bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of the Printed Part Size on the Shrinkage and Density in Binder Jetting Additive Manufacturing of Ceramics Powder
Authors: Obeidat Suleiman , Smith Chris , Basith Iftekhar , Dakeev Ulan , Ma Junkun
Published: August 2024

The additive manufacturing method discussed in this work is the binder jetting additive manufacturing process where a liquid-based binder is deposited on the powder bed to fabricate the part layer by layer. Binder Jetting 3D printing is capable of printing different types of materials such as metals, ceramics, and polymers. While the selective laser melting process can be used to make metal parts, the same process can’t be used to make ceramic parts. For this reason, in terms of 3D printing, the binder jetting additive manufacturing process is ideal for ceramic parts. In this work, ceramic particles are used to investigate the impact of the part size on the shrinkage percentage, and the apparent and relative density of the printed part. Four different shapes including cylinders, rectangular blocks, cones, and spheres of different sizes are printed at 100 %, 75%, core saturation limit at 0 seconds, and 10 seconds delay using a binder jetting 3D printer at 0.2 mm layer thickness. We print multiple samples of these different shapes. After the fabrication process, the parts are left for 6 - hours in the printer and then moved carefully to the de-powdering station where the parts are dried, and the binder is cured at 35°C for 6–8 hours to prevent any cracks during the sintering process. This process is followed by the sintering process to improve the density of the part fabricated and to make it stronger. The shrinkage percentage and the apparent and relative density of the printed parts are calculated after the sintering process for each geometry at two different sizes. A density and shrinkage comparison is conducted for the four shapes at two different sizes for the green and sintered parts at different printing parameters We use ceramic powder of particle size range 50–200 μm to print the parts. The ceramics powders consist of 50% crystalline silica (quartz), 25% kaolinite, and 25% of potassium feldspar. The binder consists of 8% Diethylene glycol, 2% Surfactant, and 90% water. It is found that the big samples at 100 % and 75 % core saturation with the number of prints one at different time delays of zero and 10 seconds, provide 11–18 % higher relative density, for cone samples, compared to the small samples. The big samples at 100 % core saturation provide bigger shrinkage than the small samples at 0 (about 27 % for the cone samples) and 10 seconds delay (17 % for the cone samples).
Multi-Facility Location Optimization to Analyze the Economics of Plastic Recycling Systems: A Study Integrating K-Means and Monte Carlo Methods
Authors: Nandimandalam Hariteja , Mendis Gamini P.
Published: August 2024

Plastic waste recycling is essential for sustainable practices, but it suffers from inefficiency due to a lack of a secondary market and difficulties in separating the plastic resins. Plastic recycling is improving substantially as technology (especially sensing technology) advances and the need for post-consumer plastic resin grows. The economics and logistics of plastic recycling plants, on the other hand, are uncertain, due to feedstock availability, logistics, and market price availability. Furthermore, pyrolysis and chemical recycling facilities are entering the market for post-consumer plastics, which has the potential to change the economics of the system and create additional demand for clean streams of waste plastic. This study combines plastic recycling facility logistics (sorting technology) to examine economic viability and determine how transportation and facility size (i.e., clusters) affect profitability under a variety of scenarios.

To achieve these objectives, the study leverages available data on the number of post-consumer plastics suppliers to locate central sorting locations by employing a K-means clustering method. This work aims to identify the optimum number of recycling facilities and their locations in the United States to make a recycling system economically viable. Monte Carlo simulations are performed to evaluate the effects of the price of plastic resin, plastic composition, the end-of-life fate of different resins, and the number of centroids on the profitability of the recycling facility. Depending on the scenario, the profit generated by recycling facilities can vary from −$197 million to $112 million.

Key factors such as the sale price of resin in the secondary recycling market, transportation type and cost, and whether polypropylene is sent to secondary recycling or pyrolysis facilities are critical variables influencing the profitability of the recycling system. The plastic composition and fate of polypropylene (recycling vs pyrolysis) strongly affect the profitability of the recycling facility. The amount of HDPE and PET, both resins with existing recycling markets are key factors for economic viability. The introduction of additional recycling centers (or clusters) results in a substantial reduction in transportation costs. However, the creation of additional recycling centers results in increased operating and capital costs per ton of plastic waste processed. The optimal number of facilities is then driven by the tradeoff between capital costs and the total transportation distance and mode of transportation used. It was identified that shipping waste plastic via train dramatically decreased transportation costs over conventional semi-truck transportation. This work is aimed at identifying potential opportunities for better plastic end of life fates and identifying the circumstances in which the recycling facilities will be viable over the long term.
Reducing Warping in ABS 3D Printed Parts Through Infill Modification
Authors: Shen Weijun , Veeramani Dharmaraj , Qin Hantang
Published: August 2024

