A comprehensive review published in Nano Research reveals how mechanical forces—such as fluid shear, matrix stiffness, and cyclic strain—are essential for building realistic organoids and organ-on-a-chip models. The work bridges mechanobiology and microengineering, offering a roadmap for designing next-generation in vitro systems that truly mimic human physiology. These advances could revolutionize drug screening, disease modeling, and personalized medicine.

Niobium/tantalum–tellurium (Nb/Ta–Te) charge density wave materials have been developed for infrared detection. Devices based on these materials enable efficient mid- and long-wave infrared sensing at room temperature under zero-bias conditions, eliminating the need for an external power supply, and achieve a detectivity of up to 10⁸ Jones. Furthermore, by integrating the detector with artificial intelligence (AI)–assisted image enhancement, the quality of single-pixel infrared imaging is significantly improved, offering a promising route toward next-generation low-power, intelligent infrared optoelectronic systems.

Researchers from Heinrich Heine University Düsseldorf (HHU) have taken an important step toward developing intelligent molecular materials. The team headed by Dr Bernd M. Schmidt (Institute of Organic Chemistry and Macromolecular Chemistry) and Professor Dr Jan Meisner (Institute of Physical Chemistry) has shown that complex molecular nanostructures can be selectively activated, disassembled in a controlled way and even reassembled again using ultrasound. The results have now been published in the renowned scientific journal Nature Communications. These findings could, for example, aid the development of more targeted cancer medication in the future.

The stability of zinc metal anodes is a critical bottleneck hindering the practical application of aqueous zinc-ion batteries. The team of Zhaoling Ma and Hongqiang Wang from Guangxi Normal University has developed a ZnV₂O₄ ion-sieve interface layer featuring a three-dimensional tunnel structure. By leveraging the synergistic effect of moderate oxygen vacancies and tunnel geometry, the material achieves ultra-fast and selective Zn²⁺ transport. This design enables symmetric cells to deliver stable cycling for over 3,700 hours at 4 mA cm⁻², and full cells to maintain a capacity retention of 52.5% after 1,000 cycles, offering a promising strategy for long-life aqueous zinc-ion batteries.

Viscosity is a fundamental property that determines how easily a material flows, affecting systems from industrial materials to the Earth's deep interior. Yet, scientists have rarely considered whether viscosity has an upper limit because high-viscosity materials are usually rock-forming minerals outside fluid dynamics studies. Now, a Japanese researcher has combined Earth observations, laboratory experiments, and numerical simulations to estimate a physically meaningful upper viscosity bound of 10^30±2 Pa s, with implications for geophysics and materials.

Researchers at the University of Osaka have used machine learning to develop a systematic framework for structural descriptors in supercooled water. A neural network model was used to quantitatively assess the performance of 16 structural descriptors in differentiating between two states of water, a high-density liquid and a low-density liquid. The framework could be used to further our understanding of the anomalous behavior of water.

The formation of supramolecular polymers within living cells is an emerging strategy for regulating cellular functions, and lipid droplets (LDs) are promising environments for such processes. LDs are cellular organelles composed mainly of neutral lipids, such as triacylglycerols and cholesterol esters, and are deeply involved in cellular functions. However, the self-assembly of supramolecular polymers in neutral lipid-rich environments, such as LDs, is not well understood. To this end, researchers from WPI-ITbM at Nagoya University in Japan have achieved programmable construction of supramolecular polymers in triolein (TO), one of the most abundant lipid components of LDs.

As artificial intelligence drives demand for faster and more energy-efficient hardware, ferroelectric memristors are attracting growing attention. A new review outlines how these devices combine memory, computation, and learning capabilities in a single platform, offering new opportunities for intelligent computing beyond the traditional von Neumann architecture.