Abstract Twin-screw extruders are essential for polymer processing, as screw element design critically influences dispersion quality. Conventional constant-pitch elements exhibit limited axial flow modulation, which restricts mixing intensification per unit length. This paper proposes a variable-pitch screw element that features periodic alternation between 25-mm and 75-mm pitches over five cycles within a 50-mm length. Small-pitch regions generate intensive shear for agglomerate breakdown, while large-pitch regions provide elongational flow for redistribution. Numerical simulations of PA66 processing demonstrate a 58% higher peak shear rate and a 73.68% longer residence time. The results demonstrate enhanced mixing capabilities that are beneficial for PA66 nanocomposite preparation and fiber spinning applications.

Viscoelastic materials differ fundamentally in their retardation spectrum characteristics. Conventional fractional-order models cannot accommodate such spectral diversity within a unified framework. To address this, a generalized ψ -Caputo fractional-order Burgers ( ψ -CFB) model is developed in this work, which enables flexible kernel function selection according to material characteristics. A spectral width factor Λ (t) is introduced to establish a mathematically grounded kernel function selection criterion. The power-law kernel is suggested for broad-spectrum materials, the exponential kernel for narrow-spectrum materials, and the logarithmic kernel for materials with intermediate spectral width. The Kachanov damage theory and the Schapery nonlinear viscoelastic theory are incorporated according to the specific characteristics of the target materials. Three representative viscoelastic materials with distinct retardation spectrum features, namely asphalt, polylactic acid (PLA), and polycarbonate (PC), are selected for assessment. The results under unconstrained single-stress fitting show that the ψ -CFB model provides accurate fitting for asphalt under high-stress conditions (Adj-R2 = 0.9995, MAPE = 0.598 ψ -CFB parameters with a few stress or data-scale factors, and the results confirm that the proposed model also agrees with the experimental data under this joint-fitting scheme.

Temperature control is crucial for magnetic nanofluid-based thermotherapy in stenotic vessels. Traditional boundary conditions lack the adaptability to local flow variations in complex geometries. To overcome this limitation, we introduce a novel shear-responsive boundary condition that dynamically couples boundary quantities with the local wall shear rate. Using this framework, a multi-physics analysis is performed to study the heat transfer enhancement in a Cu-Au hybrid nanofluid within a stenotic vessel under an induced magnetic field. This model incorporates the governing equations of momentum, magnetic induction and energy, which are solved numerically via a finite difference scheme. The results indicate that the shear-responsive condition effectively modulates the intensity of the induced magnetic field in response to the local wall shear rate, leading to enhanced heat transfer across various degrees of stenosis. In particular, as the shear-response parameter lambda increases from 0 to 6, the Nusselt number rises consistently across all examined configurations. Meanwhile, the wall temperature increases significantly, even at the stenosis center, primarily attributed to enhanced Joule heating effects. This shear-responsive mechanism shows superior thermal performance compared with conventional fixed boundary conditions and enables effective regulation of wall shear stress through the parameter lambda. This study presents a promising strategy for adaptive thermal management in biomedical applications.

Magnetic solid-phase extraction (MSPE) often suffers from significant efficiency loss in high-ionic-strength matrices, where abundant salt ions compress the electrical double layer and compete for adsorption sites, leading to an unstable extraction performance. Here, we report an ion-interference-resistant MSPE strategy that integrates a rationally engineered carbon-based sorbent with an analytical concept of ionic regulation. The sorbent incorporates nitrogen dopants and oxygen vacancy functionalities that act as controllable ion-buffering centers, selectively immobilizing Na+ and Cl- ions to stabilize the interfacial electrostatic environment. Meanwhile, a hydroxyl-enriched surface layer facilitates hydrogen bonding and π-π interactions, ensuring the efficient and selective adsorption of polar analytes such as aflatoxin B1 (AFB1). This hierarchical architecture effectively decouples ionic adsorption from target binding, maintaining robust electrostatic microenvironments under saline conditions. The optimized MSPE system retained over 90% of its efficiency at 0.1 mol/L NaCl─approximately a 4-fold improvement in salt tolerance relative to conventional magnetic carbons. When applied to trace detection of AFB1 in high-salinity food samples (oyster sauce, fermented cheese, and doubanjiang), the method achieved recoveries of 99.7%-108.2% and a detection limit of 16.0 pg/g, far outperforming commercial HPLC sorbents. This work establishes a general methodological framework for ionic regulation in MSPE, offering a robust and practical solution for trace analysis in complex high-salinity matrices.