Additive Manufacturing (AM), or 3D printing, has transformed traditional manufacturing by allowing the layer-by-layer construction of objects from digital models. This study addresses warping in Acrylonitrile Butadiene Styrene (ABS) Fused Filament Fabrication (FFF) by proposing infill structure modification. Using CR-ABS filament and a Prusa i3 MK3+ printer, we investigate three geometric shapes — strip, square, and leaf — via advanced 3D scanning for surface curvature analysis. By intentionally altering infill patterns, we analyze warping mechanisms such as non-uniform shrinkage and anisotropic thermal stress. Auto-leveling and curvature calculations evaluate the impact of modified infill strategies on warpage. Results demonstrate significant reductions in surface warpage, with modified infill structures surpassing default patterns. Improved dimensional stability is evidenced by average and maximum surface deviations alongside curvature measurements. This research offers a robust approach, highlighting the potential of infill modification to enhance reliability and stability in 3D-printed parts. While limited to ABS material and specific shapes, this study marks a substantial advancement in ABS 3D printing precision. The proposed methodology not only effectively reduces warpage but also holds promise for diverse applications across materials and printing technologies. Further research is urged to explore scalability and broader implications, which are essential for a comprehensive understanding and application of infill structure modification in 3D printing. In addressing warping challenges, this study contributes to the evolution of modern manufacturing processes, underscoring the importance of advancing warpage reduction strategies for realizing 3D printing’s full potential.
Investigation of the Morphological and Migration Behavior of Breast Cancer Cells on a Micropillar-Based Topography
Authors: Molinares Ponce Marielena , Wolpert Nicholas , Gollahon Lauren , Xu Changxue
Published: August 2024

In the case of cancer studies, comprehension of the processes and signals that regulate tumor invasion and metastasis requires a thorough understanding of cancer cell migration. The risk of cancer leading to patient death increases when carcinogenic cells undergo intravasation, leaving the primary site through vessel and developing secondary tumors after extravasation occurs. The relevance of the study of cell migration lies in being able to understand the mechanisms that promote and regulate cell motility until the invasion of adjacent tissues which physicochemical conditions favor cancer cell spreading. Changes in cell adhesion, cytoskeletal remodeling, and signaling pathways, in addition to interactions with the extracellular matrix in the microenvironment are part of the metastatic process that defines cancer as a multifactorial disease. Among the types of cues that modulate the behavior and migration of cells, topotaxis is based on the geometrical modification of the substrate surfaces which leads to the possibility of representing the architecture of the extracellular matrix at a micro or nanometer scale. For instance, breast tissue is complex to represent given its variety of cells, fibers, and proteins but representation of its extracellular matrix topography is becoming an important tool to approximate both normal and tumor microenvironment (TME). To represent part of the changes in structure that cells might undergo during attachment and migration within the extracellular matrix, we propose topography variation on polymeric substrates which manufacturing started with the design of micropillar array with distance gradient, followed by maskless lithographic to obtain a silicon master and finally transfer to PDMS. Corona discharge treatment was used to obtain a hydrophilic surface and enhance cell attachment. Prior to cells seeding, collagen, one of the proteins that promotes growth and progression in tumor sites, was included as substrate coating. As part of the proof-of-concept study of the mechanisms underlying progression, MDA-MB-231 as a high metastatic potential or invasive cell line was used in the experiment. Cellular morphology is studied in terms of aspect ratio and attachment time, and the preliminary migration investigation includes cancer cell migration speed with the incubation time. The resulting fundamental knowledge regarding cancer cell migration and invasion is beneficial to potential applications including early detection of cancer, inhibition of cancer cell migration and invasion, and drug delivery for cancer therapy.
Brief Paper: a Study of Forces and Energy Consumption in Constrained Cutting of OFHC Copper
Authors: Leahy Osian P. , Sencer Burak , Guo Yang
Published: August 2024

Constrained cutting is a novel cutting process which employs an additional constraining tool in combination of the cutting tool to enable the control of chip-forming deformation in the cutting process. In this study, a linear cutting setup equipped with force sensors was developed and used to conduct constrained cutting experiments on highly ductile OFHC copper at three controlled chip thickness ratios. The chip thickness ratio was controlled by altering the constraining tool position in the setup. The setup allows the cutting tool forces and constraining tool forces to be measured separately in the constrained cutting process. Free cutting experiment was also conducted for comparison. The results show that the total cutting force (or equivalently the cutting energy consumption) is up to 50% lower in constrained cutting than in free cutting. Both the cutting and thrust forces on the cutting tool are reduced by constrained cutting compared to free cutting. The cutting force on the constraining tool is negligibly small while the thrust force on the constraining tool is only moderate. These results indicate the energy consumption by the constraining action is negligibly small while its effect on the cutting energy reduction is substantial. The study confirms the great potential of constrained cutting as an efficient material removal process.
Effect of Layer Time Control via Physics-Based Model on Layer Temperature in Extrusion-Based Large Format Additive Manufacturing
Authors: Jo Eonyeon , Liu Lu , Ju Feng , Garg Nikhil , Ozcan Soydan , Vaidya Uday , Kim Seokpum
Published: August 2024

