Multiple remotely sensed datasets and machine learning models to predict chlorophyll-a concentration in the Nakdong River, South Korea.

The Nakdong River is a crucial water resource in South Korea, supplying water for various purposes such as potable water, irrigation, and recreation. However, the river is vulnerable to algal blooms due to the inflow of pollutants from multiple points and non-point sources. Monitoring chlorophyll-a (Chl-a) concentrations, a proxy for algal biomass is essential for assessing the trophic status of the river and managing its ecological health. This study aimed to improve the accuracy and reliability of Chl-a estimation in the Nakdong River using machine learning models (MLMs) and simultaneous use of multiple remotely sensed datasets. This study compared the performances of four MLMs: multi-layer perceptron (MLP), support vector machine (SVM), random forest (RF), and eXetreme Gradient Boosting (XGB) using three different input datasets: (1) two remotely sensed datasets (Sentinel-2 and Landsat-8), (2) standalone Sentinel-2, and (3) standalone Landsat-8. The results showed that the MLP model with multiple remotely sensed datasets outperformed other MLMs with 0.43 - 0.86 greater in R2 and 0.36 - 5.88 lower in RMSE. The MLP model demonstrated the highest performance across the range of Chl-a concentrations and predicted peaks above 20 mg/m3 relatively well compared to other models. This was likely due to the capacity of MLP to handle imbalanced datasets. The predictive map of the spatial distribution of Chl-a generated by MLP well captured the areas with high and low Chl-a concentrations. This study pointed out the impacts of imbalanced Chl-a concentration observations (dominated by low Chl-a concentrations) on the performance of MLMs. The data imbalance likely led to MLMs poorly trained for high Chl-a values, producing low prediction accuracy. In conclusion, this study demonstrated the value of multiple remotely sensed datasets in enhancing the accuracy and reliability of Chl-a estimation, mainly when using the MLP model. These findings would provide valuable insights into utilizing MLMs effectively for Chl-a monitoring.

Hierarchically Porous Ferroelectric Layer with the Aligned Dipole Moment for a High-Performance Aqueous Zn Metal Battery.

Rechargeable aqueous Zn metal batteries (AZMBs) are desirable because of the advantages of metallic Zn and aqueous media. However, AZMBs suffer from limited cyclability and low Coulombic efficiency, originating from uncontrolled dendrite growth and side reactions such as hydrogen gas evolution and corrosion. A hierarchically porous poly(vinylidene difluoride) (PVDF) protection layer with ferroelectric ß-phases is formed on the Zn metal using a simple electrospinning method. This suppresses Zn metal failure modes such as side reactions and dendrite growth and supports rapid electrolyte accessibility. The synergetic effect of hierarchically porous structures and ferroelectricity not only facilitates a supporting matrix to form uniform nucleation sites for Zn deposition but also inhibits corrosion, allowing dendrite-free Zn deposition. This multifunctional PVDF film significantly improves the cyclability of Zn symmetric cells, allowing for up to 850 h of repeated plating/stripping cycles. Moreover, it exhibits an excellent cycle life of 1000 cycles under harsh conditions and high current densities of 4.0-10.0 mA cm-2, which are 62-fold higher than those that the bare Zn electrode tolerates.

Permeable characteristics of surface film deposited on LiMn2O4 positive electrode revealed by redox-active indicator.

Herein, the ferrocene redox indicator-based surface film characteristics of spinel lithium manganese oxide (LMO) were evaluated. The pre-cycling of spinel LMO generated a film on the LMO surface. The surface film deposited on LMO surface suppresses further electrolyte decomposition, while the penetration of approximately 0.7 nm-sized redox indicator is not prevented. The facile self-discharge of LMO and regeneration current from the ferrocenium molecule was observed from the redox indicator in a specifically designed four-electrode cell. From this electrochemical behavior, a small-sized HF molecule attack on the LMO surface through a carbonate-based electrolyte-derived film is defined; hence, the prevention of small-sized molecules into the deposited surface film is crucial for the enhancement of LiMn2O4-based lithium-ion batteries.