[{"author":[{"first_name":"Diethelm","last_name":"Johannsmann","full_name":"Johannsmann, Diethelm"},{"last_name":"Häusner","full_name":"Häusner, Paul","first_name":"Paul"},{"last_name":"Langhoff","full_name":"Langhoff, Arne","first_name":"Arne"},{"first_name":"Christian","last_name":"Leppin","id":"117722","full_name":"Leppin, Christian"},{"first_name":"Ilya","full_name":"Reviakine, Ilya","last_name":"Reviakine"},{"last_name":"Vanoppen","full_name":"Vanoppen, Viktor","first_name":"Viktor"}],"volume":8,"date_updated":"2025-12-18T17:46:34Z","doi":"10.1002/adts.202401373","publication_status":"published","publication_identifier":{"issn":["2513-0390","2513-0390"]},"citation":{"chicago":"Johannsmann, Diethelm, Paul Häusner, Arne Langhoff, Christian Leppin, Ilya Reviakine, and Viktor Vanoppen. “The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples.” <i>Advanced Theory and Simulations</i> 8, no. 7 (2025). <a href=\"https://doi.org/10.1002/adts.202401373\">https://doi.org/10.1002/adts.202401373</a>.","ieee":"D. Johannsmann, P. Häusner, A. Langhoff, C. Leppin, I. Reviakine, and V. Vanoppen, “The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples,” <i>Advanced Theory and Simulations</i>, vol. 8, no. 7, Art. no. 2401373, 2025, doi: <a href=\"https://doi.org/10.1002/adts.202401373\">10.1002/adts.202401373</a>.","ama":"Johannsmann D, Häusner P, Langhoff A, Leppin C, Reviakine I, Vanoppen V. The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples. <i>Advanced Theory and Simulations</i>. 2025;8(7). doi:<a href=\"https://doi.org/10.1002/adts.202401373\">10.1002/adts.202401373</a>","mla":"Johannsmann, Diethelm, et al. “The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples.” <i>Advanced Theory and Simulations</i>, vol. 8, no. 7, 2401373, Wiley, 2025, doi:<a href=\"https://doi.org/10.1002/adts.202401373\">10.1002/adts.202401373</a>.","short":"D. Johannsmann, P. Häusner, A. Langhoff, C. Leppin, I. Reviakine, V. Vanoppen, Advanced Theory and Simulations 8 (2025).","bibtex":"@article{Johannsmann_Häusner_Langhoff_Leppin_Reviakine_Vanoppen_2025, title={The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples}, volume={8}, DOI={<a href=\"https://doi.org/10.1002/adts.202401373\">10.1002/adts.202401373</a>}, number={72401373}, journal={Advanced Theory and Simulations}, publisher={Wiley}, author={Johannsmann, Diethelm and Häusner, Paul and Langhoff, Arne and Leppin, Christian and Reviakine, Ilya and Vanoppen, Viktor}, year={2025} }","apa":"Johannsmann, D., Häusner, P., Langhoff, A., Leppin, C., Reviakine, I., &#38; Vanoppen, V. (2025). The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples. <i>Advanced Theory and Simulations</i>, <i>8</i>(7), Article 2401373. <a href=\"https://doi.org/10.1002/adts.202401373\">https://doi.org/10.1002/adts.202401373</a>"},"intvolume":"         8","user_id":"117722","_id":"63223","article_number":"2401373","article_type":"original","type":"journal_article","status":"public","date_created":"2025-12-18T16:57:22Z","publisher":"Wiley","title":"The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples","issue":"7","quality_controlled":"1","year":"2025","language":[{"iso":"eng"}],"publication":"Advanced Theory and Simulations","abstract":[{"lang":"eng","text":"<jats:title>Abstract</jats:title><jats:p>The quartz crystal microbalance with dissipation monitoring (QCM‐D) is routinely used to investigate structured samples. Here, a simulation technique is described, that predicts the shifts of frequency and half bandwidth, Δ<jats:italic>f<jats:sub>n</jats:sub></jats:italic> and ΔΓ<jats:italic><jats:sub>n</jats:sub></jats:italic>, of a quartz resonator operating on different overtone orders, <jats:italic>n</jats:italic>, induced by structured samples in contact with the resonator surface in liquid. The technique, abbreviated as FreqD‐LBM, solves the Stokes equation in the