By Gerard B. Hawkins

Managing Director, C.E.O.

The value of selecting the right catalyst Selecting the key performance criteria Sources of data: ◦ Plant data ◦ Laboratory reactor data ◦ Catalyst characterization

Recommendations

Catalyst selection is a very important activity It is a significant expenditure It has a major impact on: ◦ Plant efficiency ◦ Plant rate ◦ Achievement of desired turnaround schedule

The plant efficiency benefits can be greater than the catalyst cost

The plant rate impact of the right catalyst can be many times the cost of the catalyst ◦ The converse is equally true ◦ 1% of plant rate can be worth $0.5-1.0million/yr.

The cost of an unscheduled turnaround due to catalyst failure will be many times the cost of the catalyst ◦ 3days lost production cost >$1million

This is more difficult than it might first appear First thoughts are likely to be: ◦ Activity Want high conversion through close approach to equilibrium ◦ Pressure drop Low pressure drop improves efficiency and plant rate ◦ Strength Want zero breakage during loading and to sustain high plant

rate through stable pressure drop with time

Further thought adds some more criteria: ◦ Activity retention/stability Life may be set by the time required to reach end of life

activity ◦ Selectivity Are by-products a problem? e.g. methanol, carbon, ethanol ◦ Poison resistance In some duties (e.g. LTS) this has more impact than activity

retention on catalyst life ◦ Heat transfer Key for primary reforming products

This is a key question because the answer depends on the plant design and the business objectives of each plant

It is also important to be clear on the desired objective as there is often a trade-off between the combination of properties offered by each catalyst option

The selection criteria will be different for each catalyst ◦ e.g. primary reforming – carbon margin; LTS – poisons

resistance

Steam reforming requires high activity and high heat transfer ◦ Hence want small pellets

But smaller pellets create higher pressure drop!

The optimum is likely to be: ◦ to select the smallest pellet size that gives a pressure

drop that does not limit production rate and ◦ to put small pellets where activity and heat transfer is

required and larger pellets where most of the pressure drop is created

LTS lives are determined by the depth required for conversion (activity) and the depth required to collect poisons

So is activity or poisons most important? Look at the end of run profile:

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It should now be clear that catalyst selection is not simply looking for the highest activity or lowest pressure drop

Alternatives need to be evaluated – using rigorous plant modelling tools to determine the optimum combination of properties

Cash flow is tight so I will plan on short loading the the LTS reactor so it lasts until the turnaround in 4 years time with a 20% safety margin to allow for unforeseen changes.

The projected end of run profile says that poisons resistance is twice as important as activity ◦ So I will look for data comparing the poisons performance

of my catalyst options and choose the catalyst that minimises my volume/cost

Plant data Laboratory reactor data Catalyst characterization

Without doubt the most valuable source of performance data ◦ Especially from ones own plant No requirement to correct for space velocities/feed impurities

However with 4-8yr catalyst lives there is a good chance an improved product will be available for the replacement ◦ So one needs to use data from other plants Important that data fitting (e.g. VULCAN CERES, VULCAN

TP3) is used to consistent basis the conclusions

Laboratory reactor data can be close in value to plant data

Laboratory data is important for new products to relate performance to existing proven products

However it is difficult to reproduce plant conditions in the laboratory and hence poor understanding of the scale-down factors leads to poor data – so beware!

Real example of independent assessor of shift catalyst activity: ◦ Space velocity 14000hr-1 compared to plant at 7000hr-1

This is not as good as it appears – see below ◦ Bed length 0.075m compared to plant 4m ◦ Net effect is that gas velocity in test is 1/25th of plant laminar flow compared to plant which is turbulent ◦ With laminar flow in the test - diffusion effects dominate

and catalyst activity has secondary impact ◦ Performance mainly affected by pellet external area!

The tester commented that his data over many years had shown a good correlation between GSA and activity

This is not surprising – his test was more sensitive to GSA than activity

His test was no more than a sophisticated ruler!

Good lab testing recognizes the scale factors and each test focuses on one key performance factor

Adiabatic reactors are notoriously difficult to reproduce in the lab because of heat losses

Judging activity from rate of temperature rise is not advised

Hence lab activity tests should be performed: ◦ isothermally ◦ at very high space velocity ◦ using gas compositions representative of different parts of

the plant reactor

The sample should be tested under plant process conditions – with more severe conditions applied to the performance factor of interest: ◦ High space velocity for activity ◦ High poisons for poisons resistance

It is also preferable to have the ability to do some accelerated aging of samples ◦ fresh material is not representative of the average

condition in plant ◦ requires an understanding of the aging mechanism, so this

can be induced faster than real time

This data can be useful It is important to review how the test manages the

scale-down factors so the data can be related to real plant

This is the third type of data on catalyst that can be reviewed

It is the easiest to obtain It has huge opportunity for misinterpretation Use of this data gives a high likelihood that the

wrong catalyst will be selected and hence negatively impact on plant performance

GBHE VULCAN Series Catalysts would like to see a clear relationship between properties and performance so it would be clear that VULCAN Series products are better!

