Hydrogen Electrode Reactions in Energy-Related Electrocatalysis Systems.

Hydrogen electrode reactions, including hydrogen evolution reactions and hydrogen oxidation reactions, are fundamental and crucial within aqueous electrochemistry. Particularly in energy-related electrocatalysis processes, there is a consistent involvement of hydrogen-related electrochemical processes, underscoring the need for in-depth study. This review encompasses significant reports, delving into elementary steps and reaction mechanisms of hydrogen electrode reactions, as well as catalyst design strategies. In addition, we focus on the application of hydrogen electrode reaction mechanism in different energy-related electrocatalytic reactions, and the significance of the promotion and suppression of reaction kinetics in different reaction systems. It thoroughly elucidated the significance of these reactions and the need for a deeper understanding, offering a novel perspective for the future development of this field.

TCS-Fall: Cross-individual fall detection system based on channel state information and time-continuous stack method.

Background: Falls pose a serious health risk for the elderly, particular for those who are living alone. The utilization of WiFi-based fall detection, employing Channel State Information (CSI), emerges as a promising solution due to its non-intrusive nature and privacy preservation. Despite these advantages, the challenge lies in optimizing cross-individual performance for CSI-based methods. Objective: This study aimed to develop a resilient real-time fall detection system across individuals utilizing CSI, named TCS-Fall. This method was designed to offer continuous monitoring of activities over an extended timeframe, ensuring accurate and prompt detection of falls. Methods: Extensive CSI data on 1800 falls and 2400 daily activities was collected from 20 volunteers. The grouped coefficient of variation of CSI amplitudes were utilized as input features. These features capture signal fluctuations and are input to a convolutional neural network classifier. Cross-individual performance was extensively evaluated using various train/test participant splits. Additionally, a user-friendly CSI data collection and detection tool was developed using PyQT. To achieve real-time performance, data parsing and pre-processing computations were optimized using Numba's just-in-time compilation. Results: The proposed TCS-Fall method achieved excellent performance in cross-individual fall detection. On the test set, AUC reached 0.999, no error warning ratio score reached 0. 955 and correct warning ratio score reached of 0.975 when trained with data from only two volunteers. Performance can be further improved to 1.00 when 10 volunteers were included in training data. The optimized data parsing/pre-processing achieved over 20× speedup compared to previous method. The PyQT tool parsed and detected the fall within 100 ms. Conclusions: TCS-Fall method enables excellent real-time cross-individual fall detection utilizing WiFi CSI, promising swift alerts and timely assistance to elderly. Additionally, the optimized data processing led to a significant speedup. These results highlight the potential of our approach in enhancing real-time fall detection systems.

Structure-Function Relationship of p-Block Bismuth for Selective Photocatalytic CO2 Reduction.

Selective photocatalytic reduction of CO2 to value-added fuels, such as CH4, is highly desirable due to its high mass-energy density. Nevertheless, achieving selective CH4 with higher production yield on p-block materials is hindered by non-ideal adsorption of *CHO key intermediate and an unclear structure-function relationship. Herein, we unlock the key reaction steps of CO2 and found a volcano-type structure-function relationship for photocatalytic CO2-to-CH4 conversion by gradual reduction of the p-band center of the p-block Bi element leading to formation of Bi-oxygen vacancy heterosites. The selectivity of CH4 is also positive correlation with adsorption energy of *CHO. The Bi-oxygen vacancy heterosites with an appropriate filled Bi-6p orbital electrons and p band center (-0.64) enhance the coupling between C-2p of *CHO and Bi-6p orbitals, thereby resulting in high selectivity (95.2%) and productivity (17.4 µmol g-1 h-1) towards CH4. Further studies indicate that the synergistic effect between Bi-oxygen vacancy heterosites reduces Gibbs free energy for *CO--*CHO process, activates the C-H and C=O bonds of *CHO, and facilitates the enrichment of photoexcited electrons at active sites for multielectron photocatalytic CO2-to-CH4 conversion. This work provides a new perspective on developing p-block elements for selective photocatalytic CO2 conversion.

