Properties Of Soft Materials Research Articles

Rapid onset of molecular friction in liquids bridging between the atomistic and hydrodynamic pictures

Friction in liquids arises from conservative forces between molecules and atoms. Although the hydrodynamics at the nanoscale is subject of intense research and despite the enormous interest in the non-Markovian dynamics of single molecules and solutes, the onset of friction from the atomistic scale so far could not be demonstrated. Here, we fill this gap based on frequency-resolved friction data from high-precision simulations of three prototypical liquids, including water. Combining with theory, we show that friction in liquids emerges abruptly at a characteristic frequency, beyond which viscous liquids appear as non-dissipative, elastic solids. Concomitantly, the molecules experience Brownian forces that display persistent correlations. A critical test of the generalised Stokes–Einstein relation, mapping the friction of single molecules to the visco-elastic response of the macroscopic sample, disproves the relation for Newtonian fluids, but substantiates it exemplarily for water and a moderately supercooled liquid. The employed approach is suitable to yield insights into vitrification mechanisms and the intriguing mechanical properties of soft materials.

100th Anniversary of Macromolecular Science Viewpoint: Polymerization of Cumulated Bonds: Isocyanates, Allenes, and Ketenes as Monomers.

Polymer chemistry offers exciting opportunities to tailor the properties of soft materials through control of the composition of the polymers and their interaction with each other, additives, and surfaces. Ongoing advances in the synthesis of polymeric materials demonstrate the drive for materials with tailored properties for enhanced performance in the next generation of materials and devices. One class of small molecules that can serve as monomers in chain growth polymerization are cumulated double bonds of the general form X═Y═Z. The three most common classes of these molecules are isocyanates (N═C═O), allenes (C═C═C), and ketenes (C═C═O), each of which has been explored as monomers under a variety of conditions. The orthogonality of the two pi bonds of the cumulated double bonds (i.e., lack of conjugation) enables the formation of different polymer backbones from a single monomer, provided the regioreactivity is controlled. This Viewpoint outlines the use of these three cumulated double bonds as monomers, illustrating success and current limitations to established polymerization methods. We then provide an outlook to the future of cumulated double bonds as monomers for the generation of tailored polymer compositions.

Diacetylene-Functionalized Dendrons: Self-Assembled and Photopolymerized Three-Dimensional Networks for Advanced Self-Healing and Wringing Soft Materials.

The physical properties of supramolecular soft materials strongly depend on the molecular packing structures constructed by thermodynamically and kinetically controlled molecular self-assembly. To investigate the relationship between molecular function and self-assembled molecular packing structure, a series of diacetylene (DA)-based supramolecules was synthesized by chemically connecting flexible dendrons to DA with amide (aDA-D) or ester (eDA-D) functions. The three-dimensional (3D) organogel network of amide-functionalized aDA-D was prepared in both polar and nonpolar solvents due to the intermolecular hydrogen bonding. 3D networks of aDA-D can be further stabilized by topochemical photopolymerization. The self-healing behavior of aDA-D was observed in the sheet-like structure formed in n-dodecane by the hydrophobic interaction between the gelator and solvent. The wringing behavior of aDA-D was also demonstrated using the dynamic interaction of amide function with n-butanol solvent. Kinetically controlled and photostabilized 3D networks can be a key component from biomedical devices to soft robotic applications.

In vitro evaluation of physicochemical properties of soft lining resins after incorporation of chlorhexidine

