This PDF file contains the front matter associated with SPIE Proceedings Volume 11377 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

On demand material behavior, or functionality, has long been a target in modern engineering. The ability to design, synthesize, generate, control, and predict the response of functional materials and structures is an overarching goal pulling together expertise and ideas from various subfields. The fundamental scientific questions probed are different depending on whether you are a chemist, materials scientist, or aerospace engineer. From programmable materials and structures to integrated computing and evolutionary materials, reaching this target on a grand scale will require the early integration of science and engineering. Advances in data sciences has created the potential for us to accelerate the rate of knowledge transfer across the traditional boundaries as well as fundamentally change the way we carry out research. In this presentation, we discuss research trends in functional materials from the CMMI Mechanics of Materials and Structures program perspective. We will show recent examples from synthetic biology to metamaterials to soft robotics where many opportunities and challenges remain. We will discuss the role of data sciences and interdisciplinary teaming in carrying innovation across length and time scales and towards truly transformative research. Relevant NSF funding opportunities that are sparsely used by the community will be shared. Finally, we point to future directions for technological innovations powered by functional materials.

Shape morphing is one of the most appealing applications of adaptive structures. Among the various means of achieving shape morphing, origami-inspired folding is particularly advantageous, because folding is a powerful approach to induce three-dimensional and sophisticated shape changes. However, attaining large-amplitude folding is still a challenge in origami engineering. While promising, the use of active materials as a folding activation strategy is limited due to the constant voltage supply that is required to maintain the desired configuration of the structure. One possible solution is to embed bi-stability into the structure. Bi-stability can play two significant roles here: first, it can significantly reduce the actuation requirement to induce shape morphing, and second, it can maintain the shape change without demanding sustained energy supply. In a previous study by the authors, a unique shape morphing (or self-folding) method using harmonic excitation has been proposed for a bi-stable water-bomb base. However, this approach has some drawbacks because the nonlinear dynamic behaviors of origami are quite sensitive to different design parameters, such as initial conditions, excitation parameters, and inaccuracies in manufacturing. In this study, via numerical simulations, we show that by harnessing the intra-well resonance of the water-bomb structure and incorporating a relatively simple feedback control strategy, one can achieve a rapid and robust morphing using relatively low actuation magnitude. The results of this study can lay the foundation of a new category of morphing origami mechanisms with efficient and reliable embedded actuation.

Natural hazards are among the largest construction challenges today. By taking dynamic building envelopes designed using origami and kirigami principles, a more comprehensive structure can be built to sustain impacts by high winds. By combining a wind tunnel for small-scale simulation of hurricane conditions and computational analysis for full-scale buildings, a comparison can be made to find differences between experimental data collected and the results from computational fluid dynamics simulations. Results show that by increasing the number of facets at an angle to wind flow and decreasing the size of the facets, the size of the body direct to wind flow can be minimized and wind resistance can be decreased.

Auxetic foams have a variety of unique properties due to their negative Poisson ratio such as high energy absorption and fracture toughness for applications such as sports safety equipment, packing material, and shoe soles. The viscoelastic behavior of this relatively new material has not been extensively studied and modeled. Better knowledge of the viscoelastic behavior over a broad range of deformation rates is critical when considering the mechanical properties of the material. Previous modeling for positive Poisson ratio materials has been completed successfully to characterize the behavior. This same modeling was applied to auxetic foams with less success. The influence of nonlinear compressibility effects greatly improved calibration and prediction. Model simulations across several orders of magnitude in deformation rates are validated against data. All results are statistically validated using maximum entropy methods to obtain posterior densities for the hyperelastic and fractional order parameters. Importantly, a maximum entropy algorithm is used such that heterogeneous data can be fused to inform and validate the model and quantify its uncertainty.

