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Fibrous shape memory polymers (SMPs) have received growing interest in various applications, especially in biomedical applications, which offer new structures at the microscopic level and the potential of enhanced shape deformation of SMPs. In this paper, we report on the development and investigation of the properties of acrylate-based shape memory polymer fibers, fabricated by electrospinning technology with the addition of polystyrene (PS). Fibers with different diameters are manufactured using four different PS solution concentrations (25, 30, 35, and 40 wt%) and three flow rates (1.0, 2.5, and 5.0 mu L min(-1)) with a 25 kV applied voltage and 17 cm electrospinning distance. Scanning electron microscope (SEM) images reveal that the average fiber diameter varies with polymer concentration and flow rates, ranging from 0.655 +/- 0.376 to 4.975 +/- 1.634 mu m. Dynamic mechanical analysis (DMA) and stress-strain testing present that the glass transition temperature and tensile values are affected by fiber diameter distribution. The cyclic bending test directly proves that the electrospun SMP fiber webs are able to fully recover; additionally, the recovery speed is also affected by fiber diameter. With the combination of the SMP material and electrospinning technology, this work paves the way in designing and optimizing future SMP fibers properties by adjusting the fiber diameter. NSF CMMI Grant [2016474] Published version Financial support from the NSF CMMI Grant 2016474 is gratefully acknowledged.

While many organisms synthesize robust skeletal composites consisting of spatially discrete organic and mineral (ceramic) phases, the intrinsic mechanical properties of the mineral phases are poorly understood. Using the shell of the marine bivalve Atrina rigida as a model system, and through a combination of multiscale structural and mechanical characterization in conjunction with theoretical and computational modeling, we uncover the underlying mechanical roles of a ubiquitous structural motif in biogenic calcite, their nanoscopic intracrystalline defects. These nanoscopic defects not only suppress the soft yielding of pure calcite through the classical precipitation strengthening mechanism, but also enhance energy dissipation through controlled nano- and micro-fracture, where the defects’ size, geometry, orientation, and distribution facilitate and guide crack initialization and propagation. These nano- and micro-scale cracks are further confined by larger scale intercrystalline organic interfaces, enabling further improved damage tolerance., Biominerals are nanocomposites that often incorporate nanoscopic defects such as organic inclusions within the mineral matrix. Here, the authors report on an experimental and computational study into the effects of intracrystalline defects on the intrinsic mechanical behaviour of biominerals.

Additively manufactured (AM) materials experience shorter fatigue lives compared to their wrought form. Shorter fatigue life can be related to different effects like defects, residual stresses, surface finish, geometry, size, layer orientation, and heat treatment. One of the main contributors to the shorter fatigue life of AM alloys is their unique and complex microstructure. In this paper, we study this challenge from a novel perspective in which the interaction between the microstructure and fatigue life is explored. Among different microstructural features in the AM alloys, here we focus on the cells which form inside the grains during fabrication. While this microstructural feature is not always the prominent site for the fatigue initiation, it always has a significant role in the fatigue failure, particularly in high cycle fatigue because it occupies a high percentage of the volume in the material. A fatigue damage model is developed and verified to predict the life of cellular microstructures present in the AM metal microstructure. It is shown that the life of a cellular microstructure, which is composed of an arrangement of cells and cell boundaries is lower than a single-phase material without such an arrangement. We investigate how the arrangement if cells can govern the fatigue life, and analyze different cellular geometries to find the best performing cellular microstructure. By changing the geometrical parameters, the considerable variation in life can be as high as 95% in some strain amplitudes. Since the microstructure of cells in AM alloys can be tailored by changing the processing parameters, our results can be used as a guide to additively manufacture alloys with improved fatigue-resistance.

A novel approach is utilized to investigate the deformation mechanisms at the microstructural level in 3D-printed alloys. The complex formation methods leave a unique and complicated microstructure in the as-built 3D-printed alloys. The microstructure is three leveled, composed of meltpools, grains, and cells. Deformation mechanisms in this microstructure are still highly unexplored due to the complexities of analysis at this scale. To understand these, we establish an image processing framework that converts scanning electron microscope (SEM) images directly into models that are scaled up and 3D printed with representative stiff and soft materials for the proposed material types within the body. These bodies are loaded in uniaxial tension with digital image correlation to study the strain gradient and stress delocalization as a result of the microstructure. The same models were tested through Finite Element Analysis (FEA) with materials similar to reality. Our testing shows the hierarchical material distribution leads to an increased damage tolerance.

Some properties of amorphous polymeric nanofibers, including their modulus and strength, dramatically change when their size drops down below a specific value. Understanding the detailed mechanisms...

Graphene can be utilized as reinforcing interlayers in metal-matrix composites to improve their mechanical properties. This improvement is due to the ability of the graphene layers to transfer their exceptional strength to the metallic matrix, and their ability to hinder the propagation of dislocations inside the metallic systems. In these composites, the structure of the graphene layer (or nanoparticles) in the matrix and the interaction between graphene and metallic atoms play a vital role in the improvement of metal-graphene composites’ mechanical properties. While the interaction between metal and graphene interface, when the graphene is on the top of a metallic layer, has been extensively studied, details of the interaction when the graphene is embedded inside a metal matrix are still highly unexplored. In this paper, we considered the structure of graphene and the interaction between graphene nanoparticle edges and nickel atoms when the graphene is embedded in the nickel matrix. Using ab-initio calculations, we found that when the graphene is embedded inside a nickel matrix, the most stable graphene structure is topfcc (with graphene nano-sheets being parallel to Ni(111) surface), which is a different configuration compared to the case of having graphene on the surface of a nickel slab. Also, we found that armchair edge energy is 0.8022(eV/A) and zigzag edge energy is 2.5048(eV/A) which implies armchair edge is more stable and creates less distortion inside the nickel matrix. Less distortion by armchair edge implies that nucleation of dislocation in composites will start later at armchair edges in comparison to zigzag edges during mechanical loading.

