The prevalence of polystyrene microplastics (PS MPs) in surface water threatens the low-pressure membrane (LPM) process used for the safe supply of drinking water. Although pre-coagulated LPM processes effectively retain PS MPs and enhance effluent quality, the dynamic role of PS MPs in fouling evolution and filtration performance throughout the entire operational cycle remains unclear. Therefore, this study investigated the effects of PS MPs on the filtration performance and fouling evolution of pre-coagulated LPM processes using various coagulants (AlCl3, poly-aluminum chloride (PACl), and octadecyl-quaternium hybrid coagulant (OQHC)) over 720 h. During 0-100 h, membrane fouling was primarily governed by floc-membrane interfacial interactions. PS MPs alleviated membrane fouling by reducing the attractive acid-base interaction energy between flocs and the membrane by 1.29-2.34 mJ m-2. Notably, the OQHC processes achieved the highest permeability (normalized flux = 0.86). During 100-720 h, the predominant fouling type transformed to cake layer filtration (R2 = 0.9061-0.9485). Consequently, the influence of PS MPs on the filtration performance depended on the floc characteristics and cake layer structure. In this period, PS MPs deteriorated flux stability in AlCl3 (decay coefficients (D) = 0.0030) and OQHC processes (D = 0.0016), whereas they enhanced flux stability in the PACl process (D = 0.0037). To evaluate the relative significance of various floc characteristics on pre-coagulated LPM filtration performance, a multiple linear regression model was established. The results revealed that floc strength exerted the strongest influence on filtration performance, followed by fractal dimension, the proportion of sub-6 mu m flocs, and Zeta potential. This study provides critical insights into the dynamic role of PS MPs in LPM processes and proposes a practical evaluation framework for optimizing pre-coagulated membrane treatment.

Organic semiconductor photocatalysts provide a promising platform for solar hydrogen evolution by integrating light harvesting, exciton dynamics, and interfacial catalysis. However, in most organic semiconductors, slow proton transport through hydrophobic domains decouples photogenerated electrons from proton-coupled electron transfer and limits activity. Here we encapsulate perylenetetracarboxylic acid dianhydride (PTCDA) into a hydrogen-bonded organic framework (HOF) of H4TBAPy linkers to build proton-conductive nanochannels around photoactive pi-stacks. The hydrogen-bond network supports proton diffusion along confined pathways, increasing proton conductivity from 0.7 to 9.6 mS cm-1, while the pi-pi stacked heterojunction generates an internal electric field that enhances interfacial charge separation. As a result, the PTCDA-in-HOF composite achieves a hydrogen evolution rate of 709.05 mmol g-1 h-1 with an apparent quantum efficiency of 29.4% at 450 nm and robust cycling stability. By coupling proton-transport engineering with organic semiconductor design, this work clarifies the role of local proton availability in organic photocatalysts and guides optimization of solar hydrogen fuel production.

Fe-based catalysts have garnered considerable attention for NO3⁻ removal and conversion. However, antagonistic NO3⁻/PO43⁻ removal, low N2 selectivity, and slow degradation kinetics limit the application of Fe-based hydroxide catalysts in green denitration. In this study, an innovative La-mediated green rust (La-GR) bimetallic hydroxide was designed and synthesized, achieving over 80 % synchronous and targeted removal of NO3⁻ and PO43⁻. Combined transient reaction analyses and DFT calculations revealed that La-O-Fe coordination reconstructs the electronic structure at the catalytic interface, decoupling reduction and adsorption processes to replace competitive antagonism with synergistic promotion, thereby enabling simultaneous nitrogen and phosphorus removal. The in-situ formation of LaPO4 enhanced the built-in electric field of La-GR, creating a microenvironment conducive to local NO3⁻ reduction. The La/Fe exchange process synergistically modulated magnetic exchange interactions within GR by elevating the d-band center and reducing the spin state of the Fe sites. This optimized d-orbital electron configuration lowered the adsorption energy of nitrogen at the Fe sites and facilitated N2 desorption, thereby achieving precise regulation of N2 selectivity up to 88.83 %. Overall, this coupling of functional differentiation and spin regulation offers new paradigms for designing high-performance catalysts and elucidating catalytic mechanisms at the spin-electron scale.

