Light-Driven Microrobots for Targeted Drug Delivery.

As a new micromanipulation tool with the advantages of small size, flexible movement and easy manipulation, light-driven microrobots have a wide range of prospects in biomedical fields such as drug targeting and cell manipulation. Recently, microrobots have been controlled in various ways, and light field has become a research hotspot by its advantages of noncontact manipulation, precise localization, fast response, and biocompatibility. It utilizes the force or deformation generated by the light field to precisely control the microrobot, and combines with the drug release technology to realize the targeted drug application. Therefore, this paper provides an overview of light-driven microrobots with drug targeting to provide new ideas for the manipulation of microrobots. Here, this paper briefly categorizes the driving mechanisms and materials of light-driven microrobots, which mainly include photothermal, photochemical, and biological. Then, typical designs of light-driven microrobots with different driving mechanisms and control strategies for multiple physical fields are summarized. Finally, the applications of microrobots in the fields of drug targeting and bioimaging are presented as well as the future prospects of light-driven microrobots in the biomedical field are demonstrated.

Design and implementation of a lab-on-a-chip for assisted reproductive technologies.

Introduction: The microfluidic device is highly optimized to remove oocytes from the cumulus-corona cell mass surrounding them. Additionally, it effectively captures and immobilizes the oocytes, aiding in assessing their quality and facilitating the injection of sperm into the oocyte. In this study, a novel microfluidic chip was designed and manufactured using conventional soft lithography methods. Methods: This research proposes the utilization of a microfluidic chip as a substitute for the conventional manual procedures involved in oocyte denudation, trapping, and immobilization. The microfluidic chip was modeled and simulated using COMSOL Multiphysics® 5.2 software to optimize and enhance its design and performance. The microfluidic chip was fabricated using conventional injection molding techniques on a polydimethylsiloxane substrate by employing soft lithography methods. Results: A hydrostatic force was applied to guide the oocyte through predetermined pathways to eliminate the cumulus cells surrounding the oocyte. The oocyte was subsequently confined within the designated trap region by utilizing hydraulic resistance along the paths and immobilized by applying vacuum force. Conclusion: The application of this chip necessitates a lower level of operator expertise compared to enzymatic and mechanical techniques. Moreover, it is feasible to continuously monitor the oocyte's state throughout the procedure. There is a reduced need for cultural media compared to more standard approaches.

Unveiling Energy Conversion Mechanisms and Regulation Strategies in Perovskite Solar Cells.

Despite recent revolutionary advancements in photovoltaic (PV) technology, further improving cell efficiencies toward their Shockley-Queisser (SQ) limits remains challenging due to inherent optical, electrical, and thermal losses. Currently, most research focuses on improving optical and electrical performance through maximizing spectral utilization and suppressing carrier recombination losses, while there is a serious lack of effective opto-electro-thermal coupled management, which, however, is crucial for further improving PV performance and the practical application of PV devices. In this article, the energy conversion and loss processes of a PV device (with a specific focus on perovskite solar cells) are detailed under both steady-state and transient processes through rigorous opto-electro-thermal coupling simulation. By innovatively coupling multi-physical behaviors of photon management, carrier/ion transport, and thermodynamics, it meticulously quantifies and analyzes energy losses across optical, electrical, and thermal domains, identifies heat components amenable to regulation, and proposes specific regulatory means, evaluates their impact on device efficiency and operating temperature, offering valuable insights to advance PV technology for practical applications.

Tungsten-Doped ZnO as an Electron Transport Layer for Perovskite Solar Cells: Enhancing Efficiency and Stability.