Mechanical properties of ultra-fine polymeric nanofibers are highly size-dependent and the mechanisms for causality of the size dependency is still not quite clear yet. In this work, we investigate the origins of this size dependency at the atomistic level. By using molecular dynamics (MD) framework, two fabrication methods are utilized in this study to prepare non-drawn and hot-drawn fibers, in order to investigate the two distinguished mechanisms for nanofiber size dependency. One is rooted in the effect of surface chains which is intrinsic to low dimensional materials and the other is the chain alignment induced by drawing during fiber fabrication process. Our results show that the size dependency is not chiefly attributed to the effect of surface polymeric chains, but rather strongly relates to the chain alignment in nanofiber's microstructure. The atomistic study shows that non-drawn nanofibers have a dense core covered by a less dense shell layer, but interestingly, our investigations reveal that the core-shell structure itself will not result in the remarkable increase of modulus and strength when diameter of the fiber drops down. By testing the hot-drawn fibers, we found the size dependency mainly originates from the chain alignment. When fiber is formed by hot-drawing, higher drawing ratio leads to thinner fiber and more aligned chains in the microstructure. A three-fold increase of modulus and strength is observed when the chain orientation parameter of the hot-drawn nanofiber increases from 0.1491 to 0.3375 while the diameter of the fiber drops from 19 to 10 nm. By examining the energy evolution associated with the bond lengths, bond angles and dihedral angles at the atomistic scale, our results show that the dihedral angles play a vital role in the size-effect. Our results also show the mechanical response of fibers are affected by changing the temperature, additionally, the orientation-induced crystallization is monitored on hot-drawn fibers at 300 K, which makes the fibers become stiffer but less ductile.

Failure prediction of metallic parts fabricated by 3D printing process is still challenging so that it is of vital importance to develop accurate microstructural-based simulation tools. In this study, a micromechanical model is proposed to predict the relationship between microstructure features, such as grains and melt pools, and the damage properties of powder bed fusion additive manufacturing (AM) products. The model reproduces the role of multiple effective key parameters on the mechanical response of the AM parts, which are observed experimentally, and reveals the effects of the microscopic defects, melt pool sizes, and the crystal orientations of grains on the failure response of AM parts. The materials presented in this paper can be used as a practical reference for predicting the failure response of AM products. In addition, it provides an important step toward the development of a multidisciplinary computational package for the sake of understanding and controlling the AM build process.

Defect tolerance, the capacity of a material to maintain strength even under the presence of cracks or flaws, is one of the essential demands in the design of composite materials, as manufacturing induced defects, or those generated during operation, can lead to catastrophic failure and dramatically reduce the mechanical performance. In this paper, we combine computational modeling and advanced multimaterial 3D printing to examine the mechanics of several different classes of defect-tolerant bioinspired hierarchical composites, built from two base materials with contrasting mechanical properties (stiff and soft). We find that in contrast to the brittle base constituents of the composites, the existence of a hierarchical architecture leads to superior defect-tolerant properties. We show that composites with more hierarchical levels dramatically improve the defect tolerance of the material. We also examine the effect of adding both self-similar and dissimilar hierarchical levels to the materials architecture, and show that the geometries with multiple hierarchical levels can retain a significant portion of their fracture strength in the presence of either large edge cracklike flaws or multiple small distributed defects in the material. We compare the stress distributions in materials with different numbers of hierarchies in both simulation and experiment and find a more uniform stress distribution in the uncracked region of materials with higher hierarchy levels. These results provide micromechanical insights into the origin of the higher defect tolerance observed in simulation and experiment.

In recent years, shape-memory polymers (SMPs) have received extensive attention to be used as actuators in a broad range of applications such as medical and robotic devices. Their ability to recover large deformations and their capability to be stimulated remotely have made SMPs a superior choice among different smart materials in various applications. In this study, a ductile SMP composite with enhanced shape recovery ability is synthesized and characterized. This SMP composite is made by a mixture of acrylate-based crosslinkers and monomers, as well as polystyrene (PS) with UV curing. The composite can achieve almost 100% shape recovery in 2 s by hot water or hot air. This shape recovery speed is much faster than typical acrylate-based SMPs. In addition, the composite shows excellent ductility and viscoelasticity with reduced hardness. Molecular dynamics (MD) simulations are performed for understanding the curing mechanism of this composite. With the combination of the experimental and computational works, this study paves the way in front of designing and optimizing the future SMP devices.

Tire durability plays an important role in road transportation safety and is taken very seriously by all tire manufacturers. Defects in tires can cause vehicle instability and create catastrophic a...

