Multiphysics Model Research Articles

Advances in the Study of Techniques to Determine the Lithium-Ion Battery’s State of Charge

This study explores the challenges and advances in the estimation of the state of charge (SOC) of lithium-ion batteries (LIBs), which are crucial to optimizing their performance and lifespan. This review focuses on four main techniques of SOC estimation: experimental measurement, modeling approach, data-driven approach, and joint estimation approach, highlighting the limitations and potential inaccuracies of each method. This study suggests a combined approach, incorporating correction parameters and closed-loop feedback, to improve measurement accuracy. It introduces a multi-physics model that considers temperature, charging rate, and aging effects and proposes the integration of models and algorithms for optimal estimation of SOC. This research emphasizes the importance of considering temperature and aging factors in data-driven approaches. It suggests that the fusion of different methods could lead to more accurate SOC predictions, an important area for future research.

Interface debonding defect detection for CFST columns based on EMI measurements: Experiment, numerical simulation and blind inspection in practice

Concrete-filled steel tube (CFST) members have been widely used in skyscrapers and long-span bridges. Non-uniformly distributed hydration heat during curing, inadequate compaction during construction and unavoidable shrinkage and creep of mass concrete in service most likely lead to interface debonding defects between concrete core and steel tube, which has been a common concern. The development of effective non-destructive inspection methods for interface bonding condition of existing CFST members is critical. In this study, an interface debonding defect detection method based on electromechanical impedance (EMI) measurement using surface-mounted piezoelectric-lead-zirconate-titanate (PZT) sensors is proposed at first. Then, experimental study on the feasibility of the proposed approach is carried out with scaled CFST specimens with artificially mimicked interface debonding defects. EMI of surface-mounted PZT sensors at different frequency bands are measured and compared to verify the detectability of the proposed approach for the mimicked interface debonding defects. Thirdly, a multi-physics CFST-PZT coupling finite element model (FEM) with interface debonding defects is established, and EMI of surface-mounted PZT sensors at different locations is simulated. The influence of interface debonding defects on EMI measurements is illustrated. Finally, a blind inspection on the interface bonding condition of selected CFST columns in an existing skyscraper in service using the proposed approach is carried out. Both bonding and debonding defect in the tested CFST columns are detected correctly and validated with drilling hole observation. Experimental, numerical and engineering application results show the proposed approach is effective for interface debonding detection of CFST members and sensitive to minor debonding defect of 0.3 mm in CFST members.

Multi-Objective Optimization of Process Parameters in Laser DED Ni-Based Powder on Steel Rail Using Response Surface Design

With the rise of global industrialization, the requirements for the operating speed and carrying capacity of high-speed trains are increasingly higher. Because the wear and tear of rails gradually increases during the running of high-speed trains, strengthening or repairing rail surfaces is of paramount significance. Laser-directed energy deposition (DED) exhibits significant advantages in improving surface hardness, corrosion resistance, and abrasion resistance. Because of the multiple interacting optimization objectives, the development of a multi-objective optimization method for process parameters is significant for improving DED deposition quality. Response surface design employs multivariate quadratic regression equations to fit the functional relationship between the factors and the responses, which can be employed to find the optimal process parameters and solve multivariate problems. This study develops a multi-objective optimization model with response surface design and 2D process mappings to visually analyze the effects of scanning speed, laser power, and powder feed rate on aspect ratio, dilution rate, and microhardness. The optimal combination of process parameters for Ni-based alloys on U71Mn rail is a laser power of 431 W, a scanning speed of 5.34 mm/s, and a powder feed rate of 1.03 r/min. In addition, a multi-physics field finite element model is developed to analyze the evolution mechanism of the microstructure from the bottom to the top of the single track. This study can provide theoretical and technical support for the surface strengthening or repair of U71Mn rail.