The ferroelectric and antiferroelectric properties of ZrO₂ ultrathin films (~12 nm in thickness) prepared by atomic layer deposition (ALD) were tailored by introducing sub-nanometer interfacial layers between the ZrO₂ ultrathin film and top and bottom Pt electrodes. In terms of polarization switching ability, the ferroelectricity of ZrO₂ ultrathin films was significantly enhanced by an HfO₂ interfacial layer (i.e., a Pt/HfO₂/ZrO₂/HfO₂/Pt layered arrangement). While, a TiO₂ interfacial layer (i.e., a Pt/TiO₂/ZrO₂/TiO₂/Pt layered arrangement) led to a transition from ferroelectricity to antiferroelectricity. The modulation of ferroelectricity and antiferroelectricity of ZrO₂ ultrathin films by the interfacial layers can be achieved without post-annealing.

Conductive nanofiller-modified materials have received a significant amount of interest for use in self-sensing, nondestructive evaluation (NDE) and structural health monitoring (SHM) owing to their piezoresistive properties (i.e. having deformation-dependent electrical transport). To date, the majority of the work related to piezoresistivity has focused on the relation between direct current (DC) conductivity or resistivity and strains. However, DC-based methods of selfsensing have important limitations such as poor sensitivity to spatially distributed damage and high resistivity. Alternating current (AC)-based methods of electrical interrogation have potential to address these limitations. Unfortunately, much less work exists on the effect of strain on AC conductivity. Therefore, we herein explore the effect of strain on AC conductivity in piezoresistive polymer nanocomposites. Specifically, epoxy is modified with carbon nanofibers (CNFs) at 1 wt.% and tested under uniaxial loading as AC conductivity is measured as a function of interrogation frequency. The AC conductivity-frequency relation is then fit to a universal power law for a range of compressive and tensile strains such that power-law fitting constants can be expressed as a function of normal strain. The basic insights revealed from this work are an important step toward transitioning piezoresistive-based self-sensing from prevailing DC approaches to potentially much more powerful AC methods.

Band gaps that lead to attenuation of vibration propagation characterize locally resonant metamaterials. However, the band gaps rely on heavy resonators. In this work, we propose an electromechanical metamaterial rod that consists of an elastic rod with periodically attached electromagnetic resonators each composed of a cantilever beam and a magnetic. The magnets of multiple resonators are shunted by a resonant circuit and the stiffness of these resonators can be different. The attenuation constant surface (ACS) plots show that for unit cells of different mechanical resonators and unit cells of identical electromagnetic resonators, multiple band gap coupling phenomena can occur due to multiple local-resonance band gaps and the Bragg-type band gap coalescing, thereby forming a unified band gap much wider than a local-resonance band gap. Furthermore, the transmittance of the finite rod shows that several narrow pass bands can occur due to the slow convergence to the infinite rod. It also shows that the presence of electrical resistance suppresses the narrow pass bands. Consequently, the proposed metamaterial rod can achieve attenuation of vibration propagation in a broader frequency range than conventional metamaterial rods consisting of identical resonators.

As the development of Internet of Things (IoT), the power supply to the sensors in IoT becomes more and more important. The piezoelectric material was widely studied as a material for energy harvesting devices. Our target is to design and fabricate a flexible, eco-friendly and light functionally graded piezocomposite for energy harvesting devices by polyvinylidene fluoride (PVDF) and lead-free piezoelectric particles. Two kinds of lead-free piezoelectric particles -- barium titanate (BTO) and potassium sodium niobite (KNN) are used in the study. And the addition of the PVDF can greatly improve the toughness of the material and broaden the applications of the material. In this study, the multi-layer lead-free piezoelectric particle/PVDF composites with different contents of lead-free piezoelectric particles and structure are fabricated by spin coating and hot press method. The suitable parameters of the spin coating and hot press are found. The composites are polarized by corona poling method and optimal poling conditions of the composites are also studied. Scanning electron microscopic (SEM) observations are conducted to study the distribution of the particles in the matrix and the interface between the different layers. Then, the piezoelectric coefficient d₃₃ is measured by a piezo-d₃₃ meter. This study gives a workable fabrication method to the functionally graded piezocomposites and explores the piezoelectric properties of the composites which have potential to be used as energy harvesting device materials.

