The development of clean and low-cost solar photovoltaic technology is crucial for the global transition toward carbon neutrality and sustainable energy. Monolithic all-perovskite tandem solar cells, constructed by stacking wide- and narrow-bandgap perovskite sub-cells with an intermediate interconnecting layer, offer a theoretical efficiency of up to 45%, positioning them as a promising next-generation photovoltaic technology. However, the short-circuit current density (J_sc) of state-of-the-art all-perovskite tandem devices remains limited to below 16.7 mA cm^-2, primarily due to insufficient light utilization, which hinders further progress. Recently, Assistant Professor Renxing Lin and Professor Hairen Tan from the College of Engineering and Applied Sciences, Nanjing University published a comprehensive review titled “Light Management in Monolithic All-Perovskite Tandem Solar Cells” in Light: Science & Applications. This review describes the particularity of light management in all-perovskite tandem solar cells, and summarizes their advances, challenges, and prospects.

Researchers developed a machine-learning workflow that predicts how chemical reactions will form specific “handed” versions of molecules—critical for safe and effective drugs. Trained on small datasets from prior studies, the model screens thousands of reaction components and accurately forecasts outcomes at far lower cost than traditional simulations. By reducing dozens of lab experiments to just a handful, the tool could significantly accelerate and lower the cost of drug discovery and reaction optimization.

Statistical modeling revealed that mentions of needles and awls increase significantly in colder environments, confirming the role of sewing technology in thermoregulation and survival of ancient people.