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Biophysical cellular information at single-cell sensitivity is becoming increasingly important within analytical and separation platforms that associate the cell phenotype with markers of disease, infection, and immunity. Frequency-modulated electrically driven microfluidic measurement and separation systems offer the ability to sensitively identify single cells based on biophysical information, such as their size and shape, as well as their subcellular membrane morphology and cytoplasmic organization. However, there is a lack of reliable and reproducible model particles with well-tuned subcellular electrical phenotypes that can be used as standards to benchmark the electrical physiology of unknown cell types or to benchmark dielectrophoretic separation metrics of novel device strategies. Herein, the application of red blood cells (RBCs) as multimodal standard particles with systematically modulated subcellular electrophysiology and associated fluorescence level is presented. Using glutaraldehyde fixation to vary membrane capacitance and by membrane resealing after electrolyte penetration to vary interior cytoplasmic conductivity and fluorescence in a correlated manner, each modified RBC type can be identified at single-cell sensitivity based on phenomenological impedance metrics and fitted to dielectric models to compute biophysical information. In this manner, single-cell impedance data from unknown RBC types can be mapped versus these model RBC types for facile determination of subcellular biophysical information and their dielectrophoretic separation conditions, without the need for time-consuming algorithms that often require unknown fitting parameters. Such internal standards for biophysical cytometry can advance in-line phenotypic recognition strategies.

Antimicrobial peptides (AMPs) represent a promising class of compounds to fight antibiotic-resistant infections. In most cases, they kill bacteria by making their membrane permeable and therefore exhibit low propensity to induce bacterial resistance. In addition, they are often selective, killing bacteria at concentrations lower than those at which they are toxic to the host. However, clinical applications of AMPs are hindered by a limited understanding of their interactions with bacteria and human cells. Standard susceptibility testing methods are based on the analysis of the growth of a bacterial population and therefore require several hours. Moreover, different assays are required to assess the toxicity to host cells. In this work, we propose the use of microfluidic impedance cytometry to explore the action of AMPs on both bacteria and host cells, in a rapid manner and with single-cell resolution. We show that the electrical signatures ofBacillus megaterium (B. megaterium)cells and human red blood cells (RBCs) reflect the action of a representative antimicrobial peptide, DNS-PMAP23. In particular, the impedance phase at high frequency (e.g., 11 or 20 MHz) is a reliable label-free metric for monitoring DNS-PMAP23 bactericidal activity and toxicity to RBCs. The impedance-based characterization is validated by comparison with standard antibacterial activity assays and absorbance-based hemolytic activity assays. Furthermore, we demonstrate the applicability of the technique to a mixed sample ofB. megateriumcells and RBCs, which paves the way to study AMP selectivity for bacterial versus eukaryotic cells in presence of both cell types.

Objective: Cell counting and characterization is fundamental for medicine, science and technology. Coulter-type microfluidic devices are effective and automated systems for cell/particle analysis, based on the electrical sensing zone principle. However, their throughput and accuracy are limited by coincidences (i.e., two or more particles passing through the sensing zone nearly simultaneously), which reduce the observed number of particles and may lead to errors in the measured particle properties. In this work, a novel approach for coincidence resolution in microfluidic impedance cytometry is proposed. Methods: The approach relies on: (i) a microchannel comprising two electrical sensing zones and (ii) a model of the signals generated by coinciding particles. Maximum a posteriori probability (MAP) estimation is used to identify the model parameters and therefore characterize individual particle properties. Results: Quantitative performance assessment on synthetic data streams shows a counting sensitivity of 97% and a positive predictive value of 99% at concentrations of $2\times 10^6$ particles/ml. An application to red blood cell analysis shows accurate particle characterization up to a throughput of about 2500 particles/s. An original formula providing the expected number of coinciding particles is derived, and good agreement is found between experimental results and theoretical predictions. Conclusion: The proposed cytometer enables the decomposition of signals generated by coinciding particles into individual particle contributions, by using a Bayesian approach. Significance: This system can be profitably used in applications where accurate counting and characterization of cell/particle suspensions over a broad range of concentrations is required.

