A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter

Statistical methods, particularly machine learning models, have gained significant popularity in air quality predictions. These prediction models are commonly trained using the historical measurement datasets independently collected at the environmental monitoring stations and their operational forecasts in advance using inputs of the real-time...

Manipulate energy transport via fluorinated spacers towards record-efficiency 2D Dion-Jacobson CsPbI₃ solar cells

Two-dimensional (2D) Dion-Jacobson (D-J)-type cesium lead iodide CsPbI ₃ perform remarkably in terms of stability. However, the complex interactions between spacer and inorganic layers limit its excellent progress in perovskite solar cells (PSCs). Herein, starting from the considerable structural diversity of organic spacers, we...

Guanidium-assisted crystallization engineering for highly efficient CsPbI₃ solar cells

Iodine vacancies and uncoordinated iodide ions of CsPbI₃ films are mainly responsible for nonradiative recombination. Here, we report a composition-engineering passivation method that through guanidium (GA⁺) and I⁻ forms strong hydrogen bonds to passivate iodine vacancies and reduce defects. Both experimental...