Statement of problemIncorporating chlorhexidine into soft lining materials has been suggested to reduce biofilm development on the material surface and treat denture stomatitis. However, evaluation of the physicochemical properties of this material is necessary. PurposeThe purpose of this in vitro study was to evaluate the physicochemical properties of resin-based denture soft lining materials modified with chlorhexidine diacetate (CDA). Material and methodsTwo soft lining resins were tested, one based on polymethyl methacrylate (PMMA) and the other on polyethyl methacrylate (PEMA), into which 0.5%, 1.0%, or 2.0% of CDA was incorporated; the control group had no CDA. The specimens were stored for 2 hours, 48 hours, 7, 14, 21, and 28 days and then analyzed for polymer crystallinity, Shore A hardness, degree of monomer conversion, residual monomer leaching, and CDA release. Data were analyzed by using a 3-way ANOVA and the Tukey HSD test (α=.05). ResultsThe polymer crystallinity of PEMA and PMMA did not change after CDA incorporation. Shore A hardness increased over time, but not for any CDA concentrations tested after 28 days (P>.05). Considering the degree of conversion, PMMA-based resin showed no statistically significant difference (P>.05). However, PEMA-based resin showed a significant decrease (P<.05), which was reflected in a significant increase in residual monomer leaching from PEMA-based resin with the incorporation of 0.5% and 1.0% CDA (P<.05), mainly in the first 48 hours. PMMA-based resin showed no change in monomer leaching (P>.05). For both resins, the CDA release kinetics were related to monomer leaching; for PEMA-based resin, the values were significantly higher in the first 48 hours (P<.05), and for PMMA-based resin, the values were more sustained up to the last day of analysis. ConclusionsThe incorporation of CDA did not affect the physicochemical properties of soft resins. The properties of PMMA were better than those of PEMA.

Photoprogrammable Mesogenic Soft Helical Architectures: A Promising Avenue toward Future Chiro-Optics.

Mesogenic soft materials, having single or multiple mesogen moieties per molecule, commonly exhibit typical self-organization characteristics, which promotes the formation of elegant helical superstructures or supramolecular assemblies in chiral environments. Such helical superstructures play key roles in the propagation of circularly polarized light and display optical properties with prominent handedness, that is, chiro-optical properties. The leveraging of light to program the chiro-optical properties of such mesogenic helical soft materials by homogeneously dispersing photosensitive chiral material into an achiral soft system or covalently connecting photochromic moieties to the molecules has attracted considerable attention in terms of materials, properties, and potential applications and has been a thriving topic in both fundamental science and application engineering. State-of-the-art technologies are described in terms of the material design, synthesis, properties, and modulation of photoprogrammable chiro-optical mesogenic soft helical architectures. Additionally, the scientific issues and technical problems that hinder further development of these materials for use in various fields are outlined and discussed. Such photoprogrammable mesogenic soft helical materials are competitive candidates for use in stimulus-controllable chiro-optical devices with high optical efficiency, stable optical properties, and easy miniaturization, facilitating the future integration and systemization of chiro-optical chips in photonics, photochemistry, biomedical engineering, chemical engineering, and beyond.

Accelerated design of Fe-based soft magnetic materials using machine learning and stochastic optimization

Machine learning was utilized to efficiently boost the development of soft magnetic materials. The design process includes building a database composed of published experimental results, applying machine learning methods on the database, identifying the trends of magnetic properties in soft magnetic materials, and accelerating the design of next-generation soft magnetic nanocrystalline materials through the use of numerical optimization. Machine learning regression models were trained to predict magnetic saturation (BS), coercivity (HC) and magnetostriction (λ), with a stochastic optimization framework being used to further optimize the corresponding magnetic properties. To verify the feasibility of the machine learning model, several optimized soft magnetic materials – specified in terms of compositions and thermomechanical treatments – have been predicted and then prepared and tested, showing good agreement between predictions and experiments, proving the reliability of the designed model. Two rounds of optimization-testing iterations were conducted to search for better properties.

Dynamic Light Scattering Measurements for Soft Materials on Solid Substrates: Employing Evanescent-wave Illumination and Dark-field Collection with a High Numerical Aperture Microscope Objective.