Microfluidic impedance cytometry is a label-free technique for high-throughput single-cell analysis. Multi-frequency impedance measurements provide data that allows full characterisation of cells, linking electrical phenotype to individual biophysical properties. To efficiently extract the information embedded in the electrical signals, potentially in real-time, tailored signal processing is needed. Artificial intelligence approaches provide a promising new direction. Here we demonstrate the ability of neural networks to decipher impedance cytometry signals in two challenging scenarios: (i) to determine the intrinsic dielectric properties of single cells directly from raw impedance data streams, (ii) to capture single-cell signals that are hidden in the measured signals of coincident cells. The accuracy of the results and the high processing speed (fractions of ms per cell) demonstrate that neural networks can have an important role in impedance-based single-cell analysis.

This chapter provides an introduction to single-cell electrical characterization techniques and related devices, which play a key role in the framework of label-free biosensing for diagnostics, drug development, and life science. After a brief overview of cell dielectric properties and their modeling using Maxwell Mixture Theory and multi-shell models, three widely used approaches are discussed, namely dielectrophoresis, electrorotation, and microfluidic impedance cytometry. Their basic principles and significance are described, highlighting differences, and common features. Moreover, examples of possible device designs, modes of operation, and applications from recent literature are presented. Finally, emerging trends and expected future developments are discussed.

This paper reports an impedance-based system for the quantitative assessment of dielectrophoretic (DEP) focusing of single particles flowing in a microchannel. Particle lateral positions are detected in two electrical sensing zones placed before and after a DEP-focusing region, respectively. In each sensing zone, particle lateral positions are estimated using the unbalance between the opposite pulses of a differential current signal obtained with a straightforward coplanar electrode configuration. The system is used to monitor the focusing of polystyrene beads of 7 or 10 μm diameter, under various conditions of DEP field intensities and flow rates that produce different degrees of focusing. This electrical approach represents a simple and valuable alternative to optical methods for monitoring of particle focusing systems.

In aerobiological monitoring and agriculture there is a pressing need for accurate, label-free and automated analysis of pollen grains, in order to reduce the cost, workload and possible errors associated to traditional approaches. Methods: We propose a new multimodal approach that combines electrical sensing and optical imaging to classify pollen grains flowing in a microfluidic chip at a throughput of 150 grains per second. Electrical signals and synchronized optical images are processed by two independent machine learning-based classifiers, whose predictions are then combined to provide the final classification outcome. Results: The applicability of the method is demonstrated in a proof-of-concept classification experiment involving eight pollen classes from different taxa. The average balanced accuracy is 78.7 % for the electrical classifier, 76.7 % for the optical classifier and 84.2 % for the multimodal classifier. The accuracy is 82.8 % for the electrical classifier, 84.1 % for the optical classifier and 88.3 % for the multimodal classifier. Conclusion: The multimodal approach provides better classification results with respect to the analysis based on electrical or optical features alone. Significance: The proposed methodology paves the way for automated multimodal palynology. Moreover, it can be extended to other fields, such as diagnostics and cell therapy, where it could be used for label-free identification of cell populations in heterogeneous samples.

The biophysical analysis of single-cells by microfluidic impedance cytometry is emerging as a label-free and high-throughput means to stratify the heterogeneity of cellular systems based on their electrophysiology. Emerging applications range from fundamental life-science and drug assessment research to point-of-care diagnostics and precision medicine. Recently, novel chip designs and data analytic strategies are laying the foundation for multiparametric cell characterization and subpopulation distinction, which are essential to understand biological function, follow disease progression and monitor cell behaviour in microsystems. In this tutorial review, we present a comparative survey of the approaches to elucidate cellular and subcellular features from impedance cytometry data, covering the related subjects of device design, data analytics (i.e., signal processing, dielectric modelling, population clustering), and phenotyping applications. We give special emphasis to the exciting recent developments of the technique (timeframe 2017-2020) and provide our perspective on future challenges and directions. Its synergistic application with microfluidic separation, sensor science and machine learning can form an essential toolkit for label-free quantification and isolation of subpopulations to stratify heterogeneous biosystems.

