FINAL REPORT FOR THE PROCESS DESIGN AND TECHNOECONOMIC ANALYSIS FOR THE DOWNSTREAM RECOVERY AND PURIFICATION OF DIETHYL MALONATE

04/28/2016

Team 7Chris BilhamBrian CoventryMark KelsicYekaterina PokhilchukDan Sriratanasathavor

Sponsor:Matthew Lipscomb, PhD.CEO & Founder DMC Limited

Table of Contents

Executive Summary……………………………………………………………………………….….….2Project Statement……………………………………………………………………………………..….3Project Context…………………………………………………………………………………………....3Project Scope…………………………………………………………………………………………......3Preliminary List of Specifications…………………………………………………………………….….4Results and Conclusions………………………………………………………………………………...4

Experimental Results……………………………………………………………………………4Sensitivity Analysis Results……........................................................................................5Economic Analysis………………………………………..……………………………………11

Discussion of Results…………………………………………………………………………………...12Methods……....................................................................................................................12Economic Analysis……...................................................................................................14Environmental and Waste Analysis………………………….……….................................15

Next Steps ………………………………………………………………………………………………18References……………………………………………………………………………………………….19Appendix…………………………………………………………………………………………………21 Appendix 1………………………………………………………………………………………21 Appendix 2………………………………………………………………………………………21 Appendix 3………………………………………………………………………………………21 Appendix 4………………………………………………………………………………………22 Appendix 5………………………………………………………………………………………24

Appendix 6……………………………………………………………………………………....24Appendix 7……………………………………………………………………………………....28Appendix 8……………………………………………………………………………………....30Appendix 9………………………………………………………………………………………32

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Executive Summary

Diethyl Malonate (DEM), a chemical used in an array of manufacturing processes, is currently being produced in a non-sustainable, environmentally harmful process. DMC Limited, a Colorado based biotech startup company, has engineered a microbe that produces DEM without any bi-products. Not only does the fermentation process ameliorate the environmental impact of production, but it does so at a reduced cost making it an attractive approach.

This project focused on the recovery of DEM from a cell free broth containing water and trace salts. Two process models were developed that were connected in series to give three separate methods of recovery.

Experimental data was produced to supplement the subsequent models. This was done by determining the pH effect on the solubility of DEM in water and the partition coefficient of DEM in water-pentane systems. It was found that pH has a strong nonlinear effect, and decreasing pH significantly decreases solubility, with a pH of approximately 4 causing DEM to only be 40% as soluble compared to a neutral solution. The partition coefficient was found to be 2.4 ± 0.2 at a 95% confidence interval.

The first method investigated was simple decantation of the feed stream which achieved 94.76% DEM recovery at a unit cost of $0.142/kg DEM considering only chemical and utility costs. The second method investigated with Liquid-Liquid Extraction (LLE) using n-pentane which achieved 99.96% DEM recovery at a unit cost of $0.016/kg DEM. The third method which used the LLE to process the waste from the decanter (Series Process) achieved 99.95% DEM recovery at a unit cost of $0.011/kg DEM. The three process were optimized to find the most economical operating conditions and it was determined that the process variable that had the greatest impact on operating costs was the LLE Solvent to Feed Ratio, as it decides the balance between DEM loss and high distillation costs. Of special note is that the LLE only process is most economical when it produces 99.99% DEM product while the other two processes are most economical at 99.00% DEM product.

Capital expenditures (CAPEX) for decanting, LLE and the series process are $3,730,123.00, $1,106,229.22, and $3,730,123.00, respectively. Operational expenditure (OPEX) with full consideration for feed cost and waste disposal for the decanting, LLE and series process in $/kg product are 2.764, 2.631 and 2.626 respectively. For the same processes but only considering operational costs, the OPEX in $/kg product becomes 0.143, 0.0162 and 0.0117 respectively.

It was determined with absolute confidence that the decanting only process is simply not competitive with either the series or LLE processes. Additionally, our initial findings suggests LLE to have an edge over the series process due to its 3.2 million USD reduction in capital costs, leading to a faster return on investment. However, further economic analysis will be

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needed to safely rule out the series process from contention and is outlined in detail throughout this report.

Project Goal

Two methods for purification of diethyl malonate (DEM) from a fermentation reactor are to be designed and economically analyzed.

Project Context

Diethyl Malonate (DEM) is a common intermediate used in the synthesis of pharmaceuticals, fragrances, dyes and adhesives, and it has an annual market value of $200 million (Lipscomb, 2016). One of many chemicals derived from malonic acid, DEM is the preferred form, due to its relative stability (Lipscomb et al.). Malonic acid is synthesized using noxious chemicals such as sodium cyanide, sodium hydroxide and chloroacetic acid. Malonic acid is esterified in the presence of sulphuric acid and ethanol to form the chemically stable malonate DEM (Britton and Erza 1942, ChemicalBook 2016). This non-sustainable multi-step process is environmentally recalcitrant and alternative methods are beginning to be investigated. Malonic acid is on NREL’s Top 30 list of Value Added Chemicals from Biomass, encouraging research into alternative production methods (Werpy and Petersen 2004, Dietrich, Fortman and Steen 2015). An engineered microbe created by DMC Limited has been created to environmentally and economically mitigate the drawbacks of the traditional production method of DEM.In the fed batch fermentation process, the microbe, a sugar feedstock, trace metals, and salts are combined to amplify the microbe concentration and facilitate DEM production. The microbe generates DEM exclusively, without any byproducts.Two processes for the downstream separation and purification of DEM are being evaluated to annually yield 10,000,000 kg of DEM, with purity greater than 99%. An economic sensitivity analysis of critical parameters and their effect on capital expenditure (CAPEX) and operational expenditure (OPEX) will be presented, followed by an assessment of their environmental impact. Project Scope

Deliverables:Two types of purification processes that are fundamentally different and economically viable.Each process should include:

1. A basic flow diagram2. A detailed process flow diagram that identifies the specific unit operations to be

implemented with complete material and energy balances3. A project description and scope, complete with background, safety, environmental, and

health information4. A detailed literature and patent review for similar processes

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5. A listing of the project premises used and a description of the approach used to figure out the process

6. A sensitivity analysis exploring the range of critical process parameters that may have an impact on the Capital Expenditure (CAPEX) or Operational Expenditure (OPEX) of the unit operation

7. A description of the process and equipment specifications (design, materials of construction, etc)

8. A heating and cooling utility estimate for the proposed unit operations design

9. A complete appendix with all equipment design, utility estimates, and economic evaluation calculations summarized in detail

10. A preliminary Process Safety Assessment using HAZOPS or a similar method to identify and mitigate process hazards.

11. A preliminary Environmental Sustainability Assessment using the method of Heinzle or a comparable method.

12. A preliminary Economic Assessment using one or more of the methods and metrics from Seider that includes investment and costing

Boundary condition: An aqueous stream free of biomass is fed into the process, and product, as well as waste stream, exit.

Upstream of the design project is a fermenter outputting an aqueous stream free of biomass, at standard temperature and pressure (STP). The product and waste streams leave the purification process at STP. The scope of this project is focused exclusively on the purification process from an input stream to output streams and a new plant will be constructed for the process. Preliminary list of Specifications for project

1. DEM with a purity of >99% is to be produced2. The plant designs should produce 10,000 tonnes of DEM per year3. Two different and unique separation methods

Results and Conclusions

Experimental Results

The first experimental result of value is the pH effect on the solubility of DEM in water. The experiment was run at 22 °C and it assumed that the pH effect is independent of temperature. Since the method was done via titration and visual identification of phase separation, absolute solubility was overestimated, however a relative solubility at a neutral pH was viable. The relative solubility was calculated by dividing the titrated concentration at a given pH, by the titrated concentration at a neutral pH. These results are given below in Figure 1.

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Figure 1: Relative solubility of DEM in water at varying pHs, relative to neutral pH

As seen in Figure 1, decreasing the pH also decreases the solubility of DEM in water. This effect was found to be nonlinear, indicated by an R-Squared value of 0.998 of the fitted quadratic equation. Although the terms of the fitted quadratic equation are not known, it provides an empirical estimate to solubility.

The next parameter of investigation was the partition coefficient of DEM in a water-pentane systems. This was done using Ultraviolet-Visible (UV-VIS) spectroscopy to quantify DEM in the organic n-pentane and aqueous phases from liquid-liquid extractions. Quantification was done with a Cary 5000 UV-VIS spectrometer, a quartz cell with a 1 cm path length, baseline correction and a scanning interval of 0.5 nm using a slit width of 1 nm. Although the instrumentation operated with extreme precision (less than 1% error), n-pentane’s high volatility caused issues with sampling in the organic phase. The aqueous phase, which lacked volatility issues, provided for excellent experimental repeatability and ultimately produced a partition coefficient at a 95% confidence interval to be 2.6 ± 0.2. Calibration curves, along with tabulated results are available in Appendix 6.

Sensitivity Analysis Results

The goal of this project was to assess the economic viability of the recovery of DEM. The chemical process will be most economical when the unit operating cost has been minimized and this was the goal of the sensitivity analysis. The following 9 parameters were investigated:

1. DEM production cost ($/kg)2. DEM feed concentration 3. LLE solvent to feed ratio4. LLE number of theoretical stages5. Price of n-pentane6. Product DEM purity7. Decanter pH

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8. Decanter temperature9. LLE temperature

The results of LLE temperature analysis will not be shown. An assumption was made that the partition coefficient K for DEM-water-pentane did not vary with temperature, which dictates that the most economical way to run the process would be to not specify a temperature for the LLE. Specifying a temperature would require utilities which would only increase operational costs without improving yield.

Sensitivity to Feed Price and Feed Composition

Figure 2: Effect of feed price and feed composition on DEM unit operating cost for process run at optimal conditions. The dotted line represents the high production price ($3.10/kg DEM) and the solid line represents the low production price ($1.90/kg DEM). Figure 2B represents a zoomed view of Figure 2A.

Figure 2 shows the effect of feed price and feed composition on the DEM unit operating cost for the process run at optimal conditions. The figure shows that as the feed price of the DEM increases, the unit operating cost increases as well. This is because the process is not 100% efficient and losing DEM was seen as an operational cost. Similar amounts of DEM were lost at both production prices, but the increased value of the fed DEM resulted in a larger value of lost DEM.

Figure 2 also shows that as the feed broth concentration of DEM increased, the unit operating cost decreased. This result can be explained by the thermodynamics of separation. The first kilogram of DEM is easy to separate from water, but the last kilogram of DEM is exceptionally difficult to remove. At higher feed concentrations, more of the DEM is separated before the difficulty and price of separation increases.

Sensitivity to Solvent to Feed Ratio

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Figure 3: Effect of solvent to feed ratio and number of theoretical stages on unit operating cost for LLE-Only process at low and high production prices. Figure 3A shows the low DEM production price while Figure 3B shows the high DEM production price.

Figure 3 shows the effect of the solvent to feed ratio on the unit operating cost for the LLE-Only process. The optimization of this variable is critical because it is the parameter with the largest effect on operating cost that can be varied within the project scope. The solvent to feed ratio represents the ratio between the n-pentane solvent and the water fed to the LLE unit with larger values indicating more n-pentane. Although the total flow rate (DEM + water) may be easier to measure in a plant, this model used the water flow rate because that was the form used in the reference (Seader, Henley, & Roper, 2011).

Figure 3 shows that at both of the production prices, the optimal solvent to feed ratio with 12 stages is 0.6 kg n-pentane/kg water. As the solvent to feed ratio is increased from this point, the high cost of distillation begins to outweigh the benefits of increased DEM recovery. Meanwhile, as the ratio is decreased, the high cost of losing DEM begins to overshadow the distillation costs.

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Figure 4: Effect of solvent to feed ratio and number of theoretical stages on unit operating cost for Series Process at low and high production prices. Figure 4A shows the low DEM production price while Figure 4B shows the high DEM production price.

Figure 4 shows the effect of the solvent to feed ratio on the unit operating cost of the Series Process. This figure shows that for a 12 stage LLE column, a solvent to feed ratio of 0.5 is most ideal. While the selection of the ratio is important for the Series Process, it is not as critical as it is for the LLE-Only process. About 94% of the DEM for the Series Process is handled by the decanter. This means that the graphs do not rise as sharply at low solvent to feed ratios because the recovery of the LLE unit only represents the final 6% of recovery.

Sensitivity to Number of Theoretical Stages

Figure 5: Effect of number of theoretical stages and feed production price on the Only LLE and Series Processes. The dotted line represents the high production price ($3.10/kg DEM) and the solid line represents the low production price ($1.90/kg DEM).

Figure 5 shows the effect of the number of theoretical stages on the unit operating cost of producing DEM. Increasing the number of theoretical stages allows for a smaller solvent to feed ratio to be used, because there is more time for the solvent to contact the feed. While it may

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seem logical to use as many stages as possible, number of theoretical stages translates directly to column height. More stages means a taller column with more packing. This represents a tradeoff between capital costs and operating costs which will need to be evaluated in the scope of the entire plant.

Sensitivity to Product Purity and N-Pentane Price

Figure 6: Effect of product purity and n-pentane price on unit operating costs at $2.50 DEM production price. Each line represents an n-pentane purchase price. Figure 6A shows the results for the Series Process while Figure 6B shows the results for the LLE-Only process with purity plotted on a log scale.

Figure 6 shows the effect of product purity and n-pentane price on the unit operating costs. In this rather unusual situation, unit operating costs actually decrease as product purity is increased beyond 99%. The purchase price of $1500/tonne was determined to be the current market value for n-pentane and will be used for discussion (ICIS). The unusual behavior seen here can be explained by the fact that, the only impurity in the LLE product is n-pentane. At 99% DEM purity from the LLE, 1% of the LLE product is n-pentane. This accounts for 5 and 100 tonnes of lost n-pentane per year for the Series and LLE-Only processes, respectfully.

For the LLE-Only process shown in Figure 6B, the product purity has a large effect on the unit operating cost as the unit operating costs decreases by $0.14/kg when the product purity is increased from 99% to 99.9988%, which is the value that minimizes costs. Although it was not accounted for in the model, this increased product purity will most likely yield a higher market value.

The Series Process shown in Figure 6A does not see as great of a benefit from increased product purity as the unit operating cost only decreases by $0.0004/kg when the product purity is increased from 99% to 99.82%, which is the value that minimizes costs. The effect is smaller than the LLE-Only process because only 6% of the DEM goes to the LLE in the Series Process, leading to a lower n-pentane loss. In addition, the final product purity will not actually increase as 94% of the product comes from the evaporator at 99.0%.

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Effect of Decanter Temperature and pH

Figure 7: Effect of decanter temperature on pH for the Series Process (Figure 7A) and the Decanter Only process (Figure 7B) at $2.50/kg DEM production price.

Figure 7 shows the effect of decanter temperature and pH on the Series Process and the LLE Process. For both processes, the goal of the decanter is to send as much DEM to the evaporator as possible. For the Series Process, the evaporator has a lower operating cost per kilogram DEM product, so money can be saved by utilizing it rather than the LLE process. For the Decanter Only process, the DEM not sent to the evaporator is simply sent to waste.

Increasing the temperature decreases the solubility of DEM in water. This can be seen in Figure 7B, where the minimum operating cost is at 43°C which corresponds with the point of minimum DEM solubility in water. Although this effect is still present in the series process, Figure 7A shows that the cost of heating the feed outweighs the preference of sending DEM to the evaporator.

Decreasing the pH also decreases the solubility of DEM in water. The costs, of HCl to acidify and NaOH neutralize, were small in comparison to the operating cost, thus acidifying the feed was able to improve the operating cost for both processes. The experimental pH data ended at pH 3.92, but further improvements to operating cost may be found at lower pHs.

Operating Cost Breakdown

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Figure 8: Operating cost breakdown for Series Process (A), Decant Only (B), and LLE Only (C) all run at optimal conditions with a DEM feed production price of $2.50/kg.

Figure 8 shows the operating cost breakdown for the three process models. As can be seen, for the Series Process and LLE Only, the distillation column represents the largest operating cost while for the Decant Only process, losing DEM is the largest operating cost.

Economic Analysis

An economic analysis was performed based upon the results of the process sensitivity analysis. For results presented in this report, the parameters used were: 2.5 $/kg feed price, 40% flat tax rate, and a 10 year linear 10% depreciation rate. The flat tax and 10 year 10% depreciation was suggested from Seiders 2011. A variety of operational costs were calculated with variations of inclusion of waste disposal and feed costs. Additionally, breakeven sell prices were calculated for each variation with a 14 year and 5 year return. It was assumed that there would be no production during the first year as construction takes place, and half production the following year as systems are brought online and tuned. Capital costs included purchase costs and installation costs; these were estimated from a combination of literature, Aspen and SuperPro outputs. Utility costs were examined and taken from the sensitivity analysis. It should be noted that some of the omitted costs that could be substantial are maintenance, labor, piping/wiring/instrumentation and other variable capital costs. Finally the number of years for the lowest operation costs to dominate the revenue stream were compared to initial capital investment. The results of this economic analysis is provided below in Table 1.

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Table 1: Summary of Economic Analysis

An important feature to note from Table 1 is that although the series process has the lowest operation cost, its high capital costs cause LLE to be the preferred method. This is not surprising, as the difference in capital costs between LLE and series is approximately 3.2 million USD, while the annual savings in operation is only approximately 50 thousand USD, accounting for only 1.6% of the capital cost. To further illustrate this difference, the amount of time needed for these operational savings to dominate the revenue stream between the series and the LLE is approximately 40 years in all cases. Ultimately, decanting alone was simply not a viable option and did not economically compete with either the series or LLE. The conclusion of this analysis was to proceed with the LLE-Only process.

Discussion of Results

MethodsSolvent Selection

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The solvent for the LLE model was picked using a combination of Aspen’s LLE model, Aspen’s boiling points, and Sigma Aldrich’s online purchase prices. The results of the analysis can be seen in Appendix 3.

Aspen’s LLE model was used to produce the separation factor for each solvent-DEM-water system. These separation factors were not used in the model, but were rather used to screen for impractical solvents. While the team rejected the use of Aspen’s LLE model for the project, the use of the model for solvent selection was deemed acceptable. In addition, the boiling points provided by Aspen were considered to be correct.

The prices obtained from Sigma Aldrich must be questioned because they were obtained on a laboratory scale. n-Pentane was the cheapest solvent found with this method. Although its price on Sigma Aldrich was 4 times higher than the bulk price (ICIS), its boiling point of 36°C gives it a major advantage over other solvents.

Experimentation

The limitations of the experimental data were minor and the results had very low errors. Improvement of the experimental would consist of replicates for the relative solubility to determine a more confident value and agreement from the n- pentane LLE data would do potentially requires an accuracy check. Experimentation into the effect of salt concentration on the solubility of DEM in water should be done, as it most likely will decrease solubility in a manner similar to the pH effect. Since NaCl is a cost effective, non-hazardous, environmentally friendly and non-problematic to our process it could possibly be a inexpensive method for further increasing natural phase separation. Salting the solution could further drive down operational costs and increase recovery for the series and decanting processes, possibly changing the ultimate economic analysis and decision making.

Aspen Plus Process Model

The Aspen Plus process model can be broken down into 5 major stainless steel unit operations, that will be discussed independently. These unit operations are the: decanter, evaporator, LLE column, distillation column, and heat exchangers.

Decanter

The decanter is the source of the first major assumption in the model: salts stay in the aqueous phase and do not affect equilibrium. Although it is safe to assume the salts reside in the aqueous phase, it is plausible that the salts will have an effect on equilibrium. However, the salt's effect on equilibrium will most likely be akin to that of lowering the pH, thus increasing yield and lowering operational costs.

Evaporator

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The evaporator uses Aspen’s Vapor Liquid Equilibrium (VLE) data to perform a flash calculation on the DEM-rich stream leaving the decanter. Aspen’s VLE system was trusted by the team, however, the temperature at which the evaporator must be operated may change if salts entrain into the evaporator. When sizing the evaporator, it was noted that the evaporator in this process had a very small heat duty compared to evaporators on the market. This led the team to realize that a heat exchanger paired with a flash drum may be a better option than an evaporator.

LLE Column

The LLE column uses the same assumption as the decanter: the salts stay in the aqueous phase and do not affect equilibrium. Like the decanter, the effect of the salts on equilibrium will mostly likely force more DEM into the n-pentane solvent.

Another assumption made by the LLE column is that the column performs at 100% efficiency. Stated another way, this means that the number of real stages is equal to the number of theoretical stages. While this may be true in a perfectly designed column, a real column will most likely need to be bigger than the one specified.

Distillation Column

The distillation column uses Aspen’s VLE data to separate n-pentane from DEM. Since this unit is the largest source of operational costs, its functionality needs to be scrutinized. With boiling points of 199°C and 36°C, the separation of DEM from n-pentane should be relatively straightforward. This is apparent in the LLE process where the column only required a reflux ratio of 0.14 to achieve a bottoms purity of 99.99% DEM. The low reflux ratio indicates that Aspen is using the near-lowest energy for separation and the team feels confident in the distillation column results.

Heat Exchangers

The Series Process and the LLE-Only process each contain one heat exchanger to cool the product down to room temperature. The Decant Only process contains this heat exchanger in addition to a heat exchanger used to heat the feed before decanting. Aspen assumed 100% efficiency for these heat exchangers, thus actual utility costs may be slightly higher.

Economic Analysis

There is a high degree of confidence for the parameters and method used in the first pass economic analysis. With this said, the economic analysis could be improved by including a wider array of parameters such as: labor, maintenance, piping/instrumentation/wiring, land cost and permits. Still the model provides a good first pass estimate, as many of these costs including unnamed ones are dependent on many unknown factors, such as location, final sizing and varying market factors. Although the economics of such a process are constantly evolving, some additional recommendations, aside from the above mentioned, can be made.

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First, large capital costs were incurred in the mixing tanks for the decanter-evaporator recycle stream along with the HCl and NaOH tanks and subsequent mixing tanks for stream inclusion. These tanks were modeled as agitated tanks in Superpro and the sizing done based upon a literature recommendation stating that, in order to guarantee adequate mixing the residence time and tank volume should be 10 times the flow rate (Seider, 2009). This recommendation is inclusive of solid mixing. For this reason it is likely that, for this process, the tanks and mixers could be downsized or substituted completely, greatly reducing the capital cost and potentially making the series process more competitive. It is unlikely though that the decanting process will ever be competitively efficient on its own, as the cost of lost DEM is too high. As mentioned before, investigating salting effects is absolutely warranted as it is a cheap way to increase phase separation, again making the series process more competitive. Finally a major assumption, that could increase the operational costs of the LLE process, is: there is no n-pentane fouling and the solvent, aside from that lost in the product stream, was completely recovered. The validity of this assumption can only be experimentally determined, and because LLE is significantly more reliant upon the LLE-Distillation as the workhorse than the series, which recovers 94% of the DEM in the decanter-evaporator and has a much smaller LLE-Distillation workload, making the series process more competitive. Finally, more accurate depreciation and more detailed tax models could be produced, along with waste disposal based on production plant location.

To conclude, the first pass economic analysis is presented with confidence, especially in its ability to remove decanting-only as a process consideration. However, LLE and series methods should be further investigated as recommended above to comprehensively ascertain the most effective model.

Environmental and Waste Analysis

The United States Environmental Protection Agency (EPA) provides a list of characteristics of hazardous waste. Chemicals that have not been specifically listed may still be considered hazardous if they exhibit one of four characteristics: ignitability, corrosivity, reactivity and toxicity. Ignitable waste is defined as being able to create fires under certain conditions, spontaneously combust, or have a flash point less than 60 °C. Corrosive wastes are acids or bases that are capable of corroding a metal container and typically have a pH less than or equal to 2 or greater than or equal to 12.5 (CHW, 2012) Reactive waste is unstable under normal condition and can cause explosion, or release toxic fumes, gases or vapors when heated, compressed, or mixed with water. Toxic waste is defined as harmful when ingested or absorbed (CoFR, 2012). Even though none of the compounds in the product or waste stream have a characteristic of a hazardous waste, the waste stream needs to meet certain specification before going to a city’s publicly owned treatment works (POTW). The specific pollutant limitations and maximum concentrations in the discharge wastewater for the city of Boulder can be found in Appendix 4. Various regions have different regulations. For example, in Boulder the pH of the wastewater must be between 5.5 and 10.5. This means that for the LLE process, the wastewater, which

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may be at a pH as low as 4 if pH-dependent precipitation is used, must be treated before discharged to the POTW. The industrial wastewater permit cost $7,046 annually and the disposal of the waster cost $70 per 1000 gallons.

Hazard and Operability Study (HAZOPS)

A HAZOPS is a systematic examination of a process to identify and evaluate problems that may occur. The HAZOPS technique is qualitative, and aims to stimulate the imagination of participants to identify the potential hazards. The two categories in HAZOPS are severity and likelihood of the hazard. The degree of severity of hazard is rated from 1 to 4 where 1 is high severity (fatality or serious injury) and 4 is low severity (no injury from hazard). The same rating also applied to the likelihood where 1 is highly likely (hazard expected more than once per year) and 4 is low likelihood (hazard not expected at all in the plant life). The potential hazard needs to be mitigated if (severity) x (likelihood) < 7 or the severity = 1. For this process, the HAZOPS scope is solely the acidification at the mixer, using 12M HCl as seen in Figure 9. Table 2 shows the severity and likelihood of a safety accident around the mixer.

Table 2: Effects of Deviation

Figure 9: Potentially hazardous mixer

To mitigate the potential hazard from excess HCl in the mixer, level control will be implemented to decrease the likelihood of overflow. This can be seen in Figure 9. Additionally, running a vent line to the drain can be instilled to decrease the severity or failure.

Environmental Sustainability Assessment

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The purpose of an environmental assessment is to identify materials or process steps that cause the greatest environmental burden. This will help reduce the environmental burden and create a cleaner and more sustainable process. Using the Environmental Assessment method of Heinzel, Biwer, and Cooney’s Development of Sustainable BioProcesses: Modeling and Assessment an overall Environmental Index can be calculated. First, each component is assigned a mass index (MI) equal to its mass per mass of product produced. This will be multiplied by the environmental factor (EF) to get a final value for the environmental index (EI)This environmental assessment method has 15 impact categories. In each category, components are allocated to class A, B, or C, with A representing highly harmful, B moderately harmful, and C minimally harmful. The highest impact rating of each component is selected as its final rating. An EF is calculated by averaging the components impact rating, allocating 1, 0.3, and 0 to A, B, and C respectively. Figure 10 shows the MI and EI for each component and Table 3 shows the environmental assessment results.

Figure 10: Environmental Index (blue) and Mass Index (orange) for each component in the purification process

Table 3: Environmental assessment results for the purification process

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With the exception of n-pentane, the process has a very minimal environmental impact with B and C ratings. The pentane is present at such low concentrations that it has a very little effect. Further, it is recycled in the LLE process and is only removed from the process as an impurity in the final product. Note that the ammonium sulfate has the largest MI and EI values due to its abundance, being the third most abundant compound in the feed.

Next Steps

Experimental data should be continuously collected, especially with respect to pH and salt effects on solubility of DEM in water. It might be worthwhile to run an independent test of the partition coefficient simply for redundancy. Additional experimental trials should be run in the context of supporting the process development of a pilot plant. This will be discussed subsequently.

The process model contained several aspects that warrant further investigation. The LLE-distillation cycle needs to be evaluated in a pilot plant. While the separation of n-pentane from DEM is thermodynamically easy, operating the distillation column still represents the largest operational cost. What complicates the system is that the distillation costs can be lowered by decreasing the n-pentane flow rate, but this in-turn requires a larger LLE column. The three-way and multi-dimensional interaction between the n-pentane flow rate, the recovery of DEM, and the LLE column price must be optimized in a pilot plant with correct prices for all variables.

If decanting is to be considered in the final process, the effects of salts and pH need to be investigated further. The laboratory data stopped at pH 3.92, but the model indicated that the process would continue to decrease in operating costs as the pH is lowered further. The danger here is that at too low of a pH, the DEM will begin to breakdown. Additionally, it is predicted that the addition of salts would also decrease operating costs. These are scenarios too complex for Aspen and can only be evaluated in a pilot plant or lab.

Finally economic models should be continued to be developed and refined as outlined in the discussion of results. This would be done in tandem with the development of a pilot plant, as models are improved and specific units specified the economic model can be made considerably more accurate. Also further modifications based upon location, plant footprint, labor and other miscellaneous costs will need basis from further experimentation and implication, again most likely coming from a pilot plant.

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Lipscomb, M. (January, 2016). Process For Recovery of Diethyl Malonate. DMC Limited. Boulder, Colorado

National Center for Biotechnology Information (NCBI 2). PubChem Compound Database; CID=24450, https://pubchem.ncbi.nlm.nih.gov/compound/24450 (March 15, 2006).

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Seader, Henley, Roper. (2011). Separation Process Principles 3rd Edition. John Wiley & Sons, Inc. Hoboken, New Jersey

Seider, Seader, Lewin, Widagdo. (2009). Product and Process Design Principles 3rd Edition. John Wiley & Sons, Inc. Hoboken, New Jersey

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Appendix

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Appendix 1: Yaws’ solubility data The following equations were found from Yaws' Handbook of Properties for Aqueous Systems [Yaws, 2012] Where: Sx in y refers to the solubility of x in a solution of y in units of ppm (w/w) T refers to the temperature of the solution in units of kelvinAppendix 2: Water-DEM split ratio The split fraction of a separation process refers to the ability of the process to separate two key components into two separate phases. In this project, the ability of a solvent to split water and DEM into two separate phases was investigated and the equation used to produce the split fraction was: Where: Split refers to the split ratio Xy in z refers to the mass fraction of y in the z phase Appendix 3: Solvent selection parameters Table A3.1 shows the parameters used to select a solvent for the LLE extraction process. Non-halogenated solvents with prices under $1/g and Split ratios above 600 are shown. Price - this comes from Sigma Aldrich. The solvent was searched on Sigma Aldrich and the cheapest unit price was recorded. It should be noted that these prices will be lower in industrial quantities and that the relative prices of solvents may change when industrial prices are considered. BP - this is the boiling point of the compound as found in Aspen’s database. It should be noted that the boiling point of DEM is 199°C Split ratio - this is the split ratio as produced by Aspen when a 140 g/L solution of DEM in water was mixed with an equal mass of the solvent using the NRTL model. These numbers may not be representative of real world data. See Appendix 2 for details of the split ratio equation.

Table A3.1: Solvent selection parametersName Price

($/g)BP (°C)

Split ratio

N-PENTANE 0.006 36 52671-HEPTANAL 0.04 153 4684

TOLUENE 0.04 111 11511,2,4-TRIMETHYLBENZENE 0.06 169 52904

ETHYLBENZENE 0.06 136 9372-METHYL-BUTANE 0.065 28 4446

CYCLOHEXANE 0.07 81 4833CYCLOHEXENE 0.08 83 883

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BENZENE 0.08 80 616N-HEPTANE 0.09 98 3294

2,2,4-TRIMETHYLPENTANE 0.1 99 34991,3,5-TRIMETHYLBENZENE 0.11 165 707

N-UNDECANE 0.13 196 2836CYCLOPENTANE 0.22 49 3259

N-DECANE 0.25 174 14021-OCTANAL 0.26 172 16826

CARBON-DISULFIDE 0.26 46 13521O-NITROTOLUENE 0.27 222 11143

N-DODECANE 0.27 216 2907M-NITROTOLUENE 0.33 232 13995

PIPERIDINE 0.33 106 4129METHYLCYCLOHEXANE 0.34 101 2925

N-TETRADECANE 0.34 254 2798N-PROPYLBENZENE 0.36 159 43888

2,2-DIMETHYL-BUTANE 0.36 50 37101-HEXANAL 0.36 128 1225

INDANE 0.4 178 35221N-OCTANE 0.4 126 3164

CYCLOPENTENE 0.44 44 7155METHYLCYCLOPENTANE 0.45 72 2931

1-NONANAL 0.5 192 447453-METHYL-PENTANE 0.6 63 4679

2,3-DIMETHYL-BUTANE 0.6 58 3870N-NONANE 0.8 151 1952

N-TRIDECANE 0.82 235 3087 Appendix 4: Environmental Assessment 11-3-5. - Specific Pollutant Limitations and Maximum Allowable Industrial Loadings.Retrieved from:Boulder, Colorado - Municipal Code. (n.d.). March 7, 2016, https://www.municode.com/library/co/boulder/codes/municipal_code?nodeId=18020 (a) No user of the POTW shall discharge wastewater containing pollutants that does not

comply with the following specific pollutant limitations, based on a sampling methodology that

is most representative of the actual discharge. The city manager may also prohibit in writing

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any pollutant discharged into the POTW that is within the concentration limitations but that

interferes with the POTW plant process. The specific pollutant limitations and maximum

allowable industrial loadings permitted are shown below in Figure A4.1 and Table A4.1,

respectively.

Figure A4.1: Specific Pollutant Limitations

Flash Point (closed cup method) Minimum = 60°C (140°F)

pH* Minimum = 5.5

Maximum = 10.5

Oil and Grease Maximum = 100 mg/l

BTEX (benzene, toluene, ethlybenzene, xylenes)

mixture

Maximum = 750 ug/l

Benzene Maximum = 50 ug/l

Gas Meter Readings Lower Explosive Limit (LEL) One reading maximum = 10%

Two successive readings, maximum =

5%

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Table A4.1: Maximum Allowable Industrial Loadings to be apportioned to permitted users

(pounds per day).

Arsenic: 0.86

Cadmium: 0.57

Chromium - Total: 31.72

Chromium - Hex: 6.32

Copper: 5.36

Lead: 2.29

Mercury: 0.043

Molybdenum: 2.09

Nickel: 3.53

Selenium: 1.67

Silver: 0.64

Zinc: 27.32

Appendix 5

Project Plan- It should be noted that when adding rows for additional steps, some of the auto filled cells, for calculated hours planned for the week, are incorrect. The columns for actual work completed are correct and reflect the true numbers that should be in the calculated columns. Excel file attached for reading clarity.

Appendix 6 - Physical Experimentation

A6.1: Cary 5000 UV-VIS Data, indicates determination of absorbance wavelength of 212nm

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Figure A6.2: Calibration Curve for DEM in water (left) and n-pentane (right) at 212 nm with the Cary 5000 UV-VIS

Figure A6.3: Calibration data for water with Grubbs Test on points (Mean of Residuals for Calibration Curves)

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A6.4: Calibration data for n-pentane with Grubbs Test on points (Mean of Residuals for Calibration Curves)

A6.4: Raw data with grubbs test on individual points and means for aqueous phase LLE (Highlighted indicates Grubbs fail

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A6.5: Raw data with grubbs test on individual points and means for pentane phase LLE (Highlighted indicates Grubbs fail).

A6.6: Theoretical pH effect on partition coefficient K, experimental agreed.

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Appendix 7: Process Flow Diagrams

Figure A7.1: Decanting only PFD

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Figure A7.2: LLE only PFD

Figure A7.3: Series PFD

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Appendix 8: How to use the Aspen Models

The project comes with two Aspen models:1. Series and LLE only.apwz2. Decant only.apwz

A MATLAB file: 3. Report2Excel.m

And an excel spreadsheet: 4. formulas.xlsx

The Aspen files can be run on their own to produce mass-balance numbers; however, to complete the calculations all the way to unit operating costs, the MATLAB file will need to be used.

Running Aspen

1. Begin by opening “Series and LLE only.apwz”. This is the more complete of the two models and will be easier to understand.

2. Open C-DEFINE. This calculator block contains all of the global variables. The first 7 are the most important and are defined in Table A8.1.

3. The C-DEFINE variables should already be set up for the most economical conditions for the Series Process, so the Aspen file can be run at this point.

4. To run the process in LLE Only mode, change the LLEONLY variable in C-DEFINE to have an initial value of 1

5. Results can be obtained by right clicking streams and unit operations and going to “Results”

6. The “Decant only.apwz” file does not contain the variable SFRAC and contains many heat exchangers and calculator blocks. This model can be operated in exactly the same way as the Series and LLE only model; however, the LLESTOF should remain at 1E-10 to ensure that the LLE portion of the flowsheet does not contribute to the results

Obtaining Unit Operating Cost

1. Follow the “Running Aspen” instructions above to #42. Go to “Left Panel” > Model Analysis Tools > Sensitivity > TEMP3. Inside TEMP, ensure that the “Active” checkbox in the top left corner is checked4. The file comes with a sensitivity analysis setup for product purity. This will most likely run

without errors so at this point the model can be run.5. Go to “Left Panel” > Model Analysis Tools > Sensitivity > TEMP > Results

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6. You can view the results here, these columns can be copied to excel if the MATLAB program doesn’t work.

7. Go to “Tab Menus at Top” > Home > Report > Sensitivity > Check the box for TEMP > Ok

8. A notepad window will appear, you can leave the current name but I recommend Save-As

9. In one folder, place: the report file, Report2Excel.m, Formulas.xlsx10. Open the Report2Excel.m and follow the directions at the top of the file11. Run the MATLAB file12. Open the Excel spreadsheet it produced and follow the directions there

If all went well you should have results. If you can’t get the MATLAB program to work (we use Aspen Plus v8.8 and MATLAB 2015b), you can still copy the values into the excel spreadsheet by hand. Ideally clicking the top left corner of the TEMP Results should highlight everything, but this tends to crash for us. In any case, the columns need to be copied into formulas.xlsx. This method works but is very time consuming.

Table A8.1: Aspen Variables for C-DEFINE and TEMP

Aspen Variable Name

Units Parameter number

Description

DECTEMP °C 1 Temperature to heat/cool the decanter feed to. This has no effect in “Series and LLE only.apwz”

LLETEMP °C 2 Temperature to heat/cool the LLE feed to. This has no effect in “Series and LLE only.apwz”

LLESTAGE count 3 Number of theoretical LLE stages. This only affects “Series and LLE only.apwz”

LLESTOF ratio 8 Ratio of n-pentane to water (w/w) for the LLE. Leave this at 1E-10 in “Decant only.apwz”

FEDDFRAC mass-frac 9 Mass-fraction of DEM in feed broth

PH pH 10 pH to run decanter at. This has no effect in LLEONLY mode.

SFRAC mass-frac 11 Mass-fraction of LLE product that is n-pentane. This variable doesn’t exist in “Decant only.apwz”

LLEONLY boolean 12 This variable only appears in C-DEFINE in “Series and LLE only.apwz” and can take two values:0 - Run the process in Series mode1 - Run the process in LLE Only mode

Notes on Aspen Process

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1. The process is FED 10 ktonne/oper-year of DEM. The process achieves 99.9%+ recovery, but all numbers besides Unit Operating Cost must be scaled if exactly 10 ktonne/oper-year of DEM product is desired.

2. The Aspen file contains binary interaction parameters for DEM and water based on YAWS’ solubility data. It is unknown if this causes problems, but the model can be switched back to Aspen’s data by going to “Left Panel Low” > Properties > “Left Panel” > Methods > Parameters > Binary Interactions > NRTL-1 > Delete the column “WATER DIETH-01”

3. Aspen crashes frequently and often fails to save properly. It is recommended that you perform Save-As and change the filename about every 10 minutes

4. In “Series and LLE only.apwz” there is a string of heat exchangers that appear to do nothing. Indeed these heat exchangers don’t do anything but they were kept in the model to allow the report files from “Series and LLE only.apwz” and “Decant only.apwz” to be used interchangeably.

5. The TEMP Sensitivity block overrides C-DEFINE. This means that: 1) The initial values in TEMP should not be used. Leaving static variables in C-DEFINE and varied variables in TEMP is a more coherent system that will not change when TEMP is disabled. 2) The value of a variable in C-DEFINE does not matter when it is enabled in TEMP for sensitivity analysis

6. After changing initial values in C-DEFINE, the model should be reset. Aspen gets upset if you don’t do this.

7. The recycle stream for the n-pentane is not connected. This was to speed up convergence for sensitivity analysis runs that contain 1,000+ scenarios.

8. The GLTCHFX heat exchangers in “Decant only.apwz” fix a “glitch” where Aspen suddenly changes a stream temperature in a heat exchanger after two streams have been mixed. The utility for these heat exchangers is not tallied and their existence should be ignored.

9. HOTFEED is not tallied in the results. Mass balances must be used to find its flow rates

Appendix 9: Decanter Sizing

From Separation Process Principles, Chapter 19

E>3.3 meaning the heavy phase (DEM) is dispersed, and the light phase (water) is the continuous phase

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From:Unit Operations of Chemical Engineering, Chapter 2

The size of the decanter is established by the time required for separation, which in turn depends on the difference between the densities of the two liquids and on the viscosity of the continuous phase. The time required for the separation can be calculated by:

µ is the viscosity of the continuous phase, cP

ρ density in kg/m^3 1050 kg/m^3

Using a length to diameter ratio of 5, as suggested by Separation Process Principles:

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