Advanced Manufacturing Techniques Research Articles

Machine learning-assisted discovery of flow reactor designs

AbstractAdditive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such spaces presents a significant challenge for current approaches. Furthermore, existing parameterizations of reactor geometries are low dimensional with expensive optimization, limiting more complex solutions. To address this challenge, we have established a machine learning-assisted approach for the design of new chemical reactors, combining the application of high-dimensional parameterizations, computational fluid dynamics and multi-fidelity Bayesian optimization. We associate the development of mixing-enhancing vortical flow structures in coiled reactors with performance and used our approach to identify the key characteristics of optimal designs. By appealing to the principles of fluid dynamics, we rationalized the selection of design features that lead to experimental plug flow performance improvements of ~60% compared with conventional designs. Our results demonstrate that coupling advanced manufacturing techniques with ‘augmented intelligence’ approaches can give rise to reactor designs with enhanced performance.

Ubiquitous short-range order in multi-principal element alloys

Recent research in multi-principal element alloys (MPEAs) has increasingly focused on the role of short-range order (SRO) on material performance. However, the mechanisms of SRO formation and its precise control remain elusive, limiting the progress of SRO engineering. Here, leveraging advanced additive manufacturing techniques that produce samples with a wide range of cooling rates (up to 107 K s−1) and an enhanced semi-quantitative electron microscopy method, we characterize SRO in three CoCrNi-based face-centered-cubic (FCC) MPEAs. Surprisingly, irrespective of the processing and thermal treatment history, all samples exhibit similar levels of SRO. Atomistic simulations reveal that during solidification, prevalent local chemical order arises in the liquid-solid interface (solidification front) even under the extreme cooling rate of 1011 K s−1. This phenomenon stems from the swift atomic diffusion in the supercooled liquid, which matches or even surpasses the rate of solidification. Therefore, SRO is an inherent characteristic of most FCC MPEAs, insensitive to variations in cooling rates and even annealing treatments typically available in experiments.

Advanced Manufacturing Techniques in Aerospace Engineering

A significant change in the design, production, and integration of aircraft systems and components has been brought about by advanced manufacturing techniques in aerospace engineering. These methods, which include a variety of cutting-edge procedures and technological advancements, are revolutionizing the aerospace sector by improving the effectiveness, dependability, and performance of airplanes and spacecraft. This article provides a thorough review of the influence of advanced manufacturing methods on the high-stakes area of aerospace engineering by delving into the fundamental definitions, evolution, importance, research gaps, and present significance of these techniques.

Use of Acellular Matrices as Scaffolds in Cartilage Regeneration: A Systematic Review.

Significance: Cartilage regeneration remains a significant challenge in the field of regenerative medicine. Acellular matrix (AM)-based cartilage tissue regeneration offers an innovative approach to repairing cartilage defects by providing a scaffold for new tissue growth. Its significance lies in its potential to restore joint function, mitigate pain, and improve the quality of life for patients suffering from cartilage-related injuries and conditions. Recent Advances: Recent advances in AM-based cartilage regeneration have focused on enhancing scaffold properties for improved cell adhesion, proliferation, and differentiation. Moreover, several scaffold techniques such as combining acellular dermal matrix (ADM) and acellular cartilage matrix (ACM) with cartilage tissue, as well as biphasic scaffolding, enjoy rising research activity. Incorporating bioactive factors and advanced manufacturing techniques holds promise for producing more biomimetic scaffolds, advancing efficient cartilage repair and regeneration. Critical Issues: Obstacles in AM-based cartilage regeneration include achieving proper integration with the surrounding tissue and ensuring long-term durability of the regenerated cartilage. Furthermore, issues such as high costs and limited availability of suitable cells for scaffold seeding must be considered. The heterogeneity and limited regenerative capabilities of cartilage need to be addressed for successful clinical translation. Future Directions: Research should focus on exploring advanced biomaterials and developing new techniques, regarding easily reproducible scaffolds, ideally constructed from clinically validated and readily available commercial products. Findings underline the potential of AM-based approaches, especially the rising exploration of tissue-derived ADM and ACM. In future, the primary objective should not only be the regeneration of small cartilage defects but rather focus on fully regenerating a joint or larger cartilage defect.

