Nanofiber-based structures have shown considerable potential in semiconductor-related applications, including ultra-thin dielectric layers and flexible electronic devices, owing to their tunable micro-/nanoscale morphology. However, the manufacturing of these structures is often hindered by the complex multiparameter coupling and poor reproducibility inherent in conventional electrospinning processes. To address these challenges, this study develops an intelligent optimization framework for gas-assisted electrospinning by integrating Large Language Models (LLMs) with Bayesian Optimization (BO). A Gaussian Process Regression (GPR) surrogate model was established to navigate the high-dimensional parameter space efficiently. Comparative studies demonstrate that the proposed BO+LLM strategy not only outperforms pure data-driven BO and pure knowledge-driven LLM approaches but also surpasses the conventional Response Surface Methodology (RSM) baseline, successfully locating a verified minimum fiber diameter of 239 nm. Furthermore, through response-surface analysis, this work identifies a specific multiphysics collaborative window where electrostatic stretching and aerodynamic assistance are balanced. These findings provide a robust pathway for the reproducible fabrication of nanofiber-based electronic devices.

Coaxial electrospinning technology enables the fabrication of nanofibers with a core-shell structure, thereby facilitating the encapsulation of functional materials. Its efficacy lies in the precise regulation of mass transfer behavior at the sensing interface. However, achieving the controllable preparation of core-shell fiber structures in complex environments and quantitatively predicting their mass transfer kinetics remain challenging. This study aims to establish a predictive framework combining simulation and experiment. Firstly, finite element simulations using COMSOL clarified that increasing the shell thickness or decreasing its effective diffusion coefficient can significantly delay analyte transport. A model incorporating time-varying parameters further revealed the influence of polymer swelling on the initial release kinetics. Using the diffusion of an aqueous KCl solution as a model system, experiments confirmed that increasing the shell solution concentration is an effective processing strategy for enhancing the mass transfer barrier. Based on the Box-Behnken design and response surface methodology (RSM), a quantitative model linking key process parameters to release kinetic parameters was established. Model diagnostics indicated that the regression equation is significant and reliable. Validation experiments demonstrated that the model possesses good predictive capability for the key release kinetic parameters, with prediction errors within an acceptable range. The framework established in this study indicates that active design of the mass transfer behavior of core-shell fibers can be achieved through process control, providing a quantitative predictive tool and methodological reference for the preparation of controllable mass transfer interfaces for sensing applications.

Soft biomaterials have found widespread applications across the biomedical field; however, single-component soft biomaterials suffer from a limited tunable range of mechanical properties. To address this critical limitation, this study fabricated sinusoidal microlattice scaffolds via melt electrowriting technology and embedded them into soft biomaterials for mechanical reinforcement. A theoretical design framework was constructed for sinusoidal microlattice scaffolds to forecast the relationship between the mechanical behaviors of the materials and three key geometric parameters: amplitude, wavelength, and fiber diameter. Additionally, a lag error trajectory compensation strategy was developed to ensure the high-precision fabrication of the scaffolds. To validate the theoretical model, experimental tests and finite element simulations were conducted on sinusoidal microlattices with three distinct topological structures (triangular, orthogonal, and rectangular), revealing excellent agreement between the theoretical predictions, experimental results, and simulation outcomes. Mechanical characterizations of lattice-hydrogel composites confirmed that sinusoidal microlattice scaffolds exert a remarkable reinforcing effect on soft biological matrices. Specifically, the scaffolds significantly enhanced the ultimate stress and failure strain of hydrogels, while maintaining excellent interfacial compatibility between the scaffold and the matrix. Numerical results further demonstrated that modulating the geometric parameters enables broad-range regulation of the scaffold's mechanical properties, including elastic modulus (ranging from several kPa to several MPa), extensibility (with a maximum strain of 226%), and Poisson's ratio (varying from 0.46 to 1.75). This study provides a novel theoretical approach and technical support for predicting the mechanical properties of microlattice structures and rationally designing mechanically reinforced soft biomaterials, thereby holding great significance for advancing biomedical fields.

