A silicon photoanode protected with TiO2/stainless steel bilayer stack for solar seawater splitting

Photoelectrochemical seawater splitting is a promising route for direct utilization of solar energy and abundant seawater resources for H2 production. However, the complex salinity composition in seawater results in intractable challenges for photoelectrodes. This paper describes the fabrication of a bilayer stack consisting of stainless steel and TiO2 as a cocatalyst and protective layer for Si photoanode. The chromium-incorporated NiFe (oxy)hydroxide converted from stainless steel film serves as a protective cocatalyst for efficient oxygen evolution and retarding the adsorption of corrosive ions from seawater, while the TiO2 is capable of avoiding the plasma damage of the surface layer of Si photoanode during the sputtering of stainless steel catalysts. By implementing this approach, the TiO2 layer effectively shields the vulnerable semiconductor photoelectrode from the harsh plasma sputtering conditions in stainless steel coating, preventing surface damages. Finally, the Si photoanode with the bilayer stack inhibits the adsorption of chloride and realizes 167 h stability in chloride-containing alkaline electrolytes. Furthermore, this photoanode also demonstrates stable performance under alkaline natural seawater for over 50 h with an applied bias photon-to-current efficiency of 2.62%.

Electronic structure modification of SnO2 to accelerate CO2 reduction towards formate

A systematic theoretical study probing the catalytic potential of metal-doped SnO2(110) was conducted. The incorporation of metals such as Zr, Ti, W, V, Hf, and Ge is shown to drive electron transfer to Sn. The increased charge of Sn is injected into anti-bonding orbitals, finely tuning the catalytic activity and reducing the overpotential to -0.34 V. AIMD simulations show the stability of the modified structures. This work sheds light on the rational design of low-cost metal oxides with a high catalytic performance for CO2ER to formate.

Metastable gallium hydride mediates propane dehydrogenation on H2 co-feeding

In heterogeneous catalysis, the catalytic dehydrogenation reactions of hydrocarbons often exhibit a negative pressure dependence on hydrogen due to the competitive chemisorption of hydrocarbons and hydrogen. However, some catalysts show a positive pressure dependence for propane dehydrogenation, an important reaction for propylene production. Here we show that the positive activity dependence on H2 partial pressure of gallium oxide-based catalysts arises from metastable hydride mediation. Through in situ spectroscopic, kinetic and computational analyses, we demonstrate that under reaction conditions with H2 co-feeding, the dissociative adsorption of H2 on a partially reduced gallium oxide surface produces H atoms chemically bonded to coordinatively unsaturated Ga atoms. These metastable gallium hydride species promote C-H bond activation while inhibiting deep dehydrogenation. We found that the surface coverage of gallium hydride determines the catalytic performance. Accordingly, benefiting from proper H2 co-feeding, the alumina-supported, trace additive-modified gallium oxide catalyst GaOx-Ir-K/Al2O3 exhibited high activity and selectivity at high propane concentrations.

Structured Catalysts and Catalytic Processes: Transport and Reaction Perspectives

The structure of catalysts determines the performance of catalytic processes. Intrinsically, the electronic and geometric structures influence the interaction between active species and the surface of the catalyst, which subsequently regulates the adsorption, reaction, and desorption behaviors. In recent decades, the development of catalysts with complex structures, including bulk, interfacial, encapsulated, and atomically dispersed structures, can potentially affect the electronic and geometric structures of catalysts and lead to further control of the transport and reaction of molecules. This review describes comprehensive understandings on the influence of electronic and geometric properties and complex catalyst structures on the performance of relevant heterogeneous catalytic processes, especially for the transport and reaction over structured catalysts for the conversions of light alkanes and small molecules. The recent research progress of the electronic and geometric properties over the active sites, specifically for theoretical descriptors developed in the recent decades, is discussed at the atomic level. The designs and properties of catalysts with specific structures are summarized. The transport phenomena and reactions over structured catalysts for the conversions of light alkanes and small molecules are analyzed. At the end of this review, we present our perspectives on the challenges for the further development of structured catalysts and heterogeneous catalytic processes.

Alkaline-earth ion stabilized sub-nano-platinum tin clusters for propane dehydrogenation

The strong promotion effects of alkali/alkaline earth metals are frequently reported for heterogeneous catalytic processes such as propane dehydrogenation (PDH), but their functioning principles remain elusive. This paper describes the effect of the addition of calcium (Ca) on reducing the deactivation rate of platinum-tin (Pt-Sn) catalyzed PDH from 0.04 h-1 to 0.0098 h-1 at 873 K under a WHSV of 16.5 h-1 of propane. The Pt-Sn-Ca catalyst shows a high propylene selectivity of >96% with a propylene production rate of 41 molC3H6 (gPt h)-1 and ∼1% activity loss after regeneration. The combination of characterization and DFT simulations reveals that Ca acts as a structural promoter favoring the transition of Snn+ in the parent catalyst to Sn0 during reduction, and the latter is an electron donor that increases the electron density of Pt. This greatly suppresses coke formation from deep dehydrogenation. Moreover, it was found that Ca promotes the formation of a highly reactive and sintering-resistant sub-nano Pt-Sn alloy with a diameter of approximately 0.8 nm. These lead to high activity and selectivity for the Pt-Sn-Ca catalyst for PDH.

Tandem propane dehydrogenation and surface oxidation catalysts for selective propylene synthesis

Direct propane dehydrogenation (PDH) to propylene is a desirable commercial reaction but is highly endothermic and severely limited by thermodynamic equilibrium. Routes that oxidatively remove hydrogen as water have safety and cost challenges. We coupled chemical looping-selective hydrogen (H2) combustion and PDH with multifunctional ferric vanadate-vanadium oxide (FeVO4-VOx) redox catalysts. Well-dispersed VOx supported on aluminum oxide (Al2O3) provides dehydrogenation sites, and adjacent nanoscale FeVO4 acts as an oxygen carrier for subsequent H2 combustion. We achieved an integral performance of 81.3% propylene selectivity at 42.7% propane conversion at 550°C for 200 chemical looping cycles for the reoxidization of FeVO4. Based on catalytic experiments, spectroscopic characterization, and theory calculations, we propose a hydrogen spillover-mediated coupling mechanism. The hydrogen species generated at the VOx sites migrated to adjacent FeVO4 for combustion, which shifted PDH toward propylene. This mechanism is favored by the proximity between the dehydrogenation and combustion sites.

