Flow Chemistry Transferred to Industrial Plant Scale Up to

Volker Hessel [email protected]

Eindhoven University of Technology

Department of Chemical Engineering and Chemistry

Micro Flow Chemistry and Process Technology

NEXTLAB 2014 - The first NEXTLAB Conference,

Rueil-Malmaison, 04.04.14

Flow Chemistry Transferred to Industrial Plant Scale

Up to Modular Compact Container Plant

Session 6: The laboratory of future: platforms, projects and collaborations

PGM Recycling 2013: 150 t/a*

- 30% of annual PGM production

- about 0.2% of all PGM resources on earth

A. Hunt: Element Recovery and Sustainability,

RSC Green Chemistry Series, 2013

- Platinum as example: Germany is largest Pt exporter to USA (17%)*

- Due to exhaust gas catalyst (automobile) recycling; topping South Africa

CRITICAL ELEMENTS RECYCLING: PGM GROUP

* Salazar, McNutt, U.S. Department of the Interior, U.S. Geological Survey, Mineral Commodity Summaries 2013

Consequence: future’s chemical

plants will be different and integrate

recycling in a ‘biomimetic’ fashion

PLATFORMS AIMING AT FUTURE CHEMISTRY

Industrial Platform:

GSK - GSM

Society Platform:

NRW Landtag / Germany

THE WHOLE IS MORE THAN

THE SUM OF ITS PARTS

Learning curve: HOLISTIC

Green Chemistry needs process extension to Green Engineering

- to cover issues beyond reaction: purification, heat integration, Verbund, …

- to consider full-chain chemical manufacturing: “from cradle to …”

Green Engineering is more than Engineering Green Chemistry

Holistic Route Selection: DOW paper; Leng et al. OPRD (2012)

MEGATRENDS

1. DEMOGRAPHIC CHANGE

2. INDIVIDUALISATION REACHES

A NEW STAGE

3. SOCIAL AND CULTURAL DISPARITIES

4. REORGANISATION OF HEALTHCARE

SYSTEMS

5. CHANGES TO GENDER ROLES

6. NEW PATTERNS OF MOBILITY

7. DIGITAL CULTURE

8. LEARNING FROM NATURE

9. UBIQUITOUS INTELLIGENCE

10. TECHNOLOGY CONVERGENCE

11. GLOBALISATION 2.0

12. KNOWLEDGE-BASED ECONOMY

13. BUSINESS ECOSYSTEMS

14. CHANGES IN THE WORK WORLD

15. NEW CONSUMPTION PATTERNS

16. UPHEAVALS IN ENERGY AND

RESOURCES

17. CLIMATE CHANGE AND

ENVIRONMENTAL IMPACTS

18. URBANISATION

19. NEW POLITICAL WORLD ORDER

20. GLOBAL RISK SOCIETY

IMPLEMENTATION DEGREE OF

MICROREACTORS

Science penetration: 0.46% of all chemical (incl. eng.) literature

2012: 1050 out of 230,000 papers

0

200

400

600

800

1000

1200

2002 2006 2010 2014

Year

Pu

bli

cati

on

nu

mb

er Microreactors

Flow Chemistry

ING Healthcare Fund

2008 2009 2010 2011 2012 2013

ACS GCI Pharmaceutical Roundtable: Conti Processing = Key Area Ranked No.1

C. Jimenez-Gonzalez, P. Poechlauer, et al., Org. Process. Res. Dev. 5 (2011) 900-911.

p

T

Limitations in T

Limitations in p

Chemical Process window

• The microreactor instrumentation has widened engineering windows

• Question is: can it widen chemical windows? Novel Process Windows

T

Stouten et al. Aust. J. Chem. 66 (2013) 121

Hessel et al. ChemSusChem(2013) onlineHessel et al. Chem. Eng. Sci. 66 (2011) 1426Illg et al. Bioorg. Medic. Chem.18 (2010)3627

Hessel Chem. Eng. Technol. 32 (2009)1655Hessel et al. Energy Environ. Sci. 1 (2008)467

Hessel Curr. Org. Chem. 9 (2005)765

WIDENING OF CHEMICAL WINDOWS

6, 5 (2013) 746

NANO-, MIKRO- UND MAKRO-REAKTOREN

2491

cm

nmm

A

High-p,T

<<t

Reflux

>>t

O

OHOH

OHO OH

OH

OH

OH

OH

high THigh T

High p

Process

simplification & integration

Explosive

regime

High c,

solvent free

New chemical

transformation

Novel Process Windows

NPW Research Cluster Hessel, Cortese, de Croon Chem.