Fecal sludge (FS) contains recoverable organic matter, nitrogen, and phosphorus alongside pathogens, antibiotic resistance genes (ARGs), microplastics, and micropollutants. FS treatment technologies are often evaluated as isolated unit operations, obscuring how phase partitioning governs resource recovery and residual risks. This review summarizes current evidences within a phase-specific resource–risk framework integrating solid–liquid separation, stream-specific valorization, terminal hazard mitigation, safety verification, and data-driven control. Primary separation generally concentrates particulate organic matters, phosphorus, particle-associated pathogens, intracellular ARGs, microplastics, and hydrophobic micropollutants in the solid fraction, whereas the liquid fraction contains ammonium, soluble organic matters, free viral particles, extracellular ARGs, and hydrophilic contaminants. This partitioning establishes distinct treatment priorities. Anaerobic digestion enables biogas recovery, composting produces soil amendments, and liquid-phase processes target nutrient recovery and contaminant removal. However, biological treatment alone cannot reliably eliminate pathogens, ARGs, or persistent micropollutants. Process intensification can improve resource conversion, whereas advanced oxidation processes and thermochemical treatments can strengthen hazard attenuation but may increase energy and reagent demand, generate byproducts, or reduce agronomic value. Treatment trains should therefore align phase-specific recovery objectives with multiple safety endpoints. Data-driven models may support adaptive operation by linking process variables to resource recovery, hazard attenuation, and product quality, but FS-specific datasets, sensor reliability, model transferability, and full-scale validation remain limited. This framework supports risk-informed treatment-train design for safer resource recovery.

Eutrophication driven by excessive phosphorus discharge threatens global aquatic ecosystems. Enhanced biological phosphorus removal (EBPR) is a sustainable, widely deployed wastewater treatment technology, yet it often requires optimization to meet increasingly stringent global phosphorus emission standards. Conventional chemical supplements can achieve deep phosphorus removal, but they require excessive dosing, generate large volumes of sludge, and can inhibit the essential polyphosphate-accumulating organisms (PAOs) that drive biological treatment. Here we show that a low-dose, slow-release lanthanum aerogel (LZGA) activates PAO metabolism, enabling deep biological phosphorus removal with a near-zero chemical footprint. By releasing La3+ into sequencing batch reactors, the LZGA platform reduced effluent total phosphorus from 0.85 mg L-1 to 0.14 mg L-1 at an optimal dose of 15 mg L-1. This represents a two-order-of-magnitude reduction in chemical consumption compared to conventional precipitation methods, requiring 0.7 g of lanthanum to treat one ton of wastewater. Proteomic and microbial analyses reveal that trace La3+ stimulates potassium channels, upregulating key energy metabolism pathways and driving an order-of-magnitude increase in the protein expression of the core PAO Candidatus Accumulibacter. Furthermore, the system enhances extracellular polymeric substance (EPS) production, and improves the phosphorus absorption capacity of EPS. These findings demonstrate that targeted trace-metal activation of microbial metabolic pathways offers a strategy to upgrade existing bioreactors. This strategy provides a versatile paradigm for global wastewater management and advanced eutrophication control.

Addressing the dual challenges of excess sludge disposal and phosphorus (P) resource scarcity, this study developed a novel worm reactor (WR) integrating mechanical agitation and continuous weak aeration to achieve simultaneous sludge reduction and enhanced P release. The unique reactor design minimized worm loss while creating heterogeneous microenvironments conducive to P solubilization. By leveraging worm predation, the impacts of dissolved oxygen (DO), initial sludge concentration (ISC), and sludge retention time (SRT) on process efficiency were systematically investigated. Optimal conditions-DO 1.0 mg L-1, ISC 7000 mg L-1, and SRT 1.7 dwere identified via response surface methodology (RSM), achieving a sludge reduction rate of 732 mg L-1 d-1 and supernatant P release of 54.2 mg L-1. Significantly higher pollutant release (COD, NH4+-N, TN, TP) was observed in the WR compared to a control reactor, confirming that worm predation enhances P release. Mechanistic analysis revealed synergistic P migration pathways: biological fragmentation disrupted extracellular polymeric substances (EPS) and cells, while microbial metabolism facilitated organic P mineralization. This work provides an efficient strategy for simultaneous sludge minimization and P resource reclamation, advancing sustainable wastewater management.

