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Looking for *experimental* methane isotherms between 220 K and 350 K up to 100 bars in MOFs.

Big 10 has 18 teams, Big 12 has 16 teams. And Pac-12 has 2 teams?

Monte Carlo with expanded ensembles are powerful methods to compute adsorption and diffusion processes in nanoporous materials. In The Journal of Chemical Physics , we present RASPA3, the new version of the RASPA2 code. (1/8) pubs.aip.org/aip/jcp/articl…

Interested in working with a highly collaborative, interdisciplinary team to push the state of the art of generative AI for materials design? Join us as an intern by applying through this link! We are the team behind the MatterGen and MatterSim models from Microsoft Research AI

After working on a topic for a while, you start to see the limitations of the current SOTA. Then you have a crazy (or maybe naive) idea, but you're unsure if it's worth pursuing. Then, in the middle of the night, you stumble upon a manuscript that executes your idea. Instead of

Love this perspective on the energy landscape, which I worked on as a Ph.D. student. I transitioned from "soft" science to "hard" science but still very dear to my heart. Too bad there is no mention of "fold catastrophes" but I highly recommend looking into this concept related

BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”

Introducing Meta’s Open Materials 2024 (OMat24) Dataset and Models! All under permissive open licenses for commercial and non-commercial use! Paper: arxiv.org/abs/2410.12771 Dataset: huggingface.co/datasets/fairc… Models: huggingface.co/fairchem/OMAT24 🧵1/x

Modeling, screening, and techno-economic evaluation of metal-organic frameworks for boil-off gas capture during intercontinental transportation of LNG dx.doi.org/10.26434/chemr…

Feels like there should be a competition like this for MOFs -- anyone interested?

This is a *potentially* exciting application of MOFs that outperforms state-of-the-art technology in terms of cost-effectiveness. Huge thanks to my co-authors and to Inkyu Lee's team for their invaluable TEA contributions!

Sold me on the first sentence to keep reading the rest of the paper! "Materials do not have a genome."

So Korea is under martial law ... interesting times ...

🚀ChemBench just leveled up! We’re thrilled to announce the latest release of ChemBench—now smarter and smoother! Dive into benchmarking any chemistry AI model with our revamped framework, designed for flexibility and ease. #ChemistryAI #MachineLearning #OpenScience #Innovation

🦨"Why an over-reliance on AI-driven modeling is bad for science" there's a rush to adopt AI (wonder what "AI's rise in research" looks like for chemistry & chemical engineering 👀). - easy for researchers to overestimate the predictive capabilities of an AI model, creating the

Major academic publishers have profit margins like the some of the most profitable major tech companies.

🔬 Exploring adsorbent materials' performance in dynamic settings through breakthrough simulations offers valuable insights. However, the process can be challenging due to the requirement of learning new operating systems like Linux or dealing with complex legacy software codes.

CoRE MOF DB: A curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening cell.com/matter/fulltex…