Eng. Sci. 66, 7 (2011) 1426-1448.

Novel Process Windows Microreactor-enabled Process Intensification

Top-25 cited paper on NPW

Illg, Hessel, Löb, Bioorg. Medic.

Chem. 18, 11 (2010) 3627-4154

Activate

Confine

Orient

Boost

Simplify

Integrate

Synergize

Minimize

Novel Process

Windows

Hessel, Kralisch, Kockmann,

Noël, Wang, ChemSusChem

6, (2013) 746-789.

CHEManager Europe 5/2012 = Shine a Light

on Novel Process & Business Windows

Novel Process Windows Generate

Opportunities for Coming Projects

2008 2009 2010 2011 2012 2013 2014 2015

TOP-Punt?

ECHO ?

2 Cases – Rufinamide

– Adipic acid

PROCO4WIN ? 2 Cases – Enzymatic

– Hydrogenation

3 Cases – Oil epoxidation

– Biodiesel

– Polymerisation

CONTENTS

• NPW-Activation for Industrial Demonstration (EU Future Factory projects)

- high-T, safety: soybean oil epoxidation (Mythen)

- supercritical, cat.: biodiesel conversion (Chemtex)

- hydrodynamics, high-c: anionic polymerization (Evonik)

• NPW-Process Design for Industrial Demonstration (EU Future Factory, ERC)

- process integration: cascaded & telescoped synthesis (Rufinamide, OmniChem)

- process simplification: direct synthesis (adipic acid, DSM)

- process integration: purification (hydrogenation, Sanofi)

• Plants: Standardized production platforms (Evotrainer) and modular

plants (F3)

- GMP-type Evotrainer

- Cash-flow analysis for Evotrainer for 3 business cases

Exploration trees to materialize exploitation

possibilities and likelihood

© Partner 12

Novel

Process

Window

Existing market:

Competing

applications

New market

segments within

main area

New market

segments outside

main area

Process / material

variant

Process / material

variant

Process / material

variant

Process / material

variant

Process / material

variant

Process / material

variant

…

…

…

Product

… …

…

…

…

Product

… …

…

…

…

Product

… …

…

…

…

Epoxidation

– Initial Kinetic Thoughts … too Simplified

Goal: improve the

STY by a factor of 3

Sustainability motivation:

B. Cortese, B., M.H.J.M de Croon, V. Hessel, V. Ind. Eng. Chem. Res. 51 (2012) 1680-1689.

Epoxidation – Key to Solve: Consecutive Step

© 28.08.2012

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320

0

10

20

30

40

50

60

70

80

90

100

110

120

130

Iodine Number

Iod

ine N

um

ber

Time (minutes)

0

1

2

3

4

5

6

7

8

Epoxide Number

Ox

ira

ne N

um

ber

Epoxidation rate

Opening ring rate

E. Santacesaria, R. Tesser, M. Di Serio, R. Turco, V.

Russo, D. Verde Chem. Eng. J. 173 (2011) 198– 209

D. Kralisch, U. Krtschil, E. Santacesaria, V. Hessel

et al., ChemSusChem 5, 2 (2012) 300-311.