Accessing complex reconstructed material structures with hybrid global optimization accelerated via on-the-fly machine learning

The complex reconstructed structure of materials can be revealed by global optimization. This paper describes a hybrid evolutionary algorithm (HEA) that combines differential evolution and genetic algorithms with a multi-tribe framework. An on-the-fly machine learning calculator is adopted to expedite the identification of low-lying structures. With a superior performance to other well-established methods, we further demonstrate its efficacy by optimizing the complex oxidized surface of Pt/Pd/Cu with different facets under (4 × 4) periodicity. The obtained structures are consistent with experimental results and are energetically lower than the previously presented model.

Highly selective NH3 synthesis from N2 on electron-rich Bi0 in a pressurized electrolyzer

Electrochemical conversion of N2 into ammonia presents a sustainable pathway to produce hydrogen storage carrier but yet requires further advancement in electrocatalyst design and electrolyzer integration. This technology suffers from low selectivity and yield owing to the extremely strong N≡N bond and the exceptionally low solubility of N2 in aqueous systems. A high NH3 synthesis performance is restricted by the high activation energy of N≡N bond and the supply insufficiency of N2 to active sites. This paper describes the introduction of electron-rich Bi0 sites into Ag catalysts with a high-pressure electrolyzer that enables a dramatically enhanced Faradaic efficiency of 44.0% and yield of 28.43 μg cm-2 h-1 at 4.0 MPa. Combined with density functional theory results, in situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy demonstrates that N2 reduction reaction follows an associative mechanism, in which a high coverage of N-N bond and -NH2 intermediates suggest electron-rich Bi0 boosts sound activation of N2 molecules and low hydrogenation barrier. The proposed strategy of engineering electrochemical catalysts and devices provides powerful guidelines for achieving industrial-level green ammonia production.

[Expert consensus on the biobank development of oral genetic diseases and rare diseases and storage codes of related biological samples from craniofacial and oral region]

The biological samples of oral genetic diseases and rare diseases are extremely precious. Collecting and preserving these biological samples are helpful to elucidate the mechanisms and improve the level of diagnose and treatment of oral genetic diseases and rare diseases. The standardized construction of biobanks for oral genetic diseases and rare diseases is important for achieving these goals. At present, there is very little information on the construction of these biobanks, and the standards or suggestions for the classification and coding of biological samples from oral and maxillofacial sources, and this is not conducive to the standardization and information construction of biobanks for special oral diseases. This consensus summarizes the background, necessity, principles, and key points of constructing the biobank for oral genetic diseases and rare diseases. On the base of the group standard "Classification and Coding for Human Biomaterial" (GB/T 39768-2021) issued by the National Technical Committee for Standardization of Biological Samples, we suggest 76 new coding numbers for different of biological samples from oral and maxillofacial sources. We hope the consensus may promote the standardization, and smartization on the biobank construction as well as the overall research level of oral genetic diseases and rare diseases in China.

Guiding catalytic CO2 reduction to ethanol with copper grain boundaries

The grain boundaries (GBs) in copper (Cu) electrocatalysts have been suggested as active sites for CO₂ electroreduction to ethanol. Nevertheless, the mechanisms are still elusive. Herein, we describe how GBs tune the activity and selectivity for ethanol on two representative Cu-GB models, namely Cu∑3/(111) GB and Cu∑5/(100) GB, using joint first-principles calculations and experiments. The unique geometric structures on the GBs facilitate the adsorption of bidentate intermediates, *COOH and *CHO, which are crucial for CO₂ activation and CO protonation. The decreased CO-CHO coupling barriers on the GBs can be rationalized via kinetics analysis. Furthermore, when introducing GBs into Cu (100), the product is selectively switched from ethylene to ethanol, due to the stabilization effect for *CH₃CHO and inapposite geometric structure for *O adsorption, which are validated by experimental trends. An overall 12.5 A current and a single-pass conversion of 5.18% for ethanol can be achieved over the synthesized Cu-GB catalyst by scaling up the electrode into a 25 cm² membrane electrode assembly system.

Tunable CO2 electroreduction to ethanol and ethylene with controllable interfacial wettability

The mechanism of how interfacial wettability impacts the CO₂ electroreduction pathways to ethylene and ethanol remains unclear. This paper describes the design and realization of controllable equilibrium of kinetic-controlled *CO and *H via modifying alkanethiols with different alkyl chain lengths to reveal its contribution to ethylene and ethanol pathways. Characterization and simulation reveal that the mass transport of CO₂ and H₂O is related with interfacial wettability, which may result in the variation of kinetic-controlled *CO and *H ratio, which affects ethylene and ethanol pathways. Through modulating the hydrophilic interface to superhydrophobic interface, the reaction limitation shifts from insufficient supply of kinetic-controlled *CO to that of *H. The ethanol to ethylene ratio can be continuously tailored in a wide range from 0.9 to 1.92, with remarkable Faradaic efficiencies toward ethanol and multi-carbon (C₂₊) products up to 53.7% and 86.1%, respectively. A C₂₊ Faradaic efficiency of 80.3% can be achieved with a high C₂₊ partial current density of 321 mA cm^-2, which is among the highest selectivity at such current densities.

