To the point:

In view of recent geopolitical tensions and the disruption of energy imports, an interdisciplinary and international research team led by Yafang Cheng at the Max Planck Institute for Chemistry assessed how the costs and benefits of renewable energy expansion in the European Union may evolve under changing conditions.

Fossil fuel energy prices have risen to a level where faster deployment of renewable energies to achieve carbon neutrality is expected to provide substantial air quality, health and economic co-benefits beyond climate protection. The investigated scenarios, building on the fuel price levels observed during the years 2021–2023, yield EU-wide net benefits in the range of approximately 100 to 600 billion Euros.

A newly developed system dynamics model with country-specific parameters was applied to account for dynamic changes of electricity costs upon rapid renewable expansion, allowing for more realistic projections.

The National Institute for Materials Science (NIMS) discovered a thermal response phenomenon in which Ba₄Ru₃O₁₂, a dense, inorganic oxide formed by high-pressure synthesis, increases in volume by about 4.4% when heated, and this expanded state is retained even after cooling. Normally, such a large volume change is accompanied by substantial changes in the crystal structure or chemical reactions and alters the material properties. In this research, however, NIMS elucidated that “giant irreversible expansion” occurs through atomic rearrangement within a crystal, while retaining the basic crystal framework, i.e., the symmetry of the crystal structure, and chemical composition. The research result demonstrates a new thermal response mechanism in oxide materials, and is expected to lead to new design guidelines for ceramic materials used in a high-temperature environment or materials that control thermal deformation and stress.

Researchers at the University of California, Los Angeles (UCLA) have developed a novel image projection system that delivers super-resolution images over an extended depth of field. By combining a neural network-based digital encoder with a passive all-optical diffractive decoder, the system drastically compresses image data for efficient transmission of information. This platform operates without extra power at the decoding stage, promising advancements for next-generation virtual and augmented reality displays.

Conical intersections are crucial molecular switching points in light-driven reactions, but accurately predicting them usually requires computations. A researcher from Shibaura Institute of Technology has developed a new low-cost quantum chemistry method that can simultaneously describe ground and excited molecular states while efficiently locating these elusive structures. The approach reproduces benchmark geometries with strong accuracy and enables practical simulations of photochemical processes, making it promising for applications in photocatalysis, solar cells, and biological light-response studies.