Unveiling the physical mechanisms driving delafossite crystal (ABX2) formation through interpretable machine learning.

A method integrating machine learning with first-principles calculations is employed to forecast the formation energy of delafossite crystals, facilitating the rapid identification of stable crystals. This approach identifies several stable candidates and highlights the importance of atomic ionization energy and electron affinity in the formation of delafossite crystals.

Unveiling the Structure of Oxygen Vacancies in Bulk Ceria and the Physical Mechanisms behind Their Formation.

Understanding the structures of oxygen vacancies in bulk ceria is crucial as they significantly impact the material's catalytic and electronic properties. The complex interaction between oxygen vacancies and Ce3+ ions presents challenges in characterizing ceria's defect chemistry. We introduced a machine learning-assisted cluster-expansion model to predict the energetics of defective configurations accurately within bulk ceria. This model effectively samples configurational spaces, detailing oxygen vacancy structures across different temperatures and concentrations. At lower temperatures, vacancies tend to cluster, mediated by Ce3+ ions and electrostatic repulsion, while at higher temperatures, they distribute uniformly due to configurational entropy. Our analysis also reveals a correlation between thermodynamic stability and the band gap between occupied O 2p and unoccupied Ce 4f orbitals, with wider band gaps indicating higher stability. This work enhances our understanding of defect chemistry in oxide materials and lays the groundwork for further research into how these structural properties affect ceria's performance.

Boosting Up Electrosynthesis of Urea with Nitrate and Carbon Dioxide via Synergistic Effect of Metallic Iron Cluster and Single-Atom.

Electrocatalytic conversion of nitrates and carbon dioxide to urea under ambient conditions shows promise as a potential substitute for traditional urea synthesis processes characterized by high consumption and pollution. In this study, a straightforward one-pot method is employed to prepare a highly efficient FeNC-Fe1N4 electrocatalyst, consisting of atomically dispersed Fe1N4 sites and metallic Fe clusters (FeNC) with particle size of 4-7 nm. The FeNC-Fe1N4 catalyst exhibits remarkable electrocatalytic activity for urea synthesis from nitrate anion (NO3 -) and carbon dioxide (CO2), achieving a urea production rate of 38.2 mmol gcat -1 h-1 at -0.9 V (vs RHE) and a Faradaic efficiency of 66.5% at -0.6 V (vs RHE). Both experimental and theoretical results conclusively demonstrate that metallic Fe clusters and Fe1N4 species provide active sites for the adsorption and activation of NO3 - and CO2, respectively, and the synergistic effect between Fe1N4 and metallic Fe clusters significantly enhances the electrochemical efficiency of urea synthesis. In all, this work contributes to the rational design and comprehensive synthesis of a dual-active site iron-based electrocatalyst, facilitating efficient and sustainable urea synthesis.

Unraveling the formation of oxygen vacancies on the surface of transition metal-doped ceria utilizing artificial intelligence.

Ceria has been extensively utilized in different fields, with surface oxygen vacancies playing a central role. However, versatile oxygen vacancy regulation is still in its infancy. In this work, we propose an effective strategy to manipulate the oxygen vacancy formation energy via transition metal doping by combining first-principles calculations and analytical learning. We elucidate the underlying mechanism driving the formation of oxygen vacancies using combined symbolic regression and data analytics techniques. The results show that the Fermi level of the system and the electronegativity of the dopants are the paramount parameters (features) influencing the formation of oxygen vacancies. These insights not only enhance our understanding of the oxygen vacancy formation mechanism in ceria-based materials to improve their functionality but also potentially lay the groundwork for future strategies in the rational design of other transition metal oxide-based catalysts.

Na-mediated carbon nitride realizing CO2 photoreduction with selectivity modulation.

