You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: https://www.cecam.org/workshop-details/fair-data-management-of-theoretical-spectroscopy-and-greens-function-methods-1377.
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\r\nRegistration is required to attend the full event, take part in the social activities and present a poster at the poster session (if any). However, the EPFL community is welcome to attend specific lectures without registration if the topic is of interest to their research. Do not hesitate to contact the CECAM Event Manager if you have any question.
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\r\nDescription
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\r\nBig-data-driven methodologies have emerged as a fundamental paradigm of science, but require an enormous amount of resources to achieve their promised impact. The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles [1] ensure that scientific data can be shared and reutilized, providing an efficient route for accumulating data and taking advantage of these powerful techniques. FAIR data management allows essential knowledge to be systematically extracted from data, accelerating discoveries and innovations across various domains [2]. Furthermore, open science is essential for the verifiability and reproducibility of results and has been a topic of major discussion over the last decade. In materials science, data-driven methodologies, coupled with the appropriate FAIR data management practices, are invaluable for the discovery of new materials due to the vast combinatorial space of chemical systems that emerge from the periodic table [3, 4]. Such methodologies have been successfully applied, e.g., to design and predict new materials with desired properties using ab-initio ground state simulations, i.e., data generated from Density Functional Theory (DFT) calculations [5]. However, there remains a critical gap in replicating this success in the context of other simulation frameworks.
\r\nTheoretical spectroscopy and Green's function method simulations [6, 7], including data simulated using the GW approximation, Time-Dependent Density Functional Theory (TDDFT), the Bethe-Salpeter equation (BSE), Dynamical Mean-Field Theory (DMFT), and Korringa-Kohn-Rostoker (KKR), pose especially difficult challenges in the context of FAIR data management. These simulations not only involve extensive computational resources and produce large datasets with associated complex workflows but are also executed using a large variety of public and in-house simulation software. At the same time, these methodologies are essential for understanding excited state properties of complex materials; they are more accurate than DFT calculations and provide better comparisons with experimental results since they incorporate excited states and electronic correlation effects in a more consistent manner [8].
\r\nThere has recently been a number of individual efforts to improve the accessibility of data produced by theoretical spectroscopy and Green’s function methods through the usage of publicly accessible databases. For example, the Computational Materials Repository (CMR) [9] contains several individual databases, amongst which the Computational 2D Materials Database (C2DB) [10] contains GW and BSE data for a specific set of parameters and properties. The MaterialsCloud [11] database has some individual datasets published for these methodologies, however there is not a clear data structure for them. The NIST-JARVIS [12] database has a specific app for BeyondDFT simulations with DMFT data, but only for a specific simulation code. By making datasets findable, these efforts aim to avoid redundant computations and thus build upon existing work more efficiently. While these efforts represent an important step in the right direction, they fall short of fully achieving their goal due to a continued lack of consistency (i.e., interoperability) between individual databases. Moreover, these self-managed databases typically lack the ability to store the complete provenance of the simulated workflow, which is essential to ensure reproducibility.
\r\nRecently, FAIRmat [13], a consortium of the German research data infrastructure (NFDI) association, was formed to construct a scalable data infrastructure for Materials Science that can be easily customized for individual communities. This infrastructure consists of a primary software and repository called NOMAD [14]—a free web-service that enables the organization, analysis, sharing, and publishing of materials science data. One of the tasks within FAIRmat’s scope is to build support for theoretical spectroscopy and Green’s function simulations within NOMAD. Support for several of these methodologies have now been successfully built, and there already exists over 10 000 entries in the NOMAD repository containing GW [15], BSE [16], and DMFT [17] data, along with the full provenance of the corresponding complex workflows. The next step to developing a FAIR data infrastructure for these methods is to tackle the interoperability problem.
\r\nInteroperability within this domain is extremely challenging due to the heterogeneous character of theoretical spectroscopy and Green’s function simulations. Consequently, the adoption of common structures (e.g., describing the Green’s function, the self-energy, or the dielectric function) is the key for improving interoperability. Thus, various members of the community, including method developers, materials and data scientists, and data management experts, must come together to reach a consensus on specific common data structures.
