Large-scale Applications Research Articles

Recycling Waste Agricultural Nets as Cement Composites

The advancement of agricultural mesh technology has contributed to its improved properties. As a result, agricultural nets are widely adopted in large-scale farming applications, for example, in cereal crop farming. However, a consequence of this increased use of agricultural nets is the accumulation of large amounts of waste. The current paper focuses on the recycling of agricultural nets used in wrapping straw bales to develop additives and fillers in cement composites. The research details an analysis of the use of waste agricultural meshes as an ingredient in cement composites. Six test series of different mixtures were conducted. In the first four series, agricultural waste was utilised as an additive in a composite comprising aggregate and cement slurry (the amounts of wasted nets were 20, 40, 60, and 80 kg/m3). In the last test series, the recyclate utilised comprised a mixture of cement slurry and waste only. The composites were subjected to standard tests and thermal resistance tests. The results showcased that that the addition of a net worsened the workability of the concrete mixture, and with increasing amounts of addition, the consistency of the mixture could change from liquid to dense plastic. The flexural strength of the composite decreased with increasing amounts of recyclate. In subsequent test series, the flexural strength value was lower than that of the control (3.93 MPa), from 7.38% (3.64 MPa) for the composite with 20 kg/m3 of recyclate to 37.66% (2.45 MPa) for the composite with of 80 kg/m3 recyclate. The flexural strength value of the net-filled composite without aggregate was very high (10.44 MPa), where the value obtained for the control composite was 62.36% lower. The results of the compressive strength test showed a decrease in this parameter with increasing amounts of additive. The value assessed for the control composite was 27.99 MPa. As expected, the composite that had no aggregate and consisted of only recycled filler had the lowest compressive strength. The value of this parameter was 13.07 MPa, and it was 53.31% lower than that of the control composite. The results of the tests of resistance to temperatures were similar to those recorded for the composites with polypropylene fibres. All composites demonstrated a significant decrease in their compressive and flexural strength after annealing. SEM imaging showed that the net fibres were closely bonded to the cement stone. Finally, it was concluded that recyclates performed best as fillers in lightweight composites with a low density, low absorption, high flexural strength, and satisfactory compressive strength.

Towards More Sustainable Aqueous Zinc-Ion Batteries.

Aqueous zinc-ion batteries (AZIBs) are considered as the promising candidates for large-scale energy storage because of their high safety, low cost and environmental benignity. The large-scale applications of AZIBs will inevitably result in a large amount of spent AZIBs, which not only induce the waste of resources, but also pose environmental risks. Therefore, sustainable AZIBs have to be considered to minimize the risk of environmental pollution and maximize the utilization of spent compounds. Herein, this minireview focuses on the sustainability of AZIBs from material design and recycling techniques. The structure and degradation mechanism of AZIBs are discussed to guide the recycling design of the materials. Subsequently, the sustainability of component materials in AZIBs is further analysed to pre-evaluate their recycling behaviors and mentor the selection of more sustainable component materials, including active materials in cathodes, Zn anodes, and aqueous electrolytes, respectively. According to the features of component materials, corresponding green and economic approaches are further proposed to realize the recycling of active materials in cathodes, Zn anodes and electrolytes, respectively. These advanced technologies endow the recycling of component materials with high efficiency and a closed-loop control, ensuring that AZIBs will be the promising candidates of sustainable energy storage devices. This review will offer insight into potential future directions in the design of sustainable AZIBs.

Digital Cellulose: Recent Advances in Electroactive Paper

With the increasing global demand for net-zero carbon emissions, actions to address climate change have gained momentum among policymakers and the public. The urgent need for a sustainable economy is underscored by the mounting waste crisis in landfills and oceans. However, the proliferation of distributed electronic devices poses a significant challenge due to the resulting electronic waste. To combat this issue, the development of sustainable and environmentally friendly materials for these devices is imperative. Cellulose, an abundant and CO2-neutral substance with a long history of diverse applications, holds great potential. By integrating electrically interactive components with cellulosic materials, innovative biobased composites have been created, enabling the fabrication of bulk electroactive paper and the establishment of new, potentially more sustainable manufacturing processes for electronic devices. This review explores recent advances in bulk electroactive paper, including the fundamental interactions between its constituents, manufacturing techniques, and large-scale applications in the field of electronics. Furthermore, it addresses the importance and challenges of scaling up production of electroactive paper, highlighting the need for further research and development.