In polymer extrusion-based large format additive manufacturing (AM), the strength and structural integrity of printed parts depend on interlayer bonding, which is highly affected by layer temperature. Layer deposition with an improper layer temperature can result in undesirable defects such as warping, cracking, and debonding. A critical factor in this layer deposition process is the layer deposition time, commonly known as “layer time,” which significantly impacts layer temperature and interlayer bonding strength. For example, an excessively long layer time results in an over-cooled surface, leading to interlayer debonding, cracking, and warping. Conversely, an excessively short layer time causes overheating, leading to material collapse due to insufficient stiffness when new layers are deposited. Traditionally, layer time have been determined based on the experience of skilled operators, employing a fixed rate throughout the entire printing process. This approach often fails to address dynamic changes during the printing process. Furthermore, it is limited by the absence of comprehensive guidelines based on accurate data and systematic analysis. Determining the best optimal layer time is further complicated by the influence of variable environmental conditions, geometric complexities, and printing parameters. There exists a clear need for a layer time control framework that can determine the best optimal layer time to achieve the desired layer temperature across all deposited layers, ultimately leading to an optimal printing outcome. In response to these challenges, a finite element analysis (FEA) model was used to simulate the additive deposition process. After the deposition of each layer, the simulation process paused, and the temperature data was fed into the previously developed layer time optimization framework. With the optimization framework, an optimal layer time for each successive layer was determined based on the cooling behavior of previously deposited layers. By updating the layer time based on the results from the optimization framework, the FEA model continued the deposition process continuously. The layer temperature is adjusted with the adaptive layer time control process. By implementing this approach, a mismatch between the target temperature and the simulated layer temperature was reduced from 27.8% to 4.7% for the second layer. In addition, the mismatch for the third layer was reduced from 11.7% to 0.3%. We aim to illuminate the influence of layer time control on layer temperature during polymer extrusion-based large format AM. This research will contribute to the advancement of realtime control systems in large format AM.
Assessing the Sustainability Impacts of Additive Manufacturing: A Review
Authors: Khan Md Tarique Hasan , Rezwana Saki
Published: August 2024

This study provides a comprehensive review of the sustainability aspects of Additive Manufacturing (AM), examining its evolution from prototyping to mainstream production with a focus on material efficiency, energy consumption, and waste reduction. It highlights the adoption of recycled and bio-based materials in AM processes as a step towards environmental sustainability. The potential of AM to streamline supply chains, thereby reducing transportation emissions, and its economic impact, including the displacement and creation of jobs, are discussed. However, the review identifies significant challenges, including technical limitations, the energy-intensive nature of certain AM processes, and the need for broader market acceptance. It calls for future research to address these shortcomings, emphasizing the importance of integrating sustainability into the core of AM development. This analysis underlines the complexity of achieving sustainability in AM, suggesting a balanced approach that considers both technological advancements and their socio-economic impacts.
Enhanced Data-Driven Virtual Metrology on Chemical Mechanical Planarization Process Using Dual Linear Kalman Filter
Authors: Rahman Amanat Ur , Han Xu , Jia Xiaodong
Published: August 2024

This paper explores a new virtual metrology method using Dual Linear Kalman Filter (DLKF) to track the gradual data variations in the semiconductor manufacturing process. The prediction of Material Removal Rate (MRR) in the Chemical Mechanical Planarization (CMP) is adopted to demonstrate the results. The proposed approach ensures dynamic tracking of CMP process changes and jointly updates state and parameter accordingly for the MRR prediction. This recursive nature of DLKF allows for tracking the process drifts and self-adjusting the parameters accordingly. The effectiveness of the proposed methodology for MRR prediction is tested based on the dataset from the Prognostics and Health Management (PHM) Data Challenge 2016. The prediction performance will be evaluated and benchmarked again with other peer algorithms that are used in practice.
Brief Paper: Physics-Guided Scan Paths Optimization for Controlled Microstructure in Laser Powder Bed Fusion
Authors: Twumasi Augustine , Roy Prokash Chandra , Choi Jin Young , Gan Zhengtao
Published: August 2024