Tracking C-H bond activation for propane dehydrogenation over transition metal catalysts: work function shines

The activation of the C-H bond in heterogeneous catalysis plays a privileged role in converting light alkanes into commodity chemicals with a higher value. In contrast to traditional trial-and-error approaches, developing predictive descriptors via theoretical calculations can accelerate the process of catalyst design. Using density functional theory (DFT) calculations, this work describes tracking C-H bond activation of propane over transition metal catalysts, which is highly dependent on the electronic environment of catalytic sites. Furthermore, we reveal that the occupancy of the antibonding state for metal-adsorbate interaction is the key factor in determining the ability to activate the C-H bond. Among 10 frequently used electronic features, the work function (W) exhibits a strong negative correlation with C-H activation energies. We demonstrate that e^-W can effectively quantify the ability of C-H bond activation, surpassing the predictive capacity of the d-band center. The C-H activation temperatures of the synthesized catalysts also confirm the effectiveness of this descriptor. Apart from propane, e^-W applies to other reactants like methane.

Designing single-site alloy catalysts using a degree-of-isolation descriptor

Geometrically isolated metal atoms in alloy catalysts can target efficient and selective catalysis. However, the geometric and electronic disturbance between the active atom and its neighbouring atoms, that is, diverse microenvironments, makes the active site ambiguous. Herein, we demonstrate a methodology to describe the microenvironment and determine the effectiveness of active sites in single-site alloys. A simple descriptor, degree-of-isolation, is proposed, considering both electronic regulation and geometric modulation within a PtM ensemble (M = transition metal). The catalytic performance of PtM single-site alloy is examined thoroughly using this descriptor for an industrially important reaction, propane dehydrogenation. The volcano-shaped isolation-selectivity plot reveals a Sabatier-type principle for designing selective single-site alloys. Specifically, for a single-site alloy with a high degree-of-isolation, alternation of the active centre has a great impact on tuning selectivity, validated by the outstanding consistency between experimental propylene selectivity and the computational descriptor.

Concerted oxygen diffusion across heterogeneous oxide interfaces for intensified propane dehydrogenation

Propane dehydrogenation (PDH) is an industrial technology for direct propylene production which has received extensive attention in recent years. Nevertheless, existing non-oxidative dehydrogenation technologies still suffer from the thermodynamic equilibrium limitations and severe coking. Here, we develop the intensified propane dehydrogenation to propylene by the chemical looping engineering on nanoscale core-shell redox catalysts. The core-shell redox catalyst combines dehydrogenation catalyst and solid oxygen carrier at one particle, preferably compose of two to three atomic layer-type vanadia coating ceria nanodomains. The highest 93.5% propylene selectivity is obtained, sustaining 43.6% propylene yield under 300 long-term dehydrogenation-oxidation cycles, which outperforms an analog of industrially relevant K-CrO_x/Al₂O₃ catalysts and exhibits 45% energy savings in the scale-up of chemical looping scheme. Combining in situ spectroscopies, kinetics, and theoretical calculation, an intrinsically dynamic lattice oxygen "donator-acceptor" process is proposed that O^2- generated from the ceria oxygen carrier is boosted to diffuse and transfer to vanadia dehydrogenation sites via a concerted hopping pathway at the interface, stabilizing surface vanadia with moderate oxygen coverage at pseudo steady state for selective dehydrogenation without significant overoxidation or cracking.

Coupling acid catalysis and selective oxidation over MoO3-Fe2O3 for chemical looping oxidative dehydrogenation of propane

Redox catalysts play a vital role in chemical looping oxidative dehydrogenation processes, which have recently been considered to be a promising prospect for propylene production. This work describes the coupling of surface acid catalysis and selective oxidation from lattice oxygen over MoO₃-Fe₂O₃ redox catalysts for promoted propylene production. Atomically dispersed Mo species over γ-Fe₂O₃ introduce effective acid sites for the promotion of propane conversion. In addition, Mo could also regulate the lattice oxygen activity, which makes the oxygen species from the reduction of γ-Fe₂O₃ to Fe₃O₄ contribute to selectively oxidative dehydrogenation instead of over-oxidation in pristine γ-Fe₂O₃. The enhanced surface acidity, coupled with proper lattice oxygen activity, leads to a higher surface reaction rate and moderate oxygen diffusion rate. Consequently, this coupling strategy achieves a robust performance with 49% of propane conversion and 90% of propylene selectivity for at least 300 redox cycles and ultimately demonstrates a potential design strategy for more advanced redox catalysts.

Modulation of *CHxO Adsorption to Facilitate Electrocatalytic Reduction of CO2 to CH4 over Cu-Based Catalysts

Copper (Cu) can efficiently catalyze the electrochemical CO₂ reduction reaction (CO₂RR) to produce value-added fuels and chemicals, among which methane (CH₄) has drawn attention due to its high mass energy density. However, the linear scaling relationship between the adsorption energies of *CO and *CH_xO on Cu restricts the selectivity toward CH₄. Alloying a secondary metal in Cu provides a new freedom to break the linear scaling relationship, thus regulating the product distribution. This paper describes a controllable electrodeposition approach to alloying Cu with oxophilic metal (M) to steer the reaction pathway toward CH₄. The optimized La₅Cu₉₅ electrocatalyst exhibits a CH₄ Faradaic efficiency of 64.5%, with the partial current density of 193.5 mA cm^-2. The introduction of oxophilic La could lower the energy barrier for *CO hydrogenation to *CH_xO by strengthening the M-O bond, which would also promote the breakage of the C-O bond in *CH₃O for the formation of CH₄. This work provides a new avenue for the design of Cu-based electrocatalysts to achieve high selectivity in CO₂RR through the modulation of the adsorption behaviors of key intermediates.