The age and growth information of a ctenoid scale fossil from the Upper Cretaceous Nenjiang Formation in Songliao Basin, China.

The study of morphological characteristics and growth information in fish scales is a crucial component of modern fishery biological research, while it has been less studied in fossil materials. This paper presents a detailed morphological description and growth analysis of a fossil ctenoid scale obtained from the Upper Cretaceous Campanian lacustrine deposits in northeastern China. The morphological features of this fossil scale are well-preserved and consistent with the structures found in ctenoid scales of extant fish species and display prominent ring ornamentation radiating outward from the central focus, with grooves intersecting the rings. A comparative analysis of the morphological characteristics between the fossil ctenoid scale and those well-studied extant fish Mugilidae allows us to explore the applicability of modern fishery biological research methods to the field of fossil scales. The scale length, scale width, the vertical distance from the focus to the apex of the scale, and the total number of radii have been measured. The age of the fish that possessed this ctenoid scale has been estimated by carefully counting the annuli, suggesting an age equal to or more than seven years. The distribution of growth rings on the scale potentially reflects the warm paleoclimatic condition and fish-friendly paleoenvironment prevalent during that period. This paper, moreover, serves as a notable application of fishery biological methods in the examination of fossil materials.

Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.

BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity. METHODS: We retrospectively recruited GSP patients who underwent CT imaging within 48 h of admission from tertiary referral centre. Radiomics and CT features were extracted from CT scans. The clinical and CT features were selected by the random forest algorithm to develop the ML GSP model for the identification of severity of GSP (mild or severe), and its predictive efficacy was compared with radiomics model. The predictive performance was assessed by the area under operating characteristic curve. Calibration curve and decision curve analysis were performed to demonstrate the classification performance and clinical efficacy. Furthermore, we built a web-based open access GSP severity calculator. The study was registered with ClinicalTrials.gov (NCT05498961). RESULTS: A total of 301 patients were enrolled. They were randomly assigned into the training (n = 210) and validation (n = 91) cohorts at a ratio of 7:3. The random forest algorithm identified the level of calcium ions, WBC count, urea level, combined cholecystitis, gallbladder wall thickening, gallstones, and hydrothorax as the seven predictive factors for severity of GSP. In the validation cohort, the areas under the curve for the radiomics model and ML GSP model were 0.841 (0.757-0.926) and 0.914 (0.851-0.978), respectively. The calibration plot shows that the ML GSP model has good consistency between the prediction probability and the observation probability. Decision curve analysis showed that the ML GSP model had high clinical utility. CONCLUSIONS: We built the ML GSP model based on clinical and CT image features and distributed it as a free web-based calculator. Our results indicated that the ML GSP model is useful for predicting the severity of GSP.

ML GSP model based on machine learning has good severity discrimination in both training and validation cohorts (0.916 (0.872­0.958), 0.914 (0.851­0.978), respectively).We built an online user-friendly platform for the ML GSP model to help clinicians better identify the severity of GSP.

Visualization and Quantification of Drug Release by GSH-Responsive Multimodal Integrated Micelles.

