Hierarchical Hybrid Structure Research Articles

Carbon nanoarchitecture encapsulated highly dispersed ultrafine Ag particles composite anode for high-capacity desalination

The high capacity of silver (Ag) anodes positions them as a promising avenue for addressing pressing water purification challenges through capacitive deionization (CDI). However, it faces significant challenges such as severe volume expansion and particle crushing, leading to rapid electrochemical failure. Herein, hierarchical hybrid structures comprising highly dispersed ultrafine Ag anchored in carbon nanolayers were prepared using a temperature-mediated strategy. The coordination effect of organic precursors reduces the surface energy of Ag nanoparticles, effectively preventing aggregation during heat treatment. Carbon layer encapsulation synergized with particle size control effectively suppresses the absolute volumetric strain of the electrode in the electrochemical reaction, enhancing electrochemical stability. When used as a CDI anode, AgNC-500 demonstrated an excellent Cl- capturing capacity of 159.96 mg g-1 and a rate of 27.53 mg g−1 min−1. Furthermore, the capacity exhibited excellent stability with negligible degradation over 50 cycles. This study offers crucial insights for advancing the development of highly stable conversion electrodes.

Structural design and characterization of hybrid hierarchical lattice structures based on sheet-network Triply periodic Minimal surface topology

The ability to adjust topological features of lattice structures offers a great potential to finely calibrate their physical and mechanical response to precisely meet specific requirements. This study explores a new topological design that leverages the internal porosity of Triply Periodic Minimal Surfaces (TPMS) unit cells to optimize and control their mechanical properties. A smaller-scale TPMS lattice structure was integrated within the internal volume of the sheet-network Schwarz Primitive TPMS cell, culminating in a hybrid hierarchical architecture. Various TPMS topologies with distinct mechanical behavior and varying relative density combinations were examined. Experimental and numerical approaches were developed to reveal the structure’s deformation behaviour and quantify stiffness, anisotropy, quasi-static uniaxial compressive strength, and energy absorption capacity. The topological design of the internal lattice was found to play a key role in defining the mechanical performance of the integrated structures, leading to enhanced energy absorption up to 4 times that of the reference structure. Moreover, all the studied hierarchical topologies exhibited a lower Emax/Emin ratio in comparison to the reference topology, indicating more isotropic performance of the hybrid designs (upto 40% reduction of anisotropy). The findings underscore the significant promise of hybrid hierarchical design methodologies in attaining lattice structures with tailored properties.

A novel method for concurrent dynamic topology optimization of hierarchical hybrid structures

This paper proposes a feature-decoupled method for concurrent dynamic topology optimization of the Hierarchical Hybrid Structure (HHS) to minimize the steady-state dynamic response. First, a novel single-variable uniform multiphase material interpolation model is established based on the Gaussian function and normalization method, which achieves the decoupled description of the macroscopic topology, substructure topology, and the spatial distribution of the substructures for HHS. Second, by combining the extended multiscale finite element method (EMsFEM), which overcomes the limitations of the scale separation assumption and periodic boundary conditions in HHS response analysis, a concurrent dynamic topology optimization mathematical formulation for HHS is constructed. Finally, the sensitivity scheme is established based on the adjoint method, and the MMA algorithm was employed to update the model. Numerical examples verify the correctness and feasibility of the proposed method, demonstrate its advantages in solving HHS concurrent topology optimization problem compared to traditional methods, and explore the impact of the number of substructure types on the optimization results of HHS.

Biscrolled hierarchical hybrid structure of PEDOT:PSS/CNTs-NMP yarn based solid state linear supercapacitor for wearable e-textile

The environmental friendly flexible solid state linear supercapacitor (FSLSc) based on the hierarchical hybrid yarn with core-shell type structure of poly(3,4-ethylenedioxythiophene): polystyrenesulfonate (PEDOT:PSS) and hydrophilic carbon nanotubes (CNTs) sheet, fabricated using novel biscrolling technique is proposed. The hierarchical hybrid yarn structure of the electrode establishes the improved electrochemical interface of PEDOT:PSS with the both the hydrophilic CNTs and an aqueous PVA/H3PO4 gel electrolyte. The exterior surface of the yarn electrode rich in PEDOT:PSS which interact with ions from electrolyte and stores charges faradaically while the core region with dense CNTs yarn contributes with its multifunctional capabilities such as EDLC type capacitor, current collector and mechanical support. The observed two-fold decrease in ESR value (∼49Ω) and two-fold increase in capacitance (∼112.76 F/g) for hybrid yarn electrode with N-methyl-2-pyrrolidone (NMP) treated hydrophilic CNTs compared to the one with pristine CNTs, confirms the improved interface of PEDOT:PSS formed with hydrophilic CNTs and aqueous electrolyte. The FSLSc devices with NMP treated CNTs hybrid yarn electrodes exhibited excellent electrochemical performance in terms of the maximum power and energy density of 980 W/kg and 3.799 Wh/kg, respectively. The FSLSc displayed remarkable cycling performance upto 5000 cycles of charge-discharge and a robust bending stability after 1000 bending cycles, making it promising for practical application of the next-generation flexible solid state electrochemical energy storage in e-textiles.