The study and the characterization of cell death mechanisms are fundamental in cell biology research. Traditional death/viability assays usually involve laborious sample preparation and expensive equipment or reagents. In this work, we use electrical impedance spectroscopy as a label-free methodology to characterize viable, necrotic and apoptotic human lymphoma U937 cells. A simple three-electrode coplanar layout is used in a differential measurement scheme and thousands of cells are measured at high-throughput (≈200 cell/s). Tailored signal processing enables accurate and robust cell characterization without the need for cell focusing systems. The results suggest that, at low frequency (0.5 MHz), signal magnitude enables the discrimination between viable/necrotic cells and cell fragments, whereas phase information allows discriminating between viable cells and necrotic cells. At higher frequency (10 MHz) two subpopulations of cell fragments are distinguished. This work substantiates the prominent role of electrical impedance spectroscopy for the development of next-generation cell viability assays.

While there is a great interest in microfluidic impedance cytometry as a label-free approach for single-particle analysis, the accuracy of the technique is challenged by the positional dependence issue, i.e. identical particles flowing in the microchannel along different trajectories provide different signals. We solve this issue without resorting to particle focusing, by means of a straightforward modification of the conventional wiring scheme for the standard impedance chip comprising two pairs of facing electrodes. Instead of applying the AC voltage to electrodes on the same side of the channel and collecting the differential current flowing through the electrodes on the other side, we apply the AC voltage to diagonally opposite electrodes and collect the differential current flowing through the remaining ones. Therefore, the bipolar signal recorded upon the passage of a particle shows opposite pulses with different amplitude. The relative difference of the latter is a new metric enabling a simple compensation procedure of the signal impedance for off-center particles. Impedance data for 5.2, 6, and 7 μm particles are collected, and coefficients of variation in (electrical) diameter of particles respectively of 2.8%, 1%, and 1.2%, similar to the manufacturers’ quoted values, are obtained. The novel operation mode is successfully implemented also in a coplanar electrode configuration, exploiting two pairs of liquid electrodes.

A simple and effective corotational triangular facet shell finite element is proposed for the geometric nonlinear analysis of thin piezoactuated structures. The structures under investigation are laminated shells composed of elastic layers and sensory/active piezoelectric layers, perfectly bonded to each other. A polar decomposition based corotational framework is adopted. By filtering out large rigid body motions from structural displacements, this framework allows (i) to account for arbitrarily large displacements/rotations, provided strains are small, and (ii) to use existing and high-performance linear elements as core-elements. Within the classical laminated plate theory, the small strain core element formulation based on superposition of OPT membrane and DKT plate element is used, along with a layer-wise constant interpolation of the transversal component of the electric field. Numerical simulations dealing with benchmark problems and applications of technological interest prove accuracy and effectiveness of the proposed formulation.

We present an innovative impedance cytometer for the measurement of the cross-sectional position of single particles or cells flowing in a microchannel. As predicted by numerical simulations and experimentally validated, the proposed approach is applicable to particles/cells with either spherical or non-spherical shape. In particular, the optics-free high-throughput position detection of individual flowing red blood cells (RBCs) is demonstrated and applied to monitor RBCs hydrodynamic focusing under different sheath flow conditions. Moreover, the device provides multiparametric information useful for lab-on-a-chip applications, including particle inter-arrival times and velocity profile, as well as RBCs mean corpuscular volume, distribution width and electrical opacity.

