Chain Segments Research Articles

Chain Friction and Lubrication Balanced Ultra-Tough Polyacrylates With Wide-Span Switchable Stiffness for Strain-Programmable Deformation.

Natural mollusks perform complex mechanical actions through reversible large-strain deformation and stiffness switching, which are challenging to achieve simultaneously in synthetic materials. Herein, it is shown that a set of polyacrylates designed according to a chain friction and lubrication balanced strategy showsultra-stretchability (λ up to 324), high resilience (near 100% recovery at strain ≥ 100), and wide-span stiffness switching (up to 2073 times). The typical emulsion polymerization method and casting technique are adopted to fabricate the polyacrylate films. Quaternary ammonium surfactants are used as the emulsifier and reserved in the polymer matrix to enhance the chain segment lubrication with their long alkyl group but improve the whole chain friction through the formation of nano-eutectics. These polyacrylates undergo multimodal mechanical responses, including temperature- or time-programmed deformation and load-bearing like artificial muscles. This molecular design principle and synthetic method provide a robust platform for the fabrication of ultra-tough polymers for soft robots with multiple customized functions.

Protein folding, protein dynamics and the topology of self-motions.

It has long been recognized that segments of the protein main chain are like robotic manipulators and inverse kinematics methods from robotics have been applied to model loops to bridge gaps in protein comparative modelling. The complex internal motion of a redundant manipulator with fixed ends is called a self-motion and its character is determined by the relative position of its ends. Self-motions that are topologically equivalent (homotopic) occupy the same continous region of the configuration space. Topologically inequivalent (non-homotopic) regions are separated by co-regular surfaces and crossing a co-regular surface can result in a sudden dramatic change in the character of the self-motion. It is shown, using a five-residue type I β-turn, that these concepts apply to protein segments and that as the ends of the five-residue segment come closer together, a co-regular surface is crossed, and the structure is locked in to becoming either a type I or type I' turn. It is also shown that the type II turn is topologically equivalent to the type I' turn, not the type I turn. These results have implications for both native-state protein dynamics and protein folding.

A planning model for coal power exit scales based on minimizing idle and shortage losses: A case study of China

Owing to the rising energy demand and coal dependency in developing countries, the losses incurred from coal power exit are substantial, leading to a low willingness to exit and a high risk of tragedy of the commons. Concurrently, the normalization of peak loads and increasing penetration of renewable energy have exacerbated the contradiction between the overall electricity surplus and peak power shortages in these countries. In response to these challenges, we propose an optimal planning model for a coal power exit scale based on the minimization of losses from idle coal power and industrial power shortages. The main findings are presented as follows: First, compared with the coal power exit models guided by the energy trilemma, our model can reduce losses (the primary demand in developing countries) by at least 22 %, and, in some scenarios, it can increase the exit scale by up to 147 GW. Second, unlike existing methods that measure the overall impact of power shortages, our approach is better at capturing industries' production loss characteristics, which is important for developing countries (positioned in the production segment of the industrial chain), including the evolution patterns of resource and time losses, recovery trajectories of power interruptions, and main influencing factors. Third, China's optimal coal power exit scale for 2030 fluctuates between −7 and 282 GW, with total losses between 48.34 and 188.86 billion yuan. This study provides quantitative tools and decision-making references for optimizing coal power exit and power use.

Enhancing productiveness in E-commerce through machine learning: Challenges, Future Perspectives, and a MATLAB-Based Approach

The rapid growth of e-commerce has created an urgent need for more productive and efficient systems to handle the increasing complexity of online transactions and consumer behaviour. Machine Learning (ML) offers a transformative approach to enhancing productiveness in e-commerce by optimizing processes such as personalized recommendations, dynamic pricing, customer segmentation, and supply chain management. This article explores the integration of ML-driven initiatives in e-commerce, addressing key challenges such as data privacy, algorithmic bias, and the computational demands of large-scale ML applications. A MATLAB-based approach is proposed for developing and implementing these ML models, leveraging MATLAB’s robust toolboxes for data analysis, model training, and system simulation. Through an extensive literature review, this study highlights the current state of ML in e-commerce, identifies existing challenges, and discusses future perspectives. The introduction of ML-driven strategies not only improves operational efficiency but also enhances customer satisfaction, ultimately driving productivity in the highly competitive e-commerce landscape. The findings of this article are expected to provide valuable insights for both academic researchers and industry professionals aiming to harness the full potential of ML in e-commerce.

