Scalable Method Research Articles

High-quality VO2 thin films sputter-deposited on borosilicate glass substrates for modulating solar transmission and thermal emission

M1-phase VO2 exhibits a reversible phase transition between the insulating and metallic states at T = ∼341 K, and VO2-based smart windows have been extensively studied. The smart window application requires the growth of high-quality VO2 films with a large resistivity change and small hysteresis width (ΔT) on glass substrates using a scalable deposition method such as sputtering. However, the polymorphic nature of VO2 makes it challenging to obtain high-quality VO2 films on ordinary window glasses (borosilicate and soda-lime glasses). Thus far, VO2 films sputtered on glass substrates have exhibited resistivity changes of 1.5–2 orders of magnitude and ΔT = 3–19 °C. In this study, we show that high-quality VO2 films with a resistivity change of 2.5−3.0 orders of magnitude and ΔT = 2 °C can be grown on borosilicate glass substrates via radio-frequency sputtering followed by thermal annealing. The simultaneous achievement of such a large resistivity change and small hysteresis width is highly encouraging not only for smart windows but also for other applications. With respect to the modulation of solar transmission and thermal emission with temperature, the performance levels of the produced VO2 films were 70−75 % of those expected from pure M1-phase VO2 films.

Continuous flow synthesis of MOF UTSA-16(Zn), mixed-metal and magnetic composites for CO2 capture – toward scalable manufacture

UTSA-16(Zn) is a zinc and citrate-based metal-organic framework (MOF) which has shown highly promising performance for CO2 capture. However, the transition of this MOF to industrial application has been hindered as a scalable synthesis method has not yet been reported. Herein we report the first scalable continuous flow synthesis of UTSA-16(Zn), demonstrating a production rate of 173 g/h, which is a 77-fold increase compared to previously reported batch methods. Sustainability of the synthesis was maximised using low-cost non-toxic reagents and a low-energy flow reactor operating at atmospheric pressure. Chemical (reactant ratios, Zn/Mg mixed-metal) and process parameters (solvent ratio, flow rate, temperature) were optimised to continuously produce UTSA-16(Zn) which also demonstrated a high CO2 adsorption capacity up to 3.8 mmol/g and conversion yield of up to 66 %. Pristine MOFs are typically thermally insulating, thus thermal regeneration is challenging. To overcome this limitation, magnetic nanoparticles can be embedded within the MOF. This enables fast and energy efficient regeneration through magnetic induction heating. Here, citrate-coated Fe3O4 magnetic nanoparticles (MNP-CA) were successfully incorporated into the flow synthesis process of UTSA-16(Zn) to form UTSA-16(Zn)@MNP-CA magnetic framework composites (MFCs), representing the highest production rate reported of any MFC to date (152 g/h c.f. 13 g/h for MgFe2O4@UiO-66-NH2). UTSA-16(Zn)@MNP-CA MFCs demonstrate rapid heating under a magnetic field (26–150 °C in 60 s). The flow method developed herein is also widely applicable for scalable manufacture of other MOFs and MFCs, enabling their broader transition towards industrial applications.

The role of neuron-like cell lines and primary neuron cell models in unraveling the complexity of neurodegenerative diseases: a comprehensive review.

Neurodegenerative diseases (NDs) are characterized by the progressive loss of neurons. As to developing effective therapeutic interventions, it is crucial to understand the underlying mechanisms of NDs. Cellular models have become invaluable tools for studying the complex pathogenesis of NDs, offering insights into disease mechanisms, determining potential therapeutic targets, and aiding in drug discovery. This review provides a comprehensive overview of various cellular models used in ND research, focusing on Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. Cell lines, such as SH-SY5Y and PC12 cells, have emerged as valuable tools due to their ease of use, reproducibility, and scalability. Additionally, co-culture models, involving the growth of distinct cell types like neurons and astrocytes together, are highlighted for simulating brain interactions and microenvironment. While cell lines cannot fully replicate the complexity of the human brain, they provide a scalable method for examining important aspects of neurodegenerative diseases. Advancements in cell line technologies, including the incorporation of patient-specific genetic variants and improved co-culture models, hold promise for enhancing our understanding and expediting the development of effective treatments. Integrating multiple cellular models and advanced technologies offers the potential for significant progress in unraveling the intricacies of these debilitating diseases and improving patient outcomes.

