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14 Challenges andPerspective ofManufacturing Techniques inBiomedical Applications
The two most widely used AM techniques for metals are: drop-on-powder depo­sition methods, such as selective laser melting/sintering (SLM/SLS), electron beam melting (EBM) and continuous deposition methods, like fused deposition modeling (FDM). AM makes it convenient by offering near-net shape components, reducing post-processing steps and minimal wastage of material.
Usually, most metallic implants undergo multiple post-processing processes, such as cleaning, coating, thin lm deposition, heat treatment, and surface treat­ments, to achieve increased mechanical properties and/or biocompatibility [16].
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14.2.1 Powder Bed Fusion (PBF)

PBF encompasses laser- and electron-beam-based techniques for building 3D metal parts by selectively melting ne powders, following a digital blueprint, layer by layer [17]. While ber lasers with powers up to 1kW are common, the process typi­cally involves spreading a fresh layer of powder (15–150μm) onto the platform, melting it with the laser beam, and lowering the platform for the next layer [18]. This method boasts notable advantages like superior grain renement, enhanced chemical homogeneity, and reduced phase segregation. However, challenges lie in controlling melt pool stability to avoid unpredictable microstructures [19]. Manufacturers can achieve controlled microstructures and produce high-quality medical devices with optimal performance by ne-tuning process parameters like spacing, laser power, and scan speed [18].

14.2.2 Directed Energy Deposition

Laser Metal Deposition (LMD) is a versatile additive manufacturing (AM) tech­nique that injects ne metal powder into a focused laser beam, melting it into a small pool on the target surface. Complex geometries can be built layer-by-layer by moving the workpiece under the beam, creating entirely new parts, adding struc­tures to existing ones, or even repairing damaged components. While powder ow, speed, and laser power signicantly inuence the nal properties like deposition height, width, surface nish, and mechanics, LMD’s true strength lies in its ability to build intricate objects having graded composition or porosity, even using diverse biomaterials like shape memory alloys, stainless steel, and titanium [20]. Despite the challenge of maintaining consistent layer thickness (typically 0.3–1 mm), LMD’s potential to create customized, high-performance parts from various materi­als makes it a powerful tool in diverse elds.
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14.2.3 Design ofMetallic Biomaterials
AM technologies are revolutionizing biomedical implant production by enabling the creation of graded and porous surface constructs with precisely designed unit cells. This innovation’s appeal lies in its capacity to enhance osseointegration and cell proliferation while tailoring mechanical properties like elastic modulus and compressive strength to match native bone, thereby preventing stress-shielding issues after implantation. To effectively mirror the mechanical properties and dynamic characteristics of cortical and trabecular bone (which differ in organic/ inorganic material proportions and porosity) within a single implant, precise pore size and distribution design are crucial. Additionally, the organization and integra­tion of these bone types are highly dependent on both the skeletal region and the specic mechanical loading experienced.
Although porous titanium implants offer exciting possibilities for patient- tailored biomedical applications, research reveals that pore size, volume, and pore shape signicantly impact cell behavior. Studies categorize cellular structures into random “stochastic” structures and ordered “nonstochastic” lattices. Notably, nonstochastic geometries hold signicant advantages with their well-dened pore shapes and sizes. Such predictable designs boast superior mechanical properties and facilitate cleaner removal of leftover powder during fabrication via powder bed technologies, a clear advantage over their stochastic counterparts like metal foams. Controlling pore shape within a dened geometric framework unlocks improved cell responses and optimized manufacturing processes, paving the way for even more effective personalized implants.
A study investigated the impact of nonstochastic pore architecture in SLM­produced Ti-6Al-4V scaffolds on various aspects, including mechanical properties, cell attachment, and in vitro biological outcomes [21]. Interestingly, pore shape signicantly inuenced cell permeability, thereby affecting cell attachment, with circular pores promoting the highest attachment despite being independent of pore size. This phenomenon was attributed to differences in pore occlusion, with hexago­nal pores exhibiting greater blockage than triangular or rectangular ones.
Researchers successfully utilized nite element analysis (FEA) to design and fabricate titanium hip implants via electron beam melting (EBM), minimizing stress shielding on the surrounding bone while maintaining the implant’s strength [22]. They achieved this by replacing solid stems with customized periodic lattice struc­tures, demonstrating the feasibility of constructing nonstochastic lattices with EBM. However, they emphasized the importance of controlling strut orientation during fabrication to match the simulated model. Discrepancies between the smooth, constant-section struts in the FEA model and the textured, slightly varying struts in the actual implants necessitated the use of safety factors in the design. Despite these challenges, their study concluded that the Ti-6Al-4V stem with a mesh lattice achieved the optimal stress distribution in the femur’s proximal region among the tested congurations, offering a promising avenue for future implant design.
14 Challenges andPerspective ofManufacturing Techniques inBiomedical Applications
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14.3 Manufacturing ofPolymeric andComposite Materials
The advancements in polymer technology for additive manufacturing are signi­cantly impacting materials science and technology. The creation of this polymer­based equipment can be utilized in for human tissue failure problems. AM library of polymeric materials has grown over time to maximize its uses in the biomedical eld. The production of biocompatible polymers for SLA has advanced signi­cantly, potentially replacing traditional lithographic acrylic resins that may have harmful effects. Conversely, the results of the in vivo placement of polymeric devices produced using fused deposition modeling (FDM) or surface laser sintering (SLS) encouraged further research toward their permanent integration into standard interventional surgery procedures. The polymer components obtained naturally have certain innate bioactive and biomimetic qualities to create production methods that are more environmentally sustainable. Moreover, solution-based AM is the pre­ferred method for functionalizing materials with bioactive substances. This is seen in the case of hydrogels with regulated porosity and an exterior form that encapsu­lates growth factors or cells, and in the polymeric matrix, they are endowed with nano- or microporosity. Additionally, much work has gone into creating composite implants to improve mechanical characteristics and bioactivity [3845]. AM is also used in bone implant device fabrication. Generally, bioresorbable polymers have many advantages over metallic implants [4656].