Laser Powder Bed Fusion (L-PBF) is a renowned additive manufacturing technique, celebrated for its capability to construct intricate metal components with remarkable precision. However, one of the main challenges with L-PBF is the formation of complex microstructures, which can significantly impact the final material properties. To address this issue, our study proposes a physics-guided and machine-learning-aided approach to optimize scan paths for achieving desired microstructure outcomes, such as the generation of equiaxed grains that enhance material properties. By using phase-field modeling, a physics-based computational method, we gain insights into microstructure evolution. To reduce computational costs, we train a surrogate machine-learning model using a 3D U-Net convolutional neural network and single-track phase-field simulations as dataset. This enables the machine learning model to predict crystalline grain orientations accurately based on the initial microstructure and thermal history. As a preliminary approach, we investigate three primary scanning strategies — vertical serpentine, spiral serpentine and diagonal scanning — at various hatch spacings to identify the most effective paths for achieving the desired microstructure. This lays the foundation for a comprehensive examination of how different scan paths and parameters affect the resulting microstructure. By combining this strategic analysis with our advanced modeling techniques, we provide insights into how scan path influences the attainment of optimal crystalline grain structure in L-PBF processes. This approach not only enhances our ability to predict microstructural outcomes but also advances the precision manufacturing capabilities of L-PBF, merging theoretical knowledge with practical application to guide future advancements in additive manufacturing. Importantly, our methodology achieves a computational time reduction by approximately three orders of magnitude, underscoring the efficiency of our ML approach in accelerating the design process.
MOF-Laden 3D Printed Monolithic Filter Design and Manufacturing
Authors: Zia Akhter , Khoda Bashir
Published: August 2024

In recent years, 3D printing, a highly promising additive manufacturing technique, has garnered significant attention as it allows the addition of fused materials layer by layer, to create intricate structures with ease and also offers the flexibility to incorporate multiple materials within the same structure simultaneously, reducing production time and costs. The versatility of 3D printing has led to its application in diverse fields, including nanotechnology. For nanotechnological applications, the manipulation of the 3D printing process to achieve specific patterns or designs is crucial for desired outcomes. As a result, continuous efforts are being made to advance the 3D printing process. Recent studies have focused on varying manufacturing process parameters to analyze their impact on the mechanical properties of 3D-printed products. Parameters such as raster width, raster angle, and printing speed have been identified as influencing factors, particularly on the strength of the printed items. An exciting development in the application of 3D printing in nanotechnology involves integrating the synthesis of metal-organic frameworks (MOFs) into the 3D-printed porous structure. This innovation has opened up new possibilities, especially in fields like water treatment. The synthesis of Cu-based MOFs on 3D-printed porous PLA structures has been explored in this study, with different raster angles and air gaps. Decreasing the air gap and low raster angle have been found to increase MOF growth, and vice versa. Dispersion of MOFs reaches the maximum with an increase in air gap before starting to decrease for any further addition of air gap. Optimizing manufacturing parameters can maximize MOF availability, leading to enhanced adsorption performance for water treatment.
A Mobile Additive Manufacturing Robot Framework for Smart Manufacturing Systems
Authors: Li Yifei , Park Jeongwon , Manogharan Guha , Ju Feng , Kovalenko Ilya
Published: August 2024

Recent technological innovations in the areas of additive manufacturing and collaborative robotics have paved the way toward realizing the concept of on-demand, personalized production on the shop floor. Additive manufacturing process can provide the capability of printing highly customized parts based on various customer requirements. Autonomous, mobile systems provide the flexibility to move custom parts around the shop floor to various manufacturing operations, as needed by product requirements. In this work, we proposed a mobile additive manufacturing robot framework for merging an additive manufacturing process system with an autonomous mobile base. Two case studies showcase the potential benefits of the proposed mobile additive manufacturing framework. The first case study overviews the effect that a mobile system can have on a fused deposition modeling process. The second case study showcases how integrating a mobile additive manufacturing machine can improve the throughput of the manufacturing system. The major findings of this study are that the proposed mobile robotic AM has increased throughput by taking advantage of the travel time between operations/processing sites. It is particularly suited to perform intermittent operations (e.g., preparing feedstock) during the travel time of the robotic AM. One major implication of this study is its application in manufacturing structural components (e.g., concrete construction, and feedstock preparation during reconnaissance missions) in remote or extreme terrains with on-site or on-demand feedstocks.
Characterization of Elastoplastic Properties of Additively Manufactured Specimens From Indentation Data Using Stochastic Inverse Modeling
Authors: Olabiyi Ridwan , Weaver Jordan , Iquebal Ashif
Published: August 2024

Rapid characterization of mechanical properties and material structure of additively manufactured (AM) components via non-destructive techniques (NDT) is crucial for their wider adoption. However, accurate characterization of AM components using NDT remains a challenge. To this end, our work focuses on characterizing the elastoplastic properties of AM components from instrumented indentation measurements, addressing the inverse indentation problem. Previous approaches to this problem have limitations in generalization or in estimating the variability of elastoplastic properties. In this work, we explore a stochastic inverse problem (SIP) formulation, estimating a distribution over elastoplastic properties (Young’s modulus, yield strength, and strain hardening exponent) that aligns with observed indentation data. Implementing this methodology for AM components subjected to different heat treatments, we achieve predictions of the strain hardening exponent (n), Young’s modulus (E), and yield strength (σy) to within 1.1%, 1%, and 5% of the actual values, respectively. The recovered distributions closely match those from standard tensile tests, indicating our methodology’s accuracy in characterizing mean elastoplastic properties and their variability through high throughput indentation measurements.
A Physical Comprehensive Model for Studying Temperature Evolution in FDM 3D Printing
Authors: Sun Haofan , Albert Magnas Joseph , Remani Srikar Anudeep , Guo Shenghan , Nian Qiong
Published: August 2024

