Structural Diversity Research Articles

Unraveling the reaction mechanism of alkali-activated materials through multi-scale modeling

As an environmentally friendly alternative to cement-based materials, alkali-activated materials (AAM) have attracted much attention due to their significant ability to reduce greenhouse gas emissions and effectively utilize industrial waste. Three Si-Al monomers ([SiO2(OH)2]2-, [SiO(OH)3]-, and [Al(OH)4]-) serve as the fundamental building blocks for the formation of AAM gels. Simulating their polycondensation reactions (PR) among these monomers is of paramount importance but faces a delicate balance between precision and efficiency. To unravel the PR mechanisms, we have integrated reactive force field molecular dynamics (MD) simulations with first-principles calculations based on density functional theory. Our 100ps MD simulations reveal that Al monomers exhibit faster reaction rates and lead to the formation of Si-Al oligomers with diverse structures. Subsequent first-principles calculations on transition state models derived from MD results uncover that PR pathways involving Al monomers possess lower energy barriers, which are correlated with changes in chemical bond strength arising from electronic orbital transitions. Our study, for the first time, establishes an intrinsic link among five hierarchical levels: electronic orbital structure, chemical bond strength, reaction energy barrier, reaction rate, and reaction scale. This provides invaluable theoretical guidance for designing energy-efficient and low-barrier reaction pathways for AAM gel formation.

A novel method for evaluating shale gas preservation conditions in an area on a regional scale

The Youjiang Basin is the main area of the Middle Devonian shale gas resources in southern China, with complex geological conditions, diverse stratigraphic structures, low level of exploration and limited hydrocarbon geological data. In this study, a method is proposed for evaluating the regional shale gas preservation conditions, by which it is easy to obtain information (using available data from regional geological maps) and to process data (processed by computer software). This method was applied to the evaluation of the preservation conditions of the Middle Devonian shale gas in the Youjiang Basin. Information extracted from geologic maps includes exposed stratum, magmatic rock distribution, stratigraphic occurrence and surface fracture distribution. Evaluation criteria for three indexes (stratigraphy index, dip angle index and fracture index) were established to classify the preservation conditions into five types from good to bad. Based on the calculated values of comprehensive index (CI), the comprehensive evaluation each area: 11621.23 km2 for CI of 0.7–1.0, 37162.67 km2 for CI of 0.5–0.7, 57784.43 km2 for CI of 0.3–0.5, 69303.77 km2 for CI of 0.1–0.3, and 69303.77 km2 for CI of 0.0–0.1, accounting for 3.19%, 10.19%, 15.84%, 18.99% and 51.80% of the whole area, respectively. These results are highly consistent with the actual exploration discoveries, showing that in the northern and central parts of the Guizhong Basin, the southern part of the Xidamingshan Uplift, and the northern part of the Qiannan Basin, there are large areas with good shale gas preservation conditions.

HRTBDA: a network for post-disaster building damage assessment based on remote sensing images

ABSTRACT Efficient building damage assessment after disasters is vital for emergency response and loss evaluation, but the task is complicated by diverse building structures and complex environments. Traditional methods using Convolutional Neural Networks (CNNs) struggle to capture global contextual features, limiting damage categorization accuracy. To address this, we introduce the High-Resolution Transformer Architecture for Building Damage Assessment (HRTBDA), which enhances multi-scale feature extraction. A Cross-Attention-Based Spatial Fusion (CSF) module is proposed to utilize the attention mechanism, improving the model’s ability to identify detailed associations in damaged buildings. Additionally, we propose a deep convolution network matching optimization strategy that integrates a multilayer perceptron and expands the receptive field, enhancing global feature perception. HRTBDA’s performance was evaluated on two public datasets and compared with five recent frameworks. The model achieved an F1-score of 86.0% in building localization and 78.4% in damage assessment, with a 4.8% improvement in detecting minor damages. These results demonstrate HRTBDA’s potential for improving building damage assessment and highlight its significant advancements over existing methods.