Output Enhancement of a 3D‐Printed Triboelectric Nanogenerator Using Laser Surface 3D Patterning

This study investigates the performance of contact separation and sliding modes of triboelectric Nanogenerators (TENGs) using COMSOL Multiphysics simulation environment. The output performance of a plain surface TENG is compared with square, rectangular, and pyramid‐patterned TENGs. The pyramid pattern emerges as the most efficient geometry, demonstrating a solid output of 95.8 V (Voc) and 0.99 μA (Isc). Advanced 3D printing techniques (3DP) including powder‐based multijet fusion and resin‐based polyjet fusion are utilized to print polyamide 12 (PA12) and VeroClear, respectively. The laser surface patterning technique is used to make precise micropatterns on the surfaces of the VeroClear and PA12 layers, resulting in a consistent and effective surface morphology that enhances the surface area of triboelectric layers, and outperforms traditional approaches of patterning in consistency and efficacy. The validation of simulation results is made where the pyramid pattern is emerged as the most efficient geometry experimentally. Performance is maintained with minimal degradation after 102 cycles, and a 22 μF–63 V capacitor is successfully used to store the generated charge. This study not only sets the path for pre‐experimental analysis using simulation environment but also provides a clear demonstration of advanced manufacturing techniques for printing and patterning 3D‐printed triboelectric materials.

Determination of selective laser melting process parameters of tungsten carbide powders coated with nickel via electroless plating for improved interface properties

Tungsten carbide powders are commonly used at various industrial applications due to their high hardness. However, these powders may exhibit low binding and processing challenges without a binder. Therefore, various binding methods such as electroless Ni coating are used to hold WC powders together, increase their processability and improve the mechanical properties of the final product. Electroless Ni plating plays an important role in the use of WC powders, especially in processes such as selective laser melting. The structural, tribological, and mechanical properties of parts manufactured by SLM method are significantly influenced by the parameters employed in the process. Hence, optimizing process variables is essential to unlock the full potential of this advanced manufacturing technique. The main objective of this study was to identify the optimum process parameters for the SLM method of WC-Ni composite powders, which were prepared by coating WC powder materials with electroless Ni. Experimental investigations focused on analyzing the laser power, scanning speed, and hatch spacing parameters. The effects of these parameters on the mechanical and tribological properties of WC-Ni composite material were investigated using microhardness tester, tribometer device, optical microscope, 3D optical profilometer and scanning electron microscope. Eventually, it was determined that the manufacturing parameters employed in the SLM method had a significant impact on relative density, microstructure, surface roughness, hardness, and tribological properties. Samples exhibited a relative density of nearly 99%, and the highest observed hardness value was 1962 HV. This article supports a specialized SLM manufacturing process developed specifically to enhance durability and performance across a broad spectrum of industrial applications through interface improvement and the optimization of manufacturing parameters.

Characterization and Performance Evaluation of Digital Light Processing 3D Printed Functional Anion Exchange Membranes in Electrodialysis

With the rapid development of 3D printing technologies, more attention has been focused on using 3D printing for the fabrication of membranes. This study investigated the application of digital light processing (DLP) 3D printing combined with quaternization processes to develop dense anion exchange membranes (AEMs) for electrodialysis (ED) separation of Cl− and SO42− ions. It was discovered that at optimal curing times of 40 min, the membrane pore density was significantly enhanced and the surface roughness was reduced, and this resulted in an elevation of desalination rates (97.5–98.7%) and concentration rates (165.8–174.1%) of the ED process. Furthermore, increasing the number of printed layers improved the membranes’ overall polymerization and performance, with double-layer printing showing superior ion flux. This study also highlights the impact of the polyethylene glycol diacrylate (PEGDA) molecular weight on membrane efficacy, where PEGDA-700 outperformed PEGDA-400 in ion transport capabilities and desalination efficiency. Additionally, higher 4-vinylbenzyl chloride (VBC) content improved the quaternary ammonium group concentration and membrane conductivity, and hence elevated the ED performance. Under optimized conditions, DLP 3D printed membranes demonstrated exceptional selectivity of 24.0 for Cl−/SO42− and a selective purity of 81.4%. With a current density of 400 A/m2, the current efficiency and energy consumption were in the range of 82.4% to 99.7%, and 17.2 to 25.4 kW‧h‧kg−1, respectively, showcasing the potential of advanced manufacturing techniques in creating efficient and functional ion exchange membranes.

