Techno-economic assessment of CO2-containing polyurethane rubbers [original]

Techno-econ omic assess ment of CO 2 -containi ng
polyur ethane rubber s
Georg A. Buchner a , Nils W ulfes a , Reinhard Schomäcker a *
Technische Universität Berlin, Department of Che mistry, Straße de s 17. J uni 124, 10623
Berlin, Germany

a Technische Universität Berlin, Department of Chemistr y , TU Berlin, Straße des 17. J uni
124, 10623 Berlin, Germany

E-mail addresses: [email protected] (G.A. Buchner), n.wulf [email protected] (N.
Wulfes), schomaec ker@t u-berlin.de (R. Schomäcker)

* Corresponding author details: E-mail: [email protected] ; Phone: +49-(0)-30-314-
24973; Address: T echnische Univ ersität Berlin, Department of Chemistr y, TU Berlin, S tra ss e
des 17. Juni 124, Sekretariat TC 8, 10623 Berlin, Germany

Abstract
Ca rbon capture and utilization technologies can open up new s y nthesis routes with economic
benefits. Recently, the inclusion of carbon diox ide in pol y ols was ex tended b y
copolymerizing double bond agents. This allows for subsequent chain-extension with
diisocya nates to polyurethane rubbers. This paper assesses their economic viabilit y . A
preliminary techno-economic assessment based on e xtended block flow diag rams re veals
substantial uncertainty in profitability indicators due to appl y ing a short-cut capital
expenditure estimation method. Consequentl y , a process design for the polyol production was
carr i ed out, enabling a refined TEA incorporating an equipment-cost-b ased approach. P ositive
net present values are reported for multiple [ double bond agent] -[diisocyana te]-[ benchmark]
combinations. The n et present value is most sensi tive to the s ales and propylene ox ide prices.
The choice o f the doubl e bond moiet y has decisive effect ; the choice o f th e diisoc yana t e has
minor effect on the TEA . Finding a favorable market posi tion remains the biggest challen ge
for CO 2 -containing s y nthetic pol y urethane rubbers .

Keywords: Carbon diox ide utilization, pol y urethane, rubber, elastomer, techno-economic
assessment, process desig n

1 Introduction
While carbon capture and utilization (CCU) technologies are mostl y view ed from the
perspec tive of climate change mi tigation, they can at the same time open up new s y nthesis
routes with possible economic benefits [1 – 3]. A variet y of CCU technologies have been
proposed and research, development and deployment (RD&D) has ex perienced a very
dyna mic growth in recent y ears [4] . The c opoly m erization of carbon d ioxide (CO 2 ) with
epoxides to form poly eth er carbonate pol yols as building blocks in pol y urethane
manufacturing has attracted market interest due to life cycle impact reductions in nine
categor ies such as global warming impact [ 4,5] as well as potential economic benefits through
cost reduction [6 – 8]. Poly urethane chemistr y sho ws gre at versatilit y and i ntensive res earch on
material properties with the intent of broadening the spectrum of applications is undergoing
[9] . I n this context, CO 2 -containing pol y ols that include double bonds (DB) in the pol y mer
chain were invented, providing additional functionality [10]. The introduc tion of this ne w
polyure thane building bl ock enables new p athway s; two general research directions can be
distinguished [11,12]:
I) Low DB content, bi functional: These pol yols ca n be elongated with diisocy anates to
polyure thanes. The resulting mate rial is a sy nthetic rubber ( i.e. (linear) unsaturated
polymer chains) th at is c ompounded and vulcanized to elastomers in following steps
[13] . Hence, the novel chemistry presents an alternative for the chemical production
steps (in a narrower sense) in typical ela stomer va lue chains as depicted in Figure 1.
II ) High DB content, mul ti (>2) OH -functionalit y : These pol y ols can for ex ample be
employe d similarl y to conventional pol y ols in thermoset pol yur ethane elastomers [9]
and provide additional cross-linking, l eading t o potentiall y dens er ma terials with
enhanced properties. Additional applications are currently in research and
development [14].

Fig ure 1: Value chain o f s ynthetic elastomers, t he dashed line box is filled with the novel
CO2-containing pol yurethane rubber s y nthesis

RD&D of new te chnologies is onl y possible with prospects of monetary gain. Decision -
makers rel y heavil y on sound assessments as tools for answe ring their question about what
technology to invest sc arce resources in. R ecentl y , pitfalls and con ceptual challenges in
assessing ch emical innovations in gene ral and CC U technologies in particular were ide ntified
and tackled with the introduction of a respective techno-economic ass essment structure and
framew ork [ 15] and techno-economic assessment (TEA) & li fe c y cle assessment ( LCA)
guidelines for CO 2 uti lization [16]. This paper is a worked ex ample of the proposed
methodology. Its aim is to assess the g eneral e conomic viabilit y of novel CO 2 -containing
rubbers as part of resear ch direction I) shown above . The scope of this paper ’s assessment is
limited to TEA; an L CA of the same group of pol ymer s was published r ecently [17] . Routes
associated with research direction II) are not in the sco pe of this paper. A first assessment
aligning TEA and LCA for products of research direction II) was reported earlier b y the s ame
authors [14].
For the stru cture of the body of this paper, a classical separation into method s, results and
discussion, which is t y pically found in scientific literature, is not reasonable. The aim of this
paper rather is to mirror an actual (RD&D and) TEA approach. I n particular, the interpla y of
methodology selection and result calculations remains an often discussed issue in litera ture
[16,18] and project work. For this paper, three tiers of methodology decisions can be seen:
 Tier 1: Approach on the overall scie ntific stud y , general work principles

 Tier 2: S el ection of depth of data analysis and grade of methodology
 Tier 3: Specific calcula ti on methods
P rocess desi gn and ass essment are two different parts of technolo gy innovation (data
exchange and feedback between p ractitioners of both fields is crucial!) . Thus, this work is
separa t ed int o process design and TEA (tie r 1). I nitially , the t echnolog y of interest is
described (chapter 2). A preliminar y TEA is carried out in the followin g ( chapter 3). The
preliminary TEA leads to a decision of further process desi gn which is subsequently laid out
using established chemical engineering methodolog y (chapter 4). This then serves as the data
basis for a refined TEA (chapter 5). Both preliminar y and refined TEA follow the
afore m entioned methodological frameworks and guidance (chapter 3).
The process description and design is conducted on two levels of detail ( process design, tier
2): First, extended block flow diagrams (BFD); second, preliminary process flow dia grams
(PFD). This sepa ration is expected to deliver insights into the depth of anal y sis and
eng in eering effort needed for sound assessment i n early to m id levels of d ata av ailability (see
also [ 19]). The description and desig n sections are introduced with discussions about the data
foundations and lead to the respective flow diagrams. A variet y of s pecific, established
approac hes and methods for process and equipment desig n (process design, tier 3) are applied.
TEA is a proce ss that reflects a separation similar to ‘ methods, result and discussion ’ in its
phases : In phas e I , th e goal & s cope phase of a TEA, the general methodolo g y is sel ected, i.e.
the depth of the anal y sis and guidance on the methods that can be sel ected ( TEA, tier 2) .
Basic methodolog y suc h as composition of cost items which can be found in the
afore m entioned frameworks is recapitulate d alongside th e stud y onl y where d eemed helpful
or adapted. The numberi ng in the TEAs is: [paper chapter].[TEA it em according to [15] and
Fig ure 2] .[further division] The selection of specific methods (especially for smaller parts
such as sin gle equipment cost calculation ) can be carried out in th e subsequent phases which
can contain their own s eparation into m ethod selection and cal culation tasks [15] . For this
reason, th e specific m ethods applied and assumpti ons made are briefly introduced at the point
of their effect (T EA, ti er 3). Results are calcu lated in phases II and III and ther einafter
discussed (‘interpreted’) in phase IV.

2 Pr ocess D escription
2.1 TEA -process design interface
Every assumption and decision in process desi gn has economic impacts. For this reason,
overlaps between process de sign and TEA are unavoidabl e. The currentl y availabl e data
(‘L iterature data’ in Figure 2 ) define both the process d esign’s level of detail and th e
technology maturit y and consequ ently th e depth of adequate TEA meth odolog y . Th e TE A
scope h as to match the technolog y that is currentl y in RD&D whose planning is refl ected in
the design scope. At the same time, the design scope will follow a set of parameters that are
defined in the TEA scope. Two prominent ex amples for this relation are s ystem boundaries
and plant capa cit y. For market rea sons, this pap er’s design and TEA sco pe is limited to the
production of pol y ols and production of pol y urethanes ( as touched upo n in chapter 1 and
explicated 3.2.2) whic h are considered separate steps. Furthermore, initial market
considerations for an ad equate plant capacit y yield values that define also the design scope
(see 2.2 ). Ever y aspect of a technology is associated with cost; this means that design results
are at the same time mo del inputs to cost estimation methods. Concurrently, while selecting
equipment, the engineer i s responsible to select equipment that performs the desired task in an
economical way. For example, the design y ields equipm ent specifica tions t hat are model input
to capital ex penditure (CapEx) estimation. I n the reflection upon the desi gn and im pacts, TEA
has to consider onl y th ose deviations in sensitivity and uncert aint y anal y ses which are
technolog i call y relevant. Simultaneously, TEA has to give economicall y probable deviations
that have to be examined in terms of design consequences. The engineering and TEA scopes
will be redefined accordi ng to th e r espective risk and uncertaint y r eflections. Fi gure 2 depicts
the interplay between process design a nd TEA tas ks as performed in this stud y.

Fig ure 2: G eneral structure and int erpla y of process design and techno -e conomic assessment
tasks as performed in this study
2.2 P lant capacity
The c apacity is a decisive pa rameter for ever y process desi gn and can re s ult from initial TEA
thoughts. For this paper, three types of capacity are distinguished:
 Maximum operating capacit y : Optimum capacit y in cluding all material throughput
and considering no downtime
 Effec tive operatin g capacity : Possible capacit y including all material throughput and
considering downtime (ty pic al assumption: 760 h/a, cf. [ 20])
 Product ca pacit y : Annual amount of product produced; i.e. the product yield re sulting
from operation with effective capacit y; capacity t hat the plant is mainl y referenced and
presented w ith ( ‘nominal’ capacity ) and b asis for the design
Here, the capacit y cann ot be based on typica l pol y ol plant siz es as their markets are
differe nt, i.e. th e y most ly target direct large-s cale applications such as foams as opposed
to mi d- sc ale use for further pro cessing to rubber s [9,21] . I t ma y be poss ible to buil d a
multipurpose pol y ol plan t that can serve different compositions (especiall y functionalities
and molar masses) and thus different purposes. Howe ver, a conservative approach is
followed here: the plant has to be self-sufficient f or the rubber market. Fo r this scenario, a

combination of both market expectations and typical benchmark plants ' ca pacities serves
as orientation for the pla nt capacity. Initial market siz es for (near) drop-in solution s most
likely do not ex ceed 30 % of the immediate benchmark ’ s capacit y in the targeted r egion.
The most prominent benchmark is expected to be nitrile butadiene rubber (NBR) in the
US at ~93.8 kt/a [22] , leading to an estimated ini tial market of ~28.2 kt/a (details are part
of the marke t analy sis, section 3.4). T y pical N BR plants range from 10 to 35 kt/a [ 23].
Thus, a maximum opera ting ca pa city of 30.0 kt/a is selected here which fo r the base case
corre sponds with an effective operating capacity of about 27.4 kt/a and leads to a product
capacity of just above 23 .6 kt/a.
2.3 Approach and literature
For a first process descript ion, relevant literature is collected and the description ’s scope is
defined. Subsequentl y , b lock flow dia grams (BFD) c an be dr awn , and a fter setting up and
scaling of the material balance, extended with mass flows (see Fi gure 3 ). The extended BFDs
contain the proce ss idea in the form of a sequence of cha racteristic proce ss steps and their
rough operating conditions. Assumptions include rules of thum b and ex pert guesses believed
to be in at least correc t order of magnitude ran ge.