Research on the influence of cemented carbide micro-textured structure on tribological properties

Abstract To examine how micro-textures with distinct structures affect the tribological properties of cemented carbide tool-cutting processes, various micro-textures were meticulously fabricated on YG8 cemented carbide blocks. Subsequently, friction and wear experiments were systematically conducted to examine the microstructure nuances resulting from the diverse structures. The influence of these micro-textures on the friction coefficient of cemented carbide and its underlying factors was comprehensively analyzed. To further investigate the impact of these micro-textures on the cutting force in cemented carbide tools, finite element analysis was conducted. Identical micro-textures used in the tribological experiment were applied to the tool, followed by milling simulations aimed at elucidating the impact of these varied micro-textures on the three-dimensional cutting force exerted by the tool. Empirical investigations and finite element analyses revealed that micro-textures characterized as parallel (parallel to the main cutting edge), perpendicular (perpendicular to the main cutting edge), and a combination of “parallel + perpendicular” significantly enhance the tribological properties of cemented carbide tools. This enhancement is evident in the reduction of both the friction coefficient and cutting force of the tool. Particularly noteworthy is the substantial efficacy of vertical micro-textures in minimizing both the frictional force and cutting force, resulting in a noteworthy reduction of the primary cutting force by more than 60% and a concomitant alleviation of tool feeding force by approximately 25%.

Investigating the Behavior and Spatiotemporal Variations of Green-line Emission in the Solar Corona

Understanding coronal structure and dynamics can be facilitated by analyzing green-line emission, which enables the investigation of diverse coronal structures such as coronal loops, streamers, coronal holes, and various eruptions in the solar atmosphere. In this study, we investigated the spatiotemporal behaviors of green-line emissions in both low and high latitudes across nine solar cycles, ranging from Solar Cycle 17 to the current Solar Cycle 25, using the modified homogeneous data set. We employed methodologies such as cross correlation, power spectral density, and wavelet transform techniques for this analysis. We found distinct behaviors in green-line energy across various latitudinal distributions in the solar atmosphere. The trends observed at higher latitudes differ from those at lower latitudes. The emission behaviors show a close association with other solar phenomena like solar flares, sunspots, and coronal mass ejections throughout the solar cycles. The observed variations exhibit harmonic periods. The emission activity is significantly higher in the low latitudes, accounting for over 70% of the emissions, while the higher latitudes contribute less than 30%. The emissions exhibit asymmetric behavior between the northern and southern hemispheres, leading to a 44 yr cycle of solar hemispheric dominance shifts. Various factors, such as Alfvén waves, solar magnetic fields, sunspots, differential rotation, and reconnection events, influence the observed differences in behavior between lower and higher latitudes, suggesting the existence of potential underlying phenomena contributing to deviations in properties, intensity, temporal dynamics, and spatiotemporal lifetime.

Enormous diversity of RNA viruses in economic crustaceans.

The study delves into the largely uncharted territory of RNA viruses in crustaceans, which are not only vital for global food supply but also play a pivotal role in marine ecosystems. Focusing on economic crustaceans, the research uncovers 90 RNA viruses, with 69 being potentially new to science, highlighting the vast unknown viral diversity within these marine organisms. The findings reveal that these viruses are often related to those found in other invertebrates and tend to share close relationships with viruses from species within the same food web or habitat. This suggests that viruses may move between different marine species more frequently than previously thought. The discovery of such a wide variety of viruses, particularly the diverse genome structures of newly identified picornaviruses, is a significant leap forward in understanding the crustacean virology. This knowledge is crucial for managing disease risks in aquaculture and maintaining the balance of marine ecosystems.

DDX RNA helicases: key players in cellular homeostasis and innate antiviral immunity.

RNA helicases are integral in RNA metabolism, performing important roles in cellular homeostasis and stress responses. In particular, the DExD/H-box (DDX) helicase family possesses a conserved catalytic core that binds structural features rather than specific sequences in RNA targets. DDXs have critical roles in all aspects of RNA metabolism including ribosome biogenesis, translation, RNA export, and RNA stability. Importantly, functional specialization within this family arises from divergent N and C termini and is driven at least in part by gene duplications with 18 of the 42 human helicases having paralogs. In addition to their key roles in the homeostatic control of cellular RNA, these factors have critical roles in RNA virus infection. The canonical RIG-I-like receptors (RLRs) play pivotal roles in cytoplasmic sensing of viral RNA structures, inducing antiviral gene expression. Additional RNA helicases function as viral sensors or regulators, further diversifying the innate immune defense arsenal. Moreover, some of these helicases have been coopted by viruses to facilitate their replication. Altogether, DDX helicases exhibit functional specificity, playing intricate roles in RNA metabolism and host defense. This review will discuss the mechanisms by which these RNA helicases recognize diverse RNA structures in cellular and viral RNAs, and how this impacts RNA processing and innate immune responses.