1x 10x

50x 100x

Epoxidation – Superficial H2O2

Decomposition Scenarios

B. Cortese, B., M.H.J.M de Croon, V. Hessel, V. Ind. Eng. Chem. Res. 51 (2012) 1680-1689.

Modelling limitations for NPW

Exploration in Soybean Oil Epoxidation

Instead of using modeling as predictive tool, we needed to (co-)develop it

(together with Naples) = even with proven kinetic model

We found that existing modeling approaches allow only to predict within a

narrow range outside the process window = too narrow for our purposes

On top of that comes that >12 parameters for kinetic model used for

soybean oil epoxidation = too complex, giant task

Still busy with finding a simplified and workable solution here =

mathematical algorithm optimisation

16

D. Kralisch, V. Hessel, E. Santacesaria et al. ChemSusChem 5, 2 (2011) 300-311.

Ex-ante Process Options Evaluation

Biodiesel Production

supercritical processing

utilization of waste oil: low-cost feed valorization

chemical intensification demonstrated in lab

NPW: new chemical transformation: initial idea

Better valorization through coproduct utilization

No chemical intensification achieved, even not with new catalysts

Biodiesel – Economic Motivation,

but Lacking Process Realization

Good heterogeneous catalysts,

but leaching problems

Reaction too slow

to be implemented

Economical advantages –

Materials payback

Catalyst screening

Screening of Environmental Impacts of

Alternative Biodiesel Process Designs

„Best case“ options

D. Kralisch, Ch. Staffel , D. Ott , S. Bensaid, G. Saracco,

P. Bellantoni, P. Loeb, Green Chem.15 (2013) 463-477.

Transfer to Pilot-Plant: Waste Oil to

Biodiesel under Supercritical Conditions

scProcessing:

high ratio alcohol: oil, high T, p

but

counterbalanced by lower residence time,

high conversion rates, avoidance of waste

oil pre-treatment

+

Increased safety by micro processing

Saving potential:

Reduction of greenhouse gas emissions of maximum 70 % (= 0.86 t CO2

equivalents / t biodiesel produced) compared to a conventional

homogeneously acid-catalyzed process utilizing fresh soybean oil

Source: Courtesy of S. Bensaid, Politecnico di

Torino and P. Bellantoni, Chemtex Italia S.p.a.

D. Kralisch, Ch. Staffel , D. Ott , S. Bensaid, G. Saracco, P. Bellantoni, P. Loeb, Green Chem.15 (2013) 463-477.

Novel Process Windows: Polymerization

Living anionic polymerization from batch to continuous

• Experiments (USTUTT): • Batch → PDI = 1.03 for styrene polymerization

• Conti → PDI = 1.04

• Conti → faster conversion rate: 20 x space time yield increase

• Model (TU/e) • Single phase 2-D numerical model, taking into account:

– viscosity change by increase of MW of polymers →

– change in diffusion coefficients; for most of length

of reactor diffusion of monomer is negligible →

– almost completely segregated flow along stream paths

– PDI < 1.1, in accordance with experiments, but

– accumulation of heat from polymerization in reactor →

possible interference with highly segregated flow behavior

Anionic Polymerization

– ‘Anti-Transport Intensification’

1. Segregation effects at small radius

2. Uneven heat distribution

3. Mixer induced effects

MW ABD

Relevant parameters change

locally as a function of conversion

Velocity field Temperature

field

Cortese, Schulz, Klemm, Hessel et al. Macrom. React. Eng.

6,12 (2012) 507–515; Schulze, Cortese, Hessel, Lang, Klemm

et al. Green Process. Synth. 2, 5 (2013) 381-395.

Sanofi Process:

Hydrogenation

- Selective nitro group hydrogenation to the

respective Z- and E-amino compounds

- Desired product : Z-compound

- Production scale: 100 kg/year

C CR F DW C D R

F

WFDry W C CH D D C

C

1

2 3

4

59

6

7

8

10

11

12

13 14

15

17

18

19

20

21

2223

24

2526

28

27

29

30

C – charge; R – react; F – filter; W – wash; D – distillate; H – heat; Co – cool

Co31

32

16

I. Denčić, D. Ott, D. Kralisch, V. Hessel et

al. Org. Proc. Res. Dev. (2014) accepted

Scenarios

The following scenarios were framed and compared with the reference case (batch process):

Scenario Comments

Continuous reaction

Continuous fixed bed millireactor used instead of

the conventional batch reactor. The rest of the

process is performed in batch.

Continuous processing

Continuous reaction in a fixed bed millireactor and

subsequent continuous distillation, acidification, by

product removal, KOM crystallization, filtration and

drying.

Solvent change Replacing the current solvent acetonitrile with

dichloromethane (DCM)

Direct crystallization Direct crystallization of the Z-key compound

followed by its filtration and drying.

KOM recovery Isolation of Z-isomer prior to the reaction followed

by the recovery of KOM from the waste streams.

Microwave drying Replacing the energy-intensive process of vacuum

drying with microwave drying.