High-Throughput Screening of Electrocatalysts for Nitrogen Reduction Reactions Accelerated by Interpretable Intrinsic Descriptor

Numerous activity descriptors have been developed to rationally design single-atom catalysts (SACs), such as energy-based or electronic descriptors. However, their computationally costly and experimentally unobtainable properties limit the understanding of the structure-activity relationship to a case-by-case basis. This paper describes a simple and interpretable descriptor directly related to activity, which can be not only easily obtained from the atomic databases, but also experimentally verified by X-ray absorption spectroscopy. The defined descriptor proves to accelerate high-throughput screening of more than 700 graphene-based SAC models without computations, universal for 3-5d transition metals and C/N/P/B/O-based coordination environments. Meanwhile, the analytical formula of this descriptor reveals the intrinsic relations of various crucial features in the complicated metal-ligand interaction, thus the structure-activity relationship is clarified at the molecular orbital level. Using electrochemical nitrogen reduction as an example, this descriptor's guidance role has been experimentally validated by 13 previous reports as well as our synthesized 4 SACs. Several other new advanced catalysts are also identified. Orderly combining machine learning with physical insights, this work provides a new generalized strategy for crossing the chasm between low-cost high-throughput screening and a comprehensive understanding of the structure-mechanism-activity relationship.

Nature of Catalytic Behavior of Cobalt Oxides for CO2 Hydrogenation

Cobalt oxide (CoO _x ) catalysts are widely applied in CO₂ hydrogenation but suffer from structural evolution during the reaction. This paper describes the complicated structure-performance relationship under reaction conditions. An iterative approach was employed to simulate the reduction process with the help of neural network potential-accelerated molecular dynamics. Based on the reduced models of catalysts, a combined theoretical and experimental study has discovered that CoO(111) provides active sites to break C-O bonds for CH₄ production. The analysis of the reaction mechanism indicated that the C-O bond scission of *CH₂O species plays a key role in producing CH₄. The nature of dissociating C-O bonds is attributed to the stabilization of *O atoms after C-O bond cleavage and the weakening of C-O bond strength by surface-transferred electrons. This work may offer a paradigm to explore the origin of performance over metal oxides in heterogeneous catalysis.

Neural Network Accelerated Investigation of the Dynamic Structure-Performance Relations of Electrochemical CO2 Reduction over SnO x Surfaces

Heterogeneous catalysts, especially metal oxides, play a curial role in improving energy conversion efficiency and production of valuable chemicals. However, the surface structure at the atomic level and the nature of active sites are still ambiguous due to the dynamism of surface structure and difficulty in structure characterization under electrochemical conditions. This paper describes a strategy of the multiscale simulation to investigate the SnO _x reduction process and to build a structure-performance relation of SnO _x for CO₂ electroreduction. Employing high-dimensional neural network potential accelerated molecular dynamics and stochastic surface walking global optimization, coupled with density functional theory calculations, we propose that SnO₂ reduction is accompanied by surface reconstruction and charge density redistribution of active sites. A regulatory factor, the net charge, is identified to predict the adsorption capability for key intermediates on active sites. Systematic electronic analyses reveal the origin of the interaction between the adsorbates and the active sites. These findings uncover the quantitative correlation between electronic structure properties and the catalytic performance of SnO _x so that Sn sites with moderate charge could achieve the optimally catalytic performance of the CO₂ electroreduction to formate.

Modeling CoCu Nanoparticles Using Neural Network-Accelerated Monte Carlo Simulations

The correct description of catalytic reactions happening on bimetallic particles is not feasible without proper accounting of the segregation process. In this study, we tried to shed light on the structure of large CoCu particles, for which quite controversial results were published before. However, density functional theory (DFT) is challenging to be directly used for the systematic study of nanometer-sized particles. Therefore, we constructed a neural network-based potential and further applied it to the Monte Carlo simulations for the description of the segregation phenomenon. The resulting approach shows high efficiency and can be used in systems with thousands of atoms. The accuracy and transferability of the model to other sizes and compositions make this methodology useful for solving segregation problems.

Revealing the Mechanism of sp-N Doping in Graphdiyne for Developing Site-Defined Metal-Free Catalysts

Due to the limited reserves of metals, scientists are devoted to exploring high-performance metal-free catalysts based on carbon materials to solve environment-related issues. Doping would build up inhomogeneous charge distribution on surface, which is an efficient approach for boosting the catalytic performance. However, doping sites are difficult to control in traditional carbon materials, thus hindering their development. Taking the advantage of unique sp-C in graphdiyne (GDY), a new N doping configuration of sp-hybridized nitrogen (sp-N), bringing a Pt-comparable catalytic activity in oxygen reduction reaction is site-defined introduced. However, the reaction intermediate of this process is never captured, hindering the understanding of the mechanism and the precise synthesis of metal-free catalysts. After the four-year study, the fabrication of intermediate-like molecule is realized, and finally sp-N doped GDY via the pericyclic reaction is obtained. Compared with GDY doped with other N configurations, the designed sp-N GDY shows much higher catalytic activity in electroreduction of CO₂ toward CH₄ production, owing to the unique electronic structure introduced by sp-N, which is more favorable in stabilizing the intermediate. Thus, besides opening the black-box for the site-defined doping, this work reveals the relationship between doping configuration and products of CO₂ reduction.

Nature of the Active Sites of Copper Zinc Catalysts for Carbon Dioxide Electroreduction

The electrochemical CO₂ reduction (CO₂ ER) to multi-carbon chemical feedstocks over Cu-based catalysts is of considerable attraction but suffers with the ambiguous nature of active sites, which hinder the rational design of catalysts and large-scale industrialization. This paper describes a large-scale simulation to obtain realistic CuZn nanoparticle models and the atom-level structure of active sites for C₂₊ products on CuZn catalysts in CO₂ ER, combining neural network based global optimization and density functional theory calculations. Upon analyzing over 2000 surface sites through high throughput tests based on NN potential, two kinds of active sites are identified, balanced Cu-Zn sites and Zn-heavy Cu-Zn sites, both facilitating C-C coupling, which are verified by subsequent calculational and experimental investigations. This work provides a paradigm for the design of high-performance Cu-based catalysts and may offer a general strategy to identify accurately the atomic structures of active sites in complex catalytic systems.