Mechanistic effects of lipid binding pockets within soluble signaling proteins: Lessons from acyl-CoA-binding and START-domain-containing proteins.

While lipids serve as important energy reserves, metabolites, and cellular constituents in all forms of life, these macromolecules also function as unique carriers of information in plant communication given their diverse chemical structures. The signal transduction process involves a sophisticated interplay between messengers, receptors, signal transducers, and downstream effectors. Over the years, an array of plant signaling proteins have been identified for their crucial roles in perceiving lipid signals. However, the mechanistic effects of lipid binding on protein functions remain largely elusive. Recent literature has presented numerous fascinating models that illustrate the significance of protein-lipid interactions in mediating signaling responses. This review focuses on the category of lipophilic signaling proteins that encompass a hydrophobic binding pocket located outside of cellular membranes and provides an update on the lessons learned from two of these structures, namely the acyl-CoA-binding and START domains. It begins with a brief overview of the latest advances in understanding the functions of the two protein families in plant communication. The second part highlights five functional mechanisms of lipid ligands in concert with their target signaling proteins.

Integrated analysis of muscle lncRNA and mRNA of Chinese indigenous breed Ningxiang pig in four developmental stages.

Meat and its derivatives serve as crucial sources of protein, vitamins, minerals, and other essential nutrients for humans. Pork stands as China's primary animal-derived food product consumed widely across diverse dietary structures; evaluating intramuscular fat content becomes pivotal in assessing its quality standards. Nonetheless, the intricate molecular mechanisms governing intramuscular fat deposition remain elusive. Our study utilized sequencing technology to scrutinize longitudinal development stages within Ningxiang pig's longest dorsal muscles aiming to unravel these underlying mechanisms. In three distinct comparisons (30d vs. 90d, 90d vs. 150d and 150d vs. 210d) there were 578, 1,000 and 3,238 differentially expressed mRNA, along with 16, 158 and 85 lncRNAs were identified. STEM analysis unveiled six enriched model profiles for lncRNAs while seven such profiles emerged for mRNAs; notably, multiple shared model profiles existed between both RNA types. Enriched analysis highlighted numerous genes from mRNA profile8 and lncRNA profile7 significantly associated with pathways linked to fat deposition. Weight Gene Co-Expression Network Analysis (WGCNA) revealed that differential expression modules (DMEs) & differential expression lncRNAs primarily clustered within cyan, dark slate blue and pale turquoise modules. Furthermore, target genes PKD2 (MSTRG21592.MTRSG8859 and MTRSG18175), COL5A1 (MTRSG9969 and MTRSG180) and SOX13 (MTRSG21592 and MTRSG9088) as core components all intricately tied into processes related to fat deposition. This study lays the groundwork for deeper exploration into the molecular mechanisms underlying LDM fat deposition traits, and it also presents candidate genes for future molecular marker-assisted breeding.

Exploring the Structure-Activity Relationship of COX Inhibitors with Anticancer Effects: A Comprehensive Review.