Research Progress and Application Prospects of Solid-State Hydrogen Storage Technology

Solid-state hydrogen storage technology has emerged as a disruptive solution to the “last mile” challenge in large-scale hydrogen energy applications, garnering significant global research attention. This paper systematically reviews the Chinese research progress in solid-state hydrogen storage material systems, thermodynamic mechanisms, and system integration. It also quantitatively assesses the market potential of solid-state hydrogen storage across four major application scenarios: on-board hydrogen storage, hydrogen refueling stations, backup power supplies, and power grid peak shaving. Furthermore, it analyzes the bottlenecks and challenges in industrialization related to key materials, testing standards, and innovation platforms. While acknowledging that the cost and performance of solid-state hydrogen storage are not yet fully competitive, the paper highlights its unique advantages of high safety, energy density, and potentially lower costs, showing promise in new energy vehicles and distributed energy fields. Breakthroughs in new hydrogen storage materials like magnesium-based and vanadium-based materials, coupled with improved standards, specifications, and innovation mechanisms, are expected to propel solid-state hydrogen storage into a mainstream technology within 10–15 years, with a market scale exceeding USD 14.3 billion. To accelerate the leapfrog development of China’s solid-state hydrogen storage industry, increased investment in basic research, focused efforts on key core technologies, and streamlining the industry chain from materials to systems are recommended. This includes addressing challenges in passenger vehicles, commercial vehicles, and hydrogen refueling stations, and building a collaborative innovation ecosystem involving government, industry, academia, research, finance, and intermediary entities to support the achievement of carbon peak and neutrality goals and foster a clean, low-carbon, safe, and efficient modern energy system.

Survey of automatic plankton image recognition: challenges, existing solutions and future perspectives

Planktonic organisms including phyto-, zoo-, and mixoplankton are key components of aquatic ecosystems and respond quickly to changes in the environment, therefore their monitoring is vital to follow and understand these changes. Advances in imaging technology have enabled novel possibilities to study plankton populations, but the manual classification of images is time consuming and expert-based, making such an approach unsuitable for large-scale application and urging for automatic solutions for the analysis, especially recognizing the plankton species from images. Despite the extensive research done on automatic plankton recognition, the latest cutting-edge methods have not been widely adopted for operational use. In this paper, a comprehensive survey on existing solutions for automatic plankton recognition is presented. First, we identify the most notable challenges that make the development of plankton recognition systems difficult and restrict the deployment of these systems for operational use. Then, we provide a detailed description of solutions found in plankton recognition literature. Finally, we propose a workflow to identify the specific challenges in new datasets and the recommended approaches to address them. Many important challenges remain unsolved including the following: (1) the domain shift between the datasets hindering the development of an imaging instrument independent plankton recognition system, (2) the difficulty to identify and process the images of previously unseen classes and non-plankton particles, and (3) the uncertainty in expert annotations that affects the training of the machine learning models. To build harmonized instrument and location agnostic methods for operational purposes these challenges should be addressed in future research.

An H2O2 Self-Charging Zinc Battery with Ultrafast Power Generation and Storage.

Self-charging power systems are considered as promising alternatives for off-grid energy devices to provide sustained electricity supply. However, the conventional self-charging systems are severely restricted by the energy availability and time-consuming charging process as well as insufficient capacity. Herein, we developed an ultrafast H2O2 self-charging aqueous Zn/NaFeFe(CN)6 battery, which simultaneously integrates the H2O2 power generation and energy storage into a battery configuration. In such battery, the chemical energy conversion of H2O2 can generate electrical energy to self-charge the battery to 1.7 V through the redox reaction between H2O2 and NaFeFe(CN)6 cathode. The thermodynamically and kinetically favorable redox reaction contributes to the ultrafast H2O2 self-charging rate and the extremely short self-charging time within 60 seconds. Moreover, the rapid H2O2 power generation can promptly compensate the energy consumption of battery to provide continuous electricity supply. Impressively, this self-charging battery shows excellent scalability of device architecture and can be designed to a H2O2 single-flow battery of 7.06 Ah to extend the long-term energy supply. This work not only provides a route to design self-charging batteries with fast charging rate and high capacity, but also pushes forward the development of self-charging power systems for advanced large-scale energy storage applications.

