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.

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.

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.

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.

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.

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.

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.

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.

In Situ Resolving the Atomic Reconstruction of SnO2 (110) Surface.

Understanding surface reconstruction of nanocrystals is of great importance to their applications, however it is still challenging due to lack of atomic-level structural information under reconstruction conditions. Herein, through in situ spherical aberration corrected scanning transmission electron microscopy (STEM), the reconstruction of nanocrystalline SnO2 (110) surface was studied. By identifying the precise arrangements of surface/subsurface Sn and O columns through both in situ bright-field and high-angle annular dark-field STEM images, an unexpected added Sn2O model was determined for SnO2 (110)-(1 × 2) surface. The protruded Snδ+ of this surface could act as the active sites for activating O2 molecules according to our density functional theory (DFT) calculations. On the basis of in situ observation of atomic-level reconstruction behaviors and DFT calculations, an energy-driven reconstruction process was also revealed. We anticipate this work would help to clarify the long-standing debate regarding the reconstruction of SnO2 (110) surface and its intrinsic property.

Ultrathin structure of oxygen doped carbon nitride for efficient CO2photocatalytic reduction.

Photocatalytic conversion of carbon dioxide into fuels and valuable chemicals is a promising method for carbon neutralization and solving environmental problems. Through a simple thermal-oxidative exfoliation method, the O element was doped while exfoliated bulk g-C3N4into ultrathin structure g-C3N4. Benefitting from the ultrathin structure of g-C3N4, the larger surface area and shorter electrons migration distance effectively improve the CO2reduction efficiency. In addition, density functional thory computation proves that O element doping introduces new impurity energy levels, which making electrons easier to be excited. The prepared photocatalyst reduction of CO2to CO (116µmol g-1h-1) and CH4(47µmol g-1h-1).

Water-Assisted Homolytic Dissociation of Propyne on a Reduced Ceria Surface.

The emergence of ceria (CeO2 ) as an efficient catalyst for the selective hydrogenation of alkynes has attracted great attention. Intensive research effort has been devoted to understanding the underlying catalytic mechanism, in particular the H2 -CeO2 interaction. Herein, we show that the adsorption of propyne (C3 H4 ) on ceria, another key aspect in the hydrogenation of propyne to propene, strongly depends on the degree of reduction of the ceria surface and hydroxylation of the surface, as well as the presence of water. The dissociation of propyne and the formation of methylacetylide (CH3 CC-) have been identified through the combination of infrared reflection absorption spectroscopy (IRAS) and DFT calculations. We demonstrate that propyne undergoes heterolytic dissociation on the reduced ceria surface by forming a methylacetylide ion on the oxygen vacancy site and transferring a proton to the nearby oxygen site (OH group), while a water molecule that competes with the chemisorbed methylacetylide at the vacancy site assists the homolytic dissociation pathway by rebounding the methylacetylide to the nearby oxygen site.

Oxygen-Vacancy Dynamics and Entanglement with Polaron Hopping at the Reduced CeO_{2}(111) Surface.

The migration of oxygen vacancies (V_{O}) in ceria-based systems is crucial to their functionality in applications. Yet, although the V_{O}'s structure and the distribution of the Ce^{3+} polarons at the CeO_{2}(111) surface has received extensive attention, the dynamic behaviors of V_{O}'s and polarons are not fully understood. By combining density functional theory calculations and ab initio molecular dynamics simulations, we show that the movements of V_{O}'s and polarons exhibit very distinct entanglement characteristics within a temperature range of 300-900 K, and that the positions of the Ce^{3+} polarons play a key role in the V_{O} migration. Long-distance vacancy migration occurs at moderate temperatures when the "suitable" Ce^{3+} distribution remains long enough to promote oxygen migration. This study provides microscopic insight into the interplay between the electronic and ionic charge transport in ceria that will be beneficial for the rational design of conductive ceria-based materials.

Transmitter and receiver DSP for 112 Gbit/s PAM-4 amplifier-less transmissions using 25G-class EML and APD.

The transmission performance of 112 Gbit/s PAM-4 signal with commercial 25 G-class EML and APD is experimentally studied by using advanced digital signal processing (DSP) algorithms, i.e. pre-equalization (Pre-EQ), error-table based pre-correction (ETC), least-mean square (LMS) based equalization, direct detection faster than Nyquist (DD-FTN) algorithm. Among them, Pre-EQ and ETC are implemented at the transmitter, and ETC is a symbol-pattern-dependent pre-compensation algorithm based on the look-up-table approach. In order to obtain these pre-compensated parameters readily, a joint equalization and error table generation (JEEG) module is proposed. Employing the combination of ETC, LMS, and DD-FTN, a single line 112 Gbit/s PAM-4 40 km amplifier-less transmission with a record receiver sensitivity of -16.6 dBm (at 7% HD-FEC threshold) is experimentally demonstrated. In addition, the computational complexities of different DSP schemes are analyzed and discussed in detail. The receiver computational complexity can be effectively reduced by employing appropriate ETC and Pre-EQ in the transmitter.