Reaction kinetics of Ni-Fe oxygen carriers with high performance for chemical looping hydrogen production

The chemical looping hydrogen production (CLHP) process utilizing iron-based oxygen carriers holds promise for practical hydrogen generation applications. However, challenges persist in developing iron-based carriers that are easy to prepare and demonstrate effective reactivity. Our research focuses on evaluating the CLHP reaction performance using bimetallic Ni-Fe oxygen carrier particles, synthesized by a scalable mechanical mixing method. This study unravels the role of Ni in bimetallic Ni-Fe oxygen carriers and investigates the influence of varying nickel-doping ratios on enhancing the reduction reactivity of iron-based oxygen carriers. Compared to the undoped sample, the 20 wt% nickel-doped Fe2O3/Al2O3 (20NiFe) particles enabled a reduction in the reaction temperature by at least 50 K. With the dopant, the methane conversion rate at 923 K is 500% higher than that of carriers without the dopant. Heterogeneous kinetic analysis demonstrates that the global reduction reaction data for the Ni-Fe oxygen carriers fit with the nucleation-nuclei growth model. Through redox reactivity tests and reduction kinetic analysis, 20NiFe shows the lowest apparent activation energy at 53.93 kJ/mol. Furthermore, the kinetic study and quasi in-situ XRD analysis aid in proposing the evolution process of methane reduction reaction for nickel-doped iron-based oxygen carriers, clarifying the role of doping in improving chemical looping reactivity from a kinetic perspective. This work provides valuable guidance for the design and optimization of oxygen carriers, thus accelerating the readiness for industrial deployment of hydrogen production via chemical looping process.

Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics.

Transparent microelectrode arrays have proven useful in neural sensing, offering a clear interface for monitoring brain activity without compromising high spatial and temporal resolution. The current landscape of transparent electrode technology faces challenges in developing durable, highly transparent electrodes while maintaining low interface impedance and prioritizing scalable processing and fabrication methods. To address these limitations, we introduce artifact-resistant transparent MXene microelectrode arrays optimized for high spatiotemporal resolution recording of neural activity. With 60% transmittance at 550 nm, these arrays enable simultaneous imaging and electrophysiology for multimodal neural mapping. Electrochemical characterization shows low impedance of 563 ± 99 kΩ at 1 kHz and a charge storage capacity of 58 mC cm⁻² without chemical doping. In vivo experiments in rodent models demonstrate the transparent arrays' functionality and performance. In a rodent model of chemically-induced epileptiform activity, we tracked ictal wavefronts via calcium imaging while simultaneously recording seizure onset. In the rat barrel cortex, we recorded multi-unit activity across cortical depths, showing the feasibility of recording high-frequency electrophysiological activity. The transparency and optical absorption properties of Ti₃C₂Tx MXene microelectrodes enable high-quality recordings and simultaneous light-based stimulation and imaging without contamination from light-induced artifacts.

Systematic Study of Reaction Conditions for Size-Controlled Synthesis of Silica Nanoparticles.

This study presents a reproducible and scalable method for synthesizing silica nanoparticles (SNPs) with controlled sizes below 200 nm, achieved by systematically varying three key reaction parameters: ammonium hydroxide concentration, water concentration, and temperature. SNPs with high monodispersity and controlled dimensions were produced by optimizing these factors. The results indicated a direct correlation between ammonium hydroxide concentration and particle size, while higher temperatures resulted in smaller particles with increased polydispersity. Water concentration also influenced particle size, with a quadratic relationship observed. This method provides a robust approach for tailoring SNP sizes, with significant implications for biomedical applications, particularly in drug delivery and diagnostics. Using eco-friendly solvents such as ethanol further enhances the sustainability and cost-effectiveness of the process.

A Scalable Method to Fabricate 2D Hydrogel Substrates for Mechanobiology Studies with Independent Tuning of Adhesiveness and Stiffness.