Surface roughness and microhardness improvement of laser cladding stainless-steel 316 by laser polishing based on multiple remelting

Laser polishing (LP) has emerged as a promising alternative to traditional post-treatment technologies. Nonetheless, the LP process encounters challenges when dealing with surfaces of high roughness, since the excessive thermal input could induce undesirable effects, including the formation of mid-frequency waviness, expansion of heat-affected zone (HAZ), etc. In this study, we investigated the surface roughness and the characters of the remelted layer and HAZ of polishing the laser-cladding 316 stainless steel layer deposited on the surface of a 45# steel cylinder by a 1064 nm hundred-watt pulsed laser and a 1080 nm thousand-watt CW laser respectively. It is observed that the combination of low power density and extended interaction time failed to produce minimum roughness by the pulse laser, contradicting existing LP theories. To address this, we developed a multi-physics model to elucidate the underlying mechanisms and propose an LP scheme based on multiple remelting cycles with the pulsed laser. The Sa roughness is reduced from 20.958 μm to 0.242 μm, decreasing 98.8 %. The processing quality is equivalent to the surface of the high-power CW laser (Sa of 0.283 μm), while the remelted layer and HAZ are significantly smaller. The pulse laser polishing based on multiple remelting increased the surface microhardness by 22 % to 560 HV, while the CW laser remelting reduced it by 33 % to 309 HV. And the HAZ microhardness all decreased in all cases. This study can provide a theoretical basis and solution for the surface finishing of additive manufacturing parts.

Research on Three-Phase Wireless Power Transfer System

Aiming at the problems of low power, low energy transmission efficiency, and high stress in the circuit of a single-phase wireless power transfer system, this paper proposes a wireless power transfer (WPT) system with a three-phase angle difference of 120 degrees and establishes a COMSOL multi-physics simulation model for analysis. In this simulation model, the topology of the three-phase resonant compensation network is studied in detail, and the structure of the coupling coil is designed and adjusted. Compared with the single-phase system with the same environmental conditions, air gap, and operating frequency, the simulation results show that the proposed three-phase system can effectively reduce the magnetic flux leakage, reduce the stress in the circuit, and significantly improve the energy transmission efficiency. In order to verify the reliability of the simulation results, an experimental platform was built. The experimental results show that the efficiency and coupling degree of the new system are significantly improved at the resonant frequency of 47.5 kHz, and the stress in the circuit is also significantly reduced.

Experimental characterization and non-isothermal simulation of a zero-gap alkaline electrolyser with nickel-iron porous electrode

The availability of self-supported porous electrodes with excellent hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) catalytic activity has been an important cornerstone for the performance of alkaline water electrolysers (AWEs). In addition, the management of heat and two-phase flow during ion/electron transfer in porous electrodes poses significant challenges to the stable operation of AWE electrolysers. In this work, a two-dimensional non-isothermal multiphysical model considering two-phase flow, mass, heat and charge transfer processes is developed based on COMSOL Multiphysics and well validated with reliable experimental data. The model exhibits excellent agreement with actual electrolyser operating voltages between 323–343 K, and the relative error is within acceptable 2.2% even at high current densities up to 1.5 A cm−2. In addition, the electrode kinetic data obtained based on standard three-electrode experiments allow the model to predict the corresponding HER and OER overpotentials of the porous electrodes with great accuracy, as well as to obtain the distribution of temperature and ionic species inside the porous electrodes under various volumetric flow rates and current densities. This work provides a practical and reliable guide for the design of porous electrodes and the performance enhancement of electrolysers from both experimental and simulation perspectives.

Enhanced Computational Study with Experimental Correlation on I-V Characteristics of Tantalum Oxide (TaOx) Memristor Devices in a 1T1R Configuration.

Memristors, non-volatile switching memory platform, has recently attracted significant interest, offering unique potential to enable the realization of human brain-like neuromorphic computing efficiency. Memristors also demonstrate excellent temperature tolerance, long-term durability, and high tunability with nanosecond pulses, making them highly attractive for neuromorphic computing applications. To better understand the material processing, microstructure, and property relationship of switching mechanisms in memristor devices, computational methodologies, and tools are developed to predict the I-V characteristics of memristor devices based on tantalum oxide (TaOx) resistive random-access memory (ReRAM) integrated with an n-channel metal-oxide-semiconductor (NMOS) transistor. A multiphysics model based on coupled partial differential equations for electrical and thermal transport phenomena is solved for the high- and low-resistance states during the formation, growth, and destruction of a conducting filament through SET and RESET stages. These stages effectively represent the migration of oxygen vacancies within an oxide exchange layer. A series of parametric studies and energy minimization calculations are conducted to determine probable ranges for key material and model parameters accounting for the experimental data. The computational model successfully predicted the measured I-V curves across various gate voltages applied to the NMOS transistor in the one transistor one resistance (1T1R) configuration.