Iron-assisted aerobic granular sludge (AGS) technology shows promising potential for the treatment of high-concentration organic wastewater containing antibiotics. However, the long-term influence of magnetic particles on AGS stability remains inadequately understood, especially in the context of treating high-concentration organic wastewater containing antibiotics. In this study, the effects of Fe3O4 addition on AGS stability and treatment performance were evaluated over 150 days of operation with organic-rich wastewater amended with sulfamethoxazole. Results showed that Fe3O4 supplementation accelerated granule formation, increased biomass concentration, and improved sludge settleability, reflected by a decreased SVI5 value of 34.0 +/- 1.1 mL/g. Fe3O4 also restricted AGS particle size by selectively enriching slow-growing bacteria and enhancing shear-induced abrasion. Released iron ions cross-linked with extracellular polymeric substances (EPS) to form a dense physical barrier that limited antibiotic penetration, while altered surface properties improved antibiotic adsorption. Moreover, magnetic particles stabilized the secondary structure of EPS proteins, thereby reinforcing resistance to external stress. The Fe3O4-amended system exhibited strong resilience to antibiotic shock, maintaining high sludge structural integrity (integrity coefficient >93%). During the stabilization phase, the magnetic powder-enhanced reactor achieved a total nitrogen removal efficiency of 95.4 +/- 2.0%. The combined evidence strongly suggests that heterotrophic nitrification-aerobic denitrification served as the dominant nitrogen removal pathway, with Fe3O4 significantly enhancing denitrification performance through upregulation of key functional genes (nap, nir, nor), which reached abundances approximately five times those in the control. This study underscores the potential of Fe3O4 to advance AGS technology for effective treatment of antibiotic-containing high-strength organic wastewater.

The photoelectrochemical-peroxymonosulfate (PEC-PMS) technology is a promising water purification technology but is hindered by challenges in designing the suitable photoelectrodes and clarifying the pollutantdependent degradation mechanisms. Herein, the dual-engineering (morphology engineering and heterojunction) MoSe2/TNC photoelectrode was synthesized, which achieved near-complete degradation of diverse contaminants, like ciprofloxacin (CIP), levofloxacin (LVX), and carbamazepine (CBZ), with only 0.5 mM PMS under ultralow potentials. Density functional theory (DFT) calculations illustrated that MoSe2/TNC exhibited strong orbital hybridization that shifted the D-band center (d pound = 0.0035 eV) closer to the Fermi level with the lowest work function (phi = 3.071 eV). DFT calculations, electron spin resonance, and quenching experiments first revealed that the applied voltages significantly accelerated the rate-limiting step of PMS activation on MoSe2/ TNC. Furthermore, the PEC-PMS system provided diverse active species for oxidative degradation (1O2 and & sdot;OH) of CIP and reductive degradation (e- and & sdot;O2-) for perfluorooctanoic acid (PFOA). In summary, the PEC-PMS system achieved the energy-efficient degradation of diverse emerging contaminants (ECs) and a life cycle assessment confirmed its practical application potential. This work provides fundamental insights into the catalytic degradation mechanisms of ECs in the PEC-PMS system and the theoretical basis for future engineering applications and targeted degradation of pollutants.

Bioenergy recovery is a global priority for environmental sustainability and energy transition. The microbial electrolysis cell-anaerobic digestion hybrid system (MEC-AD) offers a promising approach for efficient methane recovery; however, the functional roles of its components remain unclear. In this study, bioanodes, biocathodes, and suspensions were isolated from a stably operated MEC-AD bioreactor to investigate their microbial community characteristics and dominant metabolic functions under controlled conditions. The bioanode was identified as the primary contributor to methane production, accounting for 69%-82% of the methane yield via mixotrophic methanogenesis, dominated by Methanothrix and Methanosarcina, in synergy with Thermoanaerobacter and Geobacter. The biocathode reshaped fermentation patterns, reducing propionate accumulation by enriching Clostridium, Syntrophobacterium, and Methanobacterium. The suspension exhibited fermentation but limited methanogenesis owing to the low abundance of methanogens. These results clarify the functional partitioning of MEC-AD systems and provide a basis for targeted regulation to reduce propionate accumulation and enhance methane productivity. This study demonstrates the distinct roles of components in MEC-AD systems in promoting efficient and stable methane production, with important implications for process optimization and improved system performance.