We developed an instrument that allows us to measure dynamic light scattering from soft materials on solid substrates by avoiding strong background due to the reflection light from substrates. In the instrument, samples on substrates are illuminated by evanescent-light field and the resultant scattered light from the samples is collected with a dark-field optical configuration by employing a high numerical aperture microscope objective. We applied the instrument to measure the dynamic properties of supported lipid bilayers (SLBs), which have been widely utilized in industries as functional materials such as biosensors. From the time course of the scattered light from the SLBs, the power spectrum with the broad peak ranging from 10 to 20 kHz is observed. The use of the microscope objectives enables us to apply the instrument to future light scattering imaging for dynamic properties of soft materials supported on various substrates by combining with conventional microscope systems.

Shape stability of a gas bubble in a soft solid.

Predicting the onset of non-spherical oscillations of bubbles in soft matter is a fundamental cavitation problem with implications to sonoprocessing, polymeric materials synthesis, and biomedical ultrasound applications. The shape stability of a bubble in a Kelvin-Voigt viscoelastic medium with nonlinear elasticity, the simplest constitutive model for soft solids, is analytically investigated and compared to experiments. Using perturbation methods, we develop a model reducing the equations of motion to two sets of evolution equations: a Rayleigh-Plesset-type equation for the mean (volume-equivalent) bubble radius and an equation for the non-spherical mode amplitudes. Parametric instability is predicted by examining the natural frequency and the Mathieu equation for the non-spherical modes, which are obtained from our model. Our theoretical results show good agreement with published experiments of the shape oscillations of a bubble in a gelatin gel. We further examine the impact of viscoelasticity on the time evolution of non-spherical mode amplitudes. In particular, we find that viscosity increases the damping rate, thus suppressing the shape instability, while shear modulus increases the natural frequency, which changes the unstable mode. We also explain the contributions of rotational and irrotational fields to the viscoelastic stresses in the surroundings and at the bubble surface, as these contributions affect the damping rate and the unstable mode. Our analysis on the role of viscoelasticity is potentially useful to measure viscoelastic properties of soft materials by experimentally observing the shape oscillations of a bubble.

Dielectric, magnetic and humidity properties of Mg–Zn–Cr ferrites

Abstract In this study, Cr3+ substituted Mg0.75Zn0.25CrxFe2-xO4 (x = 0, 0.1, 0.3) (Mg–Zn–Cr) ferrites have been synthesized using chemical co-precipitation method. The crystal structure and phase formation of Mg–Zn–Cr ferrites have been analyzed by X-Ray diffraction (XRD) method. The crystal size (from 15.37 nm to 10.84 nm) and lattice constant (from 8.405 A to 8.384 A) of the crystallized in cubic crystal structure Mg–Zn–Cr samples decreased with Cr3+ contribution. The change in lattice strain determined by Williamson-Hall (W–H) graphs. Morphological and elemental analysis were investigated using scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX) spectroscopy. The variations in temperature-dependent dielectric properties of samples between 290 K and 700 K were examined in the range from 20 Hz to 10 MHz. Curie temperature, where maximum dielectric constant is observed, shifted low temperatures with increasing Cr3+ contribution. This peak shift indicates that the materials have a relaxor ferroelectric character in accordance with the literature. Impedance analysis of Mg–Zn–Cr ferrites were investigated using Nyquist curves and relaxation process confirms Cole-Cole model. The magnetic properties of the samples in the range of ±5 kOe at 300 K were examined with the help of the Vibrating Sample Magnetometer (VSM). The M − H hysteresis loops of all samples showed the characteristic properties of soft magnetic materials. Finally, the effect of relative humidity (%RH) on the impedance of samples for different frequency values was investigated.

Multiparametric characterization of heterogeneous soft materials using contact point detection-based atomic force microscopy

Force-distance (FD) curve-based atomic force microscopy (AFM) has been widely applied for characterizing the surface morphology and mechanical properties of soft materials at nanometer resolution. In this paper, we demonstrate FD curve-based AFM using a newly developed algorithm to detect contact points (CPs) from each FD curve and to determine properties such as stiffness, adhesion, and deformation. The performance of our method is compared with that of the tapping and peak force tapping (PFT) modes by imaging the same area of a heterogeneous blend of soft and hard polymers by using the same tip. The morphology obtained with our CP detection-based method is comparable to that obtained using the tapping mode, but PFT shows strong deviation in height images obtained on soft polymer regions. We also acquire FD curves at a much higher sampling rate than PFT. A site-dependent decaying oscillation following snap-in is detected, and the frequency of the decaying oscillation appears to be related to the stiffness of the region, pointing to a new direction for characterizing viscoelastic properties of sample surfaces with a high spatial resolution.

