Dear Colleagues,

We would like to draw your attention to the upcoming International Conference on Computational & Experimental Engineering and Sciences (ICCES2024), to be held in Singapore from August 3rd to 6th, 2024. We are co-organizing Session 87: "Atomistic Modeling of Mechanical Behavior of Materials." Below are the details.

Conference Details:

• Event: ICCES2024
• Dates: August 3rd-6th, 2024
• Venue: Marina Bay Sands Conference Center, Singapore
• Session: S87. Atomistic Modeling of Mechanical Behavior of Materials

Chairs:

• Shigenobu Ogata, Osaka University, Japan
• Daisuke Matsunaka, Shinshu University, Japan
• Hideki Mori, College of Industrial Technology, Japan
• Yoshinori Shiihara, Toyota Technological Institute, Japan

Abstract Submission Deadline: April 25, 2024 (Note: The abstract submission deadline for this session has been specially extended and may differ from other published deadlines.)

Website: ICCES2024 Conference

Tentative Keynote and Invited Speakers:

• Prof. Yoshitaka Umeno, University of Tokyo (Keynote)
• Prof. Yunjiang Wang, Institute of Mechanics, Chinese Academy of Sciences (Invited)
• Prof. Yu-Chieh Lo, National Yang Ming Chiao Tung University (Invited)
• Prof. Bin Wu, Beijing Normal University (Invited)
• Prof. Emi Minamitani, Osaka University (Invited)
• Prof. Takuya Iwashita, Oita University (Invited)
• Prof. Ryosuke Matsumoto, Kyoto University of Advanced Science (Invited)
• Dr. Masato Wakeda, National Institute for Materials Science (Invited)

Aim and Scope: In the rapidly advancing field of material science, atomistic modeling has emerged as a critical approach. Grounded in the principles of quantum mechanics that underpin atomic bonds, atomistic modeling provides deep insights into the fundamental mechanisms governing the mechanical behavior of materials, even at the macroscopic scale. This includes the elucidation of atomic-level defects such as dislocation dynamics, twinning, grain boundary interactions, crack propagation, and their interactions with impurities. Understanding these processes is crucial for accurately predicting and comprehending the mechanical properties of materials—strength, ductility, and toughness—and a broad spectrum of advanced materials including multi-component alloys, nano-structured composites, and glassy materials. Furthermore, atomistic modeling is essential for understanding multiphysics phenomena, where mechanical properties correlate with ferroelectric characteristics, magnetism, chemical reactions, electrical conductivities, and more. This symposium is dedicated to presenting the latest breakthroughs in atomic simulations and the theoretical frameworks that support these advancements in material modeling. Recent innovations in machine learning approaches, in particular, have been recognized as a paradigm shift in atomic simulations, overcoming traditional barriers related to spatial and time scales. We hope this symposium will serve as a forum for discussing innovative material modeling research, including machine learning techniques and cutting-edge computational theories, and their impact on real-world applications.

Keywords: Molecular dynamics simulation, ab initio calculation, kinetic Monte Carlo, interatomic potential, machine learning approaches, lattice defects, multiphysics

We look forward to welcoming you to Singapore.

Best regards,

Yoshinori Shiihara