Cluster Complexes Research Articles

1DCAE-TSSAMC: Two-Stage Multi-Dimensional Spatial Features Based Multi-View Deep Clustering for Time Series Data

At present, as a research hotspot for time series data (TSD), the deep clustering analysis of TSD has huge research value and practical significance. However, there still exist the following three problems: (1) For deep clustering based on joint optimization, the inevitably mutual interference existing between deep feature representation learning progress and clustering progress leads to difficult model training especially in the initial stage, the possible feature space distortion, inaccurate and weak feature representation; (2) Existing deep clustering methods are difficult to intuitively define the similarity of time series and rely heavily on complex feature extraction networks and clustering algorithms. (3) Multidimensional time series have the characteristics of high dimensions, complex relationships between dimensions, and variable data forms, thus generating a huge feature space. It is difficult for existing methods to select discriminative features, resulting in generally low accuracy of methods. Accordingly, to address the above three problems, we proposed a novel general two-stage multi-dimensional spatial features based multi-view deep clustering method 1DCAE-TSSAMC (One-dimensional deep convolutional auto-encoder based two-stage stepwise amplification multi-clustering). We conducted verification and analysis based on real-world important multi-scenario, and compared with many other benchmarks ranging from the most classic approaches such as K-means and Hierarchical to the state-of-the-art approaches based on deep learning such as Deep Temporal Clustering (DTC) and Temporal Clustering Network (TCN). Experimental results show that the new method outperforms the other benchmarks, and provides more accurate, richer, and more reliable analysis results, more importantly, with significant improvement in accuracy and spatial linear separability.

Octahedral molybdenum cluster complex with glycolate ligands and study of its activity in polyurethane polymerization process

Octahedral metal clusters [{M6X8}L6]2– (where M = Mo2+ or W2+, X = Cl–, Br– or I–, and L is an apical ligand typically with a charge of 1–) have shown promise in a great variety of applications, ranging from solar energy and catalysis to cancer diagnostics and therapy. However, these clusters are not stable in water – the most widely used medium in many practical fields. An effective way to utilize and stabilize these compounds is to incorporate them into organic matrices. Along with direct impregnation, clusters can be used as monomers in polymerization process due to the ease of an addition of polymerizable functional groups in cationic part or in apical ligand environment. In this work, new cluster with six terminal glycolate ligands, (Bu4N)2[{Mo6I8}(OOCCH2OH)6], has been obtained and studied using FTIR, TGA, EDX, etc. Cluster luminescence has been studied in the temperature range of 77–300 K. As have been demonstrated experimentally and theoretically, by the DFT calculations, the coordination of glycolic acid to the cluster drastically reduces the activity of the –OH group in the polymerization of polyurethane.

Hidden Gems on a Ring: Infant Massive Clusters and Their Formation Timeline Unveiled by ALMA, HST, and JWST in NGC 3351

We use 0.1″ observations from the Atacama Large Millimeter Array (ALMA), Hubble Space Telescope (HST), and JWST to study young massive clusters (YMCs) in their embedded “infant” phase across the central starburst ring in NGC 3351. Our new ALMA data reveal 18 bright and compact (sub-)millimeter continuum sources, of which 8 have counterparts in JWST images and only 6 have counterparts in HST images. Based on the ALMA continuum and molecular line data, as well as ancillary measurements for the HST and JWST counterparts, we identify 14 sources as infant star clusters with high stellar and/or gas masses (∼105 M ⊙), small radii (≲ 5 pc), large escape velocities (6–10 km s−1), and short freefall times (0.5–1 Myr). Their multiwavelength properties motivate us to divide them into four categories, likely corresponding to four evolutionary stages from starless clumps to exposed H ii region–cluster complexes. Leveraging age estimates for HST-identified clusters in the same region, we infer an evolutionary timeline, ranging from ∼1–2 Myr before cluster formation as starless clumps, to ∼4–6 Myr after as exposed H ii region–cluster complexes. Finally, we show that the YMCs make up a substantial fraction of recent star formation across the ring, exhibit a nonuniform azimuthal distribution without a very coherent evolutionary trend along the ring, and are capable of driving large-scale gas outflows.

