COMSOL Multiphysics®: Finite element software for electrochemical analysis. A mini-review

Modeling of Power Generation and Acid Recovery in an Analogous Process of Reverse Electrodialysis

The feasibility of an analogous reverse electrodialysis (RED) process for power generation and acid recovery from acidic waste streams in the steel industry is investigated in this study. A comprehensive model was established to simulate the transport phenomena and power generation, which was validated through experimental data. The simulated operation time was 3 h, during which an acid recovery rate of 41.7% was achieved, and the maximum output power density reached 30.37 μW·cm-2. The results demonstrated a strong dependence of output power density on the acid concentration, with a linear relationship within the tested range of 1.0-3.0 mol·L-1 HCl. An optimal flow rate range was identified that maximized power output, with the best value of 90 mL∙min-1. The differences in energy harvesting between the traditional acid diffusion dialysis process and our analogous RED process were demonstrated via simulation. The importance of system electroneutrality in driving ion migration and forming ionic currents was crucial for effective power generation. The analogous RED process is a promising solution for efficient acid recovery and power generation from industrial acid waste, offering a sustainable treatment approach.

Advanced development of finite element analysis for electrochemical catalytic reactions

The development of robust simulation techniques is crucial for elucidating electrochemical catalytic mechanisms and can even provide guidance for the tailored design and regulation of highly efficient catalysts. Finite element analysis (FEA), as a powerful numerical simulation tool, can effectively simulate and analyze the sophisticated processes involved in electrochemical catalytic reactions and unveil the underlying microscopic mechanisms. By employing FEA, researchers can gain better insights into reaction kinetics and transport processes, optimize electrode design, and predict electrochemical performance under various reaction conditions. Consequently, the application of FEA in electrochemical catalytic reactions has emerged as a critical area of current research and a summary of the advanced development of FEA for electrochemical catalytic reactions is urgently required. This review focuses on exploring the applications of FEA in investigating the crystal structure effect, tip effect, multi-shell effect, porous structure effect, and mass transfer phenomena in electrochemical reactions. Particularly emphasized are its applications in the fields of CO2 reduction, oxygen evolution reaction, and nitrogen reduction reaction. Finally, the challenges encountered by this research field are discussed, along with future directions for further advancement. We aim to provide comprehensive theoretical and practical guidance on FEA methods for researchers in the field of electrochemical catalysis, thereby fostering the advancement and wider implementation of FEA within this domain.

Simulation of Interface Characteristics and Charge Transfer Dynamics for Layered Electrodes Using Cascade Capacitance in Supercapacitors by COMSOL Software

In this investigation, the performance disparity between layer-by-layer (LbL) electrodes and uniformly mixed (UM) electrodes in supercapacitors is evaluated using COMSOL Multiphysics software by utilizing a two-dimensional asymmetric structure simulation model where the LbL electrodes consist of ZnMn2O4 and graphene oxide (GO) with varying layering sequences and scales ranging from millimeters to microns. The results revealed that the LbL electrodes significantly augmented the supercapacitor's performance by enhancing charge and mass transport mechanisms. Across both millimeter and micrometer scales, the LbL electrodes surpassed the uniformly mixed electrodes due to their larger surface area and greater ionic accessibility, resulting in more effective charge storage and faster electron transfer. Cyclic voltammetry (CV) illustrated that the peak current density of the LbL electrodes increased with an increase in layers with four-layer micrometer-scale electrodes displaying characteristics closest to those of an ideal supercapacitor, showcasing more consistent and efficient energy storage and release capabilities. The analysis using electrochemical impedance spectroscopy (EIS) revealed that the LbL electrodes exhibited reduced resistance and significant capacitive characteristics about 109 F/m2. The stacked structure not only improved the surface area and conductivity of the electrodes but also accelerated the charge transfer process, minimized interfacial reaction resistance, and facilitated ion diffusion within the electrodes. Through a combination of simulation techniques and theoretical analysis, this study proposed a stacked capacitance (Cs) theory and developed a cross-scale electrochemical interface model by integrating first-principles calculations with multiscale simulations. These findings provide valuable insights for designing and optimizing high-performance materials and devices, offering a new perspective on enhancing the supercapacitor performance through electrode design.

Modelling enzyme electrodes - What do we learn and how is it useful?

There has been an enormous increase in the computational power readily available since the first numerical treatments of electrochemical problems in the early 1960s. This development has been accompanied by the development of powerful, widely available, commercial software modelling tools. Despite this, approximate analytical treatments remain extremely useful in the modelling of coupled diffusion/reaction problems in electrochemistry because of the insights they provide into the different possible behaviours of the system. In this paper we discuss the modelling of amperometric enzyme electrodes, taking as our exemplar redox hydrogel-based enzyme electrodes in which the enzyme is immobilized in a redox active polymer which wires the enzyme to the electrode. In this system the measured current is related to many different experimental variables including substrate concentration and diffusion coefficient, reaction rate constants, and film properties and thickness. The interplay of these factors is described and the role of Case diagrams in understanding coupled diffusion/reaction problems of this type is discussed.

A Novel Gelatin Binder with Helical Crosslinked Network for High-Performance Si Anodes in Lithium-Ion Batteries

Silicon (Si) is a promising anode material for lithium-ion batteries, but its large volume expansion during cycling poses a challenge for the binder design. In this study, a novel gelatin binder is designed and prepared with a helical crosslinked network structure. This gelatin binder is prepared by enzymatic crosslinking and immersion in Hofmeister salt solution, which induces the formation of network and helical secondary structures. The helical crosslinked network structure can be analogous to a spring group system to effectively dissipate the stress and strain caused by the Si expansion. The gelatin binder is further partially carbonized by low-temperature pyrolysis, which improves its conductivity and stability. The Si anode with the optimized gelatin binder exhibits high initial coulombic efficiency, excellent rate performance, and long-term cycling stability. This study provides an innovative approach for the preparation of high-performance Si anodes, namely by controlling the molecular configuration of the binder to significantly improve the cycle stability, which can also be applied to other high-capacity anode materials that suffer from large volume changes during cycling.