Capillary-Driven Microdevice Mixer Using Additive Manufacturing (SLA Technology)

This study presents a novel microfluidic mixer designed, fabricated, and characterized using additive manufacturing technology—stereolithography (SLA)—and harnessing capillarity principles achieved through microstructure patterning. Micromixers are integral components in optimizing mixing and reaction processes within microfluidic systems. The proposed microdevice employs a tank mixing method capable of blending two fluids. With a channel length of up to 6 mm, the process time is remarkably swift at 3 s, and the compact device measures 35 × 40 × 5 mm. The capillarity-driven working flow rates range from 1 μL/s to 37 μL/s, facilitated by channel dimensions varying between 400 μm and 850 μm. The total liquid volume within the device channels is 1652 mL (6176 μL including the supply tanks). The mix index, representing the homogeneity of the two fluids, is approximately 0.55 along the main channel. The manufacturing process, encompassing printing, isopropyl cleaning, and UV (ultraviolet) curing, is completed within 90 min. This microfluidic mixer showcases efficient mixing capabilities, rapid processing, and a compact design, marking it as a promising advancement in microfluidic technology. The new microfluidic mixer is a major step forward in microfluidic technology, providing a cost-effective and flexible solution for various uses. Its compatibility with SLA additive manufacturing allows for quick prototyping and design improvements, making it valuable for research and practical applications in chemistry, biology, and diagnostics. This study highlights the importance of combining advanced manufacturing techniques with basic fluid dynamics to create effective and easy-to-use microfluidic solutions.

The importance of reinforcing advanced ceramics in space projects

This article addresses the role of advanced ceramics in space exploration, highlighting their importance in tackling the unique challenges of the extraterrestrial environment. Starting with an analysis of the Space Shuttle Columbia disaster in 2003, lessons learned and safety measures implemented in the aftermath of the incident are discussed. The properties of advanced ceramics, including resistance to extreme temperatures, chemical stability, and thermal insulation capability, are explored, along with their applicability in space missions, such as radiation protection, resistance to debris, and propulsion. Strategies for maximizing the resilience of ceramics in space environments are examined, including advanced manufacturing techniques and continuous monitoring systems. Finally, specific applications of ceramics in space components, such as rocket nozzles, propulsion systems, and heat-to-electricity conversion, are discussed, emphasizing the ongoing need for innovation to ensure the success of future space missions.

Wear Rate, Tribo-Corrosion, and Plastic Deformation Values of Co-Cr-Mo Alloy in Ringer Lactate Solution.

This study investigates the tribocorrosion performance of a cast Co-Cr-Mo alloy prepared using casting and electromagnetic stirring (EMS) at specific frequencies. The tribocorrosion behaviour of the alloy was evaluated when exposed to Ringer's lactate solution to optimize the EMS parameters and improve its properties. The research focuses on biomedical implant applications and explores how EMS affects alloy wear and corrosion resistance. As did the friction coefficient and wear volume, the wear rate of samples produced with EMS frequencies of 75 Hz and 150 Hz decreased. These improvements are attributed to the ability of EMS to refine grain size and homogenize the microstructure, thereby increasing the resistance to tribocorrosion. Techniques such as scanning electron microscopy (SEM) and profilometry were used for surface and wear analysis, while mechanical properties were evaluated through instrumented indentation tests. The findings confirm that EMS improves the alloy's durability and tribocorrosion resistance, making it highly suitable for demanding biomedical applications such as joint replacements. This highlights the importance of advanced manufacturing techniques in optimizing biomedical alloys for simulated body conditions.