The methods for improving large-scale multi-view clustering efficiency: a survey

The diversity and large scale of multi-view data have brought more significant challenges to conventional clustering technology. Recently, multi-view clustering has received widespread attention because it can better use different views’ consensus and complementary information to improve clustering performance. Simultaneously, many researchers have proposed various algorithms to reduce the computational complexity to accommodate the demands of large-scale multi-view clustering. However, the current reviews do not summarize from the perspective of reducing the computational complexity of large-scale multi-view clustering. Therefore, this paper outlines various high-frequency methods used in recent years to reduce the computational complexity of large-scale multi-view clustering, i.e. third-order tensor t-SVD, anchors-based graph construction, matrix blocking, and matrix factorization, and compares the corresponding algorithms based on several open datasets. Finally, the strengths and weaknesses of the current algorithm and the point of improvement are analyzed.

Characterising galaxy clusters’ completeness function in Planck with hydrodynamical simulations

Galaxy cluster number counts are an important probe with which to constrain cosmological parameters. One of the main ingredients of the analysis, along with accurate estimates of cluster masses, is the selection function, and in particular the completeness associated with the cluster sample under consideration. Incorrectly characterising this function can lead to biases in cosmological constraints. In this work, we want to study the completeness of the Planck cluster catalogue, estimating the probability of cluster detection in a realistic setting using hydrodynamical simulations. In particular, we probe the case in which the cluster model assumed in the detection method differs from the shapes and profiles of true galaxy clusters. We created around 9000 images of the Sunyaev–Zel’dovich effect from galaxy clusters from the IllustrisTNG simulation, and used a Monte Carlo injection method to estimate the completeness function. We studied the impact of having different cluster pressure profiles and complex cluster morphologies on the detection process. We find that the cluster profile has a significant effect on completeness, with clusters with steeper profiles producing a higher completeness than ones with flatter profiles. We also show that cluster morphology has a small impact on completeness, finding that elliptical clusters have a slightly lower probability of detection with respect to spherically symmetric ones. Finally, we investigate the impact of a different completeness function on a cosmological analysis with cluster number counts, showing a shift in the constraints on Ωm and σ8 that lies in the same direction as the shift driven by the mass bias.

An Effective Clustering Based Privacy Preserving Model Against Feature Attacks

The rise in healthcare-related illnesses has generated a substantial amount of patient data, making the safeguarding of patient data privacy imperative. Existing privacy protection methods face challenges, including longer execution times, compromised data quality, and increased information loss as data dimensions expand. Effective attribute selection is vital to enhance preservation methods. Our research introduces a privacy-preserving clustering approach that addresses these concerns through two stages: feature selection and anonymization. The first stage selects relevant features using symmetrical uncertainty (SU) and eliminates duplicates with Kendall’s Tau Correlation Coefficient. The Utility Preserved Anonymization (UPA) algorithm is employed in the second phase to achieve privacy preservation. Additionally, our approach reduces data dimensionality to simplify cluster creation for anonymization. Experimental analysis on real-time data demonstrates the strategy’s effectiveness, with outstanding sensitivity (97.85%) and accuracy (95%), efficiently eliminating unnecessary features and simplifying clustering complexity.

Hydrophobic Mismatch in the Thylakoid Membrane Regulates Photosynthetic Light Harvesting.

The ability to harvest light effectively in a changing environment is necessary to ensure efficient photosynthesis and crop growth. One mechanism, known as qE, protects photosystem II (PSII) and regulates electron transfer through the harmless dissipation of excess absorbed photons as heat. This process involves reversible clustering of the major light-harvesting complexes of PSII (LHCII) in the thylakoid membrane and relies upon the ΔpH gradient and the allosteric modulator protein PsbS. To date, the exact role of PsbS in the qE mechanism has remained elusive. Here, we show that PsbS induces hydrophobic mismatch in the thylakoid membrane through dynamic rearrangement of lipids around LHCII leading to observed membrane thinning. We found that upon illumination, the thylakoid membrane reversibly shrinks from around 4.3 to 3.2 nm, without PsbS, this response is eliminated. Furthermore, we show that the lipid digalactosyldiacylglycerol (DGDG) is repelled from the LHCII-PsbS complex due to an increase in both the pKa of lumenal residues and in the dipole moment of LHCII, which allows for further conformational change and clustering in the membrane. Our results suggest a mechanistic role for PsbS as a facilitator of a hydrophobic mismatch-mediated phase transition between LHCII-PsbS and its environment. This could act as the driving force to sort LHCII into photoprotective nanodomains in the thylakoid membrane. This work shows an example of the key role of the hydrophobic mismatch process in regulating membrane protein function in plants.

