Smart Data Visualization for High-Throughput Data

Whether you are operating high-throughput equipment or you only work with the results, visualizing the data efficiently is key for sending a quick and clear message. At Avantium, we operate units that test up to 64 reactors in parallel. This means that the amount of data generated quickly builds up and conventional visualization plots provide more confusion than clarity. This makes it necessary to use smart visualization figures allowing operators and scientist to quickly decide on unit performance or interpret data in a fast and efficient way.

How to visualize Trending Data?

Assume that the reaction pressure is a critical process parameter, which you want to monitor closely. A common approach would be to create 64 scatter plots (one per reactor) showing the trends of reaction pressure versus time (see Figure 1). Reviewing these 64 individual figures would be a lengthy process and it could even become confusing with so many plots. In a different approach, you could make a scatter plot that includes the data of the 64 reactors and choose different colors (or markers) to differentiate them. In this case, the density of the data is so high that one could barely distinguish data from one reactor to the other, and there will be little understanding of what is happening with this critical process parameter, as shown in the picture.

Figure 1 : Reaction Pressure in dependence of time 

A smarter way to visualize trending data

The use of a smart figure would allow both operators and scientists to quickly identify if a process variable is within specifications or if actions are required, e.g. a pressure drift could indicate the plugging or bypassing of the catalytic bed. The smart plot we have chosen for this case is called a Cell plot. At Avantium we automatically generate these type of figures using JMP and using the trending data from our Flowrence software. A typical cell plot representing the reaction pressure as a function of time, for 64 reactors working in parallel, is shown in Figure 2.

In this case, the color represents a continuous scale, showing red and blue for the upper and lower specification limits, respectively. When you look at the graph, you can now easily see that the pressure in all 64 reactors is within the limits of the specifications. In addition, as the color per reactor varies slightly one could interpret that the pressure per reactor is stable. Besides, one could quickly detect that R21-R23 have a higher-pressure trend compared to the other reactors. This fast analysis could be followed by a more detailed review of process conditions of reactors showing irregular behavior, for example by use of Shewhart control charts, but instead of drawing 64 plots, we would need to focus only in 3 of them, corresponding to reactors R21 to R23.

Figure 2 : Cell Plot of Reaction Pressure in dependence of time 

Visualize Catalyst Performance Data

In high-throughput catalyst testing programs, the target is usually the evaluation of different catalyst formulations to identify the most promising materials considering key performance indicators, catalyst synthesis price and/or catalyst synthesis recipes. Within Avantium, we have specialized catalyst-testing services to evaluate a broad range of catalysts in terms of conversion and yield to the desired product while keeping an eye on the final price. In these large screening campaigns, the priority is to quickly identify the catalysts with the highest yield. However, we observe that there is an increasing desire to cluster the data based on the composition, which allows the customer to understand better the results.

Figure 3 : Catalyst Yield vs. Catalyst Price

In Figure 3, one could identify the circled catalyst as the most promising candidates, considering that the price is relatively low and the yield is relatively high. However, immediately questions arise: “How many of the ZSM-5 containing catalysts where tested?” or “Are these promising catalysts outliers? “

Figure 3 : Catalyst Yield vs. Catalyst Price

In Figure 3, one could identify the circled catalyst as the most promising candidates, considering that the price is relatively low and the yield is relatively high. However, immediately questions arise: “How many of the ZSM-5 containing catalysts where tested?” or “Are these promising catalysts outliers? “
One way to answer these questions is to transform the data and use a bar chart, grouped by active component as shown in Figure 4. Now, one can easily identify which catalysts perform better, based on the Yield/Price ratio, and the color map provides a direct link to rank material based on their cost.

A disadvantage is that the x-axis is saturated because of the number of catalysts screened in this test, and therefore, its analysis becomes cumbersome. This is especially ineffective for presenting data or results at management level meetings. The use of a smart figure would allow clear and fast interpretation of the data.