Using molecular imaging techniques to monitor biomarkers and drug release profiles simultaneously is highly advantageous for cancer diagnosis and treatment. However, achieving the accurate quantification of both biomarkers and drug release with a single imaging modality is challenging. This study presents the development of a glutathione (GSH)-responsive polymer-based micelle, PEG-SS-FCy7/PEG-SS-GEM (PSFG), which can precisely localize the tumor using bimodal imaging and prevent drug leakage. These PSFG micelles exhibit a small particle size of 106.3 ± 12.7 nm with a uniform size distribution, and the drug loading efficiency can also be easily controlled by changing the PEG-SS-FCy7 (PSF) and PEG-SS-GEM (PSG) feeding ratio. The PSFG micelles display weak fluorescence emission and minimal drug release under physiological conditions but collapse in the presence of GSH to trigger near-infrared fluorescence and the 19F magnetic resonance imaging signal, allowing for real-time monitoring of intracellular GSH levels and drug release. GSH could synergistically promote the disassembly of the micellar structure, resulting in accelerated probe and drug release of up to about 93.1% after 24 h. These prodrug micelles exhibit high in vitro and in vivo antitumor abilities with minimal side effects. The GSH-responsive drug delivery system with dual-modal imaging capability provides a promising imaging-guided chemotherapeutic platform to probe the tumor microenvironment and quantify real-time drug release profiles with minimal side effects.

Efficient Homolytic Cleavage of H2O2 on Hydroxyl-Enriched Spinel CuFe2O4 with Dual Lewis Acid Sites.

Traditional H2O2 cleavage mediated by macroscopic electron transfer (MET) not only has low utilization of H2O2, but also sacrifices the stability of catalysts. We present a non-redox hydroxyl-enriched spinel (CuFe2O4) catalyst with dual Lewis acid sites to realize the homolytic cleavage of H2O2. The results of systematic experiments, in situ characterizations, and theoretical calculations confirm that tetrahedral Cu sites with optimal Lewis acidity and strong electron delocalization can synergistically elongate the O-O bonds (1.47 Š→ 1.87 Å) in collaboration with adjacent bridging hydroxyl (another Lewis acid site). As a result, the free energy of H2O2 homolytic cleavage is decreased (1.28 eV → 0.98 eV). H2O2 can be efficiently split into ⋅OH induced by hydroxyl-enriched CuFe2O4 without MET, which greatly improves the catalyst stability and the H2O2 utilization (65.2 %, nearly 2 times than traditional catalysts). The system assembled with hydroxyl-enriched CuFe2O4 and H2O2 affords exceptional performance for organic pollutant elimination. The scale-up experiment using a continuous flow reactor realizes long-term stability (up to 600 mL), confirming the tremendous potential of hydroxyl-enriched CuFe2O4 for practical applications.

IAS-FET: An intelligent assistant system and an online platform for enhancing successful rate of in-vitro fertilization embryo transfer technology based on clinical features.

BACKGROUND: Among all of the assisted reproductive technology (ART) methods, in vitro fertilization-embryo transfer (IVF-ET) holds a prominent position as a key solution for overcoming infertility. However, its success rate hovers at a modest 30% to 70%. Adding to the challenge is the absence of effective models and clinical tools capable of predicting the outcome of IVF-ET before embryo formation. Our study is dedicated to filling this critical gap by aiming to predict IVF-ET outcomes and ultimately enhance the success rate of this transformative procedure. METHODS: In this retrospective study, infertile patients who received artificial assisted pregnancy treatment at Gansu Provincial Maternity and Child-care Hospital in China were enrolled from 2016 to 2020. Individual's clinical information were studied by cascade XGBoost method to build an intelligent assisted system for predicting the outcome of IVF-ET, called IAS-FET. The cascade XGBoost model was trained using clinical information from 2292 couples and externally tested using clinical information from 573 couples. In addition, several schemes which will be of help for patients to adjust their physical condition to improve their success rate on ART were suggested by IAS-FET. RESULTS: The outcome of IVF-ET can be predicted by the built IAS-FET method with the area under curve (AUC) value of 0.8759 on the external test set. Besides, this IAS-FET method can provide several schemes to improve the successful rate of IVF-ET outcomes. The built tool for IAS-FET is addressed as a free platform online at http://www.cppdd.cn/ART for the convenient usage of users. CONCLUSIONS: It suggested the significant influence of personal clinical features for the success of ART. The proposed system IAS-FET based on the top 27 factors could be a promising tool to predict the outcome of ART and propose a plan for the patient's physical adjustment. With the help of IAS-FET, patients can take informed steps towards increasing their chances of a successful outcome on their journey to parenthood.

