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.

Resistive memory devices often require an energy-intensive forming step that limits efficiency and reliability. Erbing Hua and colleagues report forming-free Pd/HfO₂ devices enabled by a Pd-O-Hf interfacial mechanism, supporting multi-bit operation and reduced energy use in spiking neural networks.

Christian E. N. Petersen and colleagues propose a method to extract charge carrier density-dependent mobility from two-terminal measurements. The approach enables mobility analysis without the need for multi-terminal devices, simplifying nanowire characterization.

Studying brain function requires synchronized recording of the brain and behavior in real time. Jarl Haggerty and colleagues describe Thalamus, an open-source platform that synchronizes multimodal data and enables low-latency closed-loop experiments.

Xuan Li and colleagues report a miniature flextensional ultrasonic surgical device driven by a pre-stressed piezoelectric stack with vibration-amplifying metal caps. In vitro robot bone cutting showed less than 1 N force and less than 6% cut width deviation from blade thickness.

Manipulating waves across different materials is limited by signal loss and a narrow bandwidth. Xiaojing Li and colleagues propose a metasurface design that achieves efficient, wideband control of electromagnetic waves at such interfaces.

Henry A. Martin and colleagues design co-packaged electronics with microfluidics to bridge the thermal gap between the device junction and the coolant. This is beneficial for mid-to-high power electronics, chiplet architectures, and multi-chip packages.

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.

Academic and professional editors share their thoughts on the features of high-quality engineering research papers.