Energy absorption characteristics of hybrid hierarchical chiral structures based on symmetrical design under in-plane impact

Drawing inspiration from hierarchical structures, axisymmetric design layouts were introduced, and hybrid hierarchical chiral structures (HHCS) based on four- and six-chiral structures were proposed. The performance of HHCSs under in-plane compression is investigated using finite element methods and experiments. The effect of different loading conditions on the behavior of HHCSs is discussed. Under low-speed impact, HHCSs exhibit a negative Poisson’s ratio (NPR) effect, which diminishes as the velocity increases and the inertial effects gradually become dominant. The parameter study shows that increasing the connectivity between subunits and the thickness can enhance the energy absorption capacity of the structure while maintaining a good NPR effect. The conventional inclined deformation mode of the chiral structure is improved by the axisymmetric layout, which effectively improves the energy absorption.

Proton-Conductive COF Evenly Embedded Cellulose Aerogels toward Water Harvesting and Spontaneous Sustained Power Generation from Ambient Moisture and Human Respiration.

Herein, we develop a new intelligent moisture-sensitive hybrid aerogel by evenly embedding a proton-conductive covalent organic framework (COF-2SO3H) into a carboxylated cellulose nanofiber network (CNF-C) for water harvesting and spontaneous sustained electricity production from ambient humidity and human respiration. Our strategy first exploits the "suspending agent" role of CNF-C to stably disperse COF materials in water for forming uniform hierarchical hybrid structures. By utilizing the synergy of COF-2SO3H and CNF-C together with their inherent structure merits and surface group effects, the hybrid aerogel displays increased water uptake and ion conductivity. Upon asymmetric moisturization, it can create a self-maintained moisture gradient to engender a concentration difference for mobile Na+ and H+, resulting in efficient charge separation and diffusion. Thus, the hybrid aerogel-based coin-type generator achieves a continuous output voltage of ∼0.55 V for at least 5 h in ambient environments in contrast to that using pure CNF-C and carbon-based generators with transient voltage response. Intriguingly, the wearable generator with an aerogel in a mask is more sensitive to human respiration and achieves repeatable and reliable self-charge for persistent electricity along with an increased output voltage of up to 1.0 V and much faster self-charge (only 3 min), both of which surpass most reported moisture-enabled generators.

NiCo-compounds inside and outside N-doped carbon nanotubes to construct a double-enhanced hierarchical structure for high energy density supercapacitors.

Attaining a high energy density that aligns with practical application requirements is a crucial indicator in the advancement of supercapacitors. In this paper, a hybrid hierarchical electrode structure of N-doped carbon nanotube (NCNT) spheres encapsulated with NiCo-Se nanoparticles (NPs) and coated with nickel-cobalt layered double hydroxide (NiCo-LDH) multilayer nanosheets was successfully synthesized on a nickel foam (NF) substrate. The self-supporting strategy enables nickel-cobalt Prussian blue analogues (Ni-Co PBAs) to be directly attached to the NF surface, which results in fluffy NCNTs with a high length-diameter ratio and considerable yield and greatly enhances the conductivity of the electrode material. The synergistic interaction between the dual transition metal compounds inside and outside the NCNTs enables the hybrid electrode material to achieve an impressive specific capacity of 1899 F g-1 (211.0 mA h g-1) at 1 A g-1. The asymmetric supercapacitor (ASC) exhibits an excellent energy density of 57.6 W h kg-1 at a power density of 798 W kg-1. This study not only provides an attractive strategy for obtaining CNTs with excellent properties from Ni-Co PBA and synthesizing hybrid electrodes with efficient synergistic effects, but also achieves a high energy density that aligns with the practical application demands of supercapacitors.

