Smart 4D-printed implants and instruments

2020 ◽  
Vol 6 (3) ◽  
pp. 209-212
Author(s):  
Michael de Wild ◽  
Sebastian Dany ◽  
Christoph John ◽  
Felix Schuler
Keyword(s):  
Mechanical Properties ◽  
Shape Memory ◽  
Process Parameters ◽  
Surgical Instruments ◽  
Phase Transformation Temperature ◽  
Niti Shape Memory Alloy ◽  
Laser Exposure ◽  
Niti Phase ◽  
3D Printed ◽  
Spatio Temporal

AbstractSelective laser melting (SLM) was used to manufacture smart programmed structures with customized properties made of biocompatible NiTi shape-memory alloy. A series of helixes was produced with systematically varied SLM process parameters Laser Exposure Time and Laser Power in order to specifically change the thermo-mechanical material properties of the 3D-structures. This innovation opens up the possibility to adjust the NiTi phase transformation temperature during the manufacturing process. This controllable property determines which of the two crystallographic phases martensite or austenite is present at a certain operating temperature and allows the mechanical properties to be adjusted: martensitic devices are soft and pseudo-plastic due to the shape-memory effect, whereas austenitic structures are pseudo-elastic. In a further step, the SLM process parameters were locally varied within 4Dprinted twin-helixes. As a result, the phases, respectively the mechanical properties of a single component were adjusted at different locations. The ratio of elastic to plastic deformation and the spring constant of the helix can be locally controlled. This allows, for example, the spatio-temporal programming of 3D-printed surgical instruments or implants that are stimuliresponsive.

Physical property of 3D-printed sinusoidal pattern using shape memory TPU filament

2020 ◽  
Vol 90 (21-22) ◽  
pp. 2399-2410 ◽  
Author(s):  
Shahbaj Kabir ◽  
Hyelim Kim ◽  
Sunhee Lee
Keyword(s):  
Mechanical Properties ◽  
Tensile Test ◽  
Shape Memory ◽  
Fused Deposition Modeling ◽  
Loss Modulus ◽  
Thermoplastic Polyurethane ◽  
Heating Process ◽  
Fused Deposition ◽  
3D Printed ◽  
Sinusoidal Pattern

This study has investigated the physical properties of 3D-printable shape memory thermoplastic polyurethane (SMTPU) filament and its 3D-printed sinusoidal pattern obtained by fused deposition modeling (FDM) technology. To investigate 3D filaments, thermoplastic polyurethane (TPU) and SMTPU filament were examined by conducting infrared spectroscopy, x-ray diffraction (XRD), dynamic mechanical thermal analysis (DMTA), differential scanning calorimetry (DSC) and a tensile test. Then, to examine the 3D-printed sinusoidal samples, a sinusoidal pattern was developed and 3D-printed. Those samples went through a three-step heating process: (a) untreated state; (b) 5 min heating at 70°C, cooling for 30 min at room temperature; and (c) a repeat of step 2. The results obtained by the three different heating processes of the 3D-printed sinusoidal samples were examined by XRD, DMTA, DSC and the tensile test to obtain the effect of heating or annealing on the structural and mechanical properties. The results show significant changes in structure, crystallinity and thermal and mechanical properties of SMTPU 3D-printed samples due to the heating steps. XRD showed the increase in crystallinity with heating. In DMTA, storage modulus, loss modulus and the tan σ peak position also changed for various heating steps. The DSC result showed that the Tg for different steps of the SMTPU 3D-printed sample remained almost the same at around 51°C. The tensile property of the TPU 3D-printed sinusoidal sample decreased in terms of both load and elongation with increased heating processes, while for the SMTPU 3D-printed sinusoidal sample, the load decreased but elongation increased about 2.5 times.

Modeling and Analysis of Compressive Properties of Porous NiTi Shape Memory Alloy Using Artificial Neural Network

2008 ◽  
Vol 41-42 ◽  
pp. 135-140 ◽  
Author(s):  
Qiang Li ◽  
Xu Dong Sun ◽  
Jing Yuan Yu ◽  
Zhi Gang Liu ◽  
Kai Duan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Thermal Explosion ◽  
Process Parameters ◽  
Niti Shape Memory Alloy ◽  
Compressive Properties ◽  
Porous Niti ◽  
Bp Model

Artificial neural network (ANN) is an intriguing data processing technique. Over the last decade, it was applied widely in the chemistry field, but there were few applications in the porous NiTi shape memory alloy (SMA). In this paper, 32 sets of samples from thermal explosion experiments were used to build a three-layer BP (back propagation) neural network model. According to the registered BP model, the effect of process parameters including heating rate ( ), green density ( ) and particle size of Ti ( d ) on compressive properties of reacted products including ultimate compressive strength ( v D σ ) and ultimate compressive strain (ε ) was analyzed. The predicted results agree with the actual data within reasonable experimental error, which shows that the BP model is a practically very useful tool in the properties analysis and process parameters design of the porous NiTi SMA prepared by thermal explosion method.

