This article examines recent discussions on the physical origins, experimental observations, and technological implications of the negative imaginary parts of the complex-valued electromagnetic parameters of materials. It covers roughly four decades of literature, from foundational quantum well gain theory to modern 2D material heterostructures. Topics covered include active plasmonic media, optical gain in semiconductors and dye-doped systems, non-equilibrium populations, and parity-time (PT) symmetric metamaterials. The negative imaginary part of the permittivity acts as a unifying element that connects laser physics, metamaterial design, and ultrafast optical science in engineered complex structures. We review arguments that have generated intense theoretical and experimental interest. In typical passive magnetic materials, the imaginary part of the complex magnetic permeability is positive, indicating energy loss (absorption) from the electromagnetic field into the medium. The detection of a negative imaginary part in certain heterostructures is a remarkable and complex phenomenon: it suggests that the medium can amplify rather than absorb magnetic field energy-a form of active electromagnetic behavior that results from the geometry and physics of the composite system, rather than from an active gain medium itself.

This Tutorial examines theoretical ideas and models related to interfaces and interphases in electrically conductive particle (e.g., carbon black)-filled polymer nanocomposites (PNC). First, special emphasis is placed on connecting these models to the macroscopic properties of PNC, particularly their electrical and mechanical responses. Next, we discuss the critical importance of interfaces and interphases when considering electrical and mechanical signals across multiple characteristic scales, from aggregate to sample. Numerical simulations, which can predict the coupling between mechanics and electromagnetism with explicit control of the individual PNC constituents, are supported by empirically based knowledge and experimental data. These results demonstrate distinct potential opportunities for multifunctional conductive particle-filled PNC, enabling new sensors and 3D smart materials applications to enhance control of electromechanical couplings. Several future directions in this active research area are also briefly discussed. (c) 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license(https://creativecommons.org/licenses/by/4.0/).https://doi.org/10.1063/5.0281380

Our understanding of the effective magnetic permeability of composite materials composed of randomly dispersed metallic ferromagnetic particles within a nonmagnetic (polymer) matrix must respond to several challenges. For these reasons, it is both timely and compelling to consider the primary constraints identified in various modeling approaches in the literature and show that they encounter several critical issues. If not properly addressed, these various systematic constraints in modeling the effective magnetic permeability can introduce limitations in the modeling process.

We consider the hyperelastic response of semi-crystalline ethylene-co-butyl acrylate (EBA) samples filled with carbon black (CB) particles. Such material is structurally complex with its microstructure being characterized by many structural parameters including crosslink density, filler/matrix interfaces, crystallinity, filler network, and chain entanglement which have different degrees of influence on the effective mechanical properties. We evaluate the ability of a number of analytical models to correctly reproduce the non-linear elastic mechanical response of these samples. We do this by considering either dry samples, or samples which are swollen by a non-polar solvent (toluene) at equilibrium, and subjected to uniaxial tension at room temperature. As test cases, we focus on six physical models for the purpose of analyzing the stress-strain curves of samples with different cross-linking densities. Among these frameworks, we show that the Mooney-Rivlin (MR), Ogden, and eight-chain models accurately describe the stress-strain curves of both dry and swollen CB-EBA samples. These findings highlight the possibility of attaining a diverse set of mechanical properties of filled polymer samples by tailoring their structural parameters. A schematic illustration of the effect of solvent (shown by the blue color) absorption on the microstructure of CB-EBA samples.image

We investigate little-appreciated features of the hierarchical core-shell (CS) models of the electrical, mechanical, and electromechanical interactions between the cell membrane (CM) and nuclear envelope (NE). We first consider a simple model of an individual cell based on a coupled resistor-capacitor (Schwan model (SM)) network and show that the CM, when exposed to ac electric fields, acts as a low pass filter while the NE acts as a wide and asymmetric bandpass filter. We provide a simplified calculation for characteristic time associated with the capacitive charging of the NE and parameterize its range of behavior. We furthermore observe several new features dealing with mechanical analogs of the SM based on elementary spring-damper combinations. The chief merit of these models is that they can predict creep compliance responses of an individual cell under static stress and their effective retardation time constants. Next, we use an alternative and a more accurate CS physical model solved by finite element simulations for which geometrical cell reshaping under electromechanical stress (electrodeformation (ED)) is included in a continuum approach with spatial resolution. We show that under an electric field excitation, the elongated nucleus scales differently compared to the electrodeformed cell.