A numerical procedure to obtain ideal piston trajectories and key design parameters for a hydrogen-fuelled resonating free piston generator

A new numerical procedure is presented to enable a hydrogen-fuelled two-stroke resonating free-piston generator target ideal Otto cycles to provide tracking paths for feedback control to maximise efficiency. Piston trajectories and design parameters are obtained for specified power, compression-ratio, and air-fuel-ratio. These parameters include scavenge port locations, heat release position, equivalent bottom-dead-centre position, and an electrical machine constant which is generally power-switched to take two values within a cycle. The main objectives of the paper are to develop the numerical procedure, and to demonstrate its use in finding a generator with maximum efficiency, and a generator with a single electrical machine constant, avoiding in-cycle power switching. To develop the procedure, a multi-physics generator model provides kinematics to an energy equation, culminating in a novel two-stage procedure. Stage-1 involves iteration and minimisation; Stage-2 just involves minimisation. Testing by simulation involves a 14-kW generator case study with compression ratio of 9, lean air-fuel equivalence ratio of 0.4, plus friction and electrical machine losses. An overall maximum generator efficiency of 54.9% is obtained using the procedure, compared to 51.3% without power switching. Computationally, the two-stage procedure proves highly efficient, typically taking around 11 min in total to complete on a desktop computer. The novelty of the procedure is its ability to optimally design and operate a hydrogen-fuelled resonating free-piston generator to meet a target specification, thereby offering a potentially inexpensive way to decarbonize transport, particularly in heavy duty applications.

A comprehensive study of a long-term creep thermo-mechanical fatigue behavior monitoring of BFRP composite pipeline using electrical capacitance sensors and deep learning algorithm

The composite pipeline is a relatively new and viable alternative pipeline to the more commonly used traditional one due to its good mechanical and fatigue properties and lower production cost. For this purpose, it is critical to assess the mechanical and fatigue performance of composite pipeline material under various working conditions, particularly for monitoring long-term creep thermo-mechanical fatigue behavior. In this paper, a long-term creep thermo-mechanical fatigue behavior in a basalt fiber reinforced polymer laminated composite pipeline is detected through an integrated expert system consisting of the electrical capacitance sensors and a deep learning algorithm. First, a multi-physics finite element model is established for the simulation of a long-term creep thermo-mechanical fatigue behavior in basalt fiber reinforced polymer composite pipelines subjected to long-term fatigue loading of internal pressure and thermal effect. Second, theoretical model results of long-term creep thermo-mechanical fatigue compliance (Sf(t)) over the time of creep are analyzed in pipeline material using the modulus degradation approach. Finally, an electrical potential change between electrical capacitance sensors electrodes corresponding to Sf(t) over the time of creep for some levels of long-term creep thermo-mechanical fatigue (Rf%) is recorded and then used in these datasets for training of the novel deep neural network based on one of the most widely used of the deep neural network families is the convolutional neural network, to predict Sf(t) in pipeline for various Rf% not included in the previous finite element model evaluation (i.e. electrical capacitance sensors technique). In this paper first is detected the long-term creep thermo-mechanical fatigue behavior for Rf%=25%,50%, and 75% from a finite element model and modulus degradation approach, and then is predicted the long-term creep thermo-mechanical fatigue behavior for Rf%=15%,35%,60%, and 85% respectively via deep neural network. The proposed method results are in good agreement with the experimental results available in the literature, thus verifying the accuracy and reliability of the proposed technique and its applicability to other different composite structures.

Multiphysics modeling of wire-to-plate electrohydrodynamic drying with air crossflow

Multiphysics modeling of wire-to-plate electrohydrodynamic drying with air crossflow

Full-spectrum radiative cooling for enhanced thermal and electrical performance of bifacial solar photovoltaic modules: A nationwide quantitative analysis

