Plain text, RIS, BibTex 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 Journal of Catalysis 453, 2026 DOI BibTeX T. Benešová, K. Pokorná, A. Erlebach and C. J. Heard Mobility and sintering of silica-supported platinum clusters via reactive neural network potentials Journal of Catalysis 453, 2026 DOI BibTeX H. Windeck, D. Willimetz, A. Erlebach, C. J. Heard, L. Grajciar, F. Berger and J. Sauer Water Adsorption at Pairs of Proximate Brønsted Acid Sites in Zeolites The Journal of Physical Chemistry Letters 17(4), 2026 DOI BibTeX T. Benešová, K. Pokorná, A. Erlebach and C. J. Heard Mobility and sintering of silica-supported platinum clusters via reactive neural network potentials Journal of Catalysis 453, 2026 DOI BibTeX 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 255, 2025 DOI BibTeX 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 4(1), 2025 DOI BibTeX 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 255, 2025 DOI BibTeX 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, 2025 DOI BibTeX 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 15(1), 2024 DOI BibTeX C. J. Heard, L. Grajciar and A. Erlebach Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials Nanoscale 16(16), 2024 DOI BibTeX 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, 2024 DOI BibTeX I. Saha, A. Erlebach, P. Nachtigall, C. J. Heard and L. Grajciar Germanium distributions in zeolites derived from neural network potentials Catalysis Science & Technology, 2024 DOI BibTeX C. J. Heard, L. Grajciar and A. Erlebach Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials Nanoscale 16(16), 2024 DOI BibTeX 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, 2024 DOI BibTeX 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. 14, 2023 DOI BibTeX 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. 14, 2023 DOI BibTeX M. Sipka, A. Erlebach and L. Grajciar Constructing Collective Variables Using Invariant Learned Representations Journal of Chemical Theory and Computation (PMID: 36696574) 19(3), 2023 DOI BibTeX A. Erlebach, P. Nachtigall and L. Grajciar Accurate large-scale simulations of siliceous zeolites by neural network potentials npj Computational Materials 8(1), 2022 DOI BibTeX
