Complete Green Metrics Evaluation of Various Routes to Methyl

Nov 19, 2015 - The adjusted ISI scores presented here based on summing scores from all input materials in a given synthesis plan is more realistic tha...
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Research Article pubs.acs.org/journal/ascecg

Complete Green Metrics Evaluation of Various Routes to Methyl Methacrylate According to Material and Energy Consumptions and Environmental and Safety Impacts: Test Case from the Chemical Industry John Andraos* CareerChem, 504-1129 Don Mills Road, Toronto, ON M3B 2W4, Canada S Supporting Information *

ABSTRACT: In this paper we present a standardized protocol for the complete evaluation of greenness of 18 industrial routes to methyl methacrylate (MMA) covering material and energy consumptions and environmental and safety impacts. A methodology for estimating energy consumption for chemical reactions and synthesis plans from published journal and patent literature procedures is fully described. A new energy metric pertaining to enthalpic changes from standard state conditions (298 K, 1 atm) to reaction conditions (Trxn, prxn) for all input materials used in a synthesis plan for the production of 1 mol of product is defined with respect to the heating and evaporation of 1 mol of water from 298 K and 1 atm. Limitations and best practices of running the protocol are discussed. The present study serves as a template for implementing the protocol to the green metrics analysis of high volume industrial chemicals. Results of plan rankings are compared with previous work on inherent safety indexes. Based on these findings, the isobutylene and t-butyl alcohol routes to MMA are found to have the overall greenest attributes among the 18 routes examined. KEYWORDS: Green metrics, Methyl methacrylate, Energy consumption, High volume production, Industrial chemistry



INTRODUCTION Various methodologies for carrying out integrated green metrics analyses of chemical reactions and synthesis plans according to material efficiency have evolved over the past decade and are now firmly established.1−9 The key materials efficiency metrics accepted by the chemical industry, most notably the pharmaceutical industry, are reaction yield (RY), atom economy (AE),10 reaction mass efficiency (RME),11−13 E-factor (E),14 and process mass intensity (PMI).15,16 In 2009 we demonstrated the use of our own algorithm using these five metrics to ascertain the best synthetic route to oseltamivir phosphate,17−19 a neuraminidase inhibitor of H5N1 influenza virus, from various published industrial and academic synthesis plans. Recently, we have endeavored to incorporate environmental and safety impact metrics in a simplified life cycle assessment (LCA), thereby increasing the breadth and depth of our metrics analysis.20 These additional metrics cover standard parameters associated with transport of chemicals in the environment, human toxicity, bioaccumulation, and climate damage including octanol−water partition coefficients, Henry’s law constants, LD50 and LC50 toxicity parameters, acidification, and global warming risk potentials among others.21 Unlike material consumption, agreement on which environmental impact and health and safety metrics to choose has been hampered due to ongoing issues related to unavailability and unreliability of necessary data, thus making analyses less © XXXX American Chemical Society

rigorous and fraught with uncertainty. Most notably, parametrizations of cancer risk potential and endocrine disruption are not yet fully understood. Despite these shortcomings, there is general consensus that combined metrics analyses of welldefined material consumption and albeit approximate environmental/safety impact give a more balanced and fair assessment of reaction or synthesis plan greenness for a given target compound than analyses based on material consumption alone. However, trade-offs between them are often exposed which leads to more difficult decision making with respect to declaring which synthetic route is the most green among a set of candidate plans. Up to now the question of energy consumption has been given very little attention22 mainly because it is customary to not report these data in standard write ups of experimental procedures. However, inferences about energy consumption can be made based on examination of reaction conditions, namely, temperature and pressure, and of purification operations such as evaporation of solvents and distillation of product. It should be pointed out that such inferences rely only on thermodynamic considerations and do not account for the actual electricity consumption of apparatuses used in all unit operations. In addition, Received: October 6, 2015 Revised: November 13, 2015

A

DOI: 10.1021/acssuschemeng.5b01240 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

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ACS Sustainable Chemistry & Engineering Scheme 1. Eighteen Industrial Routes to Methyl Methacrylate

B

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ACS Sustainable Chemistry & Engineering Scheme 1. continued

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ACS Sustainable Chemistry & Engineering Scheme 1. continued

Figure 1. Flowchart showing the steps followed in carrying out thermodynamic computations for input materials in a synthesis plan.

D

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ACS Sustainable Chemistry & Engineering

the Supporting Information). Using appropriate thermodynamic data, the molar enthalpic changes due to temperature and pressure contributions for each input substance are determined according to eq 2.30 An Excel spreadsheet is given in the Supporting Information (materials-thermodynamic-parameters.xls) summarizing thermodynamic data for all input materials used for the 18 synthetic routes to MMA.

experimental details for high volume industrial chemicals that are the first, second, and third generation feedstocks to the chemical industry are well-known and well documented in the literature. Therefore, a set of synthetic routes to any one of these feedstock chemicals from fossil fuel starting materials can serve as a good template to test a proposed method for estimating energy consumption. In this work we have chosen methyl methacrylate (MMA) as the test target compound for our present study on estimating energy consumption metrics since it has been reviewed previously and a variety of industrial routes are well-described.23−27 Scheme 1 shows 18 routes to MMA examined that were extracted from a reaction network published by Nagai24 (see Scheme S1 in Part 1 of the Supporting Information). Each chemical equation is fully balanced and the key reaction conditions of temperature and pressure for each step are shown. A complete list of references for these routes is given in Part 2 of the Supporting Information. To facilitate comparison with prior published work on this compound, we have preserved the specialized designations attached to the first 8 routes: routes 1a and 1b (ACHacetone cyanohydrin), route 2 (C2/PAethylene based via propionaldehyde), route 3 (C3propylene based via isobutyric acid), route 4 (C2/MPethylene based via methyl propionate), route 5 (iC4isobutylene based), route 6 (TBAtertiary butyl alcohol based), route 7 (PApropyl alcohol based), and route 8 (PPpropylene based via isopropyl chloride).



