Fast Transfer Research Articles

Neural network algorithm for precipitation estimation from atms radiometer data

The paper presents a neural network method for precipitation estimation using microwave measurements from ATMS radiometer on board Suomi NPP and NOAA-20/21 satellites. The algorithms based on two fully-connected neural networks, the first one is used to detect precipitation clouds and the other one is used to quantify precipitation rate. When training the neural networks, the reference source of information was an array of measurements simulated using the fast radiation transfer model RTTOV in the bands of ATMS instrument and the corresponding precipitation rates were taken from ECMWF ERA5 reanalysis data. Validation of the obtained precipitation estimates was carried out using the results of the MIRS and GPROF algorithms for satellite radiometer ATMS, as well as ground-based radar observations from NIMROD. The results of the validation showed a high accuracy level consistent with many others works in this research field. The validation was carried out for land and water surface separately. The comparison with MIRS algorithm showed the correlation coefficient was more 0.9, and the RMSE error was approximately 0.78 mm/h for water and 0.84 mm/h for land surface. The same metrics for GPROF algorithm showed the correlation coefficient was ~0.8, and the RMSE error was approximately 1.27 mm/h and 0.9 for water and land surface, respectively. When compared with ground-based NIMROD radar data, the correlation and the RMSE were 0.47 and 1.37 mm/h, respectively. The results of the validation confirm the performance of the presented neural network method for precipitation estimation. In addition, further minor refinement of the presented algorithm will make it possible to apply it to measurements of other microwave satellite instruments, including Russian ones, such as MTVZA-GY, installed on Meteor-M satellites.

Fast Seawater Desalination Integrated with Electrochemical CO2 Reduction.

Coupling desalination with electrocatalytic reactions is an emerging approach to simultaneously addressing freshwater scarcity and greenhouse gas emissions. However, the salt removal rate in such processes is slow, and the applicable water sources are often limited to those with high salt concentrations. Herein, we show high-performance electrocatalytic desalination by coupling with electrochemical CO2 reduction using a carbon catalyst. A ZIF-8-derived carbon catalyst embedded with Cu nanoparticles delivers a high Faradaic efficiency of 94.3% for CO production at 288 μmol cm-2 h-1. The efficient CO2 electroreduction generates high current densities, which drive fast salt ion transfer across ion exchange membranes. The integrated device enables one of the quickest salt removal rates of 1043.49 μg cm-2 min-1 among various desalination methods. Drinking water can be obtained with an ion removal rate of 99% when natural seawater is used as the water source.

Fast Seawater Desalination Integrated with Electrochemical CO2 Reduction

Coupling desalination with electrocatalytic reactions is an emerging approach to simultaneously addressing freshwater scarcity and greenhouse gas emissions. However, the salt removal rate in such processes is slow, and the applicable water sources are often limited to those with high salt concentrations. Herein, we show high‐performance electrocatalytic desalination by coupling with electrochemical CO2 reduction using a carbon catalyst. A ZIF‐8‐derived carbon catalyst embedded with Cu nanoparticles delivers a high Faradaic efficiency of 94.3% for CO production at 288 μmol cm‐2 h‐1. The efficient CO2 electroreduction generates high current densities, which drive fast salt ion transfer across ion exchange membranes. The integrated device enables one of the quickest salt removal rates of 1043.49 μg cm‐2 min‐1 among various desalination methods. Drinking water can be obtained with an ion removal rate of 99% when natural seawater is used as the water source.

A mixotrophic denitrification composite for treatment of nitrate-contaminated water: Performance, microbial community and functional genes

A mixotrophic denitrification composite was prepared with sulfur, pyrite, sawdust and calcium carbonate (SPSC) for the treatment of nitrate-contaminated wastewater. As a homogeneous integrated composite, fast mass transfer, convenient operation and transportation and easy attachment for microorganisms were obtained in the SPSC-based denitrification system. The long-term operation result showed that SPSC bioreactor exhibited strong resistance to the fluctuations of influent nitrate load, and 98.3% of the nitrate in the influent was reduced even under low hydraulic retention time (HRT). The SPSC system achieved an average nitrate removal rate of 4.59 mg-N/L/h, which was nearly triple the rate of sulfur autotrophic denitrification (SAD) system that utilized sulfur as its sole electron donor. The sulfate yield of the SPSC system (4.52mg SO42-/ mg NO3--N) was significantly lower than those of the SAD system (9.36mg SO42-/ mg NO3--N). Heterotrophic and autotrophic denitrifiers coexisted in the SPSC system, which was beneficial for the denitrification process. Metagenomic analysis indicated that the SPSC composite enriched the functional genes, which encoding key enzymes (nitrate reduction, sulfur oxidation and energy generation) involved in nitrogen, sulfur and carbon metabolism. Collectively, the SPSC composite synthesized in this study has provided a high efficiency, low-cost and promising technology for the treatment of nitrate-contaminated water.