Cancer is a multifaceted disease with high mortality rates, and current treatments face challenges such as chemoresistance and tumor adaptation. Since Virchow reported the first case of cancer-related chronic inflammation, numerous clinical and epidemiological studies have indicated that around 15-20% of malignant tumors are caused by inflammation. Cyclooxygenase-2 (COX-2), which is the key enzyme in inflammation, has been implicated in tumorigenesis through various mechanisms, including promoting angiogenesis, inhibiting apoptosis, and enhancing the invasiveness of cancer cells. Moreover, COX inhibitors have demonstrated a substantial reduction in death rates associated with esophageal and colon cancer. In this context, targeting COX-2 is an effective strategy for cancer prevention and treatment. This review focuses on the analysis of studies conducted between 2014 and 2024, which evaluate the structure-activity relationship of molecules intended to exhibit cytotoxic activity through COX inhibition. The studies followed both classical and non-classical COX-2 selective drug design strategies. While some focused on the classical approach, utilizing diaryl heterocyclic structures, others explored non-classical designs with a cyclic central scaffold and a linear core. Additionally, several manuscripts employed well-known COX inhibitors, including licofelone, indomethacin, naproxen, tolfenamate, celecoxib, flumizole, and ketoprofen, as starting points for further derivatization and optimization. Cytotoxic activity was evaluated using various cell lines, including MCF- 7, HCT-116, and A549, through assays such as MTT, CellTiter, and MTS. Additionally, studies examined the relationship between COX-2 inhibition and key cancer pathways, including apoptosis and the involvement of enzymes like HDAC, EGFR, and topoisomerase. The majority of studies reported promising cytotoxic activity in COX-2 selective inhibitors. Compounds synthesized with diphenyl heterocyclic scaffolds exhibited enhanced COX-2 selectivity and anticancer efficacy. In particular, derivatives in studies 9, 16, and 24 demonstrated significant activity comparable to standard drugs like celecoxib and doxorubicin. However, only a few studies indicated a weak correlation between COX-2 inhibition and cytotoxicity, suggesting the need for further investigation into other cancer-related mechanisms. This review highlights the potential of COX-2 selective inhibitors in anticancer drug development. The findings support the development of selective COX-2 inhibitors with diverse chemical structures as a promising strategy for cancer therapy.

Beyond buzzwords: fostering interdisciplinary and collaborative global health research in Germany and beyond.

Germany has increased its political and financial commitment for global health, but this needs to be backed by a robust global health research ecosystem with strong partnerships in low- and middle-income countries (LMICs). This article suggests pathways for empowering researchers to operate beyond their disciplinary silos and strengthen partnerships across sectors and countries. The authors identify barriers and enablers of operations from a nascent research network in Germany, trusting that this experience can inform other initiatives seeking to stoke interdisciplinary and collaborative global health research. This article represents the culmination of extensive reflections spanning the initial four years of the German Alliance for Global Health Research (GLOHRA). The insights have additionally been informed by an analysis of publicly available reports, internal procedural records, and externally conducted studies based on interviews with researchers and policymakers. GLOHRA has developed a toolbox of practices that foster interdisciplinary research and support capacity-building. Insights indicate that highly interdisciplinary and diverse governance structures and seed-funding for interdisciplinary and cross-sector research with appropriate review processes represent a critical step for achieving these aims. Additionally, inclusive training sessions and networking events help to bridge disciplinary boundaries, equipping researchers to envision the broader context of their work. Despite achievements, challenges persist. Wider support, especially from universities and research institutions, is necessary to make global health research an attractive career path and to reduce bureaucratic barriers for collaborators in LMICs. Sustained, longer-term federal funding mechanisms will also be essential for ongoing progress.

Stereocontrolled Synthesis of 1,4-Dicarbonyls via [3,3]-Sulfonium Rearrangement and Application to the Synthesis of Heterocycles

Due to an inherent polarity mismatch of the corresponding retrosynthetic synthons, 1,4-dicarbonyl synthesis through polar pathways requires a retrosynthetic rethink. While Umpolung-based approaches exist, efficient control of both the absolute and relative configuration of newly formed stereogenic centres within this motif has long proven particularly challenging. In this Synpacts, we highlight our work on the stereodivergent synthesis of 1,4-dicarbonyl compounds through an unusual transformation that relies on vinyl sulfoxides and ynamides as reactants. This method allows stereoselective access to each and every one out of the four possible stereoisomers of a generic 1,4-dicarbonyl target in a process where enantio- and diastereoselectivity are “dialled into” the vinyl sulfoxide partner. Recent studies show that the thus formed 1,4-dicarbonyls serve as excellent linchpins for structural diversification into highly substituted heterocycles, including those found in natural products. 1. Introduction 2. Synthesis of 1,4-dicarbonyl compounds under acid catalysis 3. Cyclisation towards γ-lactones and γ-lactams 4. Application in total synthesis 5. Conclusion

Urbanization as a catalyst for structural transformation in developing countries: The mediating impact of foreign direct investment