SODL-IR-FISTA: sparse online dictionary learning with iterative reduction FISTA for cone-beam X-ray luminescence computed tomography

Cone beam X-ray luminescence computed tomography (CB-XLCT) is an emerging imaging technique with potential for early 3D tumor detection. However, the reconstruction challenge due to low light absorption and high scattering in tissues makes it a difficult inverse problem. In this study, the online dictionary learning (ODL) method, combined with iterative reduction FISTA (IR-FISTA), has been utilized to achieve high-quality reconstruction. Our method integrates IR-FISTA for efficient and accurate sparse coding, followed by an online stochastic approximation for dictionary updates, effectively capturing the sparse features inherent to the problem. Additionally, a re-sparse step is introduced to enhance the sparsity of the solution, making it better suited for CB-XLCT reconstruction. Numerical simulations and in vivo experiments were conducted to assess the performance of the method. The SODL-IR-FISTA achieved the smallest location error of 0.325 mm in in vivo experiments, which is 58% and 45% of the IVTCG-L 1 (0.562 mm) and OMP-L 0 (0.721 mm), respectively. Additionally, it has the highest DICE similarity coefficient, which is 0.748. The results demonstrate that our approach outperforms traditional methods in terms of localization precision, shape restoration, robustness, and practicality in live subjects.

Research on the mechanism of threefold discrepancy in thermal conductivity between room temperature and phase transition temperature for 1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) crystals

Cracks originating from thermal expansion and thermally induced phase transitions significantly hinder thermal conduction in certain energetic materials. For 1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) crystals, a classic explosive, their temperature-dependent thermal conductivity serves as a crucial parameter determining safety and stability. In this work, the thermal conductivity of HMX single crystals before and after thermal damage under different heating conditions was measured and calculated, as well as the thermal conductivity of different regions of each single crystal. A threefold discrepancy in thermal conductivity was observed between room temperature and the phase transition temperature of the HMX crystal. The different effects of different types of damage and cracks, characterized by using 3D X-ray computed tomography (CT), on the thermal conduction process of the crystal were further analyzed. The results indicate that different heating methods influence the phase transformation of the crystals and the distributions of fast cracks and small cracks. The strong directivity of the fast cracks will significantly impact the thermal conductivity along two horizontal directions, whereas small cracks exert the greatest influence on the primary direction of heat conduction. The relevant conclusions were also verified by finite element analysis (FEA) modeling.

Operando Electrodeposition of Nonprecious Metal Copper Nanocatalysts on Low-Dimensional Support Materials for Nitrate Reduction Reactions

Supported nonprecious metal catalysts such as copper (Cu) are promising replacements for Pt-based catalysts for a wide range of energy-related electrochemical reactions. Direct electrochemical deposition is one of the most straightforward and versatile methods to synthesize supported nonprecious metal catalysts. However, further advancement in the design of supported nonprecious metal catalysts requires a detailed mechanistic understanding of the interplay between kinetics and thermodynamics of the deposition phenomena under realistic reaction conditions. Here, we study the electrodeposition of Cu on carbon nanotubes and graphene derivatives under electrochemical conditions using in situ liquid cell transmission electron microscopy (TEM). By combining real-time imaging, electrochemical measurements, X-ray photoelectron spectroscopy (XPS), and finite-element analysis (FEA), we show that low-dimensional support materials, especially carbon nanotubes, are excellent for generating uniform and finely dispersed platinum group metal-(PGM)-free catalysts under mild electrochemical conditions. The electrodeposited Cu on graphene and carbon nanotubes is also observed to show good electrochemical activity toward nitrate reduction reactions (NO3RRs), further supported by density functional theory (DFT) calculations. Nitrogen doping plays an important role in guiding nonprecious metal deposition, but its low electrical conductivity may give rise to lower NO3RR activity compared to its nondoped analogue. The development of supported nonprecious metals through interfacial and surface engineering for the design of supported catalysts will substantially reduce the demand for precious metals and generate robust catalysts with better durability, thereby presenting opportunities for solving the critical problems in energy storage and electrocatalysis.

Modeling and Design Parameter Optimization to Improve the Sensitivity of a Bimorph Polysilicon-Based MEMS Sensor for Helium Detection

Helium is integral in several industries, including nuclear waste management and semiconductors. Thus, developing a sensing method for detecting helium is essential to ensure the proper operation of such facilities. Several approaches can be used for helium detection, including based on the high thermal conductivity of helium, which is several times higher than air. This work utilizes the high thermal conductivity of helium to design and analyze a bimorph MEMS sensor for helium sensing applications. COMSOL Multiphysics software (version 6.2) is used to carry out this investigation. The sensor is constructed from poly-silicon and SiO2 materials with a trenched cantilever beam configuration. The sensor is electrically heated, and its morphed displacement depends on the surrounding gas's composition, which decreases in the presence of helium. Several factors were investigated to probe their effect on the sensor's sensitivity to helium, including the thickness of the poly-silicon layer, the configuration of the trench, and the thickness and location of SiO2 layer. The simulations showed that the best performance, up to 2 ppm helium detection level, can be achieved with thinner beams and medium trench lengths.

Exceptionally Fast Separation of Xylene Isomers with Zeolitic Nanotube Array Membranes

The separation of xylene isomers is of vital importance in chemical industry but remains challenging due to their similar structure and overlapping physiochemical properties. Membrane-based separations using the zeolite MFI, graphene oxide, and metal-organic frameworks have been intensively studied for this application, but the performance is limited by the well-known rule that the filtrate permeance scales inversely with the membrane thickness. We propose a novel membrane design that is capable of breaking this rule, based on an array of recently discovered zeolite nanotubes. Each zeolite nanotube possesses a 3.6-nm-wide central channel, connecting to dense, uniform 0.8-nm-wide holes on its wall that act as selective pores. Comprehensive molecular dynamics simulations show that this membrane exhibits permeance exceeding current state-of-the-art membranes by at least an order of magnitude while simultaneously maintaining an acceptable selectivity. In particular, a thicker membrane featuring longer zeolite nanotubes exhibits a higher permeance due to the presence of more selective pores. The proposed membrane design is expected to be broadly applied to other gas separations and even desalination as long as zeolitic nanotubes with customized pores are available.