Chiral electrolytes for rechargeable metal batteries

Charge transfer at the liquid (electrolyte)-solid (metal) interfaces is of fundamental importance to metal electrochemical deposition that further determines the reversibility and kinetics of energy-dense rechargeable metal batteries (RMBs). We demonstrate the fast charge transfer at the electrolyte-metal interfaces for lithium metal by designing and synthesizing electrolytes with chiral solvents: R (or S)-1,2-dimethoxypropane (R-DMP or S-DMP) and R (or S)-4-methyl-1,3-dioxolane (R-MDOL or S-MDOL). The chiral-induced spin selectivity is considered to produce spin-polarized metal surfaces, enabling the improvement in charge transfer rate and efficiency. The deposited Li metal in chiral electrolytes shows smooth and uniform morphologies, as well as high initial (>95%) and average (∼99.2%) Coulombic efficiency for Li metal stripping/plating process, thus prolonging the life-span of batteries using thin lithium anode (50 μm) to 400 cycles till 80% capacity retention. This work provides a distinct approach to regulate metal deposition beyond the limitation of ion de-solvation.

Absorption and diffusion process at the CO[formula omitted]-decane interface considering density fluctuations near the critical CO[formula omitted] point

The injection of CO2 into geological formations for storage and for efficiency enhancement of oil production is considered a promising technology. Fundamental is an understanding of the absorption and diffusion process at the CO2-decane interface and its pressure and temperature dependence when approaching the critical CO2 point (31 °C, 7.38 MPa).Based on a new conceptual model, which considers CO2 density fluctuations in the critical range, we were able to consistently explain the time dependence of the volume increase for the respective thermodynamic state. The experimental results confirm the new conceptual model that volume swelling in the non-critical pressure range (< 6 MPa) is a surface effect with limited penetration depth. In contrast, the volume increase in the critical pressure range (6 - 8 MPa) is caused by mixing of liquid CO2droplets and the oil phase, i.e. to a level increase of the liquid mixed phase. Our experimental contact angles confirm this. The measured minimum miscible pressures (MMP) are 5.6 and 6.5 MPa at 20 °C and 30 °C, respectively.The CO2 absorption process at the CO2-decane interface is studied independently with pressure decay experiments. Our model results show excellent agreement (relative error ≅ 1 %) with the experimental results for both the non-equilibrium and equilibrium model, and the early-time diffusion coefficient is 4.7±1.9×10−7m2/s, confirming a fast CO2 mass transfer process.

Studies of ZnO/NiO/MoO3 Ternary Nanocomposite as an Effective Visible Light Photocatalyst

In this work, following a facile coprecipitation technique, a novel ternary ZnO/NiO/MoO3 heterojunction photocatalysts was synthesized and characterized using SEM, TEM, UV-Vis DRS, XRD and FTIR analysis. Under visible light irradiation, the photodegradation of organic pollutants, such as methylene blue, was studied. Comparing the ternary nanocomposite to ZnO, NiO, MoO3 and binary ZnO/NiO, NiO/MoO3 nanocomposite, the former showed better photocatalytic performance. The energy band gap of ZnO/NiO/MoO3 nanocomposite was evaluated using Tauc plot from absorption spectra and resulted as 2.67 eV. The best photocatalytic activity for methylene blue (100%) was shown by ternary ZnO/NiO/MoO3 photocatalyst within 55 min. The development of the ZnO/NiO/MoO3 heterojunction photocatalyst, which is advantageous for effective fast transfer and separation of the photoexcited charge carriers, could be attributed to the better photocatalytic presentation.

One-Step Digital Light Processing 3D Printing of Robust, Conductive, Shape-Memory Hydrogel for Customizing High-Performance Soft Devices.

