Structural Decomposition Research Articles

Structural Decomposition of the Passivity-Based Control System of Wind–Solar Power Generating and Hybrid Battery-Supercapacitor Energy Storage Complex

Wind–solar power generating and hybrid battery-supercapacitor energy storage complex is used for autonomous power supply of consumers in remote areas. This work uses passivity-based control (PBC) for this complex in accordance with the accepted energy management strategy (EMS). Structural and parametric synthesis of the overall PBC system was carried out, which was accompanied by a significant amount of research. In order to simplify this synthesis, a structural decomposition of the overall dynamic system of the object presented in the form of a port-Hamiltonian system, which was described by a system of differential equations of the seventh order, into three subsystems was applied. These subsystems are a wind turbine, a PV plant, and a hybrid battery-supercapacitor system. For each of the subsystems, it is quite simple to synthesize the control influence formers according to the interconnections and damping assignment (IDA) method of PBC, which locally performs the tasks set by the EMS. The results obtained by computer simulation of the overall and decomposed systems demonstrate the effectiveness of this approach in simplifying synthesis and debugging procedures of complex multi-physical systems.

Thermal characteristics of LiMnxFe1-xPO4 (x = 0, 0.6) cathode materials for safe lithium-ion batteries

Lithium-ion batteries have recently gained attention as energy storage devices due to their high energy densities and various applications. Layered Ni-Mn-Co-based cathode materials are widely used for their high energy density; however, their high cost necessitates the exploration of alternatives. Consequently, olivine-type LiMnxFe1-xPO4 materials are gaining popularity and are being increasingly adopted. While the synthesis methods and electrochemical properties of these materials have been extensively studied, thermal analyses remain limited. In this study, we investigated the thermal properties of olivine-type LiMnxFe1-xPO4 by combining thermal analysis, structural analysis, and computational calculations to evaluate the safety of lithium-ion batteries. Our results show that the formation energy of LiMn0.6Fe0.4PO4 is more stable than that of LiFePO4. As temperature increases, LiFePO4 decomposes at 350 °C, whereas LiMn0.6Fe0.4PO4 begins to decompose at 450 °C. The P-O bond plays a crucial role in the thermal stability of these materials; as the temperature rises, the thermal stability of the PO4 group diminishes, leading to structural decomposition. To enhance thermal stability, it is recommended to experiment with doping small amounts of various elements at the P site. This paper provides valuable insights for the design and development of thermally stable olivine-structured cathodes for lithium-ion batteries.

Genesis of an Inorganic CO2 Gas Reservoir in the Dehui–Wangfu Fault Depression, Songliao Basin, China

This study systematically examines the origins and formation mechanisms of inorganic CO2 gas reservoirs located within the Dehui–Wangfu Fault in the southeastern uplift region of the Songliao Basin. The research aims to clarify the primary sources of inorganic CO2, along with its migration and accumulation processes. The identification of the Wanjinta gas reservoir within the Dehui–Wangfu Fault Zone, abundant in inorganic CO2, has sparked significant interest in the pivotal roles of volcanism and tectonic activity in gas generation and concentration. To analyze the release characteristics of CO2, this study conducted degassing experiments on volcanic and volcaniclastic rock samples from various boreholes within the fault trap. It evaluated CO2 release behaviors and controlling factors across varying temperatures (150 °C to 600 °C) and particle sizes (20, 40, and 100 µm). The findings indicated a negative correlation between CO2 release and particle size, with a notable transition at 300 °C—marking this temperature as critical for the release of adsorbed and lattice gases. Moreover, volcaniclastic rocks exhibited higher CO2 release compared to volcanic rocks, attributable to their larger specific surface area and higher porosity. At 600 °C, the decomposition of the rock crystal structure results in substantial gas escape. These observations suggest that the inorganic CO2 in this area derives not only from mantle sources but is also influenced by crustal components. Elevated temperatures prompted by tectonic activity and magmatic intrusion facilitated the degassing of the surrounding rocks, allowing released CO2 to migrate upwards through the fracture system and accumulate in the shallow crust, ultimately forming a gas reservoir. This study enhances the understanding of volcanic rock’s roles in inorganic CO2 gas generation and migration, highlighting the fracture system’s critical controlling influence on gas transport and aggregation. The findings indicate that inorganic CO2 gas reservoirs in the Dehui–Wangfu Fault Zone primarily originate from mantle sources with a mixture of crustal gases. This discovery offers new theoretical insights and practical guidance for the exploration and development of gas reservoirs in the Songliao Basin and similar regions.