Engineering mechanical compliance in polymers and composites for the design of smart flexible sensors

Polymers are one of the most popular materials for next-generation flexible sensing device fabrication due to their tunable mechanical and electrical properties. A series of prior research studies in the field of smart flexible and wearable sensing illustrates the potential of various polymer and composite materials to be applied in sensor development. In this direction, mechanical compliance plays a vital role as it ensures the stability and reliability of the fabricated sensor. Therefore, engineering mechanical compliance for the development of smart flexible solutions has emerged as a significant area of research. Furthermore, the usage of flexible sensing devices is rapidly increasing in the field of healthcare devices and robotic automation. This feature article summarizes the relevant contributions of the authors in the field of engineered polymers and composites for flexible sensor development with a focus on healthcare and physical sensing applications. We discuss the polymer and composite materials, their characteristics, fabrication technologies, finite element method analysis, and examples of flexible physical sensors, i.e. pressure, strain, and temperature sensors, for various wearable healthcare applications and robotic automation. Finally, we discuss examples of multi-sensory systems having flexible sensors.

Self-assembly of an amino acid derivative as an anode interface layer for advanced alkaline Al-air batteries

Alkaline Al-air batteries (AABs) are gaining increasing attention for large-scale energy storage systems due to their attractive intrinsic safety and cost-effectiveness. Nonetheless, the future development of AABs is substantially hampered by water-induced self-corrosion processes on the Al anode. In this work, we introduce an amino acid derivative, namely Nα-Boc-N1-formyl-L-tryptophan (NBLT), into a 4 M NaOH electrolyte to construct a unique layer that can effectively regulate the surface microstructure of the Al anode. The findings of the experiments show that NBLT can be used as a reliable corrosion inhibitor. The effectiveness of such inhibitors increases with NBLT concentration, reaching a maximum of 73.9% at 1.5 mM. In comparison to the pristine condition, there is a significant increase in anode utilization from 31.8% to 82.9%, capacity density from 947.9 to 2469.1 mA h g-1, and energy density from 1261.6 to 3384.6 W h kg-1. Theoretical calculations indicate that the carboxyl moieties present in the NBLT molecule establish coordination bonds with the Al atoms, thereby exerting a dominant role in the formation of the self-assembled barrier. The present investigation paves an effective strategy to inhibit reactions between anodes and electrolytes for advanced AABs.

Spatially-assembled binary carbon anode synergizing directional electron transfer and enriched microbe accommodation for wastewater treatment and energy conversion: From simulation to experiments

Bioelectrochemical systems (BESs) hold prospects in wastewater energy and resource recovery. Anode optimization is important for simultaneous enhancement of wastewater energy conversion and effluent quality in BESs. In this study, a multi-physics model coupling fluid flow, organic degradation and electrochemical process was constructed to guide the design and optimization of BES anodes. Based on the multi-physics simulation, spatially-assembled binary carbon anodes composed of three-dimensional carbon mesh skeleton and granular activated carbon were proposed and established. The granular activated carbon conducive to microbe accommodation played a vital role in improving effluent water quality, while the carbon mesh skeleton favoring electron collection and transfer could enhance the bioelectricity output. With an average chemical oxygen demand (COD) removal rate of 0.442 kg m-3 d-1, a maximum power density of 20.6 W m-3 was achieved in the optimized composite anode BES, which was 25% and 154% higher than carbon mesh skeleton BES and granular activated carbon BES. Electroactive bacteria were enriched in composite anodes and performed important functions related to microbial metabolism and energy production. The spatially-assembled binary carbon anode with low carbon mesh packing density was more cost-effective with a daily energy output per anode cost of 221 J d-1 RMB-1. This study not only provides a cost-efficient alternative anode to simultaneously improve organic degradation and power generation performance, but also demonstrates the potential of multi-physics simulation in offering theoretical support and prediction for BES configuration design as well as optimization.

Multiphysics Modeling of Electrochemical Impedance Spectroscopy Responses of SAM-Modified Screen-Printed Electrodes

In this work, we present a multiphysics modeling approach capable of simulating electrochemical impedance spectroscopy (EIS) responses of screen-printed electrodes (SPEs) modified with self-assembled monolayers of 11-Mercaptoundecanoic acid (MUA). Commercially available gold SPEs are electrochemically characterized through experimental cyclic voltammetry and EIS measurements with 10 mM [Fe(CN)6]3-/4- redox couple in phosphate buffered saline before and after the surface immobilization of MUA at different concentrations. We design the multiphysics model through COMSOL Multiphysics® based on the 3D geometry of the devices under test. The model includes four different physics considering the metal/solution interface electrochemical phenomena, the ion and electron potentials and currents, and the measurement set-up. The model is calibrated through a set of experimental measurements, allowing the tuning of the parameters used by the model. We use the calibrated model to simulate the EIS response of MUA-modified SPEs, comparing the results with experimental data. The simulations fit the experimental curves well, following the variation of MUA concentration on the surface from 1 µM to 100 µM. The EIS parameters, retrieved through a CPE-modified Randles' circuit, confirm the consistency with the experimental data. Notably, the simulated surface coverage estimates and the variation of charge transfer resistance due to MUA-immobilization are well matched with their experimental counterparts, reporting only a 2% difference and being consistent with the experimental electrochemical behavior of the SPEs.

Ultra-High Frequency Surface Acoustic Wave Sensors for Temperature Detection

Highly sensitive surface acoustic wave (SAW) sensors have recently been recognized as a promising tool for various industrial and medical applications. However, existing SAW sensors generally suffer from a complex design, large size, and poor robustness. In this paper, we develop a simple and stable delay line ultra-high frequency (UHF) SAW sensor for highly sensitive detection of temperature. A Z-shaped delay line is specially designed on the piezoelectric substrate to improve the sensitivity and reduce the substrate size. Herein, the optimum design parameters of extremely short-pitch interdigital transducers (IDTs) are given by numerical simulations. The extremely short pitch gives the SAW sensor ultra-high operating frequency and consequently ultra-high sensitivity. Several experiments are conducted to demonstrate that the sensitivity of the Z-shaped SAW delay line sensor can reach up to 116.685°/°C for temperature detection. The results show that the sensor is an attractive alternative to current SAW sensing platforms in many applications.