Inkjet printing is here employed for the first time as a method to produce femtoliter-scale oil droplets dispersed in water. In particular, picoliter-scale fluorinated oil (FC40) droplets are printed in the presence of perfluoro-1-octanol surfactant at a velocity higher than 5 m/s. Femtoliter-scale oil droplets in water are spontaneously formed through a fragmentation process at the water/air interface using minute amounts of nonionic surfactant (down to 0.003% v/v of Tween 80). This fragmentation occurs by a Plateau-Rayleigh mechanism at a moderately high Weber number (10(1)). A microfluidic chip with integrated microelectrodes allows droplets characterization in terms of number and diameter distribution (peaked at about 3 mu m) by means of electrical impedance measurements. These results show an unprecedented possibility to scale oil droplets down to the femtoliter scale, which opens up several perspectives for a tailored oil-in-water emulsion preparations, and cellular biology. fabrication for drug encapsulation, pharmaceutic preparations, and cellular biology.

Summary A novel mixed four-node tetrahedral finite element, equipped with nodal rotational degrees of freedom, is presented. Its formulation is based on a Hu–Washizu-type functional, suitable to the treatment of material nonlinearities. Rotation and skew-symmetric stress fields are assumed as independent variables, the latter entering the functional to impose rotational compatibility and suppress spurious modes. Exploiting the choice of equal interpolation for strain and symmetric stress fields, a robust element state determination procedure, requiring no element-level iteration, is proposed. The mixed element stability is assessed by means of an original and effective numerical test. The extension of the present formulation to geometric nonlinear problems is achieved through a polar decomposition-based corotational framework. After validation in both material and geometric nonlinear context, the element performances are investigated in demanding simulations involving complex shape memory alloy structures. Supported by the comparison with available linear and quadratic tetrahedrons and hexahedrons, the numerical results prove accuracy, robustness, and effectiveness of the proposed formulation. Copyright © 2016 John Wiley & Sons, Ltd.

Cell mechanics is a discipline that bridges cell biology with mechanics. Emerging microscale technologies are opening new venues in the field, due to their costeffectiveness, relatively easy fabrication, and high throughput. Two examples of those technologies are discussed here: microfluidic impedance cytometry and erythrocyte electrodeformation. The former is a lab-on-chip technology offering a simple, non-invasive, label-free method for counting, identifying and monitoring cellular biophysical and mechanical function at the single-cell level. The latter is a useful complement to the former, enabling cell deformation under the influence of an applied electric field.

An isogeometric analysis formulation for simulating red blood cell (RBC) electro-deformationis presented. Electrically-induced cell deformation experiments are receiving increasing attention as an attractive strategy for single-cell mechanical phenotyping. As the RBC structure consists in a very thin biological membrane enclosing a nearly-incompressible fluid, (i) a surface shell kinematic model and (ii) the imposition of the shell enclosed-volume conservation constraint are proposed within the isogeometric analysis framework. With regard to the electro-deformation, an accurate evaluation of the electric-field induced forces is achieved by the Maxwell stress tensor approach. A staggered fixed-point iteration scheme is then proposed for performing the electro-mechanical coupling, in order to use reliable mechanical and electrical problem solvers sequentially. Supported by the comparison with experimental results and reference solutions, numerical simulations concerning the large deformation of a RBC by optical tweezers and an in silico electro-deformation experiment prove the accuracy and the effectiveness of the proposed formulation.

The first high-throughput system for the electrical detection of cross-sectional position and velocity of individual particles flowing through a rectangular microchannel is presented. Lateral position (along channel width) and vertical position (along channel height) are measured using two different sets of coplanar electrodes. In particular, the ratio of travel times measured with electrodes generating a current flow transverse or oblique with respect to particle trajectory yields lateral position. The relative prominence and transit time of a bipolar double-Gaussian signal obtained with a suited electrode configuration, respectively, supply vertical position and velocity. The operating principle is presented by means of finite element numerical simulations. The method is experimentally validated by comparing the electrical estimates of position and velocity of polystyrene beads with optical estimates obtained by processing high-speed images. The system is used to observe bead focusing at different particle Reynolds numbers. This system, providing a fully electrical characterization of single-particle motion, represents a powerful tool, e.g. to understand fluid motion at the microscale, in particle separation studies, or to assess the performance of particle focusing devices. Moreover, it can be simultaneously used to perform single-cell impedance spectroscopy, thus achieving an unprecedented multiparamteric characterization.

