The anode oxygen evolution reaction (OER) is known to largely limit the efficiency of electrolyzers owing to its sluggish kinetics. While crystalline metal oxides are promising as OER catalysts, ...their amorphous phases also show high activities. Efforts to produce amorphous metal oxides have progressed slowly, and how an amorphous structure benefits the catalytic performances remains elusive. Now the first scalable synthesis of amorphous NiFeMo oxide (up to 515 g in one batch) is presented with homogeneous elemental distribution via a facile supersaturated co‐precipitation method. In contrast to its crystalline counterpart, amorphous NiFeMo oxide undergoes a faster surface self‐reconstruction process during OER, forming a metal oxy(hydroxide) active layer with rich oxygen vacancies, leading to superior OER activity (280 mV overpotential at 10 mA cm−2 in 0.1 m KOH). This opens up the potential of fast, facile, and scale‐up production of amorphous metal oxides for high‐performance OER catalysts.
Amorphous NiFeMo oxide (up to 515 g one batch) with homogeneous elemental distribution was synthesized through a facile supersaturated co‐precipitation method. The amorphous NiFeMo oxide undergoes rapid surface self‐reconstruction during OER that forms a metal oxy(hydroxide) active layer with oxygen vacancies, enabling efficient OER catalysis.
Hydroxide exchange membrane fuel cells offer possibility of adopting platinum-group-metal-free catalysts to negotiate sluggish oxygen reduction reaction. Unfortunately, the ultrafast hydrogen ...oxidation reaction (HOR) on platinum decreases at least two orders of magnitude by switching the electrolytes from acid to base, causing high platinum-group-metal loadings. Here we show that a nickel-molybdenum nanoalloy with tetragonal MoNi
phase can catalyze the HOR efficiently in alkaline electrolytes. The catalyst exhibits a high apparent exchange current density of 3.41 milliamperes per square centimeter and operates very stable, which is 1.4 times higher than that of state-of-the-art Pt/C catalyst. With this catalyst, we further demonstrate the capability to tolerate carbon monoxide poisoning. Marked HOR activity was also observed on similarly designed WNi
catalyst. We attribute this remarkable HOR reactivity to an alloy effect that enables optimum adsorption of hydrogen on nickel and hydroxyl on molybdenum (tungsten), which synergistically promotes the Volmer reaction.
Understanding the spatial patterns of heavy metals is important for the protection and remediation of urban soil. Considering that the conventional Geostatistical methods, such as ordinary kriging ...(OK), are sensitive to dataset outliers, this study converted the identified outliers into a discrete probability density function (PDF). Then, the PDF was used as soft data in the Bayesian maximum entropy (BME) framework to perform a spatial prediction of soil Zn contents in Wuhan City, Central China. By using OK as the reference method, the BME framework was found to produce an overall further accurate prediction, and the PDF of BME predictions was further informative and close to the observed Zn concentrations. An improved BME performance can be expected if soft data with high quality are provided. The BME is a promising method in environmental science, where the so-called outliers that probably carry important information are common.
A better understanding of the spatial pattern of soil organic matter (SOM) is important for scientific soil management. As multisource secondary data become increasingly cheap and readily available, ...numerous methods have been established to incorporate secondary information; however, these methods exhibit limitations under certain conditions due to their relatively strict requirements on secondary data. In this study, we tried to integrate sampled soil data and secondary data more effectively within the framework of Bayesian maximum entropy (BME). Specifically, multiple linear regression (MLR) and geographically weighted regression (GWR) were run 100 times based on environmental covariates such as terrain indices, vegetation indices and categorical variables obtained from soil maps. Then, the 95% confidence interval was derived from the multiple prediction values at each of the soft data points. For comparison, some conventional techniques, including ordinary kriging (OK), regression kriging (RK) and geographically weighted regression kriging (GWRK), were also applied. The results showed that BME exhibited a prediction accuracy comparable to that of OK and maintained the prediction uncertainty at a low level, while other studied methods (MLR, GWR, RK and GWRK) were all significantly inferior to BME and OK. The proposed methodology in this study represents a promising scenario for the digital soil mapping, especially when the relationships between the target soil attributes and various secondary information are not strong or residuals of trend models show insignificant spatial autocorrelation.
•Prediction confidence intervals of regression models can be used as soft data.•Incorporation of localized soft data optimizes estimation accuracy and uncertainty.•Bayesian maximum entropy with localized soft data is feasible in soil modeling.
•The size effect of soil colloidal particles was investigated.•Surface charge properties differed for soil NP and CP.•The critical coagulation concentration (CCC)/mobility of soil NP was higher than ...CP.•Size effect of soil particle influences CCC through its effect on Hamaker constant.
The dispersion and coagulation of soil colloidal particles concern highly with their mobility and activity, as well as the role played in biogeochemical cycle of elements. Particle size is an important factor that affects both the van der Waals potential energy and electrostatic potential energy. However, the size effect of soil particles on surface charge properties and suspension stability has rarely been investigated. Results showed that the zeta potentials (in absolute values) of soil colloidal particles (CP, particle diameter less than 1000 nm) were higher than soil nanoparticles (NP, particle diameter less than 100 nm) for the same solution pH, while the specific surface area of soil NP was 1.6 times of soil CP; taken together, the surface charge density of soil NP was smaller than that of soil CP and the surface charge number of soil NP was slightly higher than soil CP. The stability of soil NP and CP was also different. The critical coagulation concentration (CCC) of soil NP was 1.4 times of soil CP, indicating higher mobility of smaller soil particle in natural conditions. Based on DLVO theory, the Hamaker constants of soil NP and CP were simulated to be 2.06 × 10−20 J and 1.86 × 10−20 J. It could be concluded that the size effect of soil particle influences suspension stability and particle mobility through its effect on Hamaker constant. The results could deepen our understanding for aggregation mechanisms of soil colloid-sized particles and further help in predicting their environmental behaviors.
