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Additive Manufacturing: Technological Advancements, Processes, Materials, and Applications

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A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Additive Manufacturing".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 6653

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Special Issue Editor

Prof. Dr. Atila Ertas

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Guest Editor

Department of Mechanical Engineering, Texas Tech University, Lubbock, TX 79409, USA
Interests: test method development; galling; transdisciplinary complex system design; 3D printing technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Additive manufacturing (AM) is becoming increasingly capable of redefining the manufacturing landscape. The existing ecosystem for AM has greatly advanced in the areas of design digitization, deposition methods, printer capabilities, component geometry re-imagination, and post-processing methods. Big data and machine learning are reaching such levels of maturity that they have become capable of assisting targeted and rapid problem solving.

The availability of adequate materials designed for the specific purpose of leveraging existing 3D printing technology is a significantly underdeveloped area of AM. To date, most materials being used in AM are traditional “industry-standard materials” in industry-standard product forms, primarily powdered metals and wire, that were originally developed for “legacy forming manufacturing methods”—namely, press-and-sinter or metal injection molding. This use of legacy materials adapted for 3D printing technology is resulting in a sub-optimal level of product creation and market.

It would be beneficial to design wholly new “additive materials” that will complement and maximize the virtues of existing 3D printing technology, particularly low-energy, highly stable technologies such as binder jetting. This new material would achieve the required performance properties of industrial component design, but with new or significantly reformulated molecular compositions. Furthermore, the material development process would be synthesized with rapid problem-solving computational methods, supported by the continued expansion of artificial intelligence algorithms and their supporting ecosystems. We welcome you to submit papers to this Special Issue of “Additive Manufacturing: Technological advancements, processes, materials, and applications” in the following general research areas of additive manufacturing: innovative design and fabrication of 3D printing machines, development of new materials for 3D printing; manufacturing technologies in 3D printing; pre- and post-processing technologies and approaches; use of 3D printing in food, chemical, aeronautical, and healthcare industries, among others; simulation in AM (topology optimization, microstructure design, etc.); use of artificial intelligence (AI) in the additive manufacturing and developing of new 3D printing materials; the emergence of new technologies that enable the use of silicone as a 3D printing material; current challenges in additive manufacturing; and any other interesting research topics regarding 3D printing (additive manufacturing).

Prof. Dr. Atila Ertas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

additive manufacturing
3D printing
detecting voids in a material
post processing
artificial intelligence
simulation
modeling

Related Special Issue

Additive Manufacturing Research and Applications in Metals (19 articles)

Published Papers (4 papers)

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Research

16 pages, 11929 KiB

Open AccessArticle

Gas-Atomized Nickel Silicide Powders Alloyed with Molybdenum, Cobalt, Titanium, Boron, and Vanadium for Additive Manufacturing

by Mohammad Ibrahim, Qiang Du, Even Wilberg Hovig, Geir Grasmo, Christopher Hulme and Ragnhild E. Aune

Metals 2023, 13(9), 1591; https://doi.org/10.3390/met13091591 - 13 Sep 2023

Viewed by 1322

Abstract

Nickel silicides (NiSi) are renowned for their ability to withstand high temperatures and resist oxidation and corrosion in challenging environments. As a result, these alloys have garnered interest for potential applications in turbine blades and underwater settings. However, their high brittleness is a constant obstacle that hinders their use in producing larger parts. A literature review has revealed that incorporating trace amounts of transition metals can enhance the ductility of silicides. Consequently, the present study aims to create NiSi-based powders with the addition of titanium (Ti), boron (B), cobalt (Co), molybdenum (Mo), and vanadium (V) for Additive Manufacturing (AM) through the process of gas atomization. The study comprehensively assesses the microstructure, phase composition, thermal properties, and surface morphology of the produced powder particles, specifically NiSi11.9Co3.4, NiSi10.15V4.85, NiSi11.2Mo1.8, and Ni-Si10.78Ti1.84B0.1. Commonly used analytical techniques (SEM, EDS, XRD, DSC, and laser diffraction) are used to identify the alloy configuration that offers optimal characteristics for AM applications. The results show spherical particles within the size range of 20–63 μm, and only isolated satellites were observed to exist in the produced powders, securing their smooth flow during AM processing. Full article

(This article belongs to the Special Issue Additive Manufacturing: Technological Advancements, Processes, Materials, and Applications)

