Researchers explore the human immune system by looking at the active components, namely the various genes and cells involved. But there is a broad range of these, and observations necessarily produce vast amounts of data. For the first time, researchers including those from the University of Tokyo built a software tool which leverages artificial intelligence to not only offer a more consistent analysis of these cells at speed but also categorizes them and aims to spot novel patterns people have not yet seen.

Superconductors are famous for carrying electricity without resistance, but a new study shows they can also reshape the crystals in which they are housed. Scientists at Okayama University, Japan, have discovered that the topological superconductor Cu_xBi₂Se₃ can distort its crystal lattice when it reaches the superconducting state. Using synchrotron X-ray diffraction, the team detected structural changes linked to the unusual spin-triplet pairing in this material, revealing a new way superconductivity interacts with crystal structure.

A new study examines nickel and urea in early microbial habitats, showing how ancient cyanobacteria adapted to their chemical surroundings. By recreating Archean conditions in the lab, researchers uncovered clues about the delicate balances that shaped early cyanobacterial life. These findings hint at the unseen factors that may have set the stage for Earth’s first oxygen surge, providing a fresh perspective on the environmental and chemical conditions that allowed oxygen to accumulate in the atmosphere.

The rapid rise of commercial compact fusion devices has triggered fast-growing demand for high-temperature superconducting tapes, creating a major opportunity for the high-temperature superconducting (HTS) tape industry. Pulsed laser deposition (PLD) has been extensively applied for fabrication of heteroepitaxial HTS wires or tapes based on REBCO-type superconductor, also referred to as, coated conductors (CCs). A combination of multi-plume, multi-turn deposition technique and use of high-power excimer lasers has enabled and accelerated the industrialization of REBCO coated conductors. Currently, the annual production of top-tier PLD-based, HTS-wire manufacturers exceeds 3,000 km-12 mm, contributing to over half of the total global HTS wire production. PLD-REBCO tapes have demonstrated excellent in-field performance (I_c> 200 A-4 mm @20K, 20T, B//c) and competitive pricing (~$20/m). PLD technology continues to evolve, demonstrating strong competitive advantages. However, challenges remain in further cost reduction, process stability, and increasing efficiency of raw material utilization. AI-based data mining and tackling emerging fundamental issues are seen as potential solutions to further improve stability and performance.

Organic photovoltaics (OPVs) have achieved remarkable progress, with laboratory-scale single-junction devices now demonstrating power conversion efficiencies (PCEs) exceeding 20%. However, these efficiencies are highly dependent on the thickness of the photoactive layer, which is typically around 100 nm. This sensitivity poses a challenge for industrial-scale fabrication. Achieving high PCEs in thick-film OPVs is therefore essential. This review systematically examines recent advancements in thick-film OPVs, focusing on the fundamental mechanisms that lead to efficiency loss and strategies to enhance performance. We provide a comprehensive analysis spanning the complete photovoltaic process chain: from initial exciton generation and diffusion dynamics, through dissociation mechanisms, to subsequent charge-carrier transport, balance optimization, and final collection efficiency. Particular emphasis is placed on cutting-edge solutions in molecular engineering and device architecture optimization. By synthesizing these interdisciplinary approaches and investigating the potential contributions in stability, cost, and machine learning aspects, this work establishes comprehensive guidelines for designing high-performance OPVs devices with minimal thickness dependence, ultimately aiming to bridge the gap between laboratory achievements and industrial manufacturing requirements.

Identifying and interpreting vacancies in patent maps is a promising approach to discover technological opportunities. However, it remains a challenging task. Recently, scientists from Seoul National University of Science and Technology have developed an innovative machine learning approach based on text-embedding inversion, which translates patent vacancies into human-readable formats, helping to uncover technological opportunities for corporate growth.