Thermal Science and Metallurgy

A special issue of Thermo (ISSN 2673-7264).

Deadline for manuscript submissions: 30 April 2026 | Viewed by 838

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Materials Science, Energy, and Nano-Engineering MSN Department, Mohammed VI Polytechnic University, Lot 660, Hay Moulay Rachid, Ben Guerir 43150, Morocco
Interests: thermodynamics; fluid phase equilibrium; structure–properties relationships; various thermodynamic-based models; process simulation models
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Special Issue Information

Dear Colleagues,

Metallurgy is the science and technology of metals and alloys, encompassing their extraction from ores, refining, production, and applications, as well as the study of the key relationships bridging their chemistry, microstructure, thermal treatment, and physical properties. Thermal science plays a crucial role in designing metallurgical processes for various industries, including manufacturing, construction, aerospace, and energy production.

The aim of the present Special Issue is to collect original contributions, promoting the participation and exchange of ideas of a broad spectrum of stakeholders—from academics working in Metallurgical Science and related subjects to researchers and engineers working in the industry and dealing with metallurgical processes (steelmaking, aerospace, energy production, etc.). Modern environmental concerns will also be a crucial discussion point for this Special Issue (e.g., green steels, high entropy alloys, greenhouse gases remediation, remediation of impacts associated with mining and industrial byproducts, metal recovery from slags, circular economy, etc.), which can only be well addressed if accurate and reliable data are provided. This work hopes to propose new solutions for these very recent challenges in energy efficiency, renewable energy integration, and sustainability improvement goals associated with metallurgical science and associated technologies.

Prof. Dr. Johan Jacquemin
Guest Editor

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Keywords

  • metallurgical science
  • heat treatments
  • metal working
  • physical metallurgy
  • alloying
  • simulation
  • green steel

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Published Papers (1 paper)

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Research

18 pages, 4132 KiB  
Article
A Development of the Rosenthal Equation for Predicting Thermal Profiles During Additive Manufacturing
by William Keeley, Richard Turner, Bashir Mitchell and Nils Warnken
Thermo 2025, 5(2), 16; https://doi.org/10.3390/thermo5020016 - 21 May 2025
Viewed by 159
Abstract
Thermal modelling of additive manufacturing is a key method for furthering the quality of the components produced, as it allows for analysis that is not possible via experimental methods due to the difficulties involved with in situ monitoring. The thermal gradients present during [...] Read more.
Thermal modelling of additive manufacturing is a key method for furthering the quality of the components produced, as it allows for analysis that is not possible via experimental methods due to the difficulties involved with in situ monitoring. The thermal gradients present during the additive manufacturing process have a large impact on the formation of defects, such as porosity, residual stress, and cracking. The thermal gradients also have a large impact on material properties by controlling the microstructure formed. Thermal modelling methods are often based on numerical solutions of the heat conduction equation. Whilst numerical methods can be more accurate, they are often very slow because of the fine mesh requirements to capture high thermal gradients and iterative solvers to approximate the real-world solution to the required thermal field equations. An analytical model was developed to provide a fast solution to the problem. The analytical model used in this research was based on the Rosenthal equation and was analysed under a range of process parameters. A temperature-dependent Rosenthal model was also created with the aim of improving the results. The analytical model was then compared with a finite element numerical model to act as verification for the results. The analytical model accurately predicted the meltpool width over a range of process conditions. The analytical model underestimated the meltpool length compared to the numerical model, especially at high velocities. When using the standard Rosenthal model, the use of room-temperature or high-temperature thermal conductivities underestimated or overestimated the cooling rates from the meltpool, respectively. A temperature-dependent Rosenthal model was shown to produce more accurate cooling rates compared to the original Rosenthal equation. Full article
(This article belongs to the Special Issue Thermal Science and Metallurgy)
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