Mechanically robust and electrically conductive hydrogels hold significant promise for flexible device applications. However, conventional fabrication methods such as casting or injection molding meet challenges in delivering hydrogel objects with complex geometric structures and multicustomized functionalities. Herein, a 3D printable hydrogel with excellent mechanical properties and electrical conductivity is implemented via a facile one-step preparation strategy. With vat polymerization 3D printing technology, the hydrogel can be solidified based on a hybrid double-network mechanism involving in situ chemical and physical dual cross-linking. The hydrogel consists of two chemical networks including covalently cross-linked poly(acrylamide-co-acrylic acid) and chitosan, and zirconium ions are induced to form physically cross-linked metal-coordination bonds across both chemical networks. The 3D-printed hydrogel exhibits multiple excellent functionalities including enhanced mechanical properties (680% stretchability, 15.1 MJ/m3 toughness, and 7.30 MPa tensile strength), rapid printing speed (0.7-3 s/100 μm), high transparency (91%), favorable ionic conductivity (0.75 S/m), large strain gauge factor (≥7), and fast solvent transfer induced phase separation (in ∼3 s), which enable the development of high-performance flexible wearable sensors, shape memory actuators, and soft pneumatic robotics. The 3D printable multifunctional hydrogel provides a novel path for customizing next-generation intelligent soft devices.

Accelerated Transfer Learning for Cooperative Transportation Formation Change via SDPA-MAPPO (Scaled Dot Product Attention-Multi-Agent Proximal Policy Optimization)

A method for cooperative transportation, which required formation change in a traveling environment, is gaining interest. Deep reinforcement learning is used in formation changes for multi-robot cases. The MADDPG (Multi-Agent Deep Deterministic Policy Gradient) method is popularly used for recognized environments. On the other hand, re-learning may be required in unrecognized circumstances by using the MADDPG method. Although the development of MADDPG using model-based learning and imitation learning has been applied to reduce learning time, it is unclear how the learning results are transferred when the number of robots changes. For example, in the GASIL-MADDPG (Generative adversarial self-imitation learning and Multi-agent Deep Deterministic Policy Gradient) method, how the results of three robot training can be transferred to the four robots’ neural networks is uncertain. Nowadays, Scaled Dot Product Attention (SDPA) has attracted attention and is highly impactful for its speed and accuracy in natural language processing. When transfer learning is combined with fast computation, the efficiency of edge-level re-learning is improved. This paper proposes a formation change algorithm that allows easy and fast multi-robot knowledge transfer using SDPA combined with MAPPO (Multi-Agent Proximal Policy Optimization), compared to other methods. This algorithm applies SDPA to multi-robot formation learning and performs fast learning by transferring the acquired knowledge of formation changes to a certain number of robots. The proposed algorithm is verified by simulating the robot formation change and was able to achieve dramatic high-speed learning capabilities. The proposed SDPA-MAPPO (Scaled Dot Product Attention-Multi-Agent Proximal Policy Optimization) learned 20.83 times faster than the Deep Dyna-Q method. Furthermore, using transfer learning from a three-robot to five-robot case, the method shows that the learning time can be reduced by about 56.57 percent. A scenario of three-robot to five-robot is chosen based on the number of robots often used in cooperative robots.

Ligand‐Tuning Metallic Sites in Molecular Complexes for Efficient Water Oxidation

Metal‐organic hybrid catalysts with highly tunable single‐sites are promising for oxygen‐evolution reaction (OER), but molecular‐scale understanding of underlying reaction mechanisms still remain elusive on these bulk materials. Herein, we report a direct construction of heterogenized molecular complexes stabilized on carbon substrates via coordinating Fe‐Ni sites with four aromatic carboxylate ligands (FeNi‐Lx). The ligands‐tuning π‐π stacking interaction between aromatic carboxylate ligands and carbon supports promote the oxidative charge accumulation on Fe‐Ni sites via fast electron transferring, thus the optimized FeNi‐Lx rendering a mass activity of 6680 A gFe/Ni‐1 at 0.3 V overpotential. In situ characteristics and theoretical analysis demonstrate that the OH‐ nucleophilic attack on hypervalent iron sites induce the reconstruction of active Fe‐O‐Ni species, accompanying with fast valence increasing. Whereas, during OER, the unexpected valence reduction of Fe‐O‐Ni sites would be attributed to the oxygen‐generating from OOH* intermediates. These findings would establish an essential understanding of the origin of active centers in molecular complexes catalysts for oxygen‐evolution.

Ligand-Tuning Metallic Sites in Molecular Complexes for Efficient Water Oxidation.

