Next-generation catalyst technologies are transforming chemical manufacturing by enabling sustainable, low-carbon, and energy-efficient process pathways across industries such as energy, chemicals, materials, and advanced manufacturing. Catalysts are central to accelerating the transition toward decarbonized industrial systems, supporting applications including hydrogen production, carbon dioxide (CO₂) utilization, biomass conversion, and sustainable fuel synthesis.

Advancements in catalyst design, including single-atom catalysts, nanostructured materials, electrocatalysts, and bio-inspired systems, are significantly improving activity, selectivity, and stability while reducing reliance on critical materials. At the same time, the integration of artificial intelligence (AI), machine learning (ML), and high-throughput experimentation (HTE) is transforming catalyst discovery into a predictive, data-driven process that reduces development timelines and enhances innovation efficiency.

Emerging digital technologies, such as autonomous laboratories, digital twins, and operando characterization tools, are enabling deeper mechanistic understanding and accelerating the translation of laboratory discoveries into scalable industrial solutions. These technologies are fostering integrated R&D ecosystems that combine computational modeling, experimental validation, and process optimization to deliver next-generation catalytic systems.

• What role do next-generation catalysts play in enabling sustainable, low-carbon, and energy-efficient process pathways across diverse industries?
• Is your R&D roadmap equipped with high-throughput experimentation (HTE) to reduce development timelines and enhance innovation efficiency?
• Are your teams integrating autonomous laboratories and digital twins to translate laboratory discoveries into scalable industrial solutions?