This study delves into enhancing the efficiency and stability of perovskite solar cells (PSCs) by optimizing the surface morphologies and optoelectronic properties of the electron transport layer (ETL) using tungsten (W) doping in zinc oxide (ZnO). Through a unique green synthesis process and spin-coating technique, W-doped ZnO films were prepared, exhibiting improved electrical conductivity and reduced interface defects between the ETL and perovskite layers, thus facilitating efficient electron transfer at the interface. High-quality PSCs with superior ETL demonstrated a substantial 30% increase in power conversion efficiency (PCE) compared to those employing pristine ZnO ETL. These solar cells retained over 70% of their initial PCE after 4000 h of moisture exposure, surpassing reference PSCs by 50% PCE over this period. Advanced numerical multiphysics solvers, employing finite-difference time-domain (FDTD) and finite element method (FEM) techniques, were utilized to elucidate the underlying optoelectrical characteristics of the PSCs, with simulated results corroborating experimental findings. The study concludes with a thorough discussion on charge transport and recombination mechanisms, providing insights into the enhanced performance and stability achieved through W-doped ZnO ETL optimization.

Acoustic Sensors for Monitoring and Localizing Partial Discharge Signals in Oil-Immersed Transformers under Array Configuration.

Partial discharge (PD) is one of the major causes of insulation accidents in oil-immersed transformers, generating a large number of signals that represent the health status of the transformer. In particular, acoustic signals can be detected by sensors to locate the source of the partial discharge. However, the array, type, and quantity of sensors play a crucial role in the research on the localization of partial discharge sources within transformers. Hence, this paper proposes a novel sensor array for the specific localization of PD sources using COMSOL Multiphysics software 6.1 to establish a three-dimensional model of the oil-immersed transformer and the different defect types of two-dimensional models. "Electric-force-acoustic" multiphysics field simulations were conducted to model ultrasonic signals of different types of PD by setting up detection points to collect acoustic signals at different types and temperatures instead of physical sensors. Subsequently, simulated waveforms and acoustic spatial distribution maps were acquired in the software. These simulation results were then combined with the time difference of arrival (TDOA) algorithm to solve a system of equations, ultimately yielding the position of the discharge source. Calculated positions were compared with the actual positions using an error iterative algorithm method, with an average spatial error about 1.3 cm, which falls within an acceptable range for fault diagnosis in transformers, validating the accuracy of the proposed method. Therefore, the presented sensor array and computational localization method offer a reliable theoretical basis for fault diagnosis techniques in transformers.

Finite element solution of coupled multiphysics reaction-diffusion equations for fracture healing in hard biological tissues.

This study proposes a computational framework to investigate the multi-stage process of fracture healing in hard tissues, e.g., long bone, based on the mathematical Bailon-Plaza and Van der Meulen formulation. The goal is to explore the influence of critical biological factors by employing the finite element method for more realistic configurations. The model integrates a set of variables, including cell densities, growth factors, and extracellular matrix contents, managed by a coupled system of partial differential equations. A weak finite element formulation is introduced to enhance the numerical robustness for coarser mesh grids, complex geometries, and more accurate boundary conditions. This formulation is less sensitive to mesh quality and converges smoothly with mesh refinement, exhibiting superior numerical stability compared to previously available strong-form solutions. The model accurately reproduces various stages of healing, including soft cartilage callus formation, endochondral and intramembranous ossification, and hard bony callus development for various sizes of fracture gap. Model predictions align with the existing research and are logically coherent with the available experimental data. The developed multiphysics simulation clarifies the coordination of cellular dynamics, extracellular matrix alterations, and signaling growth factors during fracture healing.

Thermo-Mechanical and Thermo-Electric Properties of a Carbon-Based Epoxy Resin: An Experimental, Statistical, and Numerical Investigation.

Due to their remarkable intrinsic physical properties, carbon nanotubes (CNTs) can enhance mechanical properties and confer electrical and thermal conductivity to polymers currently being investigated for use in advanced applications based on thermal management. An epoxy resin filled with varying concentrations of CNTs (up to 3 wt%) was produced and experimentally characterized. The electrical percolation curve identified the following two critical filler concentrations: 0.5 wt%, which is near the electrical percolation threshold (EPT) and suitable for exploring mechanical and piezoresistive properties, and 3 wt% for investigating thermo-electric properties due to the Joule effect with applied voltages ranging from 70 V to 200 V. Near the electrical percolation threshold (EPT), the CNT concentration in epoxy composites forms a sparse, sensitive network ideal for deformation sensing due to significant changes in electrical resistance under strain. Above the EPT, a denser CNT network enhances electrical and thermal conductivity, making it suitable for Joule heating applications. Numerical models were developed using multiphysics simulation software. Once the models have been validated with experimental data, as a perfect agreement is found between numerical and experimental results, a simulation study is performed to investigate additional physical properties of the composites. Furthermore, a statistical approach based on the design of experiments (DoE) was employed to examine the influence of certain thermal parameters on the final performance of the materials. The purpose of this research is to promote the use of contemporary statistical and computational techniques alongside experimental methods to enhance understanding of materials science. New materials can be identified through these integrated approaches, or existing ones can be more thoroughly examined.

Advancement in computational simulation and validation of congenital heart disease: a review.

The improvement in congenital heart disease (CHD) treatment and management has increased the life expectancy in infants. However, the long-term efficacy is difficult to assess and thus, computational modelling has been applied for evaluating this. Here, we provide an overview of the applications of computational modelling in CHD based on three categories; CHD involving large blood vessels only, heart chambers only, and CHD that occurs at multiple heart structures. We highlight the advancement of computational simulation of CHD that uses multiscale and multiphysics modelling to ensure a complete representation of the heart and circulation. We provide a brief future direction of computational modelling of CHD such as to include growth and remodelling, detailed conduction system, and occurrence of myocardial infarction. We also proposed validation technique using advanced three-dimensional (3D) printing and particle image velocimetry (PIV) technologies to improve the model accuracy.

Generative Artificial Intelligence for Designing Multi-Scale Hydrogen Fuel Cell Catalyst Layer Nanostructures.

Multiscale design of catalyst layers (CLs) is important to advancing hydrogen electrochemical conversion devices toward commercialized deployment, which has nevertheless been greatly hampered by the complex interplay among multiscale CL components, high synthesis cost and vast design space. We lack rational design and optimization techniques that can accurately reflect the nanostructure-performance relationship and cost-effectively search the design space. Here, we fill this gap with a deep generative artificial intelligence (AI) framework, GLIDER, that integrates recent generative AI, data-driven surrogate techniques and collective intelligence to efficiently search the optimal CL nanostructures driven by their electrochemical performance. GLIDER achieves realistic multiscale CL digital generation by leveraging the dimensionality-reduction ability of quantized vector-variational autoencoder. The powerful generative capability of GLIDER allows the efficient search of the optimal design parameters for the Pt-carbon-ionomer nanostructures of CLs. We also demonstrate that GLIDER is transferable to other fuel cell electrode microstructure generation, e.g., fibrous gas diffusion layers and solid oxide fuel cell anode. GLIDER is of potential as a digital tool for the design and optimization of broad electrochemical energy devices.

Numerical computation of heat transfer, moisture transport and thermal comfort through walls of buildings made of concrete material in the city of Douala, Cameroon: An ab initio investigation.

The buildings of the city of Douala in Cameroon have been experiencing degradation for several decades due to the climate characterized by high humidity and oppressive heat. As a result, large grayish or black stains can be observed on these buildings. We sometimes witness the subsidence of the slab of the balconies, the cracking of the walls and the collapse of the buildings worn by the humidity. These damages are generally caused by infiltration and capillary rise. In addition, it has been demonstrated that people living in damp buildings are at risk of illnesses such as asthma and lung infections. Therefore, the novelty of this work is threefold: (i) it proposes for the very first time a numerical study of the transport of humidity and heat through the porous walls of buildings constructed with concrete material, the main construction material in the city of Douala; (ii) It was determined what level of indoor thermal comfort was appropriate for sleeping inside a real three-dimensional G+1 complex residential building constructed with concrete blocks; and (iii) Using the geographical coordinates, and time data, the sun radiation's direction of incidence was assessed throughout the simulation. The computation was performed using Comsol Multiphysics 6.0 software. The distributions of temperature, relative humidity as well as moisture level were presented at various periods. It appears from the results that face to this high humidity, the concrete material retains a large quantity of water for a considerable periods of time, which weakens the steel reinforcement of concrete which is corroded by rust. The computation of thermal comfort in the 3D building showed that the various rooms of the building were not comfortable during the night since temperature inside the building increased progressively due to diffusion of heat. In addition, the numerical solutions indicated that the energy stored within the walls diffused from the external walls to the internal walls during the night. It was also demonstrated that the walls of the building were warmer than the windows, doors and the roof at the computational times, which simply revealed a greater storage capacity of heat in the concrete blocks material. The findings highlighted that the temperature decreased rapidly in a thickness of 0.06 m of the concrete block during the nine days and this decrease was attenuated in the second part of the thickness of the concrete block (0.14 m).

A novel integrated lateral flow immunoassay platform for the detection of cardiac troponin I using hierarchical dendritic copper-nickel nanostructures.

Cardiac troponin I (cTnI) is a critical biomarker for the diagnosis of acute myocardial infarction (AMI). Herein, we report a novel integrated lateral flow immunoassay (LFIA) platform for highly sensitive point-of-care testing (POCT) of cTnI using hierarchical dendritic copper-nickel (HD-nanoCu-Ni) nanostructures. The electrodeposited HD-nanoCu-Ni film (∼22 µm thick) on an ITO-coated glass substrate exhibits superior capillary action and structural integrity. These properties enable efficient sample transport and antibody immobilization, making it a compelling alternative to conventional multi-component paper-based LFIA test strips, which are often plagued by structural fragility and susceptibility to moisture damage. The biofunctionalized HD-nanoCu-Ni substrates were laser-etched with lateral flow channels, including a sample loading/conjugate release zone, a test zone, and a control zone. Numerical simulations were used to further optimize the design of these channels to achieve optimal fluid flow and target capture. The HD-nanoCu-Ni LFIA device utilizes a fluorescence quenching based sandwich immunoassay format using antibody-labeled gold nanoparticles (AuNPs) as quenchers. Two different fluorescent materials, fluorescein isothiocyanate (FITC) and CdSe@ZnS quantum dots (QDs), were used as background fluorophores in the device. Upon the formation of a sandwich immunocomplex with cTnI on the HD-nanoCu-Ni device, introduced AuNPs led to the fluorescence quenching of the background fluorophores. The total assay time was approximately 15 min, demonstrating the rapid and efficient nature of the HD-nanoCu-Ni LFIA platform. For FITC, both inner filter effect (IFE) and fluorescence resonance energy transfer (FRET) contributed to the AuNP-mediated quenching. In the case of CdSe@ZnS QDs, IFE dominated the AuNP-induced quenching. Calibration curves were established based on the relationship between the fluorescence quenching intensity and cTnI concentration in human serum samples, ranging from 0.5 to 128 ng/mL. The limits of detection (LODs) were determined to be 0.27 ng/mL and 0.40 ng/mL for FITC and CdSe@ZnS QDs, respectively. A method comparison study using Passing-Bablok regression analysis on varying cTnI concentrations in human serum samples confirmed the equivalence of the HD-nanoCu-Ni LFIA platform to a commercial fluorescence cTnI LFIA assay kit, with no significant systematic or proportional bias observed.

Empirical and Computational Evaluation of Hemolysis in a Microfluidic Extracorporeal Membrane Oxygenator Prototype.

Microfluidic devices promise to overcome the limitations of conventional hemodialysis and oxygenation technologies by incorporating novel membranes with ultra-high permeability into portable devices with low blood volume. However, the characteristically small dimensions of these devices contribute to both non-physiologic shear that could damage blood components and laminar flow that inhibits transport. While many studies have been performed to empirically and computationally study hemolysis in medical devices, such as valves and blood pumps, little is known about blood damage in microfluidic devices. In this study, four variants of a representative microfluidic membrane-based oxygenator and two controls (positive and negative) are introduced, and computational models are used to predict hemolysis. The simulations were performed in ANSYS Fluent for nine shear stress-based parameter sets for the power law hemolysis model. We found that three of the nine tested parameters overpredict (5 to 10×) hemolysis compared to empirical experiments. However, three parameter sets demonstrated higher predictive accuracy for hemolysis values in devices characterized by low shear conditions, while another three parameter sets exhibited better performance for devices operating under higher shear conditions. Empirical testing of the devices in a recirculating loop revealed levels of hemolysis significantly lower (<2 ppm) than the hemolysis ranges observed in conventional oxygenators (>10 ppm). Evaluating the model's ability to predict hemolysis across diverse shearing conditions, both through empirical experiments and computational validation, will provide valuable insights for future micro ECMO device development by directly relating geometric and shear stress with hemolysis levels. We propose that, with an informed selection of hemolysis parameters based on the shear ranges of the test device, computational modeling can complement empirical testing in the development of novel high-flow blood-contacting microfluidic devices, allowing for a more efficient iterative design process. Furthermore, the low device-induced hemolysis measured in our study at physiologically relevant flow rates is promising for the future development of microfluidic oxygenators and dialyzers.

The Effect of Transverse Sinus Stenosis Caused by Arachnoid Granulation on Patients with Venous Pulsatile Tinnitus: A Multiphysics Interaction Simulation Investigation.

This study aimed to investigate the effect of the transverse sinus (TS) stenosis (TSS) position caused by arachnoid granulation on patients with venous pulsatile tinnitus (VPT) and to further identify the types of TSS that are of therapeutic significance for patients. Multiphysics interaction models of six patients with moderate TSS caused by arachnoid granulation and virtual stent placement in TSS were reconstructed, including three patients with TSS located in the middle segment of the TS (group 1) and three patients with TTS in the middle and proximal involvement segment of the TS (group 2). The transient multiphysics interaction simulation method was applied to elucidate the differences in biomechanical and acoustic parameters between the two groups. The results revealed that the blood flow pattern at the TS and sigmoid sinus junction was significantly changed depending on the stenosis position. Preoperative patients had increased blood flow in the TSS region and TSS downstream where the blood flow impacted the vessel wall. In group 1, the postoperative blood flow pattern, average wall pressure, vessel wall vibration, and sound pressure level of the three patients were comparable to the preoperative state. However, the postoperative blood flow velocity decreased in group 2. The postoperative average wall pressure, vessel wall vibration, and sound pressure level of the three patients were significantly improved compared with the preoperative state. Intravascular intervention therapy should be considered for patients with moderate TSS caused by arachnoid granulations in the middle and proximal involvement segment of the TS. TSS might not be considered the cause of VPT symptoms in patients with moderate TSS caused by arachnoid granulation in the middle segment of the TS.

Interaction of ultrasonic guided waves with interfacial debonding in a stiffened composite plate under variable temperature and operational conditions.

Stiffeners play a vital role in strengthening thin panels in a wide range of engineering constructions by reducing additional structural weight. However, these structures are vulnerable to issues such as interlayer delamination or skin-stiffener interfacial debonding due to high stress levels developed from external environmental conditions and operational loadings. In contrast, ultrasonic-guided wave (UGW) techniques exhibit an efficient and precise approach for monitoring discontinuities or damages in composite structures. There is a lack of research on understanding the characteristics of the interaction between UGW and interfacial debonding when in-plane edge loading and environmental factors are simultaneously taken into account. Therefore, this study is motivated by the need to develop a multiphysics numerical model which employs a commercially available finite element software, COMSOL Multiphysics®, to simulate UGW propagation in a stiffened composite plate with debonding at the plate-stiffener interface through a piezoelectric transducer under the combined influence of in-plane edge load and hygrothermal environment. The stiffened plate and piezoelectric patches are modelled with the tetrahedral element, and the bottom surface of the attached stiffener has a through-width 0.1 mm deep groove simulated for debonding. The developed FE model is validated against the results of the conducted experiments and those found in the available literature through the correlation coefficient. Further, the study conducts a comprehensive parametric investigation on stiffened cross-ply (0/90/0) laminated plates, considering variations in debonding size, in-plane load, and hygrothermal load intensity through the excitation of A0 mode. The acquired response is processed to compare the peak amplitude of various modes and energy of the waveform. Additionally, statistical indices such as normalised correlation moment (NCM) and variance of the continuous wavelet transform (CWT) peak are estimated to understand the impact of various parameters on waveform. The results show that the presence of a 90° lamina in the cross-ply laminate generates a low amplitude S0 mode in the scattered response. Moreover, a mode conversion from A0 to S0 mode is observed due to perfect bonding between the plate and the stiffener, providing insights into the bonding state in the panel. Furthermore, it is found that the magnitude of the in-plane loading marginally affects the peak amplitude of various modes in the scattered response. Additionally, when temperature intensity rises, the energy and amplitude of the UGW signals acquired through piezoelectric patches positioned in a direct line with the actuator gradually increase. The NCM value enhances with debonding regardless of exposed hygrothermal condition and reduces with increasing temperature intensity. In addition, the variance of the CWT peak reduces with debonding. The findings of this research are expected to be helpful for the development of efficient algorithms for detecting damages for structural health monitoring of stiffened composite panels.

Magnetic fields promote electrocatalytic CO2 reduction via subtle modulations of magnetic moments and molecular bonding.

Introducing a magnetic-field gradient into an electrically driven chemical reaction is expected to give rise to intriguing research possibilities. In this work, we elaborate on the modes and mechanisms of electrocatalytic activity (from the perspective of alignment of magnetic moments) and selectivity (at the molecular level) for the CO2 reduction reaction in response to external magnetic fields. We establish a positive correlation between magnetic field strengths and apparent current densities. This correlation can be rationalized by the formation of longer-range ordering of magnetic moments and the resulting decrease in the scattering of conduction electrons and charge-transfer resistances as the field strength increases. Furthermore, aided by the magnetic-field-equipped operando infrared spectroscopy, we find that applied magnetic fields are capable of weakening the C-O bond strength of the key intermediate ∗COOH and elongating the C-O bond length, thereby increasing the faradaic efficiency for the electroreduction of CO2 to CO.

Development of an ultrasound-mediated nano-sized drug-delivery system for cancer treatment: from theory to experiment.

Aim: To establish a methodology for understanding how ultrasound (US) induces drug release from nano-sized drug-delivery systems (NSDDSs) and enhances drug penetration and uptake in tumors. This aims to advance cancer treatment strategies. Materials & methods: We developed a multi-physics mathematical model to elucidate and understand the intricate mechanisms governing drug release, transport and delivery. Unique in vitro models (monolayer, multilayer, spheroid) and a tailored US exposure setup were introduced to evaluate drug penetration and uptake. Results: The results highlight the potential advantages of US-mediated NSDDSs over conventional NSDDSs and chemotherapy, notably in enhancing drug release and inducing cell death. Conclusion: Our sophisticated numerical and experimental methods aid in determining and quantifying drug penetration and uptake into solid tumors.

Analytical and numerical solutions of pore formation in elastic food materials during dehydration.

In this paper, we describe a model for pore formation in food materials during drying. As a proxy for fruits and vegetables, we take a spherical hydrogel, with a stiff elastic skin, and a central cavity filled with air and water vapour. The model describes moisture transport coupled to large deformation mechanics. Both stress and chemical potential are derived from a free energy functional, following the framework developed by Suo and coworkers. We have compared Finite Volume and Finite Element implementations and analytical solutions with each other, and we show that they render similar solutions. The Finite Element solver has a larger range of numerical stability than the Finite Volume solver, and the analytical solution also has a limited range of validity. Since the Finite Element solver operates using the mathematically intricate weak form, we introduce the method in a tutorial manner for food scientists. Subsequently, we have explored the physics of the pore formation problem further with the Finite Element solver. We show that the presence of an elastic skin is a prerequisite for the growth of the central cavity. The elastic skin must have an elastic modulus of at least 10 times that of the hydrogel. An initial pore with 10% of the size of the gel can grow to 5 times its initial size. Such an increase in porosity has been reported in the literature on drying of vegetables, if a dense hard skin is formed, known as case hardening. We discuss that models as presented in this paper, where moisture transport is strongly coupled to large deformation mechanics, are required if one wants to describe pore/structure formation during drying and intensive heating (as baking and frying) of food materials from first principles.

Thermo-Mechanical Optimization of Die Casting Molds Using Topology Optimization and Numerical Simulations.

Conventional cooling channels used in die casting molds exhibit significant drawbacks, resulting in extended cooling times for cast parts. Issues such as the formation of dirt, limescale, and corrosion substantially diminish the thermal efficiency of these channels, leading to challenges in achieving uniform cooling and potential quality issues. In response to these challenges, this study proposes Topology Optimization as a novel approach. It involves designing cooling structures through Topology Optimization to replace traditional cooling channels, incorporating both Discrete and Gaussian boundary conditions to optimize thermal efficiency. Additionally, Structural Topology Optimization is employed to ensure structural integrity, preventing deformation or yielding under high loads during the die casting process. Numerical analysis revealed superior thermal performance compared to conventional channels, particularly when subjected to Discrete and Gaussian boundary conditions. Furthermore, the application of the latter establishes conformal cooling and minimizes temperature gradients in the casting, reducing casting defects such as shrinkage porosity. These findings highlight the efficacy of Topology Optimization in addressing the challenges of traditional cooling methods, with wide-ranging implications for manufacturing processes utilizing permanent molds for shaping materials.

Carbon Binder Domain Inhomogeneity in Silicon-Monoxide/Graphite Composite Anode by 2D Multiphysics Modeling.

The Carbon-binder domain (CBD) plays a pivotal role in the performance of lithium-ion battery electrodes. The heterogeneous distribution of CBD across the electrode has garnered significant attention. However, a thorough understanding of how this CBD inhomogeneity affects anode performance remains a crucial pursuit, especially when considering the inherent material variations present in the SiO/Graphite (SiO/Gr) composite anode. In this study, an electro-chemo-mechanical model is established that provides a detailed geometric description of the particles. This model allows to quantitatively uncover the effects of CBD inhomogeneity on the fundamental behaviors of the SiO/Gr composite anode. The findings indicate that reducing the proportion of CBD in the upper domain (near the anode surface) compared to the lower domain (near the current collector) positively influences electrochemical performance, particularly in terms of capacity and Li plating. However, such an arrangement introduces potential risks of mechanical failures, and it is recommended to incorporate a higher proportion of CBD alongside the SiO particles. Finally, an anode design with a lower CBD proportion in the upper domain exhibits superior rate performance. This study represents a pioneering modeling exploration of CBD inhomogeneity, offering a promising multiphysics model with significant potential for informing advanced battery design considerations.

Image-based predictive modelling frameworks for personalised drug delivery in cancer therapy.

Personalised drug delivery enables a tailored treatment plan for each patient compared to conventional drug delivery, where a generic strategy is commonly employed. It can not only achieve precise treatment to improve effectiveness but also reduce the risk of adverse effects to improve patients' quality of life. Drug delivery involves multiple interconnected physiological and physicochemical processes, which span a wide range of time and length scales. How to consider the impact of individual differences on these processes becomes critical. Multiphysics models are an open system that allows well-controlled studies on the individual and combined effects of influencing factors on drug delivery outcomes while accommodating the patient-specific in vivo environment, which is not economically feasible through experimental means. Extensive modelling frameworks have been developed to reveal the underlying mechanisms of drug delivery and optimise effective delivery plans. This review provides an overview of currently available models, their integration with advanced medical imaging modalities, and code packages for personalised drug delivery. The potential to incorporate new technologies (i.e., machine learning) in this field is also addressed for development.