Monitoring data from urban drainage sensor networks are fundamental for system-state perception and risk-management decision-making. However, existing sensor placement (SP) studies primarily focus on detection accuracy for specific monitoring tasks while overlooking the contribution of SP to system-wide perceptibility, and typically rely on full-node hydraulic state data that is rarely available in practice. To address these limitations, we proposed a topology-first and demand-driven end-to-end framework spanning sensor placement, perceptibility assessment, and monitoring applications. The framework introduces the ideal perceptual domain (IPD) to quantify the theoretical perceptibility of sensor configurations and guide demand-driven placement optimization, while a graph-based reconstruction model is used to estimate the actual perceptual domain (APD) and support monitoring tasks. In the case study, the sensor network designed to achieve a target IPD coverage of 90% required sensors at only 3.0% of the network nodes. Under a representative rainfall event, this configuration achieved an APD coverage of 86.7%, an IPD-APD consistency coefficient of 0.96, and flooding-node identification precision and recall values of 0.95 and 0.91, respectively. The proposed framework provides a practical and interpretable solution with potential engineering applications in sensor-network design for urban drainage systems under data-limited conditions, thereby supporting urban flood-risk monitoring and decision-making for drainage-infrastructure management.

The stability of aerobic granular sludge (AGS) is frequently compromised by fluctuating organic loading rates during high-strength wastewater treatment; however, the impacts of different COD/N transition patterns on AGS stability remain inadequately characterized. This study systematically investigated the effects of COD/N transition patterns (shock vs. stepwise) on the stability of AGS during high-strength wastewater treatment. Three independent laboratory-scale SBRs (R1-R3) were operated for 150 days, with each reactor representing a distinct COD/N adjustment strategy: R1 (shock increase from 12 to 24), R2 (stepwise increase from 12 through 16 and 20 to 24), and R3 (constant 24). Results demonstrate that shock loading triggered catastrophic granule disintegration (SVI5: sludge volume index after 5 min = 72.0 mL/g, IC: integrity coefficient = 51.8 +/- 1.1 %), microbial diversity collapse (36 % reduction), and severe, persistent deterioration in nitrogen removal (40 % TN efficiency decline). In contrast, stepwise adaptation maintained structural stability through balanced extracellular polymeric substance (EPS) composition (PN/PS=3.7 +/- 0.3) and robust microbial networks (440 edges; 52 % positive correlations). Direct cultivation at a COD/N ratio of 24 was found to potentially induce systemic instability. Notably, the variation pattern of the COD/N, rather than its final steady-state value, was identified as the determining factor for long-term system resilience. These findings demonstrate that a stepwise adjustment of the COD/N ratio represents the optimal operational strategy and provide practical implementation guidelines for the full-scale application of AGS technology in the treatment of organic-rich wastewater.

Effective photocatalytic degradation of perfluorooctanoic acid (PFOA) remains challenging due to inefficient charge separation and limited visible-light absorption of conventional catalysts. Pristine Bi5O7I suffers from low specific surface area and rapid charge recombination, and NiO is limited by a wide band gap and low Ni3+ content. Here, a NiO/Bi5O7I S-scheme heterojunction (NB5) was synthesized via one-pot hydrothermal synthesis followed by calcination. In-situ growth of NiO nanoparticles increased surface area, and Bi5O7I incorporation increased the Ni3+/Ni2+ ratio, collectively strengthening the internal electric field and accelerating charge transfer. As a result, NB5 achieved 87.5% PFOA removal with an apparent rate constant of 0.439 h-1 under simulated sunlight. Mechanistic studies revealed a non-radical-dominated synergistic oxidation-reduction pathway involving direct oxidation by h+, Ni3+-mediated electron transfer, and conduction-band e-, facilitated by reversible Ni3+/Ni2+ redox cycling. Density functional theory (DFT) calculations reveal dual thermodynamically favorable oxidation pathways for PFOA anions, involving direct h+ oxidation (Delta G =-9.58 eV) and Ni3+-mediated oxidation (Delta G =-8.13 eV). The toxicity and ecological risks of PFOA and its degradation products were predicted based on structure-activity relationships using established in silico approaches. This work provides a facile strategy for S-scheme heterojunction construction and mechanistic guidance for photo-catalytic degradation of PFOA.