14.3.1 Extrusion-Based AM

The material extrusion (ME) process selectively dispenses the contents from a noz­zle tip across a moveable stage. A polymer composition that can bind together at a temperature (without degradation) can potentially be utilized in ME.A steady noz­zle speed and pressure would result in a constant cross-sectional diameter for the material deposited. When a layer is nished, the printhead advances by a stepsize (usually by 100–300μm) to allow for the creation of the subsequent layer on top of the old one. Typical extrusion-based phases are as follows: [1]: (1–2) lling of the polymer components; (3) applying pressure to push the printing components; (4) extrusion; (5) deposition of layers on a predened CAD model; (6) joining of the component parts to create a cohesive, solid framework [23]. FDM possesses a num­ber of benets, such as the elimination of the need for post-processing steps, as well as the inexpensive nature of supplies, which makes the process economical, fast, user-friendly, and broadly accessible [24].
Nevertheless, there are drawbacks associated with it, such as reduced resolution, low printing speed, and anisotropy of the printed structures. Additionally, FDM has certain restrictions regarding the geometric complexity and compatibility with materials [24]. The volumetric ow rate, material viscosity, feed deposition, and heat transfer are experimental parameters that determine the printed part’s accuracy.
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The newly extruded lament could expand after extrusion and must be combined with the existing structures. Lastly, the cooling effects will probably cause the printed object to deform during or after printing.
The most often utilized polymers are amorphous thermoplastics, such as acrylo­nitrile butadiene styrene (ABS) and polylactic acid (PLA). PLA, a plastic made from cornstarch, has a comparatively low melting point (between 150 and 160°C) and requires limited energy consumption compared to other substances. Moreover, ABS can be made by mechanically mixing styrene-acrylonitrile copolymer with butadiene or by grafting styrene and acrylonitrile onto polybutadiene at tempera­tures ranging from 176 to 260°C [25]. This makes it incredibly adaptable, allowing it to be adapted to various purposes.
14.3.2 Stereolithography andDLP (Digital Light Processing)
Vat photopolymerization is a particular kind of additive manufacturing (AM) where a liquid, the photopolymer, is selectively and spatially restored in a vat by light­activated crosslinking. Chuck Hull pioneered using UV-curable materials in the mid-1980s, creating solid polymer patterns with a scanning laser. Intriguingly, he found that layer-by-layer curing could produce solid 3D components. In 1983, Hull co-founded 3D Systems Inc., securing a patent for the rst stereolithography (SLA) machine for commercial use, with the SLA-1 model hitting the market in 1987. This group includes several AM lithography methods, such as digital light processing (DLP), multiphoton polymerization (2PP), and SLA [26].
Using coherent light sources, the SLA technology causes a liquid resin to polym­erize and crosslink, typically UV-emitting lasers. The technique’s benets include great spatial resolution due to the concentrated laser beam’s spot size. SLA relies on a photopolymerization process, converting a liquid monomer/oligomer mixture into a solidied polymer through exposure to UV light. A platform stabilizes overhang­ing structures, descending after each layer for a fresh resin application. Post-curing is usually necessary after draining excess resin.
DLP also creates free-standing sculptures by selectively crosslinking a pho­toresin layer by layer using light. Unlike SLA, DLP exposes all layers simultane­ously, reducing the impact of oxygen inhibition. DLP accommodates slurries containing metal or ceramic particles and unlled photopolymers, creating inor­ganic and polymeric phase blends [27]. Commercial resins’ crosslinking density and mechanical properties, such as compressive yield strength and elastic modulus, are inuenced by light intensity [28].
Studies like Patel etal. highlight innovations in UV-curable elastomer systems for DLP-based AM, showcasing an enhanced ability to create pliable and exible three-dimensional constructions and gadgets. Mu etal.’s research explores conduc­tive structures made of photoresin and multi-walled carbon nanotubes (MWCNTs), showcasing their potential applications in capacitive sensors, electrically activated shape memory composites, and stretchable circuits [29]. Adjusting MWCNT
14 Challenges andPerspective ofManufacturing Techniques inBiomedical Applications
concentrations and printing parameters optimizes conductivity and printing quality, with minor effects on mechanical characteristics.
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14.4 AM ofNanocomposites
Several writers used nanoparticles (NPs) to create materials with better properties, such as microscale composites. Perez etal., for instance, investigated the impact of adding reinforcing nanoparticles on the fracture surface features and mechanical attributes of ABS [30]. Tensile test ndings showed that, compared to empty poly­mer segments, NPs reinforced ABS with 5-weight percent nano titanium dioxide (TiO2) showed a 13.2% improvement in tensile strength. When nanoparticles were introduced, however, all printed composite sections displayed decreased elongation and embrittlement.
Lastly, FDM printing has made equal use of CNTs and graphene, which are mixed into thermoplastic laments. In order to create novel conductive mixes, Rymansaib etal. synthesized graphite ake microparticles and carbon nanobers (CNFs), which were then mixed with PS [31]. With a well-dened active geometric surface area, the CNF/PCNF/graphite (10/80/10wt%) composites offer high con­ductivity and robust electrochemical contact. The printed electrodes are reusable upon polishing, have a robust interface to the PS shell, and exhibit acceptable signal­to- background voltametric responses. Similar investigations were conducted by Lewicki etal., who found that the alignment of the bers causes AM CNFs to dis­play extremely orthotropic mechanical and electrical responses.