A unique property of Nickel–Titanium (NiTi) shape memory alloys is their ability to dissipate the shock loading energy by two complementary mechanisms: (a) through deformation-induced phase transformations caused by the structural vibrations, and (b) through the phase transformations caused by the stress wave propagation in the material. Despite extensive research work on the former mechanism, the latter one is still highly unknown, particularly at the atomistic scale. In this paper, the phase transformation, and consequently the energy dissipation, caused by the propagation of stress waves in single-crystal and polycrystalline NiTi alloys under shock wave loadings are investigated using molecular dynamics (MD) method. The nanostructure and dynamic response of the material, when subjected to a shock loading, are studied at the atomistic level. The effects of various nanoscale properties, including the orientation of lattice with respect to the shock loading direction, average grain size, and the effect of grain boundaries on the stress wave propagation, phase transformation propagation, and the energy dissipation in polycrystalline NiTi alloys are studied.

A micromechanical-based finite element framework is developed to investigate the rolling contact fatigue (RCF) in rails. The microstructure of a representative part of the rail in contact with the wheel during wheel passage is modeled using Voronoi tessellation algorithm. The geometry explicitly represents microstructural grain and grain interface features that represent actual microstructure of rail steel. The grain interface is modeled using cohesive elements. For higher computational efficiency, moving Hertzian load is applied to the rail surface instead of moving the wheel explicitly on top of the rail. The jump-in-cycles approach is employed to efficiently simulate a large number of loading cycles, while the material degradation at the grain interface is represented by an accurate damage evolution law. Additionally, the model is used to evaluate the effects of temperature change, traction coefficient, and grain size on initiation and progression of RCF. The results indicate that colder temperatures increase the progression of RCF, while warmer temperatures do not have any significant effects. Large traction forces at the wheel-rail interface significantly accelerate RCF growth, mainly through migration of subsurface micro-cracks to the surface of the rail. The surface cracks grow into larger ones that lead to loss of rail material. Controlling the grain size can have a positive effect on both the initiation and migration of sub-surface cracks. Changing yield strength of material with the Hall-Petch relation, the model evaluates the effect of refining the grain size. The results indicate that smaller grains can improve RCF properties of the rail. The effect of maximum contact pressure on RCF is studied, and the results show a power relation between maximum contact pressure and RCF life. Also several case studies are simulated and compared with the experimental observations. The simulation results are in close agreement with the experimental observations for the crack pattern and crack depth.

Intelligent tyres have the potential to be widely used to enhance the safety of road transportation systems by providing an estimation of the road surface friction, tyre load and several ot...

Energy dissipation in aluminum plates coated with a thin layer of Nickel–Titanium (NiTi) alloy subjected to a shock loading is studied. An experimental framework is designed and implemented to apply a shock load on the plates, using a liquid jet generated by collapsing of spark-generated bubbles under water. In this setup, a high-speed camera and a hydrophone are used to characterize the generated bubbles. Moreover, a laser Doppler vibrometer (LDV) and multiple strain gauges are implemented to investigate the vibration and mechanical responses of plates subjected to the water jet induced by cavitation bubbles. Comparing the mechanical response of an Al–NiTi plate with the same system in which the NiTi coating layer is replaced with an Al layer of the same thickness, shows that the propagation of shock waves is activating the forward and reverse phase transformations in NiTi that consequently results in dissipation of the shock wave energy in the material. The results approve the excellent cavitation erosion resistance of NiTi alloys which originates from their superior capability in attenuating stress waves and energy dissipation due to phase transformation, when the shock wave propagates in the material. Finite element simulations are also performed to investigate the energy dissipation capability of aluminum plates coated with a NiTi layer, when the structure vibrates by exerting and removing a concentrated transverse force at the center. When the energy of incident shock waves caused by cavitation bubbles is strong enough, the energy dissipation due to global structural vibrations can complement the energy dissipation due to the phase transformation. The computational results show that the observed energy dissipation in the experiments is exclusively caused by the shock wave propagation, not the transverse vibrations, and also investigate the details of energy dissipation for both NiTi and Al–NiTi composite plates subjected to a cyclic transverse load at the center.

Tire durability plays an important role in road transportation safety. Damaged tires can cause vehicle instability and create potential traffic accidents. To study the potential of using the intelligent tire concept for health monitoring of the tire, a computational method for defect detection in tire structure was developed. Comparing the trend of acceleration signals for the undamaged and damaged tires can reveal information about the crack length and location around the tire circumference. To accomplish this, a finite element model of the intelligent tire was developed using implicit dynamic analysis. In addition, using the data from the model, a health monitoring algorithm was developed for predicting the crack locations using the acceleration signals obtained from the tri-axial accelerometer attached to the tire inner-liner. It is observed that the radial component of the acceleration signal plays a key role in defect detection in intelligent tires.

Nowadays, additive manufacturing of metallic materials plays a key role in manufacturing technology due to its unique capability of printing strong and complicated components with high precision. Currently, the approach to obtain a specific mechanical performance in 2D printed metallic parts is a challenging and expensive iterative process. Using computational models to predict the mechanical properties of selective laser melting (SLM) metallic alloys based on their microscopic features can be leveraged to reduce the iteration cost for obtaining the desired mechanical properties. An accurate computational model will also be a superior tool to investigate practical modifications in the processing parameters to improve the mechanical performance of 3D printed metals. In this paper, a novel technique is developed to study the correlation between microstructural features, including melt pools and grain structures, and the macroscopic mechanical properties of SLM products. Crystal plasticity is utilized and calibrated to represent the material properties of grains. The capability of the model in considering the role of texture, process defects, mechanical loading direction, and laser scan hatch space on the mechanical behavior of SLM parts are evaluated. The good agreement between the obtained results and the reported experimental data confirms the accuracy of the developed computational model. Keywords: Selective laser melting, 3D printing, Micromechanics, Crystal plasticity, Stainless steel, Materials modeling