Cerebral small vessel disease (CSVD) is a senile brain lesion caused by the abnormal structure and function of arterioles, venules and capillaries in the aging brain. The etiology of CSVD is complex, ...and disease is often asymptomatic in its early stages. However, as CSVD develops, brain disorders may occur, such as stroke, cognitive dysfunction, dyskinesia and mood disorders, and heart, kidney, eye and systemic disorders. As the population continues to age, the burden of CSVD is increasing. Moreover, there is an urgent need for better screening methods and diagnostic markers for CSVD, in addition to preventive and asymptomatic- and mild-stage treatments. Integrative medicine (IM), which combines the holistic concepts and syndrome differentiations of Chinese medicine with modern medical perspectives, has unique advantages for the prevention and treatment of CSVD. In this review, we summarize the biological markers, ultrasound and imaging features, disease-related genes and risk factors relevant to CSVD diagnosis and screening. Furthermore, we discuss IM-based CSVD prevention and treatment strategies to stimulate further research in this field.
The anode oxygen evolution reaction (OER) is known to largely limit the efficiency of electrolyzers owing to its sluggish kinetics. While crystalline metal oxides are promising as OER catalysts, ...their amorphous phases also show high activities. Efforts to produce amorphous metal oxides have progressed slowly, and how an amorphous structure benefits the catalytic performances remains elusive. Now the first scalable synthesis of amorphous NiFeMo oxide (up to 515 g in one batch) is presented with homogeneous elemental distribution via a facile supersaturated co‐precipitation method. In contrast to its crystalline counterpart, amorphous NiFeMo oxide undergoes a faster surface self‐reconstruction process during OER, forming a metal oxy(hydroxide) active layer with rich oxygen vacancies, leading to superior OER activity (280 mV overpotential at 10 mA cm−2 in 0.1 m KOH). This opens up the potential of fast, facile, and scale‐up production of amorphous metal oxides for high‐performance OER catalysts.
Entwicklungshilfe: Amorphes NiFeMo‐Oxid (bis 515 g pro Charge) mit homogener Elementverteilung wurde durch einfache Coabscheidung aus übersättigter Lösung erhalten. Während einer Sauerstoffentwicklungsreaktion (OER) erfährt es eine rasche Oberflächen‐Selbstrekonstruktion, wobei eine aktive Metalloxy(hydroxid)‐Schicht mit Sauerstoff‐Fehlstellen entsteht, was eine effiziente OER‐Katalyse ermöglicht.
Using auxiliary information to improve the prediction accuracy of soil properties in a physically meaningful and technically efficient manner has been widely recognized in pedometrics. In this paper, ...we explored a novel technique to effectively integrate sampling data and auxiliary environmental information, including continuous and categorical variables, within the framework of the Bayesian maximum entropy (BME) theory. Soil samples and observed auxiliary variables were combined to generate probability distributions of the predicted soil variable at unsampled points. These probability distributions served as soft data of the BME theory at the unsampled locations, and, together with the hard data (sample points) were used in spatial BME prediction. To gain practical insight, the proposed approach was implemented in a real-world case study involving a dataset of soil total nitrogen (TN) contents in the Shayang County of the Hubei Province (China). Five terrain indices, soil types, and soil texture were used as auxiliary variables to generate soft data. Spatial distribution of soil total nitrogen was predicted by BME, regression kriging (RK) with auxiliary variables, and ordinary kriging (OK). The results of the prediction techniques were compared in terms of the Pearson correlation coefficient (r), mean error (ME), and root mean squared error (RMSE). These results showed that the BME predictions were less biased and more accurate than those of the kriging techniques. In sum, the present work extended the BME approach to implement certain kinds of auxiliary information in a rigorous and efficient manner. Our findings showed that the BME prediction technique involving the transformation of variables into soft data can improve prediction accuracy considerably, compared to other techniques currently in use, like RK and OK.
A novel fiber optic biosensor has been developed to monitor the growth of hexapod cells on-line. By measuring the light intensity, the dynamic growth of hexapod cells can be observed continuously. ...Such a fiber-optic sensor has many advantages, including rapid response, high sensitivity, immunity to electromagnetic interference, small detector size, and facilitated operation. Potential applications exist in drug developing and screening.
Fluorescence-based white-light-emitting diodes （WLEDs） were fabricated using blue GaN chips and green- and red-emitting CdSe/CdS/ZnS quantum dots （QDs）. The coordinate and color temperature of the ...WLEDs could be varied because of the size-tunable emission of CdSe QDs from 510 to 620 nm. Warm and cold white emissions were confirmed with the color temperature ranging from 4000 to 9000 K. Color coordinates were analyzed at different bias. The fast enhancement of blue emission resulted in the shift of color coordinates to the cold side. The stability of white emission during operation was analyzed; stable spectra were achieved within 90 min.
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