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SUMMARY:Beyond Ground State Simulations: Navigating Challenges in Excited 
 States of Extended Molecules and Materials
DTSTART;VALUE=DATE:20241105
DTSTAMP:20260410T184157Z
UID:8d9668b3467cdd9fef3259850c7058ca44370b6aacdb549711c34274
CATEGORIES:Conferences - Seminars
DESCRIPTION:You can apply to participate and find all the relevant informa
 tion (speakers\, abstracts\, program\,...) on the event website:https://ww
 w.cecam.org/workshop-details/beyond-ground-state-simulations-navigating-ch
 allenges-in-excited-states-of-extended-molecules-and-materials-1285.\n\nRe
 gistration 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 r
 egistration if the topic is of interest to their research. Do not hesitate
  to contact the CECAM Event Manager if you have any question.\n\nDescrip
 tion\nThe computational study of excited states of molecules and materials
  plays a critical role in various scientific fields and technological appl
 ications [1\,2]. It is instrumental in advancing our understanding and dev
 elopment in areas such as solar energy conversion (photocatalysts and orga
 nic electronics) [3-5] as well as forward and inverse design of molecules 
 and materials [6-9]. By providing insights into the energetics\, dynamics\
 , and properties of excited states\, computational studies enable the desi
 gn of novel materials with enhanced functionalities\, optimization of devi
 ce performance\, and the exploration of new avenues for sustainable techno
 logies [10].\nDespite the importance of excited-state simulations they are
  seriously limited by the high computational costs of quantum chemical cal
 culations and the lack of accurate methods\, especially in the realm of ex
 tended systems [2\,11]. While theoretical models and methodologies for des
 cribing excited states of small molecular systems exist\, there is a lack 
 of complementary methods to investigate excited-state processes in larger 
 systems such as large molecules (e.g.\, molecular electronics\, and biomol
 ecules) and materials (e.g.\, semiconductors and heterogeneous systems). T
 he objective of this workshop is thus to bring together experts from compu
 tational chemistry that study excited-state of molecular systems with expe
 rts from computational materials science.\nThe workshop will focus on the 
 following four challenges\, which we have identified to require particular
  attention:\n\n	1) Charge Transfer: Charge transfer processes play a cruc
 ial role for efficient charge separation and transport across material int
 erfaces or through molecular wires and junctions\, which is pivotal in\, 
 e.g.\, solar energy conversion [12\,13]. Therefore\, it is crucial to stud
 y the excited states involved in charge transfer to understand the underly
 ing mechanisms and to develop strategies to optimise the performance of mo
 lecules (photocatalysts) and materials (photovoltaics). However\, the resp
 ective computational study of charge transfer processes faces challenges d
 ue to factors such as system size\, complexity\, accurate modeling of exci
 ted states\, non-adiabatic effects and interactions with solvents and the 
 environment. Addressing these challenges necessitates advances in theoreti
 cal methods.\n	2) Long-range interactions: Long-range interactions have be
 en extensively studied in ground state simulations [14] but their signific
 ance in excited states has recently gained attention and is thought to hav
 e an even greater impact than in ground states.\n	3) Nonadiabatic Molecula
 r Dynamics: Understanding the dynamics of excited states is essential for
  predicting their properties [2\,11\,15]. However\, performing molecular d
 ynamics in the excited states is not only computationally more demanding t
 han in the ground-state\, but often also requires the treatment of nuclear
  quantum effects that make the development of new methods particularly cha
 llenging.\n	4) Machine Learning for excited states of extended systems: M
 achine learning has shown promise in accelerating materials discovery and 
 the simulation of extended systems in their ground state [5\,7]\, but thei
 r excited states are far from being explored. Challenges are for instance 
 the non-transferability of many excited-state properties between chemical 
 systems or the increasing number of states with increasing system size tha
 t need to be incorporated properly in a machine learning model.\n\nBy maki
 ng the transition from ground to excited states for extended systems and f
 ocusing on unresolved questions concerning this topic\, the CM4xS worksh
 op seeks to enhance our understanding and prediction of material propertie
 s that have historically been challenging to investigate.\n\nReferences\n[
 1] Choice Reviews Online\, 46\, 46-6208-46-6208 (2009)\n[2] P. Dral\, M. 
 Barbatti\, Nat. Rev. Chem.\, 5\, 388-405 (2021)\n[3] A. Esswein\, D. Noce
 ra\, Chem. Rev.\, 107\, 4022-4047 (2007)\n[4] C. Kranz\, M. Wächtler\, C
 hem. Soc. Rev.\, 50\, 1407-1437 (2021)\n[5] N. O’Boyle\, C. Campbell\, 
 G. Hutchison\, J. Phys. Chem. C\, 115\, 16200-16210 (2011)\n[6] A. Bartó
 k\, S. De\, C. Poelking\, N. Bernstein\, J. Kermode\, G. Csányi\, M. Ceri
 otti\, Sci. Adv.\, 3\, (2017)\n[7] J. Wang\, Y. Wang\, Y. Chen\, Material
 s\, 15\, 1811 (2022)\n[8] D. Elton\, Z. Boukouvalas\, M. Fuge\, P. Chung\
 , Mol. Syst. Des. Eng.\, 4\, 828-849 (2019)\n[9] B. Sanchez-Lengeling\, A
 . Aspuru-Guzik\, Science\, 361\, 360-365 (2018)\n[10] A. Walsh\, Nature. 
 Chem.\, 7\, 274-275 (2015)\n[11] J. Westermayr\, P. Marquetand\, Chem. Re
 v.\, 121\, 9873-9926 (2020)\n[12] Electron Transfer in Chemistry\, (Wiley
 \, 2001)\n[13] Y. Hou\, X. Zhang\, K. Chen\, D. Liu\, Z. Wang\, Q. Liu\, J
 . Zhao\, A. Barbon\, J. Mater. Chem. C\, 7\, 12048-12074 (2019)\n[14] A. 
 Ambrosetti\, A. Reilly\, R. DiStasio\, A. Tkatchenko\, The Journal of Chem
 ical Physics\, 140\, (2014)\n[15] A. Sitt\, L. Kronik\, S. Ismail-Beigi\,
  J. Chelikowsky\, Phys. Rev. A\, 76\, 054501 (2007)\n 
LOCATION:BCH 2103 https://plan.epfl.ch/?room==BCH%202103
STATUS:CONFIRMED
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