Locomotion is a critically important topic for soft actuators and robotics, however, the locomotion applications based on two-way shape memory polymers (SMPs) have not been well explored so far. In this work, a crosslinked poly(ethylene-co-vinyl acetate) (cPEVA)-based two-way SMP is synthesized using dicumyl peroxide (DCP) as the crosslinker. The influence of the DCP concentration on the mechanical properties and the two-way shape memory properties is systematically studied. A Venus flytrap-inspired soft actuator is made by cPEVA, and it is shown that the actuator can efficiently perform gripping movements, indicating that the resultant cPEVA SMP is capable of producing large output force and recovering from large deformations. This polymer is also utilized to make a self-rolling pentagon-shaped device. It is shown that the structure will efficiently roll on a hot surface, proving the applicability of the material in making sophisticated actuators. With introducing an energy barrier, jumping can be accomplished when the stored energy is fast released. Finite element simulations are also conducted to further understand the underlying mechanisms in the complex behavior of actuators based on cPEVA SMP. This work provides critical insights in designing smart materials with external stimulus responsive programmable function for soft actuator applications.

Cerium and magnesium strengthened aluminum alloys, or Al-Ce-Mg, is a recently developed alloy family that exhibits good mechanical properties at elevated temperatures (~300 °C). To examine the single-crystal properties of Al-Ce-Mg alloys, nanoindentation experiments are conducted in this study. A crystal plasticity finite element model (CPFEM) with the evolution of geometrically necessary dislocations (GNDs) is applied to simulate the indentation in individual grains. A parametric study is carried out to investigate the sensitivity of each crystal plasticity model parameter to the indentation behavior. The highly sensitive parameters are calibrated by matching the indentation load-depth curves, while the rest parameters are obtained from bulk polycrystal uniaxial tension tests. Overall, satisfactory matching between experiment and simulation is obtained for each individual grain. The calculated hardness, as determined from the experiment, shows the dependence on indent depth, which is captured by the GND model. Furthermore, the effect of grain orientation and neighboring grains to nanoindentation behavior have been discussed with the comparison between the simulation and experiments.

While metallic glasses exhibit exceptionally high strength, their relatively low ductility, accompanied by catastrophic failure caused by the formation of shear bands, is the major obstacle to using these materials in practical applications. Despite discovering some methodologies for improving the near-zero ductility of metallic glasses, overcoming this deficiency is still the most active field of research in designing and fabricating bulk metallic glasses. This work utilizes computational studies at the atomistic scale to demonstrate that adding graphene to metallic glasses is a superior method to improve their ductility. Our results show that the graphene layers in metallic glass-graphene composites will enhance the ductility by activation of three deformation mechanisms, including (i) confining the space for shear band formation, (ii) retarding the propagation of embryonic shear bands, and (iii) increasing the resistance of the metallic glass matrix against shearing during the nucleation and propagation of shear bands.

There is a promising future for the use of aluminum-cerium-magnesium alloys in a broad range of applications, including devices that operate at high temperatures. With cerium currently considered a waste product of rare earth mining validation studies of possible applications are essential to reduce the environmental waste. In this paper, a computational-experimental framework is developed to investigate the role both the intermetallic and matrix have on the mechanical properties of these alloys. A set of experiments, including SEM/EBSD imaging, nanoindentation, in-situ SEM tensile testing, and in-situ SEM-DIC tests are performed to characterize the microstructure and mechanical properties of these alloys. Furthermore, the elastic, plastic, and failure deformation mechanisms of the microstructure, and their correlation with the bulk scale mechanical properties are investigated. Experimental results are also used to calibrate parameters for a crystal plasticity finite element model, by performing a computational framework that minimizes the error between the computational and experimental results. This model is then utilized to investigate how the area percentage of intermetallics and the crystallographic texture control the mechanical properties of the alloy. Simulation results show that an increase in the percentage of intermetallics increase the strength but decrease the ductility of the alloy. Also, a change in material texture improves strength and reduces damage that leads to material failure. The development of the crystal plasticity model, as discussed in this work, opens opportunities for future investigations of similar aluminum-cerium-magnesium alloys.

This study demonstrates the significant role of recoil pressure in selective laser melting (SLM) process using multi-laser technology. High-speed photography is utilized to observe the formation mechanism, and also the behavior of spatter particles during SLM fabrication. A computational image analysis framework is developed to assess the size and the number of induced spatters. The morphology and the composition of spatters and their influence on the surface of the fabricated parts are determined. Unmelted regions, resulting from spatter deposition into the powder or the solidified layer, are found to be a detrimental type of defects on mechanical properties of SLM parts. This is followed by a discussion on demand for developing a meaningful process parameters optimization to enhance the mechanical properties of SLM products. Keywords: Selective laser melting, Spatter particles, Multi-laser technology, High-speed photography, Unmelted region

Prediction of how cracks nucleate and develop is a major concern in fracture mechanics. The purpose of this study is to provide an overview of the state of the art on fracture mechanics with primary focus on different methodologies available for crack initiation and growth prediction in rubber-based materials under the static and fatigue loading conditions. The concept of fracture mechanics applied to rubber-based materials and concern of finite element analysis for J-integral estimation in elastomers are discussed in this paper. The strain energy release rate is commonly used to describe the energy dissipated during fracture per unit of fracture surface area and can be calculated by J-integral method, which represents a path-independent integral around the crack tip. As fatigue crack growth most commonly occurs in structures, the high-cycle fatigue life of components needs to be predicted by using extended finite element, strain energy density, finite fracture mechanics, and other techniques which will be covered in this review paper. In addition, some recent testing and numerical results reported in the literature and their applications will be discussed.

