The “Computation and Simulation on Metals” Section of Metals (ISSN: 2075-4701) highlights cutting-edge research on the computational modeling and simulation of metallic materials and processes. This Section aims to advance the understanding of metal behavior through numerical methods, data-driven approaches, and multiscale simulations.

Key areas of interest include finite element analysis, phase-field modeling, molecular dynamics, machine learning applications, and simulations of microstructural evolution, mechanical properties, and material processing.

We welcome contributions that encompass both theoretical and applied research, including studies with direct industrial relevance.

As all papers published in Metals are in open access format, readers have free and unlimited access to the full texts. We invite you to explore our highly cited papers from 2023, listed below:

1. “Evaluation of the Elastic Modulus and Plateau Stress of a 2D Porous Aluminum Alloy Based on a Convolutional Neural Network”
by Jianhang Sun, Yepeng Xu and Lei Wang
Metals 2023, 13(2), 284; https://doi.org/10.3390/met13020284  
Full text available online: https://www.mdpi.com/2075-4701/13/2/284

2. “A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification”
by Nicholas Cusato, Seyed Amin Nabavizadeh and Mohsen Eshraghi
Metals 2023, 13(7), 1169; https://doi.org/10.3390/met13071169  
Full text available online: https://www.mdpi.com/2075-4701/13/7/1169

3. “An Analysis of Long-Process Ironmaking in a Reduction Smelting Furnace with Hydrogen-Enriched Conditions”
by Haifeng Li and Jingran Chen
Metals 2023, 13(10), 1756; https://doi.org/10.3390/met13101756  
Full text available online: https://www.mdpi.com/2075-4701/13/10/1756

4. “Study on the Activity Model of PbO-ZnO-FeO-Fe₂O₃-SiO₂-CaO Six-Component High-Lead Slag System”
by Jinbo Song, Wenlong Xi and Liping Niu
Metals 2023, 13(4), 734; https://doi.org/10.3390/met13040734  
Full text available online: https://www.mdpi.com/2075-4701/13/4/734

5. “Application of Digital Image Processing Techniques to Detect Through-Thickness Crack in Hole Expansion Test”
by Daniel J. Cruz, Rui L. Amaral, Abel D. Santos and João Manuel R. S. Tavares
Metals 2023, 13(7), 1197; https://doi.org/10.3390/met13071197  
Full text available online: https://www.mdpi.com/2075-4701/13/7/1197

6. “Numerical Simulation of the Slag Splashing Process in A 120 Ton Top-Blown Converter”
by Guang Yang, Baokuan Li, Meijia Sun, Deyue Qin and Liangcai Zhong
Metals 2023, 13(5), 940; https://doi.org/10.3390/met13050940  
Full text available online: https://www.mdpi.com/2075-4701/13/5/940

7. “Surface Formation of Sloping Features in Laser Powder–Bed Fusion by Multi-Track Multi-Layer Simulations”
by Trong-Nhan Le and Kevin Chou
Metals 2023, 13(5), 976; https://doi.org/10.3390/met13050976  
Full text available online: https://www.mdpi.com/2075-4701/13/5/976

8. “Data-Driven Inverse Problem for Optimizing the Induction Hardening Process of C45 Spur-Gear”
by Sevan Garois, Monzer Daoud and Francisco Chinesta
Metals 2023, 13(5), 997; https://doi.org/10.3390/met13050997  
Full text available online: https://www.mdpi.com/2075-4701/13/5/997

9. “Reproducible Quantification of the Microstructure of Complex Quenched and Quenched and Tempered Steels Using Modern Methods of Machine Learning”
by Björn-Ivo Bachmann,  Martin Müller, Dominik Britz, Thorsten Staudt and Frank Mücklich
Metals 2023, 13(8), 1395; https://doi.org/10.3390/met13081395  
Full text available online: https://www.mdpi.com/2075-4701/13/8/1395

10. “An Investigation of Spiral Dislocation Sources Using Discrete Dislocation Dynamics (DDD) Simulations”
by Luo Li and Tariq Khraishi
Metals 2023, 13(8), 1408; https://doi.org/10.3390/met13081408  
Full text available online: https://www.mdpi.com/2075-4701/13/8/1408