📢 chemiscope.org 1.0.0rc1 just dropped on pypi! We are making (a few) breaking changes to the interfaces, fixing a ton of bugs and introducing some exciting features (you can finally load datasets with > 100k points!). We'd be grateful if you test, break and report 🐛 github.com/lab-cosmo/ch...

Hope y'all are getting a great start of 2026. Here we're taking some time to add the 2025 winter card to the archives www.epfl.ch/labs/cosmo/i... 🎅=🧑‍🚀

📢 New chemiscope.org release just landed! To make it even easier to integrate ⚗️🔭 into your workflow, we added a @streamlit.bsky.social component, so you can run analyses and show you atomistic data in a web app by just writing a few lines of python! try it, break it, report it!

Congrats to 🧑‍🚀 Sergey Pozdnyakov who received a distinction (best 8% of theses at @materials-epfl.bsky.social) for his PhD thesis "Advancing understanding and practical performance of machine learning interatomic potentials". Поїхали 🚀! infoscience.epfl.ch/entities/pub...

No day goes by without a new universal #ML potential. But how different they really are? Sanggyu and Sofiia tried to give a quantitative answer by comparing the reconstruction errors between their latent-space features. If you are curious, check out the #preprint arxiv.org/html/2512.05...

📢 PET-MAD is here! 📢 It has been for a while for those who read the #arXiv, but now you get it preciously 💸 typeset by @natcomms.nature.com Take home: unconstrained architecture + good train set choices give you fast, accurate and stable universal MLIP that just works™️ www.nature.com/articles/s41...

📢 Let us (re)introduce to you our Massive Atomic Diversity dataset for universal MLIPs. MAD includes molecules, clusters, surfaces and plenty of bulk configs, we cover a lot of ground with fewer than 100k structures, using highly consistent DFT settings. Read more 📑 www.nature.com/articles/s41...

‪In this blog post, Filippo Bigi, Marcel Langer (@labcosmo.bsky.social‬) and @micheleceriotti.bsky.social write about the need to balance speed and physical laws when using ML for atomic-scale simulations aihub.org/2025/10/10/m...

A primer for non conservative (& rotationally unconstrained) MLIPs, and how to use them safely. Thanks @aihub.org for the space! aihub.org/2025/10/10/m...

Looks like @ox.ac.uk forbids their researchers to do any kind of literature search, though it seems that thankfully they can still submit to the arxiv arxiv.org/abs/2510.00027 🤷

📝 We have been told (& been telling) that ML potentials are linked quite directly to the expansion of the atomic energy into pairs, triples, and so on. But is this actually true 🤔? Go read the latest from the 🧑‍🚀 team (w/QM help from Joonho's team at Harvard) to find out more arxiv.org/html/2509.14...

Bragging time - ⚡ FlashMD⚡ was accepted as a spotlight paper at #NeurIPS25. if you still haven't checked it out, it's already on the #arxiv arxiv.org/abs/2505.19350, the code is at flashmd.org and the 🧑‍🍳📖 is here atomistic-cookbook.org/examples/fla.... Congrats to Filippo, Sanggyu and Augustinus!

Michele Parrinello giving the ICTP Colloquium (he speaks about catalysis) as part of the conference celebrating his 80th birthday. Amazing creativity throughout a long career!

I'm very pleased to say my first preprint, with @graemeday.bsky.social and @micheleceriotti.bsky.social is now online! This is the main work of my PhD, adapting a similarity kernel to be more suited for exploring molecular CSP landscapes #compchemsky #chemsky #compchem doi.org/10.26434/che...

Anticipating 🧑‍🚀 Wei Bin's talk at #psik2025 (noon@roomA), 📢 a new #preprint using PET and the MAD dataset to train a universal #ml model for the density of states, giving band gaps for solids, clusters, surfaces and molecules with MAE ~200meV. Go to the talk, or check out arxiv.org/html/2508.17...!