Mechanical signals from the extracellular matrix are crucial in guiding cellular behavior. Two-dimensional hydrogel substrates for cell cultures serve as exceptional tools for mechanobiology studies because they mimic the biomechanical and adhesive characteristics of natural environments. However, the interdisciplinary knowledge required to synthetize and manipulate these biomaterials typically restricts their widespread use in biological laboratories, which may not have the material science expertise or specialized instrumentation. To address this, we propose a scalable method that requires minimal setup to produce 2D hydrogel substrates with independent modulation of the rigidity and adhesiveness within the range typical of natural tissues. In this method, norbornene-terminated 8-arm polyethylene glycol is stoichiometrically functionalized with RGD peptides and crosslinked with a di-cysteine terminated peptide via a thiol-ene click reaction. Since the synthesis process significantly influences the final properties of the hydrogels, we provide a detailed description of the chemical procedure to ensure reproducibility and high throughput results. We demonstrate examples of cell mechanosignaling by monitoring the activation state of the mechanoeffector proteins YAP/TAZ. This method effectively dissects the influence of biophysical and adhesive cues on cell behavior. We believe that our procedure will be easily adopted by other cell biology laboratories, improving its accessibility and practical application.

Nanosizing strategy to fabricate uniformly dispersed NiO/Ni/lignin porous carbon composites for high lithium storage

Nickel oxide is considered a promising anode material for lithium-ion batteries. Nevertheless, its performance is hindered by significant volume expansion and low electrical conductivity, particularly at larger particle sizes, which lead to a notable decrease in lithium storage capacity and rate performance. To address these challenges, we introduce a nanocomposite strategy to synthesise nickel oxide and lignin-derived porous carbon composites (LPC/Ni/NiO). Through in situ polymerization, lignin macromolecules form a uniform 3D network with nickel carbonate, which, during the subsequent carbonisation process, results in the formation of nickel oxide within a conductive carbon network. This approach reduces the nickel oxide to nanosize and enhances the composite's electrical conductivity, effectively integrating the buffering framework of porous carbon with the high storage capacity of nickel oxide. As a result, the LPC/Ni/NiO composite exhibited significantly improved lithium storage capacity. Notably, when employed as an anode material in lithium-ion half-cells, the optimized composite maintained an excellent specific capacity of 1065 mAh/g after 100 cycles at a current density of 0.2 A/g. It also shown exceptional rate performance, delivering a specific discharge capacity of 505 mAh/g at a current density of 2 A/g, with stable cycling performance. The electrochemical reaction process was further validated using in ex-situ EIS. This study offers valuable insights into scalable synthesis methods for oxide nanocomposites, highlighting their potential as promising anode materials for lithium-ion batteries.

Economic valuation of carbon sequestration in Quito’s Metropolitan Park using Sentinel-2 and neural networks

This study introduces an innovative method for assessing the economic value of carbon stored by the urban park forest in Quito, Ecuador. The method uses Sentinel-2 remote sensing data and advanced deep learning techniques. A large forest study area was chosen, and detailed field measurements were taken to gather biomass and carbon data. Sentinel-2 satellite images were processed to correct for radiation and atmospheric conditions, and vegetation indices such as NDVI and EVI were calculated. To model forest biomass, a convolutional neural network (CNN) was created and trained using Sentinel-2 spectral bands and vegetation indices. The model was validated with independent field data and demonstrated high accuracy in estimating biomass and carbon, as indicated by evaluation metrics like RMSE and R². The findings include detailed maps showing the spatial distribution of biomass and carbon in the study area, which can be a valuable tool for forest management and the implementation of policies for valuing stored carbon. This approach combines the high resolution of Sentinel-2 data with the predictive power of neural networks, providing a robust and scalable method for estimating carbon across large forest areas. The study's conclusions emphasize the feasibility and accuracy of this approach and its potential for application in various forestry and geographical contexts.

Application of scalable sensor-assisted multi-scale computational methods in the simulation of micro mechanical behavior of composite materials