frequency domain. The solution provides the complex amplitude of the area‐averaged tangential stress at the resonator surface, from which Δ<jats:italic>f<jats:sub>n</jats:sub></jats:italic> and ΔΓ<jats:italic><jats:sub>n</jats:sub></jats:italic> are derived. Because the dynamical variables are complex amplitudes, the viscosity can be complex, as well. The technique naturally covers viscoelasticity. Limitations are linked to the grid resolution and to problems at large viscosity. Validation steps include viscoelastic films, rough surfaces, an oscillating cylinder in a viscous medium, and a free‐floating sphere above the resonator. Application examples are soft adsorbed particles, stiff adsorbed particles, and a large, immobile spherical cap above the resonator, which allows to study the high‐frequency properties of the material in the gap. FreqDLBM runs on an office PC and does not require expert knowledge of numerical techniques. It is accessible to an experimentalist.</jats:p>"}]},{"citation":{"mla":"Johannsmann, Diethelm, et al. “Stiffness of Contacts between Adsorbed Particles and the Surface of a QCM‐D Inferred from the Adsorption Kinetics and a Frequency‐Domain Lattice Boltzmann Simulation.” <i>Advanced Theory and Simulations</i>, vol. 6, no. 11, 2300190, Wiley, 2023, doi:<a href=\"https://doi.org/10.1002/adts.202300190\">10.1002/adts.202300190</a>.","short":"D. Johannsmann, C. Leppin, A. Langhoff, Advanced Theory and Simulations 6 (2023).","bibtex":"@article{Johannsmann_Leppin_Langhoff_2023, title={Stiffness of Contacts between Adsorbed Particles and the Surface of a QCM‐D Inferred from the Adsorption Kinetics and a Frequency‐Domain Lattice Boltzmann Simulation}, volume={6}, DOI={<a href=\"https://doi.org/10.1002/adts.202300190\">10.1002/adts.202300190</a>}, number={112300190}, journal={Advanced Theory and Simulations}, publisher={Wiley}, author={Johannsmann, Diethelm and Leppin, Christian and Langhoff, Arne}, year={2023} }","apa":"Johannsmann, D., Leppin, C., &#38; Langhoff, A. (2023). Stiffness of Contacts between Adsorbed Particles and the Surface of a QCM‐D Inferred from the Adsorption Kinetics and a Frequency‐Domain Lattice Boltzmann Simulation. <i>Advanced Theory and Simulations</i>, <i>6</i>(11), Article 2300190. <a href=\"https://doi.org/10.1002/adts.202300190\">https://doi.org/10.1002/adts.202300190</a>","ama":"Johannsmann D, Leppin C, Langhoff A. Stiffness of Contacts between Adsorbed Particles and the Surface of a QCM‐D Inferred from the Adsorption Kinetics and a Frequency‐Domain Lattice Boltzmann Simulation. <i>Advanced Theory and Simulations</i>. 2023;6(11). doi:<a href=\"https://doi.org/10.1002/adts.202300190\">10.1002/adts.202300190</a>","chicago":"Johannsmann, Diethelm, Christian Leppin, and Arne Langhoff. “Stiffness of Contacts between Adsorbed Particles and the Surface of a QCM‐D Inferred from the Adsorption Kinetics and a Frequency‐Domain Lattice Boltzmann Simulation.” <i>Advanced Theory and Simulations</i> 6, no. 11 (2023). <a href=\"https://doi.org/10.1002/adts.202300190\">https://doi.org/10.1002/adts.202300190</a>.","ieee":"D. Johannsmann, C. Leppin, and A. Langhoff, “Stiffness of Contacts between Adsorbed Particles and the Surface of a QCM‐D Inferred from the Adsorption Kinetics and a Frequency‐Domain Lattice Boltzmann Simulation,” <i>Advanced Theory and Simulations</i>, vol. 6, no. 11, Art. no. 2300190, 2023, doi: <a href=\"https://doi.org/10.1002/adts.202300190\">10.1002/adts.202300190</a>."