📢 Now out on @physrevx.bsky.social energy, journals.aps.org/prxenergy/ab... from 🧑‍🚀 @dtisi.bsky.social and Hanna Türk, our #PET -powered study of the dynamic reconstruction of LPS surfaces, and how it affects their structure, stability and reactivity.

If you are at the #psik2025 and want to know more about the #metatensor ecosystem, don't miss @luthaf.bsky.social talk tomorrow morning 9:45 in room 1

🚨 #machinelearning for #compchem goodies from our 🧑‍🚀 team incoming! After years of work it's time to share. Go check arxiv.org/abs/2508.15704 and/or metatensor.org to learn about #metatensor and #metatomic. What they are, what they do, why you should use them for all of your atomistic ML projects 🔍.

Go metatensor.org!

If you are excited about 30x longer time steps in molecular dynamics using FlashMD, but are worried about it not being symplectic, Filippo has something new cooking that should make you even more excited. Head to the #arxiv for a preview arxiv.org/html/2508.01...

Two new recipes landed in the #atomistic-cookbook 🧑‍🍳📖. One explaining how to fine-tune the #PET-MAD universal model on a system-specific dataset, one training a model with conservative fine tuning. Check them out on atomistic-cookbook.org/examples/pet... and atomistic-cookbook.org/examples/pet...

Very few things make me prouder than having Jacob and @yotamfe.bsky.social's paper published today in JCP in the special issue honoring one of my personal heroes, Abraham Nitzan. Abe is a giant of theoretical chemistry (in Israel and globally) and an inspiration to us all. doi.org/10.1063/5.02...

New 🧑‍🍳📖 #recipe landed, doubling up as a @plumed.org tutorial 🐦 atomistic-cookbook.org/examples/met..., and explaining how to use the #metatomic interface in #plumed to define custom collective variables with all the flexibility and speed of torch.

Diverse data is good data! Took a while to polish it, but we have finally released the small-but-smart MAD dataset we used to train PET-MAD. You can find more on the #preprint arxiv.org/html/2506.19... or just head to the #materialscloud to fetch MAD archive.materialscloud.org/records/xdsb...

Very proud to send Filippo Bigi to Vancouver to give an oral presentation at @icmlconf.bsky.social about our investigation of the use of "dark-side forces" in atomistic simulations. The final version is here openreview.net/forum?id=OEl... and it's worth a read even if you already read the #preprint

🎉 DFT-accurate, with built-in uncertainty quantification, providing chemical shielding anisotropy - ShiftML3.0 has it all! Building on a successful @nccr-marvel.bsky.social-funded collaboration with LRM🧲⚛️, it just landed on the arXiv arxiv.org/html/2506.13... and on pypi pypi.org/project/shif...

🏆 Congratulations to Prof Francesco Stellacci from Materials Science and Engineering at EPFL for receiving an ERC Advanced Grant for his project Engineering Protein Interactions Using Small Molecules Find out more: actu.epfl.ch/news/epfl-re...

#metatensor day about to start! Join us on zoom if you're not at #EPFL epfl.zoom.us/j/68368776745 @nccr-marvel.bsky.social

Great job from the #SCITAS team deploying an energy-efficient GPU cluster to support #AI research (and all accelerated flavors of scientific computing) at #EPFL www.lenovo.com/us/en/case-s... @epfl-ai-center.bsky.social

📢 Running molecular dynamics with time steps up to 64fs for any atomistic system, from Al(110) to Ala2? Thanks to 🧑‍🚀 Filippo Bigi and Sanggyu Chong, with some help from Agustinus Kristiadis, this is not as crazy as it sounds. Let us briefly introduce FlashMD⚡ arxiv.org/html/2505.19...

🧑‍🚀Kevin shows off his multilingual skills with a public defense that is very much for the general public 😅

First #preprint from recent 🧑‍🚀 Michelangelo Domina (+ @ppegolo.bsky.social and Filippo) provides theoretical foundations and practical architectures to build scalar-function-based approximations of tensors, in the spirit of the "scalars are universals" paper #compchem arxiv.org/html/2505.05...

