Publications

Submitted

Yang, Q., Sing-Long, C. A., Reed, E. J., Rapid Data-driven Model Reduction of Nonlinear Dynamical Systems including Chemical Reaction Networks Using L1-Regularization.

Krishnapriyan, A., Yang, Q., Zhou, Y., Cubuk, E. D., Sinclair, R., Reed, E. J., Nucleation Kinetics of Structural Phase Changes in Two-Dimensional Transition Metal Dichalcogenides.

Journals

Chen, E., Yang, Q., Decieux, V. D., Sing-Long, C. A., Freitas, R., Reed, E. J., Transferable Kinetic Monte Carlo Models with Thousands of Reactions Learned from Molecular Dynamics Simulations. The Journal of Physical Chemistry A, doi:10.1021/acs/jpca.8b09947 (2019).

Yang, Q., Sing-Long, C. A., Reed, E. J., Learning Reduced Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics. Chemical Science, doi:10.1039/C7SC01052D (2017).

Sendek, A. D., Yang, Q., Cubuk, E. D., Duerloo, K.-A. N., Cui, Y., Reed, E. J., Holistic Computational Structure Screening of more than 12,000 Candidates for Solid Lithium-ion Conductor Materials. Energy & Environmental Science, doi:10.1039/C6EE02697D (2016).

Yang, Q., Sing-Long, C. A., Reed, E. J., L1 Regularization-Based Model Reduction of Complex Chemistry Molecular Dynamics for Statistical Learning of Kinetic Monte Carlo Models. MRS Advances, doi:10.1557/adv.2016.124 (2016).

Conferences and Workshops

Yang, Q., Raju, M., Ihme, M., Reed, E. J., Machine Learning-Enabled Study of Proton Transfer Reaction Mechanisms on Titania Surfaces. NIPS Workshop on Machine Learning for Molecules and Materials (2017).

Yang Q., Diephuis B., Chu V., Forth, K. E., iBALANCE - Hardware and Software Design for a Mobile Diagnostic Device that Assesses Human Balance. Proceedings of the International Conference on Health Informatics, doi:10.5220/0003174001070114 (2011).

Book Chapters

Yang, Q., Sing-Long, C. A., Chen, E., Reed, E. J., Data-Driven Methods for Building Reduced Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations. In N. Goldman (Ed.), Computational Approaches for Chemistry Under Extreme Conditions. Springer, 28 (2019). ISBN 978-3-030-05600-1.