Micro mechanics involves the examination of the mechanical behavior of heterogeneous materials, taking into account inhomogeneities such as voids, fractures, and inclusions, and building on mathematical models developed. Composites bring engineering design barriers despite their strengths. Composite manufacturing and processing need specialized equipment, strategies, and labor, ensuring they are challenging and expensive. Mechanical behavior deals with how a composite material performs if faced with mechanical effects and action. Scalable sensor-assisted multi-scale computational Methods (SS-MSCM) are used to investigate topics ranging from the molecular basis of soot production in combustion to how molecule-level flaws influence macroscopic mechanical qualities. Carbon fiber reinforced polymers (CFRP) are generated by mixing graphene fiber with a resin, like vinyl ester and epoxy, to render a composite material with superior performance to the component ingredients. Hence, SS-MSCM-CFRP has Improved mechanical qualities achieved by incorporating nano-reinforcements, including carbon nanofibers and graphene nanoplates, into the CFRP matrix: enhanced flexural and compressive strengths, energy absorption upon impact, toughness to fracture, and interlaminar bonding. Composite materials feature excellent mechanical qualities like high strength and stiffness, fatigue resistance, and durability. It is possible to insert scalable sensors throughout the manufacturing process, which enables real-time monitoring of structural health, strain, and other factors. Scalable sensor-assisted multi-scale computational methods offer enhanced accuracy, real-time monitoring, and cost-effectiveness by integrating sensor data with computational models, improving predictions and failure mechanism insights. However, they face limitations like sensor dependency, computational complexity, data integration challenges, and high implementation costs, leading to potential discrepancies between simulation and experimental results. Important qualities include corrosion resistance, thermal conductivity, and electrical conductivity. As the composite materials develop to satisfy the established mechanical stress and temperature conditions, they offer high durability and strength.

A novel ADN/TANPDO supramolecular crystal with anti-hygroscopicity and high energy: A promising strategy to construct advanced propellant materials

Herein, encapsulating NH4+ ions through molecular self-assembly method has been employed to reduce the strong hygroscopicity of ADN (ammonium dinitramide). A novel ADN/TANPDO (2,4,6-triamino-5-nitropyrimidine-1,3-dioxide) supramolecular crystal with a 3:2 ratio was obtained using a rapid, green, efficient, and scalable self-assembly method. Compared with pure ADN, ADN/TANPDO supramolecular crystal exhibits a significantly lower hygroscopicity rate of 2.76 % (25 °C and 75 % relative humidity) and a lower impact sensitivity of 15 J, as well as a markedly higher specific impulse of 236 s. Additionally, the propellant formulation based on ADN/TANPDO supramolecular crystal presents high predicted energy with decreased content of HCl gas, making it a promising candidate for a high-energy and low-characteristic signal propellant component. Furthermore, this work offers a promising strategy to construct supramolecular crystals for solving the strong hygroscopicity of ADN and simultaneously assemble oxidizers with high-energy materials together at the molecular scale to achieve advanced propellant materials in the future.

Boosting the potassium storage property of spongia-like copper phosphide anode via nano-in-micro construction

Metal phosphides (MPs) show great promise as anode material in potassium-ion batteries (PIBs) owing to their cost-effectiveness and high theoretical capacity. Despite that, MPs anode usually manifests inferior poor cyclability as a result of dramatic volume fluctuation during discharge–charge cycling. Herein, a scalable salt template-assisted spray-drying method is developed to fabricate the porous carbon microspheres wrapped CuP2 nanoparticles (p-CuP2/C) with a nano-in-micro structure. The combination of the CuP2 nanoparticles, large meso-porous carbon microspheres can simultaneously offer plenty of reactive sites, promote electrolyte penetration, and maintain structural integrity. Additionally, the proposed synthesis strategy is suit for the industrial manufacture. As an anode for PIBs, the p-CuP2/C anode presents a high reversible capacity (494 mAh/g at 0.05 A/g), excellent cycling stability (a capacity degradation rate of 0.04 % per cycle during 2000 cycles at 2 A/g), and superior rate capability (244 mAh/g at 2 A/g). More impressively, pairing with a potassium Prussian blue cathode, the potassium-ion coin cell shows an excellent cycling lifespan with 87.1 % capacity retention after 200 cycles at a current density of 0.1 A/g, the assembled pouch cell also maintains stable cycling at 0.3 A/g over 80 cycles. This research could offer a facile approach to develop other advanced anodes with industrial practicability for alkali ion batteries.

Governance in multi-system transitions: A new methodological approach for actor involvement in policy making processes

Multi-system interactions associated with the decarbonisation of energy and mobility systems represent a complex phenomenon in the acceleration phase of net-zero transitions. In this paper, we present a novel methodological approach to examine actor involvement in the governance of multi-system transitions, with a focus on the UK's net-zero energy-mobility transitions from 2008 to 2021. Utilising Named Entity Recognition (NER), a natural language processing technique, we systematically map actors and their interactions within policy consultations and how these have changed over time. Our analysis differentiates between single-system and multi-system policy making processes; identifies weak and strong links among actors as two types of multi-system interactions; categorises actors into business, policy, academia, and society groups; and examines the evolution of engagement across multiple governance levels. Our findings indicate an increasing trend of multi-system interactions, suggesting the UK's progression towards the acceleration phase of net-zero transitions. Our analysis further reveals the predominance of policy actors, particularly from the national level, in governing such multi-system transitions processes, followed by business actors. Despite some limitations, our approach offers a scalable method for analysing large volumes of text, providing valuable insights into the governance dynamics of multi-system transitions. We conclude with implications for policy making and offer suggestions for future research, emphasising the importance of understanding actor involvement and political contestations around net-zero trajectories for ensuring the achievement of sustainability goals.