The depressed directional separation of photogenerated carriers and weak CO2 adsorption/activation activity are the main factors hampering the development of artificial photosynthesis. Herein, Na ions are embedded in graphitic carbon nitride (g-C3N4) to achieve directional migration of the photogenerated electrons to Na sites, while the electron-rich Na sites enhance CO2 adsorption and activation. Na/g-C3N4 (NaCN) shows improved photocatalytic reduction activity of CO2 to CO and CH4, and under simulated sunlight irradiation, the CO yield of NaCN synthesized by embedding Na at 550°C (NaCN-550) is 371.2 µmol g-1 h-1, which is 58.9 times more than that of the monomer g-C3N4. By means of theoretical calculations and experiments including in situ fourier transform infrared spectroscopy, the mechanism is investigated. This strategy which improves carrier separation and reduces the energy barrier at the same time is important to the development of artificial photosynthesis.

S­scheme heterojunction of thin-layer O-modified graphitic carbon nitride/cobalt porphyrin to promote photocatalytic CO2 conversion.

The emissions of CO2 are increasing year by year, which have led to serious environmental problems. Converting CO2 into valuable fuels through photocatalysis is a promising strategy. In this research, oxygen atoms were successfully innovated into graphitic carbon nitride (CN). Additionally, cobalt porphyrin (CoTPP) was successfully loaded onto the modified carbon nitride (Co/CN). The generation of interfacial electric fields and bending bands between CN and CoTPP was demonstrated experimentally. The electrons in the CN and the holes in the CoTPP were combined to form a unique S-scheme heterojunction structure, and efficient separation of carriers was promoted. As a result, the CO conversion under visible light irradiation reached an impressive 100.70 µmol g-1 h-1. By integrating theoretical and experimental findings, this study underscores the critical role of catalyst design in enabling efficient photocatalytic CO2 reduction.

Advances in Defect Engineering of Metal Oxides for Photocatalytic CO2 Reduction.

Photocatalytic CO2 reduction technology, capable of converting low-density solar energy into high-density chemical energy, stands as a promising approach to alleviate the energy crisis and achieve carbon neutrality. Semiconductor metal oxides, characterized by their abundant reserves, good stability, and easily tunable structures, have found extensive applications in the field of photocatalysis. However, the wide bandgap inherent in metal oxides contributes to their poor efficiency in photocatalytic CO2 reduction. Defect engineering presents an effective strategy to address these challenges. This paper reviews the research progress in defect engineering to enhance the photocatalytic CO2 reduction performance of metal oxides, summarizing defect classifications, preparation methods, and characterization techniques. The focus is on defect engineering, represented by vacancies and doping, for improving the performance of metal oxide photocatalysts. This includes advancements in expanding the photoresponse range, enhancing photogenerated charge separation, and promoting CO2 molecule activation. Finally, the paper provides a summary of the current issues and challenges faced by defect engineering, along with a prospective outlook on the future development of photocatalytic CO2 reduction technology.

Relationship of solid fuels use with cognitive function and efficacy of switching to cleaner fuels or using ventilation: A systematic review and meta-analysis.

BACKGROUND: A growing number of studies have examined the relation between solid fuels use and cognitive function in the mid-elderly, but results are inconsistent. Therefore, a systematic review and meta-analysis was carried out to evaluate their relevance and the efficacy of switching to cleaner fuels or using ventilation. METHOD: We used PubMed, Web of Science, and Cochrane Library databases to identify 17 studies in which the primary outcome variable was cognitive function decline or cognitive disorders, and the exposure measure was solid fuels use. The final search date of August 31, 2023. The effect size of odds ratio (OR), regression coefficient (ß), and 95% confidence interval (CI) were pooled. Heterogeneity and the possibility of publication bias were assessed by using the Q-statistic and Begg's test, respectively. RESULT: Among the 17 included papers, the study participants were ≥45 years old. Eleven studies assessed the relationship between solid fuels use and cognitive function decline [number of studies (n) = 11, ß = -0.144; I2 = 97.7%]. Five studies assessed the relationship between solid fuels use and cognitive disorders (n = 5, OR = 1.229; I2 = 41.1%). Switching from using solid fuels to clean fuels could reduce the risk of cognitive function decline as compared to those who remained on using solid fuels (n = 2; ß = 0.710; I2 = 82.4%). Among participants using solid fuels, who cooked without on ventilated stoves were correlated with an enhanced risk of cognitive disorders as compared to participants who cooked with ventilated stoves (n = 2; OR = 1.358; I2 = 44.7%). CONCLUSION: Our meta-analysis showed a negative relationship between solid fuels use with cognitive function, and a positive relationship with cognitive disorders. Cleaner fuels, using ventilation, improved cookstoves can reduce the adverse health hazards of solid fuels use.