Mechanistic analysis of hydrogen-rich Co-gasification of pine wood and polypropylene-based waste masks using Fe/Dol catalyst

Disposable masks, predominantly made of polypropylene melt-blown fabric, present a significant environmental challenge due to their large volume and resistance to natural degradation. This study explores the co-gasification of forestry waste, specifically pine wood, and waste masks to enhance biomass gasification efficiency while enabling the high-value utilization of waste materials. The Fe/Dol catalyst, prepared by loading transition metal Fe onto calcined dolomite using the impregnation method, was tested in a two-stage fixed-bed gasification system. Steam was employed as the gasifying agent. The study systematically examines the effects of steam flow rate, gasification reforming temperature, the mixing ratio of pine wood to masks, and Fe loading on the catalyst's performance in gas-phase and liquid-phase product formation.Characterization analyses revealed that Fe oxides facilitate the cleavage of aromatic rings in aromatic compounds, leading to the formation of two-carbon chain segments and promoting the production of ethylene and propylene from aliphatic hydrocarbons. Additionally, the catalyst enhanced tar cracking, generating free radicals and ring bonds. Experimental results indicate that at a steam flow rate of 3 mg/min, a gasification temperature of 850 °C, a pine wood to mask mixing ratio of 1:2, and an Fe loading of 8 %, the hydrogen (H2) volume fraction reached 52.48 %, with a gas yield of 1.67 m³/kg and a hydrogen production rate of 78.25 g/kg.

Solvation Regulation Reinforces Anion-Derived Inorganic-Rich Interphase for High-Performance Quasi-Solid-State Li Metal Batteries.

Solid-state polymer lithium metal batteries are an important strategy for achieving high safety and high energy density. However, the issue of Li dendrites and inherent inferior interface greatly restricts practical application. Herein, this study introduces tris(2,2,2-trifluoroethyl)phosphate solvent with moderate solvation ability, which can not only complex with Li+ to promote the in-situ ring-opening polymerization of 1,3-dioxolane (DOL), but also build solvated structure models to explore the effect of different solvation structures in the polymer electrolyte. Thereinto, it is dominated by the contact ion pair solvated structure with pDOL chain segments forming less lithium bonds, exhibiting faster kinetic process and constructing a robust anion-derived inorganic-rich interphase, which significantly improves the utilization rate of active Li and the high-voltage resistance of pDOL. As a result, it exhibits stable cycling at ultra-high areal capacity of 20 mAh cm-2 in half cells, and an ultra-long lifetime of over 2000h in symmetric cells can be realized. Furthermore, matched with LiNi0.9Co0.05Mn0.05O2 cathode, the capacity retention after 60 cycles is as high as 96.8% at N/P value of 3.33. Remarkably, 0.7 Ah Li||LiNi0.9Co0.05Mn0.05O2 pouch cell with an energy density of 461Wh kg-1 can be stably cycled for five cycles at 100% depth of discharge.

The Hydrogen Bonding in the Hard Domains of the Siloxane Polyurea Copolymer Elastomers.

