Noble-Metal-Free High-Entropy Alloy Nanoparticles for Efficient Solar-Driven Photocatalytic CO2 Reduction.

Metal nanoparticle (NP) cocatalysts are widely investigated for their ability to enhance the performance of photocatalytic materials; however, their practical application is often limited by the inherent instability under light irradiation. This challenge has catalyzed interest in exploring high-entropy alloys (HEAs), which, with their increased entropy and lower Gibbs free energy, provide superior stability. In this study, 3.5 nm-sized noble-metal-free NPs composed of a FeCoNiCuMn HEA are successfully synthesized. With theoretic calculation and experiments, the electronic structure of HEA in augmenting the catalytic CO2 reduction has been uncovered, including the individual roles of each element and the collective synergistic effects. Then, their photocatalytic CO2 reduction capabilities are investigated when immobilized on TiO2. HEA NPs significantly enhance the CO2 photoreduction, achieving a 23-fold increase over pristine TiO2, with CO and CH4 production rates of 235.2 and 19.9 µmol g-1 h-1, respectively. Meanwhile, HEA NPs show excellent stability under simulated solar irradiation, as well high-energy X-ray irradiation. This research emphasizes the promising role of HEA NPs, composed of earth-abundant elements, in revolutionizing the field of photocatalysis.

Confining MoSe2 Nanosheets into N-Doped Hollow Porous Carbon Microspheres for Fast-Charged and Long-Life Potassium-Ion Storage.

The potassium-ion battery (PIB) is the most promising alternative to a lithium-ion battery (LIB). Exploitation of a suitable electrode material is crucial to promote the development of PIBs. The MoSe2 material has attracted much attention due to its high theoretical capacity, unique layered structure, and good conductivity. However, the potassium storage property of MoSe2 has been suffering from structural fragmentation and sluggish reaction kinetic caused by large potassium ions upon insertion/extraction, which needs to be further improved. Herein, the MoSe2 nanosheets are confined into N-doped hollow porous carbon microspheres (MoSe2@N-HCS) by spray drying and high-temperature selenization. It delivers a superior rate performance of 113.7 mAh g-1 at 10 A g-1 and remains at a high capacity of 158.3 mAh g-1 at 2 A g-1 even after 16 700 cycles for PIBs. The excellent electrochemical performance can be attributed to unique structure, N-doping, and robust chemical bonds. The storage mechanism of MoSe2 for potassium ions was explored. The outstanding properties of MoSe2@N-HCS make it a promising anode material for PIBs.

The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis-Trans Isomerase Gene Signature in Hepatocellular Carcinoma.

Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis-trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma. Methods: The transcriptome and clinical data of hepatocellular carcinoma patients were downloaded from The Cancer Genome Atlas and the International Cancer Genome Consortium database as the training set and validation set, respectively. Peptidyl prolyl cis-trans isomerase gene sets were obtained from the Molecular Signatures Database. The differential expression of peptidyl prolyl cis-trans isomerase genes was analyzed by R software. A prognostic model based on the peptidyl prolyl cis-trans isomerase signature was established by Cox, Lasso, and stepwise regression methods. Kaplan-Meier survival analysis was used to evaluate the prognostic value of the model and validate it with an independent external data. Finally, nomogram and calibration curves were developed in combination with clinical staging and risk score. Results: Differential gene expression analysis of hepatocellular carcinoma and adjacent tissues showed that there were 16 upregulated genes. A prognostic model of hepatocellular carcinoma was constructed based on three gene signatures by Cox, Lasso, and stepwise regression analysis. The Kaplan-Meier curve showed that hepatocellular carcinoma patients in high-risk score group had a worse prognosis (p < 0.05). The receiver operating characteristic curve revealed that the area under curve values of predicting the survival rate at 1, 2, 3, 4, and 5 years were 0.725, 0.680, 0.644, 0.630, and 0.639, respectively. In addition, the evaluation results of the model by the validation set were basically consistent with those of the training set. A nomogram incorporating clinical stage and risk score was established, and the calibration curve matched well with the diagonal. Conclusion: A prognostic model based on 3 peptidyl prolyl cis-trans isomerase gene signatures is expected to provide reference for prognostic risk stratification in patients with hepatocellular carcinoma.