Insights into solid-contact ion-selective electrodes based on laser-induced graphene: Key performance parameters for long-term and continuous measurements.

This work aims to serve as a comprehensive guide to properly characterize solid-contact ion-selective electrodes (SC-ISEs) for long-term use as they advance toward calibration-free sensors. The lack of well-defined SC-ISE performance criteria limits the ability to compare results and track progress in the field. Laser-induced graphene (LIG) is a rapid and scalable method that, by adjusting the CO2 laser parameters, can create LIG substrates with tunable surface properties, including wettability, surface chemistry, and morphology. Herein, we fabricate laser-induced graphene (LIG) solid-contact electrodes using different laser settings and subsequently convert them into ion-selective sensors using a potassium-selective membrane. We measure the aforementioned tunable surface properties and correlate them with resultant low-frequency capacitance and water layer formation in an effort to pinpoint their effects on the sensitivity (Nernstian response), reproducibility (E°' variation), and potential stability of the LIG-based SC-ISEs. More specifically, we demonstrate that the surface wettability of the LIG substrate, which can be tuned by controlling the lasing parameters, can be modified to exhibit hydrophobic (contact angle > 90°) and even highly hydrophobic surfaces (contact angle ≈ 130°) to help reduce sensor drift. Recommendations are also provided to ensure proper and robust characterization of SC-ISEs for long-term and continuous measurements. Ultimately, we believe that a comprehensive understanding of the correlation between LIG tunable surface properties and SC-ISE performance can be used to improve the electrochemical behavior and stability of SC-ISEs designed with a wide range of materials beyond LIG.

The Anatomy of Iconicity: Cumulative Structural Analogies Underlie Objective and Subjective Measures of Iconicity.

The vocabularies of natural languages harbour many instances of iconicity, where words show a perceived resemblance between aspects of form and meaning. An open challenge in this domain is how to reconcile different operationalizations of iconicity and link them to an empirically grounded theory. Here we combine three ways of looking at iconicity using a set of 239 iconic words from 5 spoken languages (Japanese, Korean, Semai, Siwu and Ewe). Data on guessing accuracy serves as a baseline measure of probable iconicity and provides variation that we seek to explain and predict using structure-mapping theory and iconicity ratings. We systematically trace a range of cross-linguistically attested form-meaning correspondences in the dataset, yielding a word-level measure of cumulative iconicity that we find to be highly predictive of guessing accuracy. In a rating study, we collect iconicity judgments for all words from 78 participants. The ratings are well-predicted by our measure of cumulative iconicity and also correlate strongly with guessing accuracy, showing that rating tasks offer a scalable method to measure iconicity. Triangulating the measures reveals how structure-mapping can help open the black box of experimental measures of iconicity. While none of the methods is perfect, taken together they provide a well-rounded way to approach the meaning and measurement of iconicity in natural language vocabulary.

Van der Waals Multilayered Films: Wafer‐Scale Synthesis and Applications in Electronics and Optoelectronics

Abstract2D materials possess significant potential across various applications, with physical and chemical properties that can be effectively modulated by their thickness, enabling tailored optimization for specific uses. For instance, 2D monolayers are ideal for transparent and flexible electronics, while 2D multilayers are more suitable for solar cells and high‐speed devices. Although scalable methods for synthesizing large‐area 2D materials and their applications have been developed, most research has focused on monolayers, with comparatively limited efforts directed toward multilayers. This review provides an overview of the emerging field of 2D multilayers, revisiting the analysis of layer‐dependent properties to determine the optimal material thickness for various applications. It introduces representative techniques for synthesizing 2D multilayer films and presents applications where multilayer structures demonstrate superior performance compared to monolayers, particularly in electronics and optoelectronics. The review advocates for the development of synthesis and integration methods for 2D multilayers, calling for a shift in research focus toward these materials to enhance their technological impact and unlock new industrial applications.