ΔH = qtemp + qpress =

C p(T ) dT +

p2

∫p

1

⎡ ⎛ ⎞ ⎤ ⎢V − T ⎜ ∂V ⎟ ⎥ dp ⎝ ∂T ⎠ p⎥⎦ ⎢⎣

(2)

where ΔH = H2 − H1 is the enthalpy change in kilojoules per mole between the standard state (298 K, 1 atm) and the reaction state (Trxn, prxn), Cp (T) is a temperature dependent heat capacity function at constant pressure pertaining to the phase of the substance, T1 = 298 K, T2 = Trxn, p1 = 1 atm, p2 = prxn, and V is the molar volume (L/mol). Temperature Contribution. For each input material in a plan the enthalpy change in kilojoules for heating that substance from 298 K to the reaction temperature is determined on a per mole basis and is given by the parameter q. Processes involving heating have q > 0 and those involving cooling have q < 0. The q value of a given substance is then multiplied by its corresponding mole scale as prescribed in the synthesis plan in which that substance appears. The procedure is repeated for all input materials in a plan and the overall input energy sum is determined for a 1 ton synthesis of MMA which can then be converted back to units of kilojoules per mole. The enthalpic contribution due to heating a substance depends on the phase transitions it can undergo from standard state conditions (298 K and 1 atm) to reaction conditions. The following cases given by eqs 3−11 illustrate the possible calculation scenarios for determining the temperature change contribution to enthalpy. All thermodynamic data were obtained from the DIPPR (Design Institute for Physical Property Data) database31 and Yaws.32 Case I. Heating a liquid at 298 K from 298 K to Trxn (Trxn is above boiling point, Tb) where the liquid undergoes a phase transition from liquid to gas:

METHODOLOGY

q=

Tb

∫298 Cp,liq(T ) dT + ∫T

Trxn

C p,gas(T ) dT + ΔH vap

b

(3)

C p,liq(T ) = A + BT + CT 2 + DT 3 + ET 4

(4)

⎡ C / T ⎤2 ⎡ E / T ⎤2 C p,gas(T ) = A + B⎢ ⎥ + D⎢ ⎥ ⎣ sinh(C /T ) ⎦ ⎣ cosh(E /T ) ⎦

(5)

where ΔHvap is the heat of vaporization, the functions Cp(T) represent the temperature dependent heat capacity functions at constant pressure for liquids and gases, and the parameters A, B, C, D, and E are constants specific to a given substance. Case II. Heating a liquid at 298 K from 298 K to Trxn (Trxn is below boiling point, Tb) where the liquid does not undergo a phase transition:

1 [(AE)2 + (RY)2 + (RME)2 + (BI w )2 + (SHI w )2 6 + (SHI in)2 ]1/2

T2

1

(1) Material Consumption. For each route shown in Scheme 1, the global AE, yield, RME, and PMI parameters were determined at a common basis scale of 1 ton of methyl methacrylate using the recently updated REACTION and SYNTHESIS Excel spreadsheet algorithm.28 (ii) Environmental and Safety Impact. For each route shown in Scheme 1, the benign index for waste materials, (BI)w, safety-hazard index for waste materials, (SHI)w, and safety-hazard index for input materials, (SHI)in, were determined according to our previously reported algorithm.20 The Supporting Information contains a summary Excel spreadsheet summarizing all environmental and safety impact parameters for all input materials used in the 18 synthetic routes to MMA (environmental-safety-analysis-MMA.xls, missingdata.xls). (iii) Route Ranking Based on Materials and Environmental/ Safety Impact. The 18 routes were ranked according to the vector magnitude ratio (VMR)29 parameter covering AE, yield, RME, (BI)w, (SHI)in, and (SHI)w metrics as given by eq 1.

VMR =

∫T

(1)

(iv) Energy Consumption. Based on temperature and pressure conditions reported for each reaction step, the total input energy required to heat, cool, and pressurize all input materials in a synthesis plan at the appropriate reaction conditions were determined. In this treatment the energy consumption to operate all necessary equipment including their intrinsic efficiencies were neglected. Hence, the calculated results presented should be considered theoretical minimum estimates for actual input energy consumption. Figure 1 shows a flowchart of steps followed for carrying out thermodynamic calculations. A basis scale of 1 ton for MMA is set for all plans and the corresponding mole scales and masses of all input materials required in a given synthesis plan to produce a final mass of 1 ton of MMA are determined. The phases of each input material at 298 K and 1 atm (state 1) and at Trxn and prxn (state 2) are determined according to a set of inequality conditions based on reduced temperature and reduced pressure values (See Figure S1 in Part 3 of

q=

Trxn

∫298

C p,liq(T ) dT

(6)

Case III. Heating a gas at 298 K from 298 K to Trxn: q=

Trxn

∫298

C p,gas(T ) dT

(7)

Case IV. Heating a solid at 298 K from 298 K to Trxn (Trxn is above both the boiling point, Tb, and the melting point, Tm) where the solid undergoes phase transitions from solid to liquid and from liquid to gas:

q=

Tm

∫298 Cp,sol(T ) dT + ∫T

Tb

m

+ ΔHfus + ΔH vap E

C p,liq(T ) dT +

∫T

Trxn

C p,gas(T ) dT

b

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ACS Sustainable Chemistry & Engineering C p,sol(T ) = A + BT + CT 2 + DT 3 + ET 4

⎡ RT b 2 q=⎢ − ⎢⎣ V2 − b

(9)

where ΔHfus is the heat of fusion and Cp,sol (T) is the temperature dependent heat capacity function at constant pressure for solids. Case V. Heating a solid at 298 K from 298 K to Trxn (Trxn is above melting point, Tm) where the solid undergoes a phase transition from solid to liquid: q=

Tm

∫298

C p,sol(T ) dT +

∫T

Trxn

C p,liq(T ) dT + ΔHfus

m

⎡ RT b b −⎢ − ⎢⎣ V1 − b

Trxn

∫298

C p,sol(T ) dT

(10)

N

∑ qj ,tempxj

where xj is the number of moles of substance j and qj,temp is the heat input in kiloloules per mole given by any one of the expressions shown in eqs 3−11. Since all xj mole scales are referenced to production of 1 ton of MMA, the units for overall Qtemp from eq 12 are kilojoules per ton MMA which can then be converted to kilojoules per mole MMA. Pressure Contribution. Enthalpic contributions due to changing pressure were determined by applying the Redlich−Kwong equation of state (RKEOS) function to gases33 or the Tait equation to liquids34,35 depending on the phase of the input material at the reaction conditions. In engineering thermodynamics textbooks, calculations of enthalpy changes often neglect the pressure contribution (second term in eq 2) if reaction pressures are less than 100 atm.30,36 However, in our present investigation, we were required to take this term into account for the following cases: route 4 (step 1, p = 745 atm), route 8 (step 2, p = 400 atm), route 11 (step 1, p = 780 atm), route 12 (step 3, p = 145 atm), route 16 (step 1, p = 780), route 17 (step 1, p = 500 atm), and route 18 (step 1, p = 500 atm). Since such calculations are rarely described, we decided to implement them for any reaction we encountered that was conducted at pressures exceeding 1 atm. Illustrative examples of such calculations for substances that are gases or liquids at elevated pressures are given in part 7 of the Supporting Information. The pressure contribution to the overall input energy for N input substances in a synthesis plan is given by eq 13.

