Researchers from the Institute of Coal Chemistry, Chinese Academy of Sciences, have identified the nickel dimer (Ni₂) play vital role inCO₂ methanation. Encapsulated in MFI zeolite with MnOₓ promotion at only ~0.86% Ni loading, the catalyst achieves ~76% CO₂ conversion, ~98% CH₄ selectivity and CH₄ space time yield of ~450 mol·mol Ni^-1·h^-1 at 400°C.

With the widespread application of radar in space target detection and identification, acquiring radar images of non-cooperative targets at different attitudes has become the data foundation for supporting deep learning-based automatic target recognition algorithms. However, the uncontrollable motion trajectories of non-cooperative targets and limited illumination time render the acquisition of measured images extremely difficult; although anechoic chamber measurements and electromagnetic computations can obtain multi-attitude images, they are respectively constrained by high costs and computational time, making it difficult to meet the demand for large-scale data. Existing image generation methods based on Generative Adversarial Networks (GANs) can augment data scales, but most can only control the azimuth angle without precisely constraining the elevation angle, resulting in generated images whose projection morphology does not match reality. Therefore, how to achieve radar image generation with precise dual-dimensional control over both azimuth and elevation angles has become a key technical challenge in data augmentation for radar recognition of non-cooperative targets.

An early career Western Australian astrophysicist has helped uncover a universal rule behind one of the most powerful behaviours in the Universe: when black holes launch jets.

The discovery, accepted for publication in the prestigious Nature Astronomy, shows black holes appear to fire off powerful jets at the same critical point in their feeding cycle – whether they are about 10 times the mass of the Sun or millions of times heavier.