Along with emerging engineering requirements in multiple fields, how to fully realize the three-dimensional (3D) design has become a critical manufacturing challenge. To tackle this challenge, there is continuous research in recent years for development of additive manufacturing processes, that is 3D printing techniques. Fused deposition modeling (FDM) is one among the most extensively studied 3D printing techniques that generate 3D models, prototypes and especially end products from polymers. FDM printer uses a continuous filament of thermoplastic polymer or its nanocomposite, which is fed to the heated printer extruder head and then deposited onto the growing work. This technology offers multiple advantages over existing techniques, including fabricating complex designs, multi-material printing, rapid prototyping, high spatial resolution, on-site and on-demand production, as well as efficient material utilization with little or no waste. For example, according to existing literatures related to the FDM technique, various polymers, and their composites, such as ABS, PLA, PE, PEEK, Nylon, etc., have been designed and applied to build functional structures. In spite of current research and advancement, there are still limitations and disadvantages reported regarding FDM, e.g.., the lower strength exhibited in FDM parts compared to those by injection molding or compression molding techniques. Reasons could be explained by the insufficient bonding between the adjacent layers and the distorted shape of extruded polymers while printing, which hence needs to be improved by controlling the temperature related parameters, such as the speed of printing, temperatures of nozzle and bed. Therefore, validated by the videos from thermal camera, we here propose a new physical comprehensible model to simulate the temperature evolution during FDM 3D printing. In specific, we use finite element method (FEM) to build a heat transfer model with element activation function in ANSYS. Each element simulation is activated for multiple layers with over 1000 elements each layer at the bottom, middle and top of the sample to simulate the drop-by-drop and layer-by-layer extrudate “printing” behavior. The mesh temperature and element initial temperature are set as the same values to the bed and nozzle temperature, while the time interval of adjacent elements is set according to the printing speed in experiments. Thermal videos are generated by FLIR A320 Tempscreen from Teledyne FLIR. To further prove the accuracy of the FEM model, we collect and compare the temperature plots of the same area in thermal video and simulation. This work not only introduces a new physical comprehensive FEM model for FDM 3D printing process but also shed light on the printing process optimization and potential new future process development.
Laser Hairpin Stripping With a New Generation CO2 Laser at Lower Wavelength for E-Drive Manufacturing
Authors: Caprio Leonardo , D’Arcangelo Simone , Chesi Davide , Nocciolini Daniele , Corbinelli Rubino , Previtali Barbara , Demir Ali Gökhan
Published: August 2024

Electric drives are conventionally produced with copper hairpin windings. Rather than the flexible winding of thin wires, Cu bars with typically rectangular cross section are separately bent into the desired form and inserted to the stator to form a continuous winding. The open ends to be connected generate the so-called hairpin couples. These regions should be free of the insulating polymer coating in order to apply the successive laser welding operation successfully. The presence of polymeric material in the welded area generates material bursts, spatter, and pores due to the very low vaporization temperature compared to the welded metal. Laser hairpin stripping removes the electrically insulating enamel layer and ensures a clean surface for the successive laser welding operation that produces the contacts. Several types of pulsed wave lasers can be operated producing different types of material removal mechanisms from surface evaporation to material expulsion. CO2 lasers have been long employed in the industry for processing polymeric materials thanks to the high optical absorptivity at IR region. High power CO2 lasers sources can be an appealing solution for the hairpin stripping process combining the high absorption by the polymeric enamel and the low absorptivity of underlying copper. New generation of CO2 lasers at lower wavelengths (i.e. 9.4 μm) can provide relatively smaller spot sizes and possibly enhanced processing. This work proposes a systematic analysis of the process development starting from single pulsed material removal towards areal scanning. The processed material was Polyester (Amide) (Imide) overcoated with Polyamideimide enamel material with 95 μm thickness on ETP Cu (electrolytic tough pitch copper) bars. A CO2 laser operating at 9.4 μm wavelength with 400 W maximum average power was employed. The laser produced μs-long pulses by regulating the pulse repetition rate in the kHz level along with the duty cycle. First the material removal was evaluated at maximum output power and duty cycle varying the pulse duration and the scan speed. The conditions were analyzed categorically assessing partial and complete material removal. Multiple pass scan strategies were developed to remove material in larger areas. The most productive solutions as well as the one providing the surface with the least amount of material remaining on the surface were chosen for further evaluation. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and focal variation microscopy (FVM) were employed to analyze the surface topography, chemistry, and roughness. Using the chosen conditions hairpin couples were stripped and laser welded using a high-power active fiber laser. The quality of the hairpin stripping operation was therefore evaluated also through the outcome of the welding operation in terms of bead geometry and its mechanical strength.
Toolpath Synthesis and Mechanical Properties in Multiplexed Fused Filament Fabrication
Authors: Cleeman Jeremy , Jackson Adrian , Patel Anandkumar , Malhotra Rajiv
Published: August 2024

