🚀 We are launching the Δ Entalpic Research Fellowship Δ - supporting exceptional PhD students & postdocs at the frontier of AI for materials & chemistry. 💡 Funding, mentorship, visibility & collaboration for those exploring new datasets, generative models, agentic science,

1 week left before the @NeurIPSConf AI4Mat workshop deadline ⏰ Good luck for the last miles 🔥

On the personal side, after participating for a couple of years as an attendee & speaker, I am now joining the amazing organising team 🤩 with Anoop K, @martoskreto, Emily Jin, @KevinJablonka, Stefano Martiniani, Rocio Mercado, @santiagomiret Check out the website for more

Fellow AI for Materials researchers, The @NeurIPSConf #AI4Mat workshop's deadline is in ~20 days ! It's from experience a fantastic opportunity to submit your ongoing work, get meaningful reviews and discuss it with the community ! Whether you do AI-guided materials design,

🤗⚛️ Join the @entalpic_ai Team ⚛️🤗 At Entalpic, we combine MLIP, generative models, quantum simulations and lab experiments to optimise carbon intensive industrial processes and develop the next-generation materials. ⚠️ We are specially looking for ⚠️ * (Senior and Intern)

AI4Mat is back for NeurIPS! time to crystallize those ideas and make a solid-state submission by august 22, 2025 💪 new this year: opt-in your work for our Research Learning from Speaker Feedback program -- a new structured discussion format where spotlight presenters receive

Thank you so much #AI4X and Singapour ! A week of interesting discussions with the AI for Material/Chemistry community, experimental lab visits, amazing talks, client meetings, fancy rooftops, and more. Concluded by our presentation of Entalpic’s AI materials discovery

Matbench Discovery is out in Nature Machine Intelligence @ Paper: https://t.co/BtKuHy2fPp Leaderboard: https://t.co/lg3btmXUM1 No better time to thank all my co-authors @RhysGoodall, @PhilippBenner2, Yuan Chiang @cyrusyc_tw, @Bowen_D_, Mark Asta, Gerbrand Ceder @cedergroup,

🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT. ⚛️🔥🧪🧬

I love seeing the ongoing discussions on equivariance & energy conservation for ML Interatomic Potentials. Whether to enforce it explicitly or not, exploring the trade-off, understanding what's needed for a specific problem. Would recommend reading the thoughts of @chaitjo,

We released the Open Molecules 2025 (OMol25) Dataset last week! 🚀🧪 OMol25 is a large (100M+) and diverse molecular DFT dataset for training machine learning models. It was a massive collaborative and interdisciplinary effort and I’m super proud of the whole team! 🙌 1/7

We didn't have the pleasure to attend @iclr_conf this year, to present our LeMat-Bulk paper - accepted in the AI4Mat workshop. But it's available here --> https://t.co/QsqpoaAEqW Please let us know if you have any feedback, the full version still under review in a journal🤞

5/ 🎯 Want to help shape the next releases? Join our Slack & working groups: • Generative models for materials • LLMs for synthesis extraction • Multi-material datasets • …or pitch your idea! Let’s build the foundation models, benchmarks, and datasets that fuel tomorrow’s

4/ 🙌 Made possible by a joint effort from: @huggingface @Thom_Wolf 🤗 + contributors Ali Ramlaoui, Inel Djafar, Martin Siron, Amandine Rossello, Alexandre Duval, and the growing #LeMaterial community. Without forgetting the amazing initial effort from Materials Project,

3/ 📊 And… a benchmark for material structure hashing! You can use it to generate unique fingerprints for crystal structures and easily compare and de-duplicate data. Add your hashing/similarity method and benchmark against others! →

2/ 🛠️ We are also releasing the code that: • Fetches and updates the datasets regularly • Cleans & standardizes data • Makes it easy for the community to add more datasets →

1/ ⚛️ LeMaterial goes to Trajectories ⚛️ After releasing LeMat-Bulk - a crystals database of 6.7M structures - we’re excited to launch LeMat-Traj, a collection of ~120M structures from 3.7M atomic relaxation trajectories, compiled from Materials Project, Alexandria and OQMD.

The more time I spend in experimental materials labs, the more impressed I am by what we have accomplished as a civilisation — designing complex chemical processes with incomplete knowledge of underlying reaction mechanisms. The associated complexity is quite humbling tbh, but I

Hi together, We are having our second LeMaterial community meeting tomorrow (April 10) at 6PM CET | 9AM LA 📅 We will be discussing code / paper / datasets releases + ongoing working group progress (generative models, LLMs, data) 🤩 👉 To join:

🚨 Job alert 🚨 @entalpic_ai is hiring a Computational Chemist to lead ML-driven material discovery for liquid-phase chemical systems -- focusing on redox-active molecules, electrolytes, and molecule-solvent interactions. You will work at the interface of ML, computational