Direct in-situ insights into the asymmetric surface reconstruction of rutile TiO2 (110).

The reconstruction of rutile TiO2 (110) holds significant importance as it profoundly influences the surface chemistry and catalytic properties of this widely used material in various applications, from photocatalysis to solar energy conversion. Here, we directly observe the asymmetric surface reconstruction of rutile TiO2 (110)-(1×2) with atomic-resolution using in situ spherical aberration-corrected scanning transmission electron microscopy. Density functional theory calculations were employed to complement the experimental observations. Our findings highlight the pivotal role played by repulsive electrostatic interaction among the small polarons -formed by excess electrons following the removal of neutral oxygen atoms- and the subsequent surface relaxations induced by these polarons. The emergence and disappearance of these asymmetric structures can be controlled by adjusting the oxygen partial pressure. This research provides a deeper understanding, prediction, and manipulation of the surface reconstructions of rutile TiO2 (110), holding implications for a diverse range of applications and technological advancements involving rutile-based materials.

Gastroesophageal Reflux Disease and Rhinosinusitis: A Bidirectional Mendelian Randomization Study.

INTRODUCTION: Comorbidities, such as gastroesophageal reflux disease (GERD), are common in patients with rhinosinusitis (RS). However, the link between RS and GERD has not been fully understood. This study aimed to investigate the causal relationship between GERD and acute (ARS) or chronic RS (CRS), providing references for the pathogenesis and management of RS. METHODS: The data were obtained from the Integrative Epidemiology Unit Open GWAS project and FinnGen. A total of 972,838 individuals were included. The inverse variance-weighted (IVW) method was applied to obtain the primary results of the study. Weighted median, MR-Egger, and mode-based methods were used to determine the robustness of the results. Cochran's Q statistic and MR-Egger method were applied to detect heterogeneity and pleiotrophy in instrumental variables (IVs). Other sensitivity analyses included MR-PRESSO and leave-one-out analysis. RESULTS: The MR study showed that GERD was associated with an increased risk of CRS (OR: 1.36, 95% CI: 1.18-1.57, p < 0.001). The results of other analysis methods were broadly consistent with the IVW estimate. No heterogeneity was detected by Cochran's Q test (p = 0.061) and MR-PRESSO (p = 0.074). No horizontal pleiotropy was shown in IVs (p = 0.700). GERD was also associated with an increased risk of ARS (OR: 1.31, 95% CI: 1.17-1.48, p < 0.001). Some analytical results were inconsistent with the IVW estimate. No heterogeneity and pleiotropy were observed. There was no sufficient evidence for a reverse causal effect of RS on GERD. CONCLUSION: Our study supported that GERD promoted the risk of CRS and may be a potential risk factor for ARS. This provides additional support for further investigation into the mechanisms of GERD on RS.

Stacking Engineering of Heterojunctions in Half-Metallic Carbon Nitride for Efficient CO2 Photoreduction.