Enhanced Redox Electrocatalysis in High-Entropy Perovskite Fluorides by Tailoring d-p Hybridization

High-entropy catalysts featuring exceptional properties are, in no doubt, playing an increasingly significant role in aprotic lithium-oxygen batteries. Despite extensive effort devoted to tracing the origin of their unparalleled performance, the relationships between multiple active sites and reaction intermediates are still obscure. Here, enlightened by theoretical screening, we tailor a high-entropy perovskite fluoride (KCoMnNiMgZnF3-HEC) with various active sites to overcome the limitations of conventional catalysts in redox process. The entropy effect modulates the d-band center and d orbital occupancy of active centers, which optimizes the d-p hybridization between catalytic sites and key intermediates, enabling a moderate adsorption of LiO2 and thus reinforcing the reaction kinetics. As a result, the Li-O2 battery with KCoMnNiMgZnF3-HEC catalyst delivers a minimal discharge/charge polarization and long-term cycle stability, preceding majority of traditional catalysts reported. These encouraging results provide inspiring insights into the electron manipulation and d orbital structure optimization for advanced electrocatalyst.

Understanding Transient Ionic Diode Currents and Impedance Responses for Aquivion-Coated Microholes

Ionic diode based devices or circuits can be applied, for example, in electroosmotic pumps or in desalination processes. Aquivion ionomer coated asymmetrically over a Teflon film (5 μm thickness) with a laser-drilled microhole (approximately 10 μm diameter) gives a cationic diode with a rectification ratio of typically 10-20 (measured in 0.01 M NaCl with ±0.3 V applied bias). Steady state voltammetry, chronoamperometry, and electrochemical impedance spectroscopy data are employed to characterize the ionic diode performance parameters. Next, a COMSOL 6.0 finite element model is employed to quantitatively assess/compare transient phenomena and to extract mechanistic information by comparison with experimental data. The experimental diode time constant and diode switching process associated with a distorted semicircle (with a typical diode switching frequency of 10 Hz) in the Nyquist plot are reproduced by computer simulation and rationalized in terms of microhole diffusion-migration times. Fundamental understanding and modeling of the ionic diode switching process can be exploited in the rational/optimized design of new improved devices.

Simulation of Corrosion Phenomena in Automotive Components: A Case Study

Mathematical modelling and software simulation nowadays are very effective tools for both understanding and predicting corrosion processes and the protection of metallic components. COMSOL Multiphysics 5.6 software provides validated mathematical models that can be used, for a given geometry, as a tool to predict and prevent corrosion of components. The corrosion of zinc-coated steel sheets has been studied in this work by comparing results of the simulations with laboratory tests carried out in a salt spray. Results of both the mathematical modelling and empirical tests give the possibility to estimate the stability of the protective zinc layer over time. The examination of the discrepancies between two analytical methods for the investigation of corrosion phenomena leads to possible modifications in the model in order to reach as much as possible coherence with experimental data. As a final result, a computational model of corrosion phenomena in an automotive component has been reached, allowing in the future to partially substitute laboratory tests, usually being highly time consuming and expensive.

Sparse reconstruction based on dictionary learning and group structure strategy for cone-beam X-ray luminescence computed tomography

As a dual-modal imaging technology that has emerged in recent years, cone-beam X-ray luminescence computed tomography (CB-XLCT) has exhibited promise as a tool for the early three-dimensional detection of tumors in small animals. However, due to the challenges imposed by the low absorption and high scattering of light in tissues, the CB-XLCT reconstruction problem is a severely ill-conditioned inverse problem, rendering it difficult to obtain satisfactory reconstruction results. In this study, a strategy that utilizes dictionary learning and group structure (DLGS) is proposed to achieve satisfactory CB-XLCT reconstruction performance. The group structure is employed to account for the clustering of nanophosphors in specific regions within the organism, which can enhance the interrelation of elements in the same group. Furthermore, the dictionary learning strategy is implemented to effectively capture sparse features. The performance of the proposed method was evaluated through numerical simulations and in vivo experiments. The experimental results demonstrate that the proposed method achieves superior reconstruction performance in terms of location accuracy, target shape, robustness, dual-source resolution, and in vivo practicability.

Modelling of Nonthermal Dielectric Barrier Discharge Plasma at Atmospheric Pressure and Role of Produced Reactive Species in Surface Polymer Microbial Purification

A nonthermal atmospheric plasma reactor was used to sterilize polymer surfaces and satisfy safety constraints in a biological medium. A 1D fluid model was developed using COMSOL Multiphysics software^® 5.4 with a helium-oxygen mixture at low temperature for the decontamination of bacteria on polymer surfaces. An analysis of the evolution of the homogeneous dielectric barrier discharge (DBD) was carried out through studying the dynamic behavior of the discharge parameters including the discharge current, the consumed power, the gas gap voltage, and transport charges. In addition, the electrical characteristics of a homogeneous DBD under different operating conditions were studied. The results shown that increasing voltage or frequency caused higher ionization levels and maximum increase of metastable species' density and expanded the sterilization area. On the other hand, it was possible to operate plasma discharges at a low voltage and a high density of plasma using higher values of the secondary emission coefficient or permittivity of the dielectric barrier materials. When the discharge gas pressure increased, the current discharges declined, which indicated a lower sterilization efficiency under high pressure. A short gap width and the admixture of oxygen were needed for sufficient bio-decontamination. Plasma-based pollutant degradation devices could therefore benefit from these results.

Microfluidic Fabrication of Gadolinium-Doped Hydroxyapatite for Theragnostic Applications

Among the several possible uses of nanoparticulated systems in biomedicine, their potential as theragnostic agents has received significant interest in recent times. In this work, we have taken advantage of the medical applications of Gadolinium as a contrast agent with the versatility and huge array of possibilities that microfluidics can help to create doped Hydroxyapatite nanoparticles with magnetic properties in an efficient and functional way. First, with the help of Computational Fluid Dynamics (CFD), we performed a complete and precise study of all the elements and phases of our device to guarantee that our microfluidic system worked in the laminar regime and was not affected by the presence of nanoparticles through the flow requisite that is essential to guarantee homogeneous diffusion between the elements or phases in play. Then the obtained biomaterials were physiochemically characterized by means of XRD, FE-SEM, EDX, confocal Raman microscopy, and FT-IR, confirming the successful incorporation of the lanthanide element Gadolinium in part of the Ca (II) binding sites. Finally, the magnetic characterization confirmed the paramagnetic behaviour of the nanoparticles, demonstrating that, with a simple and automatized system, it is possible to obtain advanced nanomaterials that can offer a promising and innovative solution in theragnostic applications.

