Solving our society's issues in energy, water, environment, and health necessitates discovery of new materials and chemistry. Establishing structure-property relationships is key to realizing materials' functions for renewable energy, clean water and environment, and biomedical applications. Advances in theoretical understanding, algorithms, computational power, big data, artificial intelligence and machine learning are propelling computational tools to an increasing role in materials design, discovery, development, and optimization. One important goal is to achieve predictive modeling of materials synthesis, property, function, evolution, and lifecycle.
This workshop aims to bring together computational scientists working on focused topics of materials chemistry to exchange ideas and to stimulate discussion. The 2023 workshop will concentrate on predictive modeling of reactions in condensed phases that underlie materials synthesis, property, function, and evolution. Topics include, but are not limited to, solvation effects and models, sampling and free-energy simulations, catalysis in liquid phases, and interfacial phenomena. This workshop will provide a unique opportunity for the participants to broaden their view and deepen their understanding of important issues, challenges, and recent progress toward predictive modeling of chemistry of materials.
We wish to ensure an intimate workshop setting, with no more than 20 to 25 participants. If you are interested in attending, but have not received an invitation, please contact the workshop organizer before registering.
Telluride Science is about expanding the frontiers of science, exploring new ideas, and building collaborations. The workshop schedule will allow for substantial unstructured time for participants to talk and think. All participants are expected to stay for the entire duration of the workshop. Scientists are encouraged to consider bringing family or friends. Telluride offers a number of options for children's camps (including Telluride Academy, Aha School for the Arts, and Pinhead Institute). There is more information on childcare, camps, and family activities on Telluride Science's website. Feel free to contact Telluride Science's staff to help with any planning and/or coordinating care.
Telluride Intermediate School
721 W Colorado Ave Telluride CO 81435
Click Here for Directions
Workshop Price: $ 449.00
Early Bird Lodging Discount Available Until: 02/01/2023
A $100.00 discount is applied to your lodging cost when you register before 02/01/2023.Cancellation Policy: Once a credit card has been charged, cancelled registrations will be subject to a cancellation fee. Registration fees will be automatically processed once registration is complete. A $25 cancellation fee will be retained from a registration refund. Lodging fee payments will be processed 60 days prior to arrival, and a $100 cancellation fee will apply if cancellations occur after a lodging fee payment is completed. Telluride Science can only guarantee a refund for the remaining lodging fees if requested prior to the cancellation deadline that is specific to each lodging provider. Telluride Science recommends that participants purchase travel insurance to protect against unforeseen, last-minute travel plan changes.
|Árnadóttir, Líney||Oregon State University|
|Beran, Gregory||University of California Riverside|
|Cho, Jaeyoung||University of Texas at Austin|
|Hammer, Bjørk||Aarhus University|
|Henkelman, Graeme||University of Texas at Austin|
|Janik, Michael||Pennsylvania State University|
|Jiang, De-en||Vanderbilt University|
|Keith, John||University of Pittsburgh|
|Kim, Seonah||Colorado State University|
|Liu, Yuanyue||University of Texas at Austin|
|Neugebauer, Joerg||Max-Planck-Institut fuer Eisenforschung|
|Qi, Yue||Brown University|
|Reuter, Karsten||Fritz-Haber-Institut der MPG|
|Schneider, William F||University of Notre Dame|
|Sun, Yujie||University of Cincinnati|
|Sundararaman, Ravishankar||Rensselaer Polytechnic Institute|
|Todorova, Mira||MPI fuer Eisenforschung|
|Ulissi, Zachary||Meta Fundamental AI Research|
|Wang, Bin||University of Oklahoma|
|Wang, Wennie||University of Texas at Austin|
|Wippermann, Stefan||Marburg University|
|Yang, Zhongyue||Vanderbilt University|
|Zimmerman, Paul||University of Michigan|