Lipid Nanoparticles in Lung Cancer Therapy.

This manuscript explores the use of lipid nanoparticles (LNPs) in addressing the pivotal challenges of lung cancer treatment, including drug delivery inefficacy and multi-drug resistance. LNPs have significantly advanced targeted therapy by improving the precision and reducing the systemic toxicity of chemotherapeutics such as doxorubicin and paclitaxel. This manuscript details the design and benefits of various LNP systems, including solid lipid-polymer hybrids, which offer controlled release and enhanced drug encapsulation. Despite achievements in reducing tumor size and enhancing survival, challenges such as manufacturing complexity, biocompatibility, and variable clinical outcomes persist. Future directions are aimed at refining targeting capabilities, expanding combinatorial therapies, and integrating advanced manufacturing techniques to tailor treatments to individual patient profiles, thus promising to transform lung cancer therapy through interdisciplinary collaboration and regulatory innovation.

Preface

AbstractThis special issue of Materials Science and Engineering Technology (Materialwissenschaft und Werkstofftechnik) contains selected papers presented at the 16th International Conference on Advanced Computational Engineering and Experimenting (ACE‐X 2023) held at the Aquila Atlantis Hotel in Crete during the period 3rd–7th July, 2023. The included papers are related to advanced structured materials, their design and analysis, and advanced manufacturing and processing techniques.

Heat transfer optimisation using novel biomorphic pin-fin heat sinks: An integrated approach via design for manufacturing, numerical simulation, and machine learning

With the availability of advanced manufacturing techniques, non-conventional shapes and bio-inspired/biomorphic designs have shown to provide more efficient heat transfer. Consequently, this research investigates the heat transfer performance and fluid flow characteristics of novel biomorphic scutoid pin fins with varying volumes and top geometries. Numerical simulations were conducted using four hybrid designs for Reynolds Number 5500–13500. The impact of pin fin 'top' geometrical features on the heat transfer coefficient (HTC) was evaluated by combining computational fluid dynamics (CFD), experimental data, and machine learning. The results highlighted that the new pin fins saved 6.3 % to 14.3 % volume/material usage but produced around 1.5 to 1.7 times more heat transfer than conventional square/rectangular fins. Also, manipulating pin fins via the top geometrical properties can lead to more uniform velocity and temperature distributions while demonstrating the potential for increased thermal efficiency with reduced thermal resistance. Furthermore, six machine learning models accurately predict HTC using volume and surface area as key variables, achieving less than 5 % mean absolute percentage error (MAPE). Overall, this research introduces innovative biomorphic designs with unconventional geometries, emphasising resource optimisation and efficient HTC prediction using machine learning. It simplifies design processes, supports agile product development, calls for re-evaluation of conventional heat sink geometries, and provides promising directions for future research.

Accelerating Process Development and Product Formulation.

Currently, the lengthy time needed to bring new drugs to market or to implement postapproval changes causes multiple problems, such as delaying patients access to new lifesaving or life-enhancing medications and slowing the response to emergencies that require new treatments. However, new technologies are available that can help solve these problems. The January 2023 NIPTE pathfinding workshop on accelerating drug product development and approval included a session in which participants considered the current state of product formulation and process development, barriers to acceleration of the development timeline, and opportunities for overcoming these barriers using new technologies. The authors participated in this workshop, and in this article have shared their perspective of some of the ways forward, including advanced manufacturing techniques and adaptive development. In addition, there is a need for paradigm shifts in regulatory processes, increased pre-competitive collaboration, and a shared strategy among regulators, industry, and academia.