Compatibility degree of cluster complexes

Compatibility degree of cluster complexes

An inversion-based clustering approach for complex clusters

BackgroundThe choice of an appropriate similarity measure plays a pivotal role in the effectiveness of clustering algorithms. However, many conventional measures rely solely on feature values to evaluate the similarity between objects to be clustered. Furthermore, the assumption of feature independence, while valid in certain scenarios, does not hold true for all real-world problems. Hence, considering alternative similarity measures that account for inter-dependencies among features can enhance the effectiveness of clustering in various applications.MethodsIn this paper, we present the Inv measure, a novel similarity measure founded on the concept of inversion. The Inv measure considers the significance of features, the values of all object features, and the feature values of other objects, leading to a comprehensive and precise evaluation of similarity. To assess the performance of our proposed clustering approach that incorporates the Inv measure, we evaluate it on simulated data using the adjusted Rand index.ResultsThe simulation results strongly indicate that inversion-based clustering outperforms other methods in scenarios where clusters are complex, i.e., apparently highly overlapped. This showcases the practicality and effectiveness of the proposed approach, making it a valuable choice for applications that involve complex clusters across various domains.ConclusionsThe inversion-based clustering approach may hold significant value in the healthcare industry, offering possible benefits in tasks like hospital ranking, treatment improvement, and high-risk patient identification. In social media analysis, it may prove valuable for trend detection, sentiment analysis, and user profiling. E-commerce may be able to utilize the approach for product recommendation and customer segmentation. The manufacturing sector may benefit from improved quality control, process optimization, and predictive maintenance. Additionally, the approach may be applied to traffic management and fleet optimization in the transportation domain. Its versatility and effectiveness make it a promising solution for diverse fields, providing valuable insights and optimization opportunities for complex and dynamic data analysis tasks.

Iodine-mediated substitution of terminal ligands in [{M6I8}I6]2– (M = Mo, W) by DMSO

The family of octahedral iodide cluster complexes of molybdenum and tungsten – [{M6I8}L6]n – exhibit a unique set of properties with significant practical potential. Due to the strong influence of terminal ligands L on these properties, the search for new simpler, more convenient and cheaper approaches for their substitution is an urgent task. This work demonstrates a new one-step method for terminal ligand substitution using well-known and readily available complexes [{M6I8}I6]2–. The synthetic technique involves the addition of molecular iodine to the reaction mixture in order to bind the released I– ions, thereby facilitating the reaction process. As a result, two new cluster complexes with dimethyl sulfoxide ligands [{M6I8}(DMSO)6](I3)4 (M = Mo (1), W (2)) have been obtained and structurally characterized. The optical properties of the obtained compounds have been studied both in solid state and in solution, and Eg values have been calculated from the solid-state absorption spectra. The presence of I3– anions has been shown to quench the emission of the cluster complexes, explaining the absence of luminescence in the obtained compounds.

Statistics of a granular cluster ensemble at a liquid-solid-like phase transition.

We report on the construction of a granular network of particles to study the formation, evolution, and statistical properties of clusters of particles developing at the vicinity of a liquid-solid-like phase transition within a vertically vibrated quasi-two-dimensional granular system. Using the data of particle positions and local order from Castillo etal. [G. Castillo, N. Mujica, and R. Soto, Phys. Rev. Lett. 109, 095701 (2012)0031-900710.1103/PhysRevLett.109.095701], we extract granular clusters taken as communities of the granular network via modularity optimization. Each one of these communities is a patch of particles with a very well defined local orientational order embedded within an array of other patches forming a complex cluster network. The distributions of cluster sizes and lifespans for the cluster network depend on the distance to the liquid-solid-like phase transition of the quasi-two-dimensional granular system. Specifically, the cluster size distribution displays a scale-invariant behavior for at least a decade in cluster sizes, while cluster lifespans grow monotonically with each cluster size. We believe this systematic community analysis for clustering in granular systems can help to study and understand the spatiotemporal evolution of mesoscale structures in systems displaying out-of-equilibrium phase transitions.

Electronic Delocalization and σ-Aromaticity in Heterometallic Cluster with Multiple Thorium-Palladium Bonds.

