An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations.

Solubility of redox-active molecules is an important determining factor of the energy density in redox flow batteries. However, the advancement of electrolyte materials discovery has been constrained by the absence of extensive experimental solubility datasets, which are crucial for leveraging data-driven methodologies. In this study, we design and investigate a highly automated workflow that synergizes a high-throughput experimentation platform with a state-of-the-art active learning algorithm to significantly enhance the solubility of redox-active molecules in organic solvents. Our platform identifies multiple solvents that achieve a remarkable solubility threshold exceeding 6.20 M for the archetype redox-active molecule, 2,1,3-benzothiadiazole, from a comprehensive library of more than 2000 potential solvents. Significantly, our integrated strategy necessitates solubility assessments for fewer than 10% of these candidates, underscoring the efficiency of our approach. Our results also show that binary solvent mixtures, particularly those incorporating 1,4-dioxane, are instrumental in boosting the solubility of 2,1,3-benzothiadiazole. Beyond designing an efficient workflow for developing high-performance redox flow batteries, our machine learning-guided high-throughput robotic platform presents a robust and general approach for expedited discovery of functional materials.

The relationship between mountain wetland health and water quality: A case study of the upper Hanjiang River Basin, China.

This study investigates the degradation process of mountain wetlands in the upper Hanjiang River Basin (HRB) over a 30-year span from 1990 to 2020. In particular, the landscape development intensity (LDI) index was employed to conduct a comprehensive assessment of the wetland health. This was subsequently combined with the spatio-temporal changes of water quality in the basin to explore the potential correlations between the health status of mountain wetlands and the associated watershed water quality. The results show that over the past three decades, wetland ecosystems have shrunk by 18% due to conversion into farmland, grass, construction land and forest land. This was significant between 2010 and 2020, as shown by a land use dynamic index of -1.121% during 2010-2020, which was significantly higher than that in the preceding two decades (0.003%, 0.367%) (p < 0.05). LDI values for individual sub-watersheds across different years ranged from 2.39 to 4.93, demonstrating an increasing trend since 2010. This indicates a heightened level of human interference in mountain wetlands. Although the water quality within the basin generally adhered to the Class II surface water quality standard, total nitrogen (TN) (primarily from farming) was a concern. Areas with relatively more human activity were observed to exhibit increased pollution levels, as demonstrated by a positive correlation between LDI and the concentrations of total phosphorus (TP), ammonium nitrogen (NH4+-N), and chemical oxygen demand (COD) in the basin. The LDI of the mountain wetland exhibited a consistent positive correlation with the water quality comprehensive function, both during the flood (r = 0.77-0.81) and non-flood (r = 0.61-0.70) seasons (p < 0.05). This indicates the significant impact of the wetland landscape structure on the water quality within a 1000 m radius on either side of the river. Special attention should be paid to the management and allocation of wetland landscapes within this 1000 m buffer zone. Furthermore, efforts to control upstream pollutant emission should be strengthened.

Out-of-Plane Ionic Conductivity Measurement Configuration for High-Throughput Experiments.

An approach for measuring conductivity of thin-film electrolytes in an out-of-plane configuration, amenable to high-throughput experimentation, is presented. A comprehensive analysis of the geometric requirements for success is performed. Using samaria-doped ceria (Ce0.8Sm0.2O1.9, SDC) excellent agreement between bulk samples and thin films with continuous and patterned electrodes, 100-500 µm in diameter, is demonstrated. Films were deposited on conductive Nb-doped SrTiO3, and conductivity was measured by AC impedance spectroscopy over the temperature range from ∼200 to ∼500 °C. The patterned electrode geometry, which encompassed an array of microdot metal electrodes for making top contact, enabled measurements at hundreds of positions on the film, implying the potential for measuring hundreds of composition in a single library.