Conductivity Prediction Method of Solid Electrolyte Materials Based on Pearson Coefficient Method and Ensemble Learning

In order to screen solid electrolytic materials with high ionic conductivity more quickly and accurately, a conductivity prediction method for solid electrolyte materials based on logistic regression model and random forest regression model is constructed. The method first selects 20 characteristic descriptors related to ionic conductivity from material library according to four dimensions: structural stability, metal stability, electronic conductivity and oxidative decomposition stability. The enumeration method and feature selection method are used to combine different features. Then, the dimension reduction of the feature combinations is carried out by Pearson coefficient method, so as to screen the optimal feature combinations. Finally, according to the optimal feature combination and data subset, the constructed random forest ensemble learning model is utilized to predict the ionic conductivity of other solid-state electrolyte materials in the material library, in order to find the solid-state electrolyte materials that can meet the high conductivity. The results indicate that as the number of features in the combination increases, the prediction performance of the model shows a trend of first increasing and then decreasing. When the feature descriptor in the combination is 7, the maximum AUC (Accuracy) value is reached, and the optimal feature in this case contains 7 optimal feature subsets corresponding to feature descriptors, namely the standard deviation of the average adjacency number of Li atoms, the standard deviation of Li-X ion bonds, the average electronegativity of the straight path, the average width of the straight path, the average atomic volume, the average Li-Li bond, and the filling fraction of the sublattice. On the basis of the optimal feature screening, the average prediction accuracy of the logistic regression model is 87.13%, which has a high accuracy. Using the random forest regression model for prediction, the average absolute error and root mean square error obtained are only 0.237 and 0.134, and compared with classical classification methods such as KNN, SVM and Adaboost, they are smaller, which can better predict the ionic conductivity of solid electrolyte materials. This proves that the constructed method can quickly and accurately produce high ionic conductivity materials in solid electrolyte materials, which is worthy of further research and promotion.

Generation characteristics and molecular reaction dynamics mechanism of PAHs during oxygen-lean combustion of jet coal

Severe coalfield fires occur in China, mainly in the northwest provinces of Xinjiang, Inner Mongolia, and Ningxia. Among the organic pollutants produced by oxygen-lean combustion, PAHs are considered one of the most dangerous pollutants due to their environmental contamination and “carcinogenic, teratogenic, and mutagenic” effects on human beings. In this paper, to address the problems of PAHs generation and reaction mechanism in coalfield fire, the jet coal from Xinjiang Zhundong Coalfield was selected to conduct the experiments, and the combustion products were detected using GC–MS and FTIR. The molecular dynamics method based on the reaction force field was also used to calculate the reaction process of 17 single molecules (5083 atoms) of jet coal combusted from 300 K to 4000 K at 0.5 oxygen equivalent ratio. The experimental results show that the generation of PAHs increased roughly from 573 K to 773 K at the three oxygen concentrations, and an increase in oxygen content can enhance PAHs generation to some degree. The structural evolutions and product changes in the system have been traced, and it is also clarified that the reaction history of oxygen-lean combustion mainly experiences two stages: thermal decomposition of coal structure and transformation of aromatic structure. The generation mechanism of PAHs is proposed from the perspective of molecular reaction dynamics. On the one hand, it is due to the breakage of active sites such as C-S, C-O, and O-H during the decomposition of coal structure. On the other hand, it originates from the polycondensation reaction triggered by the dehydrogenation of aromatic structure that enlarges the aromatic dimension The research results reveal the generation characteristics and reaction pathways of PAHs in the oxygen-lean combustion of low-rank coal in the fire zone and provide certain references for coal fire management and pollutant control.

Cumulative Tariff Cost Rate and Structure in the Global Value Chain: A Theoretical and Empirical Study

Abstract This paper constructs a more unified measurement framework from the perspective of the Leontief inverse matrix and Ghosh inverse matrix (Ghosh). At the same time, referring to the four-term decomposition method of Leontief inverse matrix in Muradov (2016), this paper analyzes the structural decomposition of the cumulative tariff cost rate. Results show that (1) Overall, from 2000 to 2017, China’s cumulative tariff cost rate, direct tariff cost rate, and multi-stage tariff cost rate all showed a downward trend, and the decline was greater than that of other countries (regions). China has strictly fulfilled its WTO accession commitments and has greatly reduced the tariff rate on imported intermediate goods. (2) With China’s deep participation in the global value chain, the amplification effect of China’s tariffs has increased from 2.57 in 2000 to 3.17 in 2017, and there is a certain degree of “amplification effect” (above 1.5) in tariffs in all countries in the world. (3) From the perspective of the contribution rate of various countries in the world, China contributes the most to the global cumulative tariff cost rate, which is due to the complexity of the global production network structure, rather than the excessively high tariff rate imposed by China on imported intermediate goods. In terms of policy implications, if China did not take the initiative to reduce tariffs, the structural changes in the global production network would lead to a larger global cumulative tariff cost rate.