Research on metal-metal bonds involving f-block actinides, such as thorium, lags far behind the well-studied metal-metal bonds of d-block transition metals. The complexes with Th-TM bonds are extremely rare; all previously identified examples have only a single Th-TM bond with the Th center at an invariably +IV oxidation state. Herein, we report a series of Th2Pdn (n = 2, 3, and 6) clusters (complexes 3, 4, and 7) with multiple Th(III)-Pd bonds. Theoretical studies reveal that the Th2Pdn unit allows electronic delocalization and σ aromaticity, leading to unexpected closed-shell singlet structures for these Th(III) species. This electronic delocalization is evident in the highest occupied molecular orbital of Th(III) complexes and facilitates a 2e reduction of alkyne by complex 7, resulting in the formation of 8. Complexes 7 and 8 are distinctive in featuring a Th2Pd6 core with six and eight Th-Pd bonds, respectively, making them the largest known d-f heterometallic clusters exhibiting metal-metal bonding.

Is the RSGC4 (Alicante 8) Cluster a Real Star Cluster? Peculiar Radial Velocities of Red Supergiant Stars

Young massive star clusters, like the six red supergiant clusters in the Scutum complex, provide valuable insights into star formation and galaxy structures. We investigated the high-resolution near-infrared spectra of 60 RSG candidates in these clusters using the Immersion Grating Infrared Spectrograph. Among the candidates in RSGC4, we found significant scattering in radial velocity (−64 to 115 km s−1), unlike other clusters with velocities of ∼100 km s−1. Most candidates in RSGC4 have Q GK s values larger than 1.7, suggesting that they could be early AGB stars. Four candidates in RSGC4 exhibit infrared excess and distinct absorption features absent in other candidates. Two of these stars exhibit absorption lines resembling those of D-type symbiotic stars, showing radial velocity changes in multiepoch observations. Analysis of relative proper motions revealed no runaway/walkaway stars in RSGC4. The dynamic properties of RSGC4 and RSGC1 differ from the disklike motions of other clusters: RSGC4 has low normalized horizontal action J hor = J ϕ /J tot and vertical action J ver = (J z − J R)/J tot values and high eccentricities, while RSGC1 has vertical motions with high J ver values and inclinations. We propose that RSGC4 may not be a genuine star cluster but rather a composite of RSGs and AGB stars distributed along the line of sight at similar distances, possibly originating from various environments. Our results suggest a complex and hierarchical secular evolution of star clusters in the Scutum complex, emphasizing the importance of considering factors beyond density crowding when identifying star clusters in the bulge regions.

The Cluster Complex for Cluster Poisson Varieties and Representations of Acyclic Quivers

Abstract Let $\mathcal{X}$ be a skew-symmetrizable cluster Poisson variety. The cluster complex $\Delta ^{+}(\mathcal{X})$ was introduced in [ 12]. It codifies the theta functions on $\mathcal{X}$ that restrict to a character of a seed torus. Every seed $\textbf{s}$ for $\mathcal{X}$ determines a fan realization $\underline{\Delta ^{+}_{\textbf{s}}(\mathcal{X})}$ of $\Delta ^{+}(\mathcal{X})$. For every $\textbf{s}$ we provide a simple and explicit description of the cones of $\underline{\Delta ^{+}_{\textbf{s}}(\mathcal{X})}$ and their facets using c-vectors. Moreover, we give formulas for the theta functions parametrized by the integral points of $\underline{\Delta ^{+}_{\textbf{s}}(\mathcal{X})}$ in terms of $F$-polynomials. In case $\mathcal{X}$ is skew-symmetric and the quiver $Q$ associated to $\textbf{s}$ is acyclic, we describe the normal vectors of the supporting hyperplanes of the cones of $\underline{\Delta ^{+}_{\textbf{s}}(\mathcal{X})}$ using g-vectors of (non-necessarily rigid) objects in $\textsf{K}^{\textrm{b}}(\textrm{proj} \; kQ)$.

Current analysis of cations substitution in the oxygen-evolving complex of photosystem II.