In this study, we developed a new type of ferroelectret cellular film by using commercial polypropylene film (PQ60). We first use gas diffusion expansion method to create the void structure inside PQ60 followed by using corona discharge to trap charges in the voids. Then dynamic method was chosen to measure the piezoelectric constant d₃₃. The measured d₃₃ value was above 150 pC/N. We further use Laser-Intensity-Modulation Method to measure the heat induced current from the surface of the cellular PQ60 film at various intensity-modulated frequencies. The result of LIMM can be used to analyze sensor and actuator performance in ferroelectret.

Researchers incorporated adaptive wingtip devices in UAVs and full-scale aircraft to improve aerodynamic efficiency and to act as control effectors. However, these devices had been characterized statically, where their dynamic response was ignored. This paper characterizes the deployment dynamics of a novel adaptive multi-winglet (AMW) device. Each winglet in AMW is a feather-inspired composite exhibiting bending-torsion coupling. The gap spacing between each winglet is controlled by SMAs to vary the effective stiffness of AMW. Wind tunnel experiment’s results show the aerodynamic forces and moments produced by a wing with an AMW device with different gap spacing under different flight conditions.

Shape Memory Alloy (SMA) actuation is often cited as significantly lighter weight and more compact than conventional actuation methods such as electromechanical (EM) or hydraulic motors. Yet there few studies directly comparing and demonstrating a SMA actuation design to a conventional design for a specific application. In this paper a complete system level design, build, and test using both SMA and EM actuation are described. Adaptive spars for a medium sized UAV wing twist application are demonstrated and a detailed comparison of size, weight, power, and performance clearly demonstrates the advantages of SMA actuation.

Shape memory nickel-titanium (NiTi) thin films have demonstrated superior capabilities in microelectromechanical systems and biomedical implants due to its corrosion resistance, large work output per unit mass, radiation resistance, and biocompatibility. The goal of this project is to additively manufacture NiTi thin film devices with micrometer resolution. NiTi colloid inks for 3D printing applications were developed and characterized. NiTi thin films were then printed onto a ceramic substrate using an aerosol jet printer, subsequently, sintering and heat treatment procedures were developed. Damping capability and output power density of the printed NiTi thin films were eventually characterized.

Shape memory polymers (SMPs) are studied extensively for self-folding origami due to their low cost, large strain recovery and low activation energy. SMPs utilize viscoelastic strain recovery to induce shape change, wherein an external stimulus, e.g. light or electricity, heats the material above the glass transition temperature to accelerate the recovery. Application of electric current to a conductive SMP composite produces Joule-heating, which provides higher energy density and a shorter self-folding time compared to other stimuli. Previous research has focused on Joule-heat induced shape recovery using SMP samples containing uniformly dispersed conductive fillers. Application of an electric field to these samples causes them to heat and change shape uniformly, thus limiting the ability to fold locally. In contrast, the present study focuses on shape recovery of a prestrained SMP sheets using localized resistive Joule-heating via a nichrome wire. The localized heat input applied to the SMP enables self-folding in specific regions of the sample. A previously prestrained polymer sample, experiences a differential shrinking between its top and bottom surface when subjected to the local Joule-heat. The differential shrinking causes the polymer to have a strain gradient along the thickness, which results in self-folding of the sample. This paper studies the thermal and mechanical response of Joule-heat induced self-folding of polymer sheets subjected to varying applied current and electrical resistance. Furthermore, an in-house polymer prestraining sequence is also reported.

