Panda-UV Unlocks Deeper Protein Characterization with Internal Fragments in Ultraviolet Photodissociation Mass Spectrometry.

Ultraviolet photodissociation (UVPD) mass spectrometry unlocks insights into the protein structure and sequence through fragmentation patterns. While N- and C-terminal fragments are traditionally relied upon, this work highlights the critical role of internal fragments in achieving near-complete sequencing of protein. Previous limitations of internal fragment utilization, owing to their abundance and potential for random matching, are addressed here with the development of Panda-UV, a novel software tool combining spectral calibration, and Pearson correlation coefficient scoring for confident fragment assignment. Panda-UV showcases its power through comprehensive benchmarks on three model proteins. The inclusion of internal fragments boosts identified fragment numbers by 26% and enhances average protein sequence coverage to a remarkable 93% for intact proteins, unlocking the hidden region of the largest protein carbonic anhydrase II in model proteins. Notably, an average of 65% of internal fragments can be identified in multiple replicates, demonstrating the high confidence of the fragments Panda-UV provided. Finally, the sequence coverages of mAb subunits can be increased up to 86% and the complementary determining regions (CDRs) are nearly completely sequenced in a single experiment. The source codes of Panda-UV are available at https://github.com/PHOENIXcenter/Panda-UV.

6-Plex mdSUGAR Isobaric-Labeling Guide Fingerprint Embedding for Glycomics Analysis.

Glycans are vital biomolecules with diverse functions in biological processes. Mass spectrometry (MS) has become the most widely employed technology for glycomics studies. However, in the traditional data-dependent acquisition mode, only a subset of the abundant ions during MS1 scans are isolated and fragmented in subsequent MS2 events, which reduces reproducibility and prevents the measurement of low-abundance glycan species. Here, we reported a new method termed 6-plex mdSUGAR isobaric-labeling guide fingerprint embedding (MAGNI), to achieve multiplexed, quantitative, and targeted glycan analysis. The glycan peak signature was embedded by a triplicate-labeling strategy with a 6-plex mdSUGAR tag, and using ultrahigh-resolution mass spectrometers, the low-abundance glycans that carry the mass fingerprints can be recognized on the MS1 spectra through an in-house developed software tool, MAGNIFinder. These embedded unique fingerprints can guide the selection and fragmentation of targeted precursor ions and further provide rich information on glycan structures. Quantitative analysis of two standard glycoproteins demonstrated the accuracy and precision of MAGNI. Using this approach, we identified 304 N-glycans in two ovarian cancer cell lines. Among them, 65 unique N-glycans were found differentially expressed, which indicates a distinct glycosylation pattern for each cell line. Remarkably, 31 N-glycans can be quantified in only 1 × 103 cells, demonstrating the high sensitivity of our method. Taken together, our MAGNI method offers a useful tool for low-abundance N-glycan characterization and is capable of determining small quantitative differences in N-glycan profiling. Therefore, it will be beneficial to the field of glycobiology and will expand our understanding of glycosylation.

Application of Marine Natural Products against Alzheimer's Disease: Past, Present and Future.

Alzheimer's disease (AD), a neurodegenerative disease, is one of the most intractable illnesses which affects the elderly. Clinically manifested as various impairments in memory, language, cognition, visuospatial skills, executive function, etc., the symptoms gradually aggravated over time. The drugs currently used clinically can slow down the deterioration of AD and relieve symptoms but cannot completely cure them. The drugs are mainly acetylcholinesterase inhibitors (AChEI) and non-competitive N-methyl-D-aspartate receptor (NDMAR) antagonists. The pathogenesis of AD is inconclusive, but it is often associated with the expression of beta-amyloid. Abnormal deposition of amyloid and hyperphosphorylation of tau protein in the brain have been key targets for past, current, and future drug development for the disease. At present, researchers are paying more and more attention to excavate natural compounds which can be effective against Alzheimer's disease and other neurodegenerative pathologies. Marine natural products have been demonstrated to be the most prospective candidates of these compounds, and some have presented significant neuroprotection functions. Consequently, we intend to describe the potential effect of bioactive compounds derived from marine organisms, including polysaccharides, carotenoids, polyphenols, sterols and alkaloids as drug candidates, to further discover novel and efficacious drug compounds which are effective against AD.