Water oxidation in photosystem II (PSII) is performed by the oxygen-evolving complex Mn4CaO5 which can be extracted from PSII and then reconstructed using exogenous cations Mn(II) and Ca2+. The binding efficiency of other cations to the Mn-binding sites in Mn-depleted PSII was investigated without any positive results. At the same time, a study of the Fe cations interaction with Mn-binding sites showed that it binds at a level comparable with the binding of Mn cations. Binding of Fe(II) cations first requires its light-dependent oxidation. In general, the interaction of Fe(II) with Mn-depleted PSII has a number of features similar to the two-quantum model of photoactivation of the complex with the release of oxygen. Interestingly, incubation of Ca-depleted PSII with Fe(II) cations under certain conditions is accompanied by the formation of a chimeric cluster Mn/Fe in the oxygen-evolving complex. PSII with the cluster 2Mn2Fe was found to be capable of water oxidation, but only to the H2O2 intermediate. However, the cluster 3Mn1Fe can oxidize water to O2 with an efficiency about 25% of the original in the absence of extrinsic proteins PsbQ and PsbP. In the presence of these proteins, the efficiency of O2 evolution can reach 80% of the original when adding exogenous Ca2+. In this review, we summarized information on the formation of chimeric Mn-Fe clusters in the oxygen-evolving complex. The data cited may be useful for detailing the mechanism of water oxidation.

Utilizing data mining techniques to analyze traditional Chinese medicine patterns in patients with acute cardiorenal syndrome

AbstractObjectiveThis study intends to investigate the medication patterns of traditional Chinese medicine (TCM) for the treatment of acute cardiorenal syndrome (ACRS) through clinical data mining.MethodsA retrospective study was conducted at China‐Japan Friendship Hospital, encompassing hospitalized patients with ACSR admitted from June 1, 2013, to June 30, 2022. Patient treatment records, including TCM prescriptions, were gathered to establish a comprehensive prescription database. The prescriptions underwent analysis using the ancient and modern medical case cloud platform, incorporating the frequency, properties and flavors and channel tropism of each herbs, and clustering patterns, combination relationships, and complex network analysis of the whole.ResultsA total of 330 prescriptions from eligible hospitalized patients were included, which totally involves 324 kinds of different herbs. The therapeutic effects primarily emphasized descending qi and eliminating turbidity, promoting diuresis and reducing swelling, drying dampness and dispelling phlegm, and promoting the ascension of Yang Qi. The properties were largely warm, netural, slightly cool and cold, with warm being predominant. The flavors were chiefly sweet, spicy, and bitter, with sweetness being the most common. The major channel tropism were the lung and spleen meridians, followed by the stomach, liver, heart, and kidney meridians. Combination analysis identified 30 pairs of combinations, with higher associations found in combinations such as Jiegeng, Huangqi, Chaihu, Baizhu, Zhimu, and Dangshen. Cluster analysis categorized high‐frequency herbs into 4 groups: Gualou–Fabanxia–Chuanxiong–Chishao, Fuling–Baizhu–Zhigancao–Chenpi, Maidong–Guizhi–Huangqi–Chaihu–Shengma–Zhimu–Shanzhuyu, and Huangqi–Dangshen–Jiegeng–Chaihu–Shengma–Zhimu–Shanzhuyu. Complex network analysis revealed core prescriptions for treating ACRS, including 17 herbs.ConclusionsIn the treatment of ACRS, TCM herbs with the properties of warm and neturality, and the flavors of sweet and spicy are commonly utilized. The prescribed herbal formulas have the effect of descending qi and eliminating turbidity, tonifying qi, activating blood and resolving stasis, resolving phlegm and promoting water.

Optical Properties of Low‐Defect Large‐Area Hexagonal Boron Nitride for Quantum Applications

Intrinsic defects and their concentrations in hexagonal boron nitride (h‐BN) play a key role in single‐photon emission. In this study, the optical properties of large‐area multilayer h‐BN‐on‐sapphire grown by metal‐organic chemical vapor deposition are explored. Based on the detailed spectroscopic characterization using both cathodoluminescence (CL) and photoluminescence (PL) measurements, the material is devoid of random single‐point defects instead of a few clustered complex defects. The emission spectra of the measurements confirm a record‐low‐defect concentration of ≈104 cm−2. Post‐annealing, no significant changes are observed in the measured spectra and the defect concentrations remain unaltered. Through CL and PL spectroscopy, an optically active boron vacancy spin defect is identified and a novel complex defect combination arising from carbon impurities is revealed. This complex defect, previously unreported, signifies a unique aspect of the material. In these findings, the understanding of defect‐induced optical properties in h‐BN films is contributed, providing insights for potential applications in quantum information science.