},"intvolume":"         6","publication_status":"published","publication_identifier":{"issn":["2513-0390","2513-0390"]},"doi":"10.1002/adts.202300190","author":[{"first_name":"Diethelm","last_name":"Johannsmann","full_name":"Johannsmann, Diethelm"},{"last_name":"Leppin","id":"117722","full_name":"Leppin, Christian","first_name":"Christian"},{"full_name":"Langhoff, Arne","last_name":"Langhoff","first_name":"Arne"}],"volume":6,"date_updated":"2025-12-18T17:41:08Z","status":"public","type":"journal_article","extern":"1","article_type":"original","article_number":"2300190","user_id":"117722","_id":"63228","year":"2023","issue":"11","quality_controlled":"1","title":"Stiffness of Contacts between Adsorbed Particles and the Surface of a QCM‐D Inferred from the Adsorption Kinetics and a Frequency‐Domain Lattice Boltzmann Simulation","date_created":"2025-12-18T17:03:12Z","publisher":"Wiley","abstract":[{"text":"<jats:title>Abstract</jats:title><jats:p>A simulation based on the frequency‐domain lattice Boltzmann method (FreqD‐LBM) is employed to predict the shifts of resonance frequency, Δ<jats:italic>f</jats:italic>, and half bandwidth, ΔΓ, of a quartz crystal microbalance with dissipation monitoring (QCM‐D) induced by the adsorption of rigid spheres to the resonator surface. The comparison with the experimental values of Δ<jats:italic>f</jats:italic> and ΔΓ allows to estimate the stiffness of the contacts between the spheres and the resonator surface. The contact stiffness is of interest in contact mechanics, but also in sensing because it depends on the properties of thin films situated between the resonator surface and the sphere. The simulation differs from previous implementations of FreqD‐LBM insofar, as the material inside the particles is not included in the FreqD‐LBM algorithm. Rather, the particle surface is configured to be an oscillating boundary. The amplitude of the particles' motions (displacement and rotation) is governed by the force balance at the surface of the particle. Because the contact stiffness enters this balance, it can be derived from experimental values of Δ<jats:italic>f</jats:italic> and ΔΓ. The simulation reproduces experiments by the Krakow group. For sufficiently small spheres, a contact stiffness can be derived from the comparison of the simulation with the experiment.</jats:p>","lang":"eng"}],"publication":"Advanced Theory and Simulations","language":[{"iso":"eng"}]},{"publication_identifier":{"issn":["2513-0390","2513-0390"]},"publication_status":"published","year":"2021","citation":{"mla":"Kessler, Jan, et al. “Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo.” <i>Advanced Theory and Simulations</i>, 2000269, 2021, doi:<a href=\"https://doi.org/10.1002/adts.202000269\">10.1002/adts.202000269</a>.","short":"J. Kessler, F. Calcavecchia, T.D. Kühne, Advanced Theory and Simulations (2021).","bibtex":"@article{Kessler_Calcavecchia_Kühne_2021, title={Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo}, DOI={<a href=\"https://doi.org/10.1002/adts.202000269\">10.1002/adts.202000269</a>}, number={2000269}, journal={Advanced Theory and Simulations}, author={Kessler, Jan and Calcavecchia, Francesco and Kühne, Thomas D.}, year={2021} }","apa":"Kessler, J., Calcavecchia, F., &#38; Kühne, T. D. (2021). Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo. <i>Advanced Theory and Simulations</i>. <a href=\"https://doi.org/10.1002/adts.202000269\">https://doi.org/10.1002/adts.202000269</a>","ama":"Kessler J, Calcavecchia F, Kühne TD. Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo. <i>Advanced Theory and Simulations</i>. 2021. doi:<a href=\"https://doi.org/10.1002/adts.202000269\">10.1002/adts.202000269</a>","chicago":"Kessler, Jan, Francesco Calcavecchia, and Thomas D. Kühne. “Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo.” <i>Advanced Theory and Simulations</i>, 2021. <a href=\"https://doi.org/10.1002/adts.202000269\">https://doi.org/10.1002/adts.202000269</a>.","ieee":"J. Kessler, F. Calcavecchia, and T. D. Kühne, “Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo,” <i>Advanced Theory and Simulations</i>, 2021."