We derive the explicit Poisson kernel of Stokes equations in the half space with nonhomogeneous Navier boundary condition (BC) for both infinite and finite slip length. By using this kernel, for any q>1, we construct a finite energy solution of Stokes equations with Navier BC in the half space, with bounded velocity and velocity gradient, but having unbounded second derivatives in L^q locally near the boundary. While the Caccioppoli type inequality of Stokes equations with Navier BC is true for the first derivatives of velocity, which is proved by us in [CPAA 2023], this example shows that the corresponding inequality for the second derivatives of the velocity is not true. Moreover, we give an alternative proof of the blow-up using a shear flow example, which is simple and is the solution of both Stokes and Navier–Stokes equations.

Based on the mechanism of physical memory effects, an improved fractional Zener constitutive model is proposed to describe the boundary layer characteristics of viscoelastic fluids in magnetohydrodynamic (MHD) environments. The model employs a mixed-order structure where instantaneous elastic response maintains integer-order characteristics, while delayed elastic response and viscous flow introduce fractional operators. This design simultaneously captures the stress relaxation and strain lag characteristics of the fluid. The established model is numerically solved using the finite difference method together with a fast algorithm, and the regulatory mechanisms on the fluid boundary layer characteristics are investigated. The research reveals that the proposed model achieves more comprehensive characterization of boundary layer behavior compared to conventional models, while exhibiting unique saturation effects in magnetic field regulation. The fractional parameter α governs stress relaxation, with larger values enhancing viscous behavior and producing thicker boundary layers. Parameter β controls strain memory intensity, promoting greater flow mobility. Rheologically, a larger stress relaxation time λ1 enhances elastic character and compacts boundary layers, while an increased strain lag time λ2 extends microstructural adjustment time, manifesting as thicker boundary layers. This study establishes correlations between model parameters and physical phenomena, providing a theoretical framework for understanding MHD viscoelastic fluid boundary layer behavior.

Aflatoxin B1 (AFB1) threatens food safety due to its persistence in oils. Carbon-based solid-phase extraction (SPE) methods are effective for detecting AFB1 in aqueous food matrices, but employing it in oils is challenging due to non-polar environments. We developed highly graphitized carbon materials (HGC) with enhanced π-π interactions for AFB1 extraction in oil through a transition metal (Fe, Co, Ni)-assisted carbonization process. Adsorption experiments revealed that FeO/Fe3O4/HGC exhibited a superior AFB1 adsorption capacity of 1179.99 μg g-1, outperforming Ni/Co-HGC and pure carbon by 4-6 times. Density functional theory revealed the electron-deficient graphitized carbon structures supported by magnetic FeO/Fe3O4 clusters enhance π-π interactions with AFB1, with pore filling and hydrophobicity further aiding adsorption. Combining FeO/Fe3O4/HGC-SPE with HPLC-FLD achieved ultra-sensitive AFB1 detection in vegetable oils (2.0 pg g-1 limit). This study provides an effective method for AFB1 detection in vegetable oils, supporting the monitoring and control of contamination to enhance food safety.