Numerical assessment and optimization of photovoltaic-based hydrogen-oxygen Co-production energy system: A machine learning and multi-objective strategy

Green hydrogen production technology based on photovoltaic (PV), battery energy storage system (BESS) and proton exchange membrane (PEM) water electrolysis plays a crucial part in the transition process of energy to zero carbon technology. But few studies have focused on achieving all-day continuous hydrogen production, which is the key to large-scale hydrogen utilization. In this study, we developed an off-grid PV-BESS-PEM system for hydrogen and oxygen production. Firstly, the PV, BESS and PEM water electrolysis components were modeled and model validation was performed. Secondly, an energy management strategy (EMS) is proposed to achieve the goal of continuous and stable hydrogen production. Then, a surrogate model between design variables and optimization objectives is established based on machine learning methods, and a multi-objective optimization algorithm is used to drive the optimization process. Finally, a case study of the PV-BESS-PEM system is presented based on solar irradiation data in Lhasa, where there is sufficient solar resources and oxygen demand. The results demonstrate that the EMS can satisfy the purpose of all-day continuous and stable hydrogen production. The number of cells in the electrolyzer and the water temperature have a significant effect on the hydrogen production and the electrolysis efficiency. And the optimal system has increased the hydrogen production by 16.80 % and the electrolysis efficiency of PEM by 12.08 %, respectively. Herein, the methodological framework is expected to provide theoretical guidance for large-scale water electrolysis hydrogen production applications based on solar energy.

An inelastic beam-like model for nonlinear dynamic analyses of multi-storey buildings

This paper presents an equivalent non-uniform inelastic beam-like model for the evaluation of the nonlinear behaviour of multi-storey buildings subjected to earthquake loadings. The proposed beam can be used to model buildings with non-uniform mass and stiffness distribution. The model is characterised by a number of degrees of freedom corresponding to the number of floors of the building and is conceived to predict its nonlinear dynamic response after a proper calibration based on the results of pushover analyses performed on a nonlinear FEM model. In spite of its simplicity, the proposed equivalent model provides, with a very low computational effort, an accurate representation of the nonlinear dynamic behaviour of the building comparable to that obtained through the more demanding nonlinear 3D FEM models. The effectiveness of the proposed simplified modelling approach is here validated by means of nonlinear dynamic analyses firstly performed on a benchmark known in the literature as SAC9 building, modelled as a plane steel frame structure and secondly on a three-dimensional reinforced concrete structure, designed according to old standard structural design rules. The very good agreement with the results obtained through accurate 3D FEM frame modelling, for different earthquake loadings, on the considered benchmarks provides a first validation of the proposed inelastic equivalent beam-like model and suggests its potential use for the seismic assessment of building structures. The low computational cost related to the beam-like model could be particularly advantageous for all the seismic vulnerability approaches requiring several nonlinear dynamic analyses, as those related to large scale applications, or those expressed in terms of probability of failure generally expressed in terms of fragility curves.

RupMC: a ray-unit parallel marching cubes algorithm on CPU/GPU heterogeneous architectures

ABSTRACT The marching cubes (MC) algorithm is widely used for extracting isosurfaces from volume data and 3D visualizations because of its effectiveness and robustness but require extensive memory and computing time for large-scale applications. Additionally, MC isosurfaces lack topologic information, making them difficult to use in some geologic applications. To overcome these limitations, this study proposes an enhanced MC using CPU/GPU heterogeneous architecture called the ray-unit parallel MC (rupMC) algorithm. First, ray units form the basic voxel to determine how the surface intersects to reduce repeated computations and enhance efficiency. Then, rupMC uses multiple computing processes and threads on a CPU/GPU heterogeneous architecture to process points concurrently. Finally, the unique surface intersection indices are preserved to compose the surface triangles, and the topological surface information is directly embedded in the triangle compositions. Experiments on five stratum datasets of varying sizes demonstrated that, rupMC achieved approximately dozens of times faster than other serial MC and 4 times faster than a parallel DMC. rupMC demonstrated high scalability and adaptability to various CPUs/GPUs and datasets of various sizes. rupMC has remarkable capabilities for efficiently and feasibly extracting precise surface intersections and triangles, making it well-suited for large-scale and high-density applications.

Mitigation of caffeine micropollutants in wastewater through Ag-doped ZnO photocatalyst: mechanism and environmental impacts.