The accurate determination of the geometrical features of quasi one-dimensional nanostructures is mandatory for reducing errors and improving repeatability in the estimation of a number of geometry-dependent properties in nanotechnology. In this paper a method for the reconstruction of length and spatial orientation of single nanowires (NWs) is presented. Those quantities are calculated from a sequence of scanning electron microscope (SEM) images taken at different tilt angles using a simple 3D geometric model. The proposed method is evaluated on a collection of SEM images of single GaAs NWs. It is validated through the reconstruction of known geometric features of a standard reference calibration pattern. An overall uncertainty of about 1% in the estimated length of the NWs is achieved.

Microfluidic impedance cytometry offers a simple non-invasive method for single-cell analysis. Coplanar electrode chips are especially attractive due to ease of fabrication, yielding miniaturized, reproducible, and ultimately low-cost devices. However, their accuracy is challenged by the dependence of the measured signal on particle trajectory within the interrogation volume, that manifests itself as an error in the estimated particle size, unless any kind of focusing system is used. In this paper, we present an original five-electrode coplanar chip enabling accurate particle sizing without the need for focusing. The chip layout is designed to provide a peculiar signal shape from which a new metric correlating with particle trajectory can be extracted. This metric is exploited to correct the estimated size of polystyrene beads of 5.2, 6 and 7 μm nominal diameter, reaching coefficient of variations lower than the manufacturers' quoted values. The potential impact of the proposed device in the field of life sciences is demonstrated with an application to Saccharomyces cerevisiae yeast.

The performance of a novel microfluidic impedance cytometer (MIC) with coplanar configuration is investigated in silico. The main feature of the device is the ability to provide accurate particle-sizing despite the well-known measurement sensitivity to particle trajectory. The working principle of the device is presented and validated by means of an original virtual laboratory providing close-to-experimental synthetic data streams. It is shown that a metric correlating with particle trajectory can be extracted from the signal traces and used to compensate the trajectory-induced error in the estimated particle size, thus reaching high-accuracy. An analysis of relevant parameters of the experimental setup is also presented.

In this chapter collisions of rigid solids are considered. In particular, the multiple collisions of three balls evolving in a box are investigated. This is a 3D problem, because balls may jump.

Microfluidic impedance cytometry is a label-free approach for high-throughput analysis of particles and cells. It is based on the characterization of the dielectric properties of single particles as they flow through a microchannel with integrated electrodes. However, the measured signal depends not only on the intrinsic particle properties, but also on the particle trajectory through the measuring region, thus challenging the resolution and accuracy of the technique. In this work we show via simulation that this issue can be overcome without resorting to particle focusing, by means of a straightforward modification of the wiring scheme for the most typical and widely used microfluidic impedance chip.

This work presents a new state update algorithm for small-strain associative elastic-plastic constitutive models, treating in a unified manner a wide class of deviatoric yield functions with linear or nonlinear strain-hardening. The algorithm is based on an incremental energy minimization approach, in the framework of generalized standard materials with convex free energy and dissipation potential. An efficient method for the computation of the latter, its gradient and its Hessian is provided, using Haigh-Westergaard stress invariants. Numerical results on a single material point loading history and finite element simulations are reported to prove the effectiveness and the versatility of the method. Its merit turns out to be complementary to the classical return map strategy, because no convergence difficulties arise if the stress is close to high curvature points of the yield surface.

A flat triangular element for the nonlinear analysis of thin shells is presented. The formulation relies on (i) a polar decomposition based corotational framework and (ii) a core-element kinematic description adopting the multiplicative superposition of membrane and bending actions. The resulting element is a refined yet simple three-node displacement-based triangle accounting for thickness extensibility and initial shell curvature, and equipped with a fully consistent tangent stiffness. Numerical tests involving shell structures made of rubber-like materials or fibred biological tissues show the effectiveness of the proposed element and its suitability to problems characterized by large displacements, large rotations, large membrane strains and bending. A Matlab toolkit implementing the present formulation is provided as supplementary material.

