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Nickel–titanium (NiTi) alloys have recently attracted considerable attention due to their unique properties, i.e., shape memory effect and superelasticity. In addition, these promising alloys demonstrate unique biocompatibility, represented in their high stability and corrosion resistance in aqueous environments, qualifying them to be used inside the human body. In recent years, additive manufacturing (AM) processes have been envisioned as an enabling method for the efficient production of NiTi components with complex geometries as patient-specific implants. In spite of its great capabilities, AM as a novel fabrication process may reduce the corrosion resistance of NiTi parts leading to the excess release of the harmful Ni ions as the main corrosion byproducts. The main goal of this study is to create and evaluate a micro-arc oxidation (MAO) coating in order to enhance the corrosion resistance of additively manufacture NiTi medical devices. To this end, the process voltage and electrolyte used to produce MAO coating have been investigated and optimized. The corrosion characteristics of the MAO-coated specimens revealed that the proposed coating methodology significantly improves the corrosion resistance of NiTi parts produced using AM process.

Shape memory alloys (SMAs), such as Nitinol (i.e., NiTi), are of great importance in biomedical and engineering applications due to their unique superelasticity and shape memory properties. In recent years, additive manufacturing (AM) processes have been used to produce complex NiTi components, which provide the ability to tailor microstructure and thus the critical properties of the alloys, such as the superelastic behavior and transformation temperatures (TTs), by selection of processing parameters. In biomedical applications, superelasticity in implants play a critical role since it gives the implants bone-like behavior. In this study, a methodology of improving superelasticity in Ni-rich NiTi components without the need for any kind of post-process heat treatments will be revealed. It will be shown that superelasticity with 5.62% strain recovery and 98% recovery ratio can be observed in Ni-rich NiTi after the sample is processed with 250 W laser power, 1250 mm/s scanning speed, and 80 µm hatch spacing without, any post-process heat treatments. This superelasticity in as-fabricated Ni-rich SLM NiTi was not previously possible in the absence of post-process heat treatments. The findings of this study promise the fast, reliable and inexpensive fabrication of complex shaped superelastic NiTi components for many envisioned applications such as patient-specific biomedical implants.

Inconel 718 (IN718) is a nickel-based superalloy which is widely used in aerospace, oil, and gas industries due to its outstanding mechanical properties at high temperatures, corrosion, fatigue resistance, and excellent weldability. Selective laser melting (SLM), one of the most used powder-bed based methods, is being extensively used to fabricate functional IN718 components with high accuracy. The accuracy and the properties of the SLM fabricated IN718 parts highly depend on the process parameters employed during fabrication. Thus, depending on the desired properties, the process parameters for a given material need to be optimized for improving the overall reliability of the SLM devices. In this study, design of experiment (DOE) was used to evaluate the dimensional accuracy, composition, and hardness corresponding to the interaction between the SLM process parameters such as laser power (P), scan speed (v), and hatch spacing (h). Contour plots were generated by co-relating the determined values for each characteristic and the process parameters to improve the as-built characteristics of the fabricated IN718 parts and reduce the post-processing time. The outcome of this study shows a range of energy density values for the IN718 superalloy needed to attain optimal values for each of the analyzed characteristics. Finally, an optimal processing region for SLM IN718 fabrication was identified which is in accordance with the values for each characteristic mentioned in literature.

Shape memory alloys (SMAs) have found widespread applications as biomedical devices. Biocompatibility, corrosion resistance, and ductility make these alloys attractive for medical devices such as stents and filters. For these implants, the superelastic property is the primary function of SMAs. Additionally, these alloys, such as NiTi as the prime example, can be used for actuation. Several modes of actuation such as displacement control, force control, and compliance control have been used as harnesses with SMA devices. These two unique properties have opened another application in the form of neurosurgery and robot-assisted surgery devices, as well as controlled assistive and rehabilitation devices. This paper reviews the state of the art of application of SMAs in the latter category where control is applied to harness innovative medical devices. To this end, two major subsets of these devices: prosthesis and orthosis which take the advantage of SMAs in assistive and rehabilitation devices are studied. These devices are further categorized to hand prosthetics, elbow, knee and ankle orthotics. In most of these designs, SMA wires act as artificial muscles to mimic the motion of limbs in the target joints. The evolution of each category is explained, and the specific results of them are reported. The paper also reviews the SMA applications for neurological and neuromuscular rehabilitation. To this end, different categories of rehabilitation devices as a passive and aided exercise for the ankle, knee, and elbow are highlighted. The SMA actuator in these devices can be EMG-controlled to improved patient outcome. In addition to providing a comprehensive overview of the biomedical devices, this paper identifies several possible future directions of SMA related research in the area of assistive and rehabilitation devices.