On effect of chemical-assisted mechanical blending of barium titanate and graphene in PVDF for 3D printing applications

2020 ◽  
pp. 089270572094537
Author(s):  
Ravinder Sharma ◽  
Rupinder Singh ◽  
Ajay Batish
Keyword(s):  
Mechanical Properties ◽  
Barium Titanate ◽  
3D Printing ◽  
Comparative Study ◽  
Process Parameters ◽  
Processing Temperature ◽  
Melt Mixing ◽  
Twin Screw ◽  
3D Printed ◽  
The Comparative Study

The polyvinylidene difluoride + barium titanate (BaTiO3) +graphene composite (PBGC) is one of the widely explored thermoplastic matrix due to its 4D capabilities. The number of studies has been reported on the process parameters of twin-screw extruder (TSE) setup (as mechanical blending technique) for the development of PBGC in 3D printing applications. But, hitherto, little has been reported on chemical-assisted mechanical blending (CAMB) as solution mixing and melt mixing technique combination for preparation of PBGC. In this work, for preparation of PBGC feedstock filaments, CAMB has been used. Also, the effect of process parameters of TSE on the mechanical, dimensional, morphological, and thermal properties of prepared filament of PBGC have been explored followed by 3D printing. Further, a comparative study has been reported for the properties of prepared filaments with mechanically blended composites. Similarly, the mechanical properties of 3D printed parts of chemically and mechanically blended composites have been compared. The results of tensile testing for CAMB of PBGC show that the filament prepared with 15% BaTiO3 is having maximum peak strength 43.00 MPa and break strength 38.73 MPa. The optical microphotographs of the extruded filaments revealed that the samples prepared at 180°C extruder temperature and 60 r/min screw speed have minimum porosity, as compared to filaments prepared at high extruder temperature. Further, the results of the comparative study revealed that the filaments of CAMB composites show better mechanical properties as compared to the filaments of mechanically mixed composites. However, the dimensional properties were almost similar in both cases. It was also found that the CAMB composites have better properties at low processing temperature, whereas mechanically blended composites show better results at a higher temperature. While comparing 3D printed parts, tensile strength of specimens fabricated from CAMB was more than the mechanically blended PBGC.

scholarly journals Mechanical Properties of NiTi Shape Memory Alloy Particle/Epoxy Composites

2006 ◽  
Vol 55 (2) ◽  
pp. 230-236 ◽  
Author(s):  
Run-Xin ZHANG ◽  
Qing-Qing NI ◽  
Toshiaki NATSUKI ◽  
Ken KURASHIKI ◽  
Masaharu IWAMOTO
Keyword(s):  
Mechanical Properties ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Epoxy Composites ◽  
Niti Shape Memory Alloy ◽  
Alloy Particle

Evaluating Fretting Wear on 3D-Printed α-, β-, γ- Additives Hybridized NiTi Shape Memory Alloy

2019 ◽  
Author(s):  
O. P. Bodunde ◽  
S. M. Gao ◽  
M. Qin ◽  
W. H. Liao
Keyword(s):  
Shape Memory ◽  
Wear Test ◽  
Xrd Analysis ◽  
Fretting Wear ◽  
Niti Shape Memory Alloy ◽  
Aerospace Applications ◽  
Niti Sma ◽  
Wear Mode ◽  
3D Printed ◽  
Niti Shape Memory Alloys

Abstract Nickel-Titanium (NiTi) shape memory alloys (SMAs) are a class of promising materials for bio-implant, transportation, and aerospace applications. These interesting applications of SMA are as a result of their ability to exhibit shape memory effect (SME) and super-elasticity (SE). SMAs, especially NiTi which has been proven to have good mechanical properties, are however limited by their operational fatigue as reported in the literature. In this paper, a near equiatomic NiTi SMA was hybridized with zirconium (Zr), molybdenum (Mo) and copper (Cu), which are available and economic viable α-, β-, γ- stabilizing additives suitable for NiTi SMAs. Each of Zr, Mo, Cu were hybridized separately with the bare near equiatomic NiTi SMA. The compositional requirements for each of the sub-hybrids (NiTi-α, NiTi-β, and NiTi-γ respectively) were experimentally determined to know the optimum composition which could indicate the presence of austenitic and martensitic phases. Scan electron microscopy (SEM) was performed on each of the hybridizing additives as well as the bare equiatomic NiTi to determine their particle sizes and investigate their compatibility (between 30 and 40 microns) with the 3D printer used in the study. X-ray diffractometric (XRD) analysis also was carried out on the bare SMA and its additives to determine the presence of B2 and B19’ peaks. Afterward, NiTi-α, NiTi-β, and NiTi-γ were 3D printed to produce fretting wear test specimens and finally, the fretting wear behaviors of the NiTi hybrids were studied in detail with the objective of testing their performances under fretting wear mode as it may be required for an application. A tungsten carbide counter-body was used. The results from the characterization through XRD indicated that all of α-, β-, γ- stabilizing additives with NiTi respectively showed the presence of B2 and B19’ in the inter-metallic phases. Details of wear microstructure were reported and its information could be useful for professionals who require hybridized NiTi alloys for various engineering applications.

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