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15 pages, 16642 KiB

Open AccessArticle

Process Control Methods in Cold Wire Gas Metal Arc Additive Manufacturing

by João B. Bento, Chong Wang, Jialuo Ding and Stewart Williams

Metals 2023, 13(8), 1334; https://doi.org/10.3390/met13081334 - 26 Jul 2023

Cited by 3 | Viewed by 1819

Abstract

Cold wire gas metal arc (CWGMA) additive manufacturing (AM) is more productive and beneficial than the common electric arc processes currently used in wire arc additive manufacturing (WAAM). Adding a non-energised wire to the gas metal arc (GMA) system makes it possible to overcome a process limitation and decouple the energy input from the material feed rate. Two novel process control methods were proposed, namely, arc power and travel speed control, which can keep the required geometry accuracy in WAAM through a broad range of thermal conditions. The reinforcement area of the bead is kept constant with accurate control over the height and width while still reducing the energy input to the substrate; decreasing penetration depth, remelting, and the heat-affected zone (HAZ); and reaching a dilution lower than 10%. This work also presents improved productivity compared to all the other single-arc energy-based processes with a demonstrator part built using 9.57 kg h⁻¹ with CWGMA AM. Full article

(This article belongs to the Special Issue Additive Manufacturing: Technological Advancements, Processes, Materials, and Applications)

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15 pages, 3244 KiB

Open AccessArticle

High-Throughput Synthesis and Characterization Screening of Mg-Cu-Y Metallic Glass

by Dan J. Thoma, Janine T. Spethson, Carter S. Francis, Paul M. Voyles and John H. Perepezko

Metals 2023, 13(7), 1317; https://doi.org/10.3390/met13071317 - 24 Jul 2023

Cited by 1 | Viewed by 1040

Abstract

Bulk metallic glasses can exhibit novel material properties for engineering scale components, but the experimental discovery of new alloy compositions is time intensive and thwarts the rate of discovery. This study presents an experimental, high-throughput methodology to increase the speed of discovery for potential bulk metallic glass alloys. A well-documented system, Mg-Cu-Y, was used as a model system. A laser additive manufacturing technique, directed energy deposition, was used for the in situ alloying of elemental powders to synthesize discrete compositions in the ternary system. The laser processing technique can supply the necessary cooling rates of 10³–10⁴ Ks⁻¹ for bulk metallic glass formation. The in situ alloying enables the rapid synthesis of compositional libraries with larger sample sizes and discrete compositions than are provided by combinatorial thin films. Approximately 1000 discrete compositions can be synthesized in a day. Surface smoothness, as discerned by optical reflectivity, can suggest glass-forming alloys. X-ray diffraction coupled with energy dispersive X-ray spectroscopy can further refine amorphous alloy signatures and compositions. Transmission electron microscopy confirms amorphous samples. The tiered rate of amorphous alloy synthesis and characterization can survey a large compositional space and permits a glass-forming range to be identified within one week, making the process at least three orders of magnitude faster than other discrete composition techniques such as arc-melting or melt-spinning. Full article

(This article belongs to the Special Issue Additive Manufacturing: Technological Advancements, Processes, Materials, and Applications)

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10 pages, 1822 KiB

Open AccessArticle

Optimization of 3D Printing Parameters on Deformation by BP Neural Network Algorithm

by Yu Li, Feng Ding and Weijun Tian

Metals 2022, 12(10), 1559; https://doi.org/10.3390/met12101559 - 21 Sep 2022

Cited by 3 | Viewed by 1429

Abstract

Traditional processing technology is not suitable for the requirements of advanced manufacturing due to the disadvantages of large repeated experiments, high cost, and low economic effect. As the latest additive technology, 3D printing technology has to deal with many issues such as process parameters and nonlinear mathematical models. A three-layer backpropagation (BP) artificial neural network with a Lavenberg–Marquardt algorithm was established to train the network and predict orthogonal experimental data. Additionally, the best combination of parameters of material deformations were predicted and verified by experiments. The results show that the predicted value obtained by the BP model is in good agreement with the experimental value curve, with a small relative error and a correlation coefficient of 0.99985. Moreover, the deformation errors of the printed model are not more than 3%. The incorporation of the BP neural network algorithm into the 3D printing process can, therefore, help cope with related problems, which is a future trend. Full article

(This article belongs to the Special Issue Additive Manufacturing: Technological Advancements, Processes, Materials, and Applications)

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