In this work we use ground tire rubber (GTR) powder obtained by grinding worn tire treads as reinforcer agent in flexible polyurethane (PU). Characterization of the microstructure of the as-received powder is achieved using a series of standard techniques including scanning electron microscopy (SEM), granulometry-laser, Fourier transform infrared spectroscopy (FTIR), and x-ray diffraction (XRD). To have complementary physical information the composition and thermal characteristics of the GTR powder, thermogravimetry analysis (TGA) is also performed. The set of these preliminary characterizations shows that the GTR powder particles can be used as reinforcing fillers. For the purpose of good compatibility with the PU matrix, the GTR powder is subjected to chemical treatments for reducing the impurities on the powder particles and to create functional groups at their surface. Subsequently, a series of GTR/PU composite samples are prepared with different weight fractions of GTR using free rising foam method. The GTR/PU composites are then characterized to assess the effect of the GTR content and their chemically pre-treatment on thermal stability, compression mechanical behavior as well as sound attenuation properties. Collectively, these results indicate a significant improvement of both thermal and mechanical properties of the GTR/PU composites compared to the pristine PU matrix. Furthermore, it is also emphasized that the sound absorption response shows a significant shift of the maximum of the absorption coefficient toward lower frequencies resulting from simultaneous increase in air-flow resistivity and tortuosity which can have great potential application in the field of underwater acoustics. The effects of chemical treatments and GTR amount are also discussed. It is also shown that the results show improvement when H2O2 solvent is used in comparison with NaOH, and the optimal properties are reached for PU samples containing 20 wt% of GTR whatever the pre-treatment is. Schematic procedure for fabricating polyurethane foams filled with pre-treated ground tire rubber. image

The macroscopic properties of polymer nanocomposites (PNC) rely largely on the interphase between the polymer chains and the filler particles. One significant difficulty to solve this issue is to quantitatively model the structure-property correlations due to the interfacial region in these complex materials. While dielectric spectroscopy (DS) measurements are routinely used to characterize the effective permittivity of filled polymers, fitting standard effective medium models and mixing equations to these data remains notoriously difficult to interpret. This is due to the absence of explicit reference to internal length scales characterizing the interfaces in the PNC. As an illustrative example, a two-level homogenization framework is proposed which enables the extraction of useful information on the impact of a thin interphase confined on a nanometer length scale based on broadband DS data. This model leads to new ways of tuning the interphase so as to optimize the material's response to electric field, a situation relevant for electromagnetic shielding. This approach provides guidance on how to observe directly and experimentally the actual properties of the interface between the phases (as opposed to model-based inference). Aside from its secure physical foundation in the theory of effective medium, a significant advantage of this approach is that a genetic algorithm (GA) technique applied to this physics-based model enables the uniqueness of the fit parameters to be considered, as the GA method is robust in terms of finding globally optimum solutions, therefore placing confidence in non-universal values of the percolation exponents. Recent work in physics-informed machine learning indicates that the effective dielectric properties of PNC with many degrees of freedom due to their complex morphology can be described by considering only a few degrees of freedom describing the interface features between the phases in these composites. The macroscopic properties of polymer nanocomposites rely largely on the interphase between the polymer chains and the filler particles. A two-level homogenization framework is proposed which enables the extraction of useful information on the impact of a thin interphase confined on a nanometer length scale based on broadband dielectric spectroscopy data. image

We explore the polarization hysteretic behaviour and field-dependent permittivity of ferroelectric-dielectric 2D materials formed by random dispersions of low permittivity inclusions in a ferroelectric matrix, using finite element simulations. We show how the degree of impenetrability of dielectric inclusions plays a substantial role in controlling the coercive field, remnant and saturation polarizations of the homogenized materials. The results highlight the significance of the degree of impenetrability of inclusion in tuning the effective polarization properties of such ferroelectric composites: coercive field drops significantly as percolation threshold is attained and remnant polarization decreases faster than a linear decay.

Polarization-resolved extension of Second Harmonic Generation microscopy (PSHG) exhibits proven efficiency in cancer diagnosis. Contrary to the case of white light microscopy, PSHG can reveal small structural collagen changes, during tumorigenesis, for a broad range of organs such as breast, thyroid, lung, pancreas, and ovary. However, despite its effectiveness for cancer diagnosis, PSHG is not yet fully exploited. One way of improvement consists in taking better advantage of polarization-resolved measurements which are performed by acquiring multiple images (usually between three to 20) of the same sample under different input beam polarization conditions. Each image of the resulting stacked raw images set can contain relevant information not found in the other images of the set. In the literature, information extraction from stacked raw images is performed using methods such as averaging of all images, collagen structural parameters modeling or PSHG polarimetric parameters extraction. If the two latter methods provide a richer information than the first one, they may, however, suffer from a loss of information from the stacked raw images. To examine this potential loss of information, AI methods can be used for extracting information from the stacked raw images. Using recently available images of the public SHG-TIFF database, dealing with breast and thyroid PSHG measurements of both normal and tumor tissues, we test available AI methods for information extraction and benchmark these methods to the state-of-the-art, in terms of automatic cancer diagnosis efficiency.