B = − 1 + a(1 − Tr)1/3 + b(1 − Tr)2/3 + d(1 − Tr) pc + e(1 − Tr)4/3

(18)

where pc is the critical pressure (Pa), Tr is the reduced temperature equal to T/Tc, Tc is the critical temperature (K), ω is the acentric factor, a = −9.070 217, b = 62.453 26, d = −135.1102, e = exp[f + gω + hω2], f = 4.795 94, g = 0.250 047, and h = 1.141 88. Alternatively, eq 19 may be used to approximate q if it is assumed that the molar volume of the liquid does not change with pressure over the range 101 325 Pa to p2 Pa.

⎛V + a ⎛ 1 ⎞ 3a ln⎜ 2 ⎜ ⎟− T2 ⎝ V2 + b ⎠ 2b T2 ⎝ V2

⎡ RT b 2 − q=⎢ ⎢⎣ Vsat − b

b ⎞⎤ ⎟⎥ ⎠⎦⎥

⎛ V + b ⎞⎤ a ⎛ 1 ⎞ 3a ln⎜ 1 ⎜ ⎟− ⎟⎥ T1 ⎝ V1 + b ⎠ 2b T1 ⎝ V1 ⎠⎦⎥

(19)

Case IV. Transition from state 1 (gas at 298 K and 1 atm) to state 2 (liquid at T2 and p2) via the intermediate gaseous state at T2 and saturation pressure, psat:

where xj is the number of moles of substance j and qj,press is given by eqs 14−21 depending on the phase transition from state 1 to state 2. Case I. Transition from state 1 (gas at 298 K and 1 atm) to state 2 (gas at T2 and p2):

⎡ RTb 1 −⎢ − ⎢⎣ V1 − b

(17)

C = 0.0861488 + 0.0344483ω

(13)

j=1

⎡ RT b 2 − q=⎢ ⎢⎣ V2 − b

(16)

q = (1 − ϕT2)Vs(p2 − 101325)

∑ qj ,pressxj

(15)

where the Tait equation of state for liquids was used, ϕ is the thermal expansion coefficient equal to (1/V)(∂V/∂T)p (1/K) evaluated at the reaction temperature T2,32 Vs is the molar volume (L/mol) at reaction temperature T2 and 1 atm = 101 325 Pa, ps is the vapor pressure (Pa) at reaction temperature T2, and the constants B and C are given by eqs 17 and 18.34 The units of q from eq 16 are pascals liters per mole which can be converted to kilojoules per mole by dividing by 106.

N

Q press =

b ⎞⎤ ⎟⎥ ⎠⎦⎥

⎫ ⎛ B + 101325 ⎞⎤⎪ ⎟⎟⎥⎬ − 101325ln⎜⎜ ⎝ B + ps ⎠⎥⎦⎪ ⎭

(12)

j=1

⎛V + a ⎛ 1 ⎞ 3a ln⎜ 1 ⎜ ⎟− Tb ⎝ V1 + b ⎠ 2b Tb ⎝ V1

⎧ ⎪ q = (1 − ϕT2)Vs⎨(p2 − 101325)(1 + C) ⎪ ⎩ ⎡ ⎛B + p ⎞ ⎛ B + p2 ⎞ 2⎟ − BC ln⎜ ⎟ − C ⎢p2 ln⎜⎜ ⎟ ⎢⎣ ⎝ B + 101325 ⎠ ⎝ B + ps ⎠

(11)

The overall input energy temperature contribution for N input substances in a synthesis plan is given by eq 12.

Q temp =

b ⎞⎤ ⎟⎥ ⎠⎥⎦

where the Redlich−Kwong equation of state (RKEOS) for gases is used, a and b are the attraction and repulsion constants, and V1 and V2 are the respective molar volumes (L/mol). The units of q are liters atmospheres per mole which can be converted to kilojoules per mole by multiplying by 0.101 325. Case III. Transition from state 1 (liquid at 298 K and 1 atm = 101 325 Pa) to state 2 (liquid at T2 and p2):

Case VI. Heating a solid at 298 K from 298 K to Trxn (Trxn is below melting point, Tm) where the solid does not undergo a phase transition:

q=

⎛V + a ⎛ 1 ⎞ 3a ln⎜ 2 ⎜ ⎟− T2 ⎝ V2 + b ⎠ 2b T2 ⎝ V2

⎡ RTb 1 −⎢ − ⎢⎣ V1 − b

⎛V + 3a a ⎛ 1 ⎞ ln⎜ sat ⎜ ⎟− 2b T2 ⎝ Vsat T2 ⎝ Vsat + b ⎠ ⎛V + 3a a ⎛ 1 ⎞ ln⎜ 1 ⎜ ⎟− 2b T1 ⎝ V1 T1 ⎝ V1 + b ⎠

b ⎞⎤ ⎟⎥ ⎠⎦⎥

b ⎞⎤ ⎟⎥ ⎠⎦⎥

⎧ ⎛B+p ⎞ ⎪ 2 ⎟ + (1 − ϕT2)Vs⎨(p2 − psat )(1 + C) − BC ln⎜⎜ ⎟ ⎪ ⎝ B + psat ⎠ ⎩ ⎡ ⎛B + p ⎞ ⎛ B + p ⎞⎤⎫ ⎪ sat ⎟⎥ 2⎟ − C ⎢p2 ln⎜⎜ − psat ln⎜⎜ ⎟ ⎟⎥⎬ ⎪ ⎢⎣ + + B p B p ⎝ ⎝ s ⎠ s ⎠⎦⎭ (20)