Preparation and motion-sensing properties of ion/electron mixed conductive hydrogels fabricated by carbon-coated sepiolite nanofibers

Hydrogels have experienced significant advancements owing to their versatile applications in biomedicine, wound care, food packaging, and smart devices. The pursuit of environmentally sustainable and scalable hydrogel production methods remains a primary research objective. This study introduces an innovative hydrogel fabrication technique involving the integration of surface-modified sepiolite nanofibers with polyacrylamide (PAM), resulting in the formation of sepiolite-based composite hydrogels (PASSC). These hydrogels exhibit both ionic and electronic conductivity, along with improved mechanical properties and rheological behavior. PASSC hydrogels demonstrate remarkable fatigue resistance, maintaining mechanical integrity over 10,000 stress cycles, thereby indicating their potential for long-term applications. Additionally, these hydrogels exhibit distinctive mixed conductivity, which enhances their strain sensitivity and efficacy in strain sensing. The ability of PASSC hydrogels to accurately detect a range of movements underscores their versatility and reliability in monitoring strain changes across diverse applications.

Ultrafast Synthesis of Transition Metal Phosphides in Air via Pulsed Laser Shock.

Transition metal phosphide nanoparticles (TMP NPs) represent a promising class of nanomaterials in the field of energy; however, a universal, time-saving, energy-efficient, and scalable synthesis method is currently lacking. Here, a facile synthesis approach is first introduced using a pulsed laser shock (PLS) process mediated by metal-organic frameworks, free of any inert gas protection, enabling the synthesis of diverse TMP NPs. Additionally, through thermodynamic calculations and experimental validation, the phase selection and competition behavior between phosphorus and oxygen have been elucidated, dictated by the redox potential and electronegativity. The resulting composites exhibit a balanced performance and extended durability. When employed as electrocatalysts for overall water splitting, the as-constructed electrolyzer achieves a low cell voltage of 1.54 V at a current density of 10 mA cm-2. This laser method for phosphide synthesis provides clear guidelines and holds potential for the preparation of nanomaterials applicable in catalysis, energy storage, biosensors, and other fields.

Continuous process design of the microwave chemical recycling of waste plastics using microwave-absorbing heating elements

Conventional pyrolysis methods to chemically recycle plastic waste require significant energy input owing to inefficient energy transfer from the heat sources to plastics and the generation of excess CO2. Accordingly, there is an urgent need to develop alternative methods for the chemical recycling of waste plastics to limit global warming. In this study, the use of microwaves (MWs) as an efficient energy source for pyrolysis and chemical recycling. However, because plastic is transparent to MW energy, a method that utilizes carbon materials as MW-absorbing heating elements (MWAHEs) was developed. This method directly converted high-density polyethylene (HDPE) into light chemicals in up to 94% yield with 45% ethylene selectivity. A two-stage pyrolysis system incorporating MWAHE-assisted MW pyrolysis was also developed to produce light chemicals in 95% yield with 49% ethylene selectivity. From a chemical engineering perspective, this two-step pyrolysis system is an efficient and feasible method for producing valuable light olefins. This study also demonstrates that MWAHE assisted MW pyrolysis is effective for the chemical recycling of plastic waste. This study offers potential solutions for the environmental problems posed by plastic waste by developing efficient and scalable methods for its chemical recycling.

Fast and scalable preparation of metal–organic coordination polymeric precursor for bifunctional electrocatalysts for high performance lithium–oxygen batteries

The Metal-organic coordination polymers (MOCPs) with structural and functional diversity are considered effective cathode materials for Lithium-oxygen batteries (LOBs). Conventional synthesis methods make it difficult to obtain large quantities of materials. Here, A highly active low-cost Co-decorated N-doped carbon oxygen cathode catalyst (Co–N–C) was synthesized using a fast and scalable method based on positive and negative charge coordination. Rapid synthesis of MOCPs depends on the addition of base sites. A theory of “Lewis’s base-assisted rapid synthesis” was proposed. Co-N-C as LOBs air cathode showed 150 cycles with 1000 mAh g-1 at 500 mA g-1. The fast and scalable synthesis method can provide a feasible strategy for large-scale production of oxygen electrocatalysts for LOBs.