Use of the repeated integral transformation method to describe the transport of solute in soil

Predicting the fate and transport of contaminants in soil or groundwater systems using analytical or numerical models is crucial for environmental researchers. While the analytical models are a flexible approach to quantifying the subsurface contamination and remediation because they are non-susceptible to numerical dispersions, economical and handier; two-dimensional analytical models that describe a bilateral flow coupled with both sink and decay factors are rarely reported. Motivated by the case of a non-bare soil ridge with constant point-solute source lying internally but parallel to the longitudinal flow direction, a (2 + 1) dimensional Advection-Diffusion-Reaction Equation (ADRE) of bilateral flow coupled with the linear sorption, decay, and sink is formulated to model the transport of dissolved solute in a homogenous and isotropic non-fractured porous medium. Then, a brief review of exact and analytical methods for solving the ADRE is conducted to establish the right solution methods. The Repeated Integral Transformation Method (RITM) is employed to derive the approximate analytical solutions for the formulated model, maintaining the model's original terms for the efficient sensitivity analysis. The RITM uses Laplace and Fourier transforms with a wide range of computed results. We compare the approximate solutions with numerical simulations in COMSOL to verify the accuracy of the approximate analytical models. Then, the application of the solutions is demonstrated through a systematic analysis of the effect on solute transport of advection-diffusion, reaction, sorption, retardation, sink, and pore water velocity. Results show that the presence of sink, mimicked by plant-root uptake activity, and decay tend to reduce the solute concentration in the medium. While both the retardation and sorption factors affect the movement of the dissolved solutes, water content and pore-water velocity promote the spreading of dissolved solutes. Solute concentration in the medium increases at low Peclet numbers, signifying the influence of diffusive coefficients. The current proposed RITM-based solutions can characterize contamination in the soil, and should be useful to environmental researchers.

Use of COMSOL software for modeling and simulation of copper removal in a dynamic mode on a new biowaste

The main purpose of this investigation is to model the results related to biosorption using COMSOL (Multiphysics 4.3a), and to solve the advection-dispersion equation by using both linear and Langmuir models. A bidimensional model was then proposed to study the mass transfer in the process of copper ions sorption in a dynamic mode on cider vinegar residues. Sorption tests were realized by evaluating the influence of flow rate (0.75, 1, and 2.65 ml min^-1 ), bed height (3.5, 7 and 8.5 cm), and copper initial concentration (169 and 300 mg L^-1 ). For all cases, the mathematical formulation was solved by assuming that the column is homogeneous and the sorption is instantaneous. The corresponding results were exploited through breakthrough curve profiles, where it was shown that the solutions obtained by the "Langmuir COMSOL" model coincide with the experimental values. In contrast, the linear model has been unable to fit them. The optimal results were analyzed by Thomas, Adam-Bohart Yoon Nelson, and Ogata-Bank models, which proves that the Thomas method is well adapted with a satisfactory correlation coefficient (0.93). Further, the model validation was performed by determining the residual root mean square error, which was found less than 0.3, thereby indicating a reasonable concordance between the estimated and experimental points. The high sorption capacity obtained was around of 41.37 mg g^-1 , which suggests that the cider vinegar residues can be exploited as a low-cost, available, and effective sorbent biomass in the field of the treatment of industrial effluents. PRACTITIONER POINTS: Cider vinegar residues (CVR) as low cost biosorbent were studied for continuous biosorption. A successful COMSOL model was proposed and validated. CVR is an effective biosorbent for copper fixed bed biosorption. High sorption capacity was around of 41.37 mg g^-1 under optimal conditions.

Ultrafast and hypersensitive phase imaging of propagating internodal current flows in myelinated axons and electromagnetic pulses in dielectrics

Many ultrafast phenomena in biology and physics are fundamental to our scientific understanding but have not yet been visualized owing to the extreme speed and sensitivity requirements in imaging modalities. Two examples are the propagation of passive current flows through myelinated axons and electromagnetic pulses through dielectrics, which are both key to information processing in living organisms and electronic devices. Here, we demonstrate differentially enhanced compressed ultrafast photography (Diff-CUP) to directly visualize propagations of passive current flows at approximately 100 m/s along internodes, i.e., continuous myelinated axons between nodes of Ranvier, from Xenopus laevis sciatic nerves and of electromagnetic pulses at approximately 5 × 107 m/s through lithium niobate. The spatiotemporal dynamics of both propagation processes are consistent with the results from computational models, demonstrating that Diff-CUP can span these two extreme timescales while maintaining high phase sensitivity. With its ultrahigh speed (picosecond resolution), high sensitivity, and noninvasiveness, Diff-CUP provides a powerful tool for investigating ultrafast biological and physical phenomena.

Automated Force-Coupled Ultrasound Method for Calibration-Free Carotid Artery Blood Pressure Estimation

We develop, automate and evaluate a calibration-free technique to estimate human carotid artery blood pressure from force-coupled ultrasound images. After acquiring images and force, we use peak detection to align the raw force signal with an optical flow signal derived from the images. A trained convolutional neural network selects a seed point within the carotid in a single image. We then employ a region-growing algorithm to segment and track the carotid in subsequent images. A finite-element deformation model is fit to the observed segmentation and force via a two-stage iterative non-linear optimization. The first-stage optimization estimates carotid artery wall stiffness parameters along with systolic and diastolic carotid pressures. The second-stage optimization takes the output parameters from the first optimization and estimates the carotid blood pressure waveform. Diastolic and systolic measurements are compared with those of an oscillometric brachial blood pressure cuff. In 20 participants, average absolute diastolic and systolic errors are 6.2 and 5.6 mm Hg, respectively, and correlation coefficients are r = 0.7 and r = 0.8, respectively. Force-coupled ultrasound imaging represents an automated, standalone ultrasound-based technique for carotid blood pressure estimation, which motivates its further development and expansion of its applications.

