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SUMMARY:Automated ab initio workflows with Jobflow and atomate2
DTSTART;VALUE=DATE:20250317
DTSTAMP:20260416T072115Z
UID:51ef33894fd7ee8c3837859a2c09571821ecade9a4837f3a884a9029
CATEGORIES:Conferences - Seminars
DESCRIPTION:You can apply to participate and find all the relevant informa
 tion (speakers\, abstracts\, program\,...) on the event website: https://
 www.cecam.org/workshop-details/automated-ab-initio-workflows-with-jobflow-
 and-atomate2-1276 . \n\nRegistration is required to attend the full even
 t\, 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 the
 ir research. Do not hesitate to contact the CECAM Event Manager if you 
 have any question.\n\nDescription\n\nAutomated ab initio calculations have
  emerged as a powerful tool for computational materials science. Automated
  workflows offer many benefits over traditional manual approaches\, includ
 ing:\n\n	Reproducibility: Automation ensures a consistent calculation proc
 edure for complex properties which often require many computational steps 
 and the linking of multiple software packages.\n	Scalability: High-through
 put computations enable wide-scale computational searches (often across te
 ns of thousands of compounds) and the generation of large datasets that ar
 e essential for machine-learning.\n	Useability: Users benefit from the exp
 erience of domain experts with significant previous expertise calculating 
 the properties of interest through well-tested default values and calculat
 ion procedures.\n\nRecent years have seen the development of a number of h
 igh-throughput workflow tools for automated ab initio calculations. Atoma
 te2 is a library of over 100 computational materials science workflows an
 d is the infrastructure that powers the Materials Project database. Workfl
 ows are written using the jobflow library and can be orchestrated across
  thousands of compute nodes using the FireWorks software. A central goal
  of atomate2 is to enable the interoperability of density-functional theor
 y (DFT) packages (VASP\, CP2K\, ABINIT\, and QChem are currently supported
 )\, with a common API for inputs and outputs. This has enabled two excitin
 g advances: i) heterogenous workflows that take advantage of the different
  capabilities of DFT packages\; and ii) generalisable workflows that can b
 e written once and executed using multiple DFT codes with minimal configur
 ation. Atomate2 also integrates with many other software packages\, includ
 ing AMSET for electron-phonon and electronic transport calculations\, phon
 opy for finite temperature properties\, and Lobsterpy for bonding analysis
 .\nThe community of developers is highly international with over 20 resear
 ch groups spanning the UK\, Europe\, and the US. The user base is similarl
 y diverse both geographically (covering over 15 countries) and scientifica
 lly\, with multidisciplinary applications in computational chemistry\, phy
 sics\, materials science\, and computer science. Over one thousand questio
 ns have been asked by users on the dedicated support forum (https://matsci
 .org) and associated GitHub repositories. Furthermore\, the atomate2 softw
 are stack has been adopted by industry stakeholders\, such as Umicore who 
 are using it to orchestrate high-throughput computational searches.\nThe c
 ommunity of users and developers mostly consists of high-throughput specia
 lists with previous expertise in this area. Despite this\, there is a grow
 ing number of researchers new to the field that are interested in both app
 lying existing workflows and developing completely new ones. It is therefo
 re essential to disseminate the knowledge of these tools to broader audien
 ces across computational materials science\, chemistry\, and physics.\nInf
 ormation - remote participation\nThe tutorial will take place in hybrid mo
 de. All the lectures can be attended online. For the hands-on exercices\,
  notebooks will be shared with the online participants who will be able t
 o ask questions through the chat.\nReferences\n[1] A. Jain\, S. Ong\, W. C
 hen\, B. Medasani\, X. Qu\, M. Kocher\, M. Brafman\, G. Petretto\, G. Rign
 anese\, G. Hautier\, D. Gunter\, K. Persson\, Concurrency Computat.: Pract
 . Exper.\, 27\, 5037-5059 (2015)\n[2] K. Mathew\, J. Montoya\, A. Faghani
 nia\, S. Dwarakanath\, M. Aykol\, H. Tang\, I. Chu\, T. Smidt\, B. Bocklun
 d\, M. Horton\, J. Dagdelen\, B. Wood\, Z. Liu\, J. Neaton\, S. Ong\, K. P
 ersson\, A. Jain\, Computational Materials Science\, 139\, 140-152 (2017)
 \n[3] J. George\, G. Petretto\, A. Naik\, M. Esters\, A. Jackson\, R. Nels
 on\, R. Dronskowski\, G. Rignanese\, G. Hautier\, ChemPlusChem\, 87\, (20
 22)\n[4] J. George\, Trends in Chemistry\, 3\, 697-699 (2021)\n[5] C. Cha
 ng\, V. Deringer\, K. Katti\, V. Van Speybroeck\, C. Wolverton\, Nat. Rev.
  Mater.\, 8\, 309-313 (2023)\n 
LOCATION:BCH 2103 https://plan.epfl.ch/?room==BCH%202103
STATUS:CONFIRMED
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