Dislocations in the austenite phase of Nickel-Titanium (NiTi) shape memory alloys (SMAs) are of critical importance mainly due to their connection to the unrecoverable strains accumulated in SMAs during cyclic loadings, and also the key role of dislocations in the structure and energy of grain boundaries in these alloys. In this paper, we investigate the energy and structure of dislocations, and also the generalized stacking fault energies in NiTi austenite by implementing molecular dynamics (MD) simulations. Through our results the validity and accuracy of three different potentials, two EAM potentials with different cutoff radii and one 2NN MEAM potential, for studying defect related properties of NiTi alloys is investigated. It is shown that while none of these potentials are particularly trained for predicting defect properties in NiTi systems, they can be efficiently utilized to study the stacking fault energies, the energy and structure of edge dislocations, stress distributions at the vicinity of edge dislocations, and even the details of dislocation dissociation in NiTi austenite phase. Particularly our results can be used as a tool to select the appropriate potential for studying any problem related to a specific aspect of defects in austenite NiTi SMAs.

A computational model based on the multiscale progressive failure analysis is employed to provide the theoretical predictions for damage development in the cord-rubber composites in tires. Vulcanized rubber, reinforcing belts, and carcass used in tire structures cause the anisotropic behavior under different loading conditions. Steel reinforcement layers made of steel wires combined with rubber complicate the macro-scale finite element modeling of tires. This paper presents a new three-dimensional model of the cord-rubber composite used in tires in order to predict the different types of damage including matrix cracking, delamination, and fiber failure based on the micro-scale analysis. Additionally, intelligent tires have the potential to be widely used to enhance the safety of road transportation systems, and this paper provides an estimation of the effects of void volume fraction, fiber volume fraction, and stacking sequence of the cord-rubber composites on the acceleration profile of the tire ...

Accurate and deep understanding of the mechanical and physical behavior of sandwich panels with soft elastomeric foams, e.g. cellular solids, such as ethylene vinyl acetate is a key task in designing these structures, and also optimizing their mechanical behavior. The main objective of the present research is to present an applicable method to determine the non-linear hyper-viscoelastic response of elastomeric sandwich panels to low velocity impact loadings, by presenting an applied method. A combination of experimental results and finite element analysis, in conjunction with optimization method is used to determine the hyper-viscoelastic behavior of the studied sandwich panels. The suggested combinational approach can replace the time-consuming and expensive creep and/or relaxation experiments. A relatively simple approach is proposed to identify time-dependent viscoelastic material behavior of elastomeric foams. The calibrated finite element model is utilized to perform a set of parametric studies and the effect of various material properties is studied on the low velocity impact response of sandwich plates.

Energy and structure of tilt grain boundaries are studied in Nickel-Titanium (NiTi) alloys. Molecular dynamics (MD) simulations are utilized to investigate the excess energy of symmetric and asymmetric tilt grain boundaries as a function of the misorientation and inclination angles. Structural units of different symmetric grain boundaries are identified and the correlation between the structure and energy is investigated. It is shown that the Read-Shokley model can accurately predict the energy of low angle symmetric tilt grain boundaries in austenite NiTi alloy. Density functional theory (DFT) calculations are used to study two representative symmetric grain boundaries. Comparing to DFT calculations, it is shown that the MD results can predict the GB potential energies accurately. The Electron charge density distributions are studied and the bonding strength between atoms, and low/high charge density regions are investigated, and accosted with the structural units in the grain boundaries. It is shown that a symmetric arrangement of Ni and Ti atoms at the GB improved the uniformity of bonding and charge density distribution.

Controlled drug delivery (CDD) technologies have received extensive attention recently. Despite recent efforts, drug releasing systems still face major challenges in practice, including low efficiency in releasing the pharmaceutical compounds at the targeted location with a controlled time rate. We present an experimentally-validated acoustic-thermoelastic mathematical framework for modeling the focused ultrasound (FU)-induced thermal actuation of shape memory polymers (SMPs). This paper also investigates the feasibility of using SMPs stimulated by FU for designing CDD systems. SMPs represent a new class of materials that have gained increased attention for designing biocompatible devices. These polymers have the ability of storing a temporary shape and returning to their permanent or original shape when subjected to external stimuli such as heat. In this work, FU is used as a trigger for noninvasively stimulating SMP-based systems. FU has a superior capability to localize the heating effect, thus initiating the shape recovery process only in selected parts of the polymer. The multiphysics model optimizes the design of a SMP-based CDD system through analysis of a filament as a constituting base-structure and quantifies its activation under FU. Experimental validations are performed using a SMP filament submerged in water coupled with the acoustic waves generated by a FU transducer. The modeling results are used to examine and optimize parameters such as medium properties, input power and frequency, location, geometry and chemical composition of the SMP to achieve favorable shape recovery of a potential drug delivery system.