Shape memory polymers (SMP) have been extensively implemented for applications ranging from biomedical devices and soft robotics to deployable structures. However, these materials mostly rely on heat for shape recovery and programming. Here, we introduce a new class of smart SMPs with pressure-responsive characteristics based on dynamic porosity–an ability to configure a pore size within a solid– that allows for optical monitoring of the stimuli. Introducing pores in a structure reduces the relative density of the material and introduces interfaces resulting in a reduction in optical transparency of the bulk through light scattering. We show that utilizing the dynamic porosity, a macroporous film transitions instantly from an optically opaque (25% transmittance) to a transparent (96% transmittance) state by applying an out-of-plane contact pressure of 3.8 MPa at room temperature. The new SMP also presents an anomalous ‘cold’ shape recovery of the pressure-activated films through repeated in-plane stretching that renucleates the pores and transitions the material back to the initially opaque state. The presented concept ushers a new class of responsive materials that interlace optical sensitivity features with micro- and nanoscale material deformations, establishing new research opportunities in the field of SMPs.

Within numerous disciplines, the ability to model and then optimize structures for a given application is of paramount importance to the design process. Topology optimization has been established as a valuable tool within such a structural design process as it allows for the realization of high-performing and non-intuitive material distributions within a design domain without the need for rigorous initial parameters. Traditional topology optimization methodologies are historically applied considering only static loading conditions consisting of a limited number of forces and displacements, thus optimizing desired performance metrics only under these conditions. As an alternative, this work proposes the use of a Lindenmayer System coupled with a graphbased interpreter known as Spatial Interpretation for the Development of Reconfigurable Structures (SPIDRS) to optimize the response of a structural topology over a range of loading magnitudes. The structures examined herein have the goal of matching their mechanical response under loading to an arbitrarily defined stiffness curve. Consequently, this work is one of the first to employ topology optimization in the generation of a structure with a specified behavior across a range of loading conditions. It will be shown that the L-System/SPIDRS framework enables the design of structures which produce a desired reaction force at each of many defined displacements in both tensile and compressive loading conditions.

Bistable laminated composites are attractive for morphing structures because they can hold deformed stable shapes without any external energy and require actuation only to switch between shapes. They offer opportunities for shape morphing, energy harvesting, and flow control devices. Piezoelectric macrofiber composites (MFC) embedded in bistable laminates have been demonstrated for actuation and energy harvesting. However, their relatively high stiffness, relatively complex architecture, and arbitrary fiber orientation limit their ability to sense shape change in bistable laminates. There has been little work on the integration of sensing methods to monitor an adaptive structure’s shape; shape sensing has been investigated mainly for the detection of snap-through events. In this paper, we present self-sensing curved bistable laminates layered with piezoelectric PVDF films that can sense smooth changes as well as abrupt snap-through transitions. Measurement of smooth changes in the laminate’s curvature is enabled by an automated drift compensation charge amplifier with an extremely low cutoff frequency of 0.01 mHz. The sensing function is demonstrated on bistable laminates created using mechanical prestress. Two sensor layers are configured in the composite such that one measures change in curvature and the other measures snap-through response. The shapes measured by the sensor in terms of voltage correlate well with the shapes measured with a 3D motion capture system. An analytical model is developed to relate curvature change to voltage output and is found to be in good agreement with the measured curvature-voltage sensitivities. The weakly coupled shapes of the laminate and the low cross sensitivity of PVDF enable real-time measurement of the principal curvatures.

Maximizing the benefit of applying piezoelectric materials in composite structures, which are a mix of piezoelectric and elastic elements, requires analytical modeling. In this paper, we describe two main classes of resonators and how to model using network equivalent including material losses. These include extensional devices where the layer areas are parallel to the direction of wave travel as found in a variety of thickness or length mode transducers (BC. Stress T₁ = T₂ at boundary) and transverse mode resonators (BC. Strain S₁ = S₂ at boundary) where the major layer area is perpendicular to the wave direction as is found in radial mode or length thickness mode composite resonators. In order to illustrate these models, we will use Mason’s equivalent circuits with elastic, dielectric and piezoelectric loss. It is noted that in order to maintain consistency with the linear equations of piezoelectricity and the wave equation care is required when applying complex loss coefficients to the models. Although these techniques are applicable to other models, we use Mason’s network equivalent circuit because it is intuitive for composite modeling due to the frequency independent turns ratio. Also, because of the independence of the equations describing the elastic layers from the adjoining layer properties which aid in understanding the boundary conditions to impose on the layer boundaries. We will present network models for a variety of applications with loss and show how to calculate their impedance spectra, interface stress, strain velocity and displacement spectra.