},"date_updated":"2022-01-06T06:55:57Z","date_created":"2021-09-01T09:04:06Z","author":[{"first_name":"Jan","last_name":"Kessler","full_name":"Kessler, Jan"},{"full_name":"Calcavecchia, Francesco","last_name":"Calcavecchia","first_name":"Francesco"},{"last_name":"Kühne","full_name":"Kühne, Thomas D.","first_name":"Thomas D."}],"title":"Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo","doi":"10.1002/adts.202000269","publication":"Advanced Theory and Simulations","type":"journal_article","status":"public","_id":"23598","user_id":"65425","article_number":"2000269","language":[{"iso":"eng"}]},{"year":"2021","issue":"4","title":"Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo","date_created":"2022-10-10T08:15:23Z","publisher":"Wiley","publication":"Advanced Theory and Simulations","language":[{"iso":"eng"}],"keyword":["Multidisciplinary","Modeling and Simulation","Numerical Analysis","Statistics and Probability"],"citation":{"chicago":"Kessler, Jan, Francesco Calcavecchia, and Thomas Kühne. “Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo.” <i>Advanced Theory and Simulations</i> 4, no. 4 (2021). <a href=\"https://doi.org/10.1002/adts.202000269\">https://doi.org/10.1002/adts.202000269</a>.","ieee":"J. Kessler, F. Calcavecchia, and T. Kühne, “Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo,” <i>Advanced Theory and Simulations</i>, vol. 4, no. 4, Art. no. 2000269, 2021, doi: <a href=\"https://doi.org/10.1002/adts.202000269\">10.1002/adts.202000269</a>.","ama":"Kessler J, Calcavecchia F, Kühne T. Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo. <i>Advanced Theory and Simulations</i>. 2021;4(4). doi:<a href=\"https://doi.org/10.1002/adts.202000269\">10.1002/adts.202000269</a>","apa":"Kessler, J., Calcavecchia, F., &#38; Kühne, T. (2021). Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo. <i>Advanced Theory and Simulations</i>, <i>4</i>(4), Article 2000269. <a href=\"https://doi.org/10.1002/adts.202000269\">https://doi.org/10.1002/adts.202000269</a>","bibtex":"@article{Kessler_Calcavecchia_Kühne_2021, title={Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo}, volume={4}, DOI={<a href=\"https://doi.org/10.1002/adts.202000269\">10.1002/adts.202000269</a>}, number={42000269}, journal={Advanced Theory and Simulations}, publisher={Wiley}, author={Kessler, Jan and Calcavecchia, Francesco and Kühne, Thomas}, year={2021} }","short":"J. Kessler, F. Calcavecchia, T. Kühne, Advanced Theory and Simulations 4 (2021).","mla":"Kessler, Jan, et al. “Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo.” <i>Advanced Theory and Simulations</i>, vol. 4, no. 4, 2000269, Wiley, 2021, doi:<a href=\"https://doi.org/10.1002/adts.202000269\">10.1002/adts.202000269</a>."},"intvolume":"         4","publication_status":"published","publication_identifier":{"issn":["2513-0390","2513-0390"]},"doi":"10.1002/adts.202000269","author":[{"last_name":"Kessler","orcid":"0000-0002-8705-6992","id":"65425","full_name":"Kessler, Jan","first_name":"Jan"},{"full_name":"Calcavecchia, Francesco","last_name":"Calcavecchia","first_name":"Francesco"},{"first_name":"Thomas","last_name":"Kühne","id":"49079","full_name":"Kühne, Thomas"}],"volume":4,"date_updated":"2022-10-10T08:15:37Z","status":"public","type":"journal_article","article_number":"2000269","user_id":"71051","department":[{"_id":"613"}],"_id":"33649"},{"_id":"15725","user_id":"71051","article_number":"1900036","language":[{"iso":"eng"}],"type":"journal_article","publication":"Advanced Theory and Simulations","abstract":[{"lang":"eng","text":"Adaptive kinetic Monte Carlo simulation (aKMC) is employed to study the dynamics and the diffusion of point defects in the CuInSe2 lattice. The aKMC results show that lighter alkali atoms can diffuse into the CuInSe2 grains, whereas the diffusion of heavier alkali atoms is limited to the Cu-poor region of the absorber. The key difference between the diffusion of lighter and heavier alkali elements is the energy barrier of the ion exchange between