Journal Articles by A. Erlebach
T. Benešová,
K. Pokorná,
A. Erlebach and
C. J. Heard
Mobility and sintering of silica-supported platinum clusters via reactive neural network potentials
Mobility and sintering of silica-supported platinum clusters via reactive neural network potentials
Journal of Catalysis,
453,
2026
C. Lei,
C. Bornes,
O. Bengtsson,
A. Erlebach,
B. Slater,
L. Grajciar and
C. J. Heard
A machine learning approach for dynamical modelling of Al distributions in zeolites via23Na/27Al solid-state NMR
A machine learning approach for dynamical modelling of Al distributions in zeolites via23Na/27Al solid-state NMR
Faraday Discussions,
255,
2025
D. Willimetz,
A. Erlebach,
C. J. Heard and
L. Grajciar
27Al NMR chemical shifts in zeolite MFI via machine learning acceleration of structure sampling and shift prediction
27Al NMR chemical shifts in zeolite MFI via machine learning acceleration of structure sampling and shift prediction
Digital Discovery,
4(1),
2025
C. Lei,
C. Bornes,
O. Bengtsson,
A. Erlebach,
B. Slater,
L. Grajciar and
C. J. Heard
A machine learning approach for dynamical modelling of Al distributions in zeolites via23Na/27Al solid-state NMR
A machine learning approach for dynamical modelling of Al distributions in zeolites via23Na/27Al solid-state NMR
Faraday Discussions,
255,
2025
D. Willimetz,
A. Erlebach,
C. J. Heard and
L. Grajciar
27Al NMR chemical shifts in zeolite MFI via machine learning acceleration of structure sampling and shift prediction
27Al NMR chemical shifts in zeolite MFI via machine learning acceleration of structure sampling and shift prediction
Digital Discovery,
2025
A. Erlebach,
M. Šípka,
I. Saha,
P. Nachtigall,
C. J. Heard and
L. Grajciar
A reactive neural network framework for water-loaded acidic zeolites
A reactive neural network framework for water-loaded acidic zeolites
Nature Communications,
15(1),
2024
C. J. Heard,
L. Grajciar and
A. Erlebach
Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials
Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials
Nanoscale,
16(16),
2024
C. Lei,
C. Bornes,
O. Bengtsson,
A. Erlebach,
B. Slater,
L. Grajciar and
C. J. Heard
A machine learning approach for dynamical modelling of Al distributions in zeolites via23Na/27Al solid-state NMR
A machine learning approach for dynamical modelling of Al distributions in zeolites via23Na/27Al solid-state NMR
Faraday Discussions,
2024
I. Saha,
A. Erlebach,
P. Nachtigall,
C. J. Heard and
L. Grajciar
Germanium distributions in zeolites derived from neural network potentials
Germanium distributions in zeolites derived from neural network potentials
Catalysis Science & Technology,
2024
C. J. Heard,
L. Grajciar and
A. Erlebach
Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials
Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials
Nanoscale,
16(16),
2024
D. Willimetz,
A. Erlebach,
C. J. Heard and
L. Grajciar
27Al NMR chemical shifts in zeolite MFI via machine learning acceleration of structure sampling and shift prediction.
27Al NMR chemical shifts in zeolite MFI via machine learning acceleration of structure sampling and shift prediction.
Digital Discovery,
2024
C. Lei,
A. Erlebach,
F. Brivio,
L. Grajciar,
Z. Tošner,
C. J. Heard and
P. Nachtigall
The need for operando modelling of 27Al NMR in zeolites: the effect of temperature, topology and water
The need for operando modelling of 27Al NMR in zeolites: the effect of temperature, topology and water
Chem. Sci.,
14,
2023
C. Lei,
A. Erlebach,
F. Brivio,
L. Grajciar,
Z. Tosner,
C. J. Heard and
P. Nachtigall
The need for operando modelling of 27Al NMR in zeolites: the effect of temperature, topology and water
The need for operando modelling of 27Al NMR in zeolites: the effect of temperature, topology and water
Chem. Sci.,
14,
2023
M. Sipka,
A. Erlebach and
L. Grajciar
Constructing Collective Variables Using Invariant Learned Representations
Constructing Collective Variables Using Invariant Learned Representations
Journal of Chemical Theory and Computation (PMID: 36696574),
19(3),
2023
A. Erlebach,
P. Nachtigall and
L. Grajciar
Accurate large-scale simulations of siliceous zeolites by neural network potentials
Accurate large-scale simulations of siliceous zeolites by neural network potentials
npj Computational Materials,
8(1),
2022