This study aims to characterize the numerical simulation and mass transfer properties of ultrasound-enhanced metal-assisted chemical etching (MACE) for fabricating silicon nanopore (SiNP) arrays. Firstly, the experimental setup for ultrasound-enhanced MACE is established and the uniform SiNP arrays are successfully etched. Results indicate that the etching rate (RSi) increases significantly with temperature, HF molar concentration, and the application of ultrasound. The relationships of ln RSi with ln cHF and 1/T are determined, and thus the surface reaction rate is derived. The effects of ultrasonic and geometric parameters on fluid velocity and mass transfer coefficient (kc) are evaluated. kc is significantly dependent on the ultrasonic power, and by applying ultrasound, kc can be improved by more than an order of magnitude. The kc of perpendicular arrangement is obviously higher than that of parallel arrangement. This work helps provide guidance for the fabrication of SiNP arrays and promotes their applications.

This paper delves into the fixed-time formation control problem for stochastic nonlinear multiagent systems (MASs) with time-varying input delay (TVID). The reference for formation control is generated by the dynamic leader with human decision-making signals. The issue of nonlinear uncertainties is addressed by using neural networks (NNs). To enhance the conventional backstepping technique, the practical fixed-time control strategy is integrated into the control design, ensuring the convergence of formation errors within a fixed time. Furthermore, a modified auxiliary system with topology information is constructed to address the problem of TVID. Concomitantly, a nonlinear filter is designed to reduce computational burden and compensate for filtering errors. Through stability analysis, it is proven that the practical fixed-time stability of stochastic MASs can be actualized via the designed fixed-time formation controller. Finally, the effectiveness of the presented control method is validated by simulation results.

In this article, a fuzzy payload compensation algorithm is proposed. In the context of simulating a machine vision model reconstruction, the target object is regarded as a cylinder to obtain the corresponding geometric size data. The first fuzzy mass prediction system is then used to predict the mass of the target object. During operation, real-time processing and calculation of the robotic arm’s joint motor current data are performed. Based on the mathematical relationship between the identified basic parameter set from the dynamic parameters and the end-effector payload, the second fuzzy compensation system was used to calculate the root mean square error (RMSE) of the predicted versus collected current data of the 6-th joint motor, thereby predicting and compensating for the payload mass. The final prediction is generated upon completion of the operation. The overall experiment is conducted on the HSR-CR607 robot. The experimental results indicated that the proposed prediction algorithm consistently operates within the acceptable error range (15%) in most test cases.

Semiconductor miniaturization demands stricter material uniformity. Core-shell nanofibers, promising for semiconductor packaging and flexible circuits, face application limits due to traditional coaxial electrospinning’s electric field instability—causing poor fiber diameter uniformity and challenges with high-viscosity and low-conductivity solutions. To address this, airflow-assisted coaxial electrospinning leveraged airflow-electric field synergy to enhance fiber stretching. COMSOL Multiphysics 6.4 simulated the influence of different inner diameters of the air flow nozzles on the air flow field, while the response surface method optimized parameters. At 10 kPa air pressure, 16.71 kV voltage, and a gas nozzle inner diameter of 3.42 mm, nanofibers showed regular morphology with a diameter coefficient of variation as low as 9.2%. This study enables stable preparation of highly uniform core-shell nanofibers, providing key process support for their large-scale semiconductor application and advancing flexible electronics and photodetection.

In this paper, the adaptive tracking control problem for macro-micro composite positioning stage (MMCPS) with error constraints and input saturation is considered. The MMCPS has important applications in realizing high-speed macromotion and high-precision micromotion, which can be regarded as a non-strict feedback interconnected nonlinear system. A fixed-time prescribed performance (FTPP) function is proposed to restrict the tracking error and virtual errors. Based on the designed barrier Lyapunov function, the transform errors can also be constrainted in the prescribed constant bounds. Furthermore, an auxiliary system is constructed to compensate adverse effect of the saturation nonlinearity. By integrating the nonlinear filtering technique into the backstepping control framework, the problem of computational complexity explosion can be effectively avoided. For the purpose of achieving better transient performance and improving control precision, an adaptive FTPP tracking control method is presented. According to the Lyapunov stability theory, the proposed control method guarantees that all dynamic errors can converge to the prescribed bounds within fixed time. Finally, a simulation example is given to indicate the effectiveness of the designed controller.