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\r\nReferences
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\r\n[1] Computational Materials Repository (CMR) website
\r\n[2] S. Di Cataldo, P. Worm, J. Tomczak, L. Si, K. Held, Nat. Commun., 15, 3952 (2024)
\r\n[3] F. Meng, B. Maurer, F. Peschel, S. Selcuk, M. Hybertsen, X. Qu, C. Vorwerk, C. Draxl, J. Vinson, D. Lu, Phys. Rev. Materials, 8, 013801 (2024)
\r\n[4] M. van Setten, F. Caruso, S. Sharifzadeh, X. Ren, M. Scheffler, F. Liu, J. Lischner, L. Lin, J. Deslippe, S. Louie, C. Yang, F. Weigend, J. Neaton, F. Evers, P. Rinke, J. Chem. Theory Comput., 11, 5665-5687 (2015)
\r\n[5] M. Scheidgen, L. Himanen, A. Ladines, D. Sikter, M. Nakhaee, Á. Fekete, T. Chang, A. Golparvar, J. Márquez, S. Brockhauser, S. Brückner, L. Ghiringhelli, F. Dietrich, D. Lehmberg, T. Denell, A. Albino, H. Näsström, S. Shabih, F. Dobener, M. Kühbach, R. Mozumder, J. Rudzinski, N. Daelman, J. Pizarro, M. Kuban, C. Salazar, P. Ondračka, H. Bungartz, C. Draxl, JOSS., 8, 5388 (2023)
\r\n[6] FAIRmat website
\r\n[7] K. Choudhary, K. Garrity, A. Reid, B. DeCost, A. Biacchi, A. Hight Walker, Z. Trautt, J. Hattrick-Simpers, A. Kusne, A. Centrone, A. Davydov, J. Jiang, R. Pachter, G. Cheon, E. Reed, A. Agrawal, X. Qian, V. Sharma, H. Zhuang, S. Kalinin, B. Sumpter, G. Pilania, P. Acar, S. Mandal, K. Haule, D. Vanderbilt, K. Rabe, F. Tavazza, npj. Comput. Mater., 6, 173 (2020)
\r\n[8] L. Talirz, S. Kumbhar, E. Passaro, A. Yakutovich, V. Granata, F. Gargiulo, M. Borelli, M. Uhrin, S. Huber, S. Zoupanos, C. Adorf, C. Andersen, O. Schütt, C. Pignedoli, D. Passerone, J. VandeVondele, T. Schulthess, B. Smit, G. Pizzi, N. Marzari, Sci. Data., 7, 299 (2020)
\r\n[9] S. Haastrup, M. Strange, M. Pandey, T. Deilmann, P. Schmidt, N. Hinsche, M. Gjerding, D. Torelli, P. Larsen, A. Riis-Jensen, J. Gath, K. Jacobsen, J. Jørgen Mortensen, T. Olsen, K. Thygesen, 2D Mater., 5, 042002 (2018)
\r\n[10] M. Wilkinson, M. Dumontier, I. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J. Boiten, L. da Silva Santos, P. Bourne, J. Bouwman, A. Brookes, T. Clark, M. Crosas, I. Dillo, O. Dumon, S. Edmunds, C. Evelo, R. Finkers, A. Gonzalez-Beltran, A. Gray, P. Groth, C. Goble, J. Grethe, J. Heringa, P. ’t Hoen, R. Hooft, T. Kuhn, R. Kok, J. Kok, S. Lusher, M. Martone, A. Mons, A. Packer, B. Persson, P. Rocca-Serra, M. Roos, R. van Schaik, S. Sansone, E. Schultes, T. Sengstag, T. Slater, G. Strawn, M. Swertz, M. Thompson, J. van der Lei, E. van Mulligen, J. Velterop, A. Waagmeester, P. Wittenburg, K. Wolstencroft, J. Zhao, B. Mons, Sci. Data., 3, 160018 (2016)
\r\n[11] L. Reining et al., Comptes Rendus Physique 10, 6 (2009)
\r\n[12] V. Blum, R. Asahi, J. Autschbach, C. Bannwarth, G. Bihlmayer, S. Blügel, L. Burns, T. Crawford, W. Dawson, W. de Jong, C. Draxl, C. Filippi, L. Genovese, P. Giannozzi, N. Govind, S. Hammes-Schiffer, J. Hammond, B. Hourahine, A. Jain, Y. Kanai, P. Kent, A. Larsen, S. Lehtola, X. Li, R. Lindh, S. Maeda, N. Makri, J. Moussa, T. Nakajima, J. Nash, M. Oliveira, P. Patel, G. Pizzi, G. Pourtois, B. Pritchard, E. Rabani, M. Reiher, L. Reining, X. Ren, M. Rossi, H. Schlegel, N. Seriani, L. Slipchenko, A. Thom, E. Valeev, B. Van Troeye, L. Visscher, V. Vlcek, H. Werner, D. Williams-Young, T. Windus, Electron. Struct., (2024)
\r\n[13] L. Ghiringhelli, C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C. Koch, M. Kühbach, A. Ladines, P. Lambrix, M. Himmer, S. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll, M. Scheffler, Sci. Data., 10, 626 (2023)
\r\n[14] J. Schmidt, M. Marques, S. Botti, M. Marques, npj. Comput. Mater., 5, 83 (2019)
\r\n[15] L. Himanen, A. Geurts, A. Foster, P. Rinke, Advanced Science, 6, (2019)
\r\n[16] M. Scheffler, M. Aeschlimann, M. Albrecht, T. Bereau, H. Bungartz, C. Felser, M. Greiner, A. Groß, C. Koch, K. Kremer, W. Nagel, M. Scheidgen, C. Wöll, C. Draxl, Nature, 604, 635-642 (2022)
\r\n[17] C. Draxl, M. Scheffler, MRS Bull., 43, 676-682 (2018)
You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: https://www.cecam.org/workshop-details/challenges-in-modelling-ion-channels-simulations-meet-experiments-1369.