Application of Medical Image Navigation Technology in Minimally Invasive Puncture Robot.

Microneedle puncture is a standard minimally invasive treatment and surgical method, which is widely used in extracting blood, tissues, and their secretions for pathological examination, needle-puncture-directed drug therapy, local anaesthesia, microwave ablation needle therapy, radiotherapy, and other procedures. The use of robots for microneedle puncture has become a worldwide research hotspot, and medical imaging navigation technology plays an essential role in preoperative robotic puncture path planning, intraoperative assisted puncture, and surgical efficacy detection. This paper introduces medical imaging technology and minimally invasive puncture robots, reviews the current status of research on the application of medical imaging navigation technology in minimally invasive puncture robots, and points out its future development trends and challenges.

Passive Gate-Tunable Kinetic Photovoltage along Semiconductor-Water Interfaces.

Moving boundaries of electric double layer at solid-liquid interface enables unprecedented persistent energy conversion and provokes a kinetic photovoltaic effect by moving an illumination region along the semiconductor-water interface. Here, we report a transistor-inspired gate modulation of kinetic photovoltage by applying a bias at the semiconductor-water interface. The kinetic photovoltage of both p-type and n-type silicon samples can be facilely switched on/off, stemming from the electrical-field-modulated surface band bending. In contrast to the function of solid-state transistors relying on external sources, passive gate modulation of the kinetic photovoltage is achieved simply by introducing a counter electrode with materials of desired electrochemical potential. This architecture provides the ability to modulate the kinetic photovoltage over three orders of magnitude and opens up a new way for self-powered optoelectronic logic devices.

Carbon Black/PDMS Based Flexible Capacitive Tactile Sensor for Multi-Directional Force Sensing.

Flexible sensing tends to be widely exploited in the process of human-computer interactions of intelligent robots for its contact compliance and environmental adaptability. A novel flexible capacitive tactile sensor was proposed for multi-directional force sensing, which is based on carbon black/polydimethylsiloxane (PDMS) composite dielectric layer and upper and lower electrodes of carbon nanotubes/polydimethylsiloxane (CNTs/PDMS) composite layer. By changing the ratio of carbon black, the resolution of carbon black/PDMS composite layer increases at 4 wt%, and then decreases, which was explained according to the percolation theory of the conductive particles in the polymer matrix. Mathematical model of force and capacitance variance was established, which can be used to predict the value of the applied force. Then, the prototype with carbon black/PDMS composite dielectric layer was fabricated and characterized. SEM observation was conducted and a ratio was introduced in the composites material design. It was concluded that the resolution of carbon sensor can reach 0.1 N within 50 N in normal direction and 0.2 N in 0-10 N in tangential direction with good stability. Finally, the multi-directional force results were obtained. Compared with the individual directional force results, the output capacitance value of multi-directional force was lower, which indicated the amplitude decrease in capacity change in the normal and tangential direction. This might be caused by the deformation distribution in the normal and tangential direction under multi-directional force.

A Novel Wearable Soft Glove for Hand Rehabilitation and Assistive Grasping.

In order to assist patients with finger rehabilitation training and grasping objects, we propose a new type of soft rehabilitation gloves (SRGs), which has both flexion/extension and abduction/adduction movement function for every finger. This paper describes the structure design of the bending actuator and rotating actuator, the fabrication process of the soft actuator, and the implementation of the soft wearable gloves based on a fabric glove. FEM simulation analysis and experiments were conducted to characterize the mechanical behavior and performance of the soft glove in terms of the angle output and force output upon pressurization. To operate this soft wearable glove, we designed the hardware system for SRGs with a flexible strain sensor and force sensor in the loop and introduced a force/position hybrid PID control algorithm to regulate the pressure inputted. Experiment evaluation focused on rehabilitation training gestures; motions and the precise grasping assistance function were executed. The rotating actuator between each finger can supply abduction/adduction motion manner for patients, which will improve rehabilitation effect. The experimental results demonstrated that the developed SRGs have the potential to improve hand movement freedom and the range of grasping successfully.

Model Analysis and Experimental Investigation of Soft Pneumatic Manipulator for Fruit Grasping.

