Daytime radiative cooling multilayer films designed by a machine learning method and genetic algorithm.

Recently, there has been growing interest and attention towards daytime radiative cooling. This cooling technology is considered a potentially significant alternative to traditional cooling methods because of its neither energy consumption nor harmful gas emission during operation. In this paper, a daytime radiative cooling emitter (DRCE) consisting of polydimethylsiloxane, silicon dioxide, and aluminum nitride from top to bottom on a silver-silicon substrate was designed by a machine learning method (MLM) and genetic algorithm to achieve daytime radiative cooling. The optimal DRCE had 94.43% average total hemispherical emissivity in the atmospheric window wavelength band and 98.25% average total hemispherical reflectivity in the solar radiation wavelength band. When the ambient temperature was 30°C, and the power of solar radiation was about 900W/m 2, the net cooling power of the optimal DRCE could achieve 140.38W/m 2. The steady-state temperature of that could be approximately 9.08°C lower than the ambient temperature. This paper provides a general research strategy for MLM-driven design of DRCE.

Forestry Digital Twin With Machine Learning in Landsat 7 Data.

Forest succession analysis can predict forest change trends in the study area, which provides an important basis for other studies. Remote sensing is a recognized and effective tool in forestry succession analysis. Many forest modeling studies use statistic values, but only a few uses remote sensing images. In this study, we propose a machine learning-based digital twin approach for forestry. A data processing algorithm was designed to process Landsat 7 remote sensing data as model's input. An LSTM-based model was constructed to fit historical image data of the study area. The experimental results show that this study's digital twin method can effectively forecast the study area's future image.

Application of 2D Materials to Potassium-Ion Hybrid Capacitors.

Metal-ion hybrid supercapacitors (MICs) are a new type of electrochemical energy storage (EES) device, consisting of a battery-type electrode and a supercapacitor (SC)-type electrode. Exhibiting the advantages of both batteries and SCs (e. g., good energy density, excellent power density and long cycle life), these advanced energy storage devices have considerable commercial application prospects. Among MICs, potassium-ion hybrid supercapacitors (PICs) have several further advantages, including abundancy of resources, low standard electrode potential, and low cost. PICs are regarded as potential substitutes for lithium- or sodium-ion hybrid supercapacitors. However, the practical applications of PICs remain limited, owing to the imbalance of kinetics and capacity between the electrodes, the slow ion/electron diffusion rate, and the poor electrode structural stability. Recently, 2D materials with distinct structures and fascinating features have elicited widespread attention for application in PICs, thus achieving significant enhancements, ranging from charge storage capacity to reaction kinetics. This Review discusses research progress in 2D materials for PICs. Firstly, the energy storage principle and development requirements of MICs are introduced. The pivotal advantages and significant roles of 2D materials in the fabrication of PICs are then discussed in detail. Lastly, the challenges and prospects of the application of 2D materials to high-performance PICs are presented.

Heat-treatment-induced development of the crystalline structure and chemical stoichiometry of a CuxS counter electrode, and the influence on performance of quantum-dot-sensitized solar cells.

Recently, various phases of CuxS (1 ≤ x ≤ 2) were extensively explored as superb counter electrode (CE) materials for quantum dot-sensitized solar cells (QDSSCs). Herein, hexagonal covellite CuS (HC-CuS) with hierarchical nanostructure was grown on porous Ti substrates by chemical bath deposition, and then heat treated in the temperature range of 150-450 °C under N2 atmosphere. The reaction process and the evolution of morphology, composition and crystalline structure of CuxS with the variation of heat treatment temperature were studied by XRD, SEM, EDX, TEM and XPS. The photovoltaic properties of TiO2/CdS/CdSe QDSSCs based on CuxS CEs showed an obvious dependence on the element stoichiometry and crystalline structure of the CuxS. With HC-Cu1.28S heat-treated at 230 °C as CEs, QDSSCs achieved a power conversion efficiency of 3.88% under one sun illumination (100 mW cm-2, AM 1.5 G), which was higher than the counterparts with other compositions. Electrochemical impedance spectroscopy, Tafel polarization and cyclic voltammetry measurement showed that the electrocatalytic activity of HC-Cu1.28S CE was much higher than that of other CuxS CEs, which supported the results of the enhanced short-circuit current density, open circuit voltage and filling factor.