances containing at least one fully fluorinated methyl or methylene carbon atom, meaning that every fluorinated component in a formulation whether surfactant, wax, or polymeric binder must be analytically verified and systematically assessed for substitution. For binder chemists, this is not a marginal reformulation exercise: fluorinated polymers have historically delivered surface energies, chemical resistance, and barrier properties that are genuinely difficult to reproduce through non-fluorinated pathways, and finding mechanistically distinct alternatives is one of the defining intellectual challenges of contemporary coatings science.
On the VOC front, the pressure is simultaneously pushing formulation away from blocked isocyanate crosslinkers and toward ambient-cure waterborne two-component systems, polyaspartic chemistries, and solvent-free Michael addition networks. Among the chemistries we consider most scientifically promising, non-isocyanate polyurethanes (NIPUs) stand out. NIPUs are synthesised via the aminolysis of cyclic carbonates with amines, yielding urethane linkages under milder and more environmentally benign conditions than conventional isocyanate routes eliminating phosgene-derived reagents entirely and aligning directly with the atom-economy principles of green chemistry.
Recent work demonstrates that silane-modified bio-based NIPU coatings from carbonated soybean oil synthesised via CO₂ insertion followed by co-reaction with ethylenediamine and aminopropyltriethoxysilane produce β-hydroxyurethane–siloxane hybrid networks with thermal stability to 350°C and excellent mechanical ductility, a performance profile that would have seemed unlikely for an isocyanate-free system only a few years ago. Even more striking is the emergence of fully reprocessable NIPU systems from bio-based cyclic carbonates achieving bio-based content of 92–99%, pointing toward a future in which a coating’s recyclability becomes part of its performance specification from the first day of design.
What changes the compliance navigation equation entirely, however, is the integration of digital intelligence. The critical enabling development of 2025 and 2026 has been transfer learning applied to sparse proprietary datasets: earlier generations of predictive models required thousands of labelled experiments to reach useful accuracy, but transfer learning now pre-trains models on large public polymer and formulation repositories, making AI-guided design accessible even for novel substrate-chemistry combinations.
Equally important is the transformation of lifecycle assessment methodology: AI and machine learning are now being applied to predict the environmental performance of candidate formulations directly from Environmental Product Declaration data, addressing inventory data gaps that have historically made LCA calculations slow, expensive, and insufficiently granular for R&D decision-making. This means that global warming potential, acidification, and REACH compliance can now be evaluated computationally at the design stage not as a post-hoc reporting obligation, but as an active constraint in the optimisation loop itself.
With five EU member states having formally submitted to ECHA a REACH restriction covering over 10,000 PFAS substances with the majority of phase-outs expected between 2025 and 2027 the transition is no longer a strategic planning exercise; it is an immediate operational reality. The companies that treat this regulatory pressure as a platform for genuine chemical and digital innovation, rather than minimum-compliance reformulation, will define the performance benchmarks of the next decade. The regulatory environment, viewed through the right lens, is not a constraint on the coatings industry. It is its most powerful research agenda and artificial intelligence is the instrument that finally makes it navigable at speed.