Anchoring of boron halides BX (X: F, Cl, and Br) on transition metal (M: Cr, Mo, W) carbonyl complexes M(CO)5 (M: Cr, Mo, W): structure, bonding, and energy decomposition studies based on theoretical calculations

Anchoring of boron halides BX (X: F, Cl, and Br) on transition metal (M: Cr, Mo, W) carbonyl complexes M(CO)5 (M: Cr, Mo, W): structure, bonding, and energy decomposition studies based on theoretical calculations

Technological progress on embodied carbon emissions in Sino-Korea trade from industry perspective: input–output and structural decomposition analysis

Technological progress on embodied carbon emissions in Sino-Korea trade from industry perspective: input–output and structural decomposition analysis

A Modified Reentrant Metamaterial with Equal and Enhanced Orthogonal Elastic Properties

Herein, an improved mechanical metamaterial is proposed, which is derived from the decomposition, rotation, and reassembly of reentrant structures. The structure is parametric, allowing for rapid redesign. The study focuses on the variations in equivalent stiffness and Poisson's ratio of the structure within the linear elastic range when internal rib angle θ changes. First, based on homogenization simulation analyses, it has been verified that this design achieves the tailorable equivalent elastic modulus and Poisson's ratio over a wide range, meanwhile, maintaining equal elastic properties in the orthogonal direction at all times. Second, to reduce future repetitive experiments, an interpolation model is established to expand the design domain. The fitting formula indicates that by modifying θ and relative wall thickness t/L0, the elastic performance of the structures can be tailored. Additionally, the impact of boundary conditions is discussed to minimize experimental costs. Finally, the accuracy of the simulations is validated through uniaxial compression tests.

Quantitative assessment of PM2.5-related human health impacts at the provincial level in China and analysis of its heterogeneity affected by economic structural transformation

Rapid economic development has led to massive fossil energy consumption and emissions of air pollutants such as PM2.5, which have severely impacted human health and the environment. By uncovering the primary regions and pivotal sectors of PM2.5-related human health impacts (PM2.5-HHI) and evaluating the influence of economic structural factors on them, we can facilitate a more targeted strategy for managing PM2.5 pollution sources. This study employs a structural decomposition analysis method based on input–output analysis to evaluate the impact of China’s provincial economic structural transformation and changes in final demand on PM2.5-HHI in the years 2012, 2015, and 2017. Results indicated that PM2.5-HHI is primarily concentrated in economically developed provinces (e.g., Shandong and Guangdong), which is compared to Shanghai, Heilongjiang, Liaoning, and Hebei experienced negative growth in PM2.5-HHI during 2007–2017. The production-based PM2.5-HHI is primarily driven by energy-intensive sectors such as the production and distribution of electric power and heat power. By contrast, the building sector is key to driving consumption-based PM2.5-HHI. An increasing number of regions are reducing PM2.5-HHI by implementing production structure changes. Moreover, the driving effect of production structure changes on PM2.5-HHI growth is strengthening in Beijing and Tianjin. Changes in the final demand structure mainly led to the growth of PM2.5-HHI in areas with higher economic development levels, such as Beijing and Shandong, but this driving effect is weakening. The final demand–driven PM2.5-HHI shows an evolutionary trend of an increasing share driven by fixed capital formation and exports and a decreasing share driven by household consumption. Changes in emission intensity play a key role in decreasing PM2.5-HHI in each region. Alternatively, changes in the structure of emission sources have a relatively minor impact on PM2.5-HHI. To mitigate PM2.5-HHI, regional economic and resource endowment advantages should be used to promote regional coordinated development and strengthen green production-process innovation in energy-intensive industries. Meanwhcile, it is necessary to optimize urban construction planning and improve the energy efficiency of buildings.

Mineralized Biopolymers-Based Scaffold Encapsulating with Dual Drugs for Alveolar Ridge Preservation.