Titanium (Ti) alloys are one of the most appropriate metals for bio-medical applications, specifically in making implants. However, the high difference between the stiffness of the Ti alloys and compact bone results in stress shielding of the bone and stress concentration at the implant, both of which are undesirable and could result in implant failure. One method to reduce the stiffness of a dense implants and avoid the stress shielding is adding porosity to the structure. This however results in considerable reduction in the toughness of the structure, which is also undesirable for the long-term success of implants. In this work, we study a new method for independently tuning the stiffness and toughness of the material by adding various polymers to the additively manufactured porous Ti structures. Porous Ti samples with two levels of porosity are fabricated through additive manufacturing. Three different types of thermoplastic polymers are utilized to fill the pores and make the titanium-polymer composite parts. Compression simulations and tests are performed on both porous and composite specimens to compare the mechanical behavior of these structures. Various finite element simulations are conducted on different structures and the results are verified with experiments. Simulation results and experimental findings indicate that filling porous Ti with thermoplastic polymers leads to an increase in the toughness of the structure. The percentage increase of the toughness is assessed as a function of the polymer toughness and the level of porosity in various samples. Our results pave the way for designing polymer-composite structures with independently tunable stiffness and toughness for being employed in a broad range of applications.

This paper presents a computational framework to model the mechanical response of selective laser melting processed 316L stainless steel by considering both the grain and melt pool in the material. In this model, inspired by the experimental observations, individual melt pools are approximated by overlapped cylinder segments that are connected to each other by cohesive surfaces. Each of the melt pools contains several grains, modeled by Voronoi tessellation method to represent the realistic grains in a polycrystalline material. The proposed computational model is used to predict the effects of various microstructural properties on the mechanical properties of the manufactured samples. These microstructural properties include melt pool size, the overlap between neighboring melt pools, texture, process-induced defects, and the orientation of layers with respect to the loading direction. Furthermore, several flat dog bone shaped 316L stainless steel samples are fabricated with selected values of laser power, scanning velocity, and scanning direction and their mechanical properties were determined to relate the macro-mechanical properties to the microstructural modeling and processing parameters. Keywords: Selective laser melting (SLM), Finite element model, Cohesive zone model, Stainless steel

In this paper, the micro-mechanical mechanisms behind the initiation and propagation of rolling contact fatigue (RCF) damages caused by the large traction forces are investigated. This study provides a three-dimensional (3D) model for studying the rolling contact fatigue in rails. Since rolling contact fatigue is highly dependent on the rail’s steel microstructure behavior, a proper 3D approach to capture the microstructure- and orientation-dependent mechanical behavior is required. A precise material model known as crystal plasticity is used for this purpose. Additionally, a cohesive zone approach is implemented to capture the crack initiation and propagation at the grain boundaries. Using the 3D finite element model which is developed for this study, we evaluate the effect of various parameters such as traction forces along the rail, and also the normal forces on the RCF response. The results reveal that the RCF cracks initiate slightly below the rail surface. These cracks start propagating toward the rail surface when the contact force is applied in repeated load cycles. The results also indicate that the depth at which RCF initiates depends on the ratio between the longitudinal traction forces and the normal loads. With larger traction forces, the cracks initiate closer, or at the rail surface, whereas larger normal loads promote the cracks initiation beneath the surface.

Man-made armors often rely on rigid structures for mechanical protection, which typically results in a trade-off with flexibility and maneuverability. Chitons, a group of marine mollusks, evolved scaled armors that address similar challenges. Many chiton species possess hundreds of small, mineralized scales arrayed on the soft girdle that surrounds their overlapping shell plates. Ensuring both flexibility for locomotion and protection of the underlying soft body, the scaled girdle is an excellent model for multifunctional armor design. Here we conduct a systematic study of the material composition, nanomechanical properties, three-dimensional geometry, and interspecific structural diversity of chiton girdle scales. Moreover, inspired by the tessellated organization of chiton scales, we fabricate a synthetic flexible scaled armor analogue using parametric computational modeling and multi-material 3D printing. This approach allows us to conduct a quantitative evaluation of our chiton-inspired armor to assess its orientation-dependent flexibility and protection capabilities., Biology has often served as the inspiration for the design of body armor; one common limitation is the flexibility of the resultant armor. Here, the authors examine the armour of chiton and use the observed design principles to 3D print flexible armor.

Studies have demonstrated that cancer cells tend to have reduced stiffness (Young's modulus) compared to their healthy counterparts. The mechanical properties of primary brain cancer cells, however, have remained largely unstudied. To investigate whether the stiffness of primary brain cancer cells decreases as malignancy increases, we used a microfluidic constriction channel device to deform healthy astrocytes and astrocytoma cells of grade II, III, and IV and measured the entry time, transit time, and elongation. Calculating cell stiffness directly from the experimental measurements is not possible. To overcome this challenge, finite element simulations of the cell entry into the constriction channel were used to train a neural network to calculate the stiffness of the analyzed cells based on their experimentally measured diameter, entry time, and elongation in the channel. Our study provides the first calculation of stiffness for grades II and III astrocytoma and is the first to apply a neural network analysis to determine cell mechanical properties from a constriction channel device. Our results suggest that the stiffness of astrocytoma cells is not well-correlated with the cell grade. Furthermore, while other non-central-nervous-system cell types typically show reduced stiffness of malignant cells, we found that most astrocytoma cell lines had increased stiffness compared to healthy astrocytes, with lower-grade astrocytoma having higher stiffness values than grade IV glioblastoma. Differences in nucleus-to-cytoplasm ratio only partly explain differences in stiffness values. Although our study does have limitations, our results do not show a strong correlation of stiffness with cell grade, suggesting that other factors may play important roles in determining the invasive capability of astrocytoma. Future studies are warranted to further elucidate the mechanical properties of astrocytoma across various pathological grades.