In mechanical metamaterials, geometry and material properties dictate the structural response to mechanical loads. These materials are comprised of a tessellated array of repeat unit cells, which form a lattice that populates the domain of the structure. While the mechanical behavior of 2D lattices is well understood, recent advances in polymer based Additive Manufacturing (AM) usher in a new era of metamaterials research. However, previous work in this area has failed to address the effects of time and temperature on the transient response of polymerbased mechanical metamaterials. We seek to investigate the effects of thermal loads on the mechanical properties of mechanical metamaterials, in particular, the stiffness and damping properties of lattice structures comprised of bowtie and honeycomb representative unit cells. Towards this goal, in the present paper, an experimental approach is used to investigate the mechanical behaviour of 2D lattice structures. Experimental samples are prepared using Fused Deposition Modeling (FDM) AM. These samples are subject to quasi-static mechanical tests at room temperature. Additionally, we investigate the effects of mismatched unit cells (defects) on the mechanical behavior of the lattice. Mechanical metamaterials with adjustable stiffness and damping properties have applications in the aerospace and automotive industries, including sandwich composites, damping and impact protection.

Post-process heat treatments are conventional methods used to minimize porosities and improve the microstructure of metallic parts. It can also increase the hardness value and help tailor the mechanical properties of the part. On the other hand, the heat treatment process includes several steps and can be a costly and time-consuming procedure. The different variables and parameters in heat treatment can make this process even more complicated. Utilizing optimal heat treatment parameters decreases the cost and operation time and results in higher finish quality and better device performance. This study investigates the influence of heat treatment parameters on microstructure and metallurgical properties of NiTi shape memory alloys to find the optimum values for post-processing. The samples were cut in equally sized dimensions, and they were treated using the same equipment. Various ranges of heating duration and temperature were considered for the experiments. It was revealed that, regardless of parameters, the heat treatment process can bring about better compositional characteristics and hardness properties of NiTi. However, some particular sets of heat treatment parameters resulted in higher quality and more favorable final properties.

Carbon fiber reinforced plastic (CFRP) has been generally chosen in the areas where weight reduction is important, for instance, sports goods and aerospace. For safe operation of the system using CFRP, we have to assess the damage state and predict the remaining service life accurately, which is one of the critical issues to keep the reliability in CFRP applications. Recently, multi-functional CFRP, especially embedded with piezoelectric or magnetostrictive materials, has been explored to realize lightweight battery-free sensors for structural health monitoring (SHM). In present study, the hybrid CFRP embedded with magnetostrictive Fe-Co fibers was developed, and the effect of composite design parameters (e.g. diameter of the fibers, location of the layers, bias magnetic field) on the inverse magnetostrictive response characteristic was also investigated. Mechanical cyclic bending tests showed that the fluctuation of magnetic flux density was measured resulting from the flexural deformation of our hybrid CFRP. Moreover, the measured magnetic flux density changed drastically when the CFRP was damaged, which implies that our hybrid CFRP has damage self-sensing ability. It seems that we should experimentally and numerically design and investigate the hybrid CFRP with magnetostrictive Fe-Co fibers in order to improve the capability as sensor composite materials. Accordingly, this study must make contribution to feasibility of lightweight, buttery-free, high performance stress sensors for SHM.

Magnetostrictive materials have attracted attention as materials for energy harvesting such as vibration power generation for Internet of Things (IoT). Fe-Co alloys have been focused on since the alloys have remarkable magnetic and mechanical properties. In this work, we evaluated the effect of heat treatment on the magnetic and magnetostrictive properties of rolled Fe-Co magnetostrictive films with Cr and Mo addition as bcc stabilizing elements to clarify. It was shown that the coercivity and the residual magnetism of the annealed specimens increase with the increase of the additive element quantity. This result indicates an increase in the amount of vibration power generation due to the Villari effect.