(14)

where the Redlich−Kwong equation of state (RKEOS) for gases is used, a and b are the attraction and repulsion constants, T1 = 298 K, and V1 and V2 are the respective molar volumes (L/mol). The units of q are liters atmospheres per mole which can be converted to kilojoules per mole by multiplying by 0.101 325. Case II. Transition from state 1 (liquid at 298 K and 1 atm) to state 2 (gas at T2 and p2) via the intermediate liquid state at the boiling point, Tb, and 1 atm):

where the Redlich−Kwong equation of state (RKEOS) for gases and the Tait equation of state for liquids are used, T1 = 298 K, a and b are the attraction and repulsion constants, and V1 and Vsat are the F

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ACS Sustainable Chemistry & Engineering Table 1. Summary of Global Material Efficiency Metrics for MMA Syntheses According to Scheme 1 number of stepsa

plan route route route route route route route route route route route route route route route route route route route route a

1a (ACH) 1b (ACH) 2 (C2/PA) 3 (C3) 4 (C2/MP) 5 (iC4) 6 (TBA) 7 (PA) 8 (PP) 9 10 11 12 13a 13b 14 15 16 17 18

3, 5, 4, 3, 3, 3, 3, 3, 3, 2, 3, 4, 3, 5, 7, 2, 3, 4, 4, 3,

L C L L C L L L L L L L L L C L L L L L

RY (%)

AE (%)

E

RME (%)

PMI

rank

57.4 46.2 55.6 26.8 72.2 65.7 64.9 30.2 40.6 64.2 56.9 25.4 17.5 44.0 35.4 3.7 62.6 27.9 12.2 18.1

37.2 34.8 73.5 42.7 50.0 73.5 64.9 39.7 57.3 42.7 46.7 46.3 58.1 52.9 48.3 64.9 51.0 50.5 40.0 73.5

6.90 7.97 15.52 18.00 10.30 29.60 29.66 15.70 856.40 14.28 5.19 25.40 89.86 21.54 15.23 63.12 38.63 92.40 24.88 310.03

12.7 11.1 6.1 5.3 8.8 3.3 3.3 6.0 0.1 6.5 16.2 3.8 1.1 4.4 6.2 1.6 2.5 1.1 3.9 0.3

7.90 8.97 16.52 19.00 11.30 30.60 30.66 16.70 857.40 15.28 6.19 26.40 90.86 22.54 16.23 64.12 39.63 93.40 25.88 311.03

2 3 7 9 4 13 14 8 20 5 1 12 17 10 6 16 15 18 11 19

L = linear; C = convergent.

respective molar volumes (L/mol). By analogy with eq 19 for case III, q may be approximated by eq 21.

⎡ RT b 2 − q=⎢ ⎢⎣ Vsat − b ⎡ RTb 1 −⎢ − ⎢⎣ V1 − b

⎛V + 3a a ⎛ 1 ⎞ ln⎜ sat ⎜ ⎟− 2b T2 ⎝ Vsat T2 ⎝ Vsat + b ⎠

of synthesis plans based on this parameter are more comprehensive and should be more reliable than those determined from eq 1.



b ⎞⎤ ⎟⎥ ⎠⎦⎥

RESULTS AND DISCUSSION Material Efficiency. Table 1 summarizes the essential material efficiency metrics for the 18 routes to MMA. Rankings

⎛ V + b ⎞⎤ 3a a ⎛ 1 ⎞ ln⎜ 1 ⎜ ⎟− ⎟⎥ 2b T1 ⎝ V1 ⎠⎦⎥ T1 ⎝ V1 + b ⎠

+ (1 − ϕT2)Vs(p2 − psat )

Table 2. Global E-Factor Breakdown for MMA Syntheses According to Scheme 1

(21)

plan

Full derivations of eqs 14−21 including corresponding state-to-state path diagrams following the method of Tosun37 are given in Parts 6 and 8 of the Supporting Information. Again, the units for overall Qpress from eq 13 are kilojoules per ton MMA which can then be converted to kiljoules per mole MMA. In all cases the magnitude of the temperature change contribution to ΔH in eq 2 far exceeded that of the pressure change contribution; i.e., Qtemp ≫ Qpress. (v) Route Ranking Based on Materials, Environmental/ Safety Impact, and Energy Consumption. The 18 routes were ranked according to the vector magnitude ratio (VMR)29 parameter covering AE, yield, RME, (BI)w, (SHI)in, (SHI)w, and (EI)in metrics as given by eq 22. VMR =

route route route route route route route route route route route route route route route route route route route route

1 [(AE)2 + (RY)2 + (RME)2 + (BI w )2 + (SHI w )2 7 + (SHI in)2 + (EI in)2 ]1/2

(22)

where an energy index for input materials is defined as shown in eq 23.

⎧1, Q plan ≤ 2qwater = 92.62 ⎪ ⎪ q EI in = ⎨ water , Q plan > 2qwater = 92.62 ⎪ ⎪ Q plan − q ⎩ water

(23)

The overall input energy consumption Qplan = Qtemp + Qpress in units of kilojoules per mole MMA for a synthesis plan is compared to the energy input required to heat and evaporate 1 mol of liquid water from a starting state of 25 °C and 1 atm (46.31 kJ/mol). Note that the input energy index is defined as a value ranging between 0 and 1, consistent with the other metrics contributing to VMR. Since the VMR determined from eq 22 covers material efficiency, environmental impact, safety/hazard impact, and input energy consumption, rankings

1a (ACH) 1b (ACH) 2 (C2/PA) 3 (C3) 4 (C2/MP) 5 (iC4) 6 (TBA) 7 (PA) 8 (PP) 9 10 11 12 13a 13b 14 15 16 17 18

E-aux

E-byproducts

E-unreacted

E-total

0.75 0.77 10.50 1.22 1.25 27.21 27.21 1.17 769.20 10.28 1.21 8.92 69.85 4.12 3.05 26.26 29.93 50.44 1.01 303.06

4.30 5.11 4.61 2.37 1.12 0.64 0.64 2.37 1.82 1.83 1.54 1.60 3.40 2.38 1.62 0.57 1.03 1.18 2.69 0.38

1.86 2.09 0.41 14.41 7.93 1.75 1.81 12.16 85.06 2.17 2.44 14.88 16.62 15.04 10.56 36.28 7.68 40.78 21.17 6.60

6.90 7.97 15.52 18.00 10.30 29.60 29.66 15.70 856.09 14.28 5.19 25.40 89.86 21.54 15.23 63.12 38.63 92.40 24.88 310.03

based on PMI values are given in the last column. From these data we observe that the most material efficient plan having the least PMI is route 10 involving nickel catalyzed multicomponent assembly of ethylene, carbon monoxide and water to give propanoic acid, followed by esterification to methyl propionate, and final condensation with formaldehyde to give G

DOI: 10.1021/acssuschemeng.5b01240 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

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Closer examination of the E-factor breakdown contributions from auxiliary material consumption, reaction byproducts, and unreacted starting materials as shown in Table 2 indicates that routes 1a/b (ACH), 3 (C3), 4 (C2/MP), 7 (PA), 10 (propanoic acid), and 17 (hydroformylation-oxidation/dehydrogenation-esterification) have the least E-aux; routes 5 (iC4), 6 (TBA), 14 (isobutane oxidation/dehydogenation-esterification), and 18 (hydroformylation-oxidation/dehydrogenationesterification) have the least E-byproducts; and route 2 has the least E-unreacted starting materials. Route 10 with the lowest overall PMI has low values for each of these E-factor contributions across the board. Inclusion of Environmental-Safety/Hazard Impacts. Table 3 summarizes the BI and SHI indices, including uncertainties expressed as a percentage of missing data parameters, for all 18 MMA routes. From these data we observe that the routes producing the most benign waste with respect to environmental impact are routes 5, 6, 8, and 13a/b. Routes 1a/b arising from ingestion toxicity due to unreacted acetone cyanohydrin, route 4 arising from ingestion toxicity due to potassium cyanide, and routes 3 and 7 arising from inhalation risks due to unreacted carbon monoxide substrate produce the most environmental harm. Routes 8, 13a/b, and 17 produce the least hazardous wastes; whereas, routes 10 and 18 produce the most hazardous waste due to occupational exposure risk from nickel tetracarbonyl and quartz dust inhalation, respectively. The next ranking hazardous wastes arise from routes 9, 15, and 18 which involve occupational exposure risks from benzene solvent, nickel tetracarbonyl catalyst, and quartz dust inhalation, respectively. The same routes are implicated with respect to least and most hazardous input materials rankings. Environmental harm due to ingestion and inhalation toxicities dominated the benign index

Table 3. Summary of BI(waste), SHI(waste), and SHI(input) Indices and Uncertainty Estimates for MMA Syntheses According to Scheme 1a plan route route route route route route route route route route route route route route route route route route route route

1a (ACH) 1b (ACH) 2 (C2/PA) 3 (C3) 4 (C2/MP) 5 (iC4) 6 (TBA) 7 (PA) 8 (PP) 9 10 11 12 13a 13b 14 15 16 17 18

(BI)w 0.987; 0.989; 0.982; 0.912; 0.977; 0.995; 0.995; 0.906; 0.995; 0.975; 0.960; 0.977; 0.993; 0.996; 0.995; 0.989; 0.983; 0.982; 0.958; 0.993;

4% 3% 3% 2% 3% 3% 2% 3% 2% 8% 5% 6% 5% 6% 5% 4% 4% 4% 5% 5%

(SHI)

w

0.956; 5% 0.995; 5% 0.994; 8% 0.973; 6% 0.963; 9% 0.988; 10% 0.988; 10% 0.979; 6% 0.999; 4% 0.851; 10% 0.849; 4% 0.984; 7% 0.984; 8% 0.994; 8% 0.995; 7% 0.990; 7% 0.944; 6% 0.991; 9% 0.996; 9% 0.467; 9%

(SHI)in 0.906; 5% 0.989; 5% 0.978; 8% 0.977; 7% 0.968; 9% 0.986; 11% 0.986; 11% 0.981; 7% 0.997; 4% 0.825; 9% 0.917; 1% 0.989; 6% 0.975; 9% 0.993; 10% 0.994; 8% 0.989; 9% 0.951; 7% 0.976; 10% 0.996; 10% 0.472; 10%

a

Uncertainties are determined as the fraction of missing parameters required to determine the indices.43

MMA. The next most material efficient route is the traditional acetone cyanohydrin route (routes 1a and 1b). Route 4 (C2/ MP) has the highest overall yield, and routes 2 (C2/PA), 5 (iC4), and 18 (hydroformylation-oxidation/dehydrogenationesterification) have the highest atom economies at 73.5% each.

Figure 2. Radial polygon diagrams showing VMR scores according to eq 1 for the top six MMA plans in Scheme 1. H

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sumption), the overall greenest routes according to their VMR scores via eq 23 are routes 5 (iC4), 6 (TBA), and 2 (C2/PA) as shown by the radial polygon diagrams given in Figure 4. A complete list of VMR scores is given in Table S1 and shown graphically in Figure S2 in Parts 4 and 5 of the Supporting Information. Our result that routes 5 and 6 are the greenest routes among the 18 plans considered is consistent with the Edwards−Lawrence inherent safety index (ISI) analysis based on simple chemical and process scores23 (see Table 5). The adjusted ISI scores presented here based on summing scores from all input materials in a given synthesis plan is more realistic than selective summing of only maximal values from the most offending chemicals as was done by Edwards and Lawrence. Though the Edwards−Lawrence analysis is based on an arbitrary penalty point scoring system with no mass weighting of scores and a limited number of parameters, it is satisfying that our analysis based on direct use of a wide range of parameter values without invoking assumptions is in good agreement for the top ranking plans. However, agreement in the ranking of the rest of the nine routes listed in Table 5 begins to break down (compare columns 4 and 7). This is typical of all kinds of ranking schemes. The same best performing plans tend to rise to the top of the list and poor performing ones tend to end up at the bottom regardless of the sophistication of the algorithms used to produce the ranking. Our algorithm is able to differentiate all plans without having any ties unlike the ISI analysis which is unable to distinguish routes 5/6 and 3/7 (adjusted ISI scores) and 5/6 and 3/8 (ISI scores). ISI analysis predicts that routes 1b and 2 are the worst of the nine listed; whereas, our algorithm suggests that route 1b ranks sixth out of 9, route 2 ranks third out of 9, and route 7 ranks last. Table 6 compares rankings of routes 1a, 2, 5, and 6 using a wider list of published methods that were applied to this limited set of plans.38−42 In this comparison there is generally better agreement between best and worst plans. Again, routes 5 and 6 rank highest and route 1a ranks lowest among this limited set of MMA synthesis plans. If we consider the first 8 plans in Scheme 1 as traditional routes to MMA, then among the remaining 10 alternative routes the next greenest routes that can compete with routes 5 and 6 are routes 13a/b (ACHhydration-dehydration), 14 (isobutane oxidation/dehydogenation-esterification), and 15 (propanoic acid-condensationesterification). The main drawbacks are the number of steps (routes 13a/b), a low yield of 4% for the isobutane oxidation and a high input energy demand (route 14), and toxicity issues with nickel catalysts particularly nickel tetracarbonyl (route 15).

Table 4. Summary of Energy Consumption Data for MMA Syntheses Shown in Scheme 1

plan route 1a (ACH) route 1b (ACH) route 2 (C2/PA) route 3 (C3) route 4 (C2/MP) route 5 (iC4) route 6 (TBA) route 7 (PA) route 8 (PP) route 9 route 10 route 11 route 12 route 13a Route 13b route 14 route 15 route 16 route 17 route 18 a

energy consumption to heat input materials Qtemp (kJ/mol MMA produced)

energy consumption to pressurize input materials Qpress (kJ/ mol MMA produced)

total energy consumption, Qplan (kJ/mol MMA produced)a

rank

948

0.4

948

10

1124

0.5

1124

11

505

5

144

1

1917

14

502 144 1850

−3 0.1 −67

551

0.1

551

7

645

0.1

645

8

228

−2

230

3

377

−61

438

4

147 698 1476 2782 3185 1897 5768 1911 3972 457 4943

−2 −16 66 5 1.2 0.6 0 −41 176 −67 −111

149 714 1542 2787 3186 1898 5768 1952 4148 524 5054

2 9 12 16 17 13 20 15 18 6 19

Total input energy consumption is given by Qplan = Qtemp + |Qpress|.

contributions for all plans; whereas, occupational exposure limits and skin dose risk potentials dominated the safety-hazard index contributions. Figure 2 shows plans with the top six VMR scores that incorporate both material efficiency and environmental-safety/hazard risk potentials. The most material efficient route 10 is not among these. Instead, the most favorable routes are in descending order 5 (iC4), 6 (TBA), 2 (C2/PA), 4 (C2/ MP), 8 (PP), and 13a (ACH-hydration-dehydration). Inclusion of Input Energy Consumption. Table 4 summarizes the energy input contributions from heating and pressuring input materials for all 18 MMA syntheses calculated as described in the Methodology section. Excel workbook spreadsheets summarizing these calculations for all routes is given in the Supporting Information (change in enthalpypressure contribution-MMA.xls, energy-input-analysisMMA.xls). Routes 3 (C3), 9 (multicomponent coupling of propyne, methanol, and carbon monoxide), and 7 (PA) are the top three least energy intensive routes; whereas, routes 16 (hydroformylation-oxidation-condensation-esterification), 14 (isobutane oxidation/dehydogenation-esterification), and 18 (hydroformylation-oxidation/dehydrogenation-esterification) are the most energy demanding. From Figure 3 we observe that route 14 has the highest Qtemp contribution (step 1, T = 420 °C) and route 16 has the highest Qpress contribution (step 1, p = 780 atm) arising from compression of gaseous ethylene, carbon monoxide, hydrogen, and liquid diethyl ether. When all three layers of metrics are taken into account (material efficiency, environmental-safety/hazard risk potentials, and energy con-



CONCLUDING REMARKS In this extensive metrics study of the test case of 18 industrial syntheses of MMA we conclude that the isobutylene and tbutanol routes have the greenest attributes with respect to material efficiency, environmental and safety-hazard impacts, and input energy consumption. The basis of this conclusion relies on comparison and ranking of the normalized VMR parameter that encompasses the following seven variables: overall atom economy, overall reaction yield, global reaction mass efficiency, (BI)w, (SHI)w, (SHI)in, and a newly defined energy input index. Each of these variables varies in value between 0 and 1 where unity corresponds to complete greenness within the limitations of variables selected in the present algorithm. The benign, safety-hazard, and energy input indices are mass weighted to reflect the fractional contribution of each input or waste material to the total mass of inputs or I

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Figure 3. Histogram showing temperature and pressure contributions to total energy input for production of 1 mol of MMA.

Figure 4. Radial polygon diagrams showing VMR scores according to eq 22 for the top six MMA plans in Scheme 1.

wastes produced in a synthesis plan. Accompanying uncertainties in the determination of the BI and SHI indices are also given. The energy input index uses the energy required to evaporate 1 mol of water as a benchmark for comparing the enthalpic energy consumption from all input materials in a

synthesis plan to produce 1 mol of target product. The methodology we have introduced relies only on the availability of necessary input data to determine the required metrics variables and does not rely on any arbitrary merit or penalty point system unlike previously reported inherent safety index J

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heat integration possibilities and cooling duties in the analysis may offset the present energy estimates in the opposite direction. Another limitation of the present methodology for energy consumption is that it is limited to a given process system boundary. The analysis could be expanded by including upstream energy demands for production of the input raw materials used in the synthesis pathways, particularly for high production volume chemicals. However, there will always be the problem of how far back upstream one should go in the synthesis network to begin such an extensive analysis. Any change in where to start the energy consumption analysis also impacts the analyses of material efficiency, environmental impact, and safety-hazard impacts, since all four analyses must start from the same set of input materials. Of course, direct experimental measurement of actual energy consumption for any given reaction is the most reliable method of estimating total energy consumption and would supersede the present algorithm. Therefore, it behoves researchers to disclose such determinations, along with a complete itemization of masses of all materials used, if they claim that their process to a given a target molecule is greener than prior published work.

Table 5. Summary of Edwards−Lawrence Inherent Safety Index (ISI) Analysis on MMA Syntheses23 plan

code

route 1a route 1b

ACH (a) ACH (b) C2/PA C3 C2/MP iC4 TBA PA PP

route route route route route route route

2 3 4 5 6 7 8

adjusted ISIa

rank

overall ISIb

rank

rank from this work

99 143

2 5

51 80

2 6

7 6

146 106 160 86 86 106 119

6 3 7 1 1 3 4

63 53 68 39 39 51 53

4 3 5 1 1 2 3

3 8 4 1 2 9 5

a

ISI calculated based on summing chemical and process scores for each input material used in synthesis plan. bISI calculated based on summing only maximal chemical and process scores for each reaction step in synthesis plan.

algorithms. In principle, the current set of parameters can be expanded to include any number of potential risk variables provided data exist. Hence, the algorithm is versatile in adapting to more complex analyses. In keeping with all of our past work on metrics analysis, our latest version continues to use simple visual diagrams, radial polygons, to highlight strengths and weaknesses of individual reaction and overall plan performance with a view to provide chemists and chemical engineers with a useful tool in their ongoing efforts for process optimization. The method also produces reliable ranking of plans particularly with respect to differentiating ones that fall in between the extremes of best and worst performers. The only limitation in implementing the present algorithm is the availability of reliable environmental impact, safety-hazard impact, and thermodynamic parameters. For first, second, and third generation feedstocks having simple chemical structures this will not be a problem due to readily available extensive compilations of experimental data, and therefore it is expected to produce reliable results. However, this will not be the case for complex intermediates as found in advanced pharmaceuticals, particularly with respect to obtaining experimental thermodynamic, environmental, and toxicity data. Computational estimates of thermodynamic parameters from chemical structures such as critical constants, boiling points, melting points, and heat capacities are possible to overcome any experimental gaps that arise and are described elsewhere.34,44 With respect to estimating input energy consumption from literature experimental procedures, the present investigation gives a rigorous protocol that uses fundamental thermodynamic principles for determining energy contributions from heating, cooling, and pressurizing operations. However, it must be pointed out that such results are to be interpreted as lower limit estimates since actual electricity consumption and intrinsic efficiencies of apparatuses used in any unit operation are not taken into account. On the other hand, inclusion of process



ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssuschemeng.5b01240. Part 1: Scheme S1. Reaction network for MMA. Part 2: Reference list for routes 1a to route 18 for the synthesis of MMA. Part 3: Figure S1. Determination of phase of input materials in a given chemical reaction. Part 4: Table S1. Summary of overall VMR performances for 18 routes to MMA. Part 5: Figure S2. Radial polygon diagrams showing VMR scores according to eq 22. Part 6: Derivation of eqs 14−21. Part 7: Example calculations using Redlich−Kwong equation of state and Tait equation for pressure contribution to ΔH. Part 8: Tosun equation for enthalpy change due to temperature and pressure contributions for gases. Excel spreadsheet of environmental and safety impact data: environmentalsafety-analysis-MMA.xls, missing-data.xls. Excel spreadsheet of thermodynamic data: materials-thermodynamicparameters.xls. Excel workbook spreadsheets of thermodynamic calculations: change in enthalpy-pressure contribution-MMA.xls, change in enthalpy-pressure contribution-template.xls, energy-input-analysisMMA.xls, Redlich-Kwong-EOS-template.xls (ZIP)



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

Table 6. Summary of Literature Ranking Comparisons for Four Common Routes to MMA route

Andraos

Edwards−Lawrence (ref23)

Heikkilä (ref38)

Palaniappan (ref39)

Khan−Amyotte (ref40)

Srinivasan− Meibao (ref41)

Srinivasan−Nhan (ref42)

Sugiyama (ref26)

1a (ACH) 2 (C2/PA) 5 (iC4) 6 (TBA)

4 3 1 2

4 3 2 1

4 3 1 1

4 3 2 1

4 3 2 1

4 1 3 2

4 2 3 1

4 2 1 3

K

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indices as a step towards a complete assessment of “greenness” for chemical reactions and synthesis plans. Org. Process Res. Dev. 2012, 16, 1482−1506. (21) Guinée, J. B., Ed. Handbook on Life Cycle Assessment; Kluwer Academic Publishers: Dordrecht, 2002. (22) Gronnow, M. J.; White, R. J.; Clark, J. H.; Macquarrie, D. J. Energy efficiency in chemical reactions: a comparative study of different reaction techniques. Org. Process Res. Dev. 2005, 9, 516−518. (23) Edwards, D. W.; Lawrence, D. Assessing the inherent safety of chemical process routes: is there a relation between plant costs and inherent safety? Process Safety Environ. Protection 1993, 71, 252−258. (24) Nagai, K. New developments in the production of methyl methacrylate. Appl. Catal., A 2001, 221, 367−377. (25) Gadawar, S. B.; Schembecker, G.; Doherty, M. F. Rapid Process Design. Chem. Eng. Prog. 2006, September, 22−32. (26) Sugiyama, H.; Fischer, U.; Hungerbühler, K.; Hirao, M. Decision framework for chemical process design including different stages of environmental, health, and safety assessment. AIChE J. 2008, 54, 1037−1053. (27) Banimostafa, A.; Papadokonstantakis, S.; Hungerbühler, K. Evaluation of EHS hazard and sustainability metrics during early process design stages using principal component analysis. Process Saf. Environ. Prot. 2012, 90, 8−26. (28) Andraos, J.; Hent, A. Simplified application of material efficiency green metrics to synthesis plans−pedagogical case studies selected from Organic Syntheses. J. Chem. Educ. 2015, 92, 1820. (29) Andraos, J. A database tool for process chemists and chemical engineers to gauge the material and synthetic efficiencies of synthesis plans to industrially important target molecules. Pure Appl. Chem. 2011, 83, 1361−1378. (30) Smith, J. M., van Hess, H. C. Introduction to Chemical Engineering Thermodynamics; McGraw-Hill Book Co.: New York, 1987; pp 166−173. (31) Design Institute for Physical Property Data (DIPPR) Project 801. http://www.aiche.org/dippr/projects/801 (accessed February 2015). (32) Yaws, C. L. Chemical Properties Handbook; McGraw Hill: New York, 1999. (33) Redlich, O.; Kwong, J. N. S. On the thermodynamics of solutions. V. Chem. Rev. 1949, 44, 233−244. (34) Danner, R. P., Daubert, T. E. Manual for Predicting Chemical Process Design Data−Data Prediction Manual; American Institute of Chemical Engineers: New York, 1988. (35) Dymond, J. H.; Malhotra, R. The Tait equation: 100 years on. Int. J. Thermophys. 1988, 9, 941−951. (36) Mann, U. Principles of Chemical Reactor Analysis and Design, 2nd ed.; Wiley: New York, 2009; p 133. (37) Tosun, I. The Thermodynamics of Phase and Reaction Equilibria; Elsevier: Amsterdam, 2013; Chapter 3. (38) Heikkilä, A. M.; Hurme, M.; Jär veläi nen, M. Safety considerations in process synthesis. Comput. Chem. Eng. 1996, 20 (Supp A), S115−S120. (39) Palaniappan, C.; Srinivasan, R.; Tan, R. Selection of inherently safer process routes: a case study. Chem. Eng. Process. 2004, 43, 641− 647. (40) Khan, F. I.; Amyotte, P. R. Integrated inherent safety index (I2SI): a tool for inherent safety evaluation. Process Saf. Prog. 2004, 23, 136−148. (41) Srinivasan, R.; Meibao, X. Technical Report: iSafe index for methyl methacrylate process; National University of Singapore, 2003. (42) Srinivasan, R.; Nhan, N. T. A statistical approach for evaluating inherent benign-ness of chemical process routes in early design stages. Process Saf. Environ. Prot. 2008, 86, 163−174. (43) Andraos, J.; Ballerini, E.; Vaccaro, L. A comparative approach to the most sustainable for the β-azidation of α,β-unsaturated ketones and acids. Green Chem. 2015, 17, 913−925. (44) Poling, B. E.; Thomson, G. H.; Friend, D. G.; Rowley, R. L.; Wilding, W. V. Perry’s Chemical Engineers’ Handbook, 8th ed.; McGraw-Hill: New York, 2008; Section 2, pp 463−517.

REFERENCES

(1) Eissen, M.; Metzger, J. O. Environmental Performance Metrics for Daily Use in Synthetic Chemistry. Chem. - Eur. J. 2002, 8, 3580− 3585. (2) Andraos, J. Unification of Reaction Metrics for Green Chemistry: Applications to Reaction Analysis. Org. Process Res. Dev. 2005, 9, 149− 163. (3) Andraos, J.; Sayed, M. On the Use of ‘Green’ Metrics in the Undergraduate Organic Chemistry Lecture and Laboratory to Assess the Mass Efficiency of Organic Reactions. J. Chem. Educ. 2007, 84, 1004−1010. (4) Augé, J. A new rationale of reaction metrics for green chemistry. Mathematical expression of the environmental impact factor of chemical processes. Green Chem. 2008, 10, 225−231. (5) Lapkin, A., Constable, D. C., Eds. Green Chemistry Metrics: Measuring and Monitoring Sustainable Processes; Blackwell Scientific: Oxford, 2008. (6) Calvo-Flores, F. G. Sustainable chemistry metrics. ChemSusChem 2009, 2, 905−919. (7) Andraos, J. The Algebra of Organic Synthesis: Green Metrics, Design Strategy, Route Selection, and Optimization; CRC Press: Boca Raton, 2012. (8) Dicks, A. P., Hent, A. Green Chemistry Metrics−a guide to determining and evaluating process greenness; Springer: New York, 2014. (9) Roschangar, F.; Sheldon, R.; Senanayake, C. H. Overcoming barriers to green chemistry in the pharmaceutical industry − the Green Aspiration Level concept. Green Chem. 2015, 17, 752−768. (10) Trost, B. M. The Atom Economy − A Search for Synthetic Efficiency. Science 1991, 254, 1471−1477. (11) Constable, D. J. C.; Curzons, A. D.; Freitas dos Santos, L. M.; Geen, G. R.; Hannah, R. E.; Hayler, J. D.; Kitteringham, J.; McGuire, M. A.; Richardson, J. E.; Smith, P.; Webb, R. L.; Yu, M. Green Chemistry Measures for Process Research and Development. Green Chem. 2001, 3, 7−9. (12) Curzons, A. D.; Constable, D. J. C.; Mortimer, D. N.; Cunningham, V. L. So You Think Your Process is Green, How Do You Know? − Using Principles of Sustainability to Determine What is Green − A Corporate Perspective. Green Chem. 2001, 3, 1−6. (13) Constable, D. J. C.; Curzons, A. D.; Cunningham, V. L. Metrics to ‘Green’ Chemistry − Which Are the Best? Green Chem. 2002, 4, 521−527. (14) Sheldon, R. A. Consider the Environmental Quotient. ChemTech 1994, 24 (3), 38−47. (15) Jiménez-González, C.; Ponder, C. S.; Broxterman, Q. B.; Manley, J. B. Using the right green yardstick: why process mass intensity is used in the pharmaceutical industry to drive more sustainable processes. Org. Process Res. Dev. 2011, 15, 912−917. (16) Jiménez-González, C.; Poechlauer, P.; Broxterman, Q. B.; Yang, B. S.; am Ende, D.; Baird, J.; Bertsch, C.; Hannah, R. E.; Dell’Orco, P.; Noorman, H.; Yee, S.; Reintjens, R.; Wells, A.; Massonneau, V.; Manley, J. Key Green Engineering Research Areas for Sustainable Manufacturing: A Perspective from Pharmaceutical and Fine Chemicals Manufacturers. Org. Process Res. Dev. 2011, 15, 900−911. (17) Andraos, J. Global green chemistry metrics analysis algorithm and spreadsheets: evaluation of the material efficiency performances of synthesis plans for oseltamivir phosphate (Tamiflu) as a test case. Org. Process Res. Dev. 2009, 13, 161−185. (18) Werner, L.; Machara, A.; Sullivan, B.; Carrera, I.; Moser, M.; Adams, D. R.; Hudlicky, T.; Andraos, J. Several Generations of Chemoenzymatic Synthesis of Oseltamivir (Tamiflu): Evolution of Strategy, Quest for a Process-Quality Synthesis, and Evaluation of Efficiency Metrics. J. Org. Chem. 2011, 76, 10050−10067. (19) Andraos, J. Application of Green Metrics to Scalable Industrial Synthesis Plans: An Update on Syntheses of Oseltamivir Phosphate (Tamiflu). In Scalable Green Chemistry: Case Studies from the Pharmaceutical Industry; Koenig, S.G., Ed.; Pan Stanford Publishing: 2013, Chapter 4, pp 75−104. (20) Andraos, J. Inclusion of environmental impact parameters in radial pentagon material efficiency metrics analysis: using benign L

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