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Organic Synthesis with MIT Chemistry Lab

Experimentation performed by scientists and researchers is at the core of research in most fields of science, and many rely on the function and reliability of the instruments and equipment they work with to gather data. These invaluable data are what drives research forward, and they come at a great cost and time spent by scientists and researchers in academic institutions and pharmaceutical industry. However, inefficient workflows commonly revolve around lab instruments, and often enough, unexpected instrument failures during experimentation will delay research for days and weeks, sometimes months. Hence, tools that bolster research workflows and save time on data acquisition and management are needed to improve efficiency, and in turn productivity, in the lab.


Jon Barnes is a synthetic chemist in the Johnson Research Group at the MIT Department of Chemistry. He and his lab seek to develop new methodologies for the construction and modification of complex material libraries.

For years, Jon has been frustrated by the lack of control over simple reaction parameters including temperature monitoring, the ability to turn off a hot plate, as well as to activate a syringe pump from a remote location. Day-to-day experiments often required constant in-person monitoring, which was both inefficient and frustrating.

"In one of my projects I need to be able to closely control the temperature of a nanoparticle synthesis. If the temperature spikes/dips, then the particle distribution is very large, and I have to throw out that batch. Unfortunately, I won’t know if the batch is bad until after the reaction by using dynamic light scattering or transmission electron microscopy."

Seeking a solution to improve the safety and efficiency of the lab, Jon turned to TetraScience. TetraScience Links were deployed across various equipment types within the lab including freezers and chemical fume hoods.

"With TetraScience, I am able to immediately determine whether or not a batch is good simply based on how much the temperature fluctuated during the synthesis. If I see any erroneous spikes/dips in the temperature profile, then I know chances are high that it's a bad batch, and I can throw it out immediately without any further characterization."

TetraScience’s real-time monitoring data has granted Jon and his lab peace of mind to start experiments at the end of the day, knowing that they will be immediately alerted if anything goes wrong so they can come back to the lab and take corrective action.


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• Chemistry

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