Revealing the potential of hierarchical heterostructure of tri-metallic selenide and MOFs etched layered hydroxide dodecahedron laminated with rGO-Ni foam for a hybrid supercapacitor applications

Inaugurating the multistage hierarchical hybrid structure with ample surface area and synergistic contribution from polymetallic selenide and layered hydroxide in a conductive 3D substrate has been supposed to be appealing and highly-rated electrode material to enhance the general electrochemical parameters of supercapacitors (SCs), thanks to exclusive structural features, immense electronic states and relatively paramount electrical conductivity of the final product. In this work, hydrothermal assisted zinc‑nickel‑cobalt-selenide (ZNC-Se) nanosheets have been uniformly prepared onto the conductive rGO decorated Ni foam substrate, chased by uniform decoration of metal organic frameworks (MOFs) templated nickel‑cobalt-layered double hydroxide (NC-LDH) onto tri-metallic (ZNC-Se) nanosheets to achieve the hierarchical hybrid structure of [email protected]@rGO-NF. The as-prepared hierarchical [email protected]@rGO-NF delivers remarkable specific capacity value along with outstanding cycle stability. The proposed [email protected]@rGO-NF and MOFs derived open and hollow carbon structure (MDOHCS)-based hybrid device disclosed remarkable cyclic life and an energy/power density of 80.3 W h kg−1/15970.9 W kg−1.

A physics-informed CNN-TSE hybrid network for micro-EDM process monitoring and control

Despite being a widespread non-conventional processing technique, electrical discharge machining (EDM) has been complicated due to its removal mechanisms and weak process stability for decades. Process monitoring is an enabling technology to offer an indirect insight into the discharge phenomena, understanding the probabilistic anomaly events such as arcs and short circuits. However, the transient high-frequency pulse train poses a great challenge for statistical monitoring and control. Traditional approaches are limited to single pulse analysis, which hinders a deep understanding of the process. To address the challenge, this paper proposes a novel physics-informed deep learning architecture for real-time micro-EDM process monitoring. To prepare condition labels, a series of signal-processing techniques including sensory fusion, pulse-shape filtering and pulse segmentation are employed, followed by observation diagrams on two critical indicators, i.e. discharge energy and discharge time interval. A decision logic that allows embedding of domain knowledge is formulated, yielding physics-informed labels on each pulse train. For online monitoring applications, a hybrid hierarchical structure that combines a 1D convolutional neural network (1D-CNN) and a Transformer encoder (TSE) is designed to simultaneously extract local pulse features and temporal dependencies between pulse sequences. This deep learning model achieves a classification accuracy of 96% on the validation dataset and reaches precision and recall scores of more than 92% on the test dataset with varying processing parameters. Two model interpretation approaches, i.e. gradient-weighted class activation mapping (Grad-CAM) and attention visualization, are adopted. Consequently, it is found that the CNN module assigns high feature importance to the breakdown and maintaining stages of one pulse and the TSE module improves the feature salience and reliance on the condition of distinct events. This monitoring network is further demonstrated on a control application for adaptive regulation of the micro-EDM drilling process. The results of deep-hole drilling suggest that the CNN-TSE model can highly improve the process stability and hence the machining quality.

Research on Safety Risk Assessment Method of Wind Power Enterprises Based on Hybrid Analytic Hierarchy Process

With the increase in urban demand for wind power, wind power has become one of the main energy sources for urban production and life. There are many hidden dangers of safety production in urban wind power enterprises in China. Therefore, it is particularly necessary to study the risk evaluation model of urban wind power enterprises. However, the previous evaluation methods seldom consider the impact of risk factors. Aiming at this problem, this paper proposes a fuzzy hybrid AHP evaluation method. Firstly, combined with AHP and network AHP, a hybrid hierarchical structure model of risk evaluation indicators is established, which improves the influence relationship between risk indicators in the index hierarchy model. Secondly, combined with the fuzzy evaluation method, the experimental analysis proves that the model has certain accuracy in the process of practical application.