Micromechanical Properties of Microstructured Elastomeric Hydrogels.

Local, micromechanical environment is known to influence cellular function in heterogeneous hydrogels, and knowledge gained in micromechanics will facilitate the improved design of biomaterials for tissue regeneration. In this study, a system comprising microstructured resilin-like polypeptide (RLP)-poly(ethylene glycol) (PEG) hydrogels is utilized. The micromechanical properties of RLP-PEG hydrogels are evaluated with oscillatory shear rheometry, compression dynamic mechanic analysis, small-strain microindentation, and large-strain indentation and puncture over a range of different deformation length scales. The measured elastic moduli are consistent with volume averaging models, indicating that volume fraction, not domain size, plays a dominant role in determining the low strain mechanical response. Large-strain indentation under a confocal microscope enables the visualization of the microstructured hydrogel micromechanical deformation, emphasizing the translation, rotation, and deformation of RLP-rich domains. The fracture initiation energy results demonstrate that failure of the composite hydrogels is controlled by the RLP-rich phase, and their independence with domain size suggested that failure initiation is controlled by multiple domains within the strained volume. This approach and findings provide new quantitative insight into the micromechanical response of soft hydrogel composites and highlight the opportunities in employing these methods to understand the physical origins of mechanical properties of soft synthetic and biological materials.

Mesoscale bicontinuous networks in self-healing hydrogels delay fatigue fracture

Load-bearing biological tissues, such as muscles, are highly fatigue-resistant, but how the exquisite hierarchical structures of biological tissues contribute to their excellent fatigue resistance is not well understood. In this work, we study antifatigue properties of soft materials with hierarchical structures using polyampholyte hydrogels (PA gels) as a simple model system. PA gels are tough and self-healing, consisting of reversible ionic bonds at the 1-nm scale, a cross-linked polymer network at the 10-nm scale, and bicontinuous hard/soft phase networks at the 100-nm scale. We find that the polymer network at the 10-nm scale determines the threshold of energy release rate G0 above which the crack grows, while the bicontinuous phase networks at the 100-nm scale significantly decelerate the crack advance until a transition Gtran far above G0 In situ small-angle X-ray scattering analysis reveals that the hard phase network suppresses the crack advance to show decelerated fatigue fracture, and Gtran corresponds to the rupture of the hard phase network.

Algebraic approach towards the exploitation of “softness”: the input–output equation for morphological computation

Recently, soft robots that consist of soft and deformable materials have received much attention for their adaptability to uncertain environments. Although these robots are difficult to control with a conventional control theory owing to their complex body dynamics, research from different perspectives attempts to actively exploit these body dynamics as an asset rather than a drawback. This approach is called morphological computation, in which the soft materials are used for computation that includes a new kind of control strategy. In this article, we propose a novel approach to analyze the computational properties of soft materials based on an algebraic method, called the input–output equation used in systems analysis, particularly in systems biology. We mainly focus on the two scenarios relevant to soft robotics, that is, analysis of the computational capabilities of soft materials and design of the input force to soft devices to generate the target behaviors. The input–output equation directly describes the relationship between inputs and outputs of a system, and hence by using this equation, important properties, such as the echo state property that guarantees reproducible responses against the same input stream, can be investigated for soft structures. Several application scenarios of our proposed method are demonstrated using typical soft robotic settings in detail, including linear/nonlinear models and hydrogels driven by chemical reactions.