Material Extrusion additive manufacturing (MatEx) based on Fused Filament Fabrication (FFF) enables inexpensive bottom-up fabrication of thermoplastics and thermoplastic composites for structural, biomedical, energy, and tooling applications. The to-scale realization of these lab-scale innovations in MatEx depends significantly on mass customization, i.e., increasing the overall process throughput (including that of post-processing) while retaining high resolution and 3D geometric capability that is crucial to additive manufacturing. This paper addresses a throughput-resolution-geometry tradeoff that limits such mass customization via a Multiplexed FFF (MF3) approach that combines a unique dynamic-extrusion based toolpath strategy with the existing multi-extruder-single-gantry machine architecture. MF3 has been demonstrated in one recent work. But this past effort does not enable geometrically generalizable and automated synthesis of the atypical MF3 toolpath, does not investigate the unconventional scaling of throughput while considering partial infills that are common in additive manufacturing, and does not explore the mechanical effects of the section-section junctions created by MF3. This work establishes an automated and generalizable toolpath synthesis approach and derives analytical laws for build time reduction, both of which are prerequisites for rational process planning. A multi-extruder multi-section thermal model is created to reveal the atypical temperature history of section junctions in MF3 and is combined with mechanical testing and modelling to deconvolute geometric and thermal effects on the mechanical behavior of the section-section junctions.
An Island Type Novel Scan Pattern With Non-Linear Island Intersections for Laser Powder Bed Fusion Additive Manufacturing Processes
Authors: Roney Md Saidur Rahman , Ahsan A. M. M. Nazmul , Sezer Hayri , Kaul Sudhir
Published: August 2024

Thermal gradient and solidification time dictate the prominent mechanical properties and printing qualities of metal parts produced through the Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) techniques. Printing defects such as warpage, delamination, and cracking originate from the thermal history of the printed parts. The relatively smaller heat source (laser) following a given scan pattern results in rapid solidification and uneven distribution of thermal energy, which in turn develops residual stresses in the printed parts. Through island-type scanning, the rapid solidification phenomenon is inhibited as it allocates the thermal energy within the islands thereby raising the surface temperature. In this paper, a novel island-type scan pattern with non-linear island boundary is proposed to distribute the Heat Affected Zones (HAZs) along the lateral direction of the island span. The proposed pattern is island-type and zigzag that reflects the regular hexagonal shape arranged periodically along each island span, creating nonlinear intersections between two adjacent islands. The effect of the proposed scan pattern on residual stress development is then investigated through a numerical approach and compared with that of the existing Zigzag and Island Zigzag scan patterns. The simulation results exhibit comparable characteristics of the proposed scan pattern with a 6.67% reduction in residual stress achieved as compared to the other two scan patterns.
In-Situ Process Monitoring and Optimization for Extrusion-Based Silicone Additive Manufacturing
Authors: Ma Dingyifei , Tian Xiaoqing , Chang Tianlong , Hussain Shahid , Xia Lian , Han Jiang
Published: August 2024

The lack of direct process control of silicone material extrusion (MEX) limits the accuracy and design complexity of printed structures. In this paper, an iterative process monitoring system for silicone MEX that enables in-situ quality monitoring and optimization is presented and validated. To achieve in-situ quality monitoring, a laser profile sensor is integrated into the 3D printing platform to measure dimensional errors. The process includes virgin printing, scanning, analyzing, judging, and modified printing. Strands are initially printed and scanned step by step with the coordination of motion and sensing systems to obtain a point cloud with 3-dimensional coordinates. Data are corrected, standardized, and analyzed section by section instead of using an image process to improve efficiency and reserve information in the height direction. Centre, width, and height information are extracted for each strand cross-section. Noise and anomalies are then removed by a clustering algorithm for the center points to obtain the actual trajectory centerline and distribution of strand width along the trajectory. To achieve in-situ optimization for errors in trajectory, strand width, and height, the trajectory and process parameters are modified in the next print. The trajectory is corrected by applying the opposite trajectory deviation error vector. The feed rate is modified according to our previously proposed strand profile model that maps the process parameters to the strand cross-section geometry parameters. Compared with direct printing without in-situ quality monitoring and optimization, the overlap between the actual and the target strand was improved by 18%. The presented method demonstrates the feasibility and capability to improve accuracy and reduce errors.
Electrohydrodynamic Jet Printing Mechanisms and Applications to Flexible Electronic Devices
Authors: Chang Tianlong , Wang Zaiyu , Tian Xiaoqing , Ma Dingyifei , Hussain Shahid , Xia Lian , Han Jiang
Published: August 2024

