Isaac Tamblyn
Isaac Tamblyn
University of Ottawa & University of Waterloo
Verified email at - Homepage
Cited by
Cited by
A massive core in Jupiter predicted from first-principles simulations
B Militzer, WB Hubbard, J Vorberger, I Tamblyn, SA Bonev
The Astrophysical Journal Letters 688 (1), L45, 2008
Hydrogen-helium mixtures in the interiors of giant planets
J Vorberger, I Tamblyn, B Militzer, SA Bonev
Physical Review B 75 (2), 024206, 2007
Deep learning and the Schrödinger equation
K Mills, M Spanner, I Tamblyn
Physical Review A 96 (4), 042113, 2017
Structure and phase boundaries of compressed liquid hydrogen
I Tamblyn, SA Bonev
Physical review letters 104 (6), 65702, 2010
Relating Energy Level Alignment and Amine-Linked Single Molecule Junction Conductance
M Dell’Angela, G Kladnik, A Cossaro, A Verdini, M Kamenetska, ...
Nano letters, 2010
Molecular adsorption on metal surfaces with van der Waals density functionals
G Li, I Tamblyn, VR Cooper, HJ Gao, JB Neaton
Physical Review B 85 (12), 121409, 2012
Tetrahedral clustering in molten lithium under pressure
I Tamblyn, JY Raty, SA Bonev
Physical review letters 101 (7), 075703, 2008
Electronic energy level alignment at metal-molecule interfaces with a GW approach
I Tamblyn, P Darancet, SY Quek, SA Bonev, JB Neaton
Arxiv preprint arXiv:1111.2569, 2011
Electronic level alignment at a metal-molecule interface from a short-range hybrid functional
A Biller, I Tamblyn, JB Neaton, L Kronik
The Journal of chemical physics 135, 164706, 2011
Quantitative molecular orbital energies within a G 0 W 0 approximation
S Sharifzadeh, I Tamblyn, P Doak, PT Darancet, JB Neaton
The European Physical Journal B 85 (9), 1-5, 2012
Simultaneous determination of structures, vibrations, and frontier orbital energies from a self-consistent range-separated hybrid functional
I Tamblyn, S Refaely-Abramson, JB Neaton, L Kronik
The journal of physical chemistry letters 5 (15), 2734-2741, 2014
Deep learning and density-functional theory
K Ryczko, DA Strubbe, I Tamblyn
Physical Review A 100 (2), 022512, 2019
Common physical framework explains phase behavior and dynamics of atomic, molecular, and polymeric network formers
S Whitelam, I Tamblyn, TK Haxton, MB Wieland, NR Champness, ...
Physical Review X 4 (1), 011044, 2014
Convolutional neural networks for atomistic systems
K Ryczko, K Mills, I Luchak, C Homenick, I Tamblyn
Computational Materials Science 149, 134-142, 2018
Prebiotic chemistry within a simple impacting icy mixture
N Goldman, I Tamblyn
The Journal of Physical Chemistry A 117 (24), 5124-5131, 2013
Theory of covalent adsorbate frontier orbital energies on functionalized light-absorbing semiconductor surfaces
M Yu, P Doak, I Tamblyn, JB Neaton
The journal of physical chemistry letters 4 (10), 1701-1706, 2013
Random and ordered phases of off-lattice rhombus tiles
S Whitelam, I Tamblyn, PH Beton, JP Garrahan
Physical review letters 108 (3), 035702, 2012
Extensive deep neural networks for transferring small scale learning to large scale systems
K Mills, K Ryczko, I Luchak, A Domurad, C Beeler, I Tamblyn
Chemical science 10 (15), 4129-4140, 2019
Deep neural networks for direct, featureless learning through observation: The case of two-dimensional spin models
K Mills, I Tamblyn
Physical Review E 97 (3), 032119, 2018
Ab initio calculations of the equation of state of hydrogen in a regime relevant for inertial fusion applications
MA Morales, LX Benedict, DS Clark, E Schwegler, I Tamblyn, SA Bonev, ...
High Energy Density Physics 8 (1), 5-12, 2012
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