Designing Yolk-Shell Nanostructures for Reversible Water-Vapor-Responsive Dual-Mode Switching of Fluorescence and Structural Color.

Metal halide perovskites offer ample opportunities to develop advanced optoelectronic devices. This work showcases that the integration of metal halide perovskites into metal oxide nanoshells with controllable interior cavities can enable water-vapor-responsive dual-mode switching of fluorescence and structural color. Through a ship-in-a-bottle method to introduce a controlled amount of CsPbBr3 into MnO2 nanoshells, we have designed CsPbBr3@MnO2 yolk-shell nanostructures, which can uptake a defined amount of water to exhibit rapid (less than 1 s) and reversible (≥100 cycles) responses in both fluorescence on-off and color change when exposed to dynamic water vapor. These responses originate from the water-triggered phase transformation of CsPbBr3 to CsPb2Br5 and the structural color change of the MnO2 shell. The altered electronic and bonding structure at the oxide-halide interface, rapid water accumulation in the yolk-shell cavity, and protective effect of the oxide shell facilitate the reversible transformations. The response characteristics of the yolk-shell nanostructures have been further demonstrated in fabricating patterned films capable of multiple fluorescence/structural color responses, highlighting their potential for applications in advanced anticounterfeiting and encryption.

Revealing the Effect of the [CoO]6 Microstructure in Pseudocapacitance by Controlled Delithium of LiCoO2.

Revealing the in-depth structure-property relationship and designing specific capacity electrodes are particularly important for supercapacitors. Despite many efforts made to tune the composition and electronic structure of cobalt oxide for pseudocapacitance, insight into the [CoO]6 octahedron from the microstructure is still insufficient. Herein, we present a tunable [CoO]6 octahedron microstructure in LiCoO2 by a chemical delithiation process. The c-strained strain of the [CoO]6 octahedron is induced to form higher valence Co ions, and the (003) crystalline layer spacing increases to allow more rapid participation of OH- in the redox reaction. Interestingly, the specific capacity of L0.75CO2 is nearly four times higher than that of LiCoO2 at 10 mA g-1. The enhanced activity originated from the asymmetric strain [CoO]6 octahedra, resulting in enhanced electronic conductivity and Co-O hybridization for accelerated redox kinetics. This finding provides new insights into the modification strategy for pseudocapacitive transition metal oxides.

Catalysts and electrolyzers for the electrochemical CO2 reduction reaction: from laboratory to industrial applications.

To cope with the urgent environmental pressure and tight energy demand, using electrocatalytic methods to drive the reduction of carbon dioxide molecules and produce a variety of fuels and chemicals, is one of the effective pathways to achieve carbon neutrality. In recent years, many significant advances in the study of the electrochemical carbon dioxide reduction reaction (CO2RR) have been made, but most of the works exhibit low current density, small electrode area and poor long-term stability, which are not suitable for large-scale industrial applications. Herein, combining the research achievements obtained in laboratories and the practical demand of industrial production, we summarize recent frontier progress in the field of the electrochemical CO2RR, including the fundamentals of catalytic reactions, catalyst design and preparation, and the construction of electrolyzers. In addition, we discuss the bottleneck problem of industrial CO2 electrolysis, and further present the prospect of the essential issues to be solved by the available technology for industrial electrolysis. This review can provide some basic understanding and knowledge accumulation for the development and practical application of electrochemical CO2RR technology.

Dual-axial engineering on atomically dispersed catalysts for ultrastable oxygen reduction in acidic and alkaline solutions.

