FHI-aims

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FHI-aims

FHI-aims

@fhi_aims

All-electron electronic structure theory with numeric atom-centered orbitals.

Berlin, Deutschland Katılım Ağustos 2021
217 Takip Edilen564 Takipçiler
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FHI-aims
FHI-aims@fhi_aims·
Our big overview paper "Roadmap on Advancements of the FHI-aims Software Package" is now on ArXiV: arxiv.org/abs/2505.00125 200+ authors detailing 20 years of progress in FHI-aims. Thank you to our INCREDIBLE community of people who have contributed to this!
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FHI-aims@fhi_aims·
🎉 Happy new FHI-aims release day 🎉 Version 260331 is now available, with a huge amount of changes inside, and over 25 contributors putting new code into this version. A huge thank you to everyone! You can see the list of changes & contributors here: fhi-aims.org/uploads/docume…
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FHI-aims@fhi_aims·
We once again have two great speakers lined up, with Andrew J. Logsdail introducing QM/MM approaches for multiscale simulations of solid-state systems and Gabriel A. Bramley showcasing the recently released EmbASI framework for QM/QM embedding.
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FHI-aims@fhi_aims·
📣 We are happy to announce the next FHI-aims Webinar on Multiscale Modeling with Explicit Embedding Approaches in FHI-aims! For registration and more details, click here: lnkd.in/dEM52S3q
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FHI-aims@fhi_aims·
What a great week in Shanghai for the Hands-on Workshop on Electronic-Structure Theory and Artificial Intelligence for Materials Science! A huge thank you to our speakers, tutorial preparers, organizers, and participants for making it an excellent event to learn about FHI-aims.
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FHI-aims@fhi_aims·
We are looking forward to the Hands-on Workshop on Electronic-Structure Theory and Artificial Intelligence for Materials Science tomorrow! In case you aren't in Shanghai, you can find livestreams of all the lectures, beginning at 10.00 CST 5 November here: koushare.com/live/details/4…
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FHI-aims@fhi_aims·
The recordings of our webinar on "Explainable AI models for Materials Science with the SISSO Approach" are now available on our YouTube channel: youtube.com/playlist?list=… Thank you to everyone who attended and to our great speakers, Thomas Purcell and Lucas Foppa! 👏
FHI-aims@fhi_aims

📣 We are happy to announce the next FHI-aims webinar in September. Find out about explainable AI models for materials science using the SISSO approach with Thomas Purcell and Lucas Foppa! For more details/registration, click here: indico.ms1p.org/e/webinar_sisso

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Sampreeti Bhattacharya
Sampreeti Bhattacharya@SampreetiB·
Excited to share one of my last PhD projects! We tackle finite-size effects in systems with high dof (e.g. HOIPs) using ML potentials + structural descriptors to analyze dynamic SOC in large supercells. Grateful to Kanai Lab and my mentee! 🙌 🔗 pubs.aip.org/aip/cpr/articl…
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FHI-aims@fhi_aims·
You can find the model and tutorial on its use in the HuggingFace repository: huggingface.co/nitbha007/MACE… Huge congratulations to the authors in this work for addressing the lack of a universal MLIP for IR spectroscopy!
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FHI-aims@fhi_aims·
MACE4IR is trained on 10 million geometries and corresponding FHI-aims DFT energies, forces and dipoles from the @GoogleDeepMind QCML database. It can predict IR spectra for organic, inorganic, metal complexes and biologically relevant species at a fraction of the cost of DFT.
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FHI-aims@fhi_aims·
Interested in rapid and reliable prediction of IR spectra? Check out this pre-print on the foundational model, MACE4IR, by Nitik Bhatia, Ondrej Krejci, Silvana Botti, Patrick Rinke, and Miguel A. L. Marques : arxiv.org/abs/2508.19118
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FHI-aims@fhi_aims·
📢 New FHI-aims release 250822 📢 Lots of new things including: QM-in-QM embedding with EmbASI, superconductivity, implicit solvation with Environ, Q4C up to 1500 atoms, faster range separated hybrids, and a whole lot more. A huge thank you to everyone who contributed!
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FHI-aims@fhi_aims·
"aims-PAX is a flexible, fully automated, open-source software package for performing active learning for machine learning force fields using a parallelized algorithm that enables efficient resource management." You can find the open-source code here: github.com/tohenkes/aims-… 2/2
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FHI-aims@fhi_aims·
Interested in the automated construction of Machine Learning Force Fields? Check out this exciting new pre-print describing aims-PAX, which utilizes FHI-aims, from Tobias Henkes, Shubham Sharma, Alexandre Tkatchenko, Mariana Rossi, and Igor Poltavsky: arxiv.org/abs/2508.12888 1/2
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FHI-aims@fhi_aims·
📣 We are happy to announce the next FHI-aims webinar in September. Find out about explainable AI models for materials science using the SISSO approach with Thomas Purcell and Lucas Foppa! For more details/registration, click here: indico.ms1p.org/e/webinar_sisso
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