Ideally, everyone should be able to look at the plot and in an instant be able to judge which catalysts are performing better, and answer questions like “Did I select a reasonable amount of materials from each class?” and “What cost level is the catalyst?”. For this case, we have selected a Treemap as a smart plot visualization.

Figure 4 : Bar chart of Catalyst Yield vs. Catalyst Price

Figure 4 : Treemap plot of Catalyst Yield vs. Catalyst Price

The figure shows two axis, Yield/Cost versus Catalyst and the color as the total cost. However, the technique is now to segregate catalysts in different areas of the plot to indicate the main zeolite component, and to use the size of the individual boxes to provide information on the Yield/Cost ratio. Please note that the area of each box is proportional to the normalized Yield/Cost ratio, which allows comparison across catalysts with different zeolites.

It can easily be observed that, within these tests, a similar number of total catalysts containing USY compared to the sum of SAPO-34 and BETA were tested, and approximately a third of the samples tested contained ZSM-5 as active zeolite material. Within each of these areas, one can identify the best performing catalyst on the upper left corner and the color indicates the normalized cost.

The results shown in this Treemap indicate that the best catalyst is Cat 11 (among the tested materials, of course); the number of catalysts screened with this active component is significant (box size of ZSM-5 is a 1/3 of the total amount screened); and lastly, that a proposal for follow-up test could consider more SAPO-34 and BETA material to show that an even selection solids has been done. In our busy day-to-day activities such smart figures simplify the interpretation of results by conveying a clear message in a single picture.

General guidelines for a clear visualization

No matter which smart visualization you choose, the message should be conveyed in a simple and concise form to facilitate the communication process. Always keep in mind, advanced statistical and modeling tools are needed to make quantitative conclusions and identify optimal values for key parameters. In this newsletter, we emphasize those that must be considered sine qua non:

1. Keep it simple

Whenever possible, make simple figures and avoid saturation with unnecessary information.

2. Know your audience and define the key message

Determine your audience to tailor the graphics based on your key message. Consider three main types of audiences: managerial, technical or academics and non-technical. They all have different needs.

3. Use colors effectively

Minimize the use of color whenever possible. If you have troubles selecting colors, remember the color wheel.

4. Use the correct tool

Plots need to be informative and engaging. The correct tool, e.g. Matplotlib, R or JMP, can facilitate the preparation of your story and the visual context around it.

Flowrence® products specifications

Reactor Section

Easy and quick reactor exchange system. Possibility to use quartz reactors at high pressure.

1 block of 4 reactors

HT = High Temperature max. 800°C nominal, limited to 925°C (<0.5°C reactor to reactor deviation)

4 blocks of 4 reactors

HT  or MT = Medium Temperature max. 525°C (<0.5°C block-to-block deviation)

16 reactors with iRTC

individual Reactor Temperature Control
max. 550°C (<0.5°C reactor-to-reactor)

4 reactors with iRTC

individual Reactor Temperature Control
max. 550°C (<0.5°C reactor-to-reactor)

Temperature Ranges (°C)

100 – 800°C
up 925°C (Option)

50 – 525°C
100 – 800°C
up 925°C (Option)

50 – 550°C

50 – 550°C

Reactor Types

L= Length
OD= Outer Diameter
ID= Inner Diameter
SS= Stainless Steel (< 550⁰C)
Qz= Quartz (< 925⁰C)

L 300 mm 561 mm
OD 3 mm 6 mm
ID SS 2 / 2.6 mm 2 / 3 / 4 / 5 mm
ID Qz 2 mm 2 / 4 mm
300 mm 561 mm 561 mm
3 mm 3 mm 6 mm
2 / 2.6 mm 2 / 2.6 mm 2 / 3 / 4 / 5 mm
2 mm 2 mm 2 / 4 mm
561 mm
3 mm
2 / 2.6 mm
2 mm
561 mm
3 mm
2 / 2.6 mm
2 mm