Gas-assisted coaxial electrospinning (GACES), a simple and versatile technique for the large-scale fabrication of coaxial nanofiber membranes, possesses significant industrial potential across advanced manufacturing sectors including semiconductors—particularly for fabricating high-precision dielectric layers, high-uniformity encapsulation materials, and flexible semiconductor substrates requiring tailored core-shell architectures. However, there is still a lack of relevant studies on the effective regulation of the core-shell structures of coaxial fibers based on GACES, which greatly limits the batch preparation and wide application of coaxial fibers. Finite element simulation analysis of the flow field and development of the coaxial jet mechanics model with a gas-driven flow field—two key methodologies in this study—successfully uncovered the influence mechanism of gas-assisted flow fields on the core-shell structures of coaxial nanofibers. By adjusting the gas-assisted flow fields parameters, we reduced the total diameter of coaxial fibers by 47.33% (average fiber diameter: 334.12 ± 16.29 nm → 175.98 ± 1.18 nm), decreased the shell thickness by 72.98%, increased the core-shell ratio by 289% (core-shell ratio: 0.49 → 1.91), and improved the uniformity of the total diameter distribution of coaxial fibers by 30.64%. This study delivers a practical conceptual framework and robust experimental underpinnings for the scalable fabrication of coaxial nanofiber membranes with controllable core-shell structures, thereby promoting their practical application in semiconductor devices such as ultra-thin dielectric layers, precisely structured encapsulation materials, and high-uniformity templates for nanoscale circuit patterning.

This article aimed to study the characteristics of chaotic advection and mass transfer of viscous liquid-liquid flows in a novel 3D serpentine microchannel (TSM) with hybrid structures. The TSM and its corresponding experimental setup are established, and the CFD model is verified through flow field visualization experiments. Results reveal that efficient chaotic convection in TSM is achieved through continuous irregular spatial fluid deformation. The Lyapunov exponents greater than zero indicate the existence of chaotic behavior, and the maximum lineal stretch rate lambda M increases linearly with the characteristic Reynolds number. The mass transfer characteristics are evaluated by diffusion mass transfer number Phi and mass transfer field synergy number Fc quantitatively. The mixing index MI shows an increasing trend as Fc increases, while the mixing effectiveness ME decreases as the outlet Reynolds number ReO decreases. The relationships of MI with lambda M and Fc and the relationship of ME with ReO are established.

Silicon (Si) nanohole arrays with controllable morphology hold significant application potential. Achieving high aspect ratio vertical etching of Si nanohole arrays can be challenging due to mass transport limitations during metal-assisted chemical etching (MACE). This work reports an ultrasound-enhanced MACE method to improve the mass transport process and prepare large-area uniform, high aspect ratio and vertical Si nanohole arrays. The effects of etchant and ultrasonic enhancement on the morphology, etching rate and critical depth of Si nanoholes are systematically evaluated. Results indicate that the morphology of Si nanoholes (e.g., taper angle, porosity and surface roughness) can be customized by carefully selecting the oxidant concentration and etching duration. The etching rate of ultrasound-enhanced MACE reaches a maximum of similar to 0.82 mu mmin(-1), which is 22.73 % higher than that of conventional MACE. The mass transport in the ultrasound-enhanced MACE process is improved by increasing the effective mass transfer area and inducing convection and microstreaming flows, thereby improving the etching rate and critical depth. The key understandings in ultrasound-enhanced MACE allowed us to demonstrate the fabrication of large-area uniform Si nanohole arrays with an unprecedented depth of similar to 24.35 mu m and an aspect ratio of similar to 34.8.

