The issue of parallel processing (or high throughput) has certainly been tackled but effort is also being made in generating data that is likely to be scalable, says Jasbir Singh
From test tube to production - rapidly.
That is the objective of most chemical companies and realisation of this objective consists of two parts: speed so that much data can be generated quickly and quality so that the data is good enough to eliminate the need for extensive piloting.
The issue of parallel processing (or high throughput) has certainly been tackled but effort is also being made in generating data that is likely to be scalable.
In this article we will investigate how heterogeneous hydrogenations from 8 x10ml vessels can be scaled up without any problem by comparing the results with data from 100 and 1000ml vessels.
In a recent study by HEL, laboratory scale equipment covering two orders of magnitude in volume was compared: high pressure Chemscan 10ml, high pressure Auto-mate 100ml, and the Simular reaction calorimeter 1000ml.
A systematic study was performed to demonstrate the consistency of data across this wide range.
The equipment used in this study was fully instrumented with control of agitation, temperature and pressure.
Most importantly for hydrogenation reactions, the uptake of hydrogenation was evaluated in real time - thus the broad results were available quickly and reliably.
Experiments were performed at a range of catalyst loadings with each apparatus.
At fixed conditions of pressure and temperature (for example 6.9bar and 40C), the 'reaction time' shortened with increase in catalyst amount - up to a certain maximum catalyst amount.
This transition point reveals that regions of mass transfer control and kinetic control can be identified - important information.
Equally important data from different vessels fall on the same curve - including transition from mass transfer to kinetic control.
When data at different temperatures is compared, the results fall on separate lines - except in the mass controlled regions where the data converges.
It is clear that heterogeneous hydrogenation reactions can be performed in parallel and quantitative data can be generated in real time - as the reaction proceeds.
Equally important, it has been shown that with well designed and fully instrumented reactors, performance at different scales - varying by two orders of magnitude - can be directly compared.