Abstract
Abstract Recent advancements in data infrastructure, computational statistics, and artificial intelligence (AI) have inaugurated a transformative era for chemical sciences. These computational paradigms facilitate the optimization of complex systems at an unprecedented rate, transcending the limitations of traditional trial-and-error methodologies. This innovative convergence of domain-specific scientific knowledge and advanced heuristics is pivotal for the engineering of next-generation, sustainable chemical processes characterized by minimized energy footprints and enhanced selectivity. Significantly, this evolution fosters a deep integration between heterogeneous and homogeneous catalysis and the diverse analytical tools emerging from the digital frontier, potentially catalyzing a new “Catalysis–AI” paradigm. However, comprehensive bibliometric analyses reveal a significant break; despite the proliferation of AI literature, its substantive implementation in experimental catalysis remains nascent. The current landscape is hindered by data silos and a lack of standardized descriptors. Consequently, the formulation of robust explanatory and predictive hypotheses—anchored in both physical chemistry and data-driven insights—is imperative. Establishing such a framework is essential for achieving a fundamental understanding of active sites and reaction mechanisms, ultimately addressing the urgent scientific and technological imperatives of modern industry. However, bibliometric analyses reveal that a robust connection between diverse catalytic fields and emerging AI tools remains unestablished. A gap particularly evident in Ibero-American countries despite their strong catalysis tradition. This disconnects risks creating a substantial disparity in advancement rates compared to other scientific domains. Ultimately, bridging this divide is essential to unlock a future human-machine synergy capable of accelerating the design of novel catalytic materials. Graphical Abstract The graphical abstract was generated using NotebookLM, based on the following prompt: Minimalist scientific style with a white background. Display a shower of loose puzzle pieces of different sizes orchestrated from largest to smallest that generate a waveform entering through the left side of a computer that displays basic programming code on its screen. Connected to the right side of this computer by a cable is an android. This android acts as a teacher, writing science-related information on a screen. This whiteboard should contain a reaction coordinate graph, a heterogeneous catalyst model, and chemical molecules.