Metal aqueous corrosion is a common electrochemical phenomenon. Nonetheless, the metal corrosion simulations at the atomistic scale have not been well-established yet. In this study, several copper corrosion cases in aqueous solution with chloride ions are studied with molecular dynamics, especially the flow induced corrosion is studied for the first time to the best of our knowledge. The copper corrosion in two kinds of solutions, which are HCl and chloride ions solutions, are simulated with pre-developed reactive force field (ReaxFF) method. Here, particles diffusion, bonding among elements, and charge evolution are analyzed to understand the mechanisms of the cases. It is found that the electrolyte flowing and initial Cu surface can accelerate the corrosion process, illustrated by higher mean-squared displacement (MSD) and Cu average charge. Moreover, the initial rough surface has different effects for different electrolyte concentrations. This work may provide important references for fundamental understanding the mechanisms of copper corrosion in chloride-containing solutions at nanosized scale.

Unraveling the deformation mechanisms at the atomistic scale of metal matrix-graphene composites is a key step toward designing and fabricating these materials with exceptional mechanical properties. While these composites can be made by embedding graphene into multiple metallic matrices, it is shown that superior mechanical properties can be obtained by combining copper and graphene. In the past few years, molecular dynamics simulations have been used to investigate the fundamental deformation mechanisms at the nanoscale of Cu-graphene composites to facilitate designing these composites with improved mechanical properties. However, in all of the reported works, Lennard-Jones potential has been used for modeling the interaction between copper and carbon atoms. The complexities in the Cu-C interaction emerges the necessity of utilizing more accurate potentials. In this work, a 2NN MEAM (second nearest-neighbor modified embedded atomic method) potential for the copper and carbon atom interaction is developed. Since crystal structures like B1 or B2 are not experimentally available for the Cu-C system, first-principle calculations are used to determine the reference structure and its elastic constants in this work. It is shown that the B1 and B2 structure of Cu-C has positive formation energy, but B1 is dynamically stable. Accordingly, the B1 crystal structure is used as the reference structure for the Cu-C system to develop the interatomic potential. It is shown that the reported potential agrees reasonably well for phonon dispersion frequencies, stacking fault energies, and the atomic forces with the available experimental data and first-principle calculations. The developed potential is utilized to study the mechanical properties of copper-graphene composites subjected to uniaxial loading. Our results show that adding graphene to a defect-free Cu crystal weakens the metallic matrix’s mechanical properties. However, when the graphene is embedded into a Cu matrix with some defects, e.g., in a polycrystalline Cu, it can significantly improve the mechanical properties.

Experiments show that high-intensity focused ultrasound (HIFU) is a promising stimulus with multiple superior and unique capabilities to induce localized heating and achieve temporal and spatial thermal effects in the polymers, noninvasively. When polymers are subjected to HIFU, they heat up differently compared to the case they are subjected to heat sources directly; however, the origins of this difference are still entirely unknown. We hypothesize that the difference in the macroscale response of polymers subjected to HIFU strongly depends on the polymer chains, composition, and structure, i.e. being crystalline or amorphous. In this work, this hypothesis is investigated by molecular dynamics studies at the atomistic level and verified by experiments at the macroscopic scale. The results show that the viscoelasticity, measured by stress–strain phase lag, the reptation motion of the chains, and the vibration-induced local mobility quantified by the root mean square fluctuation contribute to the observed difference in the HIFU-induced thermal effects. This unravels the unknown mechanisms behind stimulating the polymers by HIFU, and paves the way in front of using this method in future applications.

A quasi-2D model of Micro-selective laser melting (μ-SLM) process using molecular dynamics is developed to investigate the localized melting and solidification of a randomly-distributed Aluminum nano-powder bed. One of the biggest challenges in modeling the μ-SLM process is the computational treatment of the formation and growth of crystal nuclei in the meltpool. The present work overcomes this challenge using molecular dynamics simulation because of its capability to explicitly model the nucleation and growth of grains inside the meltpool. The localized heating and rapid solidification of meltpool is simulated by the direct control of the temperature in the meltpool both spatially and temporally. The rapid solidification in the meltpool reveals the cooling rate dependent homogeneous nucleation of equiaxed grains at the center of the meltpool. Additionally, the epitaxial grain growth from the adjacent laser tracks, previous layers, and partially melted nano-powders into the solidifying meltpool is observed along the highest heat flow directions. The growth of the long columnar grains into the top layer is inhibited if the penetration depth during the remelting of a previous layer is less than the depth of the equiaxed grains. Long columnar grains that spread across three layers, equiaxed grains, nano-pores, twin boundaries, and stacking faults are observed in the final solidified nanostructure obtained after ten passes of the laser beam on three layers of Aluminum nano-powder particles. Hot isostatic pressing (HIP) of the final solidified nanostructure is employed to eliminate the nano-pores, which act as sources of crack initiation during tensile loading. Higher applied stress is required for the crack initiation and propagation in the hot isostatically pressed nanostructure compared to the as-built Aluminum nanostructure owing to the absence of nano-pores.