Fig ure 3: Methodological sequence for the process description leading to ex tended block flow
diagrams

To our best knowledge , the novel rubbe rs are currentl y solel y d eveloped by C ovestro
Deutschland AG . Information about the technology is predominantl y taken fr om patents
related to their activities. For the CO 2 -containing polyols, relevant patents are available [24 –
26]. It is assumed that thi s te chnolog y c an easil y be adapted to includin g m aleic anh y dride (or
allyl gly cid y l ether) as a third co-monomer. Fu rther information on this CO 2 -polyol formation

is revealed in research papers [4,5,13,27 – 30] . R eg arding th e rubbe r formation, very limited
information is published. This part of the paper is based on conference contributions [ 11,12].
2.4 Block flow diagram s
Base d on the literature d escribed above, the pro cesses for the fo rmation of pol y ols containin g
CO 2 and a DB moi ety (abbreviated as ‘PEC’ below) and the resulting urethan e rubber
(abbre v i ated as ‘PECU’ below) are set up.
The production method of the PEC is a double metal c y anide (DMC) cataly zed
copolymerization of propylene oxide (PO), C O 2 and maleic anhydride (MA; alternatively,
allyl gl y cid y l ether (AGE) can be emplo y ed ) sta rted on monomeric prop y len e glycol (mPG) .
Cyclic prop y lene carbonate ( cPC) is formed as a side product from CO 2 and PO via direct
reac tion or backbitin g from the polyol cha in [ 31].
The PEC process is div ided into four significant process steps ( note: literature also uses
‘functional unit’ whic h is avoided here due to its diffe rent meaning in LCA):
1 Pre-trea tment and mixing: Th is step includes th e heating of all inputs and partial
mixing of all inputs. In addition, this step comprises the pr essure increase to th e
desired reac tion pressure [24,26] .
2 Reaction: The reaction is carried out in two steps, the main reac tion in a backmix
reac to r to high but not full conversion and the post -reac tion in a displacement reactor
to yield full propylene oxide conversion [24].
3 cPC separation sta ge 1: The reaction is carried out with an excess of CO 2 which is
assumed to be quantitatively r ecycled to the first process step. The side product cPC is
separa t ed from the poly ol at elevated temperature and reduced pressure. Two
separa tion steps with different equipment and partl y different separation principles are
reported [25].
4 cPC separation stage 2: see above.
The mass balance for th e PEC production is derived from the desired PEC composition. Bi -
OH -functionality is assumed in order to form linear P ECU. For the base case, the following
polyol composition is assumed: Molecular wei ght 5000 g /mol [11] , double bond content
4 wt % [11], CO 2 content 20 wt % [4]. For an appropriate catal yst amou nt, a wide range is
reported, in particular between 15 and 1522 ppm in the poly ol reaction mass [26]. An amount
of 304 ppm is selected for this study, corresponding with 2wt% o f the starter-catal y st mi xture.
The catal y st remains in the PEC. The s electivity of the pol yol formation i s assumed as 93 wt %

[5,30] . The desired cPC content in the final PEC is assumed as 100 ppm [25]. I t is assumed
that 2% of the annual PEC production are lost due to startup and shu t-down, deviations
leading to off-spec product and l aborator y or retain samples. Th e CO 2 excess for the reaction
is assumed to be 40% [30].
For the reaction pressure, a preferred r ange of 20 to 120 b ar is reported - a value of 76 ba r is
chosen as a consistent data set is provided with it [2 4] . The process is thus assumed to be
conducted with CO 2 that is supercritica l before mi xing with the other reactants and liquid
thereafter. A lowe r press ure mi ght lead to reduced costs if mass tr ansfer influences can easil y
be mitigated. The operating conditions of the main equipment of each functional unit as
specified in the BFD are deduced from the aforementioned literatu re . Figure 4 shows
extended block flow diagrams for the PEC production.

Fig ure 4 : B lock flow diagram for the double-bond-containing polye the r carbonate pol y ol
(PEC) process, significant process steps 1 to 4, ex tended with characteristic process
conditions (tempera ture (T), pr essure (p)) in the main equipment a nd mass flows, PO –
propy lene oxide, mPG – monomeric propy lene gly col, DMC cat. – double metal cy anide
catalyst, MA – maleic anh y dride, AGE – all y l glycidyl ether, cP C – c y clic prop ylene
carbona t e

The production of the P ECU is a cataly zed chain-elongation of the PEC with diisocy anates .
For thi s paper, meth y len e diphen y l diisoc y anate (MD I) is assumed to be the most probable
diisocya nate and constitutes the base c ase. Other opti ons are toluene diisoc y anate (TDI) and
hexamethylene dii soc y anate (HDI) (discussion see 5.2.2 ). The sep aration of b y-products o r

side product s is neither reported nor expected. The PECU process is divided into two
significa nt process steps:
5 Reactive extrusion: For t he PECU formation p rocess, public stat ements are "rea ctive
extrusion"[11] and "standard TPU plant" [ 12]; however, no specific in formation is
published. Most thermoplastic polyurethane (TPU) produ ction processes are carried
out in solvent-free s ystems and apply either one -shot operation or reactive extrusion
[32] . A single but potentially rather complex reactive extrusion step is assumed for the
PECU formation. Elevated temperature is necessar y [ 9], a range of 100 t o 180°C is
reported for most pol yurethane s [ 21] ; as no f urthe r information is a vailable, an
average value was cho se n.
6 Solid handling/packag ing: Following the reactiv e extrusion, a generic soli d handling
step is emplo y ed in order to pr epare f reight shape. TPUs are commonl y supplied as
resin (gra nules), and rub bers are oft en shipped in other shape s (NBR: b ales; EPDM:
bales, pellets; CR: chips). For PECU, a viscosit y that is b y trend lower than
conventional comp arable rubbers is r eported [13] . Shippi ng as bales is thus assumed
here; however, as there is no specification at hand, this preliminary ev aluation treats
this step as ge neric ‘ solid handling / packaging ’ at ambient conditions. As it may
involve curing , it is place d inside battery limits (I S BL).
The mass balance for the PECU production is d erived f rom the desired PECU composition.
Stoichiometric input is assumed in order to form linear P ECU. The cataly st is unknown; the
mass of the catal y st is neglected. I t is assumed that 2% of the annual PEC U production is lost
due to startup and shut-down, deviations leading to off-spec produ ct as well as laborator y or
retain samples. F i gure 5 shows extended block flow diagrams for th e PECU production.

Fig ure 5: Block flow d iagram for the pol y ether carbonate pol y urethane rubber (P ECU)
process, si gnificant process steps 5 &6, extended with characteristic proce ss conditions
(tempera ture (T), pressure (p)) in the main equipment and mass flows, MDI – methylene
diphenyl diisocya nate, T DI – toluene diisoc y anate, HDI – hexameth y lene diisocyana te

For both P EC and PECU, the energ y and utilities (E&U) demand calculations on BFD level
are based on the basic thermodynamics of the ke y unit operations, i.e. without equipment
design, not considerin g heat integration or efficiencies. For the PECU en ergy calculations, it
is assumed that th e reactive ex truder is the dominating energy consumer. An e le ctrical ener gy
demand of 0.15 kWh/kg(PECU) is assumed ( see also [ 33]) for the motor; heating is assumed
to be powere d with electricit y, cooling is not considered.
3 Preliminary techno-economic asse ss ment
3.1 TRL rating (prelim inary)
The general depth of analysis follows the degree of knowledge about the process, which is
reflected in it s maturit y . For a maturit y ev aluation, rating with technolog y readiness l evels
(TRL) [ 19] is recommended [ 16] . The data availabilit y for thi s paper is believed to be notabl y
lower than the level of information present to the developing inst itution. While patents reve al
ideas for the P EC proc ess, the P ECU process remains unpublished. As a consequence,
publically ‘observed TRLs’ ( see also [19] ) remain at conceptual stages, w hile the deve lopin g
institution’s ‘rea l TR L s’ (see also [ 19] ) are believe d to be substantially hi gher. Th e
preliminary TEA is based on the process d escriptions given in chapter 2 w hose observed l evel
of data availability c orresponds with TR L 4.

3.2 G oal, scope and scenario defin ition (preliminary)
3.2.1 Goal definition (prelim inary)
The goal of this study i s to assess the genera l economic viabilit y o f a novel pol y urethane
rubber formed from a C O 2 -containing pol y ol bas ed on prop ylene ox ide and including double
bonds, which is reacted with diisocy anates. The polyol as well as pol y urethane s y nthesis are
examined. A produc t capacit y of 23.6 kt/a for a pl ant located at the US g ulf coast (USGC) in
the base y ear 2018 is projected. A full-scope assessment (see also [15] ) is targ eted, allowing
for a direct comparison of cost of goods sold (C OGS) to benchmarks’ market prices.
Further mo re, recommendations for an approach on a refined TEA shall be given. An R&D
perspec tive is taken, aiming at an audience of practitioners from both academia and industry.
3.2.2 Scope and scenario definition (preliminary)
The scope of the preliminary TEA is limited to the base case. Th e base case scenario is
constituted by a plant on the USGC which will sell (mainly) to th e US ma rket. This decision
offers a reasonable mark et siz e nearby, established infrastructure for chem ical p roduction and
easy access to fe edstocks. The currency of the anal ysis is USD. The base year is 2018 as it is
the latest year sufficient price data ar e avail able; price forecasts are avoided. The chosen
capacity is explained in 2.2 and 3.4. The s ystem boundaries for this case stud y are set b y the
chemical production (in a narrower sense) and are highlighted in Figure 1. The conventional
inputs to the PEC produ ction can be included in the assessment via their market prices; CO 2
will be discussed separately in section 3.3.2. The PECU is seen as a (near) drop-in sol ution for
selected synthetic specialty rubbers [12,13] (see 3.4).
3.3 Cost e stimation (preliminary)
3.3.1 General rem arks (preliminary)
All cost of goods sold (COGS) are included in t his TEA . C OGS are the sum of operational
expenditure (OpEx ), capital expenditure (CapEx) a nd general expenses (Ge nEx). OpEx is
further divi ded into material, energ y & uti lit y ( E&U) and indire ct cost as their estimation
methodology diff ers due to different data bases. Cost estimation is itself a process of th ree (or
four) phas es: selection of method, cost inventory and cost impact calculation (and cost
interpretation). All phases are combined in the respective sections for b etter overview. An
interpretation of c ost in the sense of an assessment is only possible as a c ost-comparison
which is ex cluded here . In contrast, a comparison to the benchmark – as given b y the market
analy sis – reveals the profitabilit y which is calculated in 3.5 and int erpre ted in 3.6. I n general,