Capacitive Sensors with Hybrid Dielectric Structures and High Sensitivity over a Wide Pressure Range for Monitoring Biosignals

Various dielectrics with porous structures or high dielectric constants have been designed to improve the sensitivity of capacitive pressure sensors (CPSs), but this strategy has only been effective for the low-pressure range. Here, a hierarchical gradient hybrid dielectric, composed of low-permittivity (low-k) polydimethylsiloxane (PDMS) foam with low Young's modulus (low-E) and high-permittivity (high-k) MWCNT/PDMS foam with high Young's modulus (high-E), is designed to develop a CPS for monitoring biosignals over a wide force range. The foam-like structure with hybrid permittivity (low-k + high-k) is facilitated to improve the sensitivity, while the hierarchical structure with gradient Young's modulus (low-E + high-E) contributes to broadening the pressure sensing range. With the hierarchical gradient hybrid structure, the flexible pressure sensor achieves an enhanced sensitivity of 2.155 kPa-1, a wide pressure range (up to 500 kPa), a minimum detection limit (50 Pa), and an excellent durability (>2500 cycles). As a demonstration, a venous thrombosis simulation and smart insole system are established to monitor venous blood clots and plantar pressures, respectively, which reveal potential applications in wearable medicine, sports health prediction, athlete training, and sports equipment design.

Study on mechanical properties of lattice structures strengthened by synergistic hierarchical arrangement

To study the synergistic hierarchical arrangement effect, three hierarchical cubic lattice structures and six kinds of hybrid hierarchical lattice structures are designed based on the synergistic hierarchical arrangement concept. While studying the synergistic hierarchical arrangement effect on the structural protection characteristics, the prediction function of structural properties and the constitutive relation of lattice structures are derived. The structural properties are accurately predicted, and the errors are within 5%. In terms of mechanical properties of lattice structures, 941 hybrid hierarchical lattice structure, similar to the hybrid hierarchical arrangement inside the femur, presents the best mechanical behavior, followed by 194 and 419 hybrid hierarchical lattice structure. The bearing capacity, specific energy absorption, and energy absorption of 941 are more than 100% of those of other hierarchical or synergistic hybrid hierarchical lattice structures. The results show that the hierarchical and synergistic hybrid hierarchical lattice structure can effectively improve the mechanical properties of the lattice structure in different directions, especially the femur-like synergistic hybrid hierarchical structure. To better determine the excellent performance of the hybrid hierarchical structure, combined with the car seat, the performance of the hybrid hierarchical structure is further studied. Ideas are provided for the subsequent application of energy-absorbing engineering.

Optimization design of a novel hybrid hierarchical cellular structure for crashworthiness

Cellular structure has attracted extensive attention due to its lightweight, superior mechanical properties, and excellent energy absorption property. In nature, the animal bone and plant stem both are cellular structures. It is found that these natural cellular structures additionally have a hierarchical characteristic which makes them extremely strong and ultra-light. Inspired by the hierarchical characteristic of the natural cellular structures, a novel hybrid hierarchical cellular structure, named octet-truss-TPMS (HOTT) structure is invented based on both octet-truss lattice and triply periodic minimal surfaces (TPMS) structure in this study. The specimens of the HOTT structures are fabricated using 3D printing technology and are tested by a universal testing machine. To carry out numerical simulation for the crashworthiness of the HOTT structure, the finite element (FE) model of the HOTT structure is established. The FE model is verified because the crushing forces and deformation modes obtained by the FE simulation are consistent with the test results. Based on the FE model, the crashworthiness of four HOTT structures with different configurations is studied. The effect of design parameters (i.e., equivalent density ρE, level set constant C, structural parameter N, and impact loading velocity v) on their crashworthiness are investigated. Moreover, a multi-objective optimization method based on metamodels and the NSGA-II algorithm is employed to optimize the crashworthiness of the HOTT structures. The optimal designs of four different HOTT structures with maximum specific energy absorption (SEA) and minimum peak crushing force (PCF) are obtained. Based on the Pareto fronts of the multi-objective optimization, the crashworthiness of four HOTT structures are compared. Furthermore, the crashworthiness of the HOTT structures is compared with that of the non-hierarchical octet-truss structure and the traditional aluminum foam with the same weight. The comparison result shows that the HOTT structure has better crashworthiness than the non-hierarchical octet-truss structure and aluminum foam. Thus, the HOTT structure is an excellent energy absorber and has extremely potential applications in impact engineering.