Unfortunately this is not easy as the examples that follow will show

Metal weight % Promoter weight % Metal surface area Pore structure (volume/diameter) Support surface area Crush strength

A key measure – but: Is the metal located where it needs to be? ◦ For acetylene hydrogenation the location of the active

metal relative to the pellet surface is critical ◦ Nickel in the centre of reforming catalysts has little impact

as reaction is close to the surface Does higher a metal level lead to loss of another

important factor? ◦ High levels can encourage sintering/deactivation ◦ High copper in LTS/methanol synthesis means lower

alumina and zinc – potentially affecting strength and poisons resistance

Usually low levels of promoters enhance performance and high levels have a negative effect – often decreasing activity

What is the optimum level? ◦ This will be different for catalysts made by different

methods ◦ For example - poisons performance of LTS catalysts with

similar alkali promoters: Chl id P i i R i t

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Accumulated Cl

CO conversion (%)

83-3X

Comp 1

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VSG-C111

Generally one would expect higher metal areas to provide more opportunity for reaction

The metal activity is also affected by the support, promoters and crystal structure

An example is LTS where the precursor crystal structure has a major impact:

This is still an active area of academic research to try to correlate pore structure to performance

Other factors such as ‘connectivity’ need to be included

A general view can be taken but it is difficult to use this data quantitatively

Example below shows the dual pore structure of VSG-F101 and its minimal change on reduction

Incremental Intrusion vs Diameter

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1.E-02 1.E-01 1.E+00Diameter (µm)

Incr

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As received 71-6Reduced 71-6

As Received F101 Reduced F101

Larger support areas may reduce sintering However the support itself can sinter and areas become

lower when the product is put into service

Note it is important when comparing data to check whether ‘catalyst surface area’ is ◦ metal or support ◦ as-supplied or post-reduction.

The as-supplied strength is important for catalyst loading

This strength may have little relationship with strength in service, and this can change with time

The plot below shows how different HTS catalyst strengths change over just a few weeks of service

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VSG-F101

Very difficult to relate this data quantitatively to catalyst performance

Main value is making sure that the catalyst supplied confirms the to suppliers specification

Plant data is the most valuable source of catalyst performance data

Data from ones own plant is the most valuable Regular data collection, reconciliation, and review

is essential ◦ More detailed recommendations follow

Overall ◦ A full plant balance should be taken at least twice a year

and the data reconciled to a consistent heat and mass balance e.g. using the VULCAN CERES / VULCAN TP3 programs

Purification ◦ Feed levels can be used to estimate absorbent usage ◦ Exit levels check performance ◦ Poison profile on discharge is key to assessing average

poison pickup for a reactor charge

Sulphur Absorbent ProfileResults of Scanning Zinc Oxide Vessel

Position in Reactor

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TRACERCO Scan Lab analysisRadio Isotope Scan

The key measurement is tube wall temperature ◦ This is the highest potential cost ◦ Data from daily inspections should be recorded monthly

A periodic reformer survey will assess catalyst performance as well as checking other aspects of reformer operation

The reactor temperature profiles should be recorded at least quarterly

The steepness of the profile shows the activity The rate of movement of the start of the profile,

coupled with discharged catalyst analysis shows the poisons performance

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The key measure here is the carbon oxides slip Note that this reactor is different to the rest as it is

kinetically limited - not equilibrium The profile should be almost complete in the top

third of the bed – but the rest of the bed is required to perform the remaining conversion form the order of 500ppm down to less than 5ppm

These are recycle loop reactors requiring modelling tools to rationalize the data, evaluate the activity (and then optimize)

The performance of ammonia catalyst changes very slowly ◦ Annual or 2 yearly evaluation of activity will show the

performance Methanol synthesis catalysts change more quickly,

particularly in the first year of operation ◦ Data should be evaluated quarterly

This can be close to the value of plant data The basis of the test must reviewed to evaluate its

relevance to real plant If the test is poorly designed – ignore the data

This suffers from a lack of ability to translate the data quantitatively to catalyst performance

Use of this data to assess different catalysts is not advised

Its best use is checking product supplied conforms to the suppliers specification

It is worth making the highest quality catalyst selection to both achieve the highest plant performance and avoid the cost of unscheduled turnaround

The most valuable source of data is from real plants – particularly ones own

Lab data is useful but must be used with caution Catalyst characterization is not advised for

performance evaluation but only as a QC check for product supplied