alkali interstitial atoms and Cu. For lighter alkali atoms like Na, the interstitial diffusion and the ion-exchange mechanism have comparable energy barriers. Therefore, Na interstitial atoms can diffuse into the grains and replace Cu atoms in the CuInSe2 lattice. In contrast to Na, the ion-exchange mechanism occurs spontaneously for heavier alkali atoms like Rb and the further diffusion of these atoms depends on the availability of Cu vacancies. The outdiffusion of alkali substitutional atoms from the grains results in the formation of Cu vacancies which in turn increases the hole concentration in the absorber. In this respect, Na is more efficient than Rb due to the higher concentration of Na substitutional defects in the CuInSe2 grains."}],"status":"public","date_updated":"2022-07-21T09:40:36Z","author":[{"first_name":"Ramya","id":"71692","full_name":"Kormath Madam Raghupathy, Ramya","orcid":"https://orcid.org/0000-0003-4667-9744","last_name":"Kormath Madam Raghupathy"},{"first_name":"Thomas","last_name":"Kühne","id":"49079","full_name":"Kühne, Thomas"},{"last_name":"Henkelman","full_name":"Henkelman, Graeme","first_name":"Graeme"},{"first_name":"Hossein","orcid":"0000-0001-6179-1545","last_name":"Mirhosseini","full_name":"Mirhosseini, Hossein","id":"71051"}],"date_created":"2020-01-30T13:06:56Z","title":"Alkali Atoms Diffusion Mechanism in CuInSe            2            Explained by Kinetic Monte Carlo Simulations","doi":"10.1002/adts.201900036","publication_status":"published","publication_identifier":{"issn":["2513-0390","2513-0390"]},"year":"2019","citation":{"chicago":"Kormath Madam Raghupathy, Ramya, Thomas Kühne, Graeme Henkelman, and Hossein Mirhosseini. “Alkali Atoms Diffusion Mechanism in CuInSe            2            Explained by Kinetic Monte Carlo Simulations.” <i>Advanced Theory and Simulations</i>, 2019. <a href=\"https://doi.org/10.1002/adts.201900036\">https://doi.org/10.1002/adts.201900036</a>.","ieee":"R. Kormath Madam Raghupathy, T. Kühne, G. Henkelman, and H. Mirhosseini, “Alkali Atoms Diffusion Mechanism in CuInSe            2            Explained by Kinetic Monte Carlo Simulations,” <i>Advanced Theory and Simulations</i>, Art. no. 1900036, 2019, doi: <a href=\"https://doi.org/10.1002/adts.201900036\">10.1002/adts.201900036</a>.","ama":"Kormath Madam Raghupathy R, Kühne T, Henkelman G, Mirhosseini H. Alkali Atoms Diffusion Mechanism in CuInSe            2            Explained by Kinetic Monte Carlo Simulations. <i>Advanced Theory and Simulations</i>. Published online 2019. doi:<a href=\"https://doi.org/10.1002/adts.201900036\">10.1002/adts.201900036</a>","short":"R. Kormath Madam Raghupathy, T. Kühne, G. Henkelman, H. Mirhosseini, Advanced Theory and Simulations (2019).","bibtex":"@article{Kormath Madam Raghupathy_Kühne_Henkelman_Mirhosseini_2019, title={Alkali Atoms Diffusion Mechanism in CuInSe            2            Explained by Kinetic Monte Carlo Simulations}, DOI={<a href=\"https://doi.org/10.1002/adts.201900036\">10.1002/adts.201900036</a>}, number={1900036}, journal={Advanced Theory and Simulations}, author={Kormath Madam Raghupathy, Ramya and Kühne, Thomas and Henkelman, Graeme and Mirhosseini, Hossein}, year={2019} }","mla":"Kormath Madam Raghupathy, Ramya, et al. “Alkali Atoms Diffusion Mechanism in CuInSe            2            Explained by Kinetic Monte Carlo Simulations.” <i>Advanced Theory and Simulations</i>, 1900036, 2019, doi:<a href=\"https://doi.org/10.1002/adts.201900036\">10.1002/adts.201900036</a>.","apa":"Kormath Madam Raghupathy, R., Kühne, T., Henkelman, G., &#38; Mirhosseini, H. (2019). Alkali Atoms Diffusion Mechanism in CuInSe            2            Explained by Kinetic Monte Carlo Simulations. <i>Advanced Theory and Simulations</i>, Article 1900036. <a href=\"https://doi.org/10.1002/adts.201900036\">https://doi.org/10.1002/adts.201900036</a>"}}]