For probing the structure-property relationships of the polyurea elastomers, we synthesize the siloxane polyurea copolymer elastomer by using two aminopropyl-terminated polysiloxane monomers with low and high number-average molecular weight (Mn), i.e., L-30D and H-130D. To study the influence of the copolymer structures on the film properties, these films are analyzed to obtain the tensile performance, UV-vis spectra, cross-sectional topographies, and glass transition temperature (Tg). The two synthetic thermoplastic elastomer films are characterized by transparency, ductility, and the Tg of the hard domains, depending on the reacting compositions. Furthermore, the film elasticity behavior is studied by the strain recovery and cyclic tensile test, and then, the linear fitting of the tensile data is used to describe the film elasticity based on the Mooney-Rivlin model. Moreover, the temperature-dependent infrared (IR) spectra during heating and cooling are conducted to study the strength and recovery rate of the hydrogen bonding, respectively, and their influence on the film performance is further analyzed; the calculated Mn of the hard segment chains is correlated to the macroscopic recovery rate of the hydrogen bonding. These results can add deep insight to the structure-property relationships of the siloxane polyurea copolymer.

Control over phase structures’ evolution within the novel organic–inorganic hybrid system for achieving a comprehensive thermal, mechanical, and dielectric properties

Significant challenges persist in developing high-performance, wave-transparent capable of operating above 500 ℃ using organic–inorganic hybrid materials. This study introduced a novel, highly reactive terminal carborane monomer, 4-(3-carborylphenyl) phthalonitrile (CB-Ph), to create a cross-linked network structure and inorganic phase. By integrating this with the conventional high-performance poly (phthalazine ether nitrate ketone) (PPENK), a novel organic–inorganic hybrid system was successfully constructed. Simultaneously, the modifications in the inorganic layer and phase structure of the material with increasing CB-Ph content were examined through nanoindentation and SEM analysis systems, establishing a structural foundation for optimizing the balance between thermal resistance, mechanical strength, and dielectric properties (balance of T-M−D). The thermal performance testing results indicates that the hybrid materials achieved high glass transition temperatures (Tg exceeding 500 ℃). This enhancement is attributable to the synergistic effects of cyanide side group micro-crosslinking and the phthalonitrile crosslinking network, which collectively restricted the movement of chain segments. The P-CB50 resin (PPENK+50 wt% CB-Ph), with its distinctive transition phase structure, boasts the most outstanding comprehensive performance. In terms of thermal stability, it not only features a Tg surpassing 500 ℃ In terms of thermal stability, it not only has a Tg exceeding 500 °C, but also loses only 5 % weight at 599.3° C in a nitrogen atmosphere (Td5%–N2 = 599.3 °C). Mechanical testing reveals that the flexural strength of the P-CB50 composite reaches an impressive 384.3 MPa, while the impact strength attains a significant 109.4 KJ/m2. Even at temperatures as high as 500 ℃, the dielectric constant of the P-CB50 composite material remains below 4, underscoring its superior high temperature wave-transparent properties. These results have firmly established a correlation between the phase structure of the hybrid system and the comprehensive performance of T-M−D, thereby laying a solid foundation for the development of high-temperature resistant and wave-transparent materials with enhanced overall performance.

Barnacle-inspired amphipathic high strength adhesives under-water/oil

Adhesives designed for bonding in liquid environments have a broad application prospect. In general, amphiphilic polymer structures are important research objects for underwater bonding. And in the study of underwater adhesives, it was found that they can quickly dispel or absorb interfacial water and form reliable bulk strength and adhesion strength. However, achieving strong adhesion in both water-based and oily environments poses a significant challenge. In this work, an adhesive inspired by barnacles that can meet the bonding requirements in both water-based and oily environments has been prepared. Hydrophilic (polyethylene glycol (PEG)) main chains and hydrophobic (1-Octadecyl thiol (ODT)) side chains are simultaneously integrated into the polyurethane structure. Different from the past, hydrophobic and hydrophilic segments are included in the hard segment and soft segment microregion, respectively; At the same time, both hydrophilic and hydrophobic chain segments have strong crystallization, which greatly strengthens the driving force of molecular segments migration and phase separation compared with ordinary hydrophilic/hydrophobic structures. Water-based and oil-based solvents drive hydrophilic and hydrophobic molecular chains to diffuse to the surface, respectively, which enhances the adhesive strength to hydrophilic and hydrophilic surfaces, respectively. In comparison to the adhesion strength observed in air, the adhesion strength of the adhesive to polymethyl methacrylate (PMMA) increases by 1.72 times in oil environments (from 1.02 to 1.75 MPa). Similarly, the adhesion strength to aluminum (Al) increases by 2.23 times under water (from 1.82 to 4.04 MPa). These findings suggest that the regulation strategy for polymer chains employed in this study holds great potential for advancing adhesive performance in diverse environments.

