Wow ! Zurich was intense and buzzing with AI for materials discovery ! In 1 day, we 🔬Visited SwissCat+ high-throughput facilities for heterogenous catalysis 🎤Presented Entalpic research, and had a super insightful discussions with ETHZ students & Jonathan Schmidt

Thanks SmartDigicat for catalysing discussions with chemists and physicists about the challenges of digitalised chemistry. Some examples: - cost and reliability of lab equipments - standardising experimental & computational databases (check out lematerial.org effort)

🚨 Job alert 🚨 Entalpic 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

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: meet.google.com/mwy-uydd-kvf

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

We didn't have the pleasure to attend ICLR 2026 this year, to present our LeMat-Bulk paper - accepted in the AI4Mat workshop. But it's available here --> openreview.net/forum?id=w0AsJ… Please let us know if you have any feedback, the full version still under review in a journal🤞

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

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 Chaitanya K. Joshi,

🚀 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. ⚛️🔥🧪🧬

Matbench Discovery is out in Nature Machine Intelligence @ Paper: rdcu.be/esRFB Leaderboard: …tbench-discovery.materialsproject.org No better time to thank all my co-authors Rhys Goodall, Philipp Benner, Yuan Chiang Yuan (Cyrus) Chiang, Bowen Deng, Mark Asta, Gerbrand Ceder Ceder Group,

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

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

🤗⚛️ Join the Entalpic 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)