SUMMARY A polar decomposition based corotational formulation for deriving geometrically nonlinear triangular shell elements is proposed. This formulation is novel in two aspects. (1) Original formulas for the projector operator and its variation are presented, leading to simple algorithms for the computation of the nodal residual vector and of the consistent tangent stiffness tensor. (2) For the first time in the context of a corotational kinematic description, a rigorous treatment of distributed dead and follower loads is performed, thoroughly accounting for the various contributions entailed in the residual vector and in the tangent stiffness. Numerical simulations of popular benchmark problems are reported, showing the effectiveness of the proposed approach. An accessible and adaptable MATLAB toolkit implementing the present formulation is provided as supplementary material.* Copyright © 2013 John Wiley & Sons, Ltd.

In this chapter collisions of rigid solids are considered. In particular, the multiple collisions of three disks evolving in a plane are investigated. Among the interesting results, let us mention that the restitution coefficient developed for collisions of two solids, is a misleading notion when three solids are involved.

Due to its crucial role in pathophysiology, erythrocyte deformability represents a subject of intense experimental and modeling research. Here a computational approach to electro-deformation for erythrocyte mechanical characterization is presented. Strong points of the proposed strategy are: (1) an accurate computation of the mechanical actions induced on the cell by the electric field, (2) a microstructurally-based continuum model of the erythrocyte mechanical behavior, (3) an original rotation-free shell finite element, especially suited to the application in hand. As proved by the numerical results, the developed tool is effective and sound, and can foster the role of electro-deformation in single-cell mechanical phenotyping.

At present, mammography is the most effective examination for an early diagnosis of breast cancer. Nevertheless, the detection of cancer signs in mammograms is a difficult procedure owing to the great number of non-pathological structures which are also present in the image. Recent statistics show that in current breast cancer screenings 10%-25% of the tumors are missed by the radiologists. For this reason, a lot of research is currently being done to develop systems for Computer Aided Detection (CADe). Probably, some causes of the false-negative screening examinations are that tumoral masses have varying dimension and irregular shape, their borders are often ill-defined and their contrast is very low, thus making difficult the discrimination from parenchymal structures. Therefore, in a CADe system a preliminary segmentation procedure has to be implemented in order to separate the mass from the background tissue. In this way, various characteristics of the segmented mass can be evaluated and used in a classification step to discriminate benign and malignant cases. In this paper, we describe an effective algorithm for massive lesions segmentation based on a region-growing technique and we provide full details the performance evaluation procedure used in this specific context.

We investigate the quasi-potential problem for the entropy cost functionals of non-entropic solutions to scalar conservation laws with smooth fluxes. We prove that the quasi-potentials coincide with the integral of a suitable Einstein entropy., Comment: 26 pages, 4 figures

Mammography is the most effective method for the early detection of breast diseases. However, the typical diagnostic signs such as microcalcifications and masses are difficult to detect because mammograms are low-contrast and noisy images. In this paper, a novel algorithm for image denoising and enhancement based on dyadic wavelet processing is proposed. The denoising phase is based on a local iterative noise variance estimation. Moreover, in the case of microcalcifications, we propose an adaptive tuning of enhancement degree at different wavelet scales, whereas in the case of mass detection, we developed a new segmentation method combining dyadic wavelet information with mathematical morphology. The innovative approach consists of using the same algorithmic core for processing images to detect both microcalcifications and masses. The proposed algorithm has been tested on a large number of clinical images, comparing the results with those obtained by several other algorithms proposed in the literature through both analytical indexes and the opinions of radiologists. Through preliminary tests, the method seems to meaningfully improve the diagnosis in the early breast cancer detection with respect to other approaches.