Topological Resistance-Free One-Way Transport in a Square-Hexagon Lattice Gyromagnetic Photonic Crystal

We theoretically propose and experimentally realize a new configuration of a photonic Chern topological insulator (PCTI) composed of a two-dimensional square-hexagon lattice gyromagnetic photonic crystal immersed in an external magnetic field. This PCTI possesses five distinct types of edges and all of them allowed the propagation of truly one-way edge states. We proceeded to utilize this special PCTI to design topological transmission lines of various configurations with sharp turns. Although the wave impedances of the edge states on both sides of the intersections in these transmission lines were very different, definitely no back reflection occurred and no mode-mixing problems and impedance-mismatching issues at the intersections were present, leading to topological resistance-free one-way transport in the whole transmission line network. Our results enrich the geometric and physical means and infrastructure to construct one-way transport and bring about novel platforms for developing topology-driven resistance-free photonic devices.

Unsupervised classification of voltammetric data beyond principal component analysis

In this study, we evaluate different apoproaches to unsupervised classification of cyclic voltammetric data, including Principal Component Analysis (PCA), t-distributed Stochastic Neighbour Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP) as well as neural networks. To this end, we exploit a form of transfer learning, based on feature extraction in an image recognition network, VGG-16, in combination with PCA, t-SNE or UMAP. Overall, we find that t-SNE performs best when applied directly to numerical data (noise-free case) or to features (in the presence of noise), followed by UMAP and then PCA.

Machine learning-based inverse design for electrochemically controlled microscopic gradients of O2 and H2O2

In microbiology, extracellular oxygen (O₂) and reactive oxygen species (ROS) are spatiotemporally heterogenous, ubiquitously, at macroscopic level. Such spatiotemporal heterogeneities are critical to microorganisms, yet a well-defined method of studying such heterogenous microenvironments is lacking. This work develops a machine learning–based inverse design strategy that builds an electrochemical platform for achieving spatiotemporal control of O₂ and ROS microenvironments relevant to microbiology. The inverse design strategy not only demonstrates the power of machine learning to design concentration profiles in electrochemistry but also accelerates the development of custom microenvironments for specific microbial systems and allows researchers to better study how microenvironments affect microorganisms in myriads of environmental, biomedical, and sustainability-related applications.

A fundamental understanding of extracellular microenvironments of O₂ and reactive oxygen species (ROS) such as H₂O₂, ubiquitous in microbiology, demands high-throughput methods of mimicking, controlling, and perturbing gradients of O₂ and H₂O₂ at microscopic scale with high spatiotemporal precision. However, there is a paucity of high-throughput strategies of microenvironment design, and it remains challenging to achieve O₂ and H₂O₂ heterogeneities with microbiologically desirable spatiotemporal resolutions. Here, we report the inverse design, based on machine learning (ML), of electrochemically generated microscopic O₂ and H₂O₂ profiles relevant for microbiology. Microwire arrays with suitably designed electrochemical catalysts enable the independent control of O₂ and H₂O₂ profiles with spatial resolution of ∼10¹ μm and temporal resolution of ∼10° s. Neural networks aided by data augmentation inversely design the experimental conditions needed for targeted O₂ and H₂O₂ microenvironments while being two orders of magnitude faster than experimental explorations. Interfacing ML-based inverse design with electrochemically controlled concentration heterogeneity creates a viable fast-response platform toward better understanding the extracellular space with desirable spatiotemporal control.

New Microfluidic System for Electrochemical Impedance Spectroscopy Assessment of Cell Culture Performance: Design and Development of New Electrode Material

Electrochemical impedance spectroscopy (EIS) is widely accepted as an effective and non-destructive method to assess cell health during cell-culture. However, there is a lack of compact devices compatible with microfluidic integration and microscopy that could provide the real-time and non-invasive monitoring of cell-cultures using EIS. In this paper, we reported the design and characterization of a modular EIS testing system based on a patented technology. This device was fabricated using easily processable methodologies including screen-printing of the impedance electrodes and molding or micromachining of the cell culture chamber with an easy assembly procedure. Accordingly, to obtain processable, biocompatible and sterilizable electrode materials that lower the impact of interfacial impedance on TEER (Transepithelial electrical resistance) measurements, and to enable concomitant microscopy observations, we optimized the formulation of the electrode inks and the design of the EIS electrodes, respectively. First, electrode materials were based on carbon biocompatible inks enriched with IrOx particles to obtain low interfacial impedance electrodes approaching the performances of classical non-biocompatible Ag/AgCl second-species electrodes. Secondly, we proposed three original electrode designs, which were compared to classical disk electrodes that were optically compatible with microscopy. We assessed the impact of the electrode design on the response of the impedance sensor using COMSOL Multiphysics. Finally, the performance of the impedance spectroscopy devices was assessed in vitro using human airway epithelial cell cultures.

Hybrid 3D printed integrated microdevice for the determination of copper ions in human body fluids

On-site screening of copper ions in body fluid plays a critical role in monitoring human health, especially in heavy pollution areas. In this study, we have developed a hybrid 3D printed integrated microdevice for the determination of copper ions in human body fluids. A fixed and low volume of sample was detected by using the integrated microdevice without any preprocessing. The hybrid channel enables sample uniform mixing and quantitative dilution with buffer solution by inducing the “horseshoe vortex” phenomenon. The electrolytic microcell based on the flow detection system shows a more effective copper ion reaction ratio and, as a result, a better sensitivity. The simulation of the finite element method (FEM) determined the relevant optimum parameters of the hybrid channel and the microcell. The design, fabrication, and detection procedure of the integrated microdevice are here illustrated. The microdevice presented superior detection properties towards copper ions. The calibration curves covered two linear ranges varying from 20 to 100 ppb and 100 to 400 ppb, respectively. The limit of detection was estimated to be 15 ppb (S/N = 3). The relative standard deviation of the peak current measurements was 2.26%. The designed microdevice was further applied to detect copper ions in practical samples (calf serum sample and synthetic human urine sample) using a standard addition method, and the average recovery was found to be 95–104%. The performance of copper ion detection with the integrated microdevice was consistent with that of the inductively coupled plasma mass spectrometry (ICP-MS) in the same practical samples, demonstrating significant practicality in the test of body fluidics. The portable integrated microdevice is an excellent choice for on-site detection and has a promising prospect in the point-of-care testing (POCT) applications.

