The emergence of the catalysis artificial intelligence paradigm transforms modern chemical and catalytic research

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. 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. 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. Recent advancements in artificial intelligence have significantly impacted science and technology. Despite the concerns and potential risks associated with artificial intelligence, the responsible integration of these tools is essential for the advancement of science and technology, especially in the field of catalysis. It is necessary to integrate catalysis, with the diverse tools of artificial intelligence, ultimately giving rise to a new paradigm of catalysis–AI. The disconnect between catalysis and artificial intelligence is particularly pronounced in Ibero-American countries, which have served as fundamental pillars in the advancement of catalytic knowledge for decades.