NiTi alloys possess distinct functional properties (i.e., shape memory effect and superelasticity) and biocompatibility, making them appealing for bone fixation applications. Additive manufacturing offers an alternative method for fabricating NiTi parts, which are known to be very difficult to machine using conventional manufacturing methods. However, poor surface quality, and the presence of impurities and defects, are some of the major concerns associated with NiTi structures manufactured using additive manufacturing. The aim of this study is to assess the in vitro corrosion properties of additively manufactured NiTi structures. NiTi samples (bulk and porous) were produced using selective laser melting (SLM), and their electrochemical corrosion characteristics and Ni ion release levels were measured and compared with conventionally fabricated NiTi parts. The additively manufactured NiTi structures were found to have electrochemical corrosion characteristics similar to those found for the conventionally fabricated NiTi alloy samples. The highest Ni ion release level was found in the case of 50% porous structures, which can be attributed to their significantly higher exposed surface area. However, the Ni ion release levels reported in this work for all the fabricated structures remain within the range of most of values for conventionally fabricated NiTi alloys reported in the literature. The results of this study suggest that the proposed SLM fabrication process does not result in a significant deterioration in the corrosion resistance of NiTi parts, making them suitable for bone fixation applications.

Inconel 718 is a nickel-based superalloy and an excellent candidate for the aerospace, oil, and gas industries due to its high strength and corrosion resistance properties. The machining of IN718 is very challenging; therefore, the application of additive manufacturing (AM) technology is an effective approach to overcoming these difficulties and for the fabrication of complex geometries that cannot be manufactured by the traditional techniques. Selective laser melting (SLM), which is a laser powder bed fusion method, can be applied for the fabrication of IN718 samples with high accuracy. However, the process parameters have a high impact on the properties of the manufactured samples. In this study, a prediction model is developed for obtaining the optimal process parameters, including laser power, hatch spacing, and scanning speed, in the SLM process of the IN718 alloy. For this purpose, artificial neural network (ANN) modeling with various algorithms is employed to estimate the process outputs, namely, sample height and surface hardness. The modeling results fit perfectly with the experimental output, and this consequently proves the benefit of ANN modeling for predicting the optimal process parameters.

Ti-6Al-4V with its eclectic array of excellent properties along with the combination of meticulous precision and flexibility offered by the laser powder bed fusion (LPBF) technology makes it a strong proponent in the field of engineering applications. As a substantial amount of research has paved the way to fabricate Ti-6AL-4V more effectively and efficiently, researchers are becoming more adventurous in finding out the optimal techniques to get better yields in terms of mechanical responses. This includes post-processing techniques i.e., heat treatment (HT) or introducing various alloying elements. Nevertheless, these techniques not only make the overall fabrication more expensive and time-consuming but also contradict the simplistic notion of additive manufacturing (AM) by imparting multistage fabrication without a considerable improvement overall. Here, we propose an innovative breakthrough in the field of Ti-6AL-4V fabrication with LPBF by introducing an in-situ approach to tackle the handicap mentioned in contemporary studies. By imparting multiple laser scans prior to and after the melting scan at each layer, a remarkable 37% improvement in yield strength (YS) can be achieved with higher elongation, while also maintaining a high relative density of around 99.99%.