Micropollutants, such as caffeine (M-CF), pose a significant threat to ecosystems and human health through water and food sources. The utilization of metal oxide-based photocatalysts has proven to be an effective treatment method for the removal of organic pollutants. This study explores the efficacy of Ag-doped ZnO (Ag/ZnO) for removing M-CF from wastewater. The characterization of Ag/ZnO underscores the crucial role of band gap energy in the photocatalytic degradation process. This parameter influences the separation of electrons and holes (e-/h+) and the generation of reactive radicals. Under solar light, Ag/ZnO demonstrated markedly superior photocatalytic activity, achieving an impressive degradation efficiency of approximately 93.4%, in stark contrast to the 53.2% occurred by ZnO. Moreover, Ag/ZnO exhibited a remarkable degradation efficiency of M-CF in wastewater, reaching 83.5%. A key advantage of Ag/ZnO lies in its potential for recovery and reuse in subsequent treatments, contributing to a reduction in operational costs for industrial wastewater treatment. Impressively, even after five cycles, Ag/ZnO maintained a noteworthy photodegradation rate of M-CF at 78.6%. These results strongly suggest that Ag/ZnO presents a promising solution for the removal of micropollutants in wastewater, with potential scalability for industrial and large-scale applications.

GHGDroid: Global heterogeneous graph-based android malware detection

As the most popular mobile platform, Android has become the major attack target of malware, and thus there is an urgent need to effectively thwart them. Recently, the graph-based technique has been a promising solution for malware detection, which highly depends on graph structures to capture behaviors separating the malware from the benign apps. However, existing graph-based malware detection approaches still suffer from high computation cost in constructing or updating a graph for APK under detection, high false negative and false positive. To cope with these issues, we propose a novel global heterogeneous graph-based Android malware detection approach, named GHGDroid. A global heterogeneous graph (GHG) with a good updatability is first built on large-scale Android applications to characterize complex relationships among APKs and sensitive APIs. And then, using the GHG, a multi-layer graph convolutional network based embedding method is proposed to learn APK embeddings for well capturing behaviors that can separate malware from benign. Finally, using APK embeddings as well their labels, a malware classifier is trained. Experiments on real-world Android applications show that GHGDroid achieves 99.17 % F1-score, which outperforms the state-of-the-art approaches. Moreover, GHGDroid spends about 8 s on detecting an APK, which shows that it has a good potential as a practical tool for the Android malware detection task.

Micromirror Array with Adjustable Reflection Characteristics Based on Different Microstructures and Its Application

The conventional reflective optical surface with adjustable reflection characteristics requires a complex external power source. The complicated structure and preparation process of the power system leads to the limited modulation of the reflective properties and difficulty of use in large-scale applications. Inspired by the biological compound eye, different microstructures are utilized to modulate the optical performance. Convex aspheric micromirror arrays (MMAs) can increase the luminance gain while expanding the field of view, with a luminance gain wide angle > 90° and a field-of-view wide angle close to 180°, which has the reflective characteristics of a large gain wide angle and a large field-of-view wide angle. Concave aspheric micromirror arrays can increase the luminance gain by a relatively large amount of up to 2.66, which has the reflective characteristics of high gain. Industrial-level production and practical applications in the projection display segment were carried out. The results confirmed that convex MMAs are able to realize luminance gain over a wide spectrum and a wide range of angles, and concave MMAs are able to substantially enhance luminance gain, which may provide new opportunities in developing advanced reflective optical surfaces.

Engineering of lithiophilic hosts for stable lithium metal anodes

Lithium (Li0) metal has been deemed the desired anode for the future of cutting-edge rechargeable Li batteries benefiting from its lowest reduction potential and ultrahigh theoretical specific capacity. Nevertheless, the large-scale applications of Li metal batteries are restricted by scattered Li dendrite formation and uncontrollable volume expansion. To address these issues, a currently prevalent measure is to use structured lithiophilic hosts for Li metal. The enhanced lithiophilicity of hosts is significant for regulating the Li nucleation barrier. By virtue of these lithiophilic measures, the Li nucleation sites will be well controlled and the Li plating layer will be more stable. Through this article, we classified various lithiophilic hosts and described their applications for Li metal batteries, including heteroatom-doping carbon, lithiophilic-material loading hosts and gradient skeletons. We discussed the inherent advantages and lithophilic mechanisms of these hosts on optimizing the lithophilic properties and analyzed various factors that induced the formation of dendrite Li. Moreover, the review outlines the current challenges and perspectives for Li metal anodes, and some understanding of the lithiophilic chemistry is given.

