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Liam Huber
Liam Huber
Research Software Consultant @ Grey Haven Solutions
Verified email at greyhavensolutions.com
Title
Cited by
Cited by
Year
A machine learning approach to model solute grain boundary segregation
L Huber, R Hadian, B Grabowski, J Neugebauer
npj Computational Materials 4 (1), 64, 2018
1002018
Atomistic simulations of the interaction of alloying elements with grain boundaries in Mg
L Huber, J Rottler, M Militzer
Acta materialia 80, 194-204, 2014
602014
Ab initio calculations of rare-earth diffusion in magnesium
L Huber, I Elfimov, J Rottler, M Militzer
Physical Review B 85 (14), 144301, 2012
602012
Ab initio modelling of solute segregation energies to a general grain boundary
L Huber, B Grabowski, M Militzer, J Neugebauer, J Rottler
Acta Materialia 132, 138-148, 2017
482017
Interplay of chemistry and faceting at grain boundaries in a model Al alloy
H Zhao, L Huber, W Lu, NJ Peter, D An, F De Geuser, G Dehm, D Ponge, ...
Physical Review Letters 124 (10), 106102, 2020
422020
Basal slip in Laves phases: the synchroshear dislocation
J Guénolé, FZ Mouhib, L Huber, B Grabowski, S Korte-Kerzel
Scripta Materialia 166, 134-138, 2019
412019
Defect phases–thermodynamics and impact on material properties
S Korte-Kerzel, T Hickel, L Huber, D Raabe, S Sandlöbes-Haut, ...
International Materials Reviews 67 (1), 89-117, 2022
262022
A QM/MM approach for low-symmetry defects in metals
L Huber, B Grabowski, M Militzer, J Neugebauer, J Rottler
Computational Materials Science 118, 259-268, 2016
172016
Systematic atomic structure datasets for machine learning potentials: Application to defects in magnesium
M Poul, L Huber, E Bitzek, J Neugebauer
Physical Review B 107 (10), 104103, 2023
82023
Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography
Y Li, Y Wei, Z Wang, X Liu, T Colnaghi, L Han, Z Rao, X Zhou, L Huber, ...
Nature Communications 14 (1), 7410, 2023
52023
Reactions in viscous media: potential and free energy surfaces in solvent–solute coordinates
L Huber, E Edwards, MV Basilevsky, N Weinberg
Molecular Physics 107 (21), 2283-2291, 2009
52009
Insights from symmetry: Improving machine-learned models for grain boundary segregation
Y Borges, L Huber, H Zapolsky, R Patte, G Demange
Computational Materials Science 232, 112663, 2024
22024
Approximating the impact of nuclear quantum effects on thermodynamic properties of crystalline solids by temperature remapping
R Dsouza, L Huber, B Grabowski, J Neugebauer
Physical Review B 105 (18), 184111, 2022
22022
Segregation to interfaces in TiAl alloys: A multiscale QM/MM study
D Gehringer, L Huber, J Neugebauer, D Holec
Physical Review Materials 7 (6), 063604, 2023
12023
Evolutionary algorithms for cardinality-constrained Ising models
VD Bhuva, DC Dang, L Huber, D Sudholt
International Conference on Parallel Problem Solving from Nature, 456-469, 2022
12022
Systematic Structure Datasets for Machine Learning Potentials: Application to Moment Tensor Potentials of Magnesium and its Defects
M Poul, L Huber, E Bitzek, J Neugebauer
Condensed Matter: Materials Science, 2022
12022
Sampling-free computation of finite temperature material properties in isochoric and isobaric ensembles using the mean-field anharmonic bond model
R Dsouza, M Poul, L Huber, TD Swinburne, J Neugebauer
Physical Review B 109 (6), 064108, 2024
2024
Tailoring α2/γ and γ/γ interfaces in TiAl alloys via segregation: A multi-method study
D Gehringer, D Holec, L Huber, J Neugebauer
2023
A Newtonian algorithm for constant pressure molecular dynamics with periodic boundary conditions
N Weinberg, E Edwards, L Huber, Z Sentell, J Spooner
Molecular Physics 120 (10), e2060145, 2022
2022
Simulating the thermodynamics of GB phases
L Huber
Seminar, Institut für Materialswissenschaft (MaWi), University of Stuttgart …, 2021
2021
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