Bio-based polyurethane triboelectric nanogenerator with superior low-temperature self-healing performance for unmanned surveillance

Damaged flexible triboelectric nanogenerators face difficulties in autonomous healing at low temperatures, limiting their application range. Impeded dynamic network reconstruction presents a challenge in developing materials for autonomous low-temperature healing. This study constructed a multi-dynamic network utilizing both strong and weak hydrogen and disulfide bonds to develop a biobased polyurethane elastomer (PBES-U, prepared from biobased monomers such as itaconic acid, sebacic acid, etc.), featuring a cross-linked network capable of cryogenic self-healing, superior toughness, and reprocessability. This elastomer extends to 1100 % of its original length, achieving 90 % self-healing efficiency at temperatures down to −10 °C due to the low glass transition temperature (Tg, −30 ℃) achieved by modulating the flexibility of chain segments. Consequently, a bio-based TENG (LS-TENG) was produced using this elastomer as a positive friction layer through a dynamic interfacial interlocking method. The results reveal that LS-TENG achieves a notable power density of 12.2 mW/m2, an output voltage reaching 160 V, and a 98 % output voltage recovery post-low-temperature self-healing. Furthermore, a non-contact LS-TENG-based monitoring system was developed with significant potential for applications in battlefield sensing, wildlife monitoring, and intelligent driving.

Research of influence of diluent on the mechanical behavior of triaxial warp-knitted composites

The composites are prepared by different processes of reinforcement and matrix, which are affected by the properties of reinforcement and matrix. In this study, composite specimens were fabricated using vacuum-assisted resin infusion (VARI) with varying mass fractions (0%, 5%, 10%, and 15%) of a diluent mixed with the resin and curing agent, serving as the matrix. Triaxial warp-knitted glass fabric was employed as the reinforcement material. The impact of the diluent mass fraction on the bending, impact, and creep properties of the composites was investigated. The least squares fitting method was applied to analyze the experimental data, leading to the establishment of a mathematical model correlating the diluent mass fraction with the bending strength. The optimal diluent mass fraction for achieving the best bending properties was determined. Furthermore, the failure mechanisms of the composites were examined through an analysis of their thermodynamic properties, reaction principles, and fracture morphologies. The results show that the epoxy group in the diluent will be connected to the cross-linking network structure of epoxy resin by ring-opening reaction, and excessive addition will lead to the increase of flexible chain segments, which makes the mechanical properties of the specimens increase first and then decrease. The mathematical model was verified by experiments, and the mass fraction of diluent was 9.65% when the bending property was optimal.

Scale-Bridging Mechanics Transfer Enables Ultrabright Mechanoluminescent Fiber Electronics.

Mechanoluminescent (ML) fibers and textiles enable stress visualization without auxiliary power, showing great potential in wearable electronics, machine vision, and human-computer interaction. However, traditional ML devices suffer from inefficient stress transfer in soft-rigid material systems, leading to low luminescence brightness and short cycle life. Here, we propose a tendon-inspired scale-bridging mechanics transfer mechanism for ML composites, which employs molecular-scale copolymerized cross-linking and nanoscale inorganic nanoparticles as hierarchical stress transfer sites. This strategy effectively reduces the dissipation of stress in molecular chain segments and alleviates local stress concentration, increases luminescence by 9 times, and extends cycle life to more than 10,000 times. Furthermore, a scalable (kilometer-scale) anti-Plateau-Rayleigh instability manufacturing technology is developed for thermoset ML fibers, compatible with various existing textile techniques. We also demonstrate its system-level applications in motion capture, underwater interaction, etc., providing a feasible strategy for the next generation of smart visual textiles.