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\r\nRegistration is required to attend the full event, take part in the social activities and present a poster at the poster session (if any). However, the EPFL community is welcome to attend specific lectures without registration if the topic is of interest to their research. Do not hesitate to contact the CECAM Event Manager if you have any question.
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\r\nDescription
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\r\nThe human genome includes more than 300 genes coding for ion channel proteins, representing approximately 2% of the total number of genes. This abundance of ion channels highlights their critical role in numerous biological processes and their involvement in diseases, underscoring their importance as potential drug targets. Ion channels exert their biological roles through three main functional characteristics: the highly efficient selective conduction of ions; the capacity to open and close in response to chemical/physical stimuli (gating); and the decrease in conductance upon sustained stimuli (inactivation). In the last 20 years, the number of experimental atomic structures of ion channels has increased from a few units to hundreds, now including representative structures for most of the ion channel families. Simulations based on these experimental structures have significantly contributed to the current understanding of conduction, selectivity, gating, and inactivation [1-2]. Strengthening the quantitative agreement between simulations and experiments is now essential for advancing in this field. This effort is currently hampered by common issues in biomolecular simulations, such as the limited timescales for observing biologically relevant events and the sub-optimal accuracy of the underlying physical models. Both of these shortcomings are expected to be mitigated by recent methodological developments. For instance, atomic simulations of ion channels with polarizable force fields have been recently reported [3]. Lack of polarization is a well-known limitation of classical force fields, especially when describing ion-protein and ion-water interactions in a crowded environment like the pore cavity. Consequently, the usage of polarizable force fields is considered a promising strategy for improving the agreement with experimental data about ion conduction and selectivity. An alternative strategy for enhancing the model accuracy in critical channel regions is to combine molecular mechanics with quantum approaches. Thanks to the ever-increasing computational resources, now combined with advancements in codes for hybrid QM/MM models, this approach is becoming feasible for ion channel research [4]. Increasing computational resources, coupled with improved algorithms for accelerating rare events and potentially harnessing machine learning, are also opening new possibilities in the study of state transitions. Gating and inactivation events of ion channels are finally becoming accessible to atomic simulations, offering important insights into the mechanistic functioning of this important protein superfamily [5]. The proposed workshop will foster further developments in the field by bringing together leading scientists in the experimental methodologies and computational techniques used in ion channel research in a stimulating and collaborative environment.