By providing a fast and accurate constitutive model suitable for use in finite element analysis, a key barrier inhibiting the development of magnetostrictive technologies will be lowered. A magnetostrictive constitutive model must calculate the nonlinear magnetization and magnetostriction of a material in response to magnetic and mechanical loads. This presentation will analyze the accuracy and computational complexity of three different integration methods performing these calculations: Riemann sums, Clenshaw-Curtis (CCQ) quadrature, and Laplace’s Method. We will show how using Laplace’s method provides an accurate and computationally efficient calculation of nonlinear magnetization, magnetostriction, and material properties for use in a FEA program.

In order to improve the energy dissipation capacity and self-centering capacity of the frame structure, a functional self-centering beam-column joint based on superelastic SMA bar was proposed. In this paper, based on OpenSees finite element software platform, the finite element numerical model of self-centering SMA reinforced concrete beam-column joints was established by using SMA material self-centering double flag constitutive model, and the finite element simulation under low-cycle reciprocating action was carried out to obtain the hysteretic curve and skeleton curve of the joints. The validity of the joints analysis model is verified by comparing with the existing experimental results. The parameter analysis was carried out, and the parameters such as the quantity, length and yield strength of SMA material were considered respectively. The influence of SMA material parameters on the hysteretic performance and self-centering ability of the joints was analyzed. The results show that the superelastic SMA reinforced concrete beam-column joints have high energy dissipation capacity and self-centering capacity. The numerical analysis model can well simulate the hysteretic behavior of self-centering SMA joints under low cyclic reciprocating loads. The mechanical parameters of SMA bars have a great influence on the seismic performance of joints: under the condition of proper reinforcement, the larger the number of SMA configurations, the smaller the residual displacement and the stronger the centering capacity. Under the same condition, after the SMA bar exceeds the plastic hinge length, it has little effect on the joint performance. Under the condition of proper reinforcement, increasing the yield strength of SMA will improve the bearing capacity and selfcentering capacity of the joints.

Shape Memory Alloys (SMAs) constitute a class of materials that are distinguished by their highly non-linear, thermo-mechanically coupled behaviour which is related with the phenomena accompanying the diffusion-less, solid-state phase transformation. This transition from the parent phase of Austenite to the product phase of Martensite and vice versa is also bound with the uncommon characteristic of “memory” exhibited when the material undergoes variable thermo-mechanical loadings. When a transformation reversal takes place, the material seems to inherently remember its state and adapts its future response in order to form closed paths, strongly dependent on the induced transformation history. Furthermore, another characteristic trait of SMAs is the asymmetry of their response when under tension or compression. During mixed loading states, such as bending of a beam, the evolution of transformation is observed to be different based on the sign of the load. The aforementioned peculiarities significantly affect the implementation SMAs in the design and realization of smart engineering structures intended for use in a wide range of fields that include but are not limited to aerospace, biomedical, wind energy, civil and automotive. To this end, efficient constitutive modeling of the phenomena related to the phase transformation is essential and of high importance in order to predict the complex performance of these materials. In this paper, emphasis is placed upon the investigation of the combined effect of tension-compression asymmetry and partial transformation on the response of SMA beams subjected to threepoint bending loading conditions. In this context, modeling of tension-compression asymmetry is investigated by using a set of different phase transformation functions based on the principles of computational plasticity, while a modified hardening function is considered to account for partial transformation behaviour. The produced numerical results are compared with respective cases that omit these phenomena in order to quantify their effect in terms of the developed stresses, material state and production/recovery of transformation strain.