Mineralization of scaffolds is essential for alveolar ridge preservation and bone tissue engineering, enhancing the mechanical strength and bioactivity of scaffolds, and promoting better integration with natural bone tissue. While the in situ mineralization method using concentrated SBF solutions is promising, there is limited comprehensive research on its effects. In this study, it is demonstrate that soaking gelatin/alginate scaffolds (GAS) in fivefold concentrated SBF significantly reduces the mineralization time to 3-7 days but also leads to considerable degradation and loss of the scaffold's original microstructure. The ratio of gelatin to alginate is optimized to improve the properties of GAS. The optimized GAS sample, when soaked in concentrated SBF to form GAS/HAp, exhibited hydroxyapatite (HAp) crystal formation starting from day 3, with mature hexagonal crystals forming by day 7. However, this process also caused significant decomposition and deformation of the scaffold's pore structure. Additionally, the biocompatibility of GAS and GAS/HAp is evaluated through in vitro, in ovo, haemolysis, and anti-ROS assays. The findings highlight the impact of SBF5× on the mineralization of GAS, laying the groundwork for further research in alveolar ridge preservation and bone tissue engineering.

Determining the optimal bid direction of a generation company using the gradient vector of the profit function in the network constraints of the electricity market

AbstractOne of the primary challenges faced by generation companies (GenCos), which operate multiple generation units within the electricity market, is the determination of the optimal bid price for these units to maximize profit. This paper proposes a novel approach to ascertain the optimal bid price direction for GenCos by leveraging the gradient vector of the profit function within the constraints of the electricity market. First, the Jacobian matrix of unit profits is computed using the electricity market structural decomposition method. This matrix highlights how the profit of generation units is affected by market input parameters, including the bid prices of the units. Then, the gradient vector of the GenCos' profit function and the optimal bid price direction are derived from the Jacobian matrix. The methodology is applied to a 24‐bus IEEE network, with results validated against those from a simulation method to confirm the efficacy of the proposed approach. The simulation results show that the highest and lowest profit changes with a step increase of 0.1$/MWh are observed for GenCo 4 and GenCo 6 with values of 60.28 and 2.20 $/h, respectively. The proposed approach can be effective in the changes of bid direction of the units of a GenCo to achieve the highest possible profit.

AIE pyrene-based luminescent zinc MOF for selective and sensitive ATP and ADP sensing in water by analyte-induced structure decomposition

Adenosine triphosphate (ATP) is a natural and universal energy carrier that produces adenosine diphosphate (ADP) by releasing chemical energy through hydrolysis, which plays a key role in various biological processes. Hence, the design of probes for the selective ATP and ADP sensing among various nucleosides is significant. In this work, 4,4′-(pyrene-1,6-diyl)dibenzoic acid (H2PDBA) has been synthesized and shows an aggregation-induced emission (AIE) effect in a THF-H2O mixture at 10 % water fraction. Based on H2PDBA, a new zinc metal–organic framework (MOF), namely {[Zn(PDBA)]·2(CH3)2NH}n (Zn-MOF, PDBA = deprotonation of H2PDBA), has been constructed under hydrothermal conditions with a coordination-induced emission (CIE) effect. Significantly, Zn-MOF has been utilized to detect ATP and ADP in water with high selectivity and quick response time (within 1 min) by fluorescence quenching. The Ksv values and detection limits have been measured to be 7.83/8.78 × 103 M−1 and 0.82/1.71 μM for ATP and ADP, respectively. The sensing mechanism investigation indicates that the interactions between the ATP or ADP and Zn2+ nodes of the framework lead to the partial collapse of the framework, followed by the release of the ligand H2PDBA with weak luminescence in pure water. Moreover, Zn-MOF has successfully been applied for the determination of ATP and ADP with the recovery method by using fetal bovine serum samples.

Extremely Fast Wicking Self‐Layered Interpenetrating Network Hydrogel for Rapid All Day Collection of Atmospheric Water

AbstractHygroscopic salt hydrogel photothermal composites and related technology are a promising pathway for water harvesting. However, due to the overly cumbersome preparation process, the distribution of the surface photothermal layer is difficult to control and the photothermal efficiency is low. In this paper, a method is proposed to greatly simplify the preparation process of photothermal layer hydrogels and improve their atmospheric water harvesting performance by constructing temperature‐sensitive interpenetrating networks. Due to the decomposition of some reversible hydrated structures in the network during heating and warming, carbon nanotubes move autonomously to form a layered structure with a photothermal effect on the upper surface, which can return to its original state after cooling and remain stable at room temperature or under solar illumination. Compared with hydrogels with general layered structure or overall distribution of photothermal materials, agar/GG/PAM/CNT hydrogel has faster moisture adsorption efficiency and higher desorption efficiency, and during the 24 h continuous sorption–desorption cycle is capable of achieving high water yield of 2.57 Lwater kgsorbents−1 day−1, superior to most recent hydrogel adsorbents. Simplifying the preparation process while maintaining high efficiency, while greatly improving photothermal performance, paves the way for cost‐effective mass production applications for a wide range of hygroscopic salt‐hydrogel photothermal composites.