the combination of OpEx/GenEx and CapEx is part of t he p rofitability calculation as these
costs refer to different time spans and thus c annot be directl y combined to a single impact.
3.3.2 Mater ial cost
For the material cost, the differe nt items in the material balance for differen t inputs/outputs
are ‘tagged’ with price s retrieved f rom trade data bases and supplier information ; see
compiled in the supporting information Table S1 . The CO 2 price is subject to intense
discussion [16]: For this stud y , the CO 2 price is composed of four elements: capture,
transport, profit margin, compression. The CO 2 source for this process is a point source [5]. A
natural gas fired power plant is selected as it allows for flexible site selection, coming with the
disadvantage of additional investment for the capture unit which leads to highe r overa ll
capture cost. The c apture cost, including purifi cation to ≥ 99,95 vol%, is calculated from
Naims [ 34] and adjusted for inflation to 84.65 $/t . With transport and profit mar gin neglected
(see also [35] ) and if target p ressure equ als the pressure at which th e CO 2 is used (which in
this case is a reasonable assumption as the use p ressure is about 76 bar an d t y pical transport
pressures would be abou t 100 bar [ 30,36]), the CO 2 cost is not affected b y the location of the
compression. As no reliable price data including compression a re at hand, the compression is
included in the PEC plant. The CO 2 input cost thus equals the calculated capture cost in this
case. Total material cost is 34.33 M$/a (1.50 $/kg). The material cost is dominated b y the PO
cost (~66.8%; 68wt% in the PECU), fo llowed b y M A cost (11.3%) and MDI cost (10.8%).
The inputs’ contributions to the material c ost are s hown in Figure 6.

Fig ure 6 : I nput cost contributions to material cost in the polyether carbonate pol y urethane
rubber (PECU), PO – propylene oxide, mPG – monomeric prop y lene glycol, D MC cat. –
double metal cy anide ca talyst, MA – maleic anhy dride, AGE – ally l gl ycidy l ether, cPC –
cy clic prop ylene carbona te, Ureth. cat. – urethaniz ation cataly st, MD I – methylene diphen y l
diisocya nate
3.3.3 Energy & utility cost (preliminary)
For a rou gh estim ate of t he E&U cost, the process is divi ded into g eneral unit operations that
are c alculated in single steps ( e.g., no intercooling for hi gh ratio compressions) in order to
repre s ent a conservative thermody namic situation:
 Heating up of reac tants (low pressure steam)
 Compression of reac tants (electricity), cooling of reactants if necessary (cooling
water)
 Cooling of total reaction hea t (coolin g wa ter)
 Heating up to sepa ration heat (medium pressure st eam)
 Vacuum as c omp ression to pressure inverse (electricit y)
 Cooling of PEC, cPC (cooling wa ter)
 Heating of reac tion mix ture (electricity)
 Extrusion (electricity)
The condition data in the block flow diagrams we re taken as start and end points. S implify ing
assumptions for material properties were made and efficienc ies were ne glected. Energ y &
utilit y p rices are listed i n the supportin g inform ation in Ta ble S 2. Th e steam prices we re
calculated for a s y stem of 40, 20 and 3 bar with natura l ga s for heating and electricit y
ge nerated from expansio n. Total E&U cost is 0.45 M$/a (0.019 $/kg).

3.3.4 Indir ect operational exp enditure
Indirect OpEx are commonl y estimated with f actored estimation in dev elopment stages. A
table with the respective factors along with the c ost items they are applie d to is given in the
supporting information ( Table S3 ). Standard liter ature values were chosen, tending towa rds
higher values if ranges are given due to the fac t that this new technology ma y come with
slightly increased op erating effort . For mainten ance and repairs, a r elatively hi gh fa ctor of 8%
on FC I (see compilation s in [ 15] and [37] for comparison) was chosen as a) this novel process
may n eed ad aptions and optimiz ation, b) processes with increased operating pressure show
higher maintenance and repair cost and c) ex truder screws and conve yor belts are subject to
abrasion, frequent replac ements ma y occur. Operating intellectual property is assumed to be
proprietary , and packaging/loading/shipping is included in marketing & sales of GenEx for
this stud y . The total indirect OpEx is 6.37 M$/a (0.27 $/kg).
3.3.5 Capital expenditure (preliminary)
PEC and PECU steps are treated as separate fixed capital investments (FCI). For the
preliminary TEA, FCI was calculated with a process step countin g method presented b y
Klumpar et al. [ 38], using information g iven in the process d escription ( chapter 2). This
method ha s shown to deliver satisf y ing estimates for thermochemical plants that do not
include numbering-up [39] and is representative for a group of process ste p counting methods .
The process steps in the PEC and PECU processes deviate from the list of descriptions for
standard characteristic steps as the y are not domi nated b y a sin gle unit op eration but combine
a multitude of equall y important ph y sical e ffects. Therefore, the rec om mended generic
complexit y exponent was chosen. The method retu rns direct ISB L c ost. Indirect I SBL cost are
believed to account for 2 8.84% (calculated from [ 40] ) of the total ISBL co st. A factor of 30%
on I S BL cost was chosen for OSBL cost. Table 1 list s the FCI items’ values .

Table 1: Fixed capital investment (FC I) estimates following Klumpar et al. [38] for direct
inside battery limit ( I SBL) cost, factored approach for other cost items, base y ear 2018, US
gulf coast, OSB L – outside batter y limits, PEC – double-bond-containing pol ye ther carbonate
polyol, PECU – polye th er carbonate pol y urethane rubber
FCI item

Cost for PEC steps [M $]
- based on process steps

Cost for PECU steps [ M$]
- based on process steps

Direct ISBL cost

16.23

5.10

Indirect I S BL cost

6.58

2.07

Total I S BL cost

22.80

7.17

OSBL cost

6.84

2.15

FCI

29.64

9.32

All depreciable costs are subsumed under FCI. W orking capital is estimated as 15.38% of
total OpEx (see also [41] ), representin g the capital that is bound in a produ ction c yc le of eight
weeks in 8000 hours annual uptime. A value of 6.48 M$ was calculated. The tot al CapEx is
45.44 M$ .
3.3.6 General expenses
There are a variet y of approaches how GenEx are allocated to different plant operations
within an economic entity . GenEx are often neglected, especially in earlier studies; however,
for full scope assessment, a complete picture of all COGS is advise d for meanin gful
profitability statements. For a first estimate, a s plit into administ ration, general research &
development and distrib ution & marketing & sales (M&S) is suit able. R eported factors for
ge neral R&D and M&S on total product cost [40,42,43] are adjusted to the expected OpE x
share and increased b y 10% to ac count for the expectable challenge of launching a first - of -a-
kind (FOAK) plant’s operation. Total GenEx are 8.78 M$/a (0.37 $/kg).
3.4 Mar ket analysis (preliminary)
In development sta ges, t he most im portant infor mation that a market an aly sis has to return are
the sales volume (here: for an initial market) and a corresponding sales price. As a ge neral
strategy, the PECU is considered a (near) drop- in solution, i.e. it s characteristics and
performance are sufficientl y simil ar to benc hmark products. With costs below the
benchmark' s mark et pric e, a fa vorable placement on the market could b e achieved. G radu al

exploitation of a bigger market c an occur b y a) r eplacing other elastomer s using lower cost as
major competitive adva nt age and/or b) filling into general market growth.
The technical anal y sis of benchmarks su ggests four possi ble competitive products [13] : Three
‘ special ty rubber s’ [ 23], nitrile butadiene rubber (NBR), eth y lene prop ylene diene meth y lene
rubber (here: EPDM), chloroprene rubber (CR) as well as one ‘ hi gh-perfor mance rubber ’
[23] , hy drogenated nitrile butadiene rubber ( HNBR ).
NBR is the preferred benchmark [11]. Hence , the potential sales volume and sales price of
NBR are set as values f or the base case. Additio nal benchmarks will be described in market
analy sis of the refined T EA (5.4 ).
Nitrile butadiene rubber is a spe cialt y rubb er with "good oil resistance" [23] . Its biggest
markets a re: Automotive, oil&gas, m echanical engineering [22] . Products include fluid lines,
seals/O-rings/gaskets, dampers, membranes, timing belts, cables [22,23,44] . In general, higher
acrylonitrile content incr eases the elastomer performance [44] . The addressed market is the
US and an entr y m arket share of 30% is assumed . The demand in 2018 is considered for the
following calculations: The p ossible sales volume is 28.2 kt/a [22] (~20% above produ ct
capacity ) at a price of 2812.80 $ /t [ 45]. The chosen NBR market shows a moderate growth (2-
3% p.a. until 2025) [22].
3.5 P rofitability analysis (preliminary)
The most important criterion in TEA is profitability . Other criteria can be found in literature
but remain inconclusive (as explained in [14,15]). The specific profit (in static calcula tion) is
chosen as an indi cator for the p reliminar y TEA. As the possible sales volum e exceeds the
plant’s capacity , the spe cific profit equals the sta tic profit divided by the market potential. I t
can thus b e added to the li st of TRL 4 indic ators (see [ 15], GenEx are add ed to th e
calculation, onl y deprec iable C apEx items are c onsidered) and co rresponds with the TRL
rating and d efined goal. The plant lifetime is 10 y ears and h ere equals th e allocation ti me in
static calculation. This conservative timeframe is decided as the FOAK p lant is expected to
lose value qui ckly. The s ales pric e is set as the be nchmark ’s market price. This is possible as
synthetic rubber pl ants currentl y operate with negligible mar gins (see also [46] ). A specific
profit of 0.49 $/kg was calculated. Its result from a possible revenue and c lustered cost items
is il lustrated with cost in crements in a waterfall depiction in Fi gure 7. It becomes obvious that
the material costs of 1.50 $/kg consume most of the possible reve nue.