Emerging application of 2D materials for dendrite-free metal batteries

Metal batteries using lithium, sodium, potassium, zinc, etc., as anodes have garnered tremendous attention in rechargeable batteries because of their highly desirable theoretical energy densities. However, large-scale application of these metal batteries is impeded by dendrite growth on the anode surface, which may penetrate the separator, leading to battery failure. Two dimensional (2D) materials featured by excellent mechanical strength and flexibility, tunable electronic properties and controllable assembly are promising materials for the construction of dendrite-free metal batteries. In this review, we summarize recent advancements of 2D materials for their potential use in critical components of dendrite-free batteries used as: (1) a host or artificial solid-electrolyte for metal anodes; (2) a solid electrolyte or modifier for electrolyte; and (3) an enhancement component for separators design. We conclude that 2D materials hold great promise for tackling the problems associated with dendrite formation by functioning as mechanical reinforcement and metal deposition regulators, along with improved safety, performance, and durability of batteries. Finally, this review discusses new perspectives and future directions in the field of 2D materials towards safe, high-energy metal batteries.

A comparison of the accumulation-based, trip-based and time delay macroscopic fundamental diagram models

Macroscopic fundamental diagram (MFD) is widely applied in network modelling and management, such as route guidance and vehicle relocation, which are formulated as generalised dynamic traffic assignment (DTA) problems. MFD can effectively reduce the spatial dimension thus making the generalised DTA problems computationally efficient. In the literature, three MFD models, the accumulation-based model, the trip-based model, and the time delay model, were proposed to capture the traffic flow propagation under different traffic conditions and demand scenarios. However, no consensus has been reached on their computational efficiency and which model should be chosen under certain traffic conditions and demand scenarios. In this paper, we revisit these models regarding two important theoretical properties regarding flow propagation in the DTA, i.e. the first-in-first-out (FIFO) principle and causality. Corresponding dynamic network loading algorithms are designed to compare their numerical accuracy and computational efficiency. Numerical comparisons with Lighthill-Whitham-Richards (LWR) model and a micro simulator confirm that the accumulation-based model is valid in saturation, the trip-based model is valid in free-flow, while the time delay model provides a good approximation in both free-flow and saturation scenarios. On the other hand, violation of strict causality is observed in the accumulation-based and trip-based models, rendering it hard to pursue analytical DTA. This issue is not observed in the time delay model. Overall, the time delay model is a promising alternative for dynamic network loading in large-scale network applications.

Time series analysis of L-band PALSAR-2 images in Istanbul and Kocaeli, Turkey

ABSTRACT Conducting long measurements of infrastructure deformation is a critical engineering task. Conventional methods are both time-consuming and expensive, limiting their use for large-scale applications. The synergy of synthetic aperture radar (SAR) and geographic information systems (GIS) offers a complementary approach. This study focuses on the feasibility of using time series analysis of L-band PALSAR-2 images to discover land displacements in Istanbul and Kocaeli, significant industrial and residential areas in Turkey. PALSAR-2 phase and intensity information were analyzed. For phase analysis, 14 L-band images from 2014 to 2021 were taken into account. Small baseline subset (SBAS) analysis was performed using 44 pairs, and results of the velocity, coherence and backscattering values are presented. Coherence of all pairs and their correlations were calculated. Principal Component Analysis (PCA) reduced the dimension of coherence pairs, enhancing feature extraction and the final geocoded velocity map revealed a fastest subsidence rate of −58 mm/yr and a mean subsidence of −20 mm/yr. These findings were confirmed through mean vertical velocity from Sentinel-1 datasets and field observations. The results showed that immature land subsidence in the mentioned areas are growing slowly, which can be taken as a serious risk in future.

Anti-Solvent-Free Fabrication of Stable FA0.9Cs0.1PbI3 Perovskite Solar Cells with Efficiency Exceeding 24.0% through a Naphthalene-Based Passivator.

The anti-solvent-free fabrication of high-efficiency perovskite solar cells (PSCs) holds immense significance for the transition from laboratory-scale to large-scale commercial applications. However, the device performance is severely hindered by the increased occurrence of surface defects resulting from the lack of control over nucleation and crystallization of perovskite using anti-solvent methods. In this study, 2-(naphthalen-2-yl)ethylamine hydriodide (NEAI) is employed as the surface passivator for perovskite films without using any anti-solvent. Naphthalene demonstrates strong π-π conjugation, which aids in the efficient extraction of charge carriers. Additionally, the naphthalene-ring moieties form a tight attachment to the perovskite surface. After NEAI treatment, FA and I vacancies are selectively occupied by NEA+ and I- in NEAI respectively, thus effectively passivating the surface defects and isolating the surface from moisture. Ultimately, the optimized NEAI-treated device achieves a promising power conversion efficiency (PCE) of 24.19% (with a certified efficiency of 23.94%), featuring a high fill factor of 83.53%. It stands out as one of the reported high PCEs achieved for PSCs using the spin-coating technique without the need for any anti-solvent so far. Furthermore, the NEAI-treated device can maintain ≈87% of its initial PCE after 2000h in ambient air with a relative humidity of 30%±5%.

