Polyurea-Graphene Nanocomposites-The Influence of Hard-Segment Content and Nanoparticle Loading on Mechanical Properties.

Polyurethane and polyurea-based adhesives are widely used in various applications, from automotive to electronics and medical applications. The adhesive performance depends strongly on its composition, and developing the formulation-structure-property relationship is crucial to making better products. Here, we investigate the dependence of the linear viscoelastic properties of polyurea nanocomposites, with an IPDI-based polyurea (PUa) matrix and exfoliated graphene nanoplatelet (xGnP) fillers, on the hard-segment weight fraction (HSWF) and the xGnP loading. We characterize the material using scanning electron microscopy (SEM) and dynamic mechanical analysis (DMA). It is found that changing the HSWF leads to a significant variation in the stiffness of the material, from about 10 MPa for 20% HSWF to about 100 MPa for 30% HSWF and about 250 MPa for the 40% HSWF polymer (as measured by the tensile storage modulus at room temperature). The effect of the xGNP loading was significantly more limited and was generally within experimental error, except for the 20% HSWF material, where the xGNP addition led to about an 80% increase in stiffness. To correctly interpret the DMA results, we developed a new physics-based rheological model for the description of the storage and loss moduli. The model is based on the fractional calculus approach and successfully describes the material rheology in a broad range of temperatures (-70 °C-+70 °C) and frequencies (0.1-100 s-1), using only six physically meaningful fitting parameters for each material. The results provide guidance for the development of nanocomposite PUa-based materials.

Deep Learning-Based Analysis of Glottal Attack and Offset Times in Adductor Laryngeal Dystonia.

OBJECTIVE: Diagnosis of adductor laryngeal dystonia (AdLD) is challenging as it mimics voice features of other voice disorders. This could lead to misdiagnosis (or delayed diagnosis) and ineffective treatments of AdLD. This paper develops automated measurements of glottal attack time (GAT) and glottal offset time (GOT) from high-speed videoendoscopy (HSV) in connected speech as objective measures that can potentially facilitate the diagnosis of this disorder in the future. METHODS: HSV data were recorded from vocally normal adults and patients with AdLD during the reading of the "Rainbow Passage" and six CAPE-V (Consensus Auditory-Perceptual Evaluation of Voice) sentences. A deep learning framework was designed and trained to segment the glottal area and detect the vocal fold edges in the HSV dataset. This automated framework allowed us to automatically measure and quantify the GATs and GOTs for the participants. Accordingly, a comparison was held between the obtained measurements among vocally normal speakers and those with AdLD. RESULTS: The automated framework was successfully developed and able to accurately segment the glottal area/edges. The precise automated measurements of GAT and GOT revealed minor, nonsignificant differences compared to the results of manual analysis-showing a strong correlation between the measures by the automated and manual methods. The results showed significant differences in the GAT values between the vocally normal subjects and AdLD patients, with larger variability in both the GAT and GOT measures in the AdLD group. CONCLUSIONS: The developed automated approach for GAT and GOT measurement can be valuable in clinical practice. These quantitative measurements can be used as meaningful biomarkers of the impaired vocal function in AdLD and help its differential diagnosis in the future.

A GENERAL RETURN-MAPPING FRAMEWORK FOR FRACTIONAL VISCO-ELASTO-PLASTICITY.

We develop a fractional return-mapping framework for power-law visco-elasto-plasticity. In our approach, the fractional viscoelasticity is accounted through canonical combinations of Scott-Blair elements to construct a series of well-known fractional linear viscoelastic models, such as Kelvin-Voigt, Maxwell, Kelvin-Zener and Poynting-Thomson. We also consider a fractional quasi-linear version of Fung's model to account for stress/strain nonlinearity. The fractional viscoelastic models are combined with a fractional visco-plastic device, coupled with fractional viscoelastic models involving serial combinations of Scott-Blair elements. We then develop a general return-mapping procedure, which is fully implicit for linear viscoelastic models, and semi-implicit for the quasi-linear case. We find that, in the correction phase, the discrete stress projection and plastic slip have the same form for all the considered models, although with different property and time-step dependent projection terms. A series of numerical experiments is carried out with analytical and reference solutions to demonstrate the convergence and computational cost of the proposed framework, which is shown to be at least first-order accurate for general loading conditions. Our numerical results demonstrate that the developed framework is more flexible, preserves the numerical accuracy of existing approaches while being more computationally tractable in the visco-plastic range due to a reduction of 50% in CPU time. Our formulation is especially suited for emerging applications of fractional calculus in bio-tissues that present the hallmark of multiple viscoelastic power-laws coupled with visco-plasticity.

Anomalous Nonlinear Dynamics Behavior of Fractional Viscoelastic Beams.

Fractional models and their parameters are sensitive to intrinsic microstructural changes in anomalous materials. We investigate how such physics-informed models propagate the evolving anomalous rheology to the nonlinear dynamics of mechanical systems. In particular, we study the vibration of a fractional, geometrically nonlinear viscoelastic cantilever beam, under base excitation and free vibration, where the viscoelasticity is described by a distributed-order fractional model. We employ Hamilton's principle to obtain the equation of motion with the choice of specific material distribution functions that recover a fractional Kelvin-Voigt viscoelastic model of order α. Through spectral decomposition in space, the resulting time-fractional partial differential equation reduces to a nonlinear time-fractional ordinary differential equation, where the linear counterpart is numerically integrated through a direct L1-difference scheme. We further develop a semi-analytical scheme to solve the nonlinear system through a method of multiple scales, yielding a cubic algebraic equation in terms of the frequency. Our numerical results suggest a set of α-dependent anomalous dynamic qualities, such as far-from-equilibrium power-law decay rates, amplitude super-sensitivity at free vibration, and bifurcation in steady-state amplitude at primary resonance.