Enhancing Ozone Decomposition in Humid Environments through Carbon Doping to Disrupt the Hydrogen Bond Network in Mullite YMnO.

The strong adsorption of water molecules at the active site of the catalyst presents significant challenges in ozone decomposition, particularly at room temperature and in humid environments. To address this issue, we doped carbon atoms into the Mn-mullite YMnO catalyst to replace oxygen, resulting in efficient and stable ozone decomposition under highly humid conditions. Utilizing DFT calculations, our study demonstrated that carbon doping disrupts hydrogen bond networks on the catalyst surface, thereby reducing water adsorption.

Multifunctional Acetamide Additive Combined with LiNO Co-Assists Low-Concentration Electrolyte Interfacial Stability for Lithium Metal Batteries.

Lithium metal batteries (LMBs) are expected to upgrade their energy density to meet the growing battery market demand; however, intractable lithium dendrites and prominent electrode-electrolyte interface problems have been the stumbling block to their practical applications. Electrolytes play a crucial role in LMBs and are directly involved in the establishment of the electrode-electrolyte interface. In particular, low-concentration electrolytes (LCEs) can significantly save electrolyte costs, but the interface issue is more noteworthy.

Formaldehyde Decomposition from -20 °C to Room Temperature on a Mn-Mullite YMnO Catalyst.

Large ambient temperature changes (-20->25 °C) bring great challenges to the purification of the indoor pollutant formaldehyde. Within such a large ambient temperature range, we herein report a manganese-based strategy, that is, a mullite catalyst (YMnO) + ozone, to efficiently remove the formaldehyde pollution. At -20 °C, the formaldehyde removal efficiency reaches 62% under the condition of 60,000 mL g h.

A Thermal Performance Analysis and Comparison of Fiber Coils with the D-CYL Winding and QAD Winding Methods.

The thermal performance under variable temperature conditions of fiber coils with double-cylinder (D-CYL) and quadrupolar (QAD) winding methods is comparatively analyzed. Simulation by the finite element method (FEM) is done to calculate the temperature distribution and the thermal-induced phase shift errors in the fiber coils. Simulation results reveal that D-CYL fiber coil itself has fragile performance when it experiences an axially asymmetrical temperature gradient.

Preparation of lignosulfonate-acrylamide-chitosan ternary graft copolymer and its flocculation performance.

As flocculant plays an important role in wastewater treatment, searching for high efficient and cost-effective flocculants has always become the challenge in chemical industry. In the current work, lignosulfonate-acrylamide-chitosan ternary copolymer was designed and prepared as a new kind of flocculant. The elemental analysis and structure characterization of FTIR and XRD showed that acrylamide successfully grafted onto the two natural polymers and amorphous macromolecules were formed.

Impact of elevated aspartate and alanine aminotransferase on metabolic syndrome and its components among adult people living in Ningxia, China.

Objective: Metabolic syndrome (MS) is a combination of medical disorders that increase the risk for cardiovascular disease and diabetes mellitus. It suggests an association between an elevated serum aminotransferase level and MS. Little data show the relationship between the levels of serum aminotransferase and the incidence of MS in Ningxia, China.

Online technique for detecting state of onboard fiber optic gyroscope.

Although angle random walk (ARW) of fiber optic gyroscope (FOG) has been well modeled and identified before being integrated into the high-accuracy attitude control system of satellite, aging and unexpected failures can affect the performance of FOG after launch, resulting in the variation of ARW coefficient. Therefore, the ARW coefficient can be regarded as an indicator of "state of health" for FOG diagnosis in some sense. The Allan variance method can be used to estimate ARW coefficient of FOG, however, it requires a large amount of data to be stored.

Online estimation of Allan variance coefficients based on a neural-extended Kalman filter.

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors.