Advanced Multiphysics Research Articles

Preliminary Verification of Key Physical Models in Oxide Fuel Performance Analysis Code FEATURE Based on COMSOL

Nuclear performance analysis is of great significance for fuel design optimization and the safe operation of a reactor. Considering the design requirements of the China initiative Accelerator Driven System (CiADS) project, it is necessary to develop relevant fuel performance analysis tools to predict fuel performance evolution during service. The Fuel Element Analysis Tool for Undercritical Reactor Engineering (FEATURE) code, based on the advanced multiphysics coupling platform COMSOL software, is under development in this context, with a current focus on oxide fuel for fast reactors. This paper mainly conducts preliminary comparative verification of the oxygen redistribution, plutonium redistribution, and fission gas release modules of the FEATURE code through model examples, code-to-code evaluation, and experimental data. The results indicate that the FEATURE code exhibits good accuracy and reliability in simulating oxygen and plutonium redistribution, as well as fission gas release, making it suitable for integrated coupling calculations.

Free Vibration of Thermally Loaded FG-GPLRC Nanoplates Integrated with Magneto-Electro-Elastic Layers in Contact with Fluid

This work investigates the free vibrations of innovative thermally loaded nanoplates constructed by integrating magneto-electro-elastic (MEE) layers with functionally-graded graphene platelet-reinforced composite cores (FG-GPLRC) and accounting for viscous fluid interactions. An advanced multiphysics model is developed using the Navier–Stokes equations to capture fluid structure coupling effects, Halpin–Tsai, and the rule of mixtures micromechanics to predict the non-uniform effective properties, third-order shear deformation plates theory (TSDPT) to incorporate thickness stretching, and the nonlocal strain gradient theory (NSGT) to characterize size dependencies. The Galerkin technique is used to solve the governing equations, which are derived from the Hamilton’s principle. Parametric analyses quantify the influences of fluid depth, temperature fluctuations, temperature profiles, nonlocal and strain gradient parameters, electric and magnetic potentials, graphene distribution patterns, graphene weight fractions, and boundary conditions on the vibration response. The outcomes of this study provide design guidelines and predictive tools enabling active vibration control systems for next-generation thermally-loaded nanocomposite structures with widespread applications from aerospace vehicles to nanoelectronics.

Unlocking high stability in perovskite solar cells through vacuum-deposited Cs3Bi2I9 thin layer

Perovskite solar cells (PSCs) show great potential for efficient solar energy conversion, but their long-term stability is still a concern. To address this issue, we developed a vacuum-deposited bismuth-based perovskite-like material (Cs3Bi2I9), which forms a high-quality thin film showing remarkable stability over 150 days of air exposure. When combined with a solution-processed MAPbI3 perovskite, the resulting device exhibits improved stability under varying environmental conditions. However, the power conversion efficiency (PCE) drops by 70% compared to the reference MAPbI3-based PSC. An advanced multiphysics optoelectrical device simulation combining 3D FDTD and FEM methods validates these findings, yielding results in excellent agreement with the experimental data. The study also provides insight into the device’s optics and electronic properties, revealing the factors that limit its performance. An optimized device design is proposed to reach an 18.81% PCE, higher than the reference device. The findings have significant implications for developing next-generation solar cells, including high-performance tandem solar cells.

Optimizing indoor air quality and energy efficiency in multifamily residences: Advanced passive pipe system parametrics study

This research focuses on enhancing natural ventilation in multifamily residential buildings to improve air quality and minimize reliance on mechanical ventilation, thereby reducing energy consumption. The study pioneers the integration of passive pipe systems within structural floor slabs and building envelopes, aiming to overcome the inherent challenges of indoor environmental quality (IEQ) related to design constraints, occupant behavior, and urban context. Our innovative approach, utilizing a novel application of Grasshopper for precise architectural modeling and Ansys for advanced multiphysics simulation, enables a detailed comparative analysis of airflow dynamics across various system configurations. A comprehensive literature review underscores the significance of natural ventilation as a key passive cooling strategy, vital for reducing energy use and enhancing IEQ in the face of urbanization challenges. Our empirical findings reveal that configurations with more inlet and outlet pipes significantly outperform simpler ones, with a notable configuration of 11 pipes (5 × 6) achieving an actual-to-required ventilation rate increase in 158.15%. This evidence highlights the substantial benefits of adopting complex system configurations for improved ventilation efficiency. The study’s outcomes include impactful design recommendations for adopting enhanced natural ventilation strategies in multifamily residential buildings. These recommendations promise to inform sustainable urban planning and building management strategies, offering a scalable solution for cities seeking to balance growth with environmental sustainability. By demonstrating the clear advantages of targeted passive cooling interventions, this research contributes valuable insights toward achieving energy efficiency and superior IEQ in residential buildings, paving the way for future exploration in diverse climatic and urban contexts.

Solid Oxide Fuel Cell Anode Porosity and Tortuosity Effect on the Exergy Efficiency

Improving the efficiency of solid oxide fuel cells (SOFCs) is critical for advancing clean energy solutions on a global scale. One major challenge in enhancing SOFC efficiency is reducing anode diffusion polarization, which can significantly hinder performance. This study addresses this issue by investigating the effects of anode tortuosity and porosity on the exergy efficiency of SOFCs. The novelty of this research lies in its comprehensive numerical model, which uniquely incorporates detailed material properties and their impact on SOFC performance—specifically focusing on anode tortuosity and porosity. Using advanced Multiphysics software, we developed a model that solves mass, electron transfer, and energy equations discretized via the finite differences method. The study meticulously examines how variations in these parameters influence SOFC efficiency, providing new insights into optimal anode design. Our methodology involves simulating different anode configurations to pinpoint the key parameters that affect exergy efficiency, thereby minimizing the experimental costs and time associated with traditional approaches. The quantitative results of this study are significant. We found that an anode tortuosity of 5.5 and a porosity range of 0.05–0.1 optimize exergy efficiency, achieving a 15% improvement compared to conventional designs. Additionally, a mean pore radius between 15 and 20 µm was identified as optimal for enhancing cell voltage. These findings elucidate the critical relationship between anode material properties and SOFC performance, offering a practical pathway to improving efficiency. This research provides a novel numerical approach to understanding and optimizing anode characteristics in SOFCs. By highlighting the importance of specific material properties, such as tortuosity and porosity, and demonstrating their impact on exergy efficiency, this study offers valuable guidance for future SOFC design and development.

From text to tech: Shaping the future of physics-based simulations with AI-driven generative models

This micro-article introduces a method for integrating Large Language Models with geometry/mesh generation software and multiphysics solvers, aimed at streamlining physics-based simulations. Users provide simulation descriptions in natural language, which the language model processes for geometry/mesh generation and physical model definition. Initial results demonstrate the feasibility of this approach, suggesting a future where non-experts can conduct advanced multiphysics simulations by simply describing their needs in natural language, while the code autonomously handles complex tasks like geometry building, meshing, and setting boundary conditions.

An open source framework for advanced Multi-physics and multiscale modelling of solid oxide fuel cells

Solid oxide fuel cells are high-efficiency renewable energy devices and considered one of the most promising net-zero carbon energy technologies. Numerical modelling is a powerful tool for the virtual design and optimisation of the next-generation solid oxide fuel cells but needs to tackle issues for incorporating the multi-scale character of the cell and further improving the accuracy and computational efficiency. While most of solid oxide fuel cell models were developed based on closed source platforms which limit the freedom of customisation in numerical discretization schemes and community participation. Here, an open source multi-physics and multiscale platform for advanced SOFC simulations consisting of both cell- and pore-scale performance models was developed using OpenFOAM. The modelling aspects are elucidated in detail, involving the coupling of various physical equations and the implementation of the pore-scale electrode in the performance model. The entire platform was carefully validated against experimental data and the other numerical models which were implemented in commercial software ANSYS Fluent and based on the lattice Boltzmann method. The cell-scale model is subsequently employed to study the effects of different fuels, i.e., pure hydrogen and different ratios of pre-reformed methane gas under various operating temperatures. It is found that the cell-scale model reasonably predicts the effects of these parameters on the cell performance, aligning well with the Fluent model. This study further identified the size of representative element volume with respect to the current density for the anode via the pore-scale model where the realistic microstructures reconstructed by a Xe plasma focused ion beam–scanning electron microscopy are employed as computational domains. It is found that a volume element size of 1243 voxels is sufficient to yield the representative current density of the whole. All these numerical investigations show that OpenFOAM is a potential multi-physics and multi-scale computational platform that is capable of accurately predicting both cell-scale and pore-scale performance and spatial information of solid oxide fuel cells. The developed models are also made public in GitHub to inspire community to further develop around it.

Understanding Photovoltaic Module Degradation: An Overview of Critical Factors, Models, and Reliability Enhancement Methods

Photovoltaic (PV) modules, though reputed for reliability and long lifespans of 25-30 years, commonly experience gradual performance degradation influenced by varying environmental factors. This literature review explores the degradation of PV modules through in-depth analysis of failure modes, characterization techniques, analytical models, and mitigation strategies. A range of failure modes seen in PV modules are discussed, including interconnect breakage, cell cracks, metallization corrosion, delamination, ethylene-vinyl acetate (EVA) discoloration, Potential-Induced Degradation (PID), Light-Induced Degradation (LID), and other. Environmental stresses like temperature, humidity, ultraviolet (UV) radiation, and dust accumulation play significant roles in accelerating almost all degradation modes. Dust is a crucial factor in Middle East/North Africa (MENA) regions. Studying degradation modes under real-world conditions remains challenging, requiring extensive field testing to examine defect frequency, evolution rate, and impacts on energy production. PID is a major degradation mode requiring modeling and correction techniques to improve PV efficiency and lifespan. However, PID models are often limited to specific conditions, posing applicability challenges. Characterization methods like visual inspection, current-voltage (I-V),various imaging methods, and resonance ultrasonic vibrations (RUV) enable effective evaluation of degradation effects on module properties. Analytical models facilitate study of particular degradation modes and prediction of lifetimes under diverse conditions. Key factors influencing PV degradation include weather variations, materials quality, design parameters, PID, and hot spots. Protective coatings, encapsulation improvements, and module cleaning help mitigate degradation and prolong lifespan. A comprehensive understanding of mechanisms through integrated experimentation and modeling is critical for performance improvements. By reviewing major degradation phenomena, characterization techniques, analytical models, and mitigation strategies, this study promotes PV durability and sustainability. Significant knowledge gaps persist regarding module behavior under varied climate conditions and synergistic effects between different degradation mechanisms. Extensive field testing across diverse environments paired with advanced multiphysics modeling can provide valuable insights to guide technological enhancements for robust, long-lasting PV systems worldwide.

A non-invasive multipoint product temperature measurement for pharmaceutical lyophilization

Monitoring product temperature during lyophilization is critical, especially during the process development stage, as the final product may be jeopardized if its process temperature exceeds a threshold value. Also, in-situ temperature monitoring of the product gives the capability of creating an optimized closed-loop lyophilization process. While conventional thermocouples can track product temperature, they are invasive, limited to a single-point measurement, and can significantly alter the freezing and drying behavior of the product in the monitored vial. This work has developed a new methodology that combines non-invasive temperature monitoring and comprehensive modeling. It allows the accurate reconstruction of the complete temperature profile of the product inside the vial during the lyophilization process. The proposed methodology is experimentally validated by combining the sensors’ wirelessly collected data with the advanced multiphysics simulations. The flexible wireless multi-point temperature sensing probe is produced using micro-manufacturing techniques and attached outside the vial, allowing for accurate extraction of the product temperature.

Advanced Couplings and Multiphysics Sensitivity Analysis Supporting the Operation and the Design of Existing and Innovative Reactors

Codes and methods are subjected to a continuous update process for answering the regulatory requirements concerning the long-term operation of existing reactors and new concept deployment. In this continuous improvement process, new generation codes are developed for supporting industrial applications and the long-term strategy. In this paper, attention is devoted to selecting codes under development in France for lattice and core steady-state and transient calculations. These codes, APOLLO3® and CATHARE3, have been selected for carrying out the activities of the H2020 CAMIVVER Project oriented to the 3D-multiphysics couplings improvements. Multiscale and multiphysics solutions are key topics to keep competitiveness and answer to newer industrial needs in plant operations, licensing, and safe operating envelope requirements. The paper presents an overview of the activities performed by Framatome to support the definition of benchmarks exercises proposed in the CAMIVVER Project. Small core configurations subjected to a Reactivity Insertion Accident (RIA) are presented with associated preliminary results. To open the discussions toward the development of Best-Estimate Plus Uncertainties (BEPU) solutions, the URANIE statistical platform was used for sensitivity analysis over different configurations. These preliminary results are also presented.

A Detailed FEM Study on the Vibro-acoustic Behaviour of Crash and Splash Musical Cymbals

Advanced numerical simulations, that include modal and frequency response function finite element analysis, frequency domain and time domain finite element method – boundary element method analysis, are performed to study the vibro-acoustic behaviour of crash and splash musical cymbals. The results of the modal analysis agree well with experimental measurements found in literature. The frequency domain and time domain coupled finite – boundary element method simulations, despite their high computational resources and time demands, are used for the crucial comparison of the velocity spectrograms on the cymbal to the radiated sound pressure spectrograms in the air. The computational analysis results show that the splash cymbal is characterized by a faster decay and a higher frequency content compared to the crash cymbal. The advanced multiphysics vibro-acoustic simulations that correlate the displacements and velocities of the vibrated structure with the radiated sound pressure results demonstrate the future capability to synthesize the sounds of cymbal music instruments.

Photochromism of UV-annealed Fe-doped SrTiO3

High-temperature annealing coupled with above bandgap UV illumination is an emerging approach to manipulate defect chemistries and resultant properties of electroceramics. To explore defect-processing-property relationships in these materials, an advanced multiphysics and multiscale model has been developed, which involves (a) high-fidelity first principles simulations of defect energies, (b) grand canonical thermodynamics of defect equilibria, (c) UV-perturbed defect formation energies from Shockley–Read–Hall generation and recombination, and (d) finite-element analyses of electrostatic potential and defect redistribution. Using this model, bottom-up insights into defect mechanisms associated with the UV-induced brown photochromism of Fe-doped SrTiO3 at high temperatures are provided. It is found that UV illumination leads to dissociation of the FeTi-vO complex and reduction in the oxygen vacancy concentration through exchange with the gas reservoir. Changes to these defect populations cause reionization of the FeTi defect from −1 to 0 charge state to maintain charge neutrality. This collectively gives rise to an increased concentration of FeTi0, which is the source of brown chromism. In addition, this model reproduces the experimentally observed electrical resistance degradation of samples annealed in this manner due to the increasing hole concentration in the material with time. The present model itself offers a route to guide and facilitate future efforts in this field.

Multiphysics coupling in the Exascale computing project

Multiphysics coupling presents a significant challenge in terms of both computational accuracy and performance. Achieving high performance on coupled simulations can be particularly challenging in a high-performance computing context. The US Department of Energy Exascale Computing Project has the mission to prepare mission-relevant applications for the delivery of the exascale computers starting in 2023. Many of these applications require multiphysics coupling, and the implementations must be performant on exascale hardware. In this special issue we feature six articles performing advanced multiphysics coupling that span the computational science domains in the Exascale Computing Project.

(Invited) Modeling and Characterization of Porous Media with Application to Electrochemical Energy Conversion and Storage Devices

Porous media are an integral part of electrochemical energy conversion and storage devices. Among them, we have gas diffusion layers (GDLs) and catalyst layers (CLs) used in polymer electrolyte membrane fuel cells (PEMFCs), as well as fibrous electrodes used in redox flow batteries (RFBs). These porous media must fulfill several critical functions, such as providing a transport pathway for reactants/products through its pore volume and ensuring charge and heat conduction through its solid structure. CLs and active electrodes have the added functionality of providing a reactive surface area. In addition, percolation transport in ion exchange membranes (IEMs) plays a critical role in PEMFCs, RFBs, and related electrochemical devices. On the way to broad commercialization, a thorough understanding of the mass, charge and heat transport properties of these components is crucial to achieving improved performance and durability.Mathematical modeling is one of the key tools used to design new components and optimize the operation of the afore-mentioned devices. However, there are several approaches to achieve this modeling. The most common technique is to use the macroscopic continuum hypothesis, which treats porous media as homogeneous domains with effective transport properties [1,2]. Examples of effective properties are the permeability used in Darcy’s law, the tortuosity factor used to correct Fick’s law of diffusion, or the effective electrical and thermal conductivities used in Ohm’s and Fourier’s laws. Nevertheless, the scientific community has long questioned the applicability of the macro-homogeneous approach to model the thin (thickness~10-500 μm) and heterogeneous porous media used in these technologies. The vast body of work presented in the literature has shown that macro-homogeneous models can be conveniently configured to describe global behaviors and trends. However, the need of guiding the development of improved components, predicting localized effects such as degradation, and diagnosing operation and performance problems demands the development of more advanced multiphysics, multiphase and multiscale models. For this reason, it has become increasingly common to model transport in porous media at the pore scale, either using pore-network modeling (PNM) or direct numerical simulation (DNS) [3-8]. The incorporation of key information extracted from pore-scale models into macroscopic models is necessary to understand electrochemical systems at multiple scales, while keeping computational cost moderate for engineering applications.In this talk, research activities performed in terms of modeling and characterization of porous media in PEMFCs, RFBs and Li-ion batteries will be presented. An overview of pore-scale and macroscopic modeling techniques will be provided, along with the development of composite models aiming to combine the ease of implementation of macroscopic continuum modeling and the computational power of PNM [9-10]. Several topics will be addressed, including two-phase transport in GDLs, mass-transport in RFBs, proton transport in copolymer membranes, and the effect of interfaces and microstructural heterogeneities in GDLs and Li-ion electrodes [1-11].[1] P.A. García-Salaberri et al., J. Power Sources 359 (2017) 634–655.[2] P.A. García-Salaberri et al., Processes 8 (2020) 775.[3] P.A. García-Salaberri et al., Int. J. Heat Mass Trans. 86 (2015) 319–333.[4] P.A. García-Salaberri et al., J. Power Sources 296 (2015) 440–453.[5] P.A. García-Salaberri et al., Electrochim. Acta 295 (2019) 861–874.[6] P.A. García-Salaberri et al., Int. J. Heat Mass Transf. 127 (2018) 687–703.[7] Z.A. Khan, P.A. García-Salaberri, T. Heenan, R. Jervis, P. Shearing, D. Brett, A. Elkamel, J.T. Gostick, J. Electrochem. Soc. 167 (2020) 040528.[8] M. Muñoz-Lorente, J.M. Rubio-Hammo, A. Forner-Cuenca, F.R. Brushett, P.A. García-Salaberri, Analysis of species mass transport in fibrous electrodes of redox flow batteries, Proc. InterPore 2019.[9] P.A. García-Salaberri et al., ECS Trans. 97 (7) 615.[10] P.A. García-Salaberri, Int. J. Heat Mass Trans. (2020), accepted.[11] N. Ureña, M.T. Pérez-Prior, P.A. García-Salaberri, Polymers (2020), submitted.

Resistor–capacitor modeling of the cell membrane: A multiphysics analysis

In this Tutorial, we provide a discussion of “What are cell membrane resistance (MR) and capacitance (MC)?” and then give a number of examples to illustrate how cell membranes constitute nature's ultimate stretchable resistor–capacitor network. There are many approaches to the analysis of the electric field effects in cell membranes, but a particularly intuitive and conceptually straightforward method is to use the biophysically inspired lumped parameter resistor (R)–capacitor (C) network in order to simulate the charging and discharging processes. By developing advanced multiphysics and multiscale numerical analysis, we expect to learn many cross-properties of biological materials which involve multiple spatial or temporal scales. These include electrodeformation (ED) and electroporation (EP) biophysical processes occurring in the cell membrane. In a first stage, we present electric and mechanical circuit analog models of cell membranes and examine their predictions and limitations. An important parameter that researchers can tune with these deterministic approaches is the strength of the transmembrane voltage Vm: at low values of Vm, MC varies quadratically as a function of Vm and MR is infinite, but as Vm is increased at a value below the EP threshold, the membrane should be considered as a nonlinear capacitor. Over the EP threshold, there is a decrease in Vm and MR due to the charge transport across the membrane. Mechanical and electrical stresses, singly or in combination, can result in damage and eventually breakdown of the membrane. In a second stage, the parameters in the finite element (FE) modeling that we present are linked to scales we know should be associated with EP and ED processes. We present simulation data and attempt to determine whether the MC and MR behaviors compare well with experimental observations and/or trends from analytical approaches. MC and MR are correlated with the dielectric, mechanical, and morphological information of cells. For an initially spherical cell exposed to an electric field, monitoring MC and MR reflects a quadratic and then higher order nonlinear behavior as a function of Vm. The quadratic regime scales with spheroidal morphologies of the stressed cell up to a critical value of Vm beyond which higher order nonlinearities arise, and the cell shape is no longer described by a spheroid. Furthermore, we consider the present challenges of connecting electrostatic stress, strain energy in multi-cellular environments to sub-cellular scale material properties, and show that they have the potential to explain the ED and EP of cell membranes via multi-physics and multi-scale numerical analysis. The emergence of Vm as a reporter of neighboring cell interactions is also discussed in a theory-based method for constructing realistic models of tissues based on densely packed environments made by irregularly shaped cells. Of particular interest is the proximity-induced ED and capacitive coupling between neighboring cells, and the subsequent correlation that this has upon anisotropic local ED distribution over a wide range of conditions. For future studies, we identify significant challenges, opportunities, and a sampling of a few used case studies for the development of tissue ED and EP modeling in the coming years.

Advanced methodology for assessing chip package interaction effects on chip performance and reliability after chip assembly and during chip operation

An advanced multiphysics EDA (Electronic Design Automation) methodology is presented for analyzing thermal and thermomechanical problems during chip assembly and operation. The tool-prototype, which was built on the basis of this methodology, employs an anisotropic effective thermal-mechanical property methodology that replaces building complex geometries in finite element analysis simulations, thereby enhancing accuracy and performance significantly. With multiscale capabilities enabled, the tool-prototype first performs full chip stress and temperature analyses and detects hotspots. Then, a detailed analysis is performed in the selected regions of interest, with the resolution adjusted to a feature-scale by adopting a finer grid for extracting effective properties, and enables one to address feature-scale stress-induced issues such as back-end-of-line cracking or stress-induced mobility degradation of transistors. When the tool-prototype is linked with power analysis and layout EDA tools, it can perform the reliability check within the design flow. The assessment procedure will help to design power efficient chips by avoiding thermal and stress hotspots that compromise chip performance and reliability.

Innovative accident tolerant fuel concept enabled through direct manufacturing technology

Nuclear energy is one of the largest sources of carbon-free electricity in the world. Some countries are looking at new ways to support and revitalize the nuclear sector since the Fukushima disaster. The accident tolerant fuel program is geared toward improving the safety of nuclear energy by investigating materials that can replace or modify the current uranium-dioxide nuclear fuel and zirconium-based cladding. This research program is being supported by all major nuclear countries since 2011. The practical limitations on allowable uranium enrichment has taken the focus away from the most promising fuels with high radioactivity retention such as tristructural isotropic particle fuel. To overcome such enrichment limitation, a new fuel concept is proposed using advanced ceramic direct manufacturing with laser-induced chemical vapor deposition. The fuel-as-fiber concept is an accident-tolerant fuel design that features high thermal conductivity, strong capability of radioactivity retention and most importantly requires reasonable enrichment levels with uranium nitride as the fuel. In this work, the initial fabrication of uranium-based fuel with laser-induced chemical vapor deposition technology is demonstrated. Then an advanced multi-physics guided modeling approach based on finite element analysis codes and informed by the manufacturing capabilities is developed to accelerate the advancement of fuel-as-fiber concept for use in current light-water reactor technology. The detailed thermomechanical analysis showed promising results for viability of the innovative fuel-as-fiber concept. The predicted stresses in the fuel structural materials were similar to the case of tristructural isotropic particle fuel experience base that has shown excellent reliability in retention of fuel radioactivity at high temperatures.

Numerical analysis of reactor relevant vibrations using advanced multiphysics CFD-CSM methods

• CFD and CSM codes are coupled. • Validation on Vattenfall Rod Vibration Experiment are performed. • Vibrations from an external load are modelled. • Comparative analyses have been performed.

Feature issue introduction: advanced computational nanophotonics: from materials to devices

Computational nanophotonics has already made a disruptive impact on the photonic and optoelectronic industries and has dramatically influenced the ways today’s optical engineers create, optimize, and use innovative materials and computer-aided services. This Feature Issue presents a set of eleven papers combined under the joint title of Advanced Computational Nanophotonics: From Materials to Devices. The science and art of computational photonics have a long established history, yet interest in new approaches to advanced multiphysics modeling at the nanoscale and hence to innovatory multi-objective optimization techniques for nanophotonics have been growing exponentially in the last decade, and are now the subject of intense cross-disciplinary research efforts. The papers selected for the Feature Issue present a diverse palette of topics that, for example, include a comprehensive review of new optimization techniques, a fundamental theoretical concept of photonic Dirac monopoles, along with new multiphysics approaches to full-wave material modeling in non-linear nanophotonics and, in particular, to innovative modeling of photonic neural networks. Applications of advanced computational methods are additionally showcased with space-time light control by dynamic metasurfaces, polarization control with structured color all-dielectric metafilms, and an optofluidic system driven by a thermoplasmonic element.

Ultrafast dynamics of laser-metal interactions in additive manufacturing alloys captured by in situ X-ray imaging

Advanced in situ characterization is essential for determining the underlying dynamics of laser-material interactions central to both laser welding and the rapidly expanding field of additive manufacturing. Traditional characterization techniques leave a critical experimental gap in understanding the complex subsurface fluid flow and metal evaporation dynamics inherent in laser-induced heating of the metal. Herein, in situ ultra-high-speed transmission X-ray imaging is revealed to be essential for bridging this information gap, particularly via comparison with and validation of advanced multiphysics simulations. Imaging on submicrosecond timescales enables correlation between dynamics of the laser-generated vapor–liquid interface and melt pool surface instabilities in industrially relevant alloys. X-ray imaging and complimentary simulations reveal vapor depression oscillations and rapid expansion due to reflection of the processing laser from the front surface of the vapor depression. Pore formation studies at steady state and during prompt removal of laser heating at the end of track reveal that the rapidly solidifying melt pool traps pores near the base of the vapor-filled depression. Moreover, pores within the melt pool are entrained by Marangoni convection which overcomes the force of buoyancy and forces the pores downward from the surface immediately before solidification. Observed solidification kinetics, consistent with previous results, give insight into surface morphology and porosity in the processed material. The information presented here is key for defining the physical models that describe laser-material interaction and ultimately increases our understanding of the emerging field of laser-based metal additive manufacturing.