This article analyzes the link between urbanization and the process of structural transformation (ST) in developing countries, taking into account the mediating role that FDI can play. We use secondary data from 2000 to 2023 to determine if FDI positively or negatively influences the ST process in these countries, thereby, altering urbanization patterns. By estimating the Generalized Method of Moments (GMM), the study explores the relationship between urbanization, the ST process, and the mediating role played by FDI. In addition, it takes into account control variables such as gross fixed capital formation (GFCF), gross domestic product per capita (GDPPC), and diversification of production structure (DPS) to analyze their effect on urbanization and, more specifically, on the ST process. The econometric results showed a negative correlation between FDI flows and urbanization, demonstrating that FDI could hinder the success of the ST process in developing countries. On the contrary, econometric results showed that the control variables, GFCF, GDPPC, and DPS, positively influence urbanization in developing countries, indicating that these variables are more conducive to a successful ST process than FDI. Based on the econometric results, policymakers in developing countries are called upon to strengthen urbanization in these countries, by encouraging local investment and the diversification and sophistication of production and export structures, rather than relying solely on FDI. Over the period studied, FDI has not contributed as expected to advancing the urbanization process, a crucial element in the ST process in developing countries.

Heterogeneous Structured Nanomaterials from Carbon and Related Materials

AbstractHeterogeneous structured nanomaterials can be considered as a class of advanced materials that integrate multiple phases, different elements, or components into a single nanoscale structure. For such materials, the different phases, components and their interactions are highly variable and tunable, which open a new avenue for the creation of new materials with unique properties unattainable by the corresponding single‐phase materials. In this review, heterogeneous structured nanomaterials constructed by different carbon allotropes are focused. Due to the unique bonding ability of carbon element, the diverse heterogeneous structures constructed by carbon structures with different dimensions possess distinctive structures and exhibit fascinating properties, providing unprecedented opportunities for various application fields, including electronic/optoelectronic devices, superhard materials, etc. This review provides a systematic elaboration for carbon‐based heterogeneous structured nanomaterials, highlighting their dimension‐dependent structural diversity, unique properties, and application prospects.

Biosynthesis of Natural and Unnatural Perylenequinones for Drug Development.

A wide range of perylenequinones (PQs) with diverse structures and versatile bioactivities have long been isolated, positioning them as highly promising agents for photodynamic therapy (PDT). However, the lack of an efficient and cost-effective method to obtain these compounds and to introduce structural diversity and complexity currently hinders their further research and application. In this concept, we present a comprehensive overview of the advancements in the biosynthetic pathways of natural PQs based on their structural classification, and also summarize recent progress in the biosynthesis of natural PQs and derivatives. These pioneering efforts may pave the way for structure modification and large-scale bioproduction of natural and unnatural PQs through synthetic biology strategies to promote their drug development.

Feature analysis of 5G traffic data based on visibility graph

IntroductionAs 5G networks become widespread and their application scenarios expand, massive amounts of traffic data are continuously generated. Properly analyzing this data is crucial for enhancing 5G services.MethodsThis paper uses the visibility graph method to convert 5G traffic data into a visibility graph network, conducting a feature analysis of the 5G traffic data. Using the AfreecaTV dataset as the research object, this paper constructs visibility networks at different scales and observes the evolution of degree distribution with varying data volumes. The paper employs the Hurst index to evaluate the 5G traffic network and uses community detection to study the networks converted from 5G traffic data of different applications.ResultsExperimental results reveal significant differences in node degree distribution and topological structures of 5G traffic data across different application scenarios, such as star structures and multiple subnetwork structures. It is found that the node degree distribution of 5G traffic networks exhibits heterogeneity, reflecting the uneven growth of node degrees during network expansion. The Hurst index analysis discovers that the 5G traffic network retains the long-term dependence and trends of the original data. Through community detection, it is observed that networks converted from 5G traffic data of different applications exhibit diverse community structures, such as high centrality nodes, star-like community structures, modularity, and multilayer characteristics.DiscussionThese findings indicate that 5G traffic networks in different application scenarios exhibit complex and diverse characteristics. The heterogeneity of node degree distribution and differences in topological structures reflect the imbalance in node connection methods during network expansion. The results of the Hurst index show that the 5G traffic network inherits the long-term dependence of the original data, providing a basis for analyzing the dynamic characteristics of the network. The diverse community structures reveal the inherent modularity and hierarchy of the network, which helps to understand the performance and optimization directions of 5G networks in different applications.