Study on Micro Production Mechanism of Corner Residual Oil after Polymer Flooding

To study the microscopic production mechanism of corner residual oil after polymer flooding, microscopic visualization oil displacement technology and COMSOL finite element numerical simulation methods were used. The influence of the viscosity and interfacial tension of the oil displacement system after polymer flooding on the movement mechanism of the corner residual oil was studied. The results show that by increasing the viscosity of the polymer, a portion of the microscopic remaining oil in the corner of the oil-wet property can be moved whereas that in the corner of the water-wet property cannot be moved at all. To move the microscopic remaining oil in the corners with water-wet properties after polymer flooding, the viscosity of the displacement fluid or the displacement speed must be increased by 100–1000 times. Decreasing the interfacial tension of the oil displacement system changed the wettability of the corner residual oil, thus increasing the wetting angle. When the interfacial tension level reached 10⁻² mN/m, the degree of movement of the remaining oil in the corner reached a maximum. If the interfacial tension is reduced, the degree of production of the residual oil in the corner does not change significantly. The microscopic production mechanism of the corner residual oil after polymer flooding expands the scope of the displacement streamlines in the corner.

Pressure Drop and Energy Recovery with a New Centrifugal Micro-Turbine: Fundamentals and Application in a Real WDN

Water distribution networks need to improve system efficiency. Hydropower is a clean and renewable energy that has been among the key solutions to environmental issues for many decades. As the turbine is the core of hydropower plants, high attention is paid to creating new design solutions and increasing the performance of turbines in order to enhance energy efficiency of leakage by pressure control. Hence, design and performance analysis of a new turbine is a crucial aspect for addressing the efficiency of its application. In this study, computational fluid dynamics (CFD) modeling is coupled with experimental tests in order to investigate the optimal performance of a new centrifugal turbine. The behavior of the flow through the turbine runner is assessed by means of velocity profiles and pressure contours at all components of the machine under different operating conditions. Finally, the turbine geometry is scaled to a real water distribution network and an optimization procedure is performed with the aim of investigating the optimal location of both the designed new centrifugal micro-turbines (CMT) and pressure reducing valves (PRV) in order to control the excess of pressure and produce energy at the same time.

Mathematical Modeling of the Limiting Current Density from Diffusion-Reaction Systems

The limiting current density is one of to the most important indicators in electroplating for the maximal current density from which a metal can be deposited effectively from an electrolyte. Hence, it is an indicator of the maximal deposition speed and the homogeneity of the thickness of the deposited metal layer. For these reasons, a major interest in the limiting current density is given in practical applications. Usually, the limiting current density is determined via measurements. In this article, a simple model to compute the limiting current density is presented, basing on a system of diffusion–reaction equations in one spatial dimension. Although the model formulations need many assumptions, it is of special interest for screenings, as well as for comparative work, and could easily be adjusted to measurements.

Morphogenesis of Liquid Indium Microdroplets on Solid Molybdenum Surfaces during Solidification at Normal Pressure and under Vacuum Conditions

Electrical and optical applications based on micro- and nanoparticles have specific demands on their interfacial properties. These properties are strongly related to atmospheric conditions to which the particles were exposed during their formation. In this study, metallic In microparticles are synthesized by solidification of In droplets on an amorphous Mo substrate at normal pressure and under vacuum conditions. The influence of ambient pressure on the interface and surface shape is investigated. While solidification at atmospheric pressure leads to collapsed particles with undisturbed contact to the substrate, low pressures result in smooth spherical particles but with cavities inside. Numerical simulations with COMSOL Multiphysics reveal different temperature profiles and heat flux in particles during solidification for both cases. This indicates different starting conditions of the solidification, which leads to the described phenomenon eventually. The investigation of the varying process conditions on the particle shape in combination with the calculated and measured temperature curves over time gives valuable insights into new approaches to synthesize micro- and nanoparticles with defined interfacial properties. Both ambient pressure and cooling rate provide well-controllable and reliable parameters for the realization of different interfacial shapes.

Versatile Tools for Understanding Electrosynthetic Mechanisms

Electrosynthesis is a popular, green alternative to traditional organic methods. Understanding the mechanisms is not trivial yet is necessary to optimize reaction processes. To this end, a multitude of analytical tools is available to identify and quantitate reaction products and intermediates. The first portion of this review serves as a guide that underscores electrosynthesis fundamentals, including instrumentation, electrode selection, impacts of electrolyte and solvent, cell configuration, and methods of electrosynthesis. Next, the broad base of analytical techniques that aid in mechanism elucidation are covered in detail. These methods are divided into electrochemical, spectroscopic, chromatographic, microscopic, and computational. Technique selection is dependent on predicted reaction pathways and electrogenerated intermediates. Often, a combination of techniques must be utilized to ensure accuracy of the proposed model. To conclude, future prospects that aim to enhance the field are discussed.

Transparent Ultramicroelectrodes for Studying Interfacial Charge-Transfer Kinetics of Photoelectrochemical Water Oxidation at TiO2 Nanorods with Scanning Electrochemical Microscopy

Scanning electrochemical microscopy (SECM) has been extensively applied to the electrochemical analysis of the surfaces and interfaces of a photoelectrochemical (PEC) system. A semiconductor photoelectrode with a well-defined geometry and active surface area comparable to SECM's tip is highly desired for accurately quantifying interfacial charge-transfer activities and photoelectrochemically generated redox species, where the broadening effects due to the mass transfer gradient and nonlocal electron transfer at a planar semiconductor surface can be minimized. Here, we present a newly developed platform as a SECM substrate for investigating semiconductor PEC activities, which is based on a transparent ultramicroelectrode (UME) fabricated by using two-step photolithographic patterning and ion milling methods. This transparent UME with a 25 μm recessed disk shape is fully characterized with SECM for quantifying the interfacial charge-transfer rates of IrCl₆^2-/IrCl₆^3- by comparing with theoretical results from finite element simulations in COMSOL Multiphysics. When coated with TiO₂ nanorods as a model semiconductor material, the transparent UME can be used to quantify the catalytic PEC water oxidation in a feedback mode of SECM by sampling tip and substrate current signals simultaneously. This transparent UME-SECM study provides insights into the potential-dependent PEC water oxidation reaction mechanism and the quantitative analysis of photocurrent contributions from water oxidation and the SECM tip-generated redox mediator. The transparent UME-SECM method can be potentially expanded to other SECM operation modes such as surface interrogation for understanding the dynamics of the electrode surfaces and interfaces of a PEC system.

