Climate variability and human activities interact to increase the abundance of woody plants in arid and semi-arid ecosystems worldwide. How woody plants interact with rainfall to influence patterns of soil moisture through time, at different depths in the soil profile and between neighboring landscape patches is poorly known. In a semi-arid mesquite savanna, we deployed a paired array of sensors beneath a mesquite canopy and in an adjacent open area to measure volumetric soil water content (Â) every 30 min at several depths between 2004 and 2007. In addition, to quantify temporally dynamic variation in soil moisture between the two microsites and across soil depths we analysed  time-series using fast Fourier transforms (FFT). FFT analyses were consistent with the prediction that by reducing evaporative losses through shade and reducing rainfall inputs through canopy interception of small rainfall events, the mesquite canopy was associated with a decline in high-frequency (hour-to-hour and day-to-day) variation in shallow Â. Finally, we found that, in both microsites, high-frequency  variation declined with increasing soil depth as the influence of evaporative losses and inputs associated with smaller rainfall events declined. In this case, we argue that the buffering of shallow soil moisture against high-frequency variations can enhance nutrient cycling and alter the carbon cycle in dryland ecosystems.

In this investigation, supervised machine learning (ML) was utilized to accurately predict the optimum bromine doping concentration in single-junction MASnI 3−x Br x devices. Data-driven optimizations were carried out on 42 000 unique devices built utilizing a solar cell capacitance simulator (SCAPS). The devices were investigated through variations of bromine doping %, bandgap, electron affinity, series resistance, back-contact metal, and acceptor concentrationparameters that were specifically chosen because of their tunable nature and ability to be modified through facile experimental fabrication techniques of the device. Five different algorithms were utilized to explore feature engineering. The first step before bromine doping within the device included validation studies of a pure tin-based system, MASnI 3 : a power conversion efficiency (PCE) of 6.71% was achieved, having close congruence with experimental data. ML analyses for optimal bromine doping resulted in the discovery of two devices with bromine concentrations of 22.43% (Br22) and 25.63% (Br25), with the latter being a more fine-tuned value obtained through extra rigorous analysis. To understand the total and relative impact of each feature on power conversion efficiency (PCE), Br22 and Br25 were analyzed with a state-of-the-art algorithm, namely, the SHapley Additive exPlanations (SHAP) algorithm. Focusing on the two discovered devices, further device optimizations were carried out utilizing SCAPS. Modulations of absorber thickness, bulk and interfacial defect density, and choice of electron transport layer (ETL) and hole transport layer (HTL) materials were tried. Device stability was analyzed through carrier lifetime studies. Following these optimization steps, Br22 and Br25 demonstrated final high PCE values of 20.72 and 17.37%, respectively. The ML-assisted quantitative analysis of the current work provides significant confidence for optimal bromine-doped tin-based devices to be considered as viable and competitive nontoxic alternatives to traditional technologies.

SCAPS simulation was utilized to complement previously published perovskite-on-Si tandem solar devices and explore herein viable all-perovskite 4-T mechanically stacked and 2-T monolithic non-Pb tandem structures. CsSn0.5Ge0.5I3 (1.5 eV) was used as top cell wide bandgap absorber, while CsSnI3 (1.3 eV) was chosen as bottom cell low bandgap absorber. The top cell was simulated with AM 1.5G 1 Sun spectrum, and the bottom cell was simulated with the filtered spectrum from the top cell. To form a 2-T monolithic tandem device, ITO was used as the recombination layer; the current matching condition was investigated by varying the thickness of the absorber layers. For a current-matched device with a Jsc of 21.2 mA/cm2, optimized thicknesses of 450 nm and 815 nm were obtained for the top and bottom absorber layers, respectively. At these thicknesses, the PCEs of the top and bottom cells were 14.08% and 9.25%, respectively, and 18.32% for the final tandem configuration. A much simpler fabricated and simulated 4-T mechanically stacked tandem device, on the other hand, showcased top and bottom cell PCEs of 15.83% and 9.15%, at absorber layer thicknesses of 1300 nm and 900 nm, respectively, and a final overall tandem device PCE of 19.86%.