The development of sustainable, cost-effective, efficient water collection materials and methods for continuous freshwater production is crucial for many regions especially in arid and semiarid regions of the world. The world population growth, urbanization, depleting water resources, and global climate change have intensified this crisis. The concern is drastically increasing and therefore scientists and engineers are challenged with urgently developing viable solutions for this problem. Also, the production of different plastic wastes is increasing day-by-day, and therefore, a growing concern to the serious environmental challenges. These wastes are rarely dissolved by microorganisms, and hence, the recycling of these plastic wastes into value-added materials could be a sustainable solution to addressing environmental issues. In this work, recycled expanded polystyrene (REPS) foam with various proportions of titanium dioxide (TiO₂) nanoparticles and aluminum (Al) microparticles were spun into superhydrophobic nanocomposite fibers using electrospinning technique and used for harvesting fog from the atmosphere. The fiber morphology, surface hydrophobicity, and fog harvesting capacity of the nanocomposite fibers were investigated. Test results reveal that the as-prepared nanocomposite fibers exhibit superhydrophobic characteristics with a water contact angle of 152.03° and an efficient fog harvesting capacity of 561 mg/cm² /hr. The nanotechnology-based collection systems are unique because of the fine structures of the nanomembranes. Thus, the electrospun superhydrophobic nanocomposite fibers from REPS have various industrial applications including water collection, water filtration, tissue engineering, and composites, etc and the produced water can be used for drinking, agriculture, industrial, and other purposes.

Selective laser melting (SLM) technique is a widely adopted fabrication procedure in metal additive manufacturing. One of the reasons for the extensive usage of SLM is the material freedom which it offers; therefore, Nickel alloy IN718 metal components were fabricated for this study. However, like in any manufacturing process, physical defects are evident in SLM fabricated parts. The origin of these defects can be attributed to the variation in the process parameters. For any physical components fabricated using the SLM technique, various stresses are developed due to the thermal gradients during the fabrication process. The developed stresses are hence termed as residual stresses. These stresses can be detrimental to the mechanical properties of the part. Residual stresses lead to warping of the part during the fabrication process, thereby leading to failure of the component. Therefore, it is necessary to investigate the effect of change in process parameters on the residual stresses. Although each process parameter has its effect on the overall properties and residual stresses, to limit the scope of the study, the scan strategy is the only parameter that is varied. Scan strategies adopted here are checkered, stripes scan strategy, FO1, and customized scan strategy, where the angle between the consecutive layers has been changed consistently at an angle of 67° . In this study, the residual stresses are measured using the contour deflection method. Based on the results, various levels of residual stresses were observed for different scan strategies. It was concluded that a more uniform scan strategy results in less residual stress.

Selective laser melting (SLM) is an additive manufacturing technique designed to use a high power-density laser to melt and fuse metallic powder to fabricate complex parts with high accuracy. The accuracy and the functional properties of the fabricated part are greatly dependent on the process parameters. Thus, depending on the desired properties and the material, the parameters need to be optimized before fabrication. The processing parameters that control the SLM process comprise of the laser power, scan speed, hatch spacing, layer thickness and scan strategy. These process parameters are dependent on each other and therefore make the task of optimizing the process parameters an important one. This research is concerned with the optimization of several process parameters as well as the development of a model to predict the best properties for Inconel 718 superalloy. This study uses the Design of Experiment (DOE) system coupled with the full factorial Composite Central Design (CCD) of the Response Surface Methodology (RSM) to perform the regression analysis on laser power, scanning speed, and hatch spacing in order to predict the CAD model deviation, hardness values, and, variation in the phase composition using X-ray Diffraction (XRD). The simulated models obtained using the RSM technique were then analyzed. These results provided valuable information and helped us in controlling the functional properties of the fabricated part.

