At Opentrons, we’ve considered liquid classes through both a Machine-centric and Liquid-centric lens. Each definition contributes to accurate pipetting. Machine-centric: A matrix of advanced pipetting parameters, validated by our science and hardware teams. It tells the robot how to aspirate and dispense based on pipette & tip pairing, volume-dependent motion tuning and other factors. Liquid-centric: Frames liquid classes around the liquid itself — treating it as an entity with defined behaviors. The robot uses this data to correct for things like density, viscosity, and surface tension
What are we launching?
Updated and improved functions for complex liquid handling operations:
transfer_with_liquid_class()
distribute_with_liquid_class()
consolidate_with_liquid_class()
Liquid Classes:
Aqueous – Based on Deionized Water
Viscous – Based on 50% Glycerol
Volatile– Based on 80% Ethanol (EtOH)
No Liquid Class selected
How did we test these Liquid Classes?
We have rigorously tested the values present in our liquid classes on robot, utilizing a gravimetric scale and automated, closed loop testing. Our internal science team next validated liquid classes function in existing protocols, highlighting the utility of plugging in the liquid classes versus optimizing the transfer steps, as would typically be done for protocols on our Library. As always, the feature has gone through full Quality Assurance batteries as well. It’s always a team effort at Opentrons to bring you the most helpful feature set possible!
For a full list of changes on all Opentrons App versions, please visit our GitHub below. Please contact our Support team at [email protected] with any questions or concerns