Global carbon transition in the passenger transportation sector over 2000–2021

The high-emitting and hard-to-abate passenger transport sector plays a crucial role in global deep decarbonization. To lead an equitable and rapid transition in the passenger transportation, this work is the first to develop a bottom-up modeling framework integrated with the latest decomposing structural decomposition methodology to assess and compare historical emission patterns and decarbonization efforts of 28 countries over the past two decades. Results indicate: (1) Carbon emissions from the global passenger transport sector increased between 2000 and 2021, peaking in 2019, with GDP per capita and population size being key drivers of rising carbon emissions across countries. (2) The decarbonization efforts of the global passenger transport sector varied by traffic mode. The largest contributors were passenger buses [−0.46 megatons of carbon dioxide per year (Mt CO2/yr)], followed by trains (−0.4 Mt CO2/yr), and airplanes (−0.28 Mt CO2/yr), while passenger cars (1.04 Mt CO2/yr) hindered the decarbonization process. (3) Although the global passenger transport sector has cumulatively decarbonized 3005.9 Mt CO2 and achieved a decarbonization rate of 5.1 %, regional performance varied significantly, exhibiting uneven and inadequate progress. Overall, the study provides an effective data-driven assessment framework for reviewing and comparing global and national passenger transport decarbonization performance, which will facilitate the planning of decarbonization pathways by global emitters and the early achievement of zero-carbon transport.

Understanding export-generated employment in India

International trade can play a catalytic role in economic development and employment enhancement. To understand the employment impact of India’s pattern of trade, we use a structural decomposition analysis utilising the World Input – Output Database. Distinguishing between final and intermediate exports from India, we quantify the domestic employment effect during 2000–14. We show that a shift in final exports’ composition towards sectors and sub-sectors with lower employment generation potential led to a negative employment effect. However, changes in international production sharing have largely had a positive impact on employment in India. Our structural decomposition analysis is complemented with a panel regression that tracks the employment effect of exports through backward linkages. We find significant differential impacts in India’s bilateral trade with middle-income versus high-income countries. While bilateral backward linkages from exports to middle-income countries enhanced employment in India, exports to high-income countries did not yield a positive employment effect.

Time-varying effects of structural oil price shocks on financial market uncertainty

This study employed the structural oil price decomposition method proposed by Ready (2018) to decompose oil price shocks into oil risk shocks, demand shocks, and supply shocks. By using the Diebold and Yilmaz (DY) spillover index and rolling window methods, the static and dynamic spillovers of structural oil price shocks on financial market uncertainty were examined. The findings suggest that oil risk shocks exhibited the strongest spillover effects on financial market uncertainty (except for South Africa), followed by oil demand shocks, while oil supply shocks had virtually no impact. Second, the effects of structural oil price shocks on financial market uncertainty were time-varying. Third, significant differences in the spillover effects of structural oil price shocks on financial market uncertainty were found across countries, and the spillover effect of oil risk shocks on the financial market uncertainty in the United States was the largest in all periods. Fourth, the spillover effects of oil demand shocks on financial market uncertainty were larger in the high than in the low oil price period (except for Japan). Finally, during the COVID-19 (coronavirus disease) pandemic compared with the pre-epidemic period, the spillover effects of oil risk shocks on the financial market uncertainty in China significantly decreased, while simultaneously, the spillover effects of oil supply shocks on the financial market uncertainty in Australia substantially increased.