14.5 Biomanufacturing

14.5.1 Tissue Engineering

Tissue engineering (TE) is a major application eld of additive manufacturing (AM) due to its stringent requirements for scaffold porosity, pore size, and anatomical structure, which are often unachievable through traditional fabrication methods. During tissue engineering (TE), a biodegradable scaffold with an interconnected porous structure is implanted. It may also include cells and bioactive chemicals. The scaffold is a temporary template that promotes cell adhesion and mechanical func­tion during tissue regeneration. Scaffold features such as porosity, chemistry, topog­raphy, and stiffness greatly inuence cell behavior and differentiation [32]. Customized additive manufacturing techniques improve the scaffold’s mechanical and biological qualities by providing exact control over scaffold composition and design at different sizes. Cutting-edge techniques like hybrid AM and μSLA enable sub-micrometer structural control to provide cells with nanometric cues [33].
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Computer-aided design and manufacturing development have made it possible to create scaffolds with customized porous structures that are clinically scaled and anatomically formed. Continuous progress in processing biomedical polymers and composites makes it possible to build tissues with various structural and functional properties, such as intricate solid organs and tubular structures, by customizing 3D scaffolds. Promising rst results have been observed in clinical applications, such as PCL devices manufactured by FDM for dental and craniofacial repair [34].
Y. O. Waidi et al.

14.5.2 Organ-on-a-Chip Models

The development of sophisticated invitro 3D models has been signicantly aided by the advancement of additive manufacturing (AM), which has made it possible to fabricate four essential components in a single continuous process: microuidic chips, live cells, or microtissues for culturing, stimulus loading components, and readout sensors. The construction of heterogeneous microenvironments that resem­ble genuine tissues is made possible by bioprinting’s capacity to accurately arrange various materials, including hydrogels, cells, growth factors, and bacteria, in sequential order with great spatial precision. Incorporating energy actuators (e.g., electrical and mechanical transducers) and sensors on chips allows for applying stimuli to cells and monitoring their activities, promoting the maturation and func­tionality of micronized organs. Some approaches integrate mechanical strain­inducing actuators, electrochemical sensors on the same chip, and complex uid handling modules. Alternatively, magnetic particles or memory-shape actuators can induce mechanical stimulation.

