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. Faraday Discussions, Royal Society of Chemistry (RSC), volume 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. Digital Discovery, Royal Society of Chemistry (RSC), 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. Nature Communications, Springer Science and Business Media LLC, volume 15, issue 1, May 2024.

C. J. Heard, L. Grajciar, and A. Erlebach. Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials. Nanoscale, Royal Society of Chemistry (RSC), volume 16, issue 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. Faraday Discussions, Royal Society of Chemistry (RSC), 2024.

I. Saha, A. Erlebach, P. Nachtigall, C. J. Heard, and L. Grajciar. Germanium distributions in zeolites derived from neural network potentials. Catalysis Science & Technology, Royal Society of Chemistry (RSC), 2024.

C. J. Heard, L. Grajciar, and A. Erlebach. Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials. Nanoscale, Royal Society of Chemistry (RSC), volume 16, issue 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. Digital Discovery, RSC, 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. Chem. Sci., The Royal Society of Chemistry, volume 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. Chem. Sci., The Royal Society of Chemistry, volume 14, 2023.

M. Sipka, A. Erlebach, and L. Grajciar. Constructing Collective Variables Using Invariant Learned Representations. Journal of Chemical Theory and Computation, volume 19, issue 3, 2023.

A. Erlebach, P. Nachtigall, and L. Grajciar. Accurate large-scale simulations of siliceous zeolites by neural network potentials. npj Computational Materials, volume 8, issue 1, August 2022.