Metal-organic hybrid catalysts with highly tunable single-sites are promising for oxygen-evolution reaction (OER), but molecular-scale understanding of underlying reaction mechanisms still remain elusive on these bulk materials. Herein, we report a direct construction of heterogenized molecular complexes stabilized on carbon substrates via coordinating Fe-Ni sites with four aromatic carboxylate ligands (FeNi-Lx). The ligands-tuning π-π stacking interaction between aromatic carboxylate ligands and carbon supports promote the oxidative charge accumulation on Fe-Ni sites via fast electron transferring, thus the optimized FeNi-Lx rendering a mass activity of 6680 A gFe/Ni-1 at 0.3 V overpotential. In situ characteristics and theoretical analysis demonstrate that the OH- nucleophilic attack on hypervalent iron sites induce the reconstruction of active Fe-O-Ni species, accompanying with fast valence increasing. Whereas, during OER, the unexpected valence reduction of Fe-O-Ni sites would be attributed to the oxygen-generating from OOH* intermediates. These findings would establish an essential understanding of the origin of active centers in molecular complexes catalysts for oxygen-evolution.

Revealing the Structural Architecture of Anions Confining Mo2CTx MXene Layers for Robust Li+ Storage.

Controllable cation preintercalation enables enhancing the electrochemical activity and kinetics of MXenes. However, the electrostatic repulsion between cations and electrolyte ions induces deteriorative electrolyte ion transport kinetics. Herein, by shifting perceptions from the cation to anion strategies, we successfully preintercalate Cl-, SO42-, and PO43- anions into Mo2CTx MXene via the utilization of diverse etching agents. Due to a smaller ionic radius and low charge, more Cl- ions can be intercalated into Mo2CTx MXene and induce higher dislocation density, larger interlayer spacing, and more negative Zeta potential value. Relying on in situ X-ray diffraction, we monitored the interlayer evolution. The lower lithium-ion concentration gradient in the Mo2CTx MXene delivers a lower concentration polarization, a fast charge and ion transfer kinetics, and an excellent lifespan, holding 540.49 mAh g-1 after 400 cycles at 200 mA g-1. The effect of anion preintercalation provides new insights into the function-oriented design of MXene materials.

Fast mass transfer processes of interfering trapped CO2-clusters at reservoir conditions: Experiment and theory

The gas-to-oil ratio (GOR) of a reservoir fluid plays a critical role in optimizing oil recovery and oil production strategies, improving oil recovery efficiency, and predicting reservoir behavior. Understanding the complicated kinetics of multicomponent mass transfer at the pore scale after gas injection into petroleum reservoirs is of great importance for estimating GOR and enhanced oil recovery (EOR). However, to date, there is a significant gap in the fundamental process understanding of the complex mass transfer process at reservoir conditions. Using micro-CT technology, we investigate the time dependence of CO2 mass transfer and cluster growth after high pressure CO2 injection into sedimented porous media (sintered 0.2 mm glass beads).Surprisingly, the CO2 partitioning equilibrium is already reached after 2 h. To the best of our knowledge, such a fast CO2 transport through water-saturated porous media, which cannot be explained by linear diffusion models (time scale 100 days for a diffusion length of 10 cm), has not been reported in the literature before. We proposed a conceptual model that assumes CO2 inflation of interfering gas clusters drives cascading CO2 transport. We verified this conceptual model through a time series of experiments at different initial gas saturation, analyzing in each case the spatial cluster distribution, cluster size distribution, and pore occupancy frequency.Whether CO2 inflation of the gas clusters occurs depends on the critical initial gas saturation, which is about 10%. Our main conclusion is that CO2 migration should be considered as gas phase diffusion cascading along a quasi-percolating cluster, since CO2 inflation leads to a high gas saturation of about 26%, which is close to the percolation threshold. Our experimental results support this physical hypothesis. We show for the first time that CO2 clusters can expand over large pore spaces and thus are close to the critical percolation threshold (mobility threshold). The cluster size distribution can be described by a power distribution with the critical exponent 2.19, i.e., it shows universal scaling.We model the interfering mass transfer processes of neighboring gas clusters with a multi-sphere model. Exploring different scenarios for the dissolution kinetics of an ensemble of interfering gas clusters allow a deeper understanding of the complicated mass transfer kinetics and agree well with experimental cluster analyses at specific times.