Enhancing charge separation in semiconductor photocatalysts is a major challenge for efficient artificial photosynthesis. Herein, a compact heterojunction is designed by embedding half-metallic C(CN)3 (hm-CN) hydrothermally in BiOBr (BOB) as the backbone. The interface between hm-CN and BOB is seamless and formed by covalent bonding to facilitate the transmission of photoinduced electrons from BOB to hm-CN. The transient photocurrents and electrochemical impedance spectra reveal that the modified composite catalyst exhibits a larger electron transfer rate. The photocatalytic activity of hm-CN/BOB increases significantly as indicated by a CO yield that is about four times higher than that of individual components. Density-functional theory calculations verify that the heterojunction improves electron transport and decreases the reaction energy barrier, thus promoting the overall photocatalytic CO2 conversion efficiency. The half-metal nitride coupled semiconductor heterojunctions might have large potential in artificial photosynthesis and related applications.

Piezo-photocatalysis for efficient charge separation to promote CO2 photoreduction in nanoclusters.

The substantial emissions of CO2 greenhouse gases have resulted in severe environmental problems, and research on the implementation of semiconductor materials to minimize CO2 is currently a highly discussed subject. Effective separation of interface charges is a major challenge for efficient piezo-photocatalytic systems. Meanwhile, the ultrasmall-sized metal nanoclusters can shorten the distance of electron transport. Herein, we synthesized Au25(p-MBA)18 nanoclusters (Au25 NCs) modified red graphitic carbon nitride (RCN) nanocatalysts with highly exposed Au active sites by in-situ seed growth method. The loading of Au25 NCs on the RCN surface provides more active sites and creates a long-range ordered electric field. It allows for the direct utilization of the piezoelectric field to separate photogenerated carriers during photo-piezoelectric excitation. Based on the above advantages, the rate of CO2 reduction to CO over Au25 NCs/RCN (111.95 µmol g-1 h-1) was more than triple compared to that of pristine RCN. This paper has positive implication for further application of metal clusters loaded semiconductor for piezo-photocatalytic CO2 reduction.

Revealing Temperature-Dependent Oxidation Dynamics of Ni Nanoparticles via Ambient Pressure Transmission Electron Microscopy.

Understanding the oxidation mechanism of metal nanoparticles under ambient pressure is extremely important to make the best use of them in a variety of applications. Through ambient pressure transmission electron microscopy, we in situ investigated the dynamic oxidation processes of Ni nanoparticles at different temperatures under atmospheric pressure, and a temperature-dependent oxidation behavior was revealed. At a relatively low temperature (e.g., 600 °C), the oxidation of Ni nanoparticles underwent a classic Kirkendall process, accompanied by the formation of oxide shells. In contrast, at a higher temperature (e.g., 800 °C), the oxidation began with a single crystal nucleus at the metal surface and then proceeded along the metal/oxide interface without voids formed during the whole process. Through our experiments and density functional theory calculations, a temperature-dependent oxidation mechanism based on Ni nanoparticles was proposed, which was derived from the discrepancy of gas adsorption and diffusion rates under different temperatures.

Statistical analysis of the performance of a variety of first-principles schemes for accurate prediction of binary semiconductor band gaps.

Standard density functional theory (DFT) approximations tend to strongly underestimate band gaps, while the more accurate GW and hybrid functionals are much more computationally demanding and unsuitable for high-throughput screening. In this work, we have performed an extensive benchmark of several approximations with different computational complexity [G0W0@PBEsol, HSE06, PBEsol, modified Becke-Johnson potential (mBJ), DFT-1/2, and ACBN0] to evaluate and compare their performance in predicting the bandgap of semiconductors. The benchmark is based on 114 binary semiconductors of different compositions and crystal structures, for about half of which experimental band gaps are known. Surprisingly, we find that, compared with G0W0@PBEsol, which exhibits a noticeable underestimation of the band gaps by about 14%, the much computationally cheaper pseudohybrid ACBN0 functional shows a competitive performance in reproducing the experimental data. The mBJ functional also performs well relative to the experiment, even slightly better than G0W0@PBEsol in terms of mean absolute (percentage) error. The HSE06 and DFT-1/2 schemes perform overall worse than ACBN0 and mBJ schemes but much better than PBEsol. Comparing the calculated band gaps on the whole dataset (including the samples with no experimental bandgap), we find that HSE06 and mBJ have excellent agreement with respect to the reference G0W0@PBEsol band gaps. The linear and monotonic correlations between the selected theoretical schemes and experiment are analyzed in terms of the Pearson and Kendall rank coefficients. Our findings strongly suggest the ACBN0 and mBJ methods as very efficient replacements for the costly G0W0 scheme in high-throughput screening of the semiconductor band gaps.

