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Additive Manufacturing and Forming Technologies of Alloy: Mechanical Properties and Microstructure Evaluation

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: 20 October 2025 | Viewed by 3200

Special Issue Editor

Prof. Dr. Yunping Li

E-Mail Website
Guest Editor
High Temperature Materials Research Institute, Central South University, Changsha, China
Interests: additive manufacturing; superalloys; powder metallurgy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue of Materials entitled "Additive Manufacturing and Forming Technologies of Alloy: Mechanical Properties and Microstructure Evaluation".

In recent years, there have been significant advancements in the field of additive manufacturing, leading to the creation of new materials with enhanced properties and applications. This Special Issue aims to showcase recent achievements related to the design, preparation, and knowledge of the metallic materials and alloys manufactured via additive manufacturing.

We welcome the submission of original research papers, reviews, and perspectives that encompass a wide range of topics related to the field. The scope of this Special Issue includes, but is not limited to, the following topics:

  • The design and synthesis of new alloys for additive manufacturing;
  • Novel processing techniques and approaches for additive manufacturing;
  • Mechanical performance of alloys produced by additive manufacturing;
  • The multiscale modeling and simulation of additive manufacturing;
  • The microstructural characterization of materials produced by additive manufacturing;
  • The application of new materials via additive manufacturing.

We particularly welcome contributions from researchers working in academia, industry, and research institutes. We believe that this Special Issue will provide a platform for researchers to share their latest findings, exchange ideas, and promote collaboration within the field.

We look forward to receiving your valuable contributions and ensuring the success of this Special Issue. Should you have any questions or require further information, please do not hesitate to contact us.

Prof. Dr. Yunping Li
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. Materials is an international peer-reviewed open access semimonthly 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
  • superalloys
  • powder metallurgy
  • microstructure
  • mechanical property
  • near net shape forming