Enabling Interfacial Lattice Matching by Selective Epitaxial Growth of CuS Crystals on Bi2WO6 Nanosheets for Efficient CO2 Photoreduction into Solar Fuels

AbstractPhotocatalytic CO2 reduction serves as an important technology for value‐added solar fuel production, however, it is generally limited by interfacial charge transport. To address this limitation, a two‐dimensional/two‐dimensional (2D/2D) p‐n heterojunction CuS‐Bi2WO6 (CS‐BWO) with highly connected and matched interfacial lattices was designed in this work via a two‐step hydrothermal tandem synthesis strategy. The integration of CuS with BWO created a robust interface electric field and provided fast charge transfer channels due to the work function difference, as well as highly connected and matched interfacial lattices. The p‐n heterojunction combination promoted the electron transfer from the Cu to Bi sites, leading to the coordination of Bi sites with high electronic density and low oxidation state. The Bi sites in the BWO nanosheets facilitated the adsorption and activation of CO2, and the generation of high‐coverage key intermediate b‐CO32−, while CuS (CS) acted as a broad light‐harvesting material to provide abundant photoinduced electrons that were injected into the conduction band of BWO for CO2 photoreduction reaction. Remarkably, the p‐n heterojunction CS‐BWO exhibited average CO and CH4 yields of 33.9 and 16.4 μmol g−1 h−1, respectively, which were significantly higher than those of CS, BWO, and physical mixture CS‐BWO samples. This work provided an innovative design strategy for developing high‐activity heterojunction photocatalyst for converting CO2 into value‐added solar fuels.

Enabling Interfacial Lattice Matching by Selective Epitaxial Growth of CuS Crystals on Bi2WO6 Nanosheets for Efficient CO2 Photoreduction into Solar Fuels.

Photocatalytic CO2 reduction serves as an important technology for value-added solar fuel production, however, it is generally limited by interfacial charge transport. To address this limitation, a two-dimensional/two-dimensional (2D/2D) p-n heterojunction CuS-Bi2WO6 (CS-BWO) with highly connected and matched interfacial lattices was designed in this work via a two-step hydrothermal tandem synthesis strategy. The integration of CuS with BWO created a robust interface electric field and provided fast charge transfer channels due to the work function difference, as well as highly connected and matched interfacial lattices. The p-n heterojunction combination promoted the electron transfer from the Cu to Bi sites, leading to the coordination of Bi sites with high electronic density and low oxidation state. The Bi sites in the BWO nanosheets facilitated the adsorption and activation of CO2, and the generation of high-coverage key intermediate b-CO3 2-, while CuS (CS) acted as a broad light-harvesting material to provide abundant photoinduced electrons that were injected into the conduction band of BWO for CO2 photoreduction reaction. Remarkably, the p-n heterojunction CS-BWO exhibited average CO and CH4 yields of 33.9 and 16.4 μmol g-1 h-1, respectively, which were significantly higher than those of CS, BWO, and physical mixture CS-BWO samples. This work provided an innovative design strategy for developing high-activity heterojunction photocatalyst for converting CO2 into value-added solar fuels.

Hierarchical porous structured biomass based COFs for photocatalytic oxidative coupling of amines

Covalent Organic Frameworks (COFs) are widely used for photocatalysis but limited by the aggregation of the catalysts, which limited the mass transfer. Herein, corn stalk cores were used as the substrate, and two kinds of biomass based COFs with different electronic structures of thiophene (C@SCOF) and pyridine (C@NCOF) were in-situ fabricated uniformly on the surface of the substrate. In this way, COFs expose more active sites rather than embedding in the agglomerated structure. Biomass based COFs, especially C@SCOF, exhibit a hierarchical porous structure containing micropores and macropores, which offer fast mass transfer channels for the catalytic and adsorbed substrates. Therefore, the biomass based COFs utilized more efficiently to achieve higher photocatalytic performance. The C@SCOF with D-A structure displays stronger photoresponse and lower impedance, which promote the dissociation of a photogenerated exciton and carrier separation efficiency, resulting remarkable photocatalytic performance for oxidation of benzylamine coupling reaction. This work could guide the design and preparation of biomass-based hybrids with promising performance.

Subradiance and superradiant long-range excitation transport among quantum emitter ensembles in a waveguide

In contrast to free space, in waveguides the dispersive and dissipative dipole–dipole interactions among quantum emitters exhibit a periodic behavior over remarkably long distances. We propose a novel setup, to our knowledge, exploiting this long-range periodicity in order to create highly excited subradiant states and facilitate fast controlled collective energy transport among far-apart ensembles coupled to a waveguide. For sufficiently large ensembles, collective superradiant emission into the fiber modes dominates over its free space counterpart. We show that, for a large number of emitters, a fast transverse coherent pulse can create almost perfect subradiant states with up to 50% excitation. On the other hand, for a coherent excitation of one sub-ensemble above an overall excitation fraction of 50% we find a nearly lossless and fast energy transfer to the ground state sub-ensemble. This transport can be enhanced or suppressed by controlling the positions of the ensembles relative to each other, while it can also be realized with a random position distribution. In the optimally enhanced case this fast transfer appears as superradiant emission with subsequent superabsorption, yet, without a superradiant decay after the absorption. The highly excited subradiant states, as well as the superradiant excitation transfer, appear as suitable building blocks in applications such as active atomic clocks, quantum batteries, quantum information protocols, and quantum metrology procedures such as fiber-based Ramsey schemes.