Bifacial photovoltaic (bPV) technologies have been garnering increasing attention in recent years due to their ability to generate more power than conventional PV systems. Passive radiative cooling through spectrally selective absorption/emission is considered one of the most practical and cost-effective solutions for the thermal management of bPV modules. In this study, a full-spectrum radiative cooling (FRC) strategy was proposed to maximize the thermal and electrical performance of bPV modules by enhancing above-bandgap absorption, sub-bandgap reflection, and thermal radiation. A multi-physics model was established to characterize bPV performance, enabling analysis of the module's spectral and thermal responses to full-spectrum light under dynamic weather conditions. The proposed model was validated through outdoor experiments with a commercial bPV module, demonstrating good prediction accuracy. To quantify the radiative cooling effect of the ideal FRC strategy and compare it with the ideal traditional radiative cooling (TRC) strategy, a nationwide simulation analysis was conducted across 32 cities in China. The results indicate that the ideal FRC strategy can achieve an annual average temperature reduction of 2.3–4.4 °C and an additional power gain of 7.3%–8.4% for commercial bPV modules. In comparison, the ideal TRC strategy can only achieve an annual average temperature reduction of 1.1–2.2 °C and an additional power gain of 0.38%–0.89%. Results from correlation analysis and sensitivity analysis show that among environmental parameters, wind speed has the most significant positive effect on lowering module temperature, while precipitable water vapor has a relatively small negative impact. Overall, this research demonstrates that the FRC strategy holds great potential for reducing temperature and boosting power output in PV devices, paving the way for promoting the development of sustainable and efficient PV systems.

A Digitalized Methodology for Co-Design Structural and Performance Optimization of Battery Modules

In this study, we present an innovative, fully automated, and digitalized methodology to optimize the energy efficiency and cost effectiveness of Li-ion battery modules. Advancing on from today’s optimization schemes that rely on user experience and other limitations, the mechanical and thermal designs are optimized simultaneously in this study by coupling 3D multi-physical behavior models to multi-objective heuristic optimization algorithms. Heat generation at various loading and ambient conditions are estimated with a physics-based, fractional-order battery cell-level model, which is extrapolated to a module that further accounts for the interconnected cells’ heat transfer phenomena. Several key performance indicators such as the surface temperature increase, the temperature variations on the cells, and heat uniformity within the module are recorded. For the air-cooled study case, the proposed coupled framework performs more than 250 module evaluations in a relatively short time for the whole available electro-thermal-mechanical design space, thereby ensuring global optimal results in the final design. The optimal module design proposed by this method is built in this work, and it is experimentally evaluated with a module composed of 12 series-connected Li-ion NMC/C 43Ah prismatic battery cells. The performance is validated at various conditions, which is achieved by accounting the thermal efficiency and pressure drop with regard to power consumption improvements. The validations presented in this study verify the applicability and overall efficiency of the proposed methodology, as well as paves the way toward better energy and cost-efficient battery systems.

A new 3-D multi-physics coupling model for lubricated piston-liner systems

In this paper, a new 3-D multi-physics coupling model is proposed for lubricated piston-liner systems. The sub-models for mixed lubrication, spatial multibody dynamics, and heat transfer are established and fully coupled on a unified absolute coordinate frame. The coupling model is discretized and solved using the unified spatial and temporal discrete methods. Then, an application example of a four-cylinder engine is employed to comprehensively investigate the coupling characteristics in the piston-liner system. The new coupling model reveals the presence of two distinct locations with the lowest local film thickness on either side of the piston's central axis, consequently yielding elevated local oil film pressures. This observation provides a reasonable explanation for the occurrence of wear and failure in the piston skirt on both sides.

Measurement of radiation induced attenuation in irradiated active fibers using optical frequency domain reflectometry

Radiation induced attenuation (RIA) is a major factor affecting the performance of fiber laser systems operated in adverse environments. To investigate the output characteristics of lasers with irradiated active fibers, measurement of detailed RIA profiles is required. Here, a novel method is proposed to explore the attenuation characteristics of irradiated active fibers using optical frequency domain reflectometry (OFDR), which enables propagation loss measurement by acquiring the spatial-resolved backscattered optical signals. With this technique, the RIA data of Yb-doped fibers (YDFs) under uniform radiation is derived by linear fitting of the OFDR traces. And, conventional optical transmission (OT) method is also exploited for comparison. Analysis show that the measured results of the two approaches are consistent. Then, the capability of OFDR is further verified for non-uniform RIA profile measurement of YDFs. For a pump bleached YDF, an upward parabolic RIA profile is attained by taking derivative of the smoothed polynomial fitting of the OFDR trace. Finally, the impacts of RIA profile on the output characteristics of Yb-doped fiber lasers are examined theoretically with a multiphysics thermal model, further validating the necessity of RIA profile measurement.