Highly Efficient and Exceptionally Durable Photooxidation Properties on Co3O4/g-C3N4 Surfaces.

Water pollution is a significant social issue that endangers human health. The technology for the photocatalytic degradation of organic pollutants in water can directly utilize solar energy and has a promising future. A novel Co3O4/g-C3N4 type-II heterojunction material was prepared by hydrothermal and calcination strategies and used for the economical photocatalytic degradation of rhodamine B (RhB) in water. Benefitting the development of type-II heterojunction structure, the separation and transfer of photogenerated electrons and holes in 5% Co3O4/g-C3N4 photocatalyst was accelerated, leading to a degradation rate 5.8 times higher than that of pure g-C3N4. The radical capturing experiments and ESR spectra indicated that the main active species are •O2- and h+. This work will provide possible routes for exploring catalysts with potential for photocatalytic applications.

CuCeOx/CuO Catalyst Derived from the Layered Double Hydroxide Precursor: Catalytic Performance in NO Reduction with CO in the Presence of Water and Oxygen.

Valencies of metal species and lattice defects, such as oxygen vacancies, play a pivotal role in metal oxide-catalyzed reactions. Herein, we report a promising synthetic strategy for preparing CuO-supported CuCeOx catalysts (CuCeOx/CuO) by calcination of a hydrotalcite precursor [Cu6Ce2(OH)16]CO3·nH2O. The structural and chemical properties of catalysts were characterized by XRD, ICP-AES, TEM, TPR, NH3-TPD, XPS, Raman spectroscopy, and N2 adsorption, which revealed that the thermal pretreatment in an oxidative atmosphere caused segregation and reconstitution processes of the precursor, resulting in a mesoporous catalyst consisting of well-dispersed CuO-supported CuCeOx clusters of 1.8-3.2 nm in size with a high population of oxygen vacancies. The as-prepared catalyst shows excellent catalytic performance in the reduction of NO by CO in the absence as well as in the presence of water and oxygen. This behavior is attributed to its high oxygen defect concentration facilitating the interplay of the redox equilibria between Cu2+ and reduced copper species (Cu+/Cu0) and (Ce4+/Ce3+). The high surface population of oxygen vacancies and in situ-generated metallic copper species have been evidenced by Raman spectroscopy and X-ray photoelectron spectroscopy. The layered double hydroxide-derived CuCeOx/CuO also showed good water tolerance and long-term stability. In situ infrared spectroscopy investigations indicated that adsorbed hyponitrite species are the main reaction intermediates of the NO conversion as also corroborated by theoretical simulations.

A review of pharmacokinetic and pharmacological properties of asiaticoside, a major active constituent of Centella asiatica (L.) Urb.

