Session Sheet - 8th World Congress on Integrated Computational Materials Engineering (ICME 2025): PSP Linkages: Multiscale/Multiphysics Modeling IV

8th World Congress on Integrated Computational Materials Engineering (ICME 2025): PSP Linkages: Multiscale/Multiphysics Modeling IV
Program Organizers: Victoria Miller, University of Florida; Stephen DeWitt, Oak Ridge National Laboratory

Thursday 8:00 AM
June 19, 2025
Room: Platinum Ballroom 5
Location: Anaheim Marriott

Session Chair: Parisa Asadi, Zeiss

8:00 AM  Invited
Observing and Predicting Grain Growth in Polycrystals: Gregory Rohrer¹; ¹Carnegie Mellon University
    Predictive models for grain growth during annealing would be useful in the ICME context because they have the potential to speed the development of new materials. Recent three-dimensional studies of grain growth have shown no correlation between curvature and migration velocity, contradicting the observed migration behavior of individual grain boundaries in bicrystals. Two types of simulations, atomistic molecular dynamics and continuum threshold dynamics have been instantiated with experimental observations and used to simulate growth under different conditions. Both of these simulations reproduce the independence of curvature and velocity observed in the experiment, as well as a reduction in energy by the replacement high energy grain boundaries with lower energy grain boundaries. A more realistic driving force for grain growth will be proposed and the prospect for predictive grain growth simulations will be discussed.

8:30 AM
Recapturing and Reusing Published Mg Alloy Texture Data: Benjamin Begley¹; Victoria Miller¹; ¹University of Florida
    Crystallographic texture is a rich data source, but when published in typical forms, e.g. as pole figures, it does not adhere to FAIR data principles. By publishing the data as an image, its reusability is severely limited. The texture encodes the effects of alloying and processing on relative deformation mode activities, making quantitative comparisons crucial. For example, during rolling the extent of basal pole splitting can be related the activity of pyramidal <c+a> slip. In this talk, we present a method for quantitatively reconstructing an ODF based on pole figure images. A variety of Mg alloy textures from the literature are recaptured and quantitatively compared. Using polycrystal plasticity simulations, their predicted mechanical behavior is evaluated. The relationships between alloying, processing, and texture features are discussed.

8:50 AM
ICME-Driven Synthesis of Nanosheets and Applications in Solar Energy Harvesting and CO₂-CH₄ Separation in Biogas: Ping Wu¹; Shunnian Wu¹; P.V.T. Weerasinghe¹; H.L. Senevirathna¹; H.N. Thenuwara¹; W.P.C. Lee¹; ¹Singapore University of Technology and Design
    This presentation showcases two studies leveraging Integrated Computational Materials Engineering (ICME) to tackle challenges in material synthesis and renewable energy. The first study utilizes ICME for the entropy-driven synthesis of 2D mica nanosheets from 3D non-Van-Der-Waals crystals. Through first-principles calculations, biaxial straining models, and experiments, we address barriers in exfoliating strongly bonded materials, focusing on their application in solar energy harvesting. The second study presents bio-inspired nanocomposites of magnesium oxide and hydroxide, modeled after the water-harvesting strategies of Namib Desert beetles, to enhance CO₂-CH₄ separation in biogas. Using density functional theory (DFT) and gas-composite interface modeling, the nanocomposites exhibit superior CO₂ adsorption and selective gas capture, with minimal CH₄ adsorption. These studies demonstrate ICME’s potential in optimizing material properties for energy applications by linking processing, microstructure, and performance, offering innovative solutions in solar energy and biogas processing.

9:10 AM
Multiscale Modeling of Mechanical Deformation in Metal-Matrix Nanocomposites Enabled by Machine Learning: Wenwu Xu¹; Colin Delaney¹; Ethan Morrison¹; Sky Soltero¹; Marivel Alfaro¹; Md. Shahrier Hasan¹; ¹San Diego State University
    We present an innovative multiscale modeling framework for Metal-Matrix Nanocomposites (MMNCs), integrating Machine Learning (ML) with Molecular Dynamics (MD) simulations and the Finite Element Method (FEM). This approach effectively captures the mechanical influence of nano-scale inclusions on the macroscopic behavior of MMNCs. Initially, MD simulations are conducted under various conditions to generate a comprehensive dataset reflecting the mechanical responses of MMNCs. This data is subsequently used to train ML models, which enhance the accuracy and computational efficiency of FEM-based analyses. Our method accurately predicts the deformation behavior of MMNCs across scales, showing strong agreement with experimental results and theoretical predictions. By seamlessly bridging atomistic and continuum modeling, this work provides a scalable and robust solution for the analysis of advanced composite materials, advancing the capabilities of predictive modeling in materials science.