In the field of biomedical devices and their applications, electrohydrodynamic jet (E-Jet) printing plays a crucial role in the fabrication of next-generation fine medical devices by virtue of its high resolution and precise control. This study focuses on optimizing the electrohydrodynamic jet printing fabrication process for flexible circuits using silver nanoparticles (AgNPs) on flexible substrates. In order to control the relationship between high preparation accuracy and low energy consumption, the working and geometrical parameters of the experimental process, such as voltage, printing speed and working height, are then explored in relation to the prepared circuits. The different states of the printing process are demonstrated in conjunction with computational fluid dynamics studies, and the causes of Taylor cone formation, cone-jet generation, jet rupture and droplet expansion are explained. The results show that the preparation of silver nanoparticle circuits using E-Jet printing technology can achieve micron-level discrimination and low energy consumption flexible circuits by regulating the process parameters, and the prepared flexible silver circuits have achieved 500 severe cyclic bending tests of 120° in the bending cycle. The results of this study provide a simple and stable solution for the preparation of E-Jet printed flexible circuits and offer a viable strategy for the fabrication of high-resolution biomedical devices.
Coupled Eulerian-Lagrangian Thermomechanical Model to Predict Residual Stress During Additive Friction Stir Deposition of Aluminum 6061
Authors: Mathews Ritin , Karandikar Jaydeep , Tyler Christopher , Smith Scott , Schmitz Tony
Published: August 2024

Additive friction stir deposition (AFSD) is a solid-state additive manufacturing process that is increasing in popularity thanks to the absence of high temperature effects in the deposited material. Due to the large amount of material flow, conventional Lagrangian (finite element) models are incapable of capturing realistic material physics involved in the process. Alternatively, although Eulerian (computational fluid dynamics) models capture large material flow, they cannot predict the mechanical (stress-strain) response of the material. Existing AFSD modeling works in the literature either apply simplifying assumptions or do not predict the mechanical response of the material. To address this research gap, a coupled Eulerian-Lagrangian (CEL) model is developed to simulate AFSD of aluminum 6061 and predict the thermomechanical response of the material during and after deposition. This physics-based model captures the influences of significant material flow, adiabatic heating due to plastic deformation and frictional heating during deposition and reasonably predicts temperature and residual stress.
Brief Paper: Model-Free Adaptive Spindle Speed Regulation for Mitigation of Machining Vibrations
Authors: Bahtiyar Kaan , Sencer Burak
Published: August 2024

This paper presents novel adaptive spindle speed control strategies to minimize machining vibrations. Machining processes suffer from forced and chatter vibrations that deteriorate surface finish, reduce tool life and can damage the machine components. Model-based process planning strategies are used to minimize the effect of these unwanted vibrations. These approaches require conducting modal (tap) testing to be performed on the machine tool and developing machining process model to determine the forced vibration levels and to generate stability lobe diagrams for chatter-free cutting conditions. Although such model-based strategies are effective in process planning and determining optimal spindle speed and depth-of-cut pairs, these model-guided strategies suffer from key bottlenecks; namely, 1) they require expert knowledge that is not widely available in small-to-medium sized enterprises and 2) their effectiveness depends on the accuracy of the employed models. Thus, the majority of machining industries utilize know-how-based process planning to mitigate vibrations in machining. This paper proposes practical and model-free self-optimizing (adaptive) spindle-speed regulation strategies that minimize machining vibrations through in-situ vibration (acceleration) measurements. Two approaches are presented aimed at mitigating the effect of both forced and chatter vibrations by monitoring the acceleration levels during machining. Strategy-I utilizes a dither signal to determine the best spindle speed to minimize overall machining vibrations, whereas strategy-II is a dither-free approach and utilizes least squares fitting to seek the optimal spindle speed. Both approaches can determine chatter-free cutting conditions and also minimize forced vibration levels for a better surface finish. Simulation studies are presented in this brief paper to showcase their effectiveness.
Aqueous Wet Etching of Silicon With Alkali Metal Hydroxides
Authors: Hasan Md Mahmudul , Rahman Faiz
Published: August 2024