Maximum Catalyst Bed Length

(isothermal zone tolerance ± 1°C)
Note: isothermal length is dependent on the temperature range

300 / 3 HT 561 / 6 HT
>120 mm @ 450°C >200 mm @ 500°C
>90 mm @ 800°C >150 mm @ 800°C
>140 mm @ 925°C
300 / 3 HT 561 / 3 MT 561 / 6 HT
>120 mm @ 450°C >310 mm @ 450°C >200 mm @ 500°C
>90 mm @ 800°C >150 mm @ 800°C
>140 mm @ 925°C
561 / 3 MT iRTC
250°C ±0.5°C 41cm (4reactors)
350°C±0.5°C 38cm (4reactors)
550°C±0.5°C 28cm (4reactors)
3 reactors at 550°C, 1 reactor 350°C:
550°C=27cm 350°C=41cm ±0.5°C
561 / 3 MT iRTC
250°C ±0.5°C 41cm (4reactors)
350°C±0.5°C 38cm (4reactors)
550°C±0.5°C 28cm (4reactors)
3 reactors at 550°C, 1 reactor 350°C:
550°C=27cm 350°C=41cm ±0.5°C

Catalyst Volume (mL)

(isothermal zone)

0.2 - 0.6 mL 0.4 - 2.0 mL
0.2 - 0.6 mL 0.4 - 1.0 mL 0.4 - 2.0 mL
0.4 - 1.0 mL
0.4 - 1.0 mL

Pressure Ranges (barg)

2 – 80 barg
0.5 – 180 barg (option)

2 – 100 barg
0.5 – 180 barg

2 – 80 barg
0.5 – 180 barg

2 – 20 barg
2 – 50 barg (option)

Reactor Pressure Control

Advanced control RSD ±0.1 barg at reference conditions (gas phase only and 20 barg). For trickle flow Advanced control RSD ±0.5barg.

Standard (±0.5 barg)
Advanced (±0.1 barg) (option)

Standard (±0.5 barg)
Advanced (±0.1 barg) (option)

Advanced (±0.1 barg)

Advanced (±0.1 barg)

Gas Feed Lines

(#Gas Feeds)

Up to 6 + Diluent gas

He, Ar, N2, H2, CH4, CO2, C2H4, C2H6, O2/Inert (≤5%), CO, Other gases

Up to 7 + Diluent gas

He, Ar, N2, H2, CH4, CO2, C2H4, C2H6, O2/Inert (≤5%), CO, Other gases

Up to 7 + Diluent gas

He, Ar, N2, H2, CH4, CO2, C2H4, C2H6, O2/Inert (≤5%), CO, Other gases

Up to 6 + Diluent gas

He, Ar, N2, H2, CH4, CO2, C2H4, C2H6, O2/Inert (≤5%), CO, Other gases

Online Analysis

Full integration GC, MS , GC/MS with data visualisation (option)

Full integration GC, MS , GC/MS with data visualisation

Full integration GC, MS , GC/MS with data visualisation

Full integration GC, MS , GC/MS with data visualisation

Liquid Feed

 Split feeding 8 + 8 reators (option)

Pump-Coriolis dosing system
(ambient, cooled)

Pump-Coriolis dosing system
(ambient, cooled, heated 80°C)

Pump-Coriolis dosing system
(ambient, cooled, heated 80°C)

Pump-Coriolis dosing system
(ambient, cooled, heated 80°C)

Liquid Distribution

Microfluidic Distribution
(4-channel glass-chip)

Microfluidics Distribution
(4x4-channel glass-chip)
(16-channel glass-chip)
Active Liquid Distribution (option)
(with automatic isolation valves)

Active Liquid Distribution
(with automatic isolation valves)

Microfluidic Distribution
(4-channel glass-chip)

Liquid Sampling

(G/L Separation)

Parallel liquid sampling (4 x 20ml vials) with sequential on-line gas phase sampling (option)

Automated liquid sampling (4 rows x 16 vials x 8ml) with sequential on-line gas phase sampling (option)

