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Metals
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Full-Cycle Innovation of Titanium Resources: From Mineral Development to High-End...
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Full-Cycle Innovation of Titanium Resources: From Mineral Development to High-End Material Manufacturing

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

Deadline for manuscript submissions: 31 January 2026 | Viewed by 517

Special Issue Editors

Dr. Lingxin Kong

E-Mail Website
Guest Editor
Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Interests: vacuum metallurgy; rare and precious metals; molten salt electrolysis; separation and purification
Special Issues, Collections and Topics in MDPI journals
Dr. Lei Gao

E-Mail Website
Guest Editor
Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Interests: pyrometallurgical technology; numerical modeling; titanium; external field metallurgy; metallurgical process strengthening
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Titanium and its alloys hold irreplaceable strategic value in aerospace, marine engineering, biomedical fields, and other critical industries because of their high specific strength, corrosion resistance, and biocompatibility. However, the efficient development and high-value utilization of titanium resources still face challenges such as difficult mineral separation, high energy consumption in metallurgy, and complex material processing. This Special Issue focuses on full-industry-chain technological innovations in titanium resources, covering three core directions: mineral processing, green metallurgy, and material design and application. These areas aim to drive the titanium industry toward low-carbon practices, intelligent manufacturing, and circular economy models.

Dr. Lingxin Kong
Dr. Lei Gao
Guest Editors

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

  • titanium alloys
  • green metallurgy
  • additive manufacturing
  • circular economy
  • carbon neutrality

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Published Papers (1 paper)

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Research

34 pages, 22828 KB  
Article
Optimization of Process Parameters in Electron Beam Cold Hearth Melting and Casting of Ti-6wt%Al-4wt%V via CFD-ML Approach
by Yuchen Xin, Jianglu Liu, Yaming Shi, Zina Cheng, Yang Liu, Lei Gao, Huanhuan Zhang, Haohang Ji, Tianrui Han, Shenghui Guo, Shubiao Yin and Qiuni Zhao
Metals 2025, 15(8), 897; https://doi.org/10.3390/met15080897 - 11 Aug 2025
Viewed by 430
Abstract
During electron beam cold hearth melting (EBCHM) of Ti-6wt%Al-4wt%V titanium alloy, aluminum volatilization causes compositional segregation in the ingot, significantly degrading material performance. Traditional methods (e.g., the Langmuir equation) struggle to accurately predict aluminum diffusion and compensation behaviors, while computational fluid dynamics (CFD), [...] Read more.
During electron beam cold hearth melting (EBCHM) of Ti-6wt%Al-4wt%V titanium alloy, aluminum volatilization causes compositional segregation in the ingot, significantly degrading material performance. Traditional methods (e.g., the Langmuir equation) struggle to accurately predict aluminum diffusion and compensation behaviors, while computational fluid dynamics (CFD), although capable of resolving multiphysics fields in the molten pool, suffer from high computational costs and insufficient research on segregation control. To address these issues, this study proposes a CFD-machine learning (backpropagation neural network, CFD-ML(BP)) approach to achieve precise prediction and optimization of aluminum segregation. First, CFD simulations are performed to obtain the molten pool’s temperature field, flow field, and aluminum concentration distribution, with model reliability validated experimentally. Subsequently, a BP neural network is trained using large-scale CFD datasets to establish an aluminum concentration prediction model, capturing the nonlinear relationships between process parameters (e.g., casting speed, temperature) and compositional segregation. Finally, optimization algorithms are applied to determine optimal process parameters, which are validated via CFD multiphysics coupling simulations. The results demonstrate that this method predicts the average aluminum concentration in the ingot with an error of ≤3%, significantly reducing computational costs. It also elucidates the kinetic mechanisms of aluminum volatilization and diffusion, revealing that non-monotonic segregation trends arise from the dynamic balance of volatilization, diffusion, convection, and solidification. Moreover, the most uniform aluminum distribution (average 6.8 wt.%, R2 = 0.002) is achieved in a double-overflow mold at a casting speed of 18 mm/min and a temperature of 2168 K. Full article
(This article belongs to the Special Issue Full-Cycle Innovation of Titanium Resources: From Mineral Development to High-End Material Manufacturing)
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