ETHNOPHARMACOLOGICAL RELEVANCE: Centella asiatica (L.) Urb., a potential medicinal plant, is widely used in orient traditional medicine. Its major active constituents include asiaticoside (AS), madecassoside (MS), asiatic acid and madecassic acid. Thereinto, AS is a pentacyclic triterpenoid saponin with a variety of pharmacological effects including antitumor, neuroprotective and wound healing effects. AIM OF THE STUDY: In this review, we summarize the pharmacokinetics, safety and pharmacological properties of AS. MATERIALS AND METHODS: We gathered information about AS from articles published up to 2022 and listed in Google scholar, PubMed, Web of Science, Elsevier, and similar databases. The keywords used in our search included "asiaticoside", "Centella asiatica", "pharmacokinetics", "nerve", "cancer", "skin", etc. RESULTS: AS appeared to degrade through a first-order reaction and had low biotoxicity. However, the pharmacokinetic properties of AS differed according to species. AS is highly blood-brain-barrier permeable without any harmful side effect. It has a variety of pharmacological effects including anti-neural inflammation and anti-cancer properties, as well as protective properties for the skin, cardiovascular system, and pulmonary system. CONCLUSION: This review comprehensively summarized current information regarding the pharmacokinetic and pharmacological properties of AS, and supported the pharmaceutical value of this compound. Future research should focus on improving bioavailability of AS and conducting clinical assessment.

Improving Symbolic Regression for Predicting Materials Properties with Iterative Variable Selection.

Symbolic regression offers a promising avenue for describing the structure-property relationships of materials with explicit mathematical expressions, yet it meets challenges when the key variables are unclear because of the high complexity of the problems. In this work, we propose to solve the difficulty by automatically searching for important variables from a large pool of input features. A new algorithm that integrates symbolic regression with iterative variable selection (VS) was designed for optimization of the model with a large amount of input features. Using the recent method SISSO for symbolic regression and random search for variable selection, we show that the VS-assisted SISSO (VS-SISSO) can effectively manage even hundreds of input features that the SISSO alone was computationally hindered, and it fastly converges to (near) optimal solutions when the model complexity is not high. The efficiency of this approach for improving the accuracy of symbolic regression in materials science was demonstrated in the two showcase applications of learning approximate equations for the band gap of inorganic halide perovskites and the stability of single-atom alloy catalysts.

Revealing Surface Restraint-Induced Hexagonal Pd Nanocrystals via In Situ Transmission Electron Microscopy.

Achieving metal nanocrystals with metastable phase draws much attention due to their anticipated fascinating properties, wheras it is still challenging because their polymorphism nature and phase transition mechanism remain elusive. Here, phase stability of face-centered cubic (fcc) Pd nanocrystals was studied via in situ spherical aberration (Cs)-corrected transmission electron microscopy (TEM). By constructing a well-defined Pd/C composite structure, Pd nanocrystals encapsulated by graphite, the dispersion process of fcc Pd was observed through a nucleation and growth process. Interestingly, Cs-corrected scanning TEM analysis demonstrated that the newly formed Pd nanocrystals could adopt a metastable hexagonal phase, which was considered challenging to obtain. Accordingly, formation mechanism of the hexagonal Pd nanocrystals was proposed, which involved the combined effect of two factors: (1) templating of graphite and (2) size effect. This work is expected to offer new insight into the polymorphism of Pd nanocrystals and pave the way for the future design of metastable metal nanomaterials.

Effect of the Configuration of Copper Oxide-Ceria Catalysts in NO Reduction with CO: Superior Performance of a Copper-Ceria Solid Solution.

Various copper-ceria-based composites have attracted attention as efficient catalysts for the reduction of NO with CO. In this comparative study, we have examined the catalytic potential of different configurations of copper oxide-ceria catalysts, including catalysts based on a copper-ceria solid solution, copper oxide particles supported on ceria, and ball-milled copper oxide-ceria. The structurally different interfaces between the constituents of these catalysts afforded very different catalytic performances. The solid solution catalyst outperformed the corresponding ceria-supported and ball-milled CuO-CeO2 catalysts. The copper cations incorporated into the ceria lattice strongly improved the activity, N2 selectivity, and water vapor tolerance compared to the other catalyst configurations. The experimental observations are supported by first-principles density functional theory (DFT) studies of the reaction pathway, which indicate that the incorporation of Cu cations into the ceria matrix lowers the energy required for activating the lattice oxygen, thereby enhancing the formation and healing of oxygen vacancies, and thus promoting NO reduction with CO.