A Hybrid Mechanism and Data‐Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics‐Informed Neural Networks

ABSTRACTOur research group has focused on the long‐term performance degradation of micro‐electro‐mechanical systems (MEMS) devices under mechanical, thermal, and electrical stresses. We previously used physics‐based models for performance prediction, but the diverse materials, structures, and environmental conditions of MEMS devices affect their long‐term stability. Traditional physics‐based models struggle to account for these factors, limiting practical application. To address this, we employ data‐driven methods to include more variables. This paper introduces a hybrid approach combining physical principles with data‐driven techniques, specifically physics‐informed neural networks (PINN), to model and analyze performance degradation in MEMS resonators. We compare this method with previous physics‐based and data‐driven approaches (support vector machine and random forest) under identical conditions. The hybrid method not only provides accurate predictions but also considers more operating conditions, enhancing practical application.

Анализ развития современной двусторонней торговли между РФ и КНР

Analysis of the development of trade and economic relations between the People's Republic of China (PRC) and the Russian Federation (RF) is an important aspect of research in the field of international economics and the development of economic relations between these two countries. Since 2022, trade turnover between them has been constantly increasing, setting new historical records. For about 14 years, China has been Russia's largest trading partner in many respects. The purpose of this article is to analyze the development of trade and economic relations between China and Russia over the past few years and identify prospects for future mutually beneficial cooperation. To do this, reports from customs departments of the two countries, expert reviews, and reports from public and private organizations have been used as the main sources of information. These sources provide detailed information on the flow of goods, currency transactions, investment projects, and other important aspects of the trade and economic relationship between the PRC (China) and Russia. Analysis of these sources revealed several key trends and factors affecting the development and prospects for mutual relations between the two countries. An increase in trade turnover was observed, as was an increase in China's share in Russian trade. Additionally, there was a diversification of the commodity structure and a deepening of investment cooperation. Problems faced by the two nations in the process of establishing economic ties were identified, along with their possible solutions. Based on this analysis, conclusions were drawn regarding the possible future evolution and prospects for mutually beneficial cooperation between China and the Russian Federation over the coming years.

Nanoscale Topography Dictates Residue Hydropathy in Proteins.

Proteins exhibit diverse structures, including pockets, cavities, channels, and bumps, which are crucial in determining their functions. This diversity in topography also introduces significant chemical heterogeneity, with polar and charged domains often juxtaposed with nonpolar domains in proximity. Consequently, accurately assessing the hydropathy of amino acid residues within the intricate nanoscale topology of proteins is essential. This study presents quantitative hydropathy data for 277,877 amino acid residues, computed using the Protocol for Assigning a Residue's Character on a Hydropathy (PARCH) scale. Leveraging this data set comprising 1000 structurally diverse proteins sourced from the Protein Data Bank, we examined residues situated in various nanoscale environments and analyzed hydropathy in relation to protein topography. Our findings indicate that the hydropathy of a residue is intricately linked to both its individual characteristics and the geometric features of its neighboring residues in response to water. Changes in the number and chemical identity of the neighbors, as well as the nanoscale topography surrounding a residue, are mirrored in its hydropathy profile. Our calculations reveal the intricate interplay of hydrophilic, hydroneutral, and hydrophobic residues distributed across the surface and core of proteins. Notably, we observe that protein surfaces can be ten times more hydrophilic than their cores.

Halogen-Driven Single-Crystal to Single-Crystal Transformation Engineering the Cluster-based Spin Crossover Frameworks.

Cluster-based spin crossover (SCO) frameworks are a new class of smart metal-organic frameworks (MOFs) with diverse structures and topologies and unique bistable physicochemical properties. Here, we report a cluster-based SCO framework [Fe3{Ag4(CN)6(H2O)}2(TPBA)3](ClO4)2·7DMF (1) with an extremely rare 3,4,6-T108 topology, in which the tripodal [Ag{Ag(CN)2}3(H2O)]2- clusters axially link the Fe2+ ions to form 2D→3D n-fold Borromean entangled networks. Under the guidance of reticular chemistry, the post-synthetic modification (PSM) from 1 with 3,4,6-T108 topology to [Fe3{Ag8X8(CN)6}(TPBA)3] (2_X, X = Cl, Br, I) with urk topology is firstly achieved via single-crystal to single-crystal (SCSC) transformation. Moreover, the successive SCSC transformations from 2_Cl to 2_Br and then to 2_I are realized for the first time. Their SCO behaviors are also modified by halogen-driven stepwise cluster transformations. Hence, these findings provide new strategies for the development of cluster-based SCO MOFs towards the smart functional porous materials.