Silicon etching is a process that is regularly employed in the semiconductor industry for many applications ranging from micromachining on the sub-millimeter scale to intricate pattern formation in tens of nanometer regime. Wet etching is used for bulk silicon removal. Such etching processes, generally, involve multiple chemical reactions where a liquid solution of etching agents removes surface atoms of silicon through chemical or electrochemical redox reactions at the substrate-etchant interface. Many wet etching processes are anisotropic, and thus the wet etching of silicon with hydroxide solutions tends to be direction or crystalline plane specific, allowing for directional control and reduced undercutting of any etch mask. An additional advantage of metal hydroxide etchants rise from their selective nature of extremely poor etch rate towards the basic oxide of silicon. This makes growing the hard mask of SiO2 a very cost effect step in the wet etching process. NaOH and KOH solutions are well known wet etching agents that offer inexpensive alternatives to anisotropic dry etching but are often either difficult to control (etch rate-wise) or result in rough etched surfaces. Only through better understanding of the chemical reaction mechanisms, i.e. the role of alkali metal cations and water molecules during the wet etching process more controllability and desired etch surface profiles can be achieved. This study summarizes the results from a series of wet etch processes with all the five different group 1 alkali metal oxides and discusses in detail how different types of group 1 metal ions impact the dynamics of the chemical reactions in the aqueous medium. Wet etching assisted by smaller cations like Li+ tend to be more controllable while larger cations like Cs+ result in much faster etch rates. Surfactants added to fast etching metal hydroxides result in finer sidewalls and smoothened etched surface on silicon. Later in the paper, the effect of microwave irradiation on the surface tension, structural arrangement of water molecules and its application in anisotropic etching are highlighted. Step by step details of the experiments are provided in the materials and methods section making the study easy to understand. Line profile plots, optical images, SEM micrographs and XRD intensity plots are presented throughout the report to support the given explanations. Research findings from the study experimentally establish a trend for anisotropic etch rates of silicon substrate with aqueous solutions of all the group 1 alkali metal hydroxides. Silicon etch rate increases down the group.
Surface modification of Al-15Al2O3-0.3G powder metallurgical alloy induced by high-current pulsed electron beam
Authors: Wang Lei , Gao Bo , Zhang Huanfeng , Shen Wenhuan , Liu Zhuang , Fu Haiyang , Lan Xin
Published: August 2024

This paper investigates the effect of high-current pulsed electron beam (HCPEB) surface treatment with two, five, and eight pulses on Al-15Al2O3-0.3G prepared by powder metallurgy. The results show that the presence of graphene during HCPEB irradiation effectively controls the extension of microcracks. The surface hardness of the samples increased by 66.56% and the wear rate decreased by 68.98% after eight-pulse HCPEB treatment. The increase in hardness is attributed to the uniform dispersion of hard particles, fine grain strengthening, dislocation strengthening, and amorphous structure formation by XRD, SEM, and TEM analysis during HCPEB irradiation. The improvement in wear resistance was attributed to the increase in hardness. The corrosion current density in 5 wt. % NaCl solution decreased from 1.212 × 10−4 to 3.353 × 10−5 after eight-pulse HCPEB treatment; the improved corrosion resistance performance is attributed to the equilibrium structure induced by HCPEB treatment.
Pt-decorated graphitic carbon nitride on carbon paper by x-ray photoelectron spectroscopy
Authors: Brugia Mattia , Gasparotto Alberto , Benedet Mattia , Barreca Davide , Rizzi Gian Andrea , Maccato Chiara
Published: August 2024

Nanocomposites based on Pt nanoparticles (NPs) and graphitic carbon nitride (gCN) have emerged as promising (photo)electrocatalysts for sustainable energy production, thanks to the synergistical combination of Pt NPs catalytic performances with the favorable gCN chemicophysical properties. In this work, we have focused on electrophoretic deposition of graphitic carbon nitride on carbon paper and subsequent system functionalization with Pt NPs by means of radio frequency sputtering under mild conditions. A final thermal treatment was performed both in air and under inert atmospheres to assess its influence on Pt oxidation states and the related interplay with ultimate functional performances. The present study is focused on x-ray photoelectron spectroscopy characterization of two representative gCN-Pt nanocomposite specimens, annealed in Ar and in air. In particular, we report the survey spectra and the detailed scans for C 1s, N 1s, O 1s, and Pt 4f regions, analyzing the principal spectral features and comparatively discussing the resulting material properties.
Realisation of broadband two-dimensional nonreciprocal acoustics using an active acoustic metasurface
Authors: Tan Joe , Cheer Jordan , House Charlie
Published: August 2024

Nonreciprocal acoustic devices have been shown to be able to control incident waves propagating in one direction whilst allowing incident waves propagating in the opposite direction to be transmitted without modification. Nonreciprocal sound transmission, typically, has been achieved by introducing nonlinearities or directional biasing through fluid motion or spatiotemporal modulation of resonant cavities. However, the spatial arrangement of these approaches creates preferential characteristics in one direction such that the direction of the nonreciprocal behaviour is fixed and, thus, they are not straightforwardly reconfigurable. To address this issue, it has previously been revealed that feedforward wave-based active controllers can be employed to drive a single subwavelength active unit cell to achieve broadband nonreciprocal sound transmission or absorption in a one-dimensional linear acoustic system. Extending this concept, this paper investigates how the feedforward wave-based active controller can be used to drive an array of subwavelength active unit cells forming a metasurface to achieve broadband nonreciprocal sound absorption over a two-dimensional plane. Through simulation and experimental studies, this paper shows that active wave-based absorption control systems can achieve broadband nonreciprocal sound absorption when the incident waves are generated by normally and obliquely positioned primary sources.