Process parameters and post-processing heat treatment techniques have been developed to produce both shape memory and superelastic NiTi using Additive Manufacturing. By introducing engineered porosity, the stiffness of NiTi can be tuned to the level closely matching cortical bone. Using additively manufactured porous superelastic NiTi, we have proposed the use of patient-specific, stiffness-matched fixation hardware, for mandible skeletal reconstructive surgery. Currently, Ti-6Al-4V is the most commonly used material for skeletal fixation devices. Although this material offers more than sufficient strength for immobilization during the bone healing process, the high stiffness of Ti-6Al-4V implants can cause stress shielding. In this paper, we present a study of mandibular reconstruction that uses a dry cadaver mandible to validate our geometric and biomechanical design and fabrication (i.e., 3D printing) of NiTi skeletal fixation hardware. Based on the reference-dried mandible, we have developed a Finite Element model to evaluate the performance of the proposed fixation. Our results show a closer-to-normal stress distribution and an enhanced contact pressure at the bone graft interface than would be in the case with Ti-6Al-4V off-the-shelf fixation hardware. The porous fixation plates used in this study were fabricated by selective laser melting.

Hinge-based Ankle Foot Orthosis (HAFO) is one of the most common non-surgical solutions for the foot drop. In conventional HAFOs, the ankle joint is almost locked, and plantar flexion is restricted due to the high stiffness of the hinge mechanism. This often leads to a rigid walking gate cycle, poor muscle activity, and muscle atrophy. Since the ankle torque-angle loop has a non-linear profile, the use of a superelastic NiTi spring within the hinge, due to its nonlinear behavior, could recreate a close-to-normal stiffness of the normal ankle joint, which, in turn, could create a more natural walk. The focus of this study is to evaluate the performance of a superelastic NiTi spring versus a conventional Stainless Steel spring in a hinge mechanism of a custom-fit HAFO. To this aim, a custom-fit HAFO was fabricated via the fast casting technique. Then, motion analysis was performed for two healthy subjects (Case I and Case II): (i) subjects with bare foot; (ii) subjects wearing a conventional HAFO with no spring; (iii) subjects wearing a conventional Stainless Steel-based HAFO; and (iv) subjects wearing a NiTi spring-based HAFO. The data related to the ankle angle and the amount of moment applied to the ankle during walking were recorded using Cortex software and used for the evaluations. Finally, Finite Element Analysis (FEA) was performed to evaluate the safety of the designed HAFO. The NiTi spring offers a higher range of motion (7.9 versus 4.14 degree) and an increased level of moment (0.55 versus 0.36 N·m/kg). Furthermore, a NiTi spring offers an ankle torque-angle loop closer to that of the healthy subjects.

Magnesium (Mg) and its alloys can degrade gradually up to complete dissolution in the physiological environment. This property makes these biomaterials appealing for different biomedical applications, such as bone implants. In order to qualify Mg and its alloys for bone implant applications, there is a need to precisely model their degradation (corrosion) behavior in the physiological environment. Therefore, the primary objective develop a model that can be used to predict the corrosion behavior of Mg-based alloys in vitro, while capturing the effect of pitting corrosion. To this end, a customized FORTRAN user material subroutine (or VUMAT) that is compatible with the finite element (FE) solver Abaqus/Explicit (Dassault Systèmes, Waltham, MA, USA) was developed. Using the developed subroutine, a continuum damage mechanism (CDM) FE model was developed to phenomenologically estimate the corrosion rate of a biocompatible Mg–Zn–Ca alloy. In addition, the mass loss immersion test was conducted to measure mass loss over time by submerging Mg–Zn–Ca coupons in a glass reactor filled with simulated body fluid (SBF) solution at pH 7.4 and 37 °C. Then, response surface methodology (RSM) was applied to calibrate the corrosion FE model parameters (i.e., Gamma (γ), Psi (ψ), Beta (β), and kinetic parameter (Ku)). The optimum values for γ, ψ, β and Ku were found to be 2.74898, 2.60477, 5.1, and 0.1005, respectively. Finally, given the good fit between FE predictions and experimental data, it was concluded that the numerical framework precisely captures the effect of corrosion on the mass loss over time.