Gas-assisted coaxial electrospinning (GACES) is a simple and general method for the mass preparation of coaxial nanofiber membranes, which has great industrial potential. However, in the manufacturing process, due to the bending instability of the jet in the electric field and the pulling effect of the gas flow field, the deposition uniformity of the fiber is still a big problem. Through finite element simulation analysis of the flow field in the manufacturing process and the construction of the jet mechanics model after adding the flow field, the influence mechanism of coaxial auxiliary flow on the fiber deposition area and its uniformity was successfully revealed in this research. Finally, the deposition area and thickness uniformity of coaxial fibers are increased by 3 times (the deposition area: 19.63 cm2 → 78.50 cm2) and 2.34 times (the standard variance: 3 μm2 → 10 μm2) by gas-assisted coaxial electrospinning. At the same time, the coaxial auxiliary gas flow also reduces the coaxial fiber diameter by 36.9% (the average fiber diameter: 241 nm ± 5 nm → 152 nm ± 23 nm) and the distribution range by 66% (the standard variance: 1.5 × 102 nm2 → 51 nm2). This research provides a reliable idea and experimental basis for homogeneous preparation of coaxial nanofiber membranes.

This study aims to characterize the mass transfer characteristics of a novel concentration-regulated metal-assisted chemical etching (MACE) system and investigate its application in the controllable fabrication of similar to 600 nm diameter silicon (Si) nanohole arrays. A concentration-regulated MACE system for Si nanohole etching is established, and the CFD simulations of fluid flow, mass fraction evolution, and mass transfer are conducted. Results reveal that the mass fraction distributions from simulations and experiments are in good agreement. As the inlet velocity increases, the average velocity and vorticity significantly increase, the mass fraction approaches the target concentration more quickly, and the mass transfer coefficient increases by 1.51 to 6.72 times compared to conventional MACE. The concentration-regulated MACE system with a fine pore array demonstrates good concentration regulation performance due to its stable mass fraction evolution process, minimal standard deviation of mass fraction, and uniform mass transfer coefficient. Utilizing the concentration-regulated MACE system, the etching rate of Si nanoholes increases by approximately 27.78 % under mass transfer enhancement, and large-area, uniform, high aspect ratio, and controllable tortuous Si nanohole arrays are successfully fabricated for the first time.

In this article, a trajectory optimization algorithm is proposed for flying chip ejection mass transfer technology, using the Bezier degree elevation techniques. First, by converting the flying chip ejection requirements into equations and inequalities, the optimization problem of flying chip ejection is constructed. Then, the Bezier curve and the degree elevation are introduced, which expand the search space for the original problem as proven by a theorem on point and curve constraints. After that, a Bezier degree elevation optimization algorithm is proposed. Comparisons with previous algorithms in simulations and platform experiments verify the effectiveness of the proposed algorithm. Results show that the proposed algorithm is more suitable for optimization problems with strict constraints.

To enhance the anti-tip-over capability during mobile robot operations, this study proposes an active mass redistribution strategy based on a two-degree-of-freedom counterweight mechanism. The approach involves: (1) Establishing a six-axis manipulator dynamics model using Denavit-Hartenberg (DH) and Newton-Euler methods to calculate dynamic loads on the mobile platform; (2) Building a tip-over stability model that minimizes the quadratic sum of moments on the tip-over axis through dynamic counterweight position optimization. MATLAB simulations demonstrate: Under material handling conditions, the tip-over probabilities are 46.19% (no counterweight), 16.93% (passive mass addition), and 0.12% (active mass redistribution system). Through 10(4) random path validations, the active mass redistribution system reduces tip-over risk by 99.7%, significantly surpassing pure weight-increasing solutions. The results prove that this adaptive device effectively improves mobile platform stability.

Abstract Multi‐needle electrospinning is a simple and general method for mass preparation of nanofiber membrane, which has great industrial potential. However, the bending instability produced in the electrospinning process makes that the deposition uniformity of the nanofiber is still a big concern, resulting in non‐uniform nanofiber membrane, which seriously affects the application of electrospun membrane in environmental filtration, new energy and medical fields. In order to improve the uniformity of nanofiber deposition in multi‐needle electrospinning, an auxiliary flow field system (AFF) is proposed, which can effectively improve the uniformity of nanofiber deposition. After image processing, the uniformity of nanofiber deposition is quantified with the index of grey distribution, and the effectiveness of this method is verified. Combined with the multi‐physical field analysis, the influence mechanism of cross‐wind field on the uniformity of fibre deposition was revealed. By optimizing the experimental parameters, the non‐uniformity of nanofiber deposition was reduced by 49.19%. Based on multi‐needle electrospinning technology, a reliable idea (AFF) and experimental basis are provided for the uniform preparation of nanofiber membrane.