A novel model for tracking copolymerization kinetics: Sequence structure quality evaluation

AbstractPrecise control over sequence structure in copolymers is essential for chemical product engineering. The complexity of sequence structures results in the challenging characterization of monomer sequences. Herein, a chemical composition model (CD model) is developed to record the distribution density of monomers in the chain segment, where the deviation of the chemical composition function between a copolymer and its ideal sequence structure can directly map the sequence structure quality. The application of the CD model in randomly generated virtual copolymers demonstrates that the model has great sensitivity and discrimination to evaluate sequence structures accurately. Furthermore, the CD model is combined with the kinetic Monte Carlo algorithm to explicitly track the evolution of sequence structure quality in the copolymerization process. The CD model provides an insight into the evolution of sequence structure, which is conducive to building the bridge between molecular structure and properties for the development of chemical product engineering.

Analyzing the green hydrogen value chain against the sustainable development goals

The emerging green hydrogen value chain provides an opportunity to develop joint sustainable strategies between different countries and implement measures to mitigate potential adverse effects. We analyze whether the green hydrogen value chain can aid in meeting the objectives outlined in the 2030 Agenda. The Value Chain Assessment methodology that we developed enables the identification of direct and indirect influences, and the categorization of positive and negative effects, of each segment (production, transportation, and end-use) of the green hydrogen value chain on the 17 SDGs and their 169 targets. We also analyze the associated temporal dimensions and reciprocal interdependences, to clarify the dynamics of the value chain over time and across different geographical scales. We present a strategic framework that can help in fostering the green hydrogen value chain for the implementation of sustainable development. We find that the use of green hydrogen can clearly accelerate progress on the SDGs in the short-term, but adverse effects could arise in the medium- to long-term. The realization of the green hydrogen value chain requires synchronized investments and policies across space and time.

The influence of the molecular structure of binary block‐type styrene‐butadiene rubber on dynamic mechanical properties under normal and high‐pressure conditions

AbstractThrough anionic two‐stage polymerization, block‐type styrene‐butadiene rubber (SSBR) with systematically regulable low‐temperature loss peaks is successfully prepared. The influence of 1,2‐Bd unit in the soft segment of block‐type SSBR on mechanical properties, dynamic mechanical properties, and microscopic morphology is studied, while pressure factors are introduced into dynamic mechanical studies. The block‐type SSBR with a soft segment containing 21.9 wt% of 1,2‐Bd exhibits the highest tensile strength, elongation at break, and tear strength. Under atmospheric pressure, the soft segment 1,2‐Bd unit influences the dynamic mechanical properties by altering the chain segment's motion loss capability. As the mass fraction of 1,2‐Bd increases from 21.9 to 58.6 wt%, tanδmax increases, the glass transition temperature of the soft segment increases from −59.0 to −18.9°C. Additionally, influenced by thermodynamic compatibility, the microscopic morphology transitions from strong separation to weak separation. Pressure affects dynamic mechanical properties by altering the free volume of the chain segments. Pressure reduces tanδmax, increases Tg, and raises the average Tg of the soft segment by 11°C. The K value of the linear equation representing the relationship between the soft segment Tg and the mass fraction of 1,2‐Bd is unaffected by pressure.