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

18 pages, 7555 KB  
Article
Considering γ’ and Dislocation in Constitutive Modeling of Hot Compression Behavior of Nickel-Based Powder Superalloy
by Liwei Xie, Jinhe Shi, Jiayu Liang, Dechong Li, Lei Zhao, Qian Bai, Kailun Zheng and Yaping Wang
Materials 2025, 18(20), 4680; https://doi.org/10.3390/ma18204680 - 12 Oct 2025
Viewed by 353
Abstract
The deformation mechanism during the hot compression of PM nickel-based superalloy FGH99 and its micro-structural evolution, especially the evolution of γ’ phases, are the key factors affecting the final molding quality of aero-engine hot forged turbine disks. In this study, a new constitutive [...] Read more.
The deformation mechanism during the hot compression of PM nickel-based superalloy FGH99 and its micro-structural evolution, especially the evolution of γ’ phases, are the key factors affecting the final molding quality of aero-engine hot forged turbine disks. In this study, a new constitutive model of viscoplasticity with micro-structures as physical internal parameters were developed to simulate the hot compression behavior of FGH99 by incorporating the strengthening effect of the γ’ phase. The mechanical behavior of high-temperature (>1000 K) compressive deformation of typical superalloys under a wide strain rate (0.001~1 s−1) is investigated using the Gleeble thermal-force dynamic simulation tester. The micro-structure after the hot deformation was characterized using EBSD and TEM. Work hardening as well as dynamic softening were observed in the hot compression tests. Based on the mechanical responses and micro-structural features, the model considered the coupled effects of dislocation density, DRX, and γ’ phase during hot flow. The model is programmed into a user subroutine based on the Fortran language and called in the simulation of the DEFORM-3D V6.1 software, thus realizing the multiscale predictive simulation of FGH99 alloy by combining macroscopic deformation and micro-structural evolution. The established viscoplastic constitutive model shows a peak discrepancy of 10.05% between its predicted hot flow stresses and the experimental values. For the average grain size of FGH99, predictions exhibit an error below 7.20%. These results demonstrate the high accuracy of the viscoplastic constitutive model developed in this study. Full article
(This article belongs to the Special Issue Additive Manufacturing and Forming Technologies of Alloy: Mechanical Properties and Microstructure Evaluation)
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14 pages, 6899 KB  
Article
Additive Manufacturing of Si-Added 7075 Aluminum Alloys: Microstructural, Mechanical, and Electrochemical Properties via Heat Treatment
by Gahyun Choi, Hobyung Chae, You Sub Kim, Soon-Ku Hong, Eunjoo Shin and Soo Yeol Lee
Materials 2025, 18(7), 1544; https://doi.org/10.3390/ma18071544 - 28 Mar 2025
Cited by 2 | Viewed by 1284
Abstract
Al 7075 alloy (AA7075) exhibits excellent strength yet poses significant challenges for additive manufacturing (AM) due to its complex composition and propensity for defects during rapid solidification. To address these issues, this study introduces a novel AA7075 containing a small amount of Si [...] Read more.
Al 7075 alloy (AA7075) exhibits excellent strength yet poses significant challenges for additive manufacturing (AM) due to its complex composition and propensity for defects during rapid solidification. To address these issues, this study introduces a novel AA7075 containing a small amount of Si fabricated by selective laser melting (SLM). Despite concerns about reduced melt-pool stability at low Si content, the alloy was successfully processed into defect-minimized samples. Systematic evaluations of as-built and heat-treated (direct aging, solid-solution, T6) samples revealed distinct microstructural evolution and clear improvements in mechanical properties and corrosion resistance. Specifically, as-built and direct aging conditions showed high strength but limited ductility and pronounced galvanic corrosion due to inhomogeneous microstructures. Conversely, solid-solution and T6 treatments effectively homogenized the microstructure, significantly enhancing ductility and reducing corrosion susceptibility, with the T6-treated samples exhibiting the most balanced mechanical and electrochemical performance. By maintaining a favorable microstructural balance while minimizing Si-induced brittleness, the low-Si AA7075 demonstrates improved SLM processability and robust performance. These findings offer a new pathway for optimizing AM aluminum alloys through tailored heat treatments. Full article
(This article belongs to the Special Issue Additive Manufacturing and Forming Technologies of Alloy: Mechanical Properties and Microstructure Evaluation)
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15 pages, 1098 KB  
Article
Real-Time Detection and Monitoring of Oxide Layer Formation in 1045 Steel Using Infrared Thermography and Advanced Image Processing Algorithms
by Antony Morales-Cervantes, Héctor Javier Vergara-Hernández, Edgar Guevara, Jorge Sergio Téllez-Martínez and Gerardo Marx Chávez-Campos
Materials 2025, 18(5), 954; https://doi.org/10.3390/ma18050954 - 21 Feb 2025
Cited by 2 | Viewed by 1191
Abstract
This study addresses the challenge of monitoring oxide layer formation in 1045 steel, a critical issue affecting mechanical properties and phase stability during high-temperature processes (900 °C). To tackle this, an image processing algorithm was developed to detect and segment regions of interest [...] Read more.
This study addresses the challenge of monitoring oxide layer formation in 1045 steel, a critical issue affecting mechanical properties and phase stability during high-temperature processes (900 °C). To tackle this, an image processing algorithm was developed to detect and segment regions of interest (ROIs) in oxidized steel surfaces, utilizing infrared thermography as a non-contact, real-time measurement technique. Controlled heating experiments ensured standardized data acquisition, and the algorithm demonstrated exceptional accuracy with performance metrics such as 96% accuracy and a Dice coefficient of 96.15%. These results underscore the algorithm’s capability to monitor oxide scale formation, directly impacting surface quality, thermal uniformity, and material integrity. The integration of thermography with machine learning techniques enhances steel manufacturing processes by enabling precise interventions, reducing material losses, and improving product quality. This work highlights the potential of advanced monitoring systems to address challenges in industrial steel production and contribute to the sustainability of advanced steel materials. Full article
(This article belongs to the Special Issue Additive Manufacturing and Forming Technologies of Alloy: Mechanical Properties and Microstructure Evaluation)
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