High-intensity focused ultrasound (HIFU) is a promising stimulus that has received extensive attention during the past two decades due to numerous advantages of this technology when compared to the conventional methods. For HIFU-responsive polymers, their applications could be extended to controlled drug delivery, soft robotics, and flexible electronics. In this work, experiments show that polymers heat up in a different manner when they are subjected to HIFU, compared to the case they are subjected to heat sources directly. However, the origins of this difference are still entirely unknown. To further investigate, molecular dynamics (MD) simulations are performed to study the thermal effect of polymers induced by HIFU. We found the difference in the macroscale response of polymers subjected to HIFU strongly depends on the polymer chains, composition, and structure. The frequency-dependent viscoelasticity, measured by stress-strain phase lag, the reputation motion of the chains, and the vibration-induced local mobility, quantified by the root mean square fluctuation (RMSF) contribute to the observed difference in the HIFU-induced thermal effects. The simulation results show a good accordance with the experiment qualitatively, and provide the fundamental mechanism for designing and optimizing stimuli-responsively polymeric devices. [Work supported by: this work was supported by NSF Grant No. CMMI-2016474.]

Selective Laser Melting (SLM) of certain alloys such as Stainless Steel yields a unique microstructure consisting of complex subgranular cell structures produced by ultra-fast cooling during solidification. Owing to the presence of these cell structures, SLM-fabricated 316L Stainless Steel displays a superior yield strength and hardness. Despite the significance of the distinctive cellular structures, their deformation characteristics and the mechanisms responsible for superior mechanical properties are not well-understood yet. In this paper, the mechanical deformation behavior of the complex cellular structures observed in the SLM-fabricated 316L Stainless Steel is investigated by performing a series of molecular dynamics simulations of uniaxial tension tests. The atomic configurations in the computational models of the cell structures are inspired by the SEM images of the microstructure of 316L Stainless Steel. The effects of compositional segregation of alloying elements, distribution of austenite and ferrite phases in the microstructure, subgranular cell sizes, and pre-existing (grown in) nano-twins on the tensile characteristics of the cellular structures are investigated. The highest yield strength is observed when the Ni concentration in the cell boundary drops very low to form a ferritic phase in the cell boundary. However, the flow stress is found to be the highest when both the cell boundary and cell interior are austenitic with higher Ni concentration in the cell interior. Moreover, governed by the initial dislocation density, the subgranular cell size has an inverse relationship with mechanical strength. Finally, the nano-twinned cells exhibit higher strength in comparison with twin-free cells as a result of the dislocation pinning at the twin boundaries. The investigation on the effect of twin spacing reveals a Hall-Petch type phenomenon in which smaller twin spacing strengthens the nano-twinned subgranular cells further.

The effect of graphene-metal interface on dislocation gliding and generation is a key element in understanding the mechanical properties of graphene metal-matrix composites. Graphene-metal interfaces can impede the propagation of dislocations, which enhances the mechanical properties, particularly the strength. On the other hand, the presence of such interfaces can also act as the dislocation source in the metal matrix, which can significantly weaken the material properties. This implies that graphene will not always improve the mechanical properties of metals, but alternatively, it can even significantly weaken the properties. Whether graphene acts as a dislocation sink or source primarily depends on the metal-graphene interface and also other pre-existing defects in the matrix. In this paper, we investigate these two opposing effects at the atomistic scale, using Molecular Dynamics (MD) simulations. To study the effect of the interface and to isolate the effects of dislocations from defects, we have reinforced a perfect crystal of nickel with graphene. We found that in the perfect crystal, the graphene in any interface structure acts as a defect and weakens the metal matrix. Each interface structure in the composite has a different effect on the system, and the topfcc structure of the graphene-nickel interface results in the least strength reduction. For graphene particles, apart from the interface, edges can also act as a dislocation nucleation site. We investigated the two edges –Zigzag and Armchair edge of graphene– and found that both the edges cause decrease in mechanical strength. Experimental results (always reported an increase in mechanical strength) are in contradiction to what we found in this work. The reason for this contradiction is that in the real metallic system, defects are already present, and those acts as a dislocation source more readily than the graphene. To verify this, we studied the metallic systems having defects in nickel crystal and the graphene is reinforced. Through these studies, we investigate the conditions in which the strengthening mechanisms overcome the weakening mechanisms, and improvement is observed in the mechanical properties, similar to some of the reported experimental works. Our results shed light on the deformation mechanisms in metal-graphene composites and can be used as a guide in designing and fabricating more efficient metal-matrix composites.

A micromechanical-based 2D framework is presented to study the rolling contact fatigue (RCF) in rail steels using finite element method. In this framework, the contact patch of rail and wheel is studied by explicitly modeling the grains and grain boundaries, to investigate the potential origin of RCF at the microstructural level. The framework incorporates Voronoi tessellation algorithm to create the microstructure geometry of rail material, and uses cohesive zone approach to simulate the behavior of grain boundaries. To study the fatigue damage caused by cyclic moving of wheels on rail, Abaqus subroutines are employed to degrade the material by increasing the number of cycles, and Jiang-Sehitoglu fatigue damage law is employed as evolution law. By applying Hertzian moving cyclic load, instead of wheel load, the effect of traction ratio and temperature change on RCF initiation and growth are studied. By considering different traction ratios (0.0 to 0.5), it is shown that increasing traction ratio significantly increases the fatigue damage. Also by increasing traction ratio, crack initiation migrates from the rail subsurface to surface. The results also show that there are no significant changes in the growth of RCF at higher temperatures, but at lower temperatures there is a measurable increase in RCF growth. This finding correlates with anecdotal information available in the rail industry about the seasonality of RCF, in which some railroads report noticing more RCF damage during the colder months.