Refined kinetic model for the simulation of polycarbonate synthesis via continuous melt transesterification

This paper establishes a kinetic model for the polymerization and condensation occurring during the melt transesterification of bisphenol A (BPA) and diphenyl carbonate (DPC). The model is based on molecular fragments and functional groups, treating polymers as an assembly of four types of chain segments. This study delves into the reaction mechanisms underlying the polycondensation of BPA and DPC, offering fresh perspectives on the process. Kinetic equations pertinent to the polycondensation mechanism were deduced from the analysis and then rigorously tested against experimental data to ascertain their validity. Kinetic constants emerged through the fitting of this experimental data, lending credence to the model’s accuracy. Utilizing the Aspen Plus software, the model was applied to simulate the annual production of 100,000 tons of polycarbonate (PC). The simulation facilitated the optimization of the operating conditions for each reactor, yielding valuable insights for scaling up to industrial production.

CADS as a Decision-making Tool: Developing an Oculoplastic Management Algorithm for Facial Nerve Palsy.

The Cornea, Asymmetry, Dynamic, Synkinesis (CADS) score is a validated grading score for periocular involvement in facial nerve palsy (FNP). We conducted a retrospective review of FNP cases, including initial CADS scores and subsequent ophthalmic interventions. The results were used to inform the development of an oculoplastic management algorithm for FNP. Single-center retrospective cohort study of patients with FNP referred to a tertiary unit between 2016 and 2022. Data collected included demographic data, etiology of FNP, treatment initiated, and CADS grading at each visit. Adult patients with ≥6 months of follow-up were included, and cases were excluded if ocular surface or oculoplastic procedures were performed elsewhere prior to the initial review by the unit. Of 408 consecutive new patients with FNP, 80 fulfilled inclusion criteria (mean age 57 years, range 21-83 years). Presentations of FNP were unilateral in 98.8% (79/80), with an underlying preganglionic etiology in 75.0% (60/80). At the initial review, surgery was recommended for 61.3% (49/80) of cases. Subgroup analysis of surgical cases for each CADS domain showed 46.9% (23/49) had C-score ≥2, which was predictive of upper lid surgery requirement (e.g., upper lid platinum segment chain; levator recession). About 63.2% (31/49) had an A-score ≥1 which predicted for lower lid surgery requirement (e.g., retractor recession, lower lid sling, medial canthal tendon plication, and lower lid full thickness skin graft) as well as a brow lift. Almost 79.6% (39/49) had a D-score ≥2, which was associated with both upper lid and lower lid surgery requirements. Also, 59.2% (29/49) had an S-score of ≥1 however, this was not associated with the surgical requirement, highlighting a different approach compared with the other CADS domains. This study represents a large cohort of patients followed up with a validated ophthalmic-specific FNP grading scale. This was utilized to develop a CADS-based management algorithm to help guide decision-making for surgical intervention versus medical management in FNP.

Synthesis and properties of bio-based semi-aromatic heat-resistant copolymer polyamide 5T-co-6T

ABSTRACT Herein, poly(pentanediamine terephthalamide) (PA5T) homopolymer was synthesized via a salt-forming reaction+solid state polycondensation method using bio-based 1,5-pentanediamine and terephthalic acid as the primary raw materials. To address the issue of its narrower processing window, poly(hexamethylene terephthalamide)(PA6T), which also cannot be melt processed due to the processing window is negative, was introduced into its molecular chain to synthesize poly (pentanediamine/hexanediamine terephthaloyl) (PA5T-co-6T) copolymers. The structures were investigated by Fourier transform infrared spectroscopy (FTIR) and nuclear magnetic resonance carbon spectroscopy (13C-NMR). Furthermore, the melting temperature, crystallization temperature, thermal stability, and crystal growth mode of the polymer were tested and analyzed using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and wide-angle x-ray diffraction (WAXD), respectively. The results demonstrate that the crystal growth mode gradually changes from three-dimensional spherical growth to two-dimensional disk-like or three-dimensional spherical growth with the increase of 6T chain segment content. Simultaneously, the crystallization temperature, melting temperature, and crystallization rate of the polymer all showed a trend of decreasing first and then increasing, which was due to the combined effects of the increase in the content of 6T chain segments on the molecular-chain structure and crystal structure of the polymer. Bio-based PA5T-co-6T has excellent heat resistance and a wider processing window than PA5T and PA6T, which possesses great application prospects in the fields of automotive, electronic appliances, and LED optics.