With the superior ductility and flexibility brought by compliant bodies, soft manipulators provide a nondestructive manner to grasp delicate objects, which has been developing gradually as a rising focus of soft robots. However, the unexpected phenomenon caused by environmental effects, leading to high internal nonlinearity and unpredictable deformation, makes it challenging to design, model, and control soft manipulators. In this paper, we designed a soft pneumatically actuated manipulator consisting of four soft actuators, as well as a flange, and investigated the influence of structural parameters on the output characteristics of the manipulator through finite element analysis (FEA). To enhance the bending deformation of the soft actuator, annular rings were employed on the soft actuator. A mathematical model for the bending deformation of air cavities was established to explore the relationship between the driving pressure and the bending angle based on the Yeoh strain energy function. Moreover, an end-output force model was established to depict the variation of the force output with the bending angle of the soft actuator, which was then experimentally validated by adopting the manufactured manipulator. The soft actuator studied in this paper can bend from 0° to 110° under an applied pressure of 0-60 kPa, and the maximum grasping load of the soft manipulator is 5.8 N. Finally, practical tests were conducted to assess the adaptability of the soft manipulator when grasping delicate fruits, such as apples, pears, tomatoes, and mangoes, demonstrating its broad application prospects in nondestructive fruit harvesting.

Cation-Deficiency-Dependent CO2 Electroreduction over Copper-Based Ruddlesden-Popper Perovskite Oxides.

We report an effective strategy to enhance CO2 electroreduction (CER) properties of Cu-based Ruddlesden-Popper (RP) perovskite oxides by engineering their A-site cation deficiencies. With La2-x CuO4-δ (L2-x C, x=0, 0.1, 0.2, and 0.3) as proof-of-concept catalysts, we demonstrate that their CER activity and selectivity (to C2+ or CH4 ) show either a volcano-type or an inverted volcano-type dependence on the x values, with the extreme point at x=0.1. Among them, at -1.4 V, the L1.9 C delivers the optimal activity (51.3 mA cm-2 ) and selectivity (41.5 %) for C2+ , comparable to or better than those of most reported Cu-based oxides, while the L1.7 C exhibits the best activity (25.1 mA cm-2 ) and selectivity (22.1 %) for CH4 . Such optimized CER properties could be ascribed to the favorable merits brought by the cation-deficiency-induced oxygen vacancies and/or CuO/RP hybrids, including the facilitated adsorption/activation of key reaction species and thus the manipulated reaction pathways.

Research on Classification Model of Panax notoginseng Taproots Based on Machine Vision Feature Fusion.

The existing classification methods for Panax notoginseng taproots suffer from low accuracy, low efficiency, and poor stability. In this study, a classification model based on image feature fusion is established for Panax notoginseng taproots. The images of Panax notoginseng taproots collected in the experiment are preprocessed by Gaussian filtering, binarization, and morphological methods. Then, a total of 40 features are extracted, including size and shape features, HSV and RGB color features, and texture features. Through BP neural network, extreme learning machine (ELM), and support vector machine (SVM) models, the importance of color, texture, and fusion features for the classification of the main roots of Panax notoginseng is verified. Among the three models, the SVM model performs the best, achieving an accuracy of 92.037% on the prediction set. Next, iterative retaining information variables (IRIVs), variable iterative space shrinkage approach (VISSA), and stepwise regression analysis (SRA) are used to reduce the dimension of all the features. Finally, a traditional machine learning SVM model based on feature selection and a deep learning model based on semantic segmentation are established. With the model size of only 125 kb and the training time of 3.4 s, the IRIV-SVM model achieves an accuracy of 95.370% on the test set, so IRIV-SVM is selected as the main root classification model for Panax notoginseng. After being optimized by the gray wolf optimizer, the IRIV-GWO-SVM model achieves the highest classification accuracy of 98.704% on the test set. The study results of this paper provide a basis for developing online classification methods of Panax notoginseng with different grades in actual production.

Tuning Reconstruction Level of Precatalysts to Design Advanced Oxygen Evolution Electrocatalysts.

Surface reconstruction engineering is an effective strategy to promote the catalytic activities of electrocatalysts, especially for water oxidation. Taking advantage of the physicochemical properties of precatalysts by manipulating their structural self-reconstruction levels provide a promising methodology for achieving suitable catalysts. In this review, we focus on recent advances in research related to the rational control of the process and level of surface transformation ultimately to design advanced oxygen evolution electrocatalysts. We start by discussing the original contributions to surface changes during electrochemical reactions and related factors that can influence the electrocatalytic properties of materials. We then present an overview of current developments and a summary of recently proposed strategies to boost electrochemical performance outcomes by the controlling structural self-reconstruction process. By conveying these insights, processes, general trends, and challenges, this review will further our understanding of surface reconstruction processes and facilitate the development of high-performance electrocatalysts beyond water oxidation.