The PET-MAD universal forcefield mingled with the dark side, and got twice as fast 🚀. Read on, or head to the 🧑‍🍳📖 atomistic-cookbook.org/examples/pet..., if you are curious of what this is all about. #atomistic-cookbook #compchem #machinelearning #mlip🧵

Last week, we continued @labcosmo.bsky.social's study of solid-state electrolytes, focusing on the properties of the LPS surfaces arxiv.org/abs/2504.11553. Many thanks to my office mate Hanna Tuerk, who did a lot of the work

@labcosmo.bsky.social continuing its strong performance with Davide Tisi's talk on transport mechanisms in solid-state electrolytes!

Sanggyu keeping up the 🧑‍🚀 banner at #AI4AM in San Sebastian. #machinelearning can be reliable, if you ask it to be, with the right uncertainty estimators!

📢 For those who missed the #preprint, torch-pme is now published in @aip.bsky.social #JChemPhys. #compchem classics like Ewald and P3M meet #machine learning. Read all about it here pubs.aip.org/aip/jcp/arti...

When you combine #machinelearning and #compchem, you need to start worrying at the QM details within your ML architecture. We use our indirect Hamiltonian framework and pySCFAD to explore the enormous design space arxiv.org/abs/2504.01187

🚨 help needed! 🚨 Does anyone, ORB-affiliated or not, can share with us the model weights orb-v2-20241011.ckpt ? We need urgently to reproduce some results we obtained with that model checkpoint, but it was removed from their huggingface repo because the model reached "end of life" 🤷. 🙏

📢 PET-MAD has just landed! 📢 What if I told you that you can match & improve the accuracy of other "universal" #machinelearning potentials training on fewer than 100k atomic structures? And be *faster* with an unconstrained architecture that is conservative with tiny symmetry breaking? Sounds like 🧑‍🚀

🧑‍🍳 A new #cookbook recipe to train, export and use a simple but effective linear model for tensorial properties - specifically molecular polarizabilities atomistic-cookbook.org/examples/pol... Thanks @ppegolo.bsky.social for the recipe, and the whole 🧑‍🚀 team for the underlying infrastructure.

Happy to share a new #cookbook recipe that shocases several new software developments in the lab, using the good ole' QTIP4P/f water model as an example. atomistic-cookbook.org/examples/wat.... TL;DR - you can now build torch-based interatomic potentials, export them and use them wherever you like!

Interesting #preprint arxiv.org/html/2502.02... showing that even with a last-gen #machinelearning potential the liquid-liquid transition in hydrogen is supercritical, exactly as found by @chengbingqing.bsky.social & Guglielmo Mazzola 5 years ago - see www.nature.com/articles/s41.... 🧑‍🦳 but 🥇!

Hello, Bluesky! ☀️ We fund frontier research in Europe—bold ideas, unexpected discoveries and science that shapes the future. So it’s only fitting we’ve landed here. Sorry for being late. Follow us for updates on ERC funding, research policy, and our grantees' discoveries.

The forest is beautiful around here, a little eerie perhaps...

@marceldotsci.bsky.social getting into very dangerous territory.

Group retreat starting!

📢 Highlighted on #PhysRevMaterials (not yet on 🦋), a little, insightful gem by 🧑‍🚀 Wei Bin, Raymond, Fede & Kevin, relevant for all of you #machinelearning electronic structure properties. Band alignment matters, but it shouldn't, so here's how to deal with it with a self-aligning loss! A short 🧵...

Very happy to announce that github.com/lab-cosmo/sp... has reached the 1.0 release milestone. Most notably, you can now `pip install sphericart[torch,jax]` and get it installed without compilation, complete with CUDA support where available. Spherical (& solid) harmonics made fast and easy!

i-PI 3.1 is released. Quite a few tweaks and bugfixes, and an exciting initial implementation of a scripting API to run i-PI from a python script, see e.g. docs.ipi-code.org/python.html. Get it while it's hot!