Asynt has reported how the deepmatter Group, with facilities in the UK, France and Germany, have developed the cloud-based SmartChemistry platform to share chemical reaction and sensor data directly from the laboratory to allow analysis of this information on an unprecedented scale.
This single platform allows reaction data to be compiled from multiple data sources to provide a cleansed, harmonised, and categorised repository for the exploitation of reaction data through Application Programming Interfaces (APIs), search tools and Machine Learning (ML)/Artificial Intelligence (AI) learning.
These tools continue to play an essential role in our laboratories, enabling a higher level of experimentation when combined with our empowering data system
Kate Rowley, Chief Business Officer at deepmatter, commented: “We knew when developing this system that it was essential to offer a complete solution to our customers that is easily accessible worldwide and enables scientists to get truly repeatable results. Due to the highly sensitive electrical components for data recording and reporting that the SmartChemistry system uses, it was equally as important to keep that apparatus free of potential contaminants and safety hazards.”
Rowley continued: “Using the DrySyn oil-free heating block platform and magnetic hotplate stirrer kits from Asynt is ideal for SmartChemistry with consistent, effective heating and agitation throughout the course of each reaction. These tools continue to play an essential role in our laboratories, enabling a higher level of experimentation when combined with our empowering data system.”
Joel Aleixo, Marketing Manager, explained that by bringing together this repeatable and proprietary data with widely available and effective tools such as DrySyn oil-free heating blocks they can improve the productivity, discovery, and sustainability of chemical reactions. The data system also enables the prediction of synthesis for novel molecules that scientists want to prepare, thus offering great value via the reduction of time and chemical waste, support for decision making, and improving optimisation processes.