Multi-Criteria Decision Analysis of an Innovative Additive Manufacturing Technique for Onboard Maintenance

Access to spare parts in the maritime industry is limited throughout most of a ship’s life cycle. The limitation is caused by both the geographical distance of vessels from suppliers and the often limited turnaround time during which parts can be delivered. Manufacturing some parts onboard is possible, but it is a time-consuming and labour-intensive process. Advanced manufacturing techniques could be used to improve access to spare parts at sea by combining the desirable materials properties and flexibility of Direct Energy Deposition (DED) and the higher dimensional tolerances of Computer Numerical Control (CNC) manufacturing. The present study assesses the comparative viability of onboard implementation of advanced manufacturing techniques for offshore assets as a capital investment in different modes against an option of no onboard advanced manufacturing using a multi-criteria decision analysis method. To this end, a Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) is employed considering the techno-economic and environmental aspects of the decision-making process as well as the inherent challenges that come with a new area of research. Finally, the challenges, opportunities, and pathways to onboard maintenance using additive manufacturing are discussed within the scope of the sustainable future for ship and offshore energy assets.

Design and Fabrication of an Acetylene Fuel Vehicle

Abstract: The transition towards sustainable transportation necessitates exploring alternative fuels with reduced environmental impacts. Acetylene has emerged as a promising candidate due to its clean combustion characteristics and high energy density. This abstract outline the design and fabrication process of an acetylene fuel vehicle, focusing on its feasibility and performance. The design phase involves meticulous material selection to ensure compatibility with acetylene's properties while prioritizing safety measures. Key components such as the fuel storage system, combustion chamber, and propulsion system are engineered to maximize energy conversion efficiency and minimize emissions. Safety protocols for acetylene handling and storage are integrated into the design to mitigate risks associated with its high reactivity. Fabrication incorporates advanced manufacturing techniques like additive manufacturing and precision machining to create a robust vehicle prototype. The integration of selected components is optimized to enhance structural integrity and overall performance. Rigorous testing procedures are conducted to validate the vehicle's functionality, including performance metrics, emissions analysis, and safety evaluations. The outcomes of this study provide valuable insights into the feasibility of acetylene as a sustainable transportation fuel. The design and fabrication processes contribute to ongoing research efforts aimed at reducing the carbon footprint of the transportation sector. The results also offer a pathway for future developments in alternative fuel technologies, driving towards a more environmentally friendly and energy-efficient transportation ecosystem.

A Comparative Study of Deep-Learning Autoencoders (DLAEs) for Vibration Anomaly Detection in Manufacturing Equipment

Speed reducers (SR) and electric motors are crucial in modern manufacturing, especially within adhesive coating equipment. The electric motor mainly transforms electrical power into mechanical force to propel most machinery. Conversely, speed reducers are vital elements that control the speed and torque of rotating machinery, ensuring optimal performance and efficiency. Interestingly, variations in chamber temperatures of adhesive coating machines and the use of specific adhesives can lead to defects in chains and jigs, causing possible breakdowns in the speed reducer and its surrounding components. This study introduces novel deep-learning autoencoder models to enhance production efficiency by presenting a comparative assessment for anomaly detection that would enable precise and predictive insights by modeling complex temporal relationships in the vibration data. The data acquisition framework facilitated adherence to data governance principles by maintaining data quality and consistency, data storage and processing operations, and aligning with data management standards. The study here would capture the attention of practitioners involved in data-centric processes, industrial engineering, and advanced manufacturing techniques.

Effects of TiN content and heat treatment on microstructural changes, mechanical strength, and corrosion resistance in selective laser melting of TiN/AISI 420 composites

