Machine Learning for Materials Informatics
Instructor: Prof. Markus J Buehler, mbuehler [at] MIT.EDU (mbuehler[at]MIT[dot]EDU)
Jul 28 - Jul 31, 2025 (3.5 days)
Learn more here: https://professional.mit.edu/course-catalog/machine-learning-materials-informatics (link to sign-up there)
Dear Colleagues
I have been playing with a very good student from Berlin with the idea that a temperature gradient along the depth of the tire could help reduce wear significantly. We all know that there is an optimal range of temperature for friction and wear --- much less known is an optimal "temperature gradient". I hope you find this study a good starting point on this idea. Maybe somebody wants to explore how to patent it!
https://lnkd.in/d5nibSYN
Mike
It is known that the balance laws of hyperelasticity (Green elasticity), i.e., conservation of mass and balance of linear and angular momenta, can be derived using the first law of thermodynamics and by postulating its invariance under superposed rigid body motions of the Euclidean ambient space---the Green-Naghdi-Rivlin theorem. In the case of a non-Euclidean ambient space, covariance of the energy balance---its invariance under arbitrary time-dependent diffeomorphisms of the ambient space---gives all the balance laws and the Doyle-Ericksen formula---the Marsden-Hughes theorem.
In this article, we are introducing a new analysis tool to identify material constants of viscoelastic problems.
J. Datta et al., Generative AI for Discovering Porous Oxide Materials for Next-Generation Energy Storage, Cell Reports Physical Science, 2025 [PDF]
Amit Acharya Ambar N. Sengupta
A method for designing variational principles for the dynamics of a possibly dissipative and non-conservatively forced chain of particles is demonstrated. Some qualitative features of the formulation are discussed.
In: Springer Proceedings in Mathematics and Statistics, Proceedings of the Conference on Continuum Mechanics and Discrete Systems 14 (CMDS-14), ed. F. Willot, J. Dirrenberger, S. Forest, D. Jeulin, A. Cherkaev, v. 457, 195-200, 2024 (published online, 2023).
As a type of shape-programmable soft materials, hard-magnetic soft materials (HMSMs) exhibit rapid and reversible deformations under applied magnetic fields, showing promise for soft robotics, flexible electronics, and biomedical devices. The realization of various controllable shape transformations is crucial to the rational design of relevant applications.
The research group Mechanics of Materials and Structures at Ghent University (UGent-MMS) has 4 vacancies for PhD and postdoc research in the field of fibre-reinforced composites. The vacancies are linked to research on composite hydrogen tanks, composite propellers for drones and finite element modelling of textile manufacturing. All research will be conducted with leading companies in the field.
More information can be found on