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\r\nReferences
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\r\n[1] E. Flood, C. Boiteux, B. Lev, I. Vorobyov, T. Allen, Chem. Rev., 119, 7737-7832 (2019)
\r\n[2] C. Guardiani, F. Cecconi, L. Chiodo, G. Cottone, P. Malgaretti, L. Maragliano, M. Barabash, G. Camisasca, M. Ceccarelli, B. Corry, R. Roth, A. Giacomello, B. Roux, Advances in Physics: X, 7, (2022)
\r\n[3] V. Ngo, H. Li, A. MacKerell, T. Allen, B. Roux, S. Noskov, J. Chem. Theory Comput., 17, 1726-1741 (2021)
\r\n[4] F. Schackert, J. Biedermann, S. Abdolvand, S. Minniberger, C. Song, A. Plested, P. Carloni, H. Sun, J. Chem. Inf. Model., 63, 1293-1300 (2023)
\r\n[5] S. Pérez-Conesa, L. Delemotte, Free energy landscapes of KcsA inactivation, 2023
The project aims to further investigate the structural, architectural, environmental, and social dimensions of TRC and its applications, particularly in the context of a new Multi-Purpose Space for the Department of Architecture & Interior Design Kenyatta University Campus, Nairobi, Kenya in collaboration with Urko Sanchez Architects. The space is intended to support academic, social, and experimental activities while serving as a living laboratory for sustainable and alternative construction methods. The pavilion should function not only as a usable academic space but also as a pedagogical tool, demonstrating climate-responsive design, material innovation, and adaptability over time. \r\n
![\"\"](\"//memento.epfl.ch/public/upload/fckeditorimage/7a/dc/2b0d232e.jpg\")
","image_description":"Summer workshop EPFL Fribourg 2025, photo: Nicolas Gemelli","creation_date":"2026-01-14T13:38:32","last_modification_date":"2026-01-30T11:31:06","link_label":"","link_url":"https://www.epfl.ch/schools/enac/education/fr/projeter-ensemble-fr/cours/enac-summer-workshops/a-prototype-pavillon-in-textile-reinforced-concrete-2/","canceled":"False","cancel_reason":"","place_and_room":"EPFL Fribourg","url_place_and_room":"","url_online_room":"","spoken_languages":["https://memento.epfl.ch/api/v1/spoken_languages/1/?format=json","https://memento.epfl.ch/api/v1/spoken_languages/2/?format=json"],"speaker":"","organizer":"Patricia Guaita, ENAC EPFL Projecter Ensemble","contact":" patricia.guaita@epfl.ch ","is_internal":"True","theme":"","vulgarization":{"id":1,"fr_label":"Tout public","en_label":"General public"},"registration":{"id":3,"fr_label":"Entrée libre","en_label":"Free"},"keywords":"","file":null,"icalendar_url":"https://memento.epfl.ch/event/export/119303/","category":{"id":1,"code":"CONF","fr_label":"Conférences - Séminaires","en_label":"Conferences - Seminars","activated":true},"academic_calendar_category":null,"domains":[],"mementos":["https://memento.epfl.ch/api/v1/mementos/8/?format=json","https://memento.epfl.ch/api/v1/mementos/1/?format=json","https://memento.epfl.ch/api/v1/mementos/4/?format=json","https://memento.epfl.ch/api/v1/mementos/32/?format=json","https://memento.epfl.ch/api/v1/mementos/6/?format=json"]},{"id":70833,"title":"EESS seminar talk on \"Biogeochemical Controls on Arsenic Methylation and Demethylation in Rice Paddy Soils\"","slug":"eess-seminar-talk-on-biogeochemical-controls-on--2","event_url":"https://memento.epfl.ch/event/eess-seminar-talk-on-biogeochemical-controls-on--2","visual_url":"https://memento.epfl.ch/image/32237/200x112.jpg","visual_large_url":"https://memento.epfl.ch/image/32237/720x405.jpg","visual_maxsize_url":"https://memento.epfl.ch/image/32237/max-size.jpg","lang":"en","start_date":"2026-04-28","end_date":"2026-04-28","start_time":"12:15:00","end_time":"13:15:00","description":"Abstract:\r\nThis summer school, organized by seven PhD students from EPFL and ETH Zurich, brings together leading researchers and postgraduate students. Participants will learn modern mathematical and probabilistic methods for linear algebra through lectures by experts in randomized numerical linear algebra. The program also includes networking opportunities with fellow participants, lecturers, and industry representatives.
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\r\nThe summer school takes place in a modern hotel in the middle of the historic lakeside town of Murten/Morat. Accommodation, food, and all other costs during the summer school will be covered. All participants are charged a small registration fee.
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\r\nRegistrations can be made until February 15 and are primarily open to doctoral students from the ETH domain, with limited exceptions for international and master’s students. It is possible to obtain 2 ECTS credits for attending MoRAT.
During a one-week Summer Workshop in Central London, students will explore drawing as a fundamental tool in architecture and engineering, engaging with the site as both a built environment and a historically transformed place. Developed in collaboration with Drawing Matter, London, the workshop integrates hands-on drawing with research into the Drawing Matter Collection, a unique archive of architectural drawings.
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\r\nProject Team 2025
\r\nDr. Patricia Guaita, architect, lecturer, IA ENAC EPFL
\r\nRaffael Baur, architect and external lecturer ENAC EPFL
\r\nNiall Hobhouse, collector and writer, Drawing Matter Director
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\r\nInvited expert
\r\nMatthew Wells, Lecturer in Architectural Studies at University of Manchester
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\r\n![\"\"](\"//memento.epfl.ch/public/upload/fckeditorimage/40/0d/ed493c2f.jpg\")