Yaoli Zhao and colleagues have developed a non-destructive method to determine the percentage of recycled plastic content in a plastic product. By combining multi-modal sensing with machine learning, this approach enables reliable verification of recycled content, supporting regulatory compliance, quality control, and circular plastics manufacturing.

Pingan Ni and colleagues proposed a multidisciplinary framework integrating high-resolution geometric data with multidimensional sky models to reveal spatiotemporal coupling heterogeneities in solar radiation distribution across large-scale heritage surfaces.

Haedo Cho and Patrick Slade developed OpenMetabolics, an open-source smartphone-based energy expenditure monitor with 18% error across real-world activities, outperforming existing devices. This tool could enable large-scale and longitudinal studies of physical activity.

Shensheng Zhao and colleagues present PaUL imaging, a laser-activated nanodroplet approach that achieves super-resolution microvascular visualization. Its controllable and persistent contrast enables on-demand, multiparametric imaging for diagnostic and therapeutic use.

Shangchun Jiang and colleagues propose a micro/nano-scale mechanical energy storage device based on two-dimensional materials. By mimicking the morphology of a spiral spring, this device achieves fully reversible mechanical energy storage within a compact space without causing plastic deformation in the material

Giovanni Franzese and colleagues introduce a low-cost calibration method using a two-socket and spherical-joint tool. Validated on various robots, the method reduces errors by up to two orders of magnitude, enabling the successful execution of high-precision manipulation tasks.

Zhenxing Yu and colleagues report that thermal runaway in lithium-ion battery releases conductive ejecta, which induces three short-circuit arc modes in high-voltage systems (case-to-case arc being the most dangerous failure mode). They reveal a three-stage arc mechanism, establish a quadratic relationship between critical breakdown voltage and electrode spacing, and propose a risk map to guide safer design of highly integrated and ultra-fast charging battery systems.

Qi Wu and colleagues report a field trial integrating fixed and mobile networks over a single optical carrier using amplitude phase layered modulation. Their approach simultaneously delivers 128 Gb/s digital data and high fidelity analog wireless signals up to 16384-QAM over 109 km, supporting advanced modulation formats and achieving record performance, highlighting a scalable path toward converged 6G ready fiber infrastructures.

Traditional flexible sensors struggle with synchronized multimodal perception and robustness, limiting their performance in extreme environments. Baijin Mao and colleagues propose an ultra-robust bionic distributed multimodal flexible sensor inspired by tiger-shark skin.

Delphine De Tavernier and colleagues report that next-generation wind turbines may face transonic flow at the blade tip during normal operation. They propose and demonstrate the use of a Transonic Safe Mode, a strategy to ensure a safe design and operation.

The development of safe and effective maternal-fetal therapeutics is significantly hindered by chronic underfunding, inequitable access to specialized care, and persistent sociopolitical stigmas surrounding women’s health. Addressing these challenges will require interdisciplinary collaboration between clinicians, scientists, and engineers to design accessible therapeutics for maternal-fetal healthcare.

Dr. Julian von Schleinitz is a former professional luge athlete and is currently the Head of Tech Excellence and AI Solutions in Financial Services at BMW Group. He also helps develop technology used to elevate the performance of Olympic athletes as part of BMW’s partnership with the German Luge, Skeleton and Bobsleigh Federation. Here, we talk to Dr. von Schleinitz about his transition from elite athlete to data scientist, the unique engineering and regulatory challenges he’s faced, and the future of artificial intelligence in ice track sports.

The use of electric vehicles contributes to sustainability efforts by reducing our reliance on fossil fuels and improving air quality. Communications Engineering is delighted to present its first complete Research Collection on the topic of Battery Management Systems for Vehicle Electrification; you can read all the content here: https://www.nature.com/collections/hfdifjjbha.

The use of synthetic medical data (SMD) in AI development is on the rise, but its broader application is limited by the lack of a comprehensive evaluation framework. Here, Ghada Zamzmi and colleagues present a novel evaluation framework tailored for medical applications, along with an SMD scorecard that quantitatively assesses synthetic datasets across seven key criteria.

Large language models show remarkable potential in healthcare but face critical explainability challenges that must be addressed before widespread clinical deployment. Here, Munib Mesinovic, Peter Watkinson and Tingting Zhu examine technical and regulatory solutions needed to develop trustworthy, transparent large language models for responsible healthcare integration.

Professor Danielle Densley Tingley is an environmental engineer based at the University of Sheffield in the UK. Her research focusses on reducing the impact of the built environment on the planet using a number of strategies. Here, Dani shares her perspectives on the benefits of collaborative R&D in building a research career and in addressing grand challenges.