Application of an Autophagy-Related Gene Prognostic Risk Model Based on TCGA Database in Cervical Cancer.

Background: Autophagy plays an important role in the development of cancer. However, the prognostic value of autophagy-related genes (ARGs) in cervical cancer (CC) is unclear. The purpose of this study is to construct a survival model for predicting the prognosis of CC patients based on ARG signature. Methods: ARGs were obtained from the Human Autophagy Database and Molecular Signatures Database. The expression profiles of ARGs and clinical data were downloaded from the TCGA database. Differential expression analysis of CC tissues and normal tissues was performed using R software to screen out ARGs with an aberrant expression. Univariate Cox, Lasso, and multivariate Cox regression analyses were used to construct a prognostic model which was validated by using the test set and the entire set. We also performed an independent prognostic analysis of risk score and some clinicopathological factors of CC. Finally, a clinical practical nomogram was established to predict individual survival probability. Results: Compared with normal tissues, there were 63 ARGs with an aberrant expression in CC tissues. A risk model based on 3 ARGs was finally obtained by Lasso and Cox regression analysis. Patients with high risk had significantly shorter overall survival (OS) than low-risk patients in both train set and validation set. The ROC curve validated its good performance in survival prediction, suggesting that this model has a certain extent sensitivity and specificity. Multivariate Cox analysis showed that the risk score was an independent prognostic factor. Finally, we mapped a nomogram to predict 1-, 3-, and 5-year survival for CC patients. The calibration curves indicated that the model was reliable. Conclusion: A risk prediction model based on CHMP4C, FOXO1, and RRAGB was successfully constructed, which could effectively predict the prognosis of CC patients. This model can provide a reference for CC patients to make precise treatment strategy.

Synthesis of a Highly Stable Pd@CeO2 Catalyst for Methane Combustion with the Synergistic Effect of Urea and Citric Acid.

Making use of synergy between urea and citric acid, a core-shell Pd@CeO2 catalyst with spherical morphology was facilely synthesized by a hydrothermal method. The formation mechanism of the core-shell structure in the presence of citric acid and hydrogen peroxide was studied. Results showed that the Pd@CeO2 catalyst exhibited high catalytic activity in methane oxidation. Pd nanoparticles were well stabilized by CeO2 shell encapsulation, resulting in high stability of the catalyst. A high CH4 conversion of 99% was retained after 50 h on-stream reaction at 500 °C. Additionally, many tiny pores on the CeO2 shell surface were beneficial for the full contact between reactants and active components. Pd nanoparticles were highly dispersed inside the shell, improving the utilization efficiency of active components. The results also demonstrated that the Pd species in the catalyst existed in the form of oxidation state, mainly in PdO (ca. 66.6%), which played an essential part in methane combustion.

Effects of A-site non-stoichiometry in YxInO3+δ on the catalytic performance during methane combustion.

A novel non-stoichiometric YxInO3+δ (YIO-x, 0.8 ≤ x ≤ 1.04) perovskite catalyst with a large number of oxygen vacancies and high specific surface area was synthesized using glycine self-propagating gel combustion. It was found that low levels of non-stoichiometry in the A site of YxInO3+δ effectively increased the amount of oxygen desorption by 39-42% when compared to the original (YIO-1) due to Y-deficiency and oxygen vacancies. Further investigations showed that the non-stoichiometry also brings a significant change to the Lewis acid sites on the surface of the sample, which confirmed to be a great promoter for the catalytic combustion of methane. In addition, the catalytic performance increased with the increasing intensity of acid sites. After 50 h of the stability test, the catalysts maintained high activity, indicating their good catalytic stability.

