Researchers at Kumamoto University and Nagoya University have developed a new class of two-dimensional (2D) metal-organic frameworks (MOFs) using triptycene-based molecules, marking a breakthrough in the quest to understand and enhance the physical properties of these promising materials. This innovation opens new possibilities for multifunctional applications in gas/molecular sensors, electrochemical energy storage, and spintronic devices.

New study reveals that the stereochemistry of lipid nanoparticles critically influences safety and efficacy in mRNA delivery.

The National Institute of Polar Research (NIPR) publishes Polar Science, a peer-reviewed quarterly journal dealing with polar science, in collaboration with Elsevier B.V. In the latest issue, it features “Sustainable development in the Arctic for Indigenous peoples”, published as part of its regular issue (Vol. 44, June 2025). The full text of featured articles will be freely accessible worldwide until 14 January 2026.

Osaka Metropolitan University researchers analyzed the interactions between two bacteria that make up intestinal microbiota. 

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics that deals with constantly changing systems, explains why optimal transport theory, a mathematical framework for the optimal change of distribution to reduce the cost, makes generative models optimal. As nonequilibrium thermodynamics has yet to be fully leveraged in designing generative models, the discovery offers a novel thermodynamic approach to machine learning research. The findings were published in the journal Physical Review X.

Industrial anomaly detection is crucial for maintaining quality control and reducing production errors, but traditional supervised models require extensive datasets. While embedding-based methods are promising for unsupervised anomaly detection, they are highly memory-intensive and unsuited to low-light conditions. In a new study, researchers developed a new unsupervised model that utilizes both well-lit and low-light images to achieve computationally efficient and memory-friendly industrial anomaly detection.

Fluorescent markers are extremely useful in science as tools to track molecules or processes as they carry out their unique activities, revealing unknown facts along the way. However, physically introducing fluorescent markers into targets can result in strong background signals, and even when chemically bound, the target’s hydrophobicity may increase, making the process far from straightforward. Moreover, fluorescent markers are often affected by the properties of the solvent in which they operate. To address these challenges, researchers have developed a method to track the behavior of cellulose nanofibers (CNFs) by conjugating water-compatible fluorescent amino acids to the CNFs. As a result, observers can now microscopically visualize CNFs by following the blue fluorescence emitted from them.

Japanese researchers have developed a human cytokine-based designer enzyme. Relying on their rational design workflow, they demonstrated that proteins can serve as ligands with the same precision as synthetic organic ligands. The resulting designer enzyme maintains its original biological functions while gaining new catalytic abilities.