List of figures

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Dedication

This thesis is dedicated to all the girls dreaming with science.

Especially for the little girl who dreamt with molecules, science, and Chemistry, it took us a long time, but now we are on the right path.

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Acknowledgments

To my parents, thank you for the living example of hard work, tenacity, and resilience, for your love and your unconditional support. My achievements come from the education and example given in our home. Words are not enough for the depth of my gratitude. Every day I give thanks for your life and for being your daughter.

To Ramiro, thank you for your love, your stupid jokes, and your amazing talent for curating a never-ending movie watchlist. Thank you for helping me stand up when I felt I could not reach my goals. Thank you for helping me design the power point! But most importantly, thank you for the last 4383 days.

To my grandmothers and grandfathers, you are my motivation. I recognize your wisdom and love.

I cherish every moment we spend together. I was fortunate enough to meet my four grandparents and blessed to still have two of my viejitos around at 33.

To Yipe, my little brother, my personal WhatsApp physician, and the first one I told I was trying to get back to finish this project. Thank you for believing in me and not discouraging my idea.

To Tec de Monterrey and the department of planning and organizational development, the you for making it possible.

Dr. Alejandro Alvarez, what can I say? You are an amazing scientist! Thank you for agreeing to be my advisor again and taking time from your super busy schedule to work with me and finish this project. My endless thank you for your leadership and guidance.

To Berenice Acevedo, thank you for your vision and recommendations. Working with you made finishing on time is due mostly to our follow- up sessions and the amazing advice you always had on making things happen.

To my committee members Dr. Ezequiel and Dr. Yasmany, thank you for your time reading my thesis. For raising insightful questions on the defense, and the suggestions you kindly provided to improve this document and project.

Crhys, Sofi, and Raul, thank you so much for your comments and ideas. I might owe you a coffee.

Thank you to Susy Garza for helping me take notes, notice errors, and rush through titrations in the lab. Your work was crucial for this thesis, and I will always be grateful to you.

To Vero Patiño and Dr. Enrique Ortiz, thank you for hiring me to be your assistant. It was an absolute pleasure to work with you and to be part of your team. To Guillermo Jiménez, thank you for teaching me so much while working with you.

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To Anita Ovalle and Mary Covarrubias. Thank you so much for everything you did for me while working together. I miss going to your offices and chatting while I slowly sipped my coffee.

Sometimes I just made out an excuse to go to your office and hang out with any of you.

Thank you to Adriana Canseco and Dr. Alejandro Aguilar for your speedy support and kindness in answering my enrollment and graduation process questions.

To my Ph.D. friends: Quique, Beto, Kish, and Meg. Somehow, knowing you were rooting for me kept me going. Thank you for your kind words, your recommendations, your friendship. Quique, thank you for reading the first draft of this document. Thank you for the ideas to make this a better record of my experiments. Beto, we graduated as engineers at the same time.

our together after all; you are the number one world champion of the world, Champ. Wait for me so we can finish a Ph.D. simultaneously.

Kish and Meg, you were part of my inspiration to pursue this degree once again. Being friends with intelligent, accomplished women in academia encouraged me to seek ways to be a little more

Hey young fellas! Jasso, Cecy, Claudio, Juan, and gang. Thank you for being there every step of the way, no matter how busy you may be. Words cannot possibly explain how lucky I feel for being part of our weird family. I love you, and I could never finish writing all my appreciation to you. I am privileged to call you my best friends. I hope we get a good family road trip soon. You are a

To Esther and Gual, for your love and kindness, for embracing me into your family with no legal documents or agreements needed. Thank you for welcoming me into your home and using the office for this project. Thank you for the amazing son you raised.

To my extended family, Peña Cruz and Welsh Rivera, for your support and help whenever I need it. Especially to my aunties for celebrating my accomplishments and loving me like a daughter.

To my other extended family, all the employees at Unidad Médica San José, in Agua Dulce, Ver.

Thank you for taking care of my mom and dad. Your presence in my life is a blessing and a true joy.

To the Ámbar family, Rodo, Karen, Gera, and Mago. Thank you for believing and loving our little project. You are all remarkable people, and I am thrilled to call you, my friends.

