August 15-16, 2024
09:00 am - 5:00 pm EDT
Quantum dynamics and nonadiabatic molecular dynamics (NA-MD) simulations can provide comprehensive insights into many photophysical and photochemical processes in a broad class of materials and natural systems. However, the complexity of such methods that comes both from the exponential scaling due to the multitude of wavepacket branching outcomes and from the steep computational demands of the underlying electronic structure calculations makes prohibitively expensive, especially when applied to nanoscale or periodic systems. Recently, machine-learning (ML) techniques have revolutionized various branches of computational chemistry and simulated the development of new approaches to handle complexity of quantum or quantum-classical simulation methods, study nanoscale systems, and investigate long timescale dynamics. Several seemingly-disjoint sub-communities of computational chemistry, such as “electronic structure”, “quantum/nonadiabatic dynamics”, and “materials”, all utilize a broad spectrum of specialized ML techniques. However, the unified underlying formalism of ML-based methods implies that the techniques and software developed by one of these groups may be re-used by the other groups. Exchanging the accumulated experiences, best practices, and developed software has a great potential to stimulate further progress in each of the identified fields. Breaking the inter-disciplinary boundaries of the sub-communities and unifying them through their shared interest in the ML can lead to new ideas and solutions.
This workshop will facilitate the exchange of ideas and promote the adoption of existing and developing software in the field of Quantum and Nonadiabatic dynamics. It aims to help the community experts to get a better awareness of the existing developments. The workshop is a melting pot of experts working in one of the three branches: (1) ML-centric material research chemistry practitioners; (2) electronic structure ML practitioners; (3) quantum/nonadiabatic dynamics ML practitioners. It is our expectation that all these groups will be able to “educate” each other, disseminate and promote the best practices and tools, and raise the present-day challenges they face.
When: August 15-16, 2024. Add to your Google Calendar.
Where: University at Buffalo, SUNY, North Campus, Natural Sciences Complex. Get directions with OpenStreetMap or Google Maps.
Contact: Please email alexeyak@buffalo.edu for more information.
Arrivals and Welcome dinner.
| Time | Name | Topic |
|---|---|---|
| 9:00 am - 9:15 am | Alexey Akimov | Introductory remarks |
| 9:15 am - 10:00 am | Daniel Crawford | MolSSI presentation |
| 10:00 am - 10:40 am | Zhenggang Lan (remote) | Research presentation |
| 10:40 am - 11:20 am | Maksim Kulichenko | Research presentation |
| 11:20 am - 12:00 am | Rafael Gomez-Bombarelli (remote) | Research presentation |
| Noon - 1:30 pm | Lunch break | |
| 1:30 pm - 2:10 pm | Michele Pavanello | Research presentation |
| 2:10 pm - 2:50 pm | Mark Tuckerman | Research presentation |
| 2:50 pm - 3:30 pm | Nitin Murthy (Johannes Hachmann group) | |
| 3:30 pm - 4:10 pm | Mohammad Shakiba (Alexey Akimov group) | Research presentation |
| 4:10 pm - 5:00 pm | Discussions |
| Time | Name | Topic |
|---|---|---|
| 9:00 am - 9:40 am | Pavlo Dral (remote) | Research presentation |
| 9:40 am - 10:20 am | Linjun Wang (remote) | Research presentation |
| 10:20 am - 11:00 am | Xiang Sun (remote) | Research presentation |
| 11:00 am - 11:40 am | Alexei Kananenka | Research presentation |
| 11:40 am - 12:00 am | Discussions | |
| Noon - 1:30 pm | Lunch break | |
| 1:30 pm - 2:10 pm | Alexey Akimov | Research presentation |
| 2:10 pm - 2:50 pm | Oleg Prezhdo | Research presentation |
| 2:50 pm - 3:30 pm | Dmitri Kilin | Research presentation |
| 3:30 pm - 4:10 pm | Johannes Hachmann (remote) | Research presentation |
| 4:10 pm - 5:50 pm | Closing remarks. Discussions |
Departures.
This workshop is made possible by the NSF MolSSI program. Thank you!