Ultra-low-pressure ceramic microfiltration (ULPCM) is fundamentally constrained by the permeability-selectivity trade-off: the accumulation of compact cake layers increases hydraulic resistance, whereas the intrinsic large pore size of microfiltration membranes limits the rejection of trace micropollutants. In this study, a tri-functional quaternary ammonium silane (AC) was introduced during polyaluminum chloride (PACl) pre-coagulation to regulate floc architecture and engineer the structure of the coagulation-derived cake layer. During 360 h (15 d) of continuous operation in both synthetic surface water and actual surface water, the AC-integrated system achieved a stable normalized flux (J/J(0) = 0.38-0.40) and exceptional PFOA sequestration (>93.71%), significantly outperforming conventional systems. Molecular dynamics (MD) simulations and spectroscopic analyses (XPS/FT-IR) elucidated that the C-18 alkyl chains and quaternary ammonium groups dictate PFOA capture through synergistic hydrophobic and electrostatic interactions, while hydrophilic silanol groups enhance dissolved organic carbon (DOC) removal via hydrogen bonding. At the interfacial level, XDLVO theory and dynamic light scattering (DLS) quantification revealed that AC effectively regulates the thermodynamics of floc adhesion, promoting the assembly of a highly branched, low-fractal-dimension (D-f) scaffold. Morphology measurements confirmed that the engineered cake layer maintained a high porosity (up to 62.79%) with a pore size distribution dominated by micro-channels (<0.5 mu m), which enhanced the water permeability of the cake layer and its retention capacity for foulants. Integrated fouling analysis using Hermia, Tansel, and saturation decay models, together with statistical evaluation, demonstrated that floc size, cake layer porosity, pore size distribution, and AC-induced hydrophobic interactions played key roles in mitigating membrane fouling and enhancing contaminant retention. These findings highlight that regulating floc architecture via amphiphilic coagulant aids provides an effective strategy for engineering cake layer microstructure and mitigating membrane fouling in low-pressure microfiltration systems.

This study presents the development of a novel Cu–Co–O-codoped graphitic carbon nitride (g-C3N4) catalyst for efficient peroxymonosulfate (PMS) activation to degrade sulfamethoxazole (SMX) in aqueous environments. The synthesized Cu–Co–O-g-C3N4 catalyst demonstrated exceptional catalytic performance, achieving 90% SMX removal within 10 min—significantly outperforming pristine g-C3N4 (14%) and O-doped g-C3N4 (22%)—with a reaction rate constant of 0.63 min−1. The superior activity was attributed to the synergistic effects of Cu-Co bimetallic doping and oxygen incorporation, which enhanced the active sites, stabilized metal ions, and minimized leaching. Mechanistic studies revealed a dual-pathway degradation process: (1) a radical pathway dominated by sulfate radicals (SO4•−) and (2) a non-radical pathway driven by singlet oxygen (1O2), with the latter identified as the dominant species through quenching experiments. The catalyst exhibited broad pH adaptability and optimal performance at neutral to alkaline conditions. Characterization techniques (XRD, FTIR, XPS) confirmed successful doping and revealed that oxygen incorporation modified the electronic structure of g-C3N4, improving charge carrier separation. This work provides a sustainable strategy for antibiotic removal, addressing key challenges in advanced oxidation processes (AOPs), and highlights the potential of multi-heteroatom-doped carbon nitride catalysts for water purification.

This study investigated the impact of hybrid electrocoagulation and ceramic membrane microfiltration (EC-CM) process on the quality of roof rainwater and explored membrane fouling mechanisms from a novel perspective by coupling variations in interfacial properties on the membrane surface and a membrane fouling model. The results showed that the removal efficiencies of SS, COD, NH3-N, TN, and TP in EC-CM reached 99.5 %, 80.8 %, 27.8 %, 35.1 % and 99.7 %, respectively, fully meeting the re-utilization standards in China. However, EC-CM only slightly improved the normalized flux compared to CM alone, suggesting that EC-CM did not effectively alleviate membrane fouling. To further investigate the membrane fouling mechanisms in EC-CM, comparative studies were conducted using 120 min of CM alone (CM-120), 60 min EC-CM and 60 min CM alone (EC-CM-60 + CM-60), and 120 min of EC-CM (EC-CM-120). The results indicated that EC could sharply aggregate particles into micro flocs and effectively remove fulvic acid-like and humic acid-like substances in organic matter. This process shifted the initial membrane fouling mechanisms from standard and complete blockage in CM alone to complete blockage in EC-CM. During this period, the normalized flux of EC-CM decreased more rapidly than that of CM alone due to larger interfacial energy of micro flocs-CM, leading to more severe chemical irreversible fouling. As the EC process continued, the micro flocs gradually evolved into larger flocs, which accumulated on the membrane surface and formed a cake layer, thus transitioning the fouling mechanism to cake filtration. Due to lower interfacial energy between flocs, EC-CM exhibited less chemical reversible fouling compared to CM alone. Furthermore, larger flocs with lower fractal dimension would form a looser cake layer compared to primary particles, leading to a reduction in physical reversible fouling. Based on the membrane fouling mechanisms mentioned above, the normalized flux was improved to 0.72 by optimizing the operational mode of EC-CM. These findings provide a promising alternative for rainwater re-utilization and offer valuable insights into the membrane fouling mechanisms in EC-CM.