9:30 AM Break

9:50 AM  Cancelled
Optimizing Non-Oriented Electrical Steel for Energy-Efficient Drives: The Role of Final Annealing in Microstructure Design: Masoud Sistaninia¹; ¹Materials Center Leoben Forschung Gmbh
    Non-oriented (NO) electrical steel is vital for applications in rotating electrical drives due to its uniform magnetic properties. The efficiency of these drives depends on optimizing processing routes like hot-rolling, cold-rolling, final annealing, and shear cutting. Our research focuses on designing high-performance NO electrical steels by controlling their microstructure and crystallographic texture through precise thermomechanical processing. This study highlights the critical role of final annealing in defining the steel’s magnetic properties. We show how specific annealing conditions influence microstructure and magnetic performance. By conducting extensive annealing experiments, we identified optimal parameters that balance grain size and texture, improving both magnetic and mechanical properties. This presentation will discuss the methodologies used, including advanced simulation tools, to support the development of NO electrical steels aimed at enhancing energy-efficient applications and promoting a sustainable energy future through optimized materials for electric drives.

10:10 AM
ICME-Driven Design of Modified Ferrium® M54® for Additive Manufacturing: Yu Lin¹; Oleg Kontsevoi¹; Andrea Love¹; Menglei Jiang¹; Abhinav Saboo¹; Thomas Kozmel¹; Diana David¹; ¹QuesTek Innovations LLC
    Additive manufacturing (AM) of high-performance steels offers a promising alternative to conventional materials for rapidly producing aerospace components, potentially reducing or eliminating post-processing steps. However, the unique challenges introduced by AM-specific processing make it difficult to use these steels as direct drop-in replacements. This program aims to advance additive manufacturing of QuesTek’s Ferrium® M54® – an ultrahigh-strength steel for structural aerospace and other applications. QuesTek has conducted initial printing trials for the baseline M54 composition and explored alternative alloy design strategies to improve its behavior and properties in additive manufacturing. Leveraging its Materials by Design® technology, ICME principals, and process-structure and structure-property models on QuesTek’s materials design platform - ICMD®, QuesTek has developed modified M54 variants with enhanced manufacturing properties.

10:30 AM
An Integrated Material Model for ICME-Based Process Simulations: Capturing Plasticity and Damage Evolution in Laser-Assisted Hole Flanging Process: Karthik Ramalingam¹; Christian Haase²; Ulrich Krupp¹; ¹IEHK Institute - RWTH Aachen; ²TU Berlin
    This study presents a material model tailored for Integrated Computational Materials Engineering (ICME)-based process simulations. The model integrates plasticity and damage evolution mechanisms, offering a refined approach to simulate material behavior under complex deformation conditions. Central to this work is the use of evolution equations for dislocation densities, enabling precise tracking of the microstructural state throughout processing and capturing critical interrelationships among process parameters, microstructure, and properties. By simulating the growth of dislocation densities and development of void fractions in each step, the model ensures accurate transfer of deformation history across sequential stages. Implemented for laser-assisted hole flanging—a multistep process where shear cutting and laser heating influence component quality and performance—this model enhances the fidelity of process simulations. Ultimately, it advances ICME by providing a reliable framework for microstructure-sensitive material modeling in thermomechanical processing.

10:50 AM
An Integrated Experimental and Computational Study on the Role of Material Interfaces in Mediating Plastic Flow in Amorphous/Crystalline Composites: Ashraf Bastawros¹; Amir Abdelmawla¹; Liming Xiong²; ¹Iowa State University; ²North Carolina State University
    In this work, we study the deformation behavior in amorphous/crystalline metallic composites (A/C-MCs) through nanoindentation experiments and molecular dynamic (MD) simulations. The atomic deformation processes in both crystalline (C-) and amorphous (A-) phases near the amorphous-crystalline interface (ACI) are investigated and correlated with the material’s overall constitutive behavior at the microscale. Our major findings are (i) the ACIs enable a co-deformation of the A- and C-phases through “stiffening” the soft phases but “softening” the stiff phases in A/C-MCs through different micro-mechanisms; (ii) there exists an ACI-induced transition zone with a thickness of ~ 10 nm; (iii) the strong coupling between shear transformation zones (STZs) and dislocations can be quantified through carefully designed indentation experiments and simulations; and (iv) the nanoscale MD-simulation-predicted mechanisms can be mapped to the “pop-in” or “excursion” events on the force–indentation depth curves extracted from microscale experiments, although there is a length-scale gap in between.