A 3D Computational Model of Nanosecond Pulsed Laser Texturing of Metals for Designing Engineered Surfaces

Abstract Laser surface texturing uses a pulsed laser that is scanned on the surface, wherein each pulse creates a micro-crater through material ablation. A variety of textures can be generated depending on the laser parameters and the overlap of the laser spots. This work presents a computational model that can predict the topography of a textured surface produced using a nanosecond pulsed laser. The model involves a multi-physics approach that considers laser ablation with plasma effects and the melt pool’s fluid dynamics to obtain the crater profile for a single pulse. The 3D surface profile created from the multi-physics model is mathematically superimposed to mimic the spatial overlapping of multiple pulses. The model predicts surface topography when a laser is scanned along a linear track with successive overlapping tracks. The experiments have confirmed that the proposed model has an accuracy greater than 90% in predicting surface roughness (Sa), as well as volume parameters such as core void volume (Vvc) and valley void volume (Vvv). It was observed that the variation of these surface characteristics is highly non-linear with the process parameters. Furthermore, the model is used to design engineered surfaces to modify friction coefficient, adhesion, and leakage probability. It is demonstrated that the surface parameters for functional requirements can be modified significantly just by varying the overlap of the laser spots in different directions. The proposed model can be used to create textured surfaces for various applications through an appropriate choice of laser parameters and scanning parameters.

Multi-physics modelling and performance analysis of an air-core reactor in the framework of solid-state fault current limiters

This study presents a comprehensive multi-physics modelling of an air-core reactor operating within a solid-state fault current limiter. By utilizing an air-core reactor in the solid-state fault current limiter, it is aimed to avoid magnetic saturation and assess a conventional fault current limiting device within a contemporary fault current limiter topology. Within the employed fault current limiter topology, the air-core reactor not only limits fault current during grid faults but also carries nearly the entire network current under normal operational conditions. Therefore, the performance of air-core reactor is investigated through thermal, electromagnetic and electrostatic aspects for normal and fault conditions. A 380 V test prototype is employed to validate the coupling of reactor model and electric circuit dynamics in the simulations. Furthermore, current results of high voltage simulations are supported by PSCAD results to reveal the results accuracy. During the operation of air-core reactor in normal and fault cases, the distribution of heat originating from eddy and resistive losses was examined through convection, radiation and conduction mechanisms. Moreover, the electric field intensities affecting the reactor are obtained for different operating conditions through electrostatic analysis, whereas the electromagnetic analysis reveals the magnetic flux densities and magnetic forces acting on the reactor.

A coupled electromagnetic and heat transfer model for casket designing for efficient microwave heating: An insight from theoretical analysis, Multiphysics simulation, and experimental investigations

Microwave heating is extensively used in several industries due to its advantageous capabilities such as volumetric heating, reduced processing time and less energy consumption as compared to conventional heating. Refractory casket insulation is primarily used in microwave heating systems for the purposes of insulation and effective microwave transmission. This investigation aims to provide knowledge and insights for selecting suitable high-temperature refractory insulating casket materials, particularly focusing on three different types: dense alumina, dense alumina-silica, and porous alumina-silica casket. The investigation involves evaluating the microwave transmission efficiency (PTC) and insulation resistance capability of the three casket materials concerning their dielectric and thermophysical properties at varying temperatures. Among three casket materials, porous alumina-silica casket showed a significantly lower values of dielectric constant (1.50 to 1.68), loss tangent (0.000086–0.00318) and thermal conductivity (0.26 W/m·K to 0.50 W/m·K) over the entire temperature range. Consequently, the porous alumina-silica casket exhibited superior insulation and PTC (0.9997 to 0.9876) during microwave heating. The heating phenomenon of each casket material has been established. The COMSOL Multiphysics model was used to analyze the microwave heating behavior of SiC susceptor with varying casket composition and geometry under similar parameters for the first time. A higher heating rate was observed by COMSOL simulation for the porous alumina-silica (58.8 °C/ min) casket than dense alumina-silica (22.31 °C/ min) and dense alumina (9.63 °C/min) casket during microwave heating of SiC susceptor at 1200 W, 1500 s. The COMSOL simulation data were corroborated with experimental results. The study serves a general guideline to select an appropriate casket material for any microwave processing.