Sulfonated Sub-1-nm Metal-Organic Framework Channels with Ultrahigh Proton Selectivity.

Biological proton channels are sub-1-nm protein pores with ultrahigh proton (H+) selectivity over other ions. Inspired by biological proton channels, developing artificial proton channels with biological-level selectivity is of fundamental significance for separation science. Herein we report synthetic proton channels fabrication based on sulfonated metal-organic frameworks (MOFs), UiO-66-X, X = SAG, NH-SAG, (NH-SAG)2 (SAG: sulfonic acid groups), which have sub-1-nm windows and a high density of sulfonic acid groups mimicking natural proton channels. The ion conductance of UiO-66-X channels follows the sequence: H+ ≫ K+ > Na+> Li+, and the sulfonated UiO-66 derivative channels show proton selectivity much higher than that of the pristine UiO-66 channels. Particularly, the UiO-66-(NH-SAG)2 channels exhibit ultrahigh proton selectivities, H+/Li+ up to ∼100, H+/Na+ of ∼80, and H+/K+ of ∼70, which are ∼3 times of that of UiO-66-NH-SAG channels, and ∼15 times of that of UiO-66@SAG channels. The ultrahigh proton selectivity in the sulfonated sub-1-nm MOF channels is mainly attributed to the narrow window-cavity pore structure functionalized with nanoconfined high-density sulfonic acid groups that facilitate fast proton transport and simultaneously exclude other cations. Our work opens an avenue to develop functional MOF channels for selective ion conduction and efficient ion separation.

Efficient Water Splitting Actualized through an Electrochemistry-Induced Hetero-Structured Antiperovskite/(Oxy)Hydroxide Hybrid.

Exploring active, stable, and low-cost bifunctional electrocatalysts for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) is crucial for water splitting technology associated with renewable energy storage in the form of hydrogen fuel. Here, a newly designed antiperovskite-based hybrid composed of a conductive InNNi3 core and amorphous InNi(oxy)hydroxide shell is first reported as promising OER/HER bifunctional electrocatalyst. Prepared by a facile electrochemical oxidation strategy, such unique hybrid (denoted as EO-InNNi3 ) exhibits excellent OER and HER activities in alkaline media, benefiting from the inherent high-efficiency HER catalytic nature of InNNi3 antiperovskite and the promoting role of OER-active InNi(oxy)hydroxide thin film, which is confirmed by theoretical simulations and in situ Raman studies. Moreover, an alkaline electrolyzer integrated EO-InNNi3 as both anode and cathode delivers a low voltage of 1.64 V at 10 mA cm-2 , while maintaining excellent durability. This work demonstrates the application of antiperovskite-based materials in the field of overall water splitting and inspires insights into the development of advanced catalysts for various energy applications.

Self-Assembled Ruddlesden-Popper/Perovskite Hybrid with Lattice-Oxygen Activation as a Superior Oxygen Evolution Electrocatalyst.

The oxygen evolution reaction (OER) is pivotal in multiple gas-involved energy conversion technologies, such as water splitting, rechargeable metal-air batteries, and CO2 /N2 electrolysis. Emerging anion-redox chemistry provides exciting opportunities for boosting catalytic activity, and thus mastering lattice-oxygen activation of metal oxides and identifying the origins are crucial for the development of advanced catalysts. Here, a strategy to activate surface lattice-oxygen sites for OER catalysis via constructing a Ruddlesden-Popper/perovskite hybrid, which is prepared by a facile one-pot self-assembly method, is developed. As a proof-of-concept, the unique hybrid catalyst (RP/P-LSCF) consists of a dominated Ruddlesden-Popper phase LaSr3 Co1.5 Fe1.5 O10-δ (RP-LSCF) and second perovskite phase La0.25 Sr0.75 Co0.5 Fe0.5 O3-δ (P-LSCF), displaying exceptional OER activity. The RP/P-LSCF achieves 10 mA cm-2 at a low overpotential of only 324 mV in 0.1 m KOH, surpassing the benchmark RuO2 and various state-of-the-art metal oxides ever reported for OER, while showing significantly higher activity and stability than single RP-LSCF oxide. The high catalytic performance for RP/P-LSCF is attributed to the strong metal-oxygen covalency and high oxygen-ion diffusion rate resulting from the phase mixture, which likely triggers the surface lattice-oxygen activation to participate in OER. The success of Ruddlesden-Popper/perovskite hybrid construction creates a new direction to design advanced catalysts for various energy applications.