[Clinical characteristics and comprehensive treatment of patients with cleidocranial dysplasia]

Objective: To summarize the clinical characteristics of patients with cleidocranial dysplasia (CCD) and analyze their treatment methods. Methods: From January 2000 to December 2020, patients with CCD who completed comprehensive treatment in the Department of Orthodontics and the First Dental Clinic, School and Hospital of Stomatology, China Medical University were retrospectively analyzed. A total of 14 CCD patients [7 males and 7 females, aged (16.1±4.5) years] were collected. There were 153 impacted permanent teeth in this study. In addition to the teeth that needed to be extracted due to special conditions, 147 impacted teeth were pulled into the dentition using closed traction. Patients were divided into adolescent group (≥12 years and<18 years, 10 patients) and adult group (≥18 years, 4 patients). Failure rate of traction was compared between the two groups. Factors affecting the success rate of closed traction such as vertical position of teeth (high, middle and low) and horizontal position of the teeth (palatal, median and buccal) were analyzed. Results: The incidence of maxillary impacted teeth [69.3% (97/140)] was higher than that of mandibular impacted teeth [40% (56/140)]. The difference was statistically significant (χ²=24.22, P<0.001). The supernumerary teeth were mainly located in the premolar area 61.4% (21/44), and most of them were in the palatal region of the permanent teeth 95.5% (42/44). They were generally located at the same height or the occlusal side of the corresponding permanent teeth. The success rate of closed traction was 93.9% (138/147). The success rate in the adolescent group [98.2% (108/110)] was higher than that in the adult group [81.1% (30/37)], and the difference was significant (χ²=14.09, P<0.05). Failure after closed traction of 9 teeth was found totally, including 7 second premolars. The success rate of traction in impacted second premolars at different vertical (χ²=11.44, P<0.05) and horizontal (χ²=9.71, P<0.05) positions in alveolar bone was different significantlly. The success rates of the second premolars were high (15/16), middle (12/13), low (2/7), and lingual palatine (10/17), median (19/19), lip-buccal (0/0), respectively. Conclusions: The closed traction of impacted teeth in patients with CCD was effective, and the age was the main variable affecting the outcome. The success rate of traction in impacted second premolars located in low position vertically or in palatal position was low, which required close observation during treatment.

Support Stabilized PtCu Single-atom Alloys for Propane Dehydrogenation

PtCu single-atom alloys (SAAs) open an extensive prospect for heterogeneous catalysis. However, as the host of SAAs, Cu suffers from severe sintering at elevated temperature, resulting in poor stability of catalysts. This paper describes the suppression of the agglomeration of Cu nanoparticles under high temperature conditions using copper phyllosilicate (CuSiO₃) as the support of PtCu SAAs. Based on quasi in situ XPS, in situ CO-DRIFTS, in situ Raman spectroscopy and in situ XRD, we demonstrated that the interfacial Cu⁺–O–Si formed upon reduction at 680 °C serves as the adhesive between Cu nanoparticles and the silicon dioxide matrix, strengthening the metal–support interaction. Consequently, the resistance to sintering of PtCu SAAs was improved, leading to high catalytic stability during propane dehydrogenation without sacrificing conversion and selectivity. The optimized PtCu SAA catalyst achieved more than 42% propane conversion and 93% propylene selectivity at 580 °C for at least 30 hours. It paves a way for the design and development of highly active supported single-atom alloy catalysts with excellent thermal stability.

This paper describes PtCu single-atom alloys supported on copper phyllosilicate via Cu⁺–O–Si. The catalyst exhibits sintering resistance in propane dehydrogenation reaction without sacrificing activity and selectivity.

SrO-layer insertion in Ruddlesden–Popper Sn-based perovskite enables efficient CO2 electroreduction towards formate

Tin (Sn)-based oxides have been proved to be promising catalysts for the electrochemical CO₂ reduction reaction (CO₂RR) to formate (HCOO⁻). However, their performance is limited by their reductive transformation into metallic derivatives during the cathodic reaction. This paper describes the catalytic chemistry of a Sr₂SnO₄ electrocatalyst with a Ruddlesden–Popper (RP) perovskite structure for the CO₂RR. The Sr₂SnO₄ electrocatalyst exhibits a faradaic efficiency of 83.7% for HCOO⁻ at −1.08 V vs. the reversible hydrogen electrode with stability for over 24 h. The insertion of the SrO-layer in the RP structure of Sr₂SnO₄ leads to a change in the filling status of the anti-bonding orbitals of the Sn active sites, which optimizes the binding energy of *OCHO and results in high selectivity for HCOO⁻. At the same time, the interlayer interaction between interfacial octahedral layers and the SrO-layers makes the crystalline structure stable during the CO₂RR. This study would provide fundamental guidelines for the exploration of perovskite-based electrocatalysts to achieve consistently high selectivity in the CO₂RR.

This paper describes how the insertion of a SrO-layer in Ruddlesden–Popper Sr₂SnO₄ perovskite electrocatalysts promotes CO₂ reduction towards formate via *OCHO intermediate. A faradaic efficiency of 83.7% and stability for over 24 h were obtained.

Enhanced C–H bond activation by tuning the local environment of surface lattice oxygen of MoO3

The lattice oxygen on transition metal oxides serves as a critical active site in the dehydrogenation of alkanes, whose activity is determined by electronic properties and environmental structures. Hydrogen affinity has been used as a universal descriptor to predict C–H bond activation, while the understanding of the environmental structure is ambiguous due to its complexity. This paper describes a combined theoretical and experimental study to reveal the activity of lattice oxygen species with different local structures, taking Mo-based oxides and C–H bond activation of low-carbon alkanes as model catalytic systems. Our theoretical work suggests that oxygen species with convex curvature are more active than those with concave curvature. Theoretically, we propose an interpretative descriptor, the activation deformation energy, to quantify the surface reconstruction induced by adsorbates with various environmental structures. Experimentally, a Mo-based polyoxometalate with the convex curvature structure shows nearly five times the initial activity than single-crystal molybdenum oxide with the concave one. This work provides theoretical guidance for designing metal oxide catalysts with high activity.