14.6 Conclusion

Different materials demand unique manufacturing processes for seamless integra­tion into biomedical products/devices. However, one commonality across all classes of materials is the increased adoption of additive manufacturing techniques in mak­ing customized parts. Design, being an integral part of the 3D printing process com­mands more focused research, especially in the inverse design workow, to make standardized techniques of rendering image les and 3D models from patient scan images. This can certainly increase the reach of 3D printing to the masses, as more clinicians will be trained in the process. Also, every 3D printing process has a printer resolution or dimensional constraint, depending on the feed material, limiting the printing accuracy and size. This can be overcome by carefully optimizing printing parameters that are unique to the feed material. Additionally, the emergence of 4D printing [35], which uses smart materials, such as shape memory alloys [9] and shape memory polymers [36], has further extended the capabilities of conventional 3D printing. This can now enable the fabrication of intricate and biomimetic
14 Challenges andPerspective ofManufacturing Techniques inBiomedical Applications
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structures [37] with dynamic capabilities to conform to tissues better and adapt over time. However, standardization of the fabrication of such stimuli-materials through 3D printing, control of design parameters, shape-changing efciency and rates is of paramount importance to leverage the full benets of these techniques in biomanufacturing.
Acknowledgments The authors would like to acknowledge Fig.14.1, which is adapted with per- mission from license Number 5723471318796 to the concerned press.

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Index

A
Additive manufacturing (AM), 183, 201, 203,
213, 254, 260, 261, 269, 287–295, 298, 412–414, 419, 434–442
Articular cartilage, 16, 17, 28–42, 44, 46, 48,
49, 52, 57, 58, 63, 65–67, 347–350, 381
Articial intelligence (AI), 213, 214,
297, 417–419
B
Biocompatibility, 2, 3, 43, 44, 46, 48, 58, 85,
92, 115–117, 119, 120, 128, 130–132, 135, 136, 139, 142, 177, 179, 185, 187, 190, 192, 201–203, 207–209, 211–214, 238, 241, 242, 253, 254, 259–262, 266–270, 273, 280, 282, 284, 293, 294, 297, 298, 315, 321, 328, 331, 337, 338, 346, 349, 365, 366, 368–370, 375–380,
383, 386–388, 412, 435 Biofabrication, 213 Bioinspiration, 8, 10, 115, 123, 203, 380 Biointerfaces, 2, 8, 9, 14, 15, 21, 246 Biomarkers, 81, 85, 95–97, 119, 154, 294 Biomaterials, 17, 48, 115, 168, 203, 265, 314,
337, 365, 435 Biomedical applications, 9, 44, 45, 116, 120,
122, 139, 154, 186, 200, 201, 203,
213–215, 252–298, 314–322, 328,
330, 334, 337, 338, 434–443 Biomedical devices, 130, 171, 173, 177, 178,
182, 184, 185, 188–192, 202–205,
207, 212–214, 260, 269, 274, 279, 285, 291, 292, 434
Biomedical systems, 171, 172, 174–176,
190, 191
Biomimetics, 3, 8, 10, 21, 30, 31, 115, 116,
123–127, 134, 136–138, 188, 192, 202, 203, 211, 218, 219, 223, 224, 227, 228, 265, 292, 293, 296, 314, 321, 379–381, 383, 419, 439, 442
Bio-tribology, 2–4, 8–10, 12–15, 21, 28–67,
92, 150, 177–178, 185–191, 218, 236, 238–245
C
Cell proliferation, 43, 125, 134, 137, 438 Contact lenses, 159, 170, 171, 224 Controlled releases, 42, 97, 119, 120, 124,
130, 253–255, 258–262, 265, 266, 269, 285, 287, 288, 293–296, 298, 332
D
Degradation, 40, 44, 48, 52, 54, 59, 97, 209,
218, 227, 260–262, 267, 269, 271–273, 276, 277, 280–282, 285–287, 290, 292, 294, 295, 331–333, 337, 338, 348, 362–366, 375, 379, 384, 385, 390, 403,
417, 439 Dental implants, 14, 237, 240, 241, 338 Device customization, 201
Springer Nature Switzerland AG 2024 A. Kumar et al. (eds.), Applications of Biotribology in Biomedical Systems,
https://doi.org/10.1007/978-3-031-58327-8
447© The Editor(s) (if applicable) and The Author(s), under exclusive license to
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