Fig ure 7 : Waterfall diag ram of re venue and clustere d cost items, cost increments, static
calculation, 10 year allocation time , product capacit y equals sales volume, sales pric e equals
benchmark price, GenE x – g eneral expenses, FC I – fixed capital investment , OpEx –
operational expenditure, E&U – energy and utilities
3.6 Inter pretation (preliminary)
3.6.1 Interpretation of indicators (preliminary)
Every TE A interpretatio n includes the followin g p arts: interp retation of indicators ( 3.6.1),
sensitivit y anal y sis and u ncertainty anal ysis (SA and UA, 3.6.2). The TEA & L CA guidelines
for CO 2 utilization [ 16] inc lude multi -criteria dec i sion analysis (MCDA) in the interpretation
phase. MC DA can be an additional step that prepares decision making b y c ombining different
criteria. This is not appli cable here as onl y profitabilit y is anal y z ed. TEA itself is a tool that
prepares decisions and it is acknowledge d that in addition to the general interpretation,
specific an al y ses can be demanded b y the respective decision -mak er. Preparing a specific
decision-making about future deve lopment is sho wcased in 3.6.3.
A positive indication for future RD &D is given i f the specific profit is positive or exceeds a
target value. F or thi s aca demic stud y , no tar get value is given. As the specific profit is
positive, a positive indication for future RD&D is given.

3.6.2 Sensitivity and uncertainty analyses (preliminary)
In a first anal ysis, th e i nfluences of all major c ost items and the sales price on the above
presented indicator are ex amined while capacity and plant life -time are viewed as invariable.
A tornado plot shows the target outputs ’ outcomes with +/ -20% model input deviation for the
base ca se ( Figure 8).

Fig ure 8: S ensitivit y anal ysis (S A) of clustere d cost items and sales price for specific pro fit
(static calculation), tornado depiction, +/ -20%, GenEx – general ex penses, FC I – fixed capital
investment, OpEx – operational expenditure, E &U – energy and utilities, NBR – nitrile
butadiene rubber

In the present ed base c ase sit uation, the specific profit is very sensitive to the sales price
(sensitivity coefficient [ 47] : 5.73), followed by high sens itivit y to material costs (-3.64 ) which
are the de cisive OpEx item (total OpEx: -4.35 ). As the mass balance is given from process
design, spec ial attention to the uncertainties of the r etrieved prices should be paid. The
sensitivit y coefficients of indirect OpEx , GenEx and FC I range betwe en - 0. 76 and -0.34; their
absolute cost increments are similar to the speci fic profit. For this reaso n, these cost items
may need c onsideration i n future calculations if they come with high uncertainties .
At this point , no dist ributions of the cost clusters are at hand. Th ese will have to b e calculated
from their important mo del input distributions. An in-depth un certaint y anal y sis is in cluded in
the re fined TE A. The uncertaint y o f FCI and its implications are di scussed withi n the
following decision preparation.

3.6.3 Preparing the dec ision for su bsequent R&D
The observed TR L was rated to be 4. In engineering te rms, the next level, TRL 5, is
summarily characterized as a level of data availability that is associated with a
(first/preliminary) PFD a nd its accompany ing tables. The question is raised i f for the current
technology assessment a n engineering effort leading to a PFD will help the TEA. In orde r to
answer this question, it has to be ex amined whe ther and how TEA methods change with a
PFD. The latter question is answered separately fo r the earlier pr esented co st clusters in Table
2.

Table 2 : Methodological changes regarding techno-economic assessment ( TEA ) with
technology readiness le vel (TR L) in crease and impli cations for and of uncertaint y and
sensitivit y anal y ses (UA, SA), GenEx – general e xpenses, CapEx – capital expenditure, OpEx
– operational expenditur e, E&U – ener gy and uti lities, FC I – fixed capita l investment, PFD –
process flow diagram, PEC, I SBL – inside battery limits, OSBL – outside batter y limits, PEC
– double-bond-containing polye ther carbonate polyol
Cost item

Me tho dol ogy change with PFD?

Do UA/SA within cost cl uster?

Implication of UA/SA?

Materia l cost

 Prices are not affected
 Materia l bal a nce is set up bas ed on
stoichiometr y of reaction a nd data o f
stream co mposition
 Process des ign will be ta ilored to material
balance
 For first process design, o nly negligib le
adaptions to m a terial ba lance expected
which will not be co nsidered
 no

 no

E&U cost

 Prices are not a ffected
 E&U balance is based on material balance
and thermodyna mic ke y steps
 For first process design, cha nges are
largely limited to the equip ments’
efficiencies and refined material
properties
 yes

 S A s hows a negligib le
dependency of t he specific pro fi t
from E&U costs
 Methodologica l changes are
limited due to restr ictions o f
thermodyna mics; uncertaint y is
judged to be less than -/+50%
 no

Indirect
OpEx

 Factored on Op Ex and FCI
 no

 no

CapEx

 Working cap ital is not a ff ected as it is
factored on Op Ex
 Characteristic process step c ounting
method based on block flow diagra m c an
be changed to eq uip m ent -cost-bas ed
methodolo gy [15]
 Change of methodo logy for direct IS BL
cost – which is the biggest o f all Cap Ex
parts (and m ajor ity o f P EC FCI)
 yes

 Characteristic process step
counting method can ha ve very
large errors
 Equip ment-factored m et hods
have by trend lower errors [15]
 yes

 Uncertainty o f FCI is very high (-36%, + 131% ,
middle 8 0% )
 Specific profit is not very sensitive to OSB L a nd
indirect IS BL factors – these w ill not be cha nged
with altered methodology
 Profit is not ve ry sensitive to p rocess temperature
and pressure e xtremes (as cons idered in [38 ])
 Profit is very se nsitive to co mplexity e xpon ent
(as considered in [38])
 In or der to reduce un certa inty, p rocess design
and change o f methodolo gy is indicate d

GenEx

 Factored on Op Ex and FCI
 no

 no

The uncertainties presented below reflect ‘qu antit y unc ertainty’ [ 48]. For price data
uncertainty, the variabilit y o f events is considered; the contributions of single events’
uncertainties are ne glected. For all other model inputs, the uncertaint y reflects the credibilit y
of data sources and overall data qualit y . The reported uncertainties depict frequencies of p ast
events and plausibl e deviations from chosen v alues respectively and are therefore inherentl y

not probabilit y distributi ons. However, the y are at the same ti me judg ed to be suitable
assumptions for prob abilit y distributions which are valid for th e proj ected time span and c an
serve the TEA ’s orientation toward future prospects. Uncertainty propagation in the TEA
model is concluded from the quantity unc ertaint y . Monte Carlo simulation wa s used for
uncertainty propagation (single analy sis, 10000 iterations).
As FCI estimation methodolog y changes as a consequence of process design and high
uncertainty can considerabl y affect the profitabil it y . Therefore, th e uncertaint y of FCI was
calculated (shown in Fi gure 9), applying normal distributions for the complexit y ex ponents
and triangular distributions for all process condition s as well as OSBL and indi rect FCI
factors. The FC I lies between 24.8 and 89.9 M$ in the interdecile range. Wit h this FCI
calculation, contingency for a P 80 estimate needs to be about 32.3 M$, adding about 83% to
the base FC I estimate. The uncertaint y corresponds with AACE interna tional class 5 [49] or
can be associated with TRL 3 [15] (-36% and +131% for middle 80 %). The c alculated
uncertainty consid erably exceeds the error expectations presented in the proposition of the
method ( cf. [38]).

Fig ure 9 : Fix ed capital in vestment (FCI) distribution as result of uncertainty anal y sis ( UA ) for
double-bond-containing pol y ether carbonate poly ol (PEC) and pol y ether carbonate
polyure thane rubb er (PECU), estimate based on ex tended block flow dia grams, step counting
method, Monte Carlo (10000 iterations)

Both PEC and PECU complexit y exponents rev eal strong sensitivities, co efficients -2.88 and -
0.91 respectivel y, and are as y mmetric, i. e. showing dispropo rtionately hi gh percentage
changes in the specific p rofit when altered. Proce ss condition extremes as well as factors for
additional FCI el ements show sensitivit y coefficients between -0.32 and - 0.01 and thus do not
require special attention even with hi gher uncertaint y . A torn ado plot shows the specific
profit’s outcome with +/ -20% deviation in the model inputs to the selected FC I estimation
method for the base cas e (Figure 10 ).

Fig ure 10 : Sensitivit y an alysis ( SA ) of cost estimation method model inputs for fix ed capital
investment, tornado depiction, +/-20%, FCI – fix ed capital investment, OSBL – outsi de
battery limi ts, P EC – double-bond-c ontainin g poly eth er carbonate pol y ol, PECU – pol y e ther
carbona t e polyurethane rubber

As the PEC’s process F CI is about three times t he P ECU’s, the PEC complex ity exponent is
the single most important parameter in the cu rrent C apEx calculation and strongl y affects the
profitability indicators. The PEC complexity e xponent itself is ver y unreliable. I t can be
avoided b y altered methodolog y at a higher TRL. In conclusion, the in dication is given to
improve the data basis fo r the next TEA iteration b y more detailed pro cess design at the level
of a preliminary P FD and change the estimation method ac cordingl y . The decision about
whether to follow thi s indication or not is not part of the TEA itself b ut ra ther a project
decision as it directly a ff ects RD&D.
4 Pr ocess design
4.1 De sign procedure
Base d on the pr eliminary TEA’s indication, the decision is made to inves t in a more detailed
process design at the level of a first PFD for the most probable proce ss ( i.e. the base case).
The design is limited to the P EC process. For PECU, it was found that the literature situation
is not satisfactory ( i. e. espec iall y regarding re action kinetics, catal y st t y pe and amount,
material prop erties) and no further design can be conducted. How this af fects the data basis
for the TEA is discussed in sections 5.1 and 5.2.2 ).

The process design incl udes knowled ge given with the process description (chapter 2 ) and
follows a t y pical desi gn process: After definition of the desig n scope, a process flow diagram
is drawn and subs equently equipment sizing and E&U calculations are car ri ed out ( Figure
11 ).