Tuning of the environmental structure near the lattice oxygen of molybdenum oxides can form a favorable spatial structure to enhance the intrinsic activity for C–H bond activation.

Dynamics of Heterogeneous Catalytic Processes at Operando Conditions

The rational design of high-performance catalysts is hindered by the lack of knowledge of the structures of active sites and the reaction pathways under reaction conditions, which can be ideally addressed by an in situ/operando characterization. Besides the experimental insights, a theoretical investigation that simulates reaction conditions-so-called operando modeling-is necessary for a plausible understanding of a working catalyst system at the atomic scale. However, there is still a huge gap between the current widely used computational model and the concept of operando modeling, which should be achieved through multiscale computational modeling. This Perspective describes various modeling approaches and machine learning techniques that step toward operando modeling, followed by selected experimental examples that present an operando understanding in the thermo- and electrocatalytic processes. At last, the remaining challenges in this area are outlined.

[Research progress on virulence factors of hypervirulent Klebsiella pneumoniae]

Hypervirulent Klebsiella pneumoniae, short for hvKP, is a hypervirulent variant of classical Klebsiella pneumoniae, which accounts for serious infection in healthy people, exhibits strong pathogenicity, high mortality and poor prognosis. At present, hvkp is of high prevalence all over the world, and the infection rate shows a continuous upward trend, which brings great challenges to public health security and clinical treatment. This paper summarized the research progress on virulence factors of hvkp, such as capsular polysaccharides, siderophore, lipopolysaccharide, adhesins and recently discovered Type Ⅵ secreting system, and aimed to deepen the understanding and recognition of hvKP.

Moderate Surface Segregation Promotes Selective Ethanol Production in CO2 Hydrogenation Reaction over CoCu Catalysts

Cobalt-copper (CoCu) catalysts have industrial potential in CO/CO₂ hydrogenation reactions, and CoCu alloy has been elucidated as a major active phase during reactions. However, due to elemental surface segregation and dealloying phenomena, the actual surface morphology of CoCu alloy is still unclear. Combining theory and experiment, the dual effect of surface segregation and varied CO coverage over the CoCu(111) surface on the reactivity in CO₂ hydrogenation reactions is explored. The relationship between C-O bond scission and further hydrogenation of intermediate *CH₂ O was discovered to be a key step to promote ethanol production. The theoretical investigation suggests that moderate Co segregation provides a suitable surface Co ensemble with lateral interactions of co-adsorbed *CO, leading to promoted selectivity to ethanol, in agreement with theory-inspired experiments.

Efficient CO2 electroreduction on facet-selective copper films with high conversion rate

Tuning the facet exposure of Cu could promote the multi-carbon (C2+) products formation in electrocatalytic CO₂ reduction. Here we report the design and realization of a dynamic deposition-etch-bombardment method for Cu(100) facets control without using capping agents and polymer binders. The synthesized Cu(100)-rich films lead to a high Faradaic efficiency of 86.5% and a full-cell electricity conversion efficiency of 36.5% towards C2+ products in a flow cell. By further scaling up the electrode into a 25 cm² membrane electrode assembly system, the overall current can ramp up to 12 A while achieving a single-pass yield of 13.2% for C2+ products. An insight into the influence of Cu facets exposure on intermediates is provided by in situ spectroscopic methods supported by theoretical calculations. The collected information will enable the precise design of CO₂ reduction reactions to obtain desired products, a step towards future industrial CO₂ refineries.

Regulation of Cu facets to promote electrocatalytic CO₂ reduction is interesting and challenging. Here the authors describe a deposition-etch-bombardment synthetic approach to prepare Cu(100)-rich thin film electrodes for CO₂ electroreduction with over 50% ethylene Faradaic efficiency at a total current of 12 A.

[Evaluation of classification of petroclival meningiomas and proposed selection of microsurgical approach: a single center experience of 179 cases]

