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MIT Short Course: Machine Learning for Materials Informatics (Jul 29 - Aug 2, 2024)

Submitted by Markus J. Buehler on

Dera iMechanica Community,

Below is information about a short course I will be offering at MIT this summer, in Live Virtual format: Machine Learning for Materials Informatics (Jul 29 - Aug 2, 2024).  This is an exciting opportunity that will cover fundamentals and applications in the emerging space of AI/ML for engineering, featuring hands-on interactive code development in Jupyter notebooks. We'll do a deep dive into all critical tools from autoencoders to graph neural nets to multimodal LLMs and multi-agent modeling. Please reach out to me if you have any questions.

Length scale insensitive phase-field fracture methodology for brittle and ductile materials

Submitted by mohsenzaeem on

Dear colleagues, I would like to share our new article (open access) that presents length scale insensitive phase-field fracture models for brittle and ductile fracture to address the deficiencies of the widely implemented models which over-estimate crack dissipation. 

A phase-field model for study of ferroelastic deformation behavior in yttria stabilized zirconia

Submitted by mohsenzaeem on

Dear colleagues, our new article (open access) is just published in Acta Materialia. In this research, we provide new insights into the mechanism of ferroelastic deformation by studying the evolution of domains in different microstructure patterns and under different loading directions and strain rates.

A. Bhattacharya and M. Asle Zaeem. A phase-field model for study of ferroelastic deformation behavior in yttria stabilized zirconia. Acta Materialia (2024) 120039.

PhD position: Machine Learning and Finite Element Modeling

Submitted by HamidAbdolvand on

We are looking for an enthusiastic student with a MSc degree to conduct research in the area of Machine Learning and finite element modelling of materials. Students with a degree in mechanical or materials engineering or mathematics are encouraged to apply.

 

Prospective candidates will be assessed based on how well they meet the following criteria:

Excellent degree in their relevant discipline.

Excellent written and spoken communication skills.

 

The following skills are desirable:

Computational morphology and morphogenesis for empowering soft-matter engineering

Submitted by Fan Xu on

Morphing soft matter, which is capable of changing its shape and function in response to stimuli, has wide-ranging applications in robotics, medicine and biology. Recently, computational models have accelerated its development. Here, we highlight advances and challenges in developing computational techniques, and explore the potential applications enabled by such models.

Yifan Yang, Fan Xu*

Nature Computational Science, 2024, https://doi.org/10.1038/s43588-024-00647-y

Universal Deformations and Inhomogeneities in Isotropic Cauchy Elasticity

Submitted by arash_yavari on

For a given class of materials, universal deformations are those deformations that can be maintained in the absence of body forces and by applying solely boundary tractions. For inhomogeneous bodies, in addition to the universality constraints that determine the universal deformations, there are extra constraints on the form of the material inhomogeneities—universal inhomogeneity constraints. Those inhomogeneities compatible with the universal inhomogeneity constraints are called universal inhomogeneities.

Funded M.S. and Ph.D. Student Positions in Additive Manufacturing

Submitted by Jun Li on

The Advanced Manufacturing Research Group in the Department of Aerospace Engineering at Embry-Riddle Aeronautical University (ERAU) invites applications for multiple fully supported M.S. and Ph.D. student positions starting in Fall 2024 / Spring 2025. Our current interdisciplinary research projects focus on next-generation additive manufacturing of high-performance composite materials (experiments and modeling) with various applications in aerospace, automotive, electronics, and biomedical industries.