The advances and opportunities of developing solid-state battery technology: Based on the patent Information Relation Matrix

There is a long way for solid-state batteries from the laboratory to large-scale application and commercialization. To overcome a series of challenges, researchers and innovators seek to further understand the processing-structure-properties relationships of solid-state batteries. However, less literature explores the advances and opportunities in solid-state battery technology based on patent analysis. The paper adopts the technology of Natural Language Processing (NLP) to analyze patent documents and reveal the advances and opportunities for developing solid-state battery technology by constructing the patent Information Relation Matrix (IRM). This paper finds innovation activities in developing solid-state batteries have been increasingly active in recent decades, but are uneven across organizations. The electrolyte is a priority area of technology development, and the advances in developing solid-state batteries are perfecting conductivity, reducing interfacial resistance, and improving density and stability. By contrast, the opportunities are to reduce cost, prevent short circuits, and prolong the life cycle. The paper perfects the extant method of constructing IRM and gives insight into the advances and opportunities for developing solid-state batteries. Our findings can help innovators better understand advances in solid-state batteries or opportunities for developing solid-state batteries, from a global perspective.

Ion-Exchange-Induced Phase Transition Enables an Intrinsically Air Stable Hydrogarnet Electrolyte for Solid-State Lithium Batteries.

Inferior air stability is a primary barrier for large-scale applications of garnet electrolytes in energy storage systems. Herein, a deeply hydrated hydrogarnet electrolyte generated by a simple ion-exchange-induced phase transition from conventional garnet, realizing a record-long air stability of more than two years when exposed to ambient air is proposed. Benefited from the elimination of air-sensitive lithium ions at 96h/48e sites and unobstructed lithium conduction path along tetragonal sites (12a) and vacancies (12b), the hydrogarnet electrolyte exhibits intrinsic air stability and comparable ion conductivity to that of traditional garnet. Moreover, the unique properties of hydrogarnet pave the way for a brand-new aqueous route to prepare lithium metal stable composite electrolyte on a large-scale, with high ionic conductivity (8.04×10-4Scm-1), wide electrochemical windows (4.95V), and a high lithium transference number (0.43). When applied in solid-state lithium batteries (SSLBs), the batteries present impressive capacity and cycle life (164mAhg-1 with capacity retention of 89.6% after 180 cycles at 1.0C under 50°C). This work not only designs a new sort of hydrogarnet electrolyte, which is stable to both air and lithium metal but also provides an eco-friendly and large-scale fabrication route for SSLBs.

Polyoxometallate Cluster Induced High-Entropy Oxide Sub-1 nm Nanosheets as Photoelectrocatalysts for Zn-Air Batteries.

The lack of highly efficient and inexpensive catalysts severely hinders the large-scale application of Zn-air batteries (ZABs). High-entropy oxides (HEOs) exhibit unique structures and attractive properties; thus, they are promising to be used in ZABs. However, conventional high-temperature synthesis methods tend to obtain microscale HEOs with a lower exposure rate of active sites. Here, we report a facile solvothermal strategy for preparing two-dimensional (2D) HEO sub-1 nm nanosheets (SNSs) induced by polyoxometalate (POM) clusters. Taking advantage of the special 2D sub-1 nm structure and precise element regulation, these 2D HEOs-POM SNSs exhibit enhanced bifunctional oxygen evolution and oxygen reduction reaction activity under light irradiation. Further applying these 2D HEOs-POM SNSs to ZABs as cathode catalysts, the CoFeNiMnCuZnOx-phosphomolybdic acid SNSs-based ZABs deliver a low charge/discharge voltage gap of 0.25 V at 2 mA cm-2 under light irradiation. Meanwhile, it could maintain an ultralong-term stability for 1600 h at 2 mA cm-2 and 930 h at 10 mA cm-2. The 2D sub-1 nm structure and fine element control in HEOs provide opportunities to solve the problems of low intrinsic activity, limited active sites, and instability of air cathodes in ZABs.