Orbital Materials is proud to host these exclusive events designed to showcase the potential of our newly released neural network potential, Orb. Across these seminars, we aim to promote groundbreaking work in computational chemistry and materials development and demonstrate the power of AI in advancing this field. You’ll have the opportunity to hear from world-class researchers doing research at the intersection of materials science, machine learning and computational chemistry - with some even sharing the results they’ve achieved using our Orb model.
Whether you’re an AI enthusiast, a materials scientist, or simply curious about the transformative possibilities of machine learning in this space, this seminar series is not to be missed.
Date: November 8, 2024
Speakers:
Marcel Langer will present his research on the effects of symmetry-breaking in non-equivariant machine learning potentials, while Jonathan Schmidt will showcase Alexandria, a new large-scale materials dataset.
Date: November 15, 2024
Speaker:
Discover how AI can solve some of the longest-standing challenges in physical chemistry. Tim Duignan will demonstrate the remarkable accuracy of the Orb model in simulating electrolyte solutions, an essential element in fields ranging from biology to chemical engineering.
Event 3: Training and Scaling Strategies for Neural Network Potentials
Date: November 21, 2024
Speakers:
This final event in the series will explore various training and scaling strategies for neural network potentials, with Yi-Lun Liao and Aditi Krishnapriyan presenting their latest research on their findings.
These events are free to attend, but spaces are limited. To secure your place, please register via Eventbrite:
Stay ahead in the world of AI-driven materials science by joining us and see how Orbital Materials and our Orb model are leading the charge in the next generation of technological innovation.