A Novel Highly Sensitive NO2 Sensor Based on Perovskite Na0.5+xBi0.5TiO3-δ Electrolyte.

NOx is one of dangerous air pollutants, and the demands for reliable sensors to detect NOx are extremely urgent recently. Conventional fluorite-phase YSZ used for NOx sensor requires higher operating temperature to obtain desirable oxygen ion conductivity. In this work, perovskite-phase Na0.5Bi0.5TiO3 (NBT) oxygen conductor was chosen as the solid electrolyte to fabricate a novel highly sensitive NO2 sensor with CuO as the sensing electrode and Pt as reference electrode. Na dopped Na0.5Bi0.5TiO3 greatly improved the sensing performance of this sensor. The optimal sensor based on Na0.51Bi0.50TiO3-δ exhibited good response-recovery characteristics to NO2 and the response current values were almost linear to NO2 concentrations in the range of 50-500 ppm at 400-600 °C. The response current value towards NO2 reached maximum 11.23 µA at 575 °C and the value on NO2 is much higher than other gases (CH4, C2H4, C3H6, C3H8, CO), indicating good selectivity for detecting NO2. The response signals of the sensor were slightly affected by coexistent O2 varying from 2 to 21 vol% at 575 °C. The response current value decreased only 4.9% over 2 months, exhibiting the potential application in motor vehicles.

Alkaline-Earth Metals-Doped Pyrochlore Gd2Zr2O7 as Oxygen Conductors for Improved NO2 Sensing Performance.

This work proposed a novel strategy to fabricate highly-stable NO2 sensor based on a pyrochlore-phase Gd2Zr2O7 oxygen conductor. The incorporation of alkaline-earth metals distinctly enhances the sensing performance of the Gd2Zr2O7 based sensors. The excellent sensor based on Gd1.95Ca0.05Zr2O7+δ exhibits rapid response-recovery characteristics with the maximum response current value (ΔI = 6.4 µA), extremely short 90% responce (3 s) and 90% recovery (35 s) time towards 500 ppm NO2 at 500 °C, which is better than that of commercial YSZ under the same condition. The ΔI value towards NO2 is much higher than those towards other gases (CH4, C3H6, C3H8, CO, NO, SO2, C2H4, CO2 and C2H6), exhibiting excellent selectivity for detecting NO2. The response signal basically maintains a stable value of 6.4 µA after the sensors was stored for half a month and a month. The outstanding selectivity and highly stability of the NO 2 sensors based on Gd2-xMxZr2O7+δ are expected to a promising application in automotive vehicles.

A GdAlO3 Perovskite Oxide Electrolyte-Based NOx Solid-State Sensor.

NOx is a notorious emission from motor vehicles and chemical factories as the precursor of acid rain and photochemical smog. Although zirconia-based NOx sensors have been developed and showed high sensitivity and selectivity at a high temperature of above 800 °C, they fail to show good performance, and even don't work at the typical work temperature window of the automotive engine (<500 °C). It still is a formidable challenge for development of mild-temperature NOx detector or sensor. Herein, a novel amperometric solid-state NOx sensor was developed using perovskite-type oxide Gd1-xCaxAlO3-δ(GCA) as the electrolyte and NiO as the sensing electrode. NOx sensing properties of the device were investigated at the temperature region of 400-500 °C. The response current value at -300 mV was almost linearly proportional to the NOx concentration between 300 and 500 ppm at 500 °C. At such a temperature, the optimal sensor gave the highest NO2 sensitivity of 20.15 nA/ppm, and the maximum response current value reached 5.57 µA. Furthermore, a 90% response and 90% recover time to 500 ppm NO2 were about 119 and 92 s, respectively. The excellent selectivity and stability towards NOx sensing showed the potential application of the sensor in motor vehicles.