Technology, Science

Hokkaido University launches Institute for Catalysis

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September 18, 2026 by Ivy Delaney

Hokkaido University has launched the Institute for Catalysis, building on its existing Catalysis Research Center. This expansion establishes eight divisions within the Department of Fundamental Research, encompassing areas from catalysis theory to macromolecular science, and represents a comprehensive approach to the field. The Institute aims to address growing needs for environmental conservation, resources, and energy, with a particular focus demonstrated by the dedicated “Research Cluster for Utilization of Natural Carbon Resources.” The university states that its mission is to meet this demand and become a global center for catalysis science research.

Complementing these divisions are four research clusters within the Department of Targeted Research, designed for focused investigation into areas like sustainable catalysts and nano-interface reaction fields. The Institute also established a Central Research Section, housing the Research Cluster for Sustainable Catalyst, and an Extensive Research Section, which includes the Research Cluster for Data-Driven Catalyst Developments. This collaborative structure, with both departmental divisions and targeted research clusters, aims to foster interdisciplinary work and accelerate innovation in catalysis science.

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Avatar of Ivy Delaney

Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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