Atomically dispersed catalysts are a promising alternative to platinum group metal catalysts for catalyzing the oxygen reduction reaction (ORR), while limited durability during the electrocatalytic process severely restricts their practical application. Here, we report an atomically dispersed Co-doped carbon-nitrogen bilayer catalyst with unique dual-axial Co-C bonds (denoted as Co/DACN) by a smart phenyl-carbon-induced strategy, realizing highly efficient electrocatalytic ORR in both alkaline and acidic media. The corresponding half-wave potential for ORR is up to 0.85 and 0.77 V (vs. reversible hydrogen electrode (RHE)) in 0.5 M H2SO4 and 0.1 M KOH, respectively, representing the best ORR activity among all non-noble metal catalysts reported to date. Impressively, the Zn-air battery (ZAB) equipped with Co/DACN cathode achieves outstanding durability after 1,688 h operation at 10 mA cm-2 with a high current density (154.2 mA cm-2) and a peak power density (210.1 mW cm-2). Density functional theory calculations reveal that the unique dual-axial cross-linking Co-C bonds of Co/DACN significantly enhance the stability during ORR and also facilitate the 4e- ORR pathway by forming a joint electron pool due to the improved interlayer electron mobility. We believe that axial engineering opens a broad avenue to develop high-performance heterogeneous electrocatalysts for advanced energy conversion and storage.

Pauling-Type Adsorption of O2 Induced by Heteroatom Doped ZnIn2 S4 for Boosted Solar-Driven H2 O2 Production.

Breaking the trade-off between activity and selectivity has perennially been a formidable endeavor in the field of hydrogen peroxide (H2 O2 ) photosynthesis, especially the side-on configuration of oxygen (O2 ) on the catalyst surface will cause the cleavage of O-O bonds, which drastically hinders the H2 O2 production performance. Herein, we present an atomically heteroatom P doped ZnIn2 S4 catalyst with tunable oxygen adsorption configuration to accelerate the ORR kinetics essential for solar-driven H2 O2 production. Indeed, the spectroscopy characterizations (such as EXAFS and in situ FTIR) and DFT calculations reveal that heteroatom P doped ZnIn2 S4 at substitutional and interstitial sites, which not only optimizes the coordination environment of Zn active sites, but also facilitates electron transfer to the Zn sites and improves charge density, avoiding the breakage of O-O bonds and reducing the energy barriers to H2 O2 production. As a result, the oxygen adsorption configuration is regulated from side-on (Yeager-type) to end-on (Pauling-type), resulting in the accelerated ORR kinetics from 874.94 to 2107.66 µmol g-1 h-1 . This finding offers a new avenue toward strategic tailoring oxygen adsorption configuration by the rational design of doped photocatalyst.

Stabilizing Undercoordinated Zn Active Sites through Confinement in CeO2 Nanotubes for Efficient Electrochemical CO2 Reduction.

Zn-based catalysts hold great potential to replace the noble metal-based ones for CO2 reduction reaction (CO2 RR). Undercoordinated Zn (Znδ+ ) sites may serve as the active sites for enhanced CO production by optimizing the binding energy of *COOH intermediates. However, there is relatively less exploration into the dynamic evolution and stability of Znδ+ sites during CO2 reduction process. Herein, we present ZnO, Znδ+ /ZnO and Zn as catalysts by varying the applied reduction potential. Theoretical studies reveal that Znδ+ sites could suppress HER and HCOOH production to induce CO generation. And Znδ+ /ZnO presents the highest CO selectivity (FECO 70.9 % at -1.48 V vs. RHE) compared to Zn and ZnO. Furthermore, we propose a CeO2 nanotube with confinement effect and Ce3+ /Ce4+ redox to stabilize Znδ+ species. The hollow core-shell structure of the Znδ+ /ZnO/CeO2 catalyst enables to extremely expose electrochemically active area while maintaining the Znδ+ sites with long-time stability. Certainly, the target catalyst affords a FECO of 76.9 % at -1.08 V vs. RHE and no significant decay of CO selectivity in excess of 18 h.