During the production of Nylon 6 (PA6) through caprolactam polymerization, approximately 10% extractables remain in PA6 chips at equilibrium state, generating extraction wastewater containing 6-15% caprolactam after hot water extraction. Direct discharge of this wastewater causes significant resource waste and environmental pollution, making its efficient treatment a critical challenge for energy conservation and emission reduction in intelligent chemical manufacturing systems. This study innovatively proposes a multi-effect evaporative concentration-pyrolysis-recovery process based on Mechanical Vapor Recompression (MVR) technology, establishing a systematic thermodynamic model and energy efficiency optimization methodology. Using Aspen Plus, we constructed simulation models for one- to five-effect MVR systems and systematically investigated the phase-change heat transfer characteristics of boiling point elevation (BPE) in caprolactam solutions, revealing the coupled influence mechanism of evaporator stages and heat transfer temperature difference on system energy efficiency. Results demonstrate that the coefficient of performance (COP) reaches optimal values at a controlled temperature difference of 5°C. The three-effect MVR system, when concentrating to 70%, effectively prevents oligomer precipitation while reducing compressor power consumption by 18.3% and fresh steam usage by 11.7% compared to single-effect systems, with a 14.8% improvement in gained output ratio (GOR). Through multi-stage energy cascade utilization and fractional vapor recompression, this process achieves a caprolactam recovery rate exceeding 99.5% with specific energy consumption reduced to 1005 kg/t, representing a 65.6% reduction in comprehensive energy consumption compared to conventional three-effect evaporation processes. These findings provide theoretical foundations and technical support for energy-efficient, high-concentration recovery of caprolactam extraction wastewater, but also offer a digitally modeled, energy-optimized unit operation module that can be integrated into intelligent chemical manufacturing and smart energy management systems, thereby supporting process intensification and contributing to carbon neutrality goals.

This study aims to develop a highly sensitive fire-warning material by synergistically combining graphene oxide (GO) with boron nitride (hBN), renowned for its exceptional thermal conductivity and flame retardancy. Urea and water were employed as precursors to exfoliate and functionalize hBN via a semi-solid-state stone-milling method, yielding amino-functionalized boron nitride nanosheets (BNNS-NH2) possessing a high aspect ratio. Subsequently, BNNS-NH2 was assembled with GO through a layer-by-layer assembly approach to fabricate a BNNS/GO composite membrane. Fire-warning tests were conducted on the composite membrane, unveiling an impressively short fire response time of only 0.2 s and an extended duration of up to 52 s, thus demonstrating its exceptional sensitivity and long-lasting fire-warning performance. Upon exposure to fire, the GO layer within the composite membrane underwent thermal reduction, leading to the formation of electrically conductive reduced graphene oxide (RGO). The high thermal conductivity of the BNNS layer, coupled with strong interfacial bonding, facilitated rapid heat propagation throughout the composite membrane, thereby promoting the thermal reduction reaction of GO and enhancing the response speed. Furthermore, the outstanding flame retardancy of BNNS contributed to the material's persistent fire-warning performance.

For the non-stationary Stokes system, it is well-known that one can improve spatial regularity in the interior, but not near the boundary if it is coupled with the no-slip boundary condition. In this note we show that, to the contrary, spatial regularity can be improved near a flat boundary if it is coupled with the Navier boundary condition, with either infinite or finite slip length. The case with finite slip length is more difficult than the case with infinite slip length.

Axial Flux Permanent Magnet Motors (AFPMM), known for their high power density, energy efficiency, and compact design, hold great potential for widespread use in electric vehicle applications. Despite these advantages, AFPMMs face challenges such as demagnetization of permanent magnets and magnetic insulation layer failure under high-temperature conditions. To mitigate these thermal challenges, this paper introduces a novel cooling structure that incorporates a corrugated spiral flow channel, utilizing nanofluids for enhanced thermal conductivity. The performance of this structure is evaluated and compared with that of the conventional linear spiral flow channel using numerical analysis. An analysis of the structural parameters' influence on fluid flow within the corrugated spiral flow channel is conducted, and a Support Vector Machine (SVM) model along with a Nondominated Sorting Genetic Algorithm II (NSGA-II) are employed to optimize these parameters for the cooling channel. The results demonstrate that the new channel exhibits superior heat transfer performance. Under identical conditions, the implementation of the corrugated spiral flow channel maintained the highest temperature at the windings of the AFPMM at 81.49 °C, which is a reduction of 1.67 °C compared to the conventional linear spiral flow channel.