Micro-supercapacitors (MSCs) have become promising micro-storage devices in the field of microelectronics due to their advantages of small size, high power density, and excellent cycling stability. In this work, a composite laser processing technique was reported to convert cyanate ester resin into highly conductive graphene (LIG) films using CO2 and fiber lasers in ambient air, respectively. Under the CO2 laser pyrolysis of resin and subsequent fiber laser annealing, the resulting LIG film exhibits an ultra-low sheet resistance (1.67 Omega per square), which is one order of magnitude lower than that of polyimide (PI)-induced LIG films, indicating the advance of the composite laser processing technique. The effect of substrates with two thermal conductivities on the morphology, sheet resistance and electrochemical performance of the LIG films was also investigated. Benefiting from the excellent thermal conductivity of metal substrate, LIG/TiMSCs with titanium substrate provide an areal capacitance of 26.4 mF/cm (2) at a scan rate of 5 mV/s, which is higher than that of LIG/PI-MSCs with PI substrate (similar to 17.6 mF/cm(2)) under the same conditions.

A permanent magnet linear synchronous motor (PMLSM) is susceptible to system uncertainties and external disturbances, resulting in a tracking error that is difficult to eliminate. To effectively reduce the tracking error of a PMLSM, this article presents a novel dynamic microactuation (DMA) method through a microactuation unit (MAU)-assisted dual-stage system. In this article, we reduce the tracking error dynamically through MAU-based actuation and use the PMLSM mover as the working end of the dual-stage system. The proposed DMA method finalizes the actuation mechanism of the MAU. Therefore, the method can dynamically actuate the MAU to act on the PMLSM mover with the appropriate actuation amount, and thus, reduce the tracking error of the motion system. Moreover, to avoid the coupling effect of MAU-based actuation on the PMLSM controller, the DMA method modifies the feedback error of the PMLSM controller by adding the actuation amount to the position error such that it remains unchanged. Thus, the stability of the electromagnetic thrust of the PMLSM can be maintained for its output. After finalizing the actuation mechanism and modifying the feedback error, the tracking error of the PMLSM can be reduced dynamically and the coupling effect of the MAU-based actuation on the PMLSM controller can be avoided. The performance of the proposed DMA method is analyzed theoretically and validated experimentally. The results show that the proposed method can effectively reduce the tracking error of a PMLSM system.

At present, the situation of air pollution is still serious, and research on air filtration is still crucial. For the nanofiber air filtration membrane, the diameter, porosity, tensile strength, and hydrophilicity of the nanofiber will affect the filtration performance and stability. In this paper, based on the far-field electrospinning process and the performance effect mechanism of the stacked structure fiber membrane, nanofiber membrane was prepared by selecting the environmental protection, degradable and pollution-free natural polysaccharide biopolymer pullulan, and polyvinylidene fluoride polymer with strong hydrophobicity and high impact strength. By combining two kinds of fiber membranes with different fiber diameter and porosity, a three-layer composite nanofiber membrane with better hydrophobicity, higher tensile strength, smaller fiber diameter, and better filtration performance was prepared. Performance characterization showed that this three-layer composite nanofiber membrane had excellent air permeability and filtration efficiency, and the filtration efficiency of particles above PM 2.5 reached 99.9%. This study also provides important reference values for the preparation of high-efficiency composite nanofiber filtration membrane.

The centrifugal electrostatic blowing process proposed in this paper solves the difficult continuous and stable deposition problem in the traditional centrifugal electrostatic spinning process. By establishing a flight deposition model of the centrifugal electrostatic spraying process, CFD is used to simulate and analyze the electrohydrodynamic effect of centrifugal jets, and the driving mechanism is explored. Subsequently, MATLAB is used to obtain the optimal solution conditions, and finally, the establishment of a two-dimensional flight trajectory model is completed and experimentally verified. In addition, the deposition model of the jet is established to clarify the flight trajectory under the multi-field coupling, the stable draft area of the jet is found according to this, and the optimal drafting station is clarified. This research provides new ideas and references for the exploration of the deposition mechanism of the centrifugal electrostatic blowing and electrostatic spinning process.