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Check out Pierre’s paper “Toward Advanced, Predictive Mixing Rules in SAFT Equations of State” on Ind. Eng. Chem. Res. doi.org/10.1021/acs.ie… #SAFT ACS Publications

Characterizing Uncertainty in Machine Learning for Chemistry #machinelearning #compchem pubs.acs.org/doi/abs/10.102…

My paper on "Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates" is now available on ChemRxiv. Check out how our ML model performs! doi.org/10.26434/chemr… #MachineLearning #CompChem

Excited to share that my paper on "Computing Kinetic Solvent Effects and Liquid Phase Rate Constants Using Quantum Chemistry and COSMO-RS Methods" is now available on The Journal of Physical Chemistry Check it out! #compchem pubs.acs.org/doi/10.1021/ac…

Chemprop: Machine Learning Package for Chemical Property Prediction #machinelearning #compchem dx.doi.org/10.26434/chemr…

Predicting Critical Properties and Acentric Factors of Fluids Using Multitask Machine Learning #machinelearning #compchem pubs.acs.org/doi/abs/10.102…

Our paper "Predicting Critical Properties and Acentric Factors of Fluids Using Multitask Machine Learning" is published on JCIM. The dataset and code are available as well! #MachineLearning #compchem JCIM & JCTC Journals Sayandeep Biswas pubs.acs.org/doi/full/10.10…

Chung and Green present a comprehensive assessment of quantum chemical methods and COSMO-RS models for predicting rate constants and solvent effects for various liquid phase reactions. Yunsie Chung MIT ChemE Dept go.acs.org/5FQ

First claimed successful replication of LK-99 Accomplished by a team at the Huazhong University of Science and Technology and posted 30 minutes ago. Why this is evidence: The LK-99 flake slightly levitates for both orientations of the magnetic field, meaning it is not simply a

Just published article on decarbonizing long-haul trucks using onboard liquid organic hydrogen carriers (LOHC) in ACS Energy and Fuels! Our LOHC powertrain design could cut GHG emissions by 71% & compete with diesel economically. Check out-doi.org/10.1021/acs.en…. #renewables

Happy to share our paper on confidence-interval and uncertainty-propagation analysis of SAFT equations of state! It was fun collaborating with Simon Müller TU Hamburg! pubs.acs.org/doi/10.1021/ac…

MIT News just covered our work on decarbonizing long-haul trucking published in ACS Energy and Fuels. ACS Publications Link - news.mit.edu/2023/harnessin…

Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets #machinelearning #compchem dx.doi.org/10.26434/chemr…

Predicting Critical Properties and Acentric Factors of Fluids Using Multitask Machine Learning #compchem pubs.acs.org/doi/10.1021/ac… Yunsie Chung Sayandeep Biswas #JCIM Vol63 Issue15 #MachineLearning #deeplearning

For my 5 followers: my first paper of my PhD was recently published! In this work, we compile new data for ionic solvation, and use these to develop corrections that reduce mean absolute errors by ~60%. Read about it here: pubs.acs.org/doi/10.1021/ac…

Excited to share that our Chemprop package paper is published on JCIM pubs.acs.org/doi/10.1021/ac… #machinelearning #ML

Check out our new paper on Chemprop in JCIM & JCTC Journals! We describe and benchmark many additional features we've added to the package since its initial release and paper in 2019. pubs.acs.org/doi/10.1021/ac…

Excited to share that my paper on "Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates" is published on Chemical Science! Data, code, models available. #MachineLearning #ML #CompChem #MyFirstChemSci pubs.rsc.org/en/Content/Art…

I’m gonna give 10 random people that repost this and follow me $25,000 for fun (the $250,000 my X video made) I’ll pick the winners in 72 hours

Check out our latest paper from Merck on “Denoising Drug Discovery Data for Improved ADMET Property Prediction”, now available in JCIM & JCTC Journals. We show how to reduce noise in datasets to improve ML models. pubs.acs.org/doi/10.1021/ac… #MachineLearning #ML #DrugDiscovery