Hydrodynamic Bulge Testing: Materials Characterization Without Measuring Deformation

AbstractCharacterizing the elastic properties of soft materials through bulge testing relies on accurate measurement of deformation, which is experimentally challenging. To avoid measuring deformation, we propose a hydrodynamic bulge test for characterizing the material properties of thick, pre-stressed elastic sheets via their fluid–structure interaction with a steady viscous fluid flow. Specifically, the hydrodynamic bulge test relies on a pressure drop measurement across a rectangular microchannel with a deformable top wall. We develop a mathematical model using first-order shear deformation theory of plates with stretching and the lubrication approximation for the Newtonian fluid flow. Specifically, a relationship is derived between the imposed flowrate and the total pressure drop. Then, this relationship is inverted numerically to yield estimates of the Young’s modulus (given the Poisson ratio) if the pressure drop is measured (given the steady flowrate). Direct numerical simulations of two-way-coupled fluid–structure interaction are carried out in ansys to determine the cross-sectional membrane deformation and the hydrodynamic pressure distribution. Taking the simulations as “ground truth,” a hydrodynamic bulge test is performed using the simulation data to ascertain the accuracy and the validity of the proposed methodology for estimating material properties. An error propagation analysis is performed via Monte Carlo simulation to characterize the susceptibility of the hydrodynamic bulge test estimates to noise. We find that, while a hydrodynamic bulge test is less accurate in characterizing material properties, it is less susceptible to noise, in the input (measured) variable, than a hydrostatic bulge test.

In vitro Cytotoxicity of Silver Nanoparticles Incorporated in a Soft Silicone Liner

Introduction: Silver nanoparticles (SNPs) have recently been suggested to increase the antimicrobial properties of soft liner materials. However, their safety remains a matter of debate. This study aimed to evaluate the cytotoxicity of Mucopren® soft silicone liner material (Mucopren; Kettenbach, Germany) incorporated in SNPs. Methods: The SNPs with over 98% purity were added to Mucopren in 0.5, 1, 2, and 3 weight percentage (wt%) concentrations and manually homogenized. The mixture of the pieces of Mucopren plus SNPs and SNPs alone were placed in 96-well plates containing Dulbecco's Modified Eagle Medium culture, FBS, and antibiotics with L929 fibroblasts. Cell viability and biocompatibility were determined after 1, 2, and 3 days of incubation using the methylthiazol tetrazolium assay. Optical density was read by an ELISA reader at 570 nm and compared to those of positive and negative controls. Results: Among Mucopren mixed with different SNPs concentration, the cell toxicity had no significant difference in the same days, and cell toxicity decreased over time (P=0.016). The SNPs alone were less cytotoxic than Mucopren incorporated SNP samples (P>0.05). Conclusion: Within the limitations of this study, the addition of 0.5, 1, 2, and 3wt% concentrations of SNPs to Mucopren did not cause a significant change in its cell toxicity in an in vitro condition

Geometric Confined Pneumatic Soft–Rigid Hybrid Actuators

In this work, we propose a new kind of soft-rigid hybrid actuator composed mainly of soft chambers and rigid frames. Compared with the well-known fiber-reinforced soft actuators, the hybrid actuators are able to ensure the design of noncircular cross-sectional shapes. It is demonstrated that rigid frames are capable of providing geometric constraints, reducing the ineffective deformation, and improving the energy utilization for the hybrid actuators with noncircular cross-sections. The essential characteristics of rigid constraints and flexible constraints are obtained by simulation and experiments on specimens with three different cross-sectional shapes. Furthermore, a spring-fluid film model is introduced to characterize the behavior of a representative hybrid linear actuator and a bending actuator with a rectangular cross-section, and it is also proved by the corresponding experiments. The change of the cross-sectional shape of fiber-reinforced soft actuators under pressurization is also explained theoretically as a contrast. Then, two application examples, namely, a robotic gripper and a caudal fin formed from linear actuators, are designed and demonstrated, showing the advantages and potential applications of the proposed geometric confined hybrid actuators. The proposed soft-rigid hybrid actuators combine the properties of soft and rigid materials, expand the design scope of the compliant actuators, and provide new solutions for robotics, especially for soft robots with specific requirements for their shapes or profiles.

Identification and analysis of static and dynamic magnetization behavior sensitive to surface laser treatments within the electromagnetic field diffusion inside GO SiFe electrical steels

Surface laser treatment of soft magnetic materials, such as GO SiFe electrical steels, is mainly used to reduce iron losses by modifying the static and the dynamic magnetic properties. Laser treatment effect on mesoscopic electromagnetic properties of soft magnetic materials is presented. An experimental procedure using the Single Sheet Tester is performed on a magnetized sheet with specific exciting induction level and frequency. Transient average magnetic flux density through the sample cross-section and its corresponding applied magnetic field are measured. Data are identified in the time-domain with numerical results obtained by solving the diffusion equation using a 1-D discretization approach. The identification strategy requires a material law that includes both non-linear static and dynamic properties and describes the magnetic behavior due to domains and walls dynamics. Next, parametric and physical studies are performed on materials submitted to different laser treatments in order to determine and interpret their effects on the identified magnetic properties and the time response in the sheet’s depth. The results show that the static and the dynamic properties can be simultaneously improved. This analysis help to understand the impact of laser treatments on the static and the dynamic behaviour in order to improve the material magnetic performances within magnetic circuits inside electrical machines and transformers.

Investigation of the properties of soft magnetic composite materials in the frequency range of harmonic oscillations up to 100 kHz

The dynamic properties of the soft magnetic composite material in the frequency range up to 100 kHz with a change in the thickness of the insulating layer and the size of iron particles were investigated. It is shown that with an increase in the thickness of the insulating layer, the loss for remagnetization decreases, but at the same time there is a decrease in the magnetic value of the saturation induction and magnetic permeability. Therefore, that the decision to reduce losses by increasing the thickness of the insulating coating is not always the best solution. It is preferable to achieve a reduction losses for remagnetization due to an increase in the specific resistance of the insulating layer with its minimum thickness.

Incorporating the Soft Magnetic Material Degradation to Numerical Simulations

This article focuses on the numerical implementation of a continuous model for local degradation in soft magnetic materials. Cutting and punching processes required for producing electric machines impact the magnetic properties of soft magnetic materials. A simplified but effective model for considering local degradation of soft magnetic materials is defined and experimentally validated. The proposed model is then implemented in the source code of numerical simulation tool to assign directly at the mesh level the material characteristics as a function of the distance from the cut edge. The procedure as well as the flow chart for the implementation is described in detail. The proposed method allows avoiding the drawbacks of multilayer approaches and consequently increased model complexity and a required finer mesh density. A comparison between simulation results and measurements of lamination rings is presented and discussed.

Seeded laser-induced cavitation for studying high-strain-rate irreversible deformation of soft materials.

Characterizing the high-strain-rate and high-strain mechanics of soft materials is critical to understanding the complex behavior of polymers and various dynamic injury mechanisms, including traumatic brain injury. However, their dynamic mechanical deformation under extreme conditions is technically difficult to quantify and often includes irreversible damage. To address such challenges, we investigate an experimental method, which allows quantification of the extreme mechanical properties of soft materials using ultrafast stroboscopic imaging of highly reproducible laser-induced cavitation events. As a reference material, we characterize variably cross-linked polydimethylsiloxane specimens using this method. The consistency of the laser-induced cavitation is achieved through the introduction of laser absorbing seed microspheres. Based on a simplified viscoelastic model, representative high-strain-rate shear moduli and viscosities of the soft specimens are quantified across different degrees of crosslinking. The quantified rheological parameters align well with the time-temperature superposition prediction of dynamic mechanical analysis. The presented method offers significant advantages with regard to quantifying high-strain rate, irreversible mechanical properties of soft materials and tissues, compared to other methods that rely upon the cyclic dynamics of cavitation. These advances are anticipated to aid in the understanding of how damage and injury develop in soft materials and tissues.