This study investigates the influence of Titanium Nitride (TiN) concentration variations and heat treatment on the microstructure, strength, and corrosion resistance of TiN/AISI 420 composites fabricated via selective laser melting (SLM). Results demonstrate that the addition of TiN particles (2 μm in size) at 0.5, 1, and 2 wt percent (wt. %) to the AISI 420 alloy enhances the toughness modulus of SLM TiN/AISI 420 to 37.0 ± 1.5 J/m3, 42.2 ± 0.4 J/m3, and 36.2 ± 0.7 J/m3, respectively, surpassing the SLM AISI 420's toughness of 21.3 ± 0.6 J/m3. Moreover, a positive relationship between TiN content and corrosion resistance is observed, with 2 wt % TiN/AISI 420 composites exhibiting the highest resistance at 105.6 ± 2.5 mm/year in a 6 wt % FeCl3 solution. Following heat treatment, a reduction in hardness is noted due to decreased surface residual stress and increased retained austenite. However, treated composites demonstrate improved mechanical and corrosion resistances. Particularly noteworthy is the highest toughness of 118.0 ± 1.3 J/m3 observed in 1 wt % TiN composites and a corrosion rate of 104.7 ± 2.7 mm/year in 2 wt % TiN composites. The homogeneous dispersion of TiN particles and the phenomenon of transformation-induced plasticity significantly enhance toughness, while increased levels of retained austenite contribute to improved corrosion resistance. This work underscores the potential of advanced manufacturing techniques in developing composite materials with diverse applications, such as robotic mold inserts. It emphasizes the pivotal role of composite formulation and post-processing in augmenting material performance.

Carbon and graphene based nanocomposites for gas sensors—Current state and advances

After the discovery of carbon nanoforms, carbon nanotube (one dimensional) and tube like nanostructure and graphene (two dimensional) nanosheets have gained immense research curiosity. Further nanotechnological developments have moved towards the formation of carbon nanotube nanocomposites and graphene nanocomposites. For the purpose, various matrices including thermoplastic polymers and conjugated polymers have been used. Methodology is the systematic gathering of the literature and development of a novel review outline, theme, and discussions regarding the discussed topics. Hence, varying conjugated polymers such as polyaniline, polythiophene, poly(3,4-ethylenedioxythiophene), and nonconjugated nylon, poly(ethylene glycol), etc. have been processed using techniques like in situ, solution, electropolymerization, spin coating, etc. In sensors, the nanocomposites need to develop fine nanoparticle dispersion, network formation, and interfacial interactions ultimately supporting the electron or charge transfer in these nanomaterials desirable for the recognition of the gaseous species. Moreover, interactions of the nanocomposite with the analyte molecules define the sensing capabilities of the nanomaterials. Consequently, nanocarbon nanocomposite based gas sensors have been analyzed for conductivity, change in resistance, sensitivity, selectivity, response time, detection limit, and other desirable properties. For future designs, it is recommended to develop high-tech combinations of conjugated polymers like polythiophene derivatives using functional forms of graphene and carbon nanotube. In addition, use of advanced manufacturing techniques like 3D/4D printing and spin coating must be applied to form efficient sensors. In conclusions, this manuscript presents not only comprehensive but also comparative analysis on different gas analysis parameters such as detection limit, concentration, response time, etc. for various nanocomposite sensors. Lastly, the encounters in preparing and applying graphene/carbon nanotube sensors, associated utilizations, and possible future prospects have been discussed.

Optimized analytical approach for the detection of process-induced defects using acoustic emission during directed energy deposition process

Directed energy deposition (DED), an advanced additive manufacturing (AM) technique, facilitates the production of complex metallic and metal matrix composite structures. The DED process has continuously improved and offers numerous advantages for depositing high-quality coatings with excellent wear and corrosion resistance onto metallic surfaces. The dynamic nature of the process, however, introduces a significant risk of process-induced defects in manufactured parts. This study presents an optimized analytical approach using acoustic emission (AE) based defect detection technique to identify and quantify process-induced cracks during the DED process. The developed signal processing technique enabled the identification of actual AE events associated with cracking, distinguishing them from other disturbances. Experimental validation was conducted using manufactured parts that were longitudinally sectioned to determine the relationship of the crack location with the recorded acoustic signal. The demonstrated correlation of acoustic signatures with cracking illustrates the robustness of the AE technique to identify the process-induced cracking for quality assurance during the DED process.