6 February / March 2018


data were collected. This has been modifi ed such that the old reference data are no longer overwritten.


Figure 4: Bar plot of the comparison of the GCxGC and DHA results from fi ve injections a day over three days of a hydrocarbon stream. The bar plots indicate the concentration of various compounds calculated after total abundance normalisation. The error bars indicate the spread of all injections over the three days (RSD < 3.5%), and the percentages above the bars indicate the absolute difference between the two techniques.


iso-paraffi n, and aromatic) were considered. Figure 4 shows the concentration of the selected compounds calculated after total abundance normalisation. The error bars indicate the spread of all injections over the three days, which was determined to be less than 3.5% RSD. The values above the bars indicate the absolute difference between the GCxGC and DHA results; as can be seen, the absolute difference was less than 6%, indicating good agreement between the two sets of data.


Online GCxGC


In process development, evaluation and optimisation of catalyst formulations is an important undertaking. In a typical approach, catalyst descriptors (based on synthesis and characterisation data) are coupled to catalyst performance data (based on experimental testing). Testing is usually performed in fi xed-bed reactors, from which the reactor effl uent composition is monitored as a function of process conditions at various moments in time. Such data are crucial to monitor the conversion level of the feed, the selectivities to products and the stability of performance as a function of conditions, and time on stream. For many reactions, this becomes complicated when reaction products are diverse (isomers, different groups and types, etc.), which does not allow the application of traditional 1D GC. For specifi c chemistries such as syngas to olefi ns (typically 15-25% heavy by-products) and syngas to liquid hydrocarbons (typically > 85 liquid products


with long hydrocarbon chains), Dow has developed on-line GCxGC in order to analyse reaction products at short intervals during operation.


One of the requirements for an online system is that it is stable. In order to determine this, a reference standard is measured regularly, which must fall between the upper and lower control limits. The current system requirements have the upper and lower control limits set at a signifi cance level of 0.03, or a confi dence level of 97%. The long term reference monitoring data is shown in Figure 5, and as can be seen, the system has been operating with stability for over three years. However, it should be noted that there is a gap in reference data for much of 2015, which is explained by the fact that the previously collected reference data were overwritten when new reference


The successful application of an online approach requires full automation of the analysis from the sampling to the analysis and reporting of the results. For the online application of GCxGC in catalysis laboratories in Dow, the full automation for the analysis was provided by the in-house customised commercial reactor control system, which controlled the sampling via sequentially selecting reaction streams for an individual reactor at a time and triggering analysis start as well as position tagging and time stamping of samples. The GC analysis, integration of results and reporting automation were made possible by confi guring the commercial control and analysis software packages mentioned in the experimental section. The automation in further processing and storing of the results to a database system was enabled by in- house written macros.


From each reactor in the instrument setup, three sets of data were collected, one- dimensional TCD data, one-dimensional FID data, and two-dimensional FID data. The macros for data automation described above converted the three sets of data collected from each individual reactor at a given time into a bar plot (Figure 6). The colour coding of the bar plot corresponds to the different hydrocarbon groups (PIONA), and allows for a visual comparison of the data collected from all of the reactors over the study duration.


Examples of chemistries explored by Dow in this unit include syngas and CO2


to


alcohols [7], syngas to light hydrocarbons [8, 9], syngas to olefi ns [10], and syngas to synthetic liquids [unpublished data].


Figure 5: Run chart of the reference signal obtained from the reference standard (arbitrary units) collected from the online GCxGC system including upper and lower control limits.


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