Super-Exchange Interaction Induced Overall Optimization in Ferromagnetic Perovskite Oxides Enables Ultrafast Water Oxidation.

Oxygen evolution reaction (OER) is crucial in many renewable electrochemical technologies including regenerative fuel cells, rechargeable metal-air batteries, and water splitting. It is found that abundant active sites with favorable electronic structure and high electrical conductivity play a dominant role in achieving high electrocatalytic efficiency of perovskites, thus efficient strategies need to be designed to generate multiple beneficial factors for OER. Here, highlighted is an unusual super-exchange effect in ferromagnetic perovskite oxide to optimize active sites and enhance electrical conductivity. A systematic exploration about the composition-dependent OER activity in SrCo1 x Rux O3- δ (denoted as SCRx) (x = 0.0-1.0) perovskite is displayed with special attention on the role of super-exchange interaction between high spin (HS) Co3+ and Ru5+ ions. Induced by the unique Co3+ -O-Ru5+ super-exchange interactions, the SCR0.1 is endowed with abundant OER active species including Co3+ /Co4+ , Ru5+ , and O2 2- /O- , high electrical conductivity, and metal-oxygen covalency. Benefiting from these advantageous factors for OER electrocatalysis, the optimized SCR0.1 catalyst exhibits a remarkable activity with a low overpotential of 360 mV at 10 mA cm-2 , which exceeds the benchmark RuO2 and most well-known perovskite oxides reported so far, while maintaining excellent durability. This work provides a new pathway in developing perovskite catalysts for efficient catalysis.

New Phosphorus-Doped Perovskite Oxide as an Oxygen Reduction Reaction Electrocatalyst in an Alkaline Solution.

Because of their structural and compositional flexibility, perovskite oxides represent an attractive alternative electrocatalyst class to precious metals for the oxygen reduction reaction (ORR); an important reaction in fuel cells and metal-air batteries. Partial replacement of the original metal cation with another cation, namely, doping, can be used to tailor the ORR activity of perovskite, for which a metal has been exclusively used as the dopant component in the past. Herein, phosphorus is proposed as a non-metal dopant for the cation site to develop a new perovskite family with the formula of La0.8 Sr0.2 Mn1-x Px O3-δ (x=0, 0.02, 0.05, and 0.1; denoted as LSM, LSMP0.02, LSMP0.05, and LSMP0.1, respectively). Powder XRD patterns reveal that the solubility of phosphorus in the perovskite structure is around 0.05. Rotating ring-disk electrode experiments in the form of linear-sweep voltammetry scans demonstrated the best ORR performance for LSMP0.05, and also revealed close to a four-electron ORR pathway for all four compositions. A chronoamperometric test (9000 s) and 500 cycle accelerated durability test demonstrated higher durability for LSMP0.05 relative to that of LSM and the commercial 20 wt % Pt/C catalyst. The higher ORR activity for LSMP0.05 is attributed to the optimised average valence of Mn, as evidenced by combined X-ray photoelectron spectroscopy and soft X-ray absorption spectroscopy data. Doping phosphorus into perovskites is an effective way to develop high-performance electrocatalysts for ORR.

Perovskite/Carbon Composites: Applications in Oxygen Electrocatalysis.