Pipette tip solid-phase extraction (PT-SPE) as a miniaturized solid-phase extraction technique have a wide range of applications in the field of sample pretreatment. In this study, ionic covalent organic frameworks@cotton (iCOF@cotton) were facilely synthesized by mechanochemical grinding method only in half an hour, and used as the adsorbents of PT-SPE. The synthesized iCOF@cotton not only had high specific surface area, suitable pore structure and cationic charge groups of iCOF that can extract polar targets quickly, but also reduced the problem of high back pressure of PT-SPE by the addition of cotton, thus accelerating extraction time. Combined with high performance liquid chromatographic tandem mass spectrometry (HPLC-MS/MS), an efficient and sensitive method was established for detection of domoic acid (DA, a toxin produced by algae). Under the optimal con-ditions, the proposed analysis method displayed excellent analytical performance, including broad range of linearity (10-1000 pg mL-1), low limit of detection (LOD, 5 pg mL-1), high correlation coefficient (0.9993), satisfactory precision (RSDs <= 6.4 %). In addition, the developed method was applied to the detection of DA in marine samples, and detected trace DA (18.6 pg mL-1) with satisfactory recovery (85.7%-107.2 %). The above results indicated that the prepared iCOF@cotton have great potential as the adsorbents for PT-SPE.

Flower-like particles have attracted much attention due to their efficient surface accessible sites and unique hierarchical porous structure. However, their synthesis is usually challenging and requires complex procedures. Herein, we present a simple method for rapid preparation of flower-like hierarchical porous TiO2 (FHP-TiO2) at room temperature for the first time. This method can accurately control the size of FHP-TiO2 from 150 nm to 400 nm by combining co-assembly and Stober reaction. The formation mechanism and influencing factors of FHP-TiO2 were systematically investigated, and its excellent metal oxide affinity was confirmed by theoretical calculations. Due to its hierarchical porous structure, large surface area and high specificity performance, FHP-TiO2 served as an appealing restricted-access adsorbent for specific and efficient enrichment of molecules with phosphate groups in a complex sample matrix, thereby realizing the quantitative analysis of these important biomolecules by coupling with high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Moreover, compared with other morphologies (rough surface, and hollow dendritic and mesoporous structure) of TiO2 and flower-like SiO2, FHP-TiO2 showed the best affinity binding ability. This research not only presents a novel approach for tunable room-temperature synthesis of FHP-TiO2 with different sizes, but also expands the application of FHP-TiO2 as an appealing sample-enricher for food safety monitoring and early disease diagnosis.

The photoelectric conversion efficiency of photovoltaic thermal (PVT) systems is a key concern in solar energy research. The widespread use of continuous nanofluid cooling in PVT/NPCM (NanoEnhanced Phase Change Material) systems leads to heightened energy consumption. In order to improve efficiency of the PVT/NPCM systems, a two-dimensional transient heat transfer numerical model is established to analyze the PVT/NPCM system with intermittent flow cooling. Corresponding govern equations with boundary conditions are proposed, and numerically solved by using the finite element method. Simulation results are compared with experimental data, showing a deviation of less than 7 %. The findings indicate that the intermittent cooling reduces the flow energy consumption required to drive 2220 L of nanofluid compared to continuous cooling over a 7-h period. Furthermore, under intermittent cooling conditions, the average electrical efficiency stands at approximately 19.7 %. Notably, the electrical efficiency of PVT/NPCM systems employing intermittent flow cooling closely aligns with those employing continuous flow cooling, exhibiting a maximum deviation of merely 0.0348 %. Additionally, intermittent flow cooling emerges as a favorable choice under solar radiation intensities surpasses 1000W/m 2 , enabling a significant reduction in overall energy consumption while maintaining commendable cooling performance.

In this paper, an equivalent circuit model of electro-mechanical converter (EMC) is developed using Cauer circuits, which can be used to improve the response speed of high-speed switching valves (HSVs), and this model can replace the transient analysis method of finite element model with high computational cost and the traditional magnetic circuit model that cannot accurately reflect the eddy current and skinning effect of coils. For EMC with high-frequency operation, the Cauer circuit can be used to describe the eddy currents on the physical layer and the skinning effect of the soft magnetic material. In this paper, a multi-field coupled EMC trapezoidal circuit simulation model is developed, and the reliability of the model is verified by experiments. The model can be used to analyze the energy consumption in order to identify the main optimized components of the EMC, and the genetic algorithm is selected as the optimization method to improve the structure, which leads to the reduction of eddy current losses and the improvement of the overall dynamic response of the EMC.