Heterogeneous graph community detection method based on K-nearest neighbor graph neural network

Traditional community detection models either ignore the feature space information and require a large amount of domain knowledge to define the meta-paths manually, or fail to distinguish the importance of different meta-paths. To overcome these limitations, we propose a novel heterogeneous graph community detection method (called KGNN_HCD, heterogeneous graph Community Detection method based on K-nearest neighbor Graph Neural Network). Firstly, the similarity matrix is generated to construct the topological structure of K-nearest neighbor graph; secondly, the meta-path information matrix is generated using a meta-path transformation layer (Mp-Trans Layer) by adding weighted convolution; finally, a graph convolutional network (GCN) is used to learn high-quality node representation, and the k-means algorithm is adopted on node embeddings to detect the community structure. We perform extensive experiments and on three heterogeneous datasets, ACM, DBLP and IMDB, and we consider as competitors 11 community detection methods such as CP-GNN and GTN. The experimental results show that the proposed KGNN_HCD method improves 2.54% and 2.56% on the ACM dataset, 2.59% and 1.47% on the DBLP dataset, and 1.22% and 1.67% on the IMDB dataset for both NMI and ARI. Experiments findings suggest that the proposed KGNN_HCD method is reasonable and effective, and KGNN_HCD can be applied to complex network classification and clustering tasks.

Copper(I)‐Arsine Clusters with a Near‐Unity Phosphorescence Quantum Yield for X‐Ray Scintillation and LED Applications

AbstractRare‐earth element‐free materials that exhibit strong room temperature phosphorescence (RTP) and X‐ray scintillation properties are gaining global interest incessantly in the recent years. This work reports a series of easily synthesizable cubane Cu4I4‐triarsenic clusters [Cu4I4(R3As)3L] (L = none or nitrile), that exhibit a strong yellow‐green RTP with quantum efficiencies up to 100% and short decay times (4.4–4.9 µs). The title cluster complexes display X‐ray scintillation properties with a record ultralow detection limit (18.1 nGy s−1) and a perfectly linear dose rate response within a remarkably wide dose rate window (0–640 µGyair s−1). The cluster [Cu4I4(Ph3As)3] is highlighted as an efficient phosphor for UV‐pumped white and yellow LED devices, demonstrating an excellent white spectrum with a CIE index of (0.32,0.33) and bright yellow emission, respectively. These results may stimulate the future efforts in designing highly efficient arsenic‐based RTP materials and enriching the Cu4I4 cluster family.

Impact of Copper(II)-Imidazole Complex Modification on Polycrystalline TiO2: Insights into Formation, Characterization, and Photocatalytic Performance

Micrometer-sized polycrystalline anatase particles are widely used in materials and life sciences, serving as essential components in photocatalytic materials. The ability to tailor their composition, shape, morphology, and functionality holds significant importance. In this study, we identified and examined the non-destructive route of Copper(II) implantation at the surface of polycrystalline TiO2. The [Cu(en)(Im)2]2+ complex ion demonstrated a remarkable affinity to concentrate and bind with the semiconductor’s surface, such as anatase, forming a surface-bound adduct: ≡TiO2 + [Cu(en)(Im)2]2+ → ≡TiO2//[Cu(en)(Im)2]2+. The misalignment of Fermi levels in TiO2//[Cu(en)(Im)2]2+ triggered electron transfer, leading to the reduction of the metal center, releasing Copper(I) in the process. Although less efficient, the released Copper(I) encountered a highly favorable environment, resulting in the formation of the surface complex TiO2:CuIIsc. The implanted Cu(I) was converted back into Cu(II) due to re-oxidation by dissolved oxygen. The penetration of the metal ion into the surface level of the polycrystalline TiO2 lattice was influenced by surface residual forces, making surface grafting of the Cu(II) ion inevitable due to surface chemistry. FTIR, UV–vis, Raman, XRD, EPR, and surface morphological (SEM, EDAX, and HRTEM) analyses identified the typical surface grafting of the Cu(II) cluster complex on the anatase surface matrix. Moreover, the XRD results also showed the formation of an impure phase. The TiO2 polycrystalline materials, modified by the incorporation of copper complexes, demonstrated an enhanced visible-light photocatalytic capability in the degradation of Rhodamine B dye in aqueous solutions. This modification significantly improved the efficiency of the photocatalytic process, expanding the applicability of TiO2 to visible light wavelengths. These studies open up the possibility of using copper complexes grafted on metal oxide surfaces for visible-light active photocatalytic applications. Moreover, this investigation not only showcases the improved visible-light photocatalytic behavior of copper-modified TiO2 polycrystalline materials, but also underscores the broader implications of this improvement in the advancement of sustainable and efficient water treatment technologies.