Room temperature sorption kinetics is conducted on semi-crystalline ethylene-co-butyl acrylate (EBA) polymer samples filled with different contents of carbon black (CB) in polar (ethanol) or non-polar (toluene) solvents. Equilibrium swelling data obtained by solvent uptake measurements are found to decrease as the CB content increases. This is due to the increase of the crosslink density and tortuosity inside the EBA/CB samples. The preferential area occupied by the solvent molecules in the samples is determined by analyzing the behavior of the wetting coefficient. Higher equilibrium uptake and faster solvent penetration are observed for toluene compared to the case of ethanol. Billmeyer's approach, that is phenomenologically sound and insightful while mathematically straightforward to implement, is applied where the specific parameters of this approach are determined from experiments. Subsequently, the transport mechanisms are discussed using the Peppas-Sahlin and Berens-Hopfenberg relaxation-diffusion models. A significant drop in the tensile properties is observed in the swollen samples compared to their dry counterparts. Furthermore, the sorption data and the mechanical response are found to be well correlated. Additionally, the stress-strain curves of the swollen and dry samples under large deformation are analyzed with the Haward-Thackray model by considering microstructure characteristics (CB content, strain hardening modulus, entanglement, cross-linking degree and polymer-solvent interaction).

Interest in the phenomenon of laser ablation (LA) has gained significant attention in recent years due to its potential for machining, high-precision drilling, and cutting materials, such as metals, semiconductors, and dielectrics. Here, LA of ethylene-butyl acrylate (EBA) filled with different volume fractions (4%, 8%, and 20%) of CB particles is studied. Upon irradiation with the second harmonics (532 nm) of the nanosecond pulsed Nd:YAG laser, a structuration is evidenced at the sample surface in a restricted range of fluence and at high pulse number (PN) (500 pulses, 1 Hz). The laser-ablated surface is analyzed by microtopography, scanning electron microscopy (SEM), and x-ray photoelectron spectroscopy (XPS). Collectively, our data show a lowering in ablation threshold and depth for CB volume fractions larger than the conduction threshold (8%), indicating that visible radiation primarily induces photothermal effects. After redeposition of the ablation products at the surface, XPS indicates that high CB content in the EBA matrix induces high oxidation level of the composite surface. Furthermore, our results reveal that LA produces a significant proportion of amorphous carbon. Several parameters which affect heat accumulation and CB particle shielding are discussed. Such parameters include laser fluence and repetition rate, and CB content.

Our interests in biophysics are driven by questions about “how things work” and “why things are” which leads naturally to morphology and emergent dynamic behavior. We are basically interested in getting an insight into how quantitative cell biophysics is implemented today and can offer the appropriate methods to deepen our knowledge and insight. The purpose of this chapter is threefold. First, we aim to discuss topics in physics that are particularly relevant for the scientific community in order to delineate and sharpen EMB’s potential. The organization of this chapter reflects this identification of topics, with each section covering one area. Second, within each section we summarize the state of the art of each of these areas, both from a theoretical and an observational point of view, highlighting central analytical methods and their applications as well as general theoretical and experimental results and their practical applications. Third, in order to keep this chapter both manageable and useful, rather than presenting an extensive detailed review of each topic, we have opted for sufficiently concise reviews, referring to excellent recent articles in the archival literature.

Multi-physics simulation techniques provide a platform that is used to gain insights into complex biological problems with multiple length scales such as cell electrodeformation (ED) and electropermeabilization (EP). However, owing to the large degrees of freedom required to compute the electromechanical properties at very different length scales (membrane thickness, cell size, and customized tissue scaffold) finite element (FE) simulations can be computationally very expensive. Here, we report on a general method of analysis by which we can systematically simulate multiscale ED under direct-current electric fields. In the context of electromechanical continuum behavior, the key novelty of our work is the introduction of a specific Dirichlet boundary condition, i.e. thin-layer approximation (TLA), to represent the capacitive elastic cell membrane. To test the robustness of this newly proposed procedure, Maxwell stress tensor (MST) and cell displacement arising from ED forces obtained with the TLA are compared with a model using a physical thickness of the cell membrane. Furthermore, we present our results in terms of benchmark points for vesicle deformation induced by an electric field excitation and we confirm our approximate results are relevant to predict the aspect ratio characterizing the ellipsoidal deformation of an initially spherical vesicle.