Compressive property of a hybrid hierarchical metamaterial

Hierarchical truss topology of octahedron-of-octahedra is adopted to construct metamaterials using a snap-fit route. Hybrid material concept is utilized for lattice construction using carbon fiber reinforced polymer (CFRP) out-of-plane trusses and Ti-6Al-4V in-plane trusses. Analytical models are developed for hierarchical structures’ stiffnesses and strengths, allowing for failure map construction. Compressive properties of hybrid hierarchical structures are assessed experimentally and shown to be consistent with model estimations. The proposed metamaterial exhibits competitive response to numerous existing cellular solids, demonstrate its potential for light-weighting load-supporting applications.

Construction of a Hierarchical Micro-/Submicro-/Nanostructured 3D-Printed Ti6Al4V Surface Feature to Promote Osteogenesis: Involvement of Sema7A through the ITGB1/FAK/ERK Signaling Pathway.

Constructing hierarchical hybrid structures is considered a facile method to improve the osseointegration of implants. Herein, a hierarchical micro-/submicro-/nanostructured surface feature of Ti6Al4V implants (3DAT group) was successfully constructed by combining the inherently formed three-dimensional (3D)-printed microscale topography, acid-etched sub-micropits, and anodized nanotubes. Compared with the classical SLA surface, the microscale topography and sub-micropits increased the three-dimensional space for the cell growth and mechanical stability of implants, while the modification of nanotubes dramatically improved the surface hydrophilicity, protein adsorption, and biomineralization. Most importantly, the 3DAT surface feature possessed excellent osteogenic performance in vitro and in vivo, with the involvement of semaphorin 7A (Sema7A) as revealed by RNA-seq through the ITGB1/FAK/ERK signaling pathway. The present study suggested that the hierarchically structured surface design strategy could accelerate the osseointegration rate of 3D-printed Ti6Al4V implants, promising personalized reconstruction of bone defects.

Numerical and random forest modelling of the impact response of hierarchical auxetic structures

Major sources of concern when auxetic protective structures are deployed in service of mission-critical applications encompass the triggering of high impact stress and the weakening of the structures’ elastic strength in response to the impact events. The current prevailing approach to assessing the impact resistance of these structures broadly hinges on mechanics-informed nonlinear finite element (FE) analysis. However, this method is computationally expensive and ill-suited for tackling the implementation of automated condition monitoring schemes. To address these issues, first, this paper proposes a hybrid hierarchical auxetic structure named Hybrid-Hierarchical Re-entrant Honeycomb (HHRH) that is endowed with impact stress-reducing capabilities. Next, using explicit FE, the investigation uncovers the interplay between the key geometric features of this HHRH auxetic structure and the impact performance under low, intermediate, and high crushing velocities. The outcome of the nonlinear explicit FE simulations is then unified with random forests (RF) scheme towards the establishment of intelligent auxetic structural systems. The results revealed that the developed HHRH maintained the auxeticity of the regular re-entrant auxetic and exhibited superior performance in some crushing strain regions. Moreover, the HHRH structure manifests up to an 85 % reduction in peak stress and the proposed reinforcement boosts the auxetic property by up to 23 % when compared to the regular re-entrant auxetic structure under high-velocity applications. Regarding the established data-driven RF-enabled machine learning model, its predictive strength with optimally-tuned hyperparameters is demonstrated to excellently capture the nonlinear multi-modal crushing stress response at various crushing strains, velocities, and geometric variations. Data AvailabilityThe raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study.

High-Performance Surface-Enhanced Raman Scattering Substrates Based on the ZnO/Ag Core-Satellite Nanostructures.

Recently, hierarchical hybrid structures based on the combination of semiconductor micro/nanostructures and noble metal nanoparticles have become a hot research topic in the area of surface-enhanced Raman scattering (SERS). In this work, two core-satellite nanostructures of metal oxide/metal nanoparticles were successfully introduced into SERS substrates, assembling monodispersed small silver nanoparticles (Ag NPs) on large polydispersed ZnO nanospheres (p-ZnO NSs) or monodispersed ZnO nanospheres (m-ZnO NSs) core. The p-ZnO NSs and m-ZnO NSs were synthesized by the pyrolysis method without any template. The Ag NPs were prepared by the thermal evaporation method without any annealing process. An ultralow limit of detection (LOD) of 1 × 10−13 M was achieved in the two core-satellite nanostructures with Rhodamine 6G (R6G) as the probe molecule. Compared with the silicon (Si)/Ag NPs substrate, the two core-satellite nanostructures of Si/p-ZnO NSs/Ag NPs and Si/m-ZnO NSs/Ag NPs substrates have higher enhancement factors (EF) of 2.6 × 108 and 2.5 × 108 for R6G as the probe molecule due to the enhanced electromagnetic field. The two core-satellite nanostructures have great application potential in the low-cost massive production of large-area SERS substrates due to their excellent SERS effect and simple preparation process without any template.