Oxygen electrocatalysis, i.e., oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), plays an extremely important role in oxygen-based renewable-energy technologies such as rechargeable metal-air batteries, regenerative fuel cells and water splitting. Perovskite oxides have recently attracted increasing interest and hold great promise as efficient ORR and OER catalysts to replace noble-metal-based catalysts, owing to their high intrinsic catalytic activity, abundant variety, low cost, and rich resources. The introduction of perovskite-carbon interfaces by forming perovskite/carbon composites may bring a synergistic effect between the two phases, thus benefiting the oxygen electrocatalysis. This review provides a comprehensive overview of recent advances in perovskite/carbon composites for oxygen electrocatalysis in alkaline media, aiming to provide insights into the key parameters that influence the ORR/OER performance of the composites, including the physical/chemical properties and morphologies of the perovskites, the multiple roles of carbon, the synthetic method and the synergistic effect. A special emphasis is placed on the origin of the synergistic effect associated with the interfacial interaction between the perovskite and the carbon phases for enhanced ORR/OER performance. Finally, the existing challenges and the future directions for the synthesis and development of more efficient oxygen catalysts based on perovskite/carbon composites are proposed.

B-Site Cation Ordered Double Perovskites as Efficient and Stable Electrocatalysts for Oxygen Evolution Reaction.

Simple disordered perovskite oxides have been intensively exploited as promising electrocatalysts for the oxygen evolution reaction (OER) towards their application in water splitting, reversible fuel cells, and rechargeable metal-air batteries. Here, the B-site cation-ordered double perovskites Ba2 Bix Sc0.2 Co1.8-x O6-δ , with two types of cobalt local environments, are demonstrated to be superior electrocatalysts for OER in alkaline solution, demonstrating ultrahigh catalytic activity. In addition, no obvious performance degradation is observed for the Ba2 Bi0.1 Sc0.2 Co1.7 O6-δ sample after a continuous chronopotentiometry test. The critical role of the ordered [Co2+ ] and [Sc3+ , Bi5+ , Co3+ ] dual environments in improving OER activity is exhibited. These results indicate that B-site cation-ordered double perovskite oxides may represent a new class of promising electrocatalysts for the OER in sustainable energy storage and conversion systems.

Promotion of Oxygen Reduction by Exsolved Silver Nanoparticles on a Perovskite Scaffold for Low-Temperature Solid Oxide Fuel Cells.

Solid oxide fuel cells (SOFCs) have potential to be the cleanest and most efficient electrochemical energy conversion devices with excellent fuel flexibility. To make SOFC systems more durable and economically competitive, however, the operation temperature must be significantly reduced, which depends sensitively on the development of highly active electrocatalysts for oxygen reduction reaction (ORR) at low temperatures. Here we report a novel silver nanoparticle-decorated perovskite oxide, prepared via a facile exsolution process from a Sr0.95Ag0.05Nb0.1Co0.9O3-δ (SANC) perovskite precursor, as a highly active and robust ORR electrocatalyst for low-temperature SOFCs. The exsolved Sr0.95Ag0.05Nb0.1Co0.9O3-δ (denoted as e-SANC) electrode is very active for ORR, achieving a very low area specific resistance (∼0.214 Ω cm(2) at 500 °C). An anode-supported cell with the new heterostructured cathode demonstrates very high peak power density (1116 mW cm(-2) at 500 °C) and stable operation for 140 h at a current density of 625 mA cm(-2). The superior ORR activity and stability are attributed to the fast oxygen surface exchange kinetics and the firm adhesion of the Ag nanoparticles to the Sr0.95Nb0.1Co0.9O3-δ (SNC0.95) support. Moreover, the e-SANC cathode displays improved tolerance to CO2. These unique features make the new heterostructured material a highly promising cathode for low-temperature SOFCs.

Activity and Stability of Ruddlesden-Popper-Type La(n+1) Ni(n) O(3n+1) (n=1, 2, 3, and ∞) Electrocatalysts for Oxygen Reduction and Evolution Reactions in Alkaline Media.

Increasing energy demands have stimulated intense research activity on cleaner energy conversion such as regenerative fuel cells and reversible metal-air batteries. It is highly challenging but desirable to develop low-cost bifunctional catalysts for both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER), the lack of which is currently one of the major limiting components towards commercialization of these technologies. Here, we have conducted a systematic study on the OER and ORR performances of the Ruddlesden-Popper family of La(n+1)Ni(n) O(3n+1) (n=1, 2, 3, and ∞) in an alkaline medium for the first time. It is apparent that the Ni-O bond lengths and the hyperstoichiometric oxides in the rock-salt layers correlate with the ORR activities, whereas the OER activities appear to be influenced by the OH(-) content on the surface of the compounds. In our case, the electronic configuration fails to predict the electrocatalytic activity of these compounds. This work provides guidelines to develop new electrocatalysts with improved performances.