Resonant Vibrational Enhancement of Downhill Energy Transfer in the C-Phycocyanin Chromophore Dimer.

Energy transfer between electronically coupled photosynthetic light-harvesting antenna pigments is frequently assisted by protein and chromophore nuclear motion. This energy transfer mechanism usually occurs in the weak or intermediate system-bath coupling regime. Redfield theory is frequently used to describe the energy transfer in this regime. Spectral densities describe vibronic coupling in visible transitions of the chromophores and govern energy transfer in the Redfield mechanism. In this work, we perform finely sampled broadband pump-probe spectroscopy on the phycobilisome antenna complex with sub-10-fs pump and probe pulses. The spectral density obtained by Fourier transforming the pump-probe time-domain signal is used to perform modified Redfield rate calculations to check for vibrational enhancement of energy transfer in a coupled chromophore dimer in the C-phycocyanin protein of the phycobilisome antenna. We find two low-frequency vibrations to be in near-resonance with the interexcitonic energy gap and a few-fold enhancement in the interexcitonic energy transfer rate due to these resonances at room temperature. Our observations and calculations explain the fast downhill energy transfer process in C-phycocyanin. We also observe high-frequency vibrations involving chromophore-protein residue interactions in the excited state of the phycocyanobilin chromophore. We suggest that these vibrations lock the chromophore nuclear configuration of the excited state and prevent the energetic relaxation that blocks energy transfer.

Rational design of MoS2/CNT heterostructure with rich S-vacancy for enhanced HER performance.

Molybdenum disulfide (MoS2) is a promising electrocatalyst for the hydrogen evolution reaction (HER) due to excellent stability and low cost. However, the utilization in electrocatalytic hydrogen evolution is constrained by inherent shortcomings, including fewer edge active sites, poor dispersion, and electrical conductivity. In this work, MoS2 was compounded with carbon nanotubes (CNTs), which are known for their high specific surface area and excellent electrical conductivity. These CNTs, laden with oxygen-containing functional groups, provided nucleation sites that facilitated the rapid assembly of MoS2 nanoflowers under hydrothermal conditions within 3h. Due to their diminutive size (∼300nm), these nanoflowers possess a large specific surface area and numerous active sites at their edges. Furthermore, MoS2 nanoflowers exhibited a high concentration of intrinsic S-vacancies. This heterojunction material exhibited superior HER properties. In addition, density functional theory simulation further confirmed that the MoS2 with S vacancy and CNT heterojunction electrocatalysts (VS-M/C) provided a fast charge transfer pathway for water electrolysis, and analysis showed that the conduction band minimum and valence band maximum were mainly contributed by the d orbits of Mo and the p orbits of C. This study proffered a novel approach for the engineering of high-performance MoS2-based HER electrocatalysts.

Structural Regulation of a Multi-Component Co2P2O7-MoN/NC Electrocatalyst for Efficient Oxygen Evolution Reaction.

Realizing efficient and durable non-precious metal-based electrocatalysts for oxygen evolution reaction (OER) still remains a great challenge. Here, a multi-component composite of Co2P2O7-MoN/NC containing pyrophosphate, nitride, and nitrogen-doped carbon is successfully prepared via a facile two-step synthesis method. Combining the structural regulation between the active metal- and non-metal-based species, Co2P2O7-MoN/NC demonstrates superior activity and durability for OER, requiring an overpotential of 278 mV at a current density of 10 mA cm-2, a Tafel slope of 83.3 mV dec-1, and long-term stability over 100 h in an alkaline solution. Post-characterizations reveal that synergistic effect among stable Co2P2O7, partially dissolved MoN, N-doped carbon, and new-formed CoOOH nanosheets enable structural reconstruction, fast charge transfer, and formation of oxygen-containing intermediates, promoting the OER performance significantly. This work provides a promising pathway to tune multi-components to fabricate efficient transition-metal-based electrocatalysts in energy conversion applications.