Fig ure 11 : Methodolo gical sequence fo r the pro cess design leadin g to a process flow diagram,
starting from a process description including block flow diagra ms

As this paper takes an outside perspective, re-engineering from publically available data is
conducted, including m ajor assumptions; conformit y with the actual process at the d eveloping
institution is not claimed. The resulting PFD includes a first equipment desig n and E&U
balance , thus detailin g th e process conditions given in the extended BFDs. The d esign has to
stop at a preliminary level since data a re not sufficiently av ailable for a d etailed design. The
following genera l rules f or the preliminary de sign were decided:
 No heat integra tion (see Table 2 and Figure 8: E&U is not important for the TEA)
 Delivery pumps excluded, i.e. pressure loss he at exchangers, pipin g, etc. neglected;
plant layout neg lected, i. e. delivery head neglected
 Reactor residence time from patents, i.e. no distinct kinetic model
 Steady state calcul ations, i.e. no dynamic behavior
 Simplif y ing assu mptions for m aterial properties, e.g., heat capacities assumed as
additive, heat capacit y and d ensity of liqui ds assumed as indepe ndent from
temperature when only minor change s are ex pected, or similar
4.2 P rocess flow d iagram
The equipment sizing and E&U calculations were based on spreadsheets (partial calculations
in ASPEN HYSYS and Berkele y Madonna) and follow standard approaches on preliminary
design des cribed in common textbooks (such as [ 40,41,43,50,51] ). I nformation from patents

EP3164441B1 [24] (steps 1&2) and EP3164443 B1 [2 5] (steps 3&4) s erve as the main b asis
for the followin g process: The compression of CO 2 from standard to mi xing conditions (76.23
bar, 60°C ) is carried out in three sta ges with int ercooling. Catal yst and mPG starter are mixed
in a separate v essel and h eated up at the same time. The starter-catal yst mixture is mixed with
first PO and then CO 2 at mixing conditions and fed into the reactor. A mixture of MA and P O
is fed to the reactor s eparatel y . The main reaction is carried out in two parallel CSTRs at
107°C with 96% PO conversion during a resi dence time of 3.36 h. The post re action is
conducted in an insulated (nearl y adi abatic) PFTR to full PO conversion during a residence
time of 0.12 h, reaching 125°C at the reactor outlet. The ex cess CO 2 is flashed at 4.24 bar and
fed bac k to the CO 2 co mpression (after the first stage). The remaining mixture of PEC and
cPC is heated to 160°C and fed into an a gitated falling film evaporator o perating at 10 mbar
in which 70% of the cPC is e vaporated. The cPC is condensed and c ooled to 30°C . The
mixture of PEC and remaining cPC is fed to a packed column operatin g at 160°C and 80 mbar
(head pressure) in whi ch almost all remaining cPC is separated b y a combination of
evapora tion and stripping with nitrogen as strip gas. The cPC is subsequently cond ensed and
cooled to 30°C. P EC (with 100 ppm cPC rest) is obtained at the bottom of the column and
cooled to 30°C. Figur e 12 shows the preliminary P FD for the P EC process. Accompanying
equipment summary, stream summar y an d utili ty stream summar y tables are enclosed in the
supporting information (Tables S4 to S6 ).

Fig ure 12: Process flow diag ram for the double-bond-containing polyether carbonate pol y ol
(PEC) process, max imum operating capacit y : 30 kt/a, product capacity: 23.6 kt/a, base case,
a) pre-treatment & mix ing and reaction steps (and flash s eparation), b) cPC separation steps ,
separa tion stream numbers ‘S’, cP C – cyc lic prop y len e carbonate; DMC cat. – double metal
cy anide catalyst, mPG – monomeric propy lene glyc ol, PO – prop y lene oxide, MA – maleic
anhy dride

5 Refined TEA
5.1 TRL rating (re fined)
The process design (re-engineering based on obs erved data) provided in chapter 4 increase s
the data availability in a wa y that full-s cope TEA methodolog y associated with up t o observed
TRL 5 (PEC) or TR L 4 (PECU) can be applied (s ee also [15,19] ).
5.2 G oal, scope and scenario defin ition (refined)
5.2.1 Goal definition (refined)
The goal of the preliminar y TEA is applicable for the refined TEA. I n ad dition, the results of
the process design (chapter 4) are include d. D y namic profitability ca lcul ation is aimed at.
5.2.2 Scope and scenario definition (refined)
In general, the scop e o f the refined TEA remains uncha nged. All prelimi nary TEA results ar e
also contained in th e refined TEA. On top, the following adaptions re finements are made: For
the cost estimation, the process desi gn no w g i ves the data b asis for E& U cost and FCI
estimation of the PEC proce ss. The market an alysis is extended to cater to the s cenario
analy sis. The profitability an al ysis targets d y na mic indi cators. Furthermore, sensit ivity and
uncertainty analyse s are enlarge d to include model inputs of all cost clusters. In addition, the
results of the pre liminar y TEA and the refine d TEA are compared.
For an assessment of the general viabili ty of a n ew technolog y , it is recommended to examine
multiple technology options, i.e. TEA scenarios. Varying parameters are t he DB moi et y , the
diisocya nate for PECU production and the market sit uation as implied by the ben chmarks.
Any detailed judgement of technical implications of combinations – especially im plications of
altered pol y mer composi tion on properties and thus sales price (ben chmark) – is left to the
development team and cannot be done here due to lack of data. For the DB a ge nt, MA and
AGE are considered. Th e isoc yana te selection foll ows the eco nomic ide a of easy availabilit y
and accessibility. Most e stablished linear pol y urethanes are made with MDI or aliphatic
diisocya nates [ 9]. MDI accounts for 65-70% of t he global diisoc yanate market, TDI for 27-
32% and aliphatic diisocyanates fo r 3-4% with HDI being the most popular aliphatic
diisocya nate [ 9]. I t is expected that chain -elongation can be performed wit h those three major
isocya nates in ver y sim ilar manner. Alternative benchmarks are EPDM and CR . HNBR is
curre ntl y excluded as a benchmark. The exclusi on of HNBR leads to 18 possible
combinations, with ‘MA -MDI- NBR’ fixed as the base case.

5.3 Cost e stimation (refined)
5.3.1 General rem arks (refined)
As define d in the decision prepa ration of the pr eliminary TEA, for th e refined TEA, material
costs and the methodology for indir ect Op Ex and GenEx remain unchanged. For this r eason,
only upd ates on CapEx and E&U cost are p resented in thi s section. Total material cost is
35.33 M$/a (1.50 $/k g); total indirect OpEx is 6.08 M$/a (0.26 $/k g), t otal GenEx is 8. 75
M$/a (0.37 $/kg).
5.3.2 Energy & utility cost (refined)
Energy & utilit y costs were obtained sim ilar to the material cost b y ‘tagging’ all relevant
energy and utilit y stre ams with their respective prices after equipment design. Table 3 li sts the
resulting costs separated b y the four ch aracteristic PEC process steps and PECU steps. Total
E&U cost is 0.58 M$/ a (0.024 $/kg). Electricit y cost make up for 80% of the E&U cost; 75 %
of which is consumed in the PECU process ; 71% of it for powering the reactive extruder . In
the PEC process, 46% of the electricit y is consumed in the pre- treatm ent & mixing step,
mostl y by the CO 2 compressors.

Table 3 : Energy & utilities (E &U ) cost b y item, and b y process steps (for double-bond-
containing pol y ether c arbonate pol y ol (PEC)), and as total proce ss (for pol y ether carbonate
polyure thane rubber (PEC U)), all, cPC – c y clic propylene carbonate

Cost [$/a] for different pr ocess step s

E&U item

PEC
Pre-treatm ent
& m ixing

PEC
Reaction (m ain
and post)

PEC
cPC separati on
stage 1

PEC
cPC separati on
stage 2

PECU
Reactive extrus ion
& solid hand ling /
pack aging

All

Low pressure ste am

20 ,496

Medium pre ssure
steam

73, 436

Cooling w ater

1,038

18 ,626

417

3,116

23 , 19 7

Electricity

51, 85 2

18,037

7, 3 40

36 ,318

346,0 47

459, 594

To tal

73,386

36,663

81,195

39,435

346,047

576, 725

5.3.3 Capital expenditure (refined)
The FCI of the PEC process steps in the refined TEA is calculated based on equipment cost.
The cost surrounding items such as piping add up to the installed cost and are estimated via
factors to the total equipment cost (following [41] , factors adjusted); a detailed list of cost

items and factors can be found in the supporting information in Table S7. The sum of the
installed cost for ever y piece of equipment is the direct I SB L cost. The equipment cost was
calculated to be 4.62 M$ by appl y ing cost correlations [ 41,52] and e xponent rules (see also
[53] ); a detailed li st can be found in the supporting info rmation in Table S 8. The direct ISB L
of the P EC process steps is 14.80 M$. The PEC FCI is calculated as described in section 3.3.5
to be 27.03 M$ . Further details are shown in the following together with an evaluation; the
latter is originally part of the interpretation but is given here for the sake of clarity. The direct
ISBL cost can be split into the four significant process steps, with the pre-t reatment and
mixing sep arated into CO 2 compre ssion and o ther pr e-treatment and mixing – shown in
Fig ure 13 a) . Pre - and po st-treatment parts are far more expensive than the reaction p art itself;
the separation (both sta ges) is the most expensive part of the p rocess. Th is is not surprising
and applies to a lot of chemical plants. The cPC separation stage 2 is the most ex pensive
process step. There is potential for lowerin g cost in more detailed en gineering for this step or
in lower purity requirements which might be allowa ble as cPC is commonly us ed as a
plasticizer in rubber com pounding. Figure 13 b) sh ows the equipment cost s plit int o t y pes of
equipment, namel y compressors and pumps, h eat ex changers, r eactors and towers or other
vessels. The compressors are the most expensive part of the process. This is not surprising for
a chemical plant working at elevated pressures and/or vacuum. The reactors (in sum) ar e the
second most expensive type of equipment. This was ex pected due to high residence times and
elevated re action pr essure. The heat exchangers are relatively inexpensive. This a gain is
common for chemical plants. The separation tow ers present the largest part of the remaining
equipment cost.
PECU FCI remains un changed. Working capital is calculated to b e 6.50 M $. The total CapEx
in the refined TEA is 42.80 M$

Fig ure 13 : Double-bond-containing pol yether ca rbonate pol yol (PEC ) process steps fixed
capital investm ent (FCI) details, a) d istribution of inside battery limi ts ( ISBL) cost for the
PEC plant by proc ess ste ps , b) dist ribution of equipment cost for the P EC plant by equipment
type, cPC – cy cli c propylene carbonate
5.4 Mar ket analysis (refined)
As defined in the goal & scope phase o f the refined TEA (5.2.2), two additional benchmark
materials must be analyzed, EPDM and CR (see also 3.4): EPDM is considered a specialt y
rubber with "good heat and weather resistance" [2 3]. However, the term ‘ EPDM ’ summarizes
a particularly wide range of chemical compositions; it is rather a class of materials than a
single material [54] . For this reason, the market is comparabl y huge but is has to be
considered that a lot of available EPDM structur e options may not be a suitable benchmark.
The following information and calculations refer to avera ge market values. The bi ggest
markets are the automotive, electrical or building & construction industries [55] . Products
include lubricant additives, cable covers, tubing, belts, seals or profiles for construction
[23,55]. A market growth of 5-6% p.a. unti l 2025 is currently expected; the possible sales
volume is calculated to be 220.59 kt/a [55] (which is ~9 times the product capac it y) at an
average pri ce of 2072.50 $ /t [56]. CR is a specialt y rubber with "medium oil resistance and
good ozone resistance [ and] low flammability" [ 23] . Products include con veyor belts, cables,
profiles (such as window seals) or hoses/sheaths [23,57,58] . The US market has experienced a
slow growth or sta gnation at < 0.4% p.a. The global market is very concentrated and as the
US market is saturated [ 59] . Ex port ma y be n ecessar y , adding to the cost of goods sold. The
possible sales volume was calcula t ed to be 68.00 kt/a (demand in North Americ a 2020 [59]
(which is ~14% below product capacit y) at a price of 5247.60 $ /t [ 60]. It is acknowledged that

this market anal y sis is limited to market avera ge values and uncertain data. More in -depth
analy ses require commercial intelligence d ata which could not be accessed for this study and
are left to actual de velopment and deplo y ment projects for thi s technolog y.
5.5 P rofitablility analysis (refined)
It can b e discussed whe ther the inc reased level of observed readiness and data availabilit y
may allow fo r the c alculation of d ynamic indicators. This study pres ents a bord erline case
with large parts of the process considered TRL 5 and other parts falling behind. As
particularly a net present value (NPV) is often asked for and is a p owerful profitabilit y
indicator, it is provided here. However, it is acknowledged that static calculation might be
preferre d b y some practi tioners at this level o f data av ailability (see 5.6.3). For NPV
calculations, an ini tial market diffusion phas e of three years with incr easing sales potentia l
(70-80-90% of produ ct capac it y) is assumed. The plant is constructed over two y ea rs, startin g
2018, with half of the FC I spent each year, follo wed by one year of commi ssioning in which
the working capital is due . Depreciation is linear over th e plant lif etime of 10 y ears. A
potential salvage value i s neglected. The tax rate is assumed as 28.5% [61] and a WACC
value of 7% (see also [ 62]) is used as discount rate. The NPV for the b ase case with refined
cost items is 31.58 M$, corre sponding with an internal rate o f retur n of 17 .02 %. The
minimum required sales price is 2.49 $/kg.
Fernández-Dacosta et al. [30] report COGM of about 1. 33 $/kg for a pol y ol with 20wt% CO 2
(starter: gly cerin/mPG 80/20, M w ~4000 g /mol , 250 kt/a, 2015, NWE , reaction conditions:
135°C, 20 bar). In comparison, this stud y c alculates COGM of 1.72 $/kg for a PEC without
double bonds (adjusted to 25 ye ars, 7.5% discoun t rate to enable comparison). The difference
of 0.39 $/kg can in large parts b e attributed to the vastl y different plant sizes and differing
technical a ssumptions, most notabl y the inclusion of cPC separa tion effort and diff erent
reac tion conditions in this anal y sis.
5.6 Inter pretation (refined)
5.6.1 Interpretation of indicators (refined)
A positive indication for future RD&D is given if the NPV is posi tive or exceeds a target
value. For this a cademic study, no tar get value is given. As the NPV is positive, a positive
indication for future RD&D is given.

5.6.2 Sensitivity and uncertainty analyses (refined)
A sensitivi ty anal y sis is performed for the NPV, varying the model inputs within the cost
clusters. A SA of CapEx is omitted as its composition was shown earlier and all calculations
from equipment cost to CapEx are li near. A comprehensive SA, split into substance price s,
PEC composition, E&U prices, indirect Op Ex, GenEx and parameters for d ynamic
profitability calculation is included in the supporting information as tornado plots ( Figure s S1
to S 6); selected influential model inputs (more than 10% NPV change with +20% variation)
are shown in a tornado p lot in Figure 14. The an al y ses show that the NPV is very sensit ive to
th e sales price (sensitivit y coefficient: 8.52), followed by the PO cost (-3.67). The NPV is
particularly insensitive to E&U pr ices and indirect OpEx apart from maintenance & repairs.

Fig ure 14 : Sensitivit y anal y sis (SA) of selected t he ten most important m odel inputs for n et
present value (NPV), t ornado depiction, +/ -20%, NBR – nitrile butadiene rubber, PO –
propy lene oxide, MA – maleic anhydride, WAC C – weighted average co st of ca pital, GenEx
– general ex penses, PEC – double-bond-containing pol y ether carbonate pol y ol, MDI –
methylene diphen yl diisoc y anate, OpEx – operational expenditure, cPC – c y clic prop y lene
carbona t e

For the uncertaint y analysis of the refined FCI estimate, triangular di stributions of the
equipment installation items between 90 and 110% are set up, correspo nding with a 'Lang
factor' o f 4.19 to 4.81. S im ilarly, for the equipm ent, triangular dist ributions between 70 and
130% percent are s et up . The total FCI distributi on including the refined P EC FCI estimate is
shown in Figure 15. The FCI lies between 32.1 and 55.6 M$ in the interdecile range. With this

calculation, contingenc y for a P80 estimate needs to be about 12.1 M$, adding about 33% to
the base FCI estimate; conti ngency for a P50 estimate needs to be about 3. 4 M$, addin g about
9% to the base FCI estimate. C ontingency is a management decision and thus not included in
this stud y (see also [63 – 66] ). The uncertainty corresponds with AACE international class 4
[49] or can be associated with TR L 4 or 5[15] (-12% and +53% for middle 80%).

Fig ure 15 : Fix ed capital investm ent (FCI) distribution as result of uncertainty anal ysis (UA)
for double-bond-containing pol y ether carbonat e pol y ol (PEC) and p olyether carbonate
polyure thane rubber (PEC U), estimate based on extended block flow diag ram (PECU) with
step counting method a nd equipment-cost-based ( PEC), Monte Carlo (10000 iterations)

For the UA of the NPV, distributions for all major model input s (including substance pri ces,
PEC composition, E&U prices, indirect Op Ex, GenEx and parameters for d ynamic
profitability calculation) were set up. As the NPV is particularl y sensitive to material costs
and selling price, special attention was pay ed to their uncertainties: D ist ributions were derived

from a set of trad e action s (excluding CO 2 and catalysts). R eported ran ges from literature and
expert guesses were used for the remaining distributions. An e xhaustive list of all functions
with their underl y ing d ata and assumptions can be found in th e supporti ng info rmation in
Table S9. Th e resulting NPV dist ribution for the base case is sho wn in Figure 16. The NPV
lies between -54 and 72 M$ in the interdecile range. There is a 61 % chance of generating a
NPV, i.e. this technology bein g economicall y vi able in the b ase case. The relativel y wide
NPV distribution is a consequence of considera ble uncertaint y of the main input costs and the
sales price.

Fig ure 16 : Net present value (NPV) dist ribution as result of uncertainty a nalysis (UA), base
case, refined capital expenditure (CapEx) and energy & utili ties (E&U) cos t estimates, Monte
Carlo (10000 itera tions)
5.6.3 Comparison of preliminary and refined TEA
The refine d E&U calculations about double the E& U cost of the PEC proc ess, leading to a
27.9% increase in the total E&U cost. The notion that E& U costs a re a very minor part of the

COGS remains unaffec t ed. The refined CapEx estimate is 5.8% lower than the preliminar y
estimate due to an FCI P EC decrease o f 8.8%. W hereas the FCI bas e values are ver y sim ilar,
they displa y a substantial decrease in uncertaint y with absolute narrowing of 24% for lower
and 78% fo r upper estimate respectivel y (middle 80%). This implies an advance from AACE
international class 5 to 4 and is associated w ith a TR L increase from 3 to 4 or 5. Refined E &U
and CapEx calculations increa se the base value of the specific profit b y 3.9 % to 0.51 $/kg. To
show the influence of the FCI un certaint y on the overall profitabilit y , UA s were repeated for
the specific profit, only applying the FC I model input distributions. The analy sis w as carried
out for both the preliminary FC I estimate (Figure 17 a) and the refined FC I estimate based on
equipment cost for the PEC process (Figure 17 b) respectively:
a) P reliminary : The specif ic profit (static) lies be tween -0.03 and 0.64 $/kg in the
interdecile ran ge. Th ere is a 11.1 % chance of achieving a n egative profit due to FCI
uncertainty.
b) Refined: The specific profit (static) lies between 0 .31 and 0.55 $/kg in th e interdecile
range. There is a 0.7 % chance of achieving a negative profit due to FCI uncertaint y .
The profitabilit y ’s uncertainty was thus drasticall y reduced with the refined anal y sis
after the process design.

Fig ure 17 : S pecific profit (static calculation) distribution as result of uncertaint y analysis
(UA), including onl y fix ed capital investment (FCI) uncertainty, Mo nte Carlo (10000
iterations), a ) preliminary FC I estimate with process step counting m ethods for double -bond-
containing pol ye ther carbonate pol y ol (PEC) and polyether carbonate p ol yure thane rubber
(PECU), b) refined FC I e stimate with equipment-cost -based method for PEC and process step
counting method f or PEC U
5.6.4 Scenario analysis
The scenarios investigated in this stud y are distinct deviations from the base case resultin g
from single d ecisions instead of numer al distributions. For thi s reason, they can be treated as
context uncerta inty[48] and therefore belong in the interpr etation of the TEA. It is assumed
that process adaptions ar e neg li gible, so that FC I and E&U do not deviate from the base case.
This is justified b y the fact that the material costs are the dominant cost driver and no drastic

changes in the process are expected du e to pol y mer composition changes. In addition, effects
of varied pol y mer composit ion on market opportunities are neglected here. In order to account
for chan ges in mark et op portunities for different P ECU composit ions, both s tructure-propert y
and cost-performance relations would be neede d.
Fig ure 18 s hows NPVs for all scenarios set up in the scope of the refined TEA (5.2.2). The
choice of the diisoc y anate is not cruc ial for the PECU’s profitability. This is due to the low
amount incorpora ted and a relatively n arrow pri ce range for the most common diisocy anates.
For more spe cial isoc y anates, a change in profitabilit y situation is expected; a quick anal ysis
revea ls that an isoc yana te with MDI properties more expensive than 8.92 $/kg would lead to a
negative NPV. I t is acknowledged that the choice of the double bond moiety can have
considerable effect on the TEA. Using MA or AGE comes with differe nt structural
implications: MA leads to double bonds in the main chain, whereas A GE leads to double
bonds in side chains. This will affec t the material properties. The anal ysis reveals that the
AGE option can only be viable if a sales price hi gher than 3.25 $/kg can be achieved. The use
of AGE instead of MA thus has to be just ified wi th an increase in mat erial perfor m ance. This
is due to the substantiall y higher price o f AG E (5.19 $/kg as opposed to 1.21 $/kg of MA ).
The P ECU can be profitable in compar ison to NBR and CR . R egarding EPDM, the
profitability is unsure as EPDM is a large group o f materia ls; more specific EPDM
benchmarks with respective price information must be found. There are different grades of
NBR comin g with dif ferent prices, mostl y determined b y the acr ylonitrile content. The TEA
suggests that it is important to ensure that properties of at le ast medium acr y lonitrile content
NBR can be achieved. If the PECU can be a com petitor to C R and persist on a tight ma rket,
considerable p rofit can be made. Ov erall, the scenario anal ysis reco mmends continued
research on structur e-property relationships alongside h anding over pilot ing products to
potential customers in o rder to reveal sp ecific a pplications and determine a possible sales
price.

Fig ure 18: Net present value (NPV) for di fferent scenarios, “[ double bond agent]-
[diisoc y anate]- [benchmark]”, base c ase “MA -MD I- NBR” , MA – maleic anh y dride, AGE –
allyl gl y cid yl ether, MDI - meth ylene diphen y l diisocyanate, TD I – toluene diisoc y anate, HD I
– hexamethy lene diisoc y an ate, N BR – nitrile b utadiene rubber, CR – chloroprene rubber,
EPDM – ethylene propylene diene monomer rubb er
6 Conclusion and Outlook
The process of the formation of a novel CO 2 -containing polyol (that is based on prop y lene
oxide and includes double bonds in the pol ymer chain) and its cha in-elongation with
diisocya nates to form rubbers is described in this paper. The scope of this stud y is a 23.6 kt/ a
plant (product capacit y ) buil t at the US gulf coast , based on 2018 cost, with a FCI allocation /
deprec i ation time and pla nt lifetime of 10 y ears. Based on a first d escription, characterized b y
extended block flow diagrams, a preliminary TEA was carried out. The major cost clusters of
COGS were calculated t o be: material cost 1.50 $/kg, E &U cost 0.019 $/ kg, indir ect OpEx
0.27 $/kg, GenEx 0.37 $/kg , C apEx 45.4 M$. The COGS were subtracted from a sales price
of 2.81 $/kg which was retrieved from the anal y sis of the respec tive NBR market – the most
probable ben chmark product. I n st atic calculation, a specific profit of 0.49 $/kg was
calculated , indicating a profitable technology. SA and UA disclosed th at there is considerable
uncertainty in the FCI estimate which entails substantial influence on the profit. It was thus
decided to invest in a more detailed process design, aiming at providing a preliminar y p rocess
flow diagram which en ables switching from ver y uncertain process step counting FC I

estimation methodology to more certa in equipment-cost-base d F C I est imation. A process
design was carried out fo r the PEC process, increasing the (observed) level of data av ailabilit y
from TR L 4 to TR L 5. A process design fo r the P ECU process was omitted due to insufficient
literature da ta. The process desig n results form the basis for a refined TEA which wa s
subsequently carried out and provides updated E&U cost of 0.024 $/kg and CapEx of
42.8 M$ (material cost: 1.50 $/kg, indirect OpEx : 0.26 $/kg, GenEx : 0.3 7 $/kg). The
profitability an alysis confirms in dy namic ca l culation that the technolog y can g enerate profit :
In the base case, an NP V of 31.6 M$ is ac hieved. The UA reveals a 61 % chance of the NPV
being positive. The NP V is most sensitive to the sales price (assumed as benchmark price),
followed by the PO price. This comes as no surprise, as the final product contains 68wt%
propy lene oxide and is p roduced in a relativel y i nexpensive proce ss. AGE as a double bond
agent entails considerably hi gher COGS and renders pro fit imposs ible bel ow a sales price of
3.25 $/kg (comp ared to 2 .49 $/kg with MA). The general profitabilit y situati on is not affected
by the choi ce of the diisoc y anate if the options are limited to readil y available and relativel y
inexpensive subst ances, especiall y MD I , TD I and HD I. NBR, EPDM and CR are pr esented as
benchmark substances b oth with respect to properties as well as market opportunities. For
NBR, the general increase in performance and pr ice with increasin g acr y lonitrile content has
to be considered. EPDM is a large group of substances; the p resented PECU is economically
viable in comparison to EPDM average v alues; however, deeper market insights are needed to
streng th en this positi on. The CR market is tight and stagnating but sho ws b y trend hi gher
sales prices that indicate positive market and revenue potential if CR ca n be replac ed by
PECU.
Recommendations for future R&D a re: Prior t o deplo y m ent, it is im perative to further
examine market implications of different structural options and retrieve c orresponding sales
prices as well as entr y markets. In addition, more detailed process desi gn, especiall y for the
PECU formation and subsequent tre atment, c an further reduce un certainty in the C OGS and
help to reveal suitable commercial strate gies. A rece nt LCA of the same group of pol ymers
shows substantial reductions in global w arming im pact and fossil r esource depletion [17] . I t is
recommende d to surve y whether or not customers are willing to pa y a premium for a synthetic
specialty rubber with t his altered environmental profile.

Acknowledgement
The authors would like to thank J ason Collis and Philipp Kretzschmar (TU Berlin) for
valuable le ads on the p rocess design, Annika Marxen and J ohannes Wunderlich (TU Berlin)
for intense assessment methodolog y discussions , Kai Stepputat, Arian Hohgräve and Laura
Heine (TU Berlin) for the preparation of thi s wor k. This work was funded by the Europ ean
Institute of Technolog y (EIT) Cli mate- KIC initiative and the German Federa l Ministr y o f
Education and Researc h (BMBF) FONA3 r +Impuls program.

Funding: This work was supported b y the European Institute of I nnovation and Technology
Climate-KI C and the Ger man Federal Ministr y of Education and Research (BMBF).

Declarat ions of interest: none

Reference s
[1] P. S ty ring, E.A. Quadrelli, K. Armstrong, eds., Carbon Dioxide Utilisation - Closing
the Carbon Cyc l e, 1st ed., Elsevier B.V., 2014. doi:10.1016/B978-0-444-62746-
9.00001-3.
[2] CO2 Sciences - The Global CO2 I nitiative, Global Roadmap for Implementing CO2
Utilization, 2016.
https://assets.ctfassets.net/xg0g v1arhdr3/27vQZEvrx aQiQEAsGy oSQu/44ee0b72ceb92
31ec53ed180cb759614/CO2U_I CEF_Roadmap_FINAL_2016_12_07.pdf.
[3] A.W. Zimmermann, M. Kant, eds., CO2 Utilisation Toda y , Berlin, Ge rmany, 2017.
doi:10.14279/depositonce-5806.
[4] J. Art z, T.E. Müller, K. Thenert, J. Kleinekorte, R. Me y s, A. Sternberg, A. Bardo w, W.
Le itner, S ustainable Conversion of Carbon Dioxide: An I ntegrated R eview of Catalysis
and L ife Cycle Assessment, Chem. Rev. 118 (2018) 434 – 504.
doi:10.1021/acs.chemre v.7b00435.
[5] N. von de r Asse n, A. Ba rdow, Life cy cle assessment of pol y ols for po l y urethane
production using CO 2 as fee dstock: I nsi ghts from an industrial case st udy, Gree n
Chem. 16 (2014) 3272 – 3280. doi:10.1039/c4gc00513a.
[6] A. Scott, Learning To Love CO2, Chem. Eng. News. (2015).
https://cen.acs.org/ar ticles/93/i45/ Lea rning- Love-CO2.html (accessed April 1, 2019).
[7] A.H. Tullo, Novomer takes CO2 chemistry to mar ket, Chem. Eng . News. (2016).
https://cen.acs.org/ar ticles/94/i46/ Novomer-takes-CO2-chemistr y -market.html
(accessed A pril 1, 2019).
[8] S. Robinson, Econic: m aking good use of carbon dioxide (CO2), Urethanes Technol.
Int. (2018). htt ps://utech-pol y urethane.com/information/econic-making-good-use-co2/
(accessed A pril 1, 2019).
[9] M.F. Sonnenschein, Polyurethanes: S cience, Technolog y , Markets, and Trends, W iley
& Sons, Incor po rated, Hoboken, NJ, 2015.
[10] J. Norwig, CroCO2PETs: Cross -linkable CO2 – polye ther pol yols, EnCO2re - Enabling

CO2 Re-Use. (2016). htt p://enco2re.c limate- kic.org/projects/croco2pets/ (accessed
April 1, 2019).
[11] J. Norwig, CO2 – A Versatile Building Block - for a Broad Range of Appli cations,
Presentation, NOVA 11t h I nternational Conference on Bio-based Materials, Ma y 16th,
(2018).
[12] J. Norwig, CroCO2PETs - Cross-linkable Pol ymer s from CO2, Presentation,
Macromolec ul ar Colloquium Freiburg, Germa n y, Feb 16th, (2017).
[13] C. Hopmann, A. L ipski, Optimisation of the Compound Quality of CO2 -b ased Rubber
Compounds, KGK, Elastomers Plast. (2017) 28 – 31.
[14] G.A. Buc hner, R. Sch omäcker, R. Me y s, A. Bardow, Guiding innovation with
integrated life-c y cle ass essment (LCA) and techno -economic assessment (TEA) - the
case o f CO2-containing pol y urethane elastomers, E IT C limate -KIC enCO2re repo rt,
2018.
[15] G.A. Buchner, A.W . Z i mmermann, A.E. Hohgräve, R . Schomäcker, T echno -economic
Assessment Framework for the Chem ical I ndustry - Based on Technology R eadiness
Le vels, Ind. Eng. Chem. Res. 57 (2018) 8502 – 8517. doi:10.1021/acs.iecr.8b01248.
[16] A.W. Zimmermann, J . Wunderlich, G.A. Buchner, L. Müller, K. Armstrong , S .
Michailos, A. Marxen, H. Naims, P. St yring, R. Scho mäcker, A. Bardow, Techno -
Economic Assessment & Life C ycle Assessm ent Guidelines for CO 2 Utilization,
CO2Chem Media and Publishing L td, 2018. doi:10.3998/2027.42/ 145436.
[17] R. Mey s, A. Kätelhön, A. Bardow, Towa rds sustainable elastomers from C O2: lif e
cy cle assessment of carbon capture and utilization for rubbers, Green Chem. (2019).
doi:10.1039/c9gc00267g .
[18] A.W. Zimmermann, R. S chomäcker, Asse ssing Early-Sta ge CO2 utilization
Technologies-Compar in g Apples and Oran ges?, Energ y Te chnol. 5 (2017) 850 – 860.
doi:10.1002/ente.201600805.
[19] G.A. Buchner, K.J. Stepputat, A.W. Zimmermann, R . Schomäcker, S pecify ing
Technology Re adiness Levels for the Chemical I ndustr y , I nd. En g. Chem. Res. 58

(2019) 6957 – 6969. doi:10.1021/acs.iec r.8b05693.
[20] R.A. Ogle, A.R. Carpenter, Calculating the Cap acit y of Chemical Plants, Aiche CEP
Mag. (2014) 59 – 63.
[21] N. Adam, G. Avar, H. Blanke nheim, W. Friedrichs, M. Giersig, E. Weigand, M.
Halfmann, F.-W. W ittbecker, D. -R. Larimer, U. Maier, S. Me y er -Ahrens, K.- L. Noble,
H. -G. W ussow, Polyurethanes, Ullmann’s Enc yc lopedia of I ndustrial Chemistr y , 2012.
doi:10.1002/14356007.a21.
[22] Grand View Research, Nitrile Butadiene Rubber (NB R) Market Anal y sis By Product
(Hoses, Belts, Cables, M olded, Seals & O -rings, Gloves), B y Application (Automotive,
Oil & Gas, Mi ning, Construction, Medical), And Segment Forecasts, 2018 - 2025, S an
Francisco, CA, 2015. https:/ /www.g randviewresearch.com/industr y-anal y sis/nitrile-
butadiene-rubber- m arket/request.
[23] D. Threadingham, W . Obrecht, W . W ieder, G. Wachholz, R. Engeha usen, Rubber, 3.
Synthetic Rubbers, I ntro duction and Overview, Ullm ann’s Enc ycl. Ind. Chem. (2011)
1 – 26. doi:10.1002/14356007.a23_239.pub5.
[24] S. Braun, H. Zwick, M. W ohak, J. Hofmann, A. Wolf, M. Tr aving, R . Bachmann,
Method for producing pol y ether carbonate pol yols and device fo r the same,
EP3164441B1, 2015.
[25] J. Hofmann, S. Braun, K. Laemmerhold, M. Wohak, C. Ahmadzade -Youssefi, J .
Bausa, Method for the purification of pol y carbonate polyols and cleaning device for the
same, EP3164443B1, 2015.
[26] J. Hofmann, S. Bra un, A. W olf, Method for manufacturing polyether c arbonate
polyols, EP3219741A1, 2016.
[27] J. L anganke, A. Wolf, J. Hofmann, K. Böhm, M.A. Subhani, T.E. Mül ler, W. L eitner,
C. Gürtler, Carbon dioxide (CO2) as sustainable feedstock for polyurethane production,
Green Chem. 16 (2014) 1865 – 1870. doi:10.1039/c3gc41788c.
[28] J. L anganke, A. W olf, I ntensified Co -Oligomerization of Propy lene Ox ide and Carbon
Dioxide in a Continuous Heat Exchanger Loop Reactor at Elevated P r essures, Or g.

Process Res. Dev. 19 ( 2015) 735 – 739. doi:10.1021/op500268r.
[29] M. P ohl, E. Danieli, M. Le ven, W. Leitner, B. Blümich, T.E. Müller, Dynamics of
Pol y ether P olyols and Po l y ether Carbonate Pol yols, Macromolecules. 49 (2016) 8995 –
9003. doi:10.1021/acs.macromol.6b01601.
[30] C. Ferná ndez-Dacosta, M. van der Spek, C.R. Hung , G.D. Ore gionni, R. Skage stad, P.
Parihar, D.T. Gokak, A.H. Strømman, A. Ramirez, Prospective techno-economic and
environmental assessment of carbon capture at a refinery and CO2 utilisation in pol y ol
synthesis, J. CO2 Util. 21 (2017) 405 – 422. doi:10.1016/j.jcou.2017.08.005.
[31] J. L anganke, A. W olf, I ntensified Co -Oligomerization of Propy lene Ox ide and Carbon
Dioxide in a Continuous Heat Exchanger Loop Reactor at Elevated P re ssures, Or g.
Process Res. Dev. 19 ( 2015) 735 – 739. doi:10.1021/op500268r.
[32] T. Ouhadi, S. Abdou -Sabet, H.-G. Wussow, L.M. R ya n, L. Plum mer, F.E. Baumann, J .
Lohmar, H.F. Vermeire, F.L.G. M alet, Thermop lastic Elastomers, Ullmann’s Enc ycl.
Ind. Che m. (2013) 1 – 41. doi:10.1016/B978-0-12-394584-6.00013-3.
[33] C. Abe y koon, A.L. Kell y, E.C. Brown, J. Vera-Sorroche, P.D. Coates, E. H arkin-J ones,
K.B. Ho well, J . Deng, K. L i, M. Price, Investigation of the process energy demand in
polymer ex trusion: A brief review and an experimental stud y , Appl. Energ y . 136
(2014) 726 – 737. doi:10.1016/j.apenergy .2014.09.024.
[34] H. Naims, Economics of carbon diox ide ca pture and utili zation - a suppl y and dem and
perspec tive, Environ. Sci. Pollut. Res. 23 (2016) 22226 – 22241. doi: 10.1007/s11356-
016-6810-2.
[35] Global C CS I nstitute, C O2 Transport Costs, Feasibilit y S tud y C CS -Rea diness
Guangdong 2010 Annu. Rep. (2010).
https://hub.globalccsinstitute.com/publications/feasibility-stud y - ccs -r eadiness-
gua ngdong -gdccsr-2010-annual-report/co2-transport-costs (accessed April 1, 2019).
[36] S. Paul, R. Shepherd, P. W oollin, Material selection for supercritical CO2 transport, in:
First Int. For um Transp. CO2 by Pipeline, 2010.
[37] T.J. Ward, Economic ev aluation, in: Kirk-Othmer Ency cl. Chem. Technol., John Wil ey

& Sons, 2001: pp. 525 – 550.
[38] I. V. Klumpar, R.F. Brown, J .W. Fromme, Rapid Capital Estimation Ba sed on Process
Modules, AACE Trans. (1983) B-8.1-6.
[39] G.A. Buchner, J. Wunderlich, R. Schomäcker, (EST -2912) Technology Readiness
Le vels Guiding Cost Estimation in the Chemical Industry, in: AACE I nt. Trans.,
Morgantown, WV, 2018: p. EST.2912.1-23.
[40] M.S. Peters, K.D. Timmerhaus, R.E. W est, Plant Design and Economics f or C hemical
Engineers, fith e d., McGr aw Hill, New York, 2004.
[41] R. Sinnott, G. Towler, Chemical Engineering Design, 2014 repri, Elsevier Ltd,
Amsterdam, 2009.
[42] S.Y. Ereev, M.K. Patel, Practitioner ’ s Section Standardized cost estimation for new
technolog i es ( SCENT ) - methodolog y and tool, 9 (2012).
[43] R. Turton, R.C. Bailie, W.B. W hiting, J .A. Shaeiwitz, D. Bhattacha r yya, Analysis,
Synthesis, and Design of Chemical Processes, P rentice H all, Pearson, U pper Saddle
River, NJ, USA, 2012.
[44] International Institute of S ynthetic R ubber Pro ducers Inc., A cr y lonitrile -Butadiene
Rubber (NBR), 2012. https://iisrp.com/wp-content/uploads/07NBR16Aug 2012.pdf.
[45] UN Comtrade Da tabase, HS 400259, US , imports, (2018). http://comtrade .un.org.
[46] C.A. Saavedra, Th e Marketing Challenge f or Industrial C ompanies, Advanced
Concepts and Prac tices, Springer International Publishing Switzerland, 2016.
[47] A. Saltelli, K. Chan, E. M. Scott, eds., Sensitivity Anal y sis, John Wile y & S ons Ltd.,
Chichester, West Sussex, 2000.
[48] E. I gos, E. Benetto, R. Mey er, P. Baustert, B. Othoniel, How to treat uncertainties in
life cycle ass essment studies?, Int. J . Life C yc l e Assess. (2018). doi:10.1007/s11367 -
018-1477-1.
[49] L.R. D yse rt, P. Christensen, AACE International R ecommended P ractice No. 18R -97;
Cost Estimate Classificaton S y stem – As applied in engineering, procurement, and

construction for the process indus tries - TCM Framew ork: 7.3 – Cost Es timating and
Budgeting, Morga ntown, 2016.
[50] W.D. Seider, J .D. Seader, D.R. Lewin, S. W idagdo, Produ ct and Pro cess Desi gn
Principles, Wiley & Sons (Asia), New Delhi, 2010.
[51] R. S mith, Chem ical Process Desi gn and Integration, 2nd editio, J ohn Wiley & Sons,
Chichester, West Sussex, 2016.
[52] D. Milligan, J. Milligan, Matches’ Process E quipment Cost Estimates, (2014).
http://www.matche.com/equipcost/De fault.html (accessed April 3, 2019).
[53] R. W illiams J r., Six -Tenths Factor Aids in Approx imating Costs, Chem. Eng. 54
(1947) 124 – 125.
[54] Internationa l Institute of Synthetic Rubber Prod ucers Inc., Eth ylene-Prop y lene Rubbers
& Elastomers (EPR / EPDM), 2012.
[55] Grand View R esearch, Ethy lene Prop ylene Diene Monome r (EPDM) Market Size,
Share & T rends Anal ysis Report By Applic ation ( Electrical & Electronics, Building &
Construction, Wires & Cables), And Segment For ecasts, 2019 - 2025, sample, San
Francisco, CA, 2019. htt ps://www.gra ndviewresearch.com/industry- anal ysis/ethy lene-
propy lene-diene-monom er-epdm-market/request.
[56] UN Comtrade Da tabase, HS 400270, US , imports, (2018). http://comtrade.un.org.
[57] Grand Vie w Research, Chloroprene Rubber Marke t Siz e, Application Analysis,
Regional Outlook, Competitive Strategies A nd Forecasts, 2014 To 2020, San
Francisco, CA, 2020. https:/ /www.grandviewresearch.com/industry-
analy sis/chloroprene -rubber-market/request-toc.
[58] Internationa l Institute of Sy nthetic Rubber Producers I nc., Pol y chloroprene,
Chloroprene Rubber (CR), 2012.
[59] Jacobs Consultancy Ltd, Assessment of Technical and Financial Viability of Nairit
Chemical Plant Opera tio n, Washington, DC, 2015.
[60] UN Comtrade Da tabase, HS 400249, US , imports, (2018). http://comtrade .un.org.

[61] K. Pomerleau, The Unit ed States’ Corporate Income Tax Rate is Now More in Line
with Those Levied b y Other Major Nations, (2018). htt ps://taxfoundation.org/us-
corpora t e-income-tax-more-competitive/ (accessed April 1, 2019).
[62] A. Damodaran, Cost of C apital b y Sector (US), (2019).
http://pages.stern.ny u.edu/~adamodar/New_Home_Page/datafile/wacc.htm (acc essed
April 1, 2019).
[63] AACE Interna tional, K.K. Hum phre y s, AACE International Recommended Prac tice
No. 41R-08; Risk Analy sis and Conting enc y Determination Using Range Estimating,
2008.
[64] AACE I nternational, J.K. Hollmann, AACE I nternational Recommended Practice No.
42R-08; Risk Analysis and Contingency Determination Using Parametric Estimating,
2011.
[65] AACE Inter national, R. Prasad, AACE I nternatio nal Recomme nded Practice No. 43R -
08; Risk Analy sis and Conti nge nc y Determination Using Parametric E stimating -
Example Models as Applied for the Process Industries, 2011.
[66] AACE I nternational, J.K. Hollmann, AACE I nternational Recommended Practice No.
44R-08: Risk Analysis and Contingency Determi nation Using Expected Value, 2012.

Vitae
Georg A. Buchner received his M.Sc. in I ndustrial Engineering
and Management from TU Berlin. Since 2015, he has been a
researcher in the group of Prof. Schomäcke r at the same
institution. His researc h focusses on tec hno -economic
assessment, reaction engineering, and the development o f
scalable p rocess concepts for pol y m er s yntheses and multiphase
reac tion systems. In 2019, he joined the MIT En ergy Initiative as
a visiting re searcher.

Nils Wulf es is a gra duate student in TU Berlin’s Industria l
Engineering and Management program. His studies focus on
chemical & process engineering fo r pol ymer starters and
intermediates. H e has pr ofessional experience in the development
of alterna tive powertrain s and business models.

Reinhard S chom äcker is Professor for Reaction Engineering at
TU Berlin. His r esearch fields are reaction kineti cs, re actors and
process concepts as well as technolog y assessment. He has
experience in gree n chemistr y research such as photocataly tic
water splitting, wastewater tre atment, and electroc hemical
conversion of CO 2 . He re ceived the I nnovation Award of the
German Gas I ndustr y for his research in oxidative couplin g of
methane in 2016.

Why organizations use Identific for document trust, entry 24

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