To Claudia Arias, Dr. Brenda Buxadé, Ana Pau Molina, and Dione Milauskas, my health coaches.

Thank you for teaching me fantastic health

professionals in my corner.

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Evaluation of the usage of ionic liquids as solvents in the crystallization process of acetylsalicylic acid based on the Green Chemistry principles

by

Griselda Peña Welsh

Abstract

This study proposes an alternate process in the crystallization of acetylsalicylic acid and evaluates the environmental impact of the new process. As a solution, proposes the use of ionic liquids as a substitute for conventional organic solvents. After creating solubility graphics for acetylsalicylic acid in three different ionic liquids, experimentation validated the new experimentation processes. The experiments show a higher yield of acetylsalicylic acid crystals than the yield obtained from conventional organic solvents.

Finally, the study proposes a new environmental evaluation tool, the Solvent Greenness Preliminary Evaluation, to evaluate the environmental impact of the crystallization processes with ionic liquids. This tool scores each process's impact without considering the manufacture of the solvents involved in the process. The evaluation scores one of the ionic liquids as the greener option for crystallization.

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List of figures

Figure 1. Chemical reaction for the obtention of ASA from salicylic acid and acetic

anhydride ... 6

Figure 2. Stages of the LCA ... 22

Figure 3. Types of LCA ... 23

Figure 4. Structural formulas for a) [bmim][otf], b) [emim][bf4], and c) [emim][dep] ... 30

Figure 5. Diagram of the experimental system ... 31

Figure 6. Pictures of the equipment used during the experimental phase of the project 32 Figure 7. Parameters of the evaluation are sorted into the Green Chemistry principles. ... 37

Figure 8. Parameters of the evaluation are sorted into the Sustainable Development principles. ... 38

Figure 9. Solubility curve using the ionic liquid [bmim][otf] ... 40

Figure 10. Solubility curve using the ionic liquid [emim][dep] ... 41

Figure 11. Solubility curve using the ionic liquid [emim][bf4] ... 41

Figure 12. Performance of the crystallization experiment: yield and depletion of ASA concentration in the liquid phase ... 42

Figure 13. Experimental yield of crystallization of ASA using ILs ... 44

Figure 14. Comparison for the theoretical yield of the processes ... 50

Figure 15. Score comparison for the four solvents ... 52

Figure 16. SGPE parameters, excluding yield ... 52

Figure 17. Images of the pictograms considered in SGPE ... 59

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List of tables

Table 1. Experimental conditions for solubility experiments ... 33

Table 2. The concentration of Acetylsalicylic acid present in the samples taken and yield of crystallization over time. ... 43

Table 3. Theoretical and actual yield of ASA crystallization ... 45

Table 4. Parameters used in the creation of the evaluation method ... 47

Table 5. Calculation method and assignment of penalties in SGPE ... 49

Table 6. Results of the evaluation ... 51

Table 7. Information of density, heat capacity, and molar mass of the solvents ... 57

Table 8. Toxicological information obtained from MSDS of the chemicals ... 57

Table 9. Data obtained from the crystallization experiments, and reference mass used for calculations ... 57

Table 10. Information pertaining the energy estimates and calculations ... 58

Table 11. Calculations for the heat capacity of the solvent solution H2O+IL 50% v/v ... 58

Table 12. Data obtain for the comparison and penalty allocation ... 59

Table 13. Data from [bmim][otf] experiments. ... 60

Table 14. Data from [emim][bf4] experiments ... 61

Table 15. Data from [emim][dep] experiments ... 62

Table 16. Data from the crystallization experiment with [bmim][otf] ... 63

Table 17. Data obtained from the crystallization experiments. ... 64

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1 Introduction

Acetylsalicylic acid (ASA) is a non-steroidal anti-inflammatory drug considered one of the oldest drugs in use by humanity. Ancient Greeks used the willow bark as an anti- inflammatory remedy, and ASA is the modern version of that remedy (Stuntz & Bernstein, 2017). ASA is one of the most readily available drugs to the public and has been used to treat or prevent several diseases (Huremovic et al., 2016) since its introduction to the pharmaceutical market in 1904 (Ittaman et al., 2014). For those reasons, obtaining this drug should be considered for innovation and improvements concerning its waste, environmental impact, and general safety for the people involved in the handling procedures.