System and multi-physics coupling model of liquid-CO2 injection on CO2 storage with enhanced gas recovery (CSEGR) framework

Injecting CO2 into gas reservoirs can achieve CO2 Storage with enhanced gas recovery (CSEGR). The development of liquid-CO2 injection has the characteristics of high injectability, high mobility ratio, and low diffusion coefficient. Therefore, this paper established a wellbore-reservoir-thermo-hydro-mechanical-diffusion (WR-THMD) multi-physics fully coupled model of the wellbore-reservoir system, and verified the model based on field and experimental data. The mass transfer, heat transfer, and gas physical property changes in the wellbore and reservoir during the injection of liquid-CO2 were studied. The impact of different engineering parameters on improving CH4 recovery and CO2 storage is also discussed. The results show that the impact of the wellbore on the physical properties and phase state of CO2 is crucial. The injection of liquid-CO2 is beneficial to the storage of CO2 and the displacement of CH4. Lowering the injection temperature will slightly improve the injectability of liquid-CO2 and increase the CO2 storage rate by 5.13%. Using a high injection mass flow rate will effectively raise CH4 recovery rate by 15.60%, but it will weaken the injectability of CO2 and cause CO2 to break through in the production well prematurely. The research results provide important suggestions and theoretical support for the application of liquid-CO2 injection on CSEGR.

Impacts of distributed thermal and electric contact resistance on performance and geometric optimization of thermoelectric generators

Thermal and electric contact resistance (TCR/ECR) critically impact performance and geometric optimization of thermoelectric generators (TEGs). However, conventional treatments usually ignored or simplified them as lumped variables, neglecting their actual distributions across the TEG system. In this study, we proposed a multi-physical model to characterize TEG performance with explicitly specifying TCRs/ECRs at different TEG interfaces (locations). The numerical results show that the lumped-variabletreatment led to maximal overestimations of 16.9 % and 24.5 % in the TEG output power and efficiency, respectively, compared to the results with distributed TCR in this article. Importantly, it also reveals that the TEG performance was susceptible to the TCR location—the interfaces on the cold side exerted more negative impacts than those on the hot side. Furthermore, reducing both TCR and ECR could improve TEG performance and reducing TCR is more effective. It is shown that an 80 % reduction in TCR increased the maximum TEG output power by 35.6 %, while the same reduction percentage in ECR only improved it by 8.8 %. As to geometric optimization, an optimal TE leg height equal to 0.6 mm was obtained for the maximum output power. This contrasts with previous studies without considering TCR and ECR, which always favoured shorter heights. As for copper electrodes, their optimal heights were in the range of 0.2–0.4 mm corresponding to the maximum efficiency, far smaller than those (0.7–1.2 mm) obtained when TCR/ECR were neglected. The latter even further resulted in a reduction in the maximum efficiency by more than 1 % compared to its true peak. In this study, all these numerical results clearly elucidate the important impacts of distributed TCR and ECR on TEG performance, and provide a comprehensive and balanced guideline for TEG design.

Acoustically enhanced porous media enables dramatic improvements in filtration performance

Indoor air pollution affects millions of people worldwide. Conventional air purification techniques struggle to balance between safety, power consumption, efficacy, and cost. Acoustics have previously been leveraged to improve air purification with fiber filters, but little is known about how the arrangement of the fibers influences the acoustic effects, particularly for non-agglomerative purification performance relevant to fine and ultrafine pollutants. Here, we explore performance enhancements to fiber filters by applying external standing acoustic waves. We investigate the effects of the porous media arrangement in ordered (aligned and staggered) and disordered fiber media by building a multiphysics model, incorporating thermos-viscous acoustics, laminar flow, and particle tracing. Particles are modeled as point forces to isolate acoustic radiation forces and streaming. Attractive acoustic radiation forces dominate in the porous domain, leading to increased particle/boundary interactions. We find that the average acoustic radiation forces scale linearly with the average scattered acoustic pressure by the fiber medium. The scattered pressure varies depending on the fiber arrangement, indicating that there is an optimal design to increase the performance of acoustic-induced effects. We show a dramatic increase in performance efficiency, up to two orders of magnitude (123 times) for a staggered domain. This work has important applications to further advance acoustically enhanced filtration as a compelling solution for micro/nanoparticle separation processes.