Objective: To evaluate the classification of petroclival meningiomas(PCM), proposed selection of microsurgical approach and therapeutic outcomes. Methods: Retrospectively analyzed clinical data of 179 cases of PCM from Department of Neurosurgery, Xiangya Hospital, Central South University between January 2011 and November 2020. There were 28 males and 151 females with an age of(49.9±10.2) years(range: 22 to 75 years) and the tumor size of(44.8±10.3)mm(range: 15 to 80 mm). The mean duration of symptom(M(QR)) was 18.0(40.6)months(range:1 week to 320 months) and the mean preoperative Karnofsky performance scale(KPS) was 78.6±13.3(range: 40 to 100). The PCM were classified into 5 types according to the difference in the origin of dural attachment, involvement of adjacent structures and growth patterns through preoperative MRI. The surgical approaches were selected based on the proposed classification, and the clinical characteristics, surgical record, and follow-up data of each type were reviewed. Results: The PCM were divided into clivus type(CV, 4 cases), petroclival type(PC, 60 cases), petroclivosphenoidal type(PC-S, 62 cases), sphenopetroclival type with 2 subtypes(S-PC, 50 cases) and central skull base type(CSB, 3 cases). All of 176 cases were obtained microsurgical treatment except CSB type. The gross total resection reached in 124 cases(70.5%) with 112 cases of retrosigmoid approach(RSA), 27 cases of subtemporal transtentorial transpetrosal approach, 13 cases of pretemporal trancavernous anterior transpetrosal approach(PTCA), 12 cases of extended pterional transtentorial approach(EPTA) and presigmoid combined supra-infratentorial approach, respectively. The RSA could be adopted in both of CV type and PC type and most of PC-S type(71.0%). S-PC subtype Ⅰ and subtype Ⅱ were mainly underwent EPTA(40.8%) and PTCA(52.2%), respectively. Seventy-two cases(40.9%) gained new neurological dysfunctions mainly with the cranial nerve paralysis. The postoperative morbidity and complications were recovered or improved with conservative and positive symptomatic and supportive treatment. There was no intraoperative and postoperative death case. One hundred and sixty four cases(93.2%) of operative patients were followed with the duration of 24(48)months(range:3 to 108 months). Tumor recurrence and progress were identified in 14 cases(10.4%) and 14 cases(28.6%), respectively. Compared with postoperative neurological status, 89 patients(54.3%) had improved and 38 patients(23.2%) were still suffering various degrees of neurological dysfunctions during the follow-up. The recent KPS was 84.2±11.4(range: 50 to 100) without statistical difference from preoperative KPS(t=-1.356,P=0.125). As for each type, there were statistically significant differences in brain stem edema(χ2=3.482,P=0.038), gross total resection(χ2=9.127,P=0.001), surgical duration(F=8.954, P=0.013), postoperative length of stay(F=3.652, P=0.025), postoperative complications(χ2=1.550,P=0.024), postoperative KPS(F=2.856, P=0.042) and tumor recurrence/progress(χ2=4.824,P=0.013). Conclusion: The precise and comprehensive classification of PCM and specific individual treatment strategy are benefit to evaluate the diverse clinical prognosis, choose optimal surgical approaches, elevate gross total resection, diminish neurological dysfunctions and restraint tumor recurrence, so as to improve the quality of life for patients.

CLCU-Net: Cross-level connected U-shaped network with selective feature aggregation attention module for brain tumor segmentation

BACKGROUND AND OBJECTIVE

Brain tumors are among the most deadly cancers worldwide. Due to the development of deep convolutional neural networks, many brain tumor segmentation methods help clinicians diagnose and operate. However, most of these methods insufficiently use multi-scale features, reducing their ability to extract brain tumors' features and details. To assist clinicians in the accurate automatic segmentation of brain tumors, we built a new deep learning network to make full use of multi-scale features for improving the performance of brain tumor segmentation.

METHODS

We propose a novel cross-level connected U-shaped network (CLCU-Net) to connect different scales' features for fully utilizing multi-scale features. Besides, we propose a generic attention module (Segmented Attention Module, SAM) on the connections of different scale features for selectively aggregating features, which provides a more efficient connection of different scale features. Moreover, we employ deep supervision and spatial pyramid pooling (SSP) to improve the method's performance further.

RESULTS

We evaluated our method on the BRATS 2018 dataset by five indexes and achieved excellent performance with a Dice Score of 88.5%, a Precision of 91.98%, a Recall of 85.62%, a Params of 36.34M and Inference Time of 8.89ms for the whole tumor, which outperformed six state-of-the-art methods. Moreover, the performed analysis of different attention modules' heatmaps proved that the attention module proposed in this study was more suitable for segmentation tasks than the other existing popular attention modules.

CONCLUSION

Both the qualitative and quantitative experimental results indicate that our cross-level connected U-shaped network with selective feature aggregation attention module can achieve accurate brain tumor segmentation and is considered quite instrumental in clinical practice implementation.

Controllable Distribution of Oxygen Vacancies in Grain Boundaries of p-Si/TiO2 Heterojunction Photocathodes for Solar Water Splitting

Silicon is a promising photocathode material in photoelectrochemical water splitting for hydrogen production, but it is primarily limited by photocorrosion in aqueous electrolytes. As an extensively used protective material, crystalline TiO₂ could protect Si photoelectrode against corrosion. However, a large number of grain boundaries (GBs) in polycrystalline TiO₂ would induce excessive recombination centers, impeding the carrier transport. This paper describes the introduction of oxygen vacancies (O_vac ) with controllable spatial distribution for GBs to promote carrier transport. Two kinds of O_vac distribution, O_vac along GBs and O_vac inside grains, are compared, where the latter one is demonstrated to facilitate carrier transport owing to the formation of tunneling paths across GBs. Consequently, a simple p-Si/TiO₂ /Pt heterojunction photocathode with controllable O_vac distribution in TiO₂ shows a +400 mV onset potential shift and yields an applied bias photon-to-current efficiency of 5.9 %, which is the best efficiency reported among silicon photocathodes except for silicon homojunction.

Coupling of Cu(100) and (110) Facets Promotes Carbon Dioxide Conversion to Hydrocarbons and Alcohols

Copper can efficiently electro-catalyze carbon dioxide reduction to C₂₊ products (C₂ H₄ , C₂ H₅ OH, n-propanol). However, the correlation between the activity and active sites remains ambiguous, impeding further improvements in their performance. The facet effect of copper crystals to promote CO adsorption and C-C coupling and consequently yield a superior selectivity for C₂₊ products is described. We achieve a high Faradaic efficiency (FE) of 87 % and a large partial current density of 217 mA cm^-2 toward C₂₊ products on Cu(OH)₂ -D at only -0.54 V versus the reversible hydrogen electrode in a flow-cell electrolyzer. With further coupled to a Si solar cell, record-high solar conversion efficiencies of 4.47 % and 6.4 % are achieved for C₂ H₄ and C₂₊ products, respectively. This study provides an in-depth understanding of the selective formation of C₂₊ products on Cu and paves the way for the practical application of electrocatalytic or solar-driven CO₂ reduction.

