Exciting new research at Tohoku University’s Advanced Institute for Materials Research (WPI-AIMR) explains how to transform decades of scattered literature data into computable design rules for catalysts. By using human intelligence, regression models, and AI agents, researchers can accelerate the discovery of efficient, low-cost catalysts for clean energy technologies like fuel cells, water splitting, and CO₂ reduction. By combining these methods, researchers can uncover new discoveries that were hidden in the literature data all along.
Catalysts, which speed up chemical reactions, are crucial for many important technologies and manufacturing processes. However, finding the right catalyst for the job is tricky. While the first step is usually to refer to previously published scientific literature, making a cohesive summary of all this data can be overwhelming. Even studies that investigate the same catalyst might cover different experimental conditions and measure different variables, making comparisons difficult. How do we find the best catalyst candidate if the data is all over the place? It would be like trying to compare a database of cake recipes that use different ingredient amounts, bake times, and oven temperatures.
“There is an enormous amount of information in the wealth of scientific literature published so far on catalysts,” remarks Distinguished Professor Hao Li (WPI-AIMR). “But taking all of these disparate, individual studies and summarizing them into actionable information – such as gleaning the blueprints for rational catalyst design – is incredibly difficult.”
This study summarizes three current methods for reorganizing, re-analyzing, and remodeling information that is “hidden” in the literature. The first is using human brainpower to summarize data manually. The second is data analysis, such as performing a statistical analysis called a regression model on big data to get a quantitative assessment of a certain catalyst’s structure-performance characteristics. The third is to use artificial intelligence (AI) to further assess the findings, and propose new candidate materials. Ideally, researchers will use all three together.
“Doing everything by hand is too slow, but relying solely on AI without careful cross-checking can be faulty, so we need a careful balance,” says Li.
Re-analyzing data from multiple studies may reveal new information or even anomalies that need the combination of human intelligence and AI to puzzle out an underlying theory to explain it. In this way, even old data can reveal new tricks.
Developing systematic methods to improve catalyst performance such as those proposed in this paper is highly beneficial to our society as they can lead to the faster development of sustainable energy solutions, reduced reliance on expensive noble metals, and progress toward a carbon-neutral society.
These findings were published in EES Catalysis on May 14, 2026.
About the World Premier International Research Center Initiative (WPI)
The WPI program was launched in 2007 by Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT) to foster globally visible research centers boasting the highest standards and outstanding research environments. Numbering more than a dozen and operating at institutions throughout the country, these centers are given a high degree of autonomy, allowing them to engage in innovative modes of management and research. The program is administered by the Japan Society for the Promotion of Science (JSPS).
See the latest research news from the centers at the WPI News Portal: https://www.eurekalert.org/newsportal/WPI
Main WPI program site: www.jsps.go.jp/english/e-toplevel
Advanced Institute for Materials Research (AIMR)
Tohoku University
Establishing a World-Leading Research Center for Materials Science
AIMR aims to contribute to society through its actions as a world-leading research center for materials science and push the boundaries of research frontiers. To this end, the institute gathers excellent researchers in the fields of physics, chemistry, materials science, engineering, and mathematics and provides a world-class research environment.
AIMR site: https://www.wpi-aimr.tohoku.ac.jp/en/
EES Catalysis
Finding the Hidden Catalytic Knowledge from Literature Data
14-May-2026