Synergies quantification and evolution on air pollutant and CO2 emissions driven by different socio-economic effects

Realizing a synergistic reduction of air pollutant and CO2 emissions (APCE) is an important approach to promote a green socio-economic transformation in China, and it can provide a solid foundation for the achievement of clean energy production and climate action under a sustainable development goal framework. The objective of this study is to explore the quantitative relationship and evolution of synergies between APCE in industrial sectors driven by different socio-economic effects from 2007 to 2020 in China. The results indicated that the main sectors of pollutant emissions had consistency, however, large differences in the reduction efficiency of emissions exist among pollutants. The efficiency in reducing CO2 emissions was about 48% lower when compared with reductions of SO2 (95%), NOx (86%), and smoke and dust (83%) emissions from 2007 to 2020. The effects of improved technology were the main contributor to a reduction in pollutant emissions, but the synergies between APCE driving by it were not achieved. While the synergies between APCE driven by structure and final demand effects were significant. The synergies between NOx and CO2 emissions were stronger driven by final demand structure and type effects, with correlation coefficients of 1.06 and 1.13, respectively. Besides, the degree of synergistic reduction between APCE in most industrial sectors was around zero. Therefore, the efficiency of synergistic pollution reduction should be improved with the development of a synergistic governance system for industrial sectors. The structural decomposition analysis based on input-output model combined with the cross-elasticity analysis method to quantitively synergies between APCE from the consumption (demand) perspective, considering the connections between industrial sectors with socio-economic developing, which would contribute to the industrial synergistic reduction and green transformation as the consumption driven gradually increasing.

Soil Organic Matter and Bulk Density: Driving Factors in the Vegetation-Mediated Restoration of Coastal Saline Lands in North China

Coastal saline soils are an important soil resource that, when restored, can enhance arable land and preserve the natural ecology. With the aim of improving the use of coastal saline soils, we conducted a spot survey at Bohai coastal saline land to investigate the differences in soil properties between different vegetation types. The soil physical and chemical properties of various vegetation types, including Aeluropus sinensis, Imperata cylindrica, Tamarix chinensis, Lycium chinense, Hibiscus moscheutos, Helianthus annuus, Gossypium hirsutum, and Zea mays, were examined at two depth layers: 0–20 cm and 20–40 cm, and in two seasons, spring and autumn. The soil properties were compared with bare land as a control. The results indicated that the electrical conductivity, total soil salt content, sodium adsorption ratio, and bulk density of soils with vegetation cover were lower than those with bare land. On the other hand, soil pH, organic matter content, mean weight diameter, and saturated hydraulic conductivity were higher. The redundancy analysis results revealed a substantial positive correlation between soil pH, saturated hydraulic conductivity, water content, mean weight diameter, and organic matter content, as well as a significant positive correlation between soil electrical conductivity, total soil salt content, sodium adsorption ratio, and bulk density. Soil pH, saturated hydraulic conductivity, water content, mean weight diameter, organic matter content, and soil electrical conductivity, total soil salt content, sodium adsorption ratio, and bulk density were negatively correlated. The results of the structural equation model and variance decomposition showed that soil organic matter and bulk density were the key factors affecting the degree of soil salinization, and compared with their independent effects, their combined effect on soil salinization was greater. This study’s conclusions can provide a point of reference for further research on the mechanisms of soil improvement and desalinization in coastal saline land.

Encapsulating Halide Perovskite Quantum Dots in Metal–Organic Frameworks for Efficient Photocatalytic CO2 Reduction

Halide perovskite has shown great potential in photocatalysis owing to its diversity, suitable energy band alignment, rapid charge transfer, and excellent optical properties. However, poor stability, especially under humid conditions, hinders their practical application in photocatalysis. In this work, we report the encapsulation of inorganic–organic hybrid perovskite QDs into MIL-101(Cr) through an in situ growth strategy to prepare a series of MAPbBr3@MIL-101(Cr) (MA = CH3NH3+) composites. The perovskite precursors, i.e., MABr and PbBr2, were successively introduced into the pores of MOF, where the perovskite quantum dots were self-assembled in the confined environment. In photocatalytic CO2 reduction, 11%MAPbBr3@MIL-101(Cr) composite displayed the best performance among the composites with a total CO and CH4 yield of 875 μmol g−1 in 9 h, which was 8 times higher than that of the pure MAPbBr3. Such high gas production efficiency could be maintained for 78 h at least without structural and morphologic decomposition. The remarkable stability and catalytic activity of composites are mainly due to the synergistic effect and improved electron transfer between MAPbBr3 and MIL-101(Cr). Moreover, these composites revealed a novel mechanism, showing switched CH4 selectivity with the controlling of the perovskite location and contents. Those with perovskites encapsulated in the mesopores of MIL-101(Cr) were more preferential for CO production, while those with perovskites encapsulated in both meso- and micropores could produce CH4 dominantly.