Application of fuzzy-logic for design assessment of complex engineering systems in the early design stages

Performance characteristics of production-logistic systems arestrongly dependent on their initial design. Hence, it is crucial to employ proper performance assessment approaches at their early design stages. Existing approaches mostly use optimisation for quantitative performance assessment. However, qualitative aspects of such systems considerably impact their lifetime performance. Uncertainty is significant in assessing the qualitative performance of a system. Fuzzy-logic is a useful approach in addressing uncertainty. This paper investigates the application of fuzzy-logic for design assessment of such systems against qualitative criteria. The proposed approach can be utilised as a decision-supporting framework at early design stages of such systems. The framework allows design assessment by modelling the subjective opinion of domain experts. The framework has a hybrid-hierarchical structure, embodying the complex structure of a system to fuzzy-models in a hierarchical manner and allocates related knowledge to fuzzy-models in different hierarchy levels. The framework is applied to a real case to demonstrate its application.

Hierarchical micro-nano structure based NiCoAl-LDH nanosheets reinforced by NiCo2S4 on carbon cloth for asymmetric supercapacitor

All-solid-state asymmetric supercapacitor based on hierarchical hybrid structure decorated with conductive NiCo 2 S 4 on NiCoAl-LDH has good energy density and power density. • NCA-LDH@NCS@CC is synthesized by a simple and low-cost hydrothermal method. • Hierarchical hybrid structure NCA-LDH@NCS is formed on carbon cloth. • NiCo 2 S 4 boosts overall electrical conductivity and hinders agglomeration of LDH. • NCA-LDH@NCS@CC//AC@CC is assembled with high energy density and cycle stability. Rational construction of microstructure and successful incorporation of multiple components offer a scalable strategy for applying electrode materials in asymmetric supercapacitors. Herein, a hierarchical hybrid structure of NiCoAl-layered double hydroxide (NCA-LDH) and ternary spinel NiCo 2 S 4 (NCS) on carbon cloth (CC) without binders is obtained through three-step hydrothermal reaction. The NCA-LDH@NCS@CC electrode exhibits outstanding electrochemical performance with 1775F g −1 at 1 A g −1 . Its capacitance retention is 79.6% when cycles reach 10 000 under 10 A g −1 , benefiting from the hierarchical hybrid structure and improved overall conductivity. A flexible solid-state asymmetric supercapacitor (FSASC) is assembled using NCA-LDH@NCS@CC and activated carbon coated on carbon cloth (AC@CC) for positive and negative electrodes, respectively. It possesses 33.13 Wh kg −1 under 750 W kg −1 , and also maintains a better cycling performance of 71.4% at 1 A g −1 after 10 000 cycles. Hierarchical hybrid NCA-LDH@NCS@CC electrode provides a favorable and scalable candidate for the development of FSASC device with superior performance.

Peptide-mediated green synthesis of the MnO2@ZIF-8 core–shell nanoparticles for efficient removal of pollutant dyes from wastewater via a synergistic process

The MnO2@ZIF-8 core–shell nanoparticles for highly efficient dye degradation have been synthesized with a green method. ZIF-8 crystals with controlled morphology and size are first synthesized by using peptide to modulate the crystal growth. MnO2 is then coated on ZIF-8 via in situ reaction. The surface MnO2 density can be controlled by the dosage of KMnO4. The MnO2@ZIF-8 nanoparticles work as photocatalyst to degrade rhodamine B in a Fenton-like process, giving a degradation ratio of > 96.0%. The degradation kinetics comply well with the Pseudo-second-order model and the experimental equilibrium data meet the Langmuir model best. The specific hierarchical structure of MnO2@ZIF-8 assures a synergistic enhancement of the catalytic degradation performance from several aspects. First, anchoring of the MnO2 nanoparticles on ZIF-8 allows their well disperse to provide more active surface area. Second, highly porous ZIF-8 can adsorb dye molecules to accumulate them at the surface reactive sites. Third, the MnO2/ZIF-8 nano-heterojunctions enhance charge carrier transfer and accelerate the production of free oxidative radicals. The study demonstrates a green method for fabrication of hierarchical hybrid structures, paving the way for designing novel photocatalysts with potential applications for wastewater treatment.