Simulation of Cold Atmospheric Plasma Generated by Floating-Electrode Dielectric Barrier Pulsed Discharge Used for the Cancer Cell Necrosis

A numerical simulation of a pulsed floating electrode dielectric barrier discharge (FE-DBD) at atmospheric pressure, used for melanoma cancer cell therapy, is performed using a plasma model in COMSOL Multiphysics software. Distributions of electron density, space charge, and electric field are presented at different instants of the pulsed argon discharge. Significant results related to the characteristics of the plasma device used, the inter-electrodes distance, and the power supply are obtained to improve the efficiency of FE-DBD apparatus for melanoma cancer cell treatment. The FE-DBD presents a higher sensitivity to short pulse durations, related to the accumulated charge over the dielectric barrier around the powered electrode. At higher applied voltage, more energy is injected into the discharge channel and an increase in electron density and electric consumed power is noted. Anticancer activity provided by the FE-DBD plasma is improved using a small interelectrode distance with a high electron emission coefficient and a high dielectric constant with a small dielectric thickness, allowing higher electron density, generating reactive species responsible for the apoptosis of tumor cells.

A General and Efficient Approach for the Dual-Scale Infiltration Flow Balancing in In Situ Injection Molding of Continuous Fiber Reinforced Thermoplastic Composites

In situ injection molding of continuous fiber reinforced thermoplastic composites is challenged by unbalanced dual-scale infiltration flow due to the pronounced capillary effect. In this paper, a general and efficient approach was proposed for dual-scale infiltration flow balancing based on numerical simulation. Specifically, Stokes and Brinkman equations were used to describe the infiltration flow in inter- and intra-fiber bundles. In particular, capillary pressure drop was integrated in the Brinkmann equation to consider the capillary effect. The infiltration flow front is tracked by the level set method. Numerical simulation and experimental results indicate that the numerical model can accurately demonstrate the unbalanced infiltration flow in inter- and intra-fiber bundles caused by the changes of the injection rate, the resin viscosity, the injection rate, the fiber volume fraction and the capillary number. In addition, the infiltration flow velocity in inter- and intra-fiber bundles can be efficiently tuned by the capillary number, which is mainly determined by the injection rate for a specified resin system. The optimal capillary numbers obtained by simulation and experiment are 0.022 and 0.026, which are very close to each other. Finally, one-dimensional in situ injection molding experiments with constant injection pressure were conducted to prepare fiber reinforced polymerized cyclic butylene terephthalate composite laminate with various flow rates along the infiltration direction. The experimental results confirmed that the lowest porosity and the highest interlaminar shear strength of the composite can only be obtained with the optimized capillary number, which is basically consistent with the simulation results.

Charge regulated solid-liquid interfaces interacting on the nanoscale: Benchmarking of a generalized speciation code (SINFONIA)

Surface chemistry of mineral phases in aqueous environments generates the electrostatic forces involved in particle-particle interactions. However, few models directly take into account the influence of surface speciation and changes in solution speciation when the diffuse layer potential profiles of approaching particles overlap and affect each other. These electrostatic interactions can be quantified, ideally, through charge regulation, considering solution and surface speciation changes upon particle approach by coupling state-of-the-art surface complexation models for the two particle surfaces with a Poisson-Boltzmann type distribution of electrostatic potential and ions in the inter-particle space. These models greatly improve the accuracy of inter-particle force calculations at small inter-particle separations compared to constant charge and constant potential approaches. This work aims at advancing charge regulation calculations by including full chemical speciation and advanced surface complexation models (Basic Stern-, three-, or four plane models and charge distribution concepts), for cases of similar and dissimilar surfaces involving the numerical solution of the Poisson-Boltzmann equation for arbitrary electrolytes. The concept was implemented as a Python-based code and in COMSOL. The flexibility and precision of both, concept and implementations are demonstrated in several benchmark calculations testing the new codes against published results or simulations using established speciation codes, including aqueous speciation, surface complexation and various interaction force examples. Due to the flexibility in terms of aqueous chemistry and surface complexation models for various geometries, a large variety of potential applications can be tackled with the developed codes including industrial, biological, and environmental systems, from colloidal suspensions to gas bubbles, emulsions, slurries like cement paste, as well as new possibilities to assess the chemistry in nano-confined systems.

Prediction of Transient Temperature Distributions for Laser Welding of Dissimilar Metals

Distribution of temperature during the welding process is essential for predicting and realizing some important welding features such as microstructure of the welds, heat-affected zone (HAZ), residual stresses, and their effects. In this paper, a numerical model was developed using COMSOL Multiphysics of dissimilar laser welding (butt joint) of AISI 316L and Ti6Al4V thin sheet of 2.5 mm thickness. A continuous mode (CW) fiber laser heat source of 300 W laser power was used for the present study. A time-dependent prediction of temperature distributions was attempted. The heat source was assumed as a Hermit–Gaussian analytical function with a moving velocity of 120 mm/min. Both convective and radiant heat loss and phase change of the materials were considered for the analysis. In addition, variation of temperature-dependent material properties was also considered. The maximum and minimum temperature for the two materials at different times and the temperature in the different penetration depths were also predicted. It was found that the average temperature that can be achieved in the bottom-most surface near the weld line was more than 2400 K, which justifies the penetration. Averages of maximum temperatures on the weld line at different times at the laser spot irradiation were identified near 3000 K.The temperature fluctuation near the weld line was minimal and decreased more in the traverse direction. Scanning with a displaced laser relative to the interface toward the Ti6Al4V side reduces the maximum temperature at the interface and the HAZ of the 316L side. All of these predictions agree well with the experimental results reported in current literature studies.