Microfluidic impedance cytometry is emerging as a powerful label-free technique for the characterization of single biological cells. In order to increase the sensitivity and the specificity of the technique, suited digital signal processing methods are required to extract meaningful information from measured impedance data. In this study, a simple and robust event-detection algorithm for impedance cytometry is presented. Since a differential measuring scheme is generally adopted, the signal recorded when a cell passes through the sensing region of the device exhibits a typical odd-symmetric pattern. This feature is exploited twice by the proposed algorithm: first, a preliminary segmentation, based on the correlation of the data stream with the simplest odd-symmetric template, is performed; then, the quality of detected events is established by evaluating their $\text{E$_{2}$O}$ index, that is, a measure of the ratio between their even and odd parts. A thorough performance analysis is reported, showing the robustness of the algorithm with respect to parameter choice and noise level. In terms of sensitivity and positive predictive value, an overall performance of 94.9% and 98.5%, respectively, was achieved on two datasets relevant to microfluidic chips with very different characteristics, considering three noise levels. The present algorithm can foster the role of impedance cytometry in single-cell analysis, which is the new frontier in “Omics.”

Cell shape is a fundamental biological feature, providing specific information about physiological or pathological cellular conditions. Most of the state-of-the-art microfluidic cytometers, however, only allow simple cell analysis, including viability studies, cell counting and sorting. In this work, we present a non-invasive, label-free device capable of single cell morphology discrimination in continuous flow. The device is based on the principle of liquid electrodes, fabricated in a cross configuration around a sensing zone. This arrangement allows measurement of cell impedance along orthogonal orientations and extraction of an index describing cell shape anisotropy. By adding prior to the sensing volume a series of lateral liquid electrodes, the particle stream was focused toward the channel midline and each cell was oriented in a specific direction before shape sensing. We demonstrate the proof of concept by performing spherical and elongated particle discrimination. As an application, we show that the shape changes experienced during cell division can be monitored and characterized. In particular, budding yeasts at different stages of the mitotic cycle were identified by extracting their anisotropy index.

This contribution shows the effectiveness and versatility of the corotational formulation in the development of shell finite elements for geometric and material nonlinear analysis of thin structures. In particular, flat triangular elements especially suited to shell structures made of shape memory alloys (SMA) or soft biological tissues are dealt with. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)

Aim of this paper is to develop a new shape memory alloy (SMA) facet-shell finite element accounting for material and geometric nonlinearities. A corotational formulation is exploited, able to filter out large rigid-body motions from the element transformation. Accordingly, a geometrically linear core-element is employed, along with a SMA constitutive model formulated in the small strain framework. In particular, in accordance with the formulation of the classical thin shell theory, a plane-stress SMA model accounting for the pseudo-elastic as well as the shape memory effect is adopted. The time integration of the evolutive equation is performed developing a step-by-step backward-Euler numerical procedure. A highly efficient implementation of the corotational machinery is used, endowed with a fully consistent tangent stiffness. Applications are carried out for assessing the performances of the developed computational procedure and to investigate on some interesting engineering examples. The numerical results show the effectiveness of the proposed shell element, whose simplicity makes it attractive for the design of new advanced SMA-based devices undergoing significant configuration changes during their operation.

A new microfluidic cytometer for single-cell dielectric spectroscopy is proposed in this paper and analyzed in silico by means of a finite-element model. The device, inspired by electrical impedance tomography, includes two circumferential arrays of electrodes instead of just two pairs of coplanar or parallel-facing electrodes, thus allowing a great versatility in stimulation and measurement patterns. In particular, using stimulation patterns with different spatial orientation provides information on cell morphology, besides quantitative cell-volume estimation. Moreover, the performance limitation at low frequency due to electrode polarization is overcome, owing to a peculiar recording scheme: Current is injected between an electrode pair, and the resulting voltages are measured at remaining electrodes using high-input impedance differential amplifiers. These features significantly enhance the cytometer discrimination capabilities.