Corner-Sharing Tetrahedrally Coordinated W-V Dual Active Sites on Cu2 V2 O7 for Photoelectrochemical Water Oxidation.

The sluggish four-electron oxygen evolving reaction is one of the key limitations of photoelectrochemical water decomposition. Optimizing the binding of active sites to oxygen in water and promoting the conversion of *O to *OOH are the key to enhancing oxygen evolution reaction. In this work, W-doped Cu2 V2 O7 (CVO) constructs corner-sharing tetrahedrally coordinated W-V dual active sites to induce the generation of electron deficiency active centers, promote the adsorption of ─OH, and accelerate the transformation of *O to *OOH for water splitting. The photocurrent obtained by the W-modified CVO photoanode is 0.97 mA cm-2 at 1.23 V versus RHE, which is much superior to that of the reported CVO. Experimental and theoretical results show that the excellent catalytic performance may be attributed to the formation of synergistic dual active sites between W and V atoms, and the introduction of W ions reduces the charge migration distance and prolongs the lifetime of photogenerated carriers. Meanwhile, the electronic structure in the center of the d-band is modulated, which leads to the redistribution of the electron density in CVO and lowers the energy barrier for the conversion of the rate-limiting step *O to *OOH.

Selective CO2 -to-Syngas Conversion Enabled by Bimetallic Gold/Zinc Sites in Partially Reduced Gold/Zinc Oxide Arrays.

Electrocatalytic CO2 -to-syngas (gaseous mixture of CO and H2 ) is a promising way to curb excessive CO2 emission and the greenhouse gas effect. Herein, we present a bimetallic AuZn@ZnO (AuZn/ZnO) catalyst with high efficiency and durability for the electrocatalytic reduction of CO2 and H2 O, which enables a high Faradaic efficiency of 66.4 % for CO and 26.5 % for H2 and 3 h stability of CO2 -to-syngas at -0.9 V vs. the reversible hydrogen electrode (RHE). The CO/H2 ratios show a wide range from 0.25 to 2.50 over a narrow potential window (-0.7 V to -1.1 V vs. RHE). In situ attenuated total reflection surface-enhanced infrared absorption spectroscopy combined with density functional theory calculations reveals that the bimetallic synergistic effect between Au and Zn sites lowers the activation energy barrier of CO2 molecules and facilitates electronic transfer, further highlighting the potential to control CO/H2 ratios for efficient syngas production using the coexisting Au sites and Zn sites.

Efficient Catalytic Production of Hydrogen Peroxide Using Tin-containing Zeolite Fixed Palladium Nanoparticles with Oxidation Resistance.

The metal surfaces tend to be oxidized in air through dissociation of the O-O bond of oxygen to reduce the performances in various fields. Although several ligand modification routes have alleviated the oxidation of bulky metal surfaces, it is still a challenge for the oxidation resistance of small-size metal nanoparticles. Herein, we fixed the small-size Pd nanoparticles in tin-contained MFI zeolite crystals, where the tin acts as an electron donor to efficiently hinder the oxidation of Pd by weakening the adsorption of molecular oxygen and suppressing the O-O cleavage. This oxidation-resistant Pd catalyst exhibited superior performance in directly synthesizing hydrogen peroxide from hydrogen and oxygen, with the productivity of hydrogen peroxide at ≈10,170 mmol gPd -1 h-1 , steadily outperforming the catalysts tested previously. This work leads to the hypothesis that tin is an electron donor to realize oxidation-resistant Pd within zeolite crystals for efficient catalysis to overcome the limitation of generally supported Pd catalysts and further motivates the use of oxidation-resistant metal nanoparticles in various fields.

An NIR Fluorescence Turn-on and MRl Bimodal Probe for Concurrent Real-time in vivo Sensing and Labeling of ß-Galactosidase.