I. Denčić, D. Ott, D. Kralisch, V. Hessel et al. Org. Proc. Res. Dev. (2014) accepted

Production Cost Breakdown

Change for Conti Processing

Reference and

continuous

reaction case

Reference case: 17336 $/kg Continuous reaction: 13350 $/kg

Capital cost17%

Labor19%

Other

materials

9%

KIM53%

Waste1%

Utilities1%

Capital

cost

16%

Labour

21%

Other

materials

13%

KIM

49%

Waste

0.3%

Utilities

1%

Reference case: 17336 $/kg Continuous processing: 11330 $/kg

Capital cost7%

Labor17%

Other

materials11%KIM

63%

Waste1%

Utilities1%

Capital

cost

16%

Labour

21%

Other

materials

13%

KIM

49%

Waste

0.3%

Utilities

1%

Reference and

continuous

operation case

Cost Reduction

- Categorywise

Continuous reaction

Continuous processing

Solvent change

Direct crystallization

KOM recovery

Microwave drying

Equipment cost 0.22 0.72 -0.74 -0.03 -0.18 0.32

Materials 0.22 0.22 0.07 0.04 0.11 0.0

Labor 0.30 0.47 0.55 0.20 0.28 0.02

Waste -0.04 -0.04 0.36 0.24 0.39 0.0

Utilities -0.02 -0.02 0.34 0.24 0.13 0.0

Total cost reduction

0.23 0.35 0.04 0.06 0.13 0.06


Performance Metrics

for PI Process Options

Reference

case

Continuous

reaction

Continuous

operation

Solvent

change

Direct

crystallization

KOM

recovery MW drying

Yield (%) 47 52 52 47 50 54 47

Labor hrs

(h/kgKOM) 61.0 43.2 32.8 25.5 26.2 42.7 59.6

PMI

(kg/kgKOM) 118.1 131.3 125.9 72.0 85.8 101.1 118.1

CED

(GJ/kgKOM) 12.5 12.8 11.8 6.0 15.3 14.2 16.7

Solvent waste

(kgSolv/kgKOM) 113.5 128.7 123.4 68.2 87.7 68.2 113.5

Feasibility

remarks ++ ++ + - ++ - +

NOTE: PMI – Process mass intensity

CED - Cumulative energy demand Unfavourable due to diluted reaction mixture


Reaction Network – Multi-step in Flow

Process integration

TELESCOPED MULTI-STEP SYNTHESIS

The European Agency for

Evaluation of Medicinal

Products, London, UK, 2002.

Syrris, Flexx module

15 ppm in API is allowed.

A. Carlos-Varaz, V. Hessel, T. Noel, Q. Wang ChemSusChem 5, 9 (2012) 1703-1707.

TWO ISSUES IN MULTISTAGE

(INDUSTRIAL) FLOW PROCESSING

Extraction Stage Residual Copper

start 3156 ppm

1 159 ± 9 ppm

2 97 ± 3 ppm

3 14 ± 1 ppm

Dipolarophile choice

Entry Dipolarophile Toxicity

(NFPA)

Cost*

($/kg)

Time

(h)

Yield

(%)

T

(ºC)

Excess Solvent/ Additives -R

1[7a]

4 136

24 72 80 1.5 Neat -CN

2[7b]

3

184 2 80 25 1 Water-tBuOH/ Ascorbic acid/

CuSO4

-COOH

3[7c]

2

1500 5 48

65 1 Water -COOMe

4[9]

0

100 28 85 135 1.2 Neat -COOMe

Microfluidic extraction Borukhova, Noel, Metten, de Vos, Hessel ChemSusChem 6, 12 (2013) 2220.

Parameters

Future work

• Copper content in feed

• pH

• Other metals e.g. Pd, Pt

• Different mixing element

Scavenger % Extraction

EDTA, 0.0016 M 90.9

EDTA, 0.0160 M 97.6

DTPA, 0.0160 M 97.9

Cu(PPh3)3Br, 150 ppm feed, toluene, pH: 9.4

EDTA 0.016 M, 150 ppm feed, DMF/toluene, pH: 9.4

Organic solvent % Extraction

DMF 87.2

DMF/Tolene 92.2

Tolene 97.6

EDTA 0.016 M, Cu(PPh3)3Br, 150 ppm feed, pH: 9.4

Copper source % Extraction

CuI(PPh3)3Br 92.2

CuII 98.3

CuIISO4 84.2

CuII(OAc)2 87.7

CONTINUOUS COPPER SCAVENGING

1 stage

Variation of scavenging agent: EDDS

• Variation tested:

• EDTA DTPA

• Similar structure, biodegradable unlike EDTA

EDDS

Scavenger type and

concentration

Molar ratio of

Scavenger : Cu

Cu content (ppm) Cu

Extracted Feed Aq (btm) Org (top)

EDTA 0.016 M

10:1

123 120 3 98%

DTPA 0.016 M 142 139 3 98%

EDDS 0.016 M 118 114 4 97%

EDTA 0.0016 M

1:1

126 115 11 91%

DTPA 0.0016 M 124 118 6 95%

EDDS 0.0016 M 118 81 37 70%

Palladium Scavenging

• Experimental condition is kept similar as Cu scavenging:

• Total flow rate: 60 ml/hr

• EDTA: 0.016 M

• Pd source: Pd(OAc)2

93%

41%

0%

20%

40%

60%

80%

100%

8 8.5 9 9.5 10

Pd

ex

tra

cte

d

Scavenger pH

INDUSTRIAL-SCALE PROCESS DESIGN

Process integration ‘2-Step’

‘Direct’

400,000 t/a

I. Vural Gursel, Q. Wang, T. Noel, V. Hessel, Chem. Eng. Trans. 29 (2012) 565

COST ANALYSIS – ADIPIC ACID

Pu

rch

as

e C

os

t o

f E

qu

ipm

en

t, M

€

0

5

10

15

20

25

30

35

40

45

2-Step Route Direct Route

Pumps

Compressors

Dryer

Vessels / tanks

Distillation columns

Centrifuges / Filters

Crystallizers

Reactors

V. Hessel, I. Vural Gursel, Q. Wang, T. Noel, J. Lang, Chem. Eng. Tech. 35 (2012) 1184

V. Hessel, I. Vural Gursel, Q. Wang, T. Noel, J. Lang, Chem. Ing. Tech. 84 (2012) 660

I. Vural Gursel, V. Hessel, Q. Wang, T. Noel, J. Lang, Green Proc. Synt. 4 (2012) 315

400,000 t/a

Cost Analysis – Adipic Acid

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2-Step Route Direct Route

Pumps

Compressors

Dryer

Vessels / tanks

Distillation columns

Centrifuges / Filters

Crystallizers

Reactors

I. Vural Gursel, Q. Wang, T. Noel, V. Hessel, Chem. Eng. Trans. 29 (2012) 565

To

tal P

urc

hase C

ost

of

Eq

uip

men

t (S

hare

of

Co

sts

)

Other

Equip.

Other

Equip.

Reactor

Reactor

400,000 t/a

Qi, kW Qh, kW Qc, kW Qi, kW Qh, kW Qc, kW

2705 21450 11552 12290 600

35719 18339 1003 2881

17688 2400 15399 947

108 1758 108

3884 654 2290

4293

143

6787

0 60105 42189 28441 18516 600

Initial HEN Design New HEN Design

Total

19116 kW 102294 kW

Qi: process-to-process; Qh: hot utility; Qc: cold utility

70 %

reduction Cost 19.8 x 106 €/yr 6.0 x 106 €/yr

Total utility

ENERGY COMPARISON

I. Vural Gursel, Q. Wang, T. Noel, V. Hessel, J. Tinge, Ind. Eng. Chem. Res. 52, 23 (2013) 7827-7835.

PA

GE

Extra Capital Cost

(106 €)

Operating Cost Saving

(106 €/yr)

Pay-back time

(months)

9.28 13.80 8

I. Vural Gursel, Q. Wang, T. Noel, V. Hessel, J. Tinge, Ind. Eng. Chem. Res. 52, 23 (2013) 7827-7835.

IMPROVED HEN DESIGN

DIRECT ROUTE – LCA FOOTPRINT

1. AP: acidification potential (average European)

2. GWP 20a: climate change in 20 years

3. EP: Eutrophication potential (average European)

4. FAETP 20a: freshwater aquatic ecotoxicity in 20 years

5. HTP 20a: human toxicity in 20 years

6. Land Use

7. Malodours Air

8. MAETP 20a: marine aquatic ecotoxicity in 20 years

9. High NOx Photochemical oxidant creation potential

10. Depletion of abiotic resources

11. TAETP 20a: Terrestrial ecotoxicity in 20 years Database: Ecoinvent. Source: CML2001

Q. Wang, I. Vural Gursel, M.

Shang, V. Hessel, Chem. Eng. J.

234 (2013, 300-311.

©

Fraunhof

Building a Process

or Plants in Boxes?

“Container Village” ChemPark

Unit-operational process

assembly

Central docking hubs

CONTAINER PLANT FOR F3

FACTORY AT INVITE FACILITY

Process Equipment Container (PEC) Process Equipment Assembly (PEA)

Docking Station PEC – BASF/Polymer

PEC – Bayer/Pharma

Our approach: “in one box” from process idea to a plant

Lab work, evaluation plant and small production in the same environment

Lab – Pilot – Production

= same Professional Environment

©

Fraunhof

Option for automatic

filling

Raw material logitics

transport can

Option for air

conditioning

Desaster collection

pan (WHG)

Element for

environmental

protection

Control room

Ex zone gate

Extinguishing

installation

Constructive fire protection

Reduced emissions

e.g. nois

Bus integration:

a) lighting

b) Ex control

c) cabel ways, power

d) Pneumatic system

e) Field bus

f) compressed air,

gases

g) cooling water,

sole

h) local area network

i) air ventilation

j) etc.

* Easy entry

* integrated emergency exits

* montage doors

integrated elements

for construction

On demand

CMP- a./o. clean room

condition

Modular measure and

control technology

Patent pending

A chemical plant

in a box ??

Transfer of Evonik´s Evotrainer for

POLYCAT to Fraunhofer ICT-IMM

site for project demonstration works

Integration of multipurpose flow-system

into Evotrainer process room

addressing API synthesis needs

CONTAINER PLANTS

– POTENTIAL FOR COST REDUCTION?

Lower interest rates

Faster time to market

(“50% idea”)

Wo

rkfl

ow

Ba

sed

on

Mo

du

lar

Co

mp

on

en

ts Process Selection

Modular Assembly Planning

Preassembling Modules

Short Field Installation

Start-up

Optimal Configuration Selection

More efficient embedding of

smart production technologies

Standardized infrastructure: fixed,

small-serial manufacturing costs

Risk depends on capacity risk [%] > risk [%]

NPV ECV

cash

time risk [%]

Compactness

Fine-chemical Case – Capital Investment (200 t/a)

Microreactor operation higher investment cost due to higher cost of more

advanced flow reactor, with 60% yield due to smaller reactor, lower cost

Evotrainer enables ~15% lower capital investment than conventional plant

Evotrainer gives

opportunity for

micro to have

comparable

investment cost

I. Vural Gursel, V. Hessel, Q. Wang, T. Noel, J. Lang, Green Proc. Synth. 1, 4 (2012) 315

Fine-chemical Case – Operating Cost (200 t/a)

Microreactor lower raw material (excess of KHCO3 3 fold instead of 6 fold) and

labour requirement, with 60% yield significant raw material cost reduction

High value product example, raw material cost dominates, Evotrainer effect small


Evotrainer advantageous for fine-chemical and pharma production

Bulk-chemical not profitable at this low production rate

Three Chemical Applications (200 t/a)

PAGE 49

Pharmaceutical

Fine-chemical

Bulk-chemical

2,4-dihydroxybenzoic acid

adipic acid

naproxen

All in flow

ca. 25%


Book Novel Process Windows

Green Processing & Synthesis

Dr. Q. Wang Assistant prof.

G. Kolb Part-time prof.

N. Straathof PhD

L. Borukhova PhD

Dr. T. Noel, Assistant prof.

I. Vural, PhD

I. Dencic PhD

S. Stouten, PhD

SFP Group: Micro Flow Chemistry

and Process Technology

F. Aldiansyah Master

M. Shang PhD

B. Spasova PhD at IMM/TUD

J. Tibhe, PhD

B. Patil PhD

A. Anastasopolou PhD

A. Hemert Secretariat

J. Smit Editorial Assistant

E. Shahbazali PhD

H. Gemoets PhD

S. Sundaram PhD

MERCI !!!

Documents

Flow Chemistry Transferred to Industrial Plant Scale Up to