A comprehensive monitoring of urban drainage network (UDN) is essential for maintenance, management, and sustainable urban development. However, limited sensor deployment hinders the acquisition of sufficient information. Conventional deep learning methodologies can predict and correct monitored data but struggle with unobserved data. Hydraulic models can simulate behaviors but face data collection challenges and low real-time performance. To address these issues, a novel spatiotemporal graph convolutional network (STGCN) model, based on graph neural networks, is proposed to reconstruct a real-time information system for UDNs. By extracting fundamental elements from limited monitoring data and UDN topology, the STGCN model effectively reconstructed unmonitored node data. The experimental results showed that the training efficiency and reconstruction accuracy of the model could be optimized by reducing the spatial data dimensionality to 0.6, adopting a passive-masked training strategy with a ratio of 4:3 for model-training sensors to loss-calculation sensors, and using a historical data input length of 3 h. This approach allowed for the reconstruction of water levels for 527 unmonitored nodes using only seven monitoring nodes, with a median mean absolute error of 0.038 m and an accuracy of 71.3 %. These results demonstrate that the STGCN model can accurately reconstruct unmonitored node data using low monitoring-node density and basic network topology, offering a practical solution to datadriven challenges in intelligent UDNs. The source code is available at https://github.com/holylove9412/ UDNs_STGCN_model.

Direct oxidation of per- and polyfluoroalkyl substances (PFAS) necessitates excessive energy or prolonged treatment, while reductive defluorination effectively cleaves C-F bonds. However, strict anaerobic requirements hinder its practical implementation. Herein, a photoelectrocatalytic-peroxymonosulfate (PEC-PMS) integrated system was developed for perfluorooctanoic acid (PFOA) degradation under ambient conditions. The PEC-PMS system with the sophisticated MoSe2/TiO2 photoelectrode demonstrated 93.6 % PFOA removal within 40 min. Density functional theory (DFT) calculations revealed enhanced PFOA adsorption on MoSe2/TiO2 (Eads = -4.25 eV) compared to TiO2 (Eads = -0.89 eV). Furthermore, the Mo4+/Mo5+ redox pairs promoted PMS activation to accelerate reaction kinetics. The quenching experiments and electron paramagnetic resonance spectra elucidated the crucial role of electrons (63.7 %) and superoxide radicals (42.2 %) during the degradation. Moreover, DFT calculations and intermediate product analyses clarified the main degradation pathway of PFOA. PFOA reacted with electrons to generate C7H15· (Gibbs free energy, ΔG = -0.267 eV/mol), which was subsequently oxidized by superoxide radicals (ΔG = -4.379 eV) to form short-chain PFAS. Overall, our investigations achieved efficient PFOA elimination under air conditions and clarified their degradation mechanisms, providing a new perspective for the treatment of PFAS-contaminated wastewater.

This study developed novel polyferric titanium chlorides (PFTC) with varying Fe/Ti ratios and basicity (B) to achieve safe and effective surface water treatment. The formation of Fe-O-Ti was confirmed through the characterization of PFTC and its impact on physicochemical properties and coagulation performance was thoroughly investigated. Additionally, the molecular-level coagulation mechanism was elucidated. The results demonstrated that PFTC exhibited remarkable stability, with a distinct pH-stable phase during alkaline titration. PFTC showed excellent bridging adsorption capacity, achieving bovine serum albumin (BSA) removal efficiency of 78.33%. The flocculation rate increased to more than 222%, producing larger, denser flocs with superior settling performance, while posing no environmental risks to treated water. XPS and FTIR analyses revealed that hydrogen bond was the primary mechanism driving bridging adsorption. Molecular docking analysis indicated that PFTC hydrolysates formed stronger hydrogen bonds with higher binding energy at key BSA residues compared to polyferric chloride (PFC). According to XDLVO theory, the dominant hydrogen bond range between PFTC and BSA was more than 2.75 times greater than that of PFC and BSA. The hydrogen bond domain expansion effect, coupled with robust hydrogen bond, overcame distance barriers, enabling PFTC to establish strong bridging adsorption interactions with a broader range of BSA molecules, thereby enhancing coagulation efficiency. This study provides valuable insights into the interaction mechanisms between PFTC and BSA, supporting the practical application of polymeric metal composite coagulants.