Infinite dilution activity coefficient is a key thermodynamic parameter in solvent design for chemical processes. Although ...
In recent years, the integration of machine learning and robotics technologies in chemical analysis has transformed the landscape of scientific research and industry practices. This revolution is not ...
A web application for use by experimental chemists created by us. Uploading a file calculated with commercially available software, and the electronic state can be analyzed. We are working on creating ...
Chemists have created a machine learning tool that can identify the chemical composition of dried salt solutions from an image with 99% accuracy. By using robotics to prepare thousands of samples and ...
Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...
The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...
Soft sensors, also known as virtual sensors, are software that can process hundreds of measurements in combination. Plant managers who want to add soft sensors may be overwhelmed by the scope of ...
Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...
(Nanowerk News) Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of ...
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