Giving drones a sense of “pain”: a new way to predict instability before it happens
Peer-Reviewed Publication
Updates every hour. Last Updated: 30-Oct-2026 04:16 ET (30-Oct-2026 08:16 GMT/UTC)
By combining simulations, flight data analysis and extensive experimental testing, researchers from Delft University of Technology and Wageningen University and Research (The Netherlands) were able to identify which combinations of damage, flight conditions and manoeuvres are most likely to result in loss of control. In addition, these indicators can be used not only to detect instability, but also to adapt system behaviour in real-time. For example, they could help determine strategies that maintain flight despite damage to an aircraft’s wing—much in the same way humans accommodate ankle injuries by limping in order to keep walking.
Anuja Tripathi’s childhood exposure to coal fly ash in Kanpur, India, later inspired her research at Georgia Tech on turning the waste into a source of rare earth elements. Working with Ching-Hua Huang and Xing Xie, she developed a cleaner extraction method using a recyclable ionic liquid and electrical current, avoiding the harsh acids, high heat, and excess waste common in other approaches. The process can selectively recover valuable elements like neodymium, which is used in electric vehicles, wind turbines, and defense technologies. While the method has only been tested in small batches so far, it could eventually help recover critical materials from coal ash, batteries, electronics, and other waste streams.
Azo compounds are widely used in many applications, and photoelectrochemical synthesis provides a promising green route for producing them under mild conditions. Researchers at the University of Science and Technology of China reported that Cs+-induced surface reconstruction of BiVO4 photoanodes can stabilize the electrode interface, accelerate charge transfer, and promote efficient photoelectrochemical synthesis of azobenzene under illumination.
Chemist Focuses on Developments Paving the Way to the Quantum Internet – European Research Council is Founding “Hilbert Molecules” Project with roughly EUR 2.5 million
Since Wilhelm Röntgen discovered X-rays in 1895, X-ray imaging has become an indispensable tool in modern medical diagnosis, industrial non-destructive testing, security screening, and even cultural heritage preservation. In X-ray imaging systems, detection methods fall into two main categories: direct and indirect. Direct detection uses semiconductor materials to convert X-ray photons directly into electrical signals, offering fast response and high spatial resolution, but it is often expensive and complex to manufacture. Indirect detection employs a “scintillator + photodetector” structure: X-rays are first absorbed by a scintillator material and converted into visible or ultraviolet light, which is then captured by a photodiode or CCD/CMOS sensor and transformed into electrical signals. Indirect detection dominates the current X-ray imaging market because of its mature technology, controllable cost, and excellent compatibility with existing sensors.
Two-dimensional (2D) perovskites have emerged as promising optoelectronic materials. However, their practical and rational design is hindered by poor understanding of the relationship between the screening environment and excitonic properties. In a new study, researchers developed a new method to isolate the effects of the screening environment, offering a new predictive model for excitonic properties of 2D perovskites. This will contribute to more stable and tunable optoelectronic technologies.