The optical path error, the position-independent geometric error, and the form and position tolerance of the substrate will lead to position deviations of the laser focus resulting in the inconsistency of the large area micro-structure and limiting the processing range of the femtosecond laser fabrication platform. To realize continuous defocus compensation along the processing trajectory, an autofocus scheme consisting of an optimized depth from focus (DFF) method based on grid division and the bilinear interpolation algorithm is proposed in this paper. The optimized DFF method includes the Laplace-DWT evaluation function combining the advantages of spatial domain and frequency domain sharpness evaluation function, an adaptive focusing window selection method, and an adaptive step length three-step hill-climbing search method. The optimized DFF method was used to obtain the best focus position of each grid point. Compared with the traditional DFF method, the optimized algorithm has higher focusing precision and avoids the disadvantage of time-consuming focusing. Then, to compensate for interpolating points of the processing trajectory, the bilinear interpolation algorithm was introduced to achieve online focusing during two-photon lithography processing. Finally, the feasibility and effectiveness of the auto-focusing scheme were validated by experiments. Through defocus compensation, the sharpness evaluation value of the focus image on the processing trajectory improved by 90%, which indicated the successful focus of the laser beam on the workpiece surface. Moreover, a high-precision and large-area encoded micro-polarizer array with consistent structure were fabricated successfully. This paper provides a simple way to identify and compensate the defocus errors online with high accuracy and efficiency. The proposed method can improve the machining accuracy and quality of the femtosecond laser direct writing.

This paper introduces fractional Brownian motion into the study of Maxwell nanofluids over a stretching surface. Nonlinear coupled spatial fractional-order energy and mass equations are established and solved numerically by the finite difference method with Newton’s iterative technique. The quantities of physical interest are graphically presented and discussed in detail. It is found that the modified model with fractional Brownian motion is more capable of explaining the thermal conductivity enhancement. The results indicate that a reduction in the fractional parameter leads to thinner thermal and concentration boundary layers, accompanied by higher local Nusselt and Sherwood numbers. Consequently, the introduction of a fractional Brownian model not only enriches our comprehension of the thermal conductivity enhancement phenomenon but also amplifies the efficacy of heat and mass transfer within Maxwell nanofluids. This achievement demonstrates practical application potential in optimizing the efficiency of fluid heating and cooling processes, underscoring its importance in the realm of thermal management and energy conservation.

A fluid-assisted fused deposition modeling (FA-FDM) 3D printing technique was proposed and employed to create anisotropically thermally conductive polymer composites (aniso-TCPCs). These composites have precisely controllable heat conduction pathways achieved by spraying boron nitride (BN) on both sides of the FDM 3D printed POE/PP materials. At the same BN content (cBN), the thermal conductivity (lambda) of the aniso-TCPCs is higher than that of the isotropic composites. When cBN = 60 wt%, the lambda of the aniso-TCPCs could reach 1.43 W m � 1 K- 1, improved over 510 % as compared to the POE/PP matrix. Both experimental and simulation results show that the design of the anisotropically thermally conductive pathways can significantly improve the thermal conductivity of the polymer composites for efficient heat dispersion. Overall, the present study would provide a point of reference for the rational design of effective heat dissipation materials with highly and precisely tunable heat transfer pathways.

Due to its exceptional mechanical and chemical properties at high temperatures, Inconel 718 is extensively utilized in industries such as aerospace, aviation, and marine. Investigating the flow behavior of Inconel 718 under high strain rates and high temperatures is vital for comprehending the dynamic characteristics of the material in manufacturing processes. This paper introduces a physics-based constitutive model that accounts for dislocation motion and its density evolution, capable of simulating the plastic behavior of Inconel 718 during large strain deformations caused by machining processes. Utilizing a microstructure-based flow stress model, the machinability of Inconel 718 in terms of cutting forces and temperatures is quantitatively predicted and compared with results from orthogonal cutting experiments. The model’s predictive precision, with a margin of error between 5 and 8%, ensures reliable consistency and enhances our comprehension of the high-speed machining dynamics of Inconel 718 components.