The nature of active sites for carbon dioxide electroreduction over oxide-derived copper catalysts

The active sites for CO₂ electroreduction (CO₂R) to multi-carbon (C₂₊) products over oxide-derived copper (OD-Cu) catalysts are under long-term intense debate. This paper describes the atomic structure motifs for product-specific active sites on OD-Cu catalysts in CO₂R. Herein, we describe realistic OD-Cu surface models by simulating the oxide-derived process via the molecular dynamic simulation with neural network (NN) potential. After the analysis of over 150 surface sites through NN potential based high-throughput testing, coupled with density functional theory calculations, three square-like sites for C-C coupling are identified. Among them, Σ3 grain boundary like planar-square sites and convex-square sites are responsible for ethylene production while step-square sites, i.e. n(111) × (100), favor alcohols generation, due to the geometric effect for stabilizing acetaldehyde intermediates and destabilizing Cu-O interactions, which are quantitatively demonstrated by combined theoretical and experimental results. This finding provides fundamental insights into the origin of activity and selectivity over Cu-based catalysts and illustrates the value of our research framework in identifying active sites for complex heterogeneous catalysts.

The Expression of IbMYB1 Is Essential to Maintain the Purple Color of Leaf and Storage Root in Sweet Potato [Ipomoea batatas (L.) Lam]

IbMYB1 was one of the major anthocyanin biosynthesis regulatory genes that has been identified and utilized in purple-fleshed sweet potato breeding. At least three members of this gene, namely, IbMYB1-1, -2a, and -2b, have been reported. We found that IbMYB1-2a and -2b are not necessary for anthocyanin accumulation in a variety of cultivated species (hexaploid) with purple shoots or purplish rings/spots of flesh. Transcriptomic and quantitative reverse transcription PCR (RT-qPCR) analyses revealed that persistent and vigorous expression of IbMYB1 is essential to maintain the purple color of leaves and storage roots in this type of cultivated species, which did not contain IbMYB1-2 gene members. Compared with IbbHLH2, IbMYB1 is an early response gene of anthocyanin biosynthesis in sweet potato. It cannot exclude the possibility that other MYBs participate in this gene regulation networks. Twenty-two MYB-like genes were identified from 156 MYBs to be highly positively or negatively correlated with the anthocyanin content in leaves or flesh. Even so, the IbMYB1 was most coordinately expressed with anthocyanin biosynthesis genes. Differences in flanking and coding sequences confirm that IbMYB2s, the highest similarity genes of IbMYB1, are not the members of IbMYB1. This phenomenon indicates that there may be more members of IbMYB1 in sweet potato, and the genetic complementation of these members is involved in the regulation of anthocyanin biosynthesis. The 3' flanking sequence of IbMYB1-1 is homologous to the retrotransposon sequence of TNT1-94. Transposon movement is involved in the formation of multiple members of IbMYB1. This study provides critical insights into the expression patterns of IbMYB1, which are involved in the regulation of anthocyanin biosynthesis in the leaf and storage root. Notably, our study also emphasized the presence of a multiple member of IbMYB1 for genetic improvement.

Selective Electroreduction of Carbon Dioxide over SnO2 -Nanodot Catalysts

The development of electrochemical CO₂ conversion allows green carbon utilization. Formate and syngas are two typical products of electrochemical CO₂ reduction, and the coproduction of these two products will maximize the energy efficiency of CO₂ conversion. However, few works have successfully achieved the cogeneration of formate and syngas. This paper describes a novel strategy to maximize the efficiency of CO₂ conversion through coproduction of formate and syngas on ultrasmall SnO₂ nanodots (NDs) homogeneously anchored on carbon nanotubes (CNT#SnO₂ NDs) electrodes. The CNT#SnO₂ NDs not only decreased the adsorption energy of *OCHO but also reduced the adsorption energy difference of *COOH and *H. High energy efficiency toward formate and adjustable H₂ /CO ratio were obtained over a broad potential window with long-term stability. In addition, CNT#SnO₂ NDs and Ir foil were coupled together to construct an electrolyzer for electrochemical CO₂ reduction reaction and oxygen evolution reaction (CO₂ ERR-OER), which also produced formate and syngas with 24 h stability. A promising approach is presented for the electrochemical CO₂ conversion in fuel production.

[Research progress on the regulation mechanism of Pseudomonas aeruginosa biofilm]

Pseudomonas aeruginosa is one of the common multidrug-resistant bacteria in the clinic. Because it can produce a "protective" biofilm, it can affect the penetration and killing efficacy of antibacterial drugs, leading to the formation of a persistent and persistent chronic infection in the host. Biofilms make Pseudomonas aeruginosa resistant to antibacterials and evasive to the host's immune system. Therefore, traditional conventional antibacterials are difficult to achieve effective bactericidal treatment. Understanding the process of P. aeruginosa biofilm formation and the regulatory mechanisms that affect biofilms can provide ideas and methods for our future research on new antibacterial drugs.

Strong Electronic Oxide-Support Interaction over In2O3/ZrO2 for Highly Selective CO2 Hydrogenation to Methanol

Metal oxides are widely employed in heterogeneous catalysis, but it remains challenging to determine their exact structure and understand the reaction mechanisms at the molecular level due to their structural complexity, in particular for binary oxides. This paper describes the observation of the strong electronic interaction between In₂O₃ and monoclinic ZrO₂ (m-ZrO₂) by quasi-in-situ XPS experiments combined with theoretical studies, which leads to support-dependent methanol selectivity. In₂O₃/m-ZrO₂ exhibits methanol selectivity up to 84.6% with a CO₂ conversion of 12.1%. Moreover, at a wide range of temperatures, the methanol yield of In₂O₃/m-ZrO₂ is much higher than that of In₂O₃/t-ZrO₂ (t-: tetragonal), which is due to the high dispersion of the In-O-In structure over m-ZrO₂ as determined by in situ Raman spectra. The electron transfer from m-ZrO₂ to In₂O₃ is confirmed by XPS and DFT calculations and improves the electron density of In₂O₃, which promotes H₂ dissociation and hydrogenation of formate intermediates to methanol. The concept of the electronic interaction between an oxide and a support provides guidelines to develop hydrogenation catalysts.