Water Adsorption and Dissociation on Ceria-Supported Single-Atom Catalysts: A First-Principles DFT+U Investigation.

Single-atom catalysts have attracted wide attention owing to their extremely high atom efficiency and activities. In this paper, we applied density functional theory with the inclusion of the on-site Coulomb interaction (DFT+U) to investigate water adsorption and dissociation on clean CeO2 (111) surfaces and single transition metal atoms (STMAs) adsorbed on the CeO2 (111) surface. It is found that the most stable water configuration is molecular adsorption on the clean CeO2 (111) surface and dissociative adsorption on STMA/CeO2 (111) surfaces, respectively. In addition, our results indicate that the more the electrons that transfer from STMA to the ceria substrate, the stronger the binding energies between the STMA and ceria surfaces. A linear relationship is identified between the water dissociation barriers and the d band centers of STMA, known as the generalized Brønsted-Evans-Polanyi principle. By combining the oxygen spillovers, single-atom dispersion stabilities, and water dissociation barriers, Zn, Cr, and V are identified as potential candidates for the future design of ceria-supported single-atom catalysts for reactions in which the dissociation of water plays an important role, such as the water-gas shift reaction.

Identification and expression analysis of QM-like gene from Spodoptera litura after challenge by the entomopathogenic fungus Nomuraea rileyi.

A partial sequence of QM homologue was isolated from a Spodoptera litura fatbody suppression subtractive hybridization library. The full-length Spodoptera litura QM (SpLQM) cDNA of 838 bp contains a 5' untranslated region (UTR) of 112 bp, a 3' UTR of 66 bp, and an open reading frame of 660 nucleotides coding for a 219 amino acid peptide with a molecular weight of 25.5 kDa. Analysis of SpLQM sequence revealed the presence of characteristic motifs, including the ribosomal protein L10 signature and SH3-binding motif. Multiple alignment analysis revealed that SpLQM shares an overall identity of 57.1-99.1% with other members of QM family. Phylogenetic analysis confirmed that SpLQM is closely related to other insect QMs. Analysis of the tissue expression pattern showed that the SpLQM mRNA was expressed in all tissues tested, with highest levels measured in hemocytes, followed by fat bodies. Upon Nomuraea rileyi challenge, SpLQM showed significant upregulation in fat bodies and hemocytes, while slightly upregulation in midguts. The results suggest that SpLQM might play an important role in the innate immunity of S. litura in response to N. rileyi infection. SpLQM was also successfully overexpressed in Escherichia coli, and the recombinant fusion protein SpLQM-His has a molecular weight of 32 kDa.

Identification of suitable reference genes for gene expression studies by qRT-PCR in the blister beetle Mylabris cichorii.

The blister beetle Mylabris cichorii L. (Coleoptera: Meloidae) is a traditional medicinal insect recorded in the Chinese Pharmacopoeia. It synthesizes cantharidin, which kills cancer cells efficiently. Only males produce large amounts of cantharidin. Reference genes are required as endogenous controls for the analysis of differential gene expression in M. cichorii. Our study chose 10 genes as candidate reference genes. The stability of expression of these genes was analyzed by quantitative PCR and determined with two algorithms, geNorm and Normfinder. We recommend UBE3A and RPL22e as suitable reference genes in females and UBE3A, TAF5, and RPL22e in males.

Global Optimization of Cation Ordering in Perovskites by Recommendation-Based Basin-Hopping.

Cation ordering in multication perovskites is related to many important material properties and performances, but computational determination of the cation ordering remains a major challenge. Here, we propose a new computational approach by introducing a machine learning recommender system into the basin-hopping framework (RBH) for optimizing cation ordering. Taking the electrocatalyst Ba0.5Sr0.5Co0.8Fe0.2O3 (BSCF5582) as a showcase example, we found that the efficiency of RBH in identifying low-energy configurations outperforms the methods of cluster expansion and conventional basin-hopping. The RBH results revealed that the BSCF5582 catalyst tended to have a layered ordering of A-site cations and disordered B-site cations both in bulk and on the surfaces. Further, on the A-site-terminated surface, we found the segregation of large Ba atoms. Similarly, on the A-site- terminated surface of the recently developed Cs0.2Sr0.8Co0.4Fe0.6O3 (CSCF2846) catalyst, layered ordering at the A-site and surface enrichment of large Cs atoms were also found. The layered ordering was robust against thermal effects, as found from molecular dynamics simulations at 800 K. This work provides a new approach for thermodynamic global optimization of chemical ordering in multicomponent materials.

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.

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.

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.