Automated liquid sampling (4 rows x 16 vials x 8ml) with sequential on-line gas phase sampling (option)

Parallel liquid sampling (4 x 20ml vials) with sequential on-line gas phase sampling (option)

Reactors Effluent Handling

(Off-line Analysis Connection)

Full heated circuit up to 180°C with sequential on-line full gas phase sampling (option)

Full heated circuit up to 200°C with sequential on-line full gas phase sampling

Full heated circuit up to 200°C with sequential on-line full gas phase sampling

Full heated circuit up to 200°C with sequential on-line full gas phase sampling

Offline Analysis

Integrated Workflow: SimDist, total S/N, liquid density, balance, label printer, barcode (option)

Integrated Workflow: SimDist, total S/N, liquid density, balance, label printer, barcode

Integrated Workflow: SimDist, total S/N, liquid density, balance, label printer, barcode

Integrated Workflow: SimDist, total S/N, liquid density, balance, label printer, barcode

Waste Handling

Ambient temperature
Heated wax trapping (option)

Ambient temperature / Cooled containers / Heated compartment (wax trapping, heavies)

Ambient temperature / Cooled containers / Heated compartment (wax trapping, heavies)

Ambient temperature / Cooled containers / Heated compartment (wax trapping, heavies)

Safety

Gas sensors and control box (CO, LEL, VOC)

Gas sensors and control box (CO, LEL, VOC)

Gas sensors and control box (CO, LEL, VOC)

Gas sensors and control box (CO, LEL, VOC)

Flowrence® Software

Flowrence® recipe builder, control & database builder

Flowrence® recipe builder, control & database builder

Flowrence® recipe builder, control & database builder

Flowrence® recipe builder, control & database builder

Microfluidics modular gas distribution

Unrivalled accuracy in gas distribution with patented glass-chips for 4 and 16 reactors, with a guaranteed flow distribution of 0.5% RSD. Quick exchange of glass-chips for different operating conditions. Flexibility to cover a wide range of applications.

TinyPressure glass-chip holder with integrated pressure measurement

Compact modular design for gas and liquid distribution. No high-temperature pressure sensors required. Quick exchange of the microfluidic glass-chips, without the need for time-consuming leak testing.

Tube-in-tube reactor technology with effluent dilution

Unique tube-in-tube design with easy and rapid exchange of the reactor tubes (within minutes!). No need for any connections. Use of inert diluent gas (outside of reactor) to maintain the pressure prevents dead volumes and back flow. Possibility to use quartz reactors at high pressure applications.

Automated liquid sampling system

Programmable, fully automated liquid product sampling robot for 24/7 hands-off operation. Robot equipped with a compact manifold aiming at depressurizing the effluent immediately after each reactor to atmospheric pressure. Eliminates the use of high pressure valves.

Reactor Pressure Control (RPC)

The most accurate and stable pressure regulator for a 16-parallel reactors with just ±0.1bar RSD. The RPC uses microfluidics technology to regulate the pressure of each reactor, maintaining equal distribution of the inlet flow over the 16 reactors.

Auto-calibrating liquid feed distribution, measurement, and control

Distribution of difficult feedstocks e.g., VGO, HVGO, DAO. Liquid distribution 0.2% RSD, making it the most accurate liquid distribution device on the market. Option to selectively isolate each reactor.

Single-Pellet-String-Reactors (SPSR)

No dead-zones, no bed packing & distribution effects. The catalyst packing is straightforward and does not require special procedures. A single string of catalyst particles is loaded in the reactors avoiding maldistribution, eliminating channeling and incomplete wetting.

EasyLoad®

Unique reactor closing system with no connections. Rapid reactor replacement minimizing delays, improving uptime and reliability. Stable evaporation by liquid injection into reactor.

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Avantium Headquarters

+31 (0)20 586 8080

Zekeringstraat 29
1014 BV Amsterdam
The Netherlands

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