Assessing refrigerated preservation performance using Listeria predictive microbiology models and temperature data: Refrigerator performance indicator and time-temperature equivalent.

Time-temperature data for queso fresco (QF) cheese varieties stored in a residential refrigerator operating at 5°C and a predictive microbiology secondary model for Listeria monocytogenes in QF were used to estimate a refrigerator performance indicator (RPI) of microbial preservation. RPI values were used to assess how compressor technology (single [SS] and variable speed [VS]), ambient temperature (21.1°C [LT] and 32.2°C [HT]), and refrigerator load (22.5kg regular load and 39kg higher load) affected preservation performance. All deterministic and probabilistic RPI estimations slightly exceeded the desirable 1.0 value, i.e., the variable temperatures for the QF kept in the refrigerator were worse than keeping it constantly at the temperature recommended by food safety agencies for QF. Furthermore, the mean comparison of estimates of the time-temperature equivalent indicator previously developed by French researchers showed similar behavior to those observed for RPI. Finally, statistical analysis showed that Tambient was the factor with the highest impact on refrigerator performance because of its impact on the sample temperature increase during door openings and when exposed to ambient temperature during product use. This highlights the need to reduce the time for product temperature recovery by improving the compressor operation logic. Also important are consumer behavior changes such as a reduction in product exposure to ambient temperature and in the door opening duration and frequency. PRACTICAL APPLICATION: This study demonstrated how a quantitative tool (RPI) can assess refrigerator preservation performance. Although the findings presented can be applied to any cold chain segment, the data used was collected for its weakest link, the domestic refrigerator. Surveys show that 77% of them operate above the recommended 4°C. The RPI methodology is ready for use by refrigerator designers to assess performance improvements possible by modifications of the compressor operation logic. Moreover, it can be integrated into smart-hubs monitoring the frequency and duration of refrigerator door openings to inform consumers when their habits are compromising the preservation performance of the refrigerator.

Construction of low-resistance nano-transport channels with UiO-66-(NH2)2 “transmembrane” in polyamide layer structure for efficient nanofiltration

Metal-organic frameworks (MOFs) is always a research hotspot as the modifier for fabrication of thin-film nanocomposite (TFN) membrane due to their excellent chemical tunability and suitable pore size. However, the traditional strategy for the involvement of MOFs into interfacial polymerization (IP) process has its limitations, as the addition of MOFs only serve to modulate the structure of the polyamide (PA) layer and to optimize the transport path of water molecules, rather than play an important role in selectively sieving solutes. To solve the problem that MOF embedded under the PA layer cannot directly participate in solute sieving, this study designed a “transmembrane” structure of MOF in the PA layer. Here, the feasibility of 1,3,5-Benzenetricarbonyl chloride modified UiO-66-(NH2)2 was verified based on Gibbs free energy calculations. By adding chlorinated UiO-66-(NH2)2 nanomaterials in the dual IP process, a high-throughput nanofiltration membrane was innovatively constructed. In contrast to conventional thin-film composite membrane prepared by only one IP process, the sieving mechanism no longer relied solely on the free volume of the PA chain segments. Instead, it was determined by the combination of the pore channels of UiO-66-(NH2)2 and the matrix gaps. Based on density functional theory (DFT), the calculated diffusion energy barriers of H2O and Na2SO4 in UiO-66-(NH2)2 and PA matrices reveal the reasons for the improvement of water flux and changes in retention rate of TFN membranes. In addition, the gap size between PA-MOFs was determined by comparing the solvation and de-solvation structures of dye molecules. This work provides a new theoretical basis for explaining the changes in the separation performance of TFN membranes, and offers new ideas for the development of novel TFN membrane structures.