To realize sensing and labeling biomarkers is quite challenging in terms of designing multimodal imaging probes. In this study, we developed a novel ß-galactosidase (ß-gal) activated bimodal imaging probe that combines near-infrared (NIR) fluorescence and magnetic resonance imaging (MRI) to enable real-time visualization of activity in living organisms. Upon ß-gal activation, Gal-Cy-Gd-1 exhibits a remarkable 42-fold increase in NIR fluorescence intensity at 717 nm, allowing covalent labeling of adjacent target enzymes or proteins and avoiding molecular escape to promote probe accumulation at the tumor site. This fluorescence reaction enhances the longitudinal relaxivity by approximately 1.9 times, facilitating high-resolution MRI. The unique features of Gal-Cy-Gd-1 enable real-time and precise visualization of ß-gal activity in live tumor cells and mice. The probe's utilization aids in identifying in situ ovarian tumors, offering valuable assistance in the precise removal of tumor tissue during surgical procedures in mice. The fusion of NIR fluorescence and MRI activation through self-immobilizing target enzymes or proteins provides a robust approach for visualizing ß-gal activity. Moreover, this approach sets the groundwork for developing other activatable bimodal probes, allowing real-time in vivo imaging of enzyme activity and localization.

Polymer Chainmail: Steric Hindrance and Charge Compensation of Anion-Doped PEDOT to Boost Stress Deformation of Compressible Supercapacitor.

Conducting polymers with high theoretical capacitance and deformability are among the optimal candidates for compressible supercapacitor electrode materials. However, achieving both mechanical and electrochemical stabilities in a single electrode remains a great challenge. To address this issue, the "Polymer Chainmail" is proposed with reversible deformation capability and enhances stability because of the steric hindrance and charge compensation effect of doped anions. As a proof of concept, four common anions are selected as dopants for Poly(3,4-ethylenedioxythiophene) (PEDOT), and their effects on the adsorption and diffusion of H+ on PEDOT are verified using density functional theory calculations. Owing to the film formation effect, the PF 6 - ${{\rm{PF}}_6^- }$ doped PEDOT/nitrogen-doped carbon foam exhibits good mechanical properties. Furthermore, the composite demonstrates excellent rate performance and stability due to suitable anion doping. This finding provides new insights into the preparation of electrochemically stable conductive polymer-based compressible electrode materials.

Electrochemical NO3- Reduction Catalyzed by Atomically Precise Ag30Pd4 Bimetallic Nanocluster: Synergistic Catalysis or Tandem Catalysis?

Electrochemically converting NO3- compounds into ammonia represents a sustainable route to remove industrial pollutants in wastewater and produce valuable chemicals. Bimetallic nanomaterials usually exhibit better catalytic performance than the monometallic counterparts, yet unveiling the reaction mechanism is extremely challenging. Herein, we report an atomically precise [Ag30Pd4 (C6H9)26](BPh4)2 (Ag30Pd4) nanocluster as a model catalyst toward the electrochemical NO3- reduction reaction (eNO3-RR) to elucidate the different role of the Ag and Pd site and unveil the comprehensive catalytic mechanism. Ag30Pd4 is the homoleptic alkynyl-protected superatom with 2 free electrons, and it has a Ag30Pd4 metal core where 4 Pd atoms are located at the subcenter of the metal core. Furthermore, Ag30Pd4 exhibits excellent performance toward eNO3-RR and robust stability for prolonged operation, and it can achieve the highest Faradaic efficiency of NH3 over 90%. In situ Fourier-transform infrared study revealed that a Ag site plays a more critical role in converting NO3- into NO2-, while the Pd site makes a major contribution to catalyze NO2- into NH3. The bimetallic nanocluster adopts a tandem catalytic mechanism rather than a synergistic catalytic effect in eNO3-RR. Such finding was further confirmed by density functional theory calculations, as they disclosed that Ag is the most preferable binding site for NO3-, which then binds a water molecule to release NO2-. Subsequently, NO2- can transfer to the vicinal exposed Pd site to promote NH3 formation.