1.1 Motivation

According to a 2010 analysis, 80 to 90% of the waste generated in pharmaceutical industries is related to solvents (Raymond et al., 2010), the report from the Environmental Protection Agency, the Toxic Release inventory from 2019 reports that pharmaceutical processes in the USA create an approximate of 3 million kg of waste each year, inferring that 80 to 90% of that waste are solvents.

In the industrial process to produce ASA, the most common solvents are volatile organic compounds, chemicals with known toxicity for the environment and human health. It is essential to consider an update on the process and search for safer solvents for their use within the process.

This thesis poses the possibility of replacing volatile organic compounds with a greener solvent in the obtention process of ASA.

is necessary to research the evaluation tools available for these purposes or create one that accurately assesses the conditions of the process and evaluates if the new solvent is truly greener.

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1.2 Problem Statement and Context

Problem statement: The production of ASA presents a high amount of waste coming from the use of volatile organic compounds as solvents in the reaction and crystallization process.

Within the uses of ASA in medicine, it is common knowledge the prescription of this drug for generally mild pain, reduction of fever, and swelling caused by some diseases. A report on the benefits of a small dose of ASA for secondary treatment of various cardiovascular diseases like brain strokes or myocardial infarction; there is also evidence that ASA might help prevent colorectal cancer (Maia & Giulietti, 2008).

Within its uses, ASA is a prevention treatment for cardiac diseases. A study in 2009 showed that using ASA is effective for preventing cardiovascular disease (CVD), and there is a generalized use of the drug in patients who had one or more CVD events (Collins et al., 2009). In the United States of America, an epidemiological study showed that from 2012 to 2015, ASA therapy is also a medicine commonly used to prevent CVD in the population over 60 years old (Stuntz & Bernstein, 2017).

ASA is an active pharmaceutical ingredient of great interest since its usage is widely spread worldwide and is easily accessible as an over-the-counter pain management drug.

The manufacture of this medication presents exciting challenges: the waste produced, the solvents used, and the type of production. For this study, the focus will be on the solvents used during the crystallization of ASA.

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1.3 Research Questions

How to replace the volatile organic solvents used in the crystallization of acetylsalicylic acid?

How to for the replacement of solvents in the crystallization of acetylsalicylic acid?

1.4 Solution Overview

This thesis aims to take the following course of action to answer the questions posed for the research:

1. Choose the solvents that will perform effectively in the crystallization of ASA, considering previous studies concerning the behavior of ILs in the process.

2. Design the experiments to characterize the solubility of ASA in the ILs. Design is an essential step for the design of a crystallization process.

3. Perform crystallization experiments to obtain information on the performance of the process using ILs.

4. Search for different methods to evaluate the

5. Adapt or create an evaluation for crystallization processes.

6. Compare the crystallization with a volatile organic solvent and the crystallization with ILs.

The results for this project will include the solubility curves for ASA in ILs, the characterization of the crystallization process for ASA in ILs, the evaluation of the greenness of the process with ILs, and its comparison con the process with volatile organic compounds.

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1.5 Objectives

To propose a process for the purification of ASA using ionic liquids as solvents.

To design the experiments needed to characterize the solubility of ASA in ILs.

To validate through experimentation the technical feasibility for the use of the chosen ILs.

To evaluate the greenness of the crystallization process using ionic liquids and compare them with one of the most common solvents used in the process for the purification of acetylsalicylic acid.

To conduct a literature review of the different methods for evaluating chemical processes based on green chemistry.

To adapt or propose an evaluation method based on the green chemistry principles.

To evaluate the crystallization processes with ILs and volatile organic compounds to compare the greenness of each process.

1.6 Main contributions

The study will present a feasible replacement for the solvents used in the crystallization process of ASA. This change would lower the environmental impact of the process by

The replacement of solvents will aid in the diminishing of the hazards related to the operation of the process, given that the volatility of ionic liquids is negligible and therefore reduces the respiratory exposure of workers to potentially toxic fumes.

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1.7 Dissertation organization

The organization of the thesis follows the structure described below:

1. A first chapter for the setting of the main problems and goals for this study.

Including a context for the problem, its relevance, and motivations.

2. The second chapter is the theoretical framework. It comprises the main concepts needed to understand the contents of the thesis (crystallization, ILs, green chemistry, green metrics) and the literature review conducted to evaluate the method that will be proposed further on within the text.

3. The third chapter includes the methodology followed to solve the posed problem and all the materials and equipment needed for the experiments.

4. The fourth chapter presents the results from the experiments and the evaluation for the greenness of the proposed process. The chapter also includes a discussion of the results.

5. Finally, the fifth chapter contains the conclusions of the study.

6. The reader will find additional information regarding the study and links to the spreadsheets created for this work in the appendix.

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2 Theoretical Framework

This chapter of the study covers the main ideas and concepts needed to develop the work conducted. First, the reader can find information regarding obtaining acetylsalicylic acid (ASA); the following section contains a general overview of the process at the center of the examination, crystallization. The third section deals with ionic liquids (ILs) and their main advantages and disadvantages. Finally, the reader will find a review of existing methods and metrics based on the principles of Green Chemistry.

2.1 Acetylsalicylic acid: properties and method of obtention

The IUPAC name for ASA is 2-(acetyloxy) benzene carboxylic acid, with the condensed formula C9H8O4. In its production patent, The manufacture of ASA begins by reacting salicylic acid in solution with anhydride acid and toluene in an acid medium. The heating of the solution happens between 88 and 92°C for 20 hours. After the reaction, the solution is cooled for three to four days until it reaches a temperature between 15 and 25°C. This cooling stage is where the crystallization of ASA occurs. Afterward, the purification by recrystallization takes place in a process that reaches 3°C. Next, recovery of crystals happens by filtration or centrifugation. The crystals are subsequently washed and dried for further purification. This wash will eliminate the acetic acid obtained as a subproduct of the reaction. Then, the acetic acid is stored and processed to obtain acetic anhydride used for the first stage.

Figure 1. Chemical reaction for the obtention of ASA from salicylic acid and acetic anhydride

Source: (Huremovic et al., 2016)

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The solvents commonly used in the crystallization process of ASA are benzene, xylene, ethylbenzene, and toluene (USA Patent, 1966). Those solvents are known for possible damage to human health, the safety hazard due to their flammability, volatility, and toxicity to the environment (Amberg et al., 2015).

Toluene is the solvent used in crystallization that yields high-purity and uniform-sized crystals (USA Patent, 1954). According to its material safety data sheet, toluene is a volatile organic compound, classified as a flammable substance, irritant to the skin, and is considered a hazard for reproductive toxicity and aspiration. One of the main changes proposed for the innovation and diminishing of the manufacturing process for ASA is the trade-off for the solvent used in the crystallization.

Another innovation proposed for the process is the switch from batch to a continuous process. Batch processes are the standard rule in the pharmaceutical industry. These methods require a long time to manufacture a final product. By switching to a continuous process, a reduction in production time could turn out, and other advantages, like improved process control and decreased inventory capacity (Domokos et al., 2020).

In their 2020 study, Domokos and colleagues proposed an integration for the steps to produce ASA. They used a continuous mixed-suspension-mixed-product-removal reactor for the crystallization and primary reaction of the process. A continuous filtration carousel for both filtration and drying of the product was connected to the reactor. They discovered the need to use the vacuum-driven slurry transfer system of the continuous filtration carousel as the reactor outlet to avoid the breakage of crystals. The blending of the product took place in twin-screw multipurpose equipment. Subsequently, the main product was mixed with an excipient and shaped into tablets. After reaching the steady- state, the team analyzed the 500 mg tablets with 100 mg dose of ASA and found them acceptable in purity and content uniformity.

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For ASA and many other compounds, crystallization is an essential step in its obtention process. A report concludes that 90% of pharmaceutic products contain crystals within their main ingredients or excipients (H. Zhang et al., 2012). In the crystallization process, the manufacturer makes sure the target size and shape of the crystals are adequate since these parameters affect the overall manufacturing process's yield and the final product's bioavailability (Domokos et al., 2020). In the following sections, the reader will find the key ideas and definitions for this vital process.

2.2 Purification methods for pharmaceuticals: crystallization

Crystallization is a separation process based on differences in solubility (Gilbert & Martin, 2010). During the process, the forming of solid particles occurs from a homogeneous base. For this study, we will consider only the crystallization of a liquid solution, which is a practical method for obtaining substances with high purity in acceptable conditions for its packaging and storage (McCabe et al., 1993).

In the industrial production of pharmaceuticals, crystallization can affect the efficiency of the downstream process (Fujiwara et al., 2005) and the efficacy of the drugs (Alvarez et al., 2011). The production of active pharmaceutical ingredients occurs primarily in crystalline form because of their chemical stability for packaging, shipping, and storage (Stieger & Liebenberg, 2012). Crystallization is a process used in the pharmaceutical

(H. Zhang et al., 2012).

As a process based on a difference of solubilities, this is an essential parameter for crystallization processes. According to the Handbook of Industrial Crystallization, solubility is the amount of solute required to make a saturated solution at a given condition (Myerson et al., 2019). A solution is the homogeneous mixture of a solid solute into a solvent. A solution has a maximum amount of solute that can dissolve at any given temperature. The solution is saturated when it reaches the maximum amount of solute.

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Solubility is a crucial part of the design, development, and operation of a crystallization.

Often, solubility data will not be available in the literature, and accuracy is paramount in developing the design process. Solubility must be measured at a constant controlled temperature and employing agitation (Myerson et al., 2019). The recommended procedure for the measurement of solubility is:

1) In a vessel with temperature control or jacketed, add a known mass of solvent. The temperature control must be 0.1°C or better.

2) Bring the solvent to the temperature for the measurement. Use a condenser to prevent evaporation if needed.

3) Add solute in excess (the total mass added should be known). Agitate for an extended period, more than four h and preferably 24 h if possible.

4) Sample the solution and analyze for the solute concentration. This step can be replaced by filtration of the solution, drying of the solid, and weighting. Finally, subtract the amount undissolved from the mass added initially.

The crystallization yield indicates the percentage of crystals obtained compared with the initial mass added to the solution. For this study, the calculation for yield followed the equation below:

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The crystallization yield can be obtained directly from the experimental data for the crystallization or the solubility curves created for those purposes. When the yield comes from experiments, it is considered an actual yield. The theoretical yield is the one obtained from the information on the solubility curves.

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2.3 Ionic Liquids: properties, advantages, and disadvantages

Ionic liquids (ILs) are liquid salts with dissociated cations and anions. These chemicals are composed of an anion and cation of very different sizes. The difference in size provides ILs with a wide array of possibilities for their use, especially as solvents.

ILs can dissolve hydrophobic, hydrophilic, and polymeric compounds (Moniruzzaman &

Goto, 2011). These properties give them a vast range of possible chemicals to dissolve.

There are possibly a million binary ILs that can be potentially obtained (Abramenko et al., 2020). For those reasons, ILs can take part in several processes.

Another use of ILs is as substitutes for common solvents in chemical synthesis (Erbeldinger et al., 2000), bio-catalysis (Scholten et al., 2012; R. Sheldon, 2001), separation ((P. Zhang et al., 2014), and extraction processes (Sun et al., 2012).

ILs can be tailor-made for the process and application required. With the appropriate design of ILs, it is possible to lower physical properties like flammability and vapor pressure or increase other properties like chemical and thermal stability (Marullo et al., 2021; Yavir et al., 2019).

In the design of ILs, scientists can manipulate other physical and chemical properties of the compound (e. g. density, heat capacity, and viscosity). The manipulation is possible by variations of features like main alkyl chain length, cation type, and anion type (Crosthwaite et al., 2004).

As shown previously, ILs are compounds that have been researched extