Humidity dependence of fracture toughness of cellulose fibrous networks.

Cellulose-based materials are increasingly finding applications in technology due to their sustainability and biodegradability. The sensitivity of cellulose fiber networks to environmental conditions such as temperature and humidity is well known. Yet, there is an incomplete understanding of the dependence of the fracture toughness of cellulose networks on environmental conditions. In the current study, we assess the effect of moisture content on the out-of-plane (i.e., z-dir.) fracture toughness of a particular cellulose network, specifically Whatman cellulose filter paper. Experimental measurements are performed at 16% RH along the desorption isotherm and 23, 37, 50, 75% RH along the adsorption isotherm using out-of-plane tensile tests and double cantilever beam (DCB) tests. Cohesive zone modeling and finite element simulations are used to extract quantitative properties that describe the crack growth behavior. Overall, the fracture toughness of filter paper decreased with increasing humidity. Additionally, a novel model is developed to capture the high peak and sudden drop in the experimental force measurement caused by the existence of an initiation region. This model is found to be in good agreement with experimental data. The relative effect of each independent cohesive parameter is explored to better understand the cohesive zone-based humidity dependence model. The methods described here may be applied to study rupture of other fiber networks with weak bonds.

Adhesion of flat-ended pillars with non-circular contacts.

Fibrillar adhesives composed of fibers with non-circular cross-sections and contacts, including squares and rectangles, offer advantages that include a larger real contact area when arranged in arrays and simplicity in fabrication. However, they typically have a lower adhesion strength compared to circular pillars due to a stress concentration at the corner of the non-circular contact. We investigate the adhesion of composite pillars with circular, square and rectangular cross-sections each consisting of a stiff pillar terminated by a thin compliant layer at the tip. Finite element mechanics modeling is used to assess differences in the stress distribution at the interface for the different geometries and the adhesion strength of different shape pillars is measured in experiments. The composite fibrillar structure results in a favorable stress distribution on the adhered interface that shifts the crack initiation site away from the edge for all of the cross-sectional contact shapes studied. The highest adhesion strength achieved among the square and rectangular composite pillars with various tip layer thicknesses is approximately 65 kPa. This is comparable to the highest strength measured for circular composite pillars and is about 6.5× higher than the adhesion strength of a homogenous square or rectangular pillar. The results suggest that a composite fibrillar adhesive structure with a local stress concentration at a corner can achieve comparable adhesion strength to a fibrillar structure without such local stress concentrations if the magnitude of the corner stress concentrations are sufficiently small such that failure does not initiate near the corners, and the magnitude of the peak interface stress away from the edge and the tip layer thickness are comparable.

Enhancing the stiffness of vertical graphene sheets through ion beam irradiation and fluorination.

Many applications of graphene can benefit from the enhanced mechanical robustness of graphene-based components. We report how the stiffness of vertical graphene (VG) sheets is affected by the introduction of defects and fluorination, both separately and combined. The defects were created using a high-energy ion beam while fluorination was performed in a XeF2 etching system. After ion bombardment alone, the average effective reduced modulus (E r), equal to ∼4.9 MPa for the as-grown VG sheets, approximately doubled to ∼10.0 MPa, while fluorination alone almost quadrupled it to ∼18.4 MPa. The maximum average E r of ∼32.4 MPa was achieved by repeatedly applying fluorination and ion bombardment. This increase can be explained by the formation of covalent bonds between the VG sheets due to ion bombardment, as well as the conversion from sp2 to sp3 and increased corrugation due to fluorination.

Tuning the mechanical properties of vertical graphene sheets through atomic layer deposition.

We report the fabrication and characterization of graphene nanostructures with mechanical properties that are tuned by conformal deposition of alumina. Vertical graphene (VG) sheets, also called carbon nanowalls (CNWs), were grown on copper foil substrates using a radio-frequency plasma-enhanced chemical vapor deposition (RF-PECVD) technique and conformally coated with different thicknesses of alumina (Al2O3) using atomic layer deposition (ALD). Nanoindentation was used to characterize the mechanical properties of pristine and alumina-coated VG sheets. Results show a significant increase in the effective Young's modulus of the VG sheets with increasing thickness of deposited alumina. Deposition of only a 5 nm thick alumina layer on the VG sheets nearly triples the effective Young's modulus of the VG structures. Both energy absorption and strain recovery were lower in VG sheets coated with alumina than in pure VG sheets (for the same peak force). This may be attributed to the increase in bending stiffness of the VG sheets and the creation of connections between the sheets after ALD deposition. These results demonstrate that the mechanical properties of VG sheets can be tuned over a wide range through conformal atomic layer deposition, facilitating the use of VG sheets in applications where specific mechanical properties are needed.

Friction laws at the nanoscale.

Macroscopic laws of friction do not generally apply to nanoscale contacts. Although continuum mechanics models have been predicted to break down at the nanoscale, they continue to be applied for lack of a better theory. An understanding of how friction force depends on applied load and contact area at these scales is essential for the design of miniaturized devices with optimal mechanical performance. Here we use large-scale molecular dynamics simulations with realistic force fields to establish friction laws in dry nanoscale contacts. We show that friction force depends linearly on the number of atoms that chemically interact across the contact. By defining the contact area as being proportional to this number of interacting atoms, we show that the macroscopically observed linear relationship between friction force and contact area can be extended to the nanoscale. Our model predicts that as the adhesion between the contacting surfaces is reduced, a transition takes place from nonlinear to linear dependence of friction force on load. This transition is consistent with the results of several nanoscale friction experiments. We demonstrate that the breakdown of continuum mechanics can be understood as a result of the rough (multi-asperity) nature of the contact, and show that roughness theories of friction can be applied at the nanoscale.

Simulated adhesion between realistic hydrocarbon materials: effects of composition, roughness, and contact point.

The work of adhesion is an interfacial materials property that is often extracted from atomic force microscope (AFM) measurements of the pull-off force for tips in contact with flat substrates. Such measurements rely on the use of continuum contact mechanics models, which ignore the atomic structure and contain other assumptions that can be challenging to justify from experiments alone. In this work, molecular dynamics is used to examine work of adhesion values obtained from simulations that mimic such AFM experiments and to examine variables that influence the calculated work of adhesion. Ultrastrong carbon-based materials, which are relevant to high-performance AFM and nano- and micromanufacturing applications, are considered. The three tips used in the simulations were composed of amorphous carbon terminated with hydrogen (a-C-H), and ultrananocrystalline diamond with and without hydrogen (UNCD-H and UNCD, respectively). The model substrate materials used were amorphous carbon with hydrogen termination (a-C-H) and without hydrogen (a-C); ultrananocrystalline diamond with (UNCD-H) and without hydrogen (UNCD); and the (111) face of single crystal diamond with (C(111)-H) and without a monolayer of hydrogen (C(111)). The a-C-H tip was found to have the lowest work of adhesion on all substrates examined, followed by the UNCD-H and then the UNCD tips. This trend is attributable to a combination of roughness on both the tip and sample, the degree of alignment of tip and substrate atoms, and the surface termination. Continuum estimates of the pull-off forces were approximately 2-5 times larger than the MD value for all but one tip-sample pair.

Identifying heterogeneous micromechanical properties of biological tissues via physics-informed neural networks.

The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying the full-field heterogeneous elastic properties of soft materials using traditional computational and engineering approaches is fundamentally challenging due to difficulties in estimating local stress fields. Recently, there has been a growing interest in using data-driven models to learn full-field mechanical responses such as displacement and strain from experimental or synthetic data. However, research studies on inferring the full-field elastic properties of materials, a more challenging problem, are scarce, particularly for large deformation, hyperelastic materials. Here, we propose a physics-informed machine learning approach to identify the elastic modulus distribution in nonlinear, large deformation hyperelastic materials. We evaluate the prediction accuracies and computational efficiency of physics-informed neural networks (PINNs) on inferring the heterogeneous material parameter maps across three nonlinear materials with structural complexity that closely resemble real tissue patterns, such as brain tissue and tricuspid valve tissue. Our improved PINN architecture accurately estimates the full-field elastic properties of three hyperelastic constitutive models, with relative errors of less than 5% across all examples. This research has significant potential for advancing our understanding of micromechanical behaviors in biological materials, impacting future innovations in engineering and medicine.

Bellybutton: accessible and customizable deep-learning image segmentation.

The conversion of raw images into quantifiable data can be a major hurdle and time-sink in experimental research, and typically involves identifying region(s) of interest, a process known as segmentation. Machine learning tools for image segmentation are often specific to a set of tasks, such as tracking cells, or require substantial compute or coding knowledge to train and use. Here we introduce an easy-to-use (no coding required), image segmentation method, using a 15-layer convolutional neural network that can be trained on a laptop: Bellybutton. The algorithm trains on user-provided segmentation of example images, but, as we show, just one or even a sub-selection of one training image can be sufficient in some cases. We detail the machine learning method and give three use cases where Bellybutton correctly segments images despite substantial lighting, shape, size, focus, and/or structure variation across the regions(s) of interest. Instructions for easy download and use, with further details and the datasets used in this paper are available at pypi.org/project/Bellybuttonseg .

Biomechanical Impact of Pathogenic MYBPC3 Truncation Variant Revealed by Dynamically Tuning In Vitro Afterload.

Engineered cardiac microtissues were fabricated using pluripotent stem cells with a hypertrophic cardiomyopathy associated c. 2827 C>T; p.R943x truncation variant in myosin binding protein C (MYBPC3+/-). Microtissues were mounted on iron-incorporated cantilevers, allowing manipulations of cantilever stiffness using magnets, enabling examination of how in vitro afterload affects contractility. MYPBC3+/- microtissues developed augmented force, work, and power when cultured with increased in vitro afterload when compared with isogenic controls in which the MYBPC3 mutation had been corrected (MYPBC3+/+(ed)), but weaker contractility when cultured with lower in vitro afterload. After initial tissue maturation, MYPBC3+/- CMTs exhibited increased force, work, and power in response to both acute and sustained increases of in vitro afterload. Together, these studies demonstrate that extrinsic biomechanical challenges potentiate genetically-driven intrinsic increases in contractility that may contribute to clinical disease progression in patients with HCM due to hypercontractile MYBPC3 variants.

Versatile Adhesion-Based Gripping via an Unstructured Variable Stiffness Membrane.

Reversible and variable dry adhesion is a promising approach for versatile robotic grasping. Variable stiffness materials with a modulus that can be tuned using an external stimulus offer a unique approach to realize dynamic control of adhesion. In this study, an unstructured shape memory polymer (SMP) membrane with variable stiffness is used to pick-and-place three-dimensional objects. The variable stiffness of the SMP allows the membrane to conform to and make good contact with objects of various shapes in its soft state and then achieve high adhesive load capacity by switching to the stiff state. Release of objects is realized by switching to the soft state. The ratio between the high-adhesion and low-adhesion state is demonstrated to be >2000 on a curved substrate and ∼115 on a flat substrate. This gripper exhibits no adhesion in the unactivated state and maintains adhesion passively once actuation is complete.

The Interplay of Polymer Bridging and Entanglement in Toughening Polymer-Infiltrated Nanoparticle Films.

Polymer-nanoparticle composite films (PNCFs) with high loadings of nanoparticles (NPs) (>50 vol %) have applications in multiple areas, and an understanding of their mechanical properties is essential for their broader use. The high-volume fraction and small size of the NPs lead to physical confinement of the polymers that can drastically change the properties of polymers relative to the bulk. We investigate the fracture behavior of a class of highly loaded PNCFs prepared by polymer infiltration into NP packings. These polymer-infiltrated nanoparticle films (PINFs) have applications as multifunctional coatings and membranes and provide a platform to understand the behavior of polymers that are highly confined. Here, the extent of confinement in PINFs is tuned from 0.1 to 44 and the fracture toughness of PINFs is increased by up to a factor of 12 by varying the molecular weight of the polymers over 3 orders of magnitude and using NPs with diameters ranging from 9 to 100 nm. The results show that brittle, low molecular weight (MW) polymers can significantly toughen NP packings, and this toughening effect becomes less pronounced with increasing NP size. In contrast, high MW polymers capable of forming interchain entanglements are more effective in toughening large NP packings. We propose that confinement has competing effects of polymer bridging increasing toughness and chain disentanglement decreasing toughness. These findings provide insight into the fracture behavior of confined polymers and will guide the development of mechanically robust PINFs as well as other highly loaded PNCFs.

Versatile Soft Robot Gripper Enabled by Stiffness and Adhesion Tuning via Thermoplastic Composite.

Within the field of robotics, stiffness tuning technologies have potential for a variety of applications-perhaps most notably for robotic grasping. Many stiffness tuning grippers have been developed that can grasp fragile or irregularly shaped objects without causing damage and while still accommodating large loads. In addition to limiting gripper deformation when lifting an object, increasing gripper stiffness after contact formation improves load sharing at the interface and enhances adhesion. In this study, we present a novel stiffness and adhesion tuning gripper, enabled by the thermally induced phase change of a thermoplastic composite material embedded within a silicone contact pad. The gripper operates by bringing the pad into contact with an object while in its heated, soft state, and then allowing the pad to cool and stiffen to form a strong adhesive bond before lifting the object. Pull-off tests conducted using the gripper show that transitioning from a soft to stiff state during grasping enables up to 6 × increase in adhesion strength. Additionally, a finite element model is developed to simulate the behavior of the gripper. Finally, pick-and-place demonstrations are performed, which highlight the gripper's ability to delicately grasp objects of various shapes, sizes, and weights.

A mechanics-based approach to realize high-force capacity electroadhesives for robots.

Materials with electroprogrammable stiffness and adhesion can enhance the performance of robotic systems, but achieving large changes in stiffness and adhesive forces in real time is an ongoing challenge. Electroadhesive clutches can rapidly adhere high stiffness elements, although their low force capacities and high activation voltages have limited their applications. A major challenge in realizing stronger electroadhesive clutches is that current parallel plate models poorly predict clutch force capacity and cannot be used to design better devices. Here, we use a fracture mechanics framework to understand the relationship between clutch design and force capacity. We demonstrate and verify a mechanics-based model that predicts clutch performance across multiple geometries and applied voltages. On the basis of this approach, we build a clutch with 63 times the force capacity per unit electrostatic force of state-of-the-art electroadhesive clutches. Last, we demonstrate the ability of our electroadhesives to increase the load capacity of a soft, pneumatic finger by a factor of 27 times compared with a finger without an electroadhesive.

Role of Molecular Layering in the Enhanced Mechanical Properties of Stable Glasses.

The density, degree of molecular orientation, and molecular layering of vapor-deposited stable glasses (SGs) vary with substrate temperature (Tdep) below the glass-transition temperature (Tg). Density and orientation have been suggested to be factors influencing the mechanical properties of SGs. We perform nanoindentation on two molecules which differ by only a single substituent, allowing one molecule to adopt an in-plane orientation at low Tdep. The reduced elastic modulus and hardness of both molecules show similar Tdep dependences, with enhancements of 15-20% in reduced modulus and 30-45% in hardness at Tdep ≈ 0.8Tg, where the density of vapor-deposited films is enhanced by ∼1.4% compared to that of the liquid-quenched glass. At Tdep < 0.8Tg, one of the molecules produces highly unstable glasses with in-plane orientation. However, both systems show enhanced mechanics. Both the modulus and hardness correlate with the degree of layering, which is similar in both systems despite their variable stability. We suggest that nanoindentation performed normal to the film's surface is influenced by the tighter packing of the molecules in this direction.

Polymer-infiltrated nanoplatelet films with nacre-like structure via flow coating and capillary rise infiltration (CaRI).

Alignment of highly anisotropic nanomaterials in a polymer matrix can yield nanocomposites with unique mechanical and transport properties. Conventional methods of nanocomposite film fabrication are not well-suited for manufacturing composites with very high concentrations of anisotropic nanomaterials, potentially limiting the widespread implementation of these useful structures. In this work, we present a scalable approach to fabricate polymer-infiltrated nanoplatelet films (PINFs) based on flow coating and capillary rise infiltration (CaRI) and study the processing-structure-property relationship of these PINFs. We show that films with high aspect ratio (AR) gibbsite (Al (OH)3) nanoplatelets (NPTs) aligned parallel to the substrate can be prepared using a flow coating process. NPTs are highly aligned with a Herman's order parameter of 0.96 and a high packing fraction >80 vol%. Such packings show significantly higher fracture toughness compared to low AR nanoparticle (NP) packings. By depositing NPTs on a polymer film and subsequently annealing the bilayer above the glass transition temperature of the polymer, polymer infiltrates into the tortuous NPT packings though capillarity. We observe larger enhancement in the modulus, hardness and scratch resistance of NPT films upon polymer infiltration compared to NP packings. The excellent mechanical properties of such films benefit from both thermally promoted oxide bridge formation between NPTs as well as polymer infiltration increasing the strength of NPT contacts. Our approach is widely applicable to highly anisotropic nanomaterials and allows the generation of mechanically robust polymer nanocomposite films for a diverse set of applications.

Materials with Electroprogrammable Stiffness.

Stiffness is a mechanical property of vital importance to any material system and is typically considered a static quantity. Recent work, however, has shown that novel materials with programmable stiffness can enhance the performance and simplify the design of engineered systems, such as morphing wings, robotic grippers, and wearable exoskeletons. For many of these applications, the ability to program stiffness with electrical activation is advantageous because of the natural compatibility with electrical sensing, control, and power networks ubiquitous in autonomous machines and robots. The numerous applications for materials with electrically driven stiffness modulation has driven a rapid increase in the number of publications in this field. Here, a comprehensive review of the available materials that realize electroprogrammable stiffness is provided, showing that all current approaches can be categorized as using electrostatics or electrically activated phase changes, and summarizing the advantages, limitations, and applications of these materials. Finally, a perspective identifies state-of-the-art trends and an outlook of future opportunities for the development and use of materials with electroprogrammable stiffness.

Magnetic field tuning of mechanical properties of ultrasoft PDMS-based magnetorheological elastomers for biological applications.

We report tuning of the moduli and surface roughness of magnetorheological elastomers (MREs) by varying applied magnetic field. Ultrasoft MREs are fabricated using a physiologically relevant commercial polymer, Sylgard™ 527, and carbonyl iron powder (CIP). We found that the shear storage modulus, Young's modulus, and root-mean-square surface roughness are increased by ~41×, ~11×, and ~11×, respectively, when subjected to a magnetic field strength of 95.5 kA m-1. Single fit parameter equations are presented that capture the tunability of the moduli and surface roughness as a function of CIP volume fraction and magnetic field strength. These magnetic field-induced changes in the mechanical moduli and surface roughness of MREs are key parameters for biological applications.

Measurement of single-cell adhesion strength using a microfluidic assay.

Despite the importance of cell adhesion in numerous physiological, pathological, and biomaterial-related responses, our understanding of adhesion strength at the cell-substrate interface and its relationship to cell function remains incomplete. One reason for this deficit is a lack of accessible experimental approaches that quantify adhesion strength at the single-cell level and facilitate large numbers of tests. The current work describes the design, fabrication, and use of a microfluidic-based method for single-cell adhesion strength measurements. By applying a monotonically increasing flow rate in a microfluidic channel in combination with video microscopy, the adhesion strength of individual NIH3T3 fibroblasts cultured for 24 h on various surfaces was measured. The small height of the channel allows high shear stresses to be generated under laminar conditions, allowing strength measurements on well-spread, strongly adhered cells that cannot be characterized in most conventional assays. This assay was used to quantify the relationship between morphological characteristics and adhesion strength for individual well-spread cells. Cell adhesion strength was found to be positively correlated with both cell area and circularity. Computational fluid dynamics (CFD) analysis was performed to examine the role of cell geometry in determining the actual stress applied to the cell. Use of this method to examine adhesion at the single-cell level allows the detachment of strongly-adhered cells under a highly-controllable, uniform loading to be directly observed and will enable the characterization of biological events and relationships that cannot currently be achieved using existing methods.

Switchable Adhesion via Subsurface Pressure Modulation.

Materials and devices with tunable dry adhesion have many applications, including transfer printing, climbing robots, and gripping in pick-and-place processes. In this paper, a novel soft device to achieve dynamically tunable dry adhesion via modulation of subsurface pneumatic pressure is introduced. Specifically, a cylindrical elastomer pillar with a mushroom-shaped cap and annular chamber that can be pressurized to tune the adhesion is investigated. Finite element-based mechanics models and experiments are used to design, understand, and demonstrate the adhesion of the device. Specifically, the device is designed using mechanics modeling such that the pressure applied inside the annular chamber significantly alters the stress distribution at the adhered interface and thus changes the effective adhesion strength. Devices made of polydimethylsiloxane (PDMS) with different elastic moduli were tested against glass, silicon, and aluminum substrates. Adhesion strengths (σ0) ranging from ∼37 kPa (between PDMS and glass) to ∼67 kPa (between PDMS and polished aluminum) are achieved for the nonpressurized state. For all cases, regardless of the material and roughness of the substrates, the adhesion strength dropped to 40% of the strength of the nonpressurized state (equivalent to a 2.5× adhesion switching ratio) by increasing the chamber pressure from 0.3σ0 to 0.6σ0. Furthermore, the strength drops to 20% of the unpressurized strength (equivalent to a 5× adhesion switching ratio) when the chamber pressure is increased to σ0.

Strong, Ultralight Nanofoams with Extreme Recovery and Dissipation by Manipulation of Internal Adhesive Contacts.

Advances in three-dimensional nanofabrication techniques have enabled the development of lightweight solids, such as hollow nanolattices, having record values of specific stiffness and strength, albeit at low production throughput. At the length scales of the structural elements of these solids-which are often tens of nanometers or smaller-forces required for elastic deformation can be comparable to adhesive forces, rendering the possibility to tailor bulk mechanical properties based on the relative balance of these forces. Herein, we study this interplay via the mechanics of ultralight ceramic-coated carbon nanotube (CNT) structures. We show that ceramic-CNT foams surpass other architected nanomaterials in density-normalized strength and that, when the structures are designed to minimize internal adhesive interactions between CNTs, more than 97% of the strain after compression beyond densification is recovered. Via experiments and modeling, we study the dependence of the recovery and dissipation on the coating thickness, demonstrate that internal adhesive contacts impede recovery, and identify design guidelines for ultralight materials to have maximum recovery. The combination of high recovery and dissipation in ceramic-CNT foams may be useful in structural damping and shock absorption, and the general principles could be broadly applied to both architected and stochastic nanofoams.