The introduction and development of additive manufacturing (AM) has led to rapid rise in the innovative design and fabrication of lightweight metallic porous structures. This fabrication technique removes the difficulties presented by conventionally manufactured porous structures. Characteristics of conventionally manufactured porous include simple shapes and high cost because of its complicated manufacturing processes such as roll forming, brazing, and resistance welding. Porous structures with different levels of porosity offer customized mechanical properties, reduction in weight, and material quantity while improving functionality and hence can fulfill the demand for lightweight structures compared to a solid structure. Typically, the structures have high equivalent stiffness, strength, energy absorption, and heat dissipation. This concept is applied in various fields like medical and aerospace for its lightweight property. In this project, CAD models are developed with different porous structures, including BCC, BCC-Z, FCC, FCC-Z, Gyroid, Schwartz, and Diamond. The parts are then fabricated on an EOS M290 metal printer using Inconel 718 powder material. Detailed microstructure and mechanical characterization were carried out in order to obtain an in-depth understanding of the cellular parts with same level of porosity, but different porous structure. This study provides an insight on how to effectively choose the porosity type in a way to maximize the functionality of cellular structures for a specific application.

Additive manufacturing is a modern manufacturing technique that provides extreme design freedom and ability to manufacture multiple parts with high complexities at the same time. Various fabrication techniques have been developed and this study focuses on selective laser melting (SLM) due to its ability to provide near-perfect complex parts at low cost, while being able to work with a wide range of materials. In SLM, the part is manufactured layer-by-layer, by melting and solidification of powder material under controlled inert conditions. The fabrication of complex geometries is not possible without proper allocation of support structures for the part, which keeps the component intact and retains structural stability while manufacturing. Supports are attached to the part and are to be removed after fabrication in such a way that the required surface finish is not compromised. The challenge is to provide appropriate support structures after analyzing the part and the part orientation while ameliorating the functionality of removability, reducing material consumption, and enhancing structural support. Inconel 718 is a type of high-strength corrosion resistant super alloy, which consists of nickel and chromium. It can withstand extremely high pressure and heat which makes it suitable for high-end applications such as aerospace and petroleum. This study focuses on the surface topography for Inconel 718 parts after the removal of various support structures. A comprehensive report on optimal support structure design is provided after studying the fundamental parameters from design, fabrication, and testing phases. Varying the support structure design resulted in a range of surface qualities.

Metal-graphene nano-composites with low volume/weight fractions of graphene inclusions exhibit significantly high mechanical strength and hardness. However, manufacturing of metal-graphene nano-composites for high strength, hardness, and elastic properties is in its infancy stage. Enhancing mechanical strength of materials has been of great interest worldwide by introducing secondary phase reinforcement particles into the metal structure. Researchers across the world have applied this method to improve the mechanical properties of the composite, such as elastic modulus, tensile strength, compression strength, bending strength, toughness, and hardness. A highly desirable output was achieved by the above research effort, although the development of cost-ffective manufacturing techniques of metal composites is still an unsolved problem. In this study, we focus on searching new reinforcing materials as “nano-fillers” in composites of vital importance. To improve the role of nano-fillers as new reinforcing particles, some of the key features must be considered during the manufacturing process to further improve the mechanical strength of the material. These include surface and high aspect ratio, strong binding property with metal matrix after inclusion, and homogeneous dispersion of reinforcing particles in the matrix to further avoid agglomeration. The whole process should also be cost effective. With the above approach, many types of reinforcing nano-inclusions, such as ceramic nanoparticles, nano-fibers, metallic nanoparticles and carbon nanotubes have been highly exploited in effective materials engineering. This application of nanotechnology in manufacturing of improved metal composites with high mechanical properties is the subject of interest of this paper, which mainly needs intense research focus and has scope for further advancements in materials engineering. With the approach, ceramic nanoparticles, nanofibers, metallic nanoparticles and carbon nanotubes have been effectively exploited as reinforcing nanoscale inclusions. It was concluded that the strengthening effect of graphene reinforcement in the metal-graphene composites is much more significant than the combined effects of the nano-layered structure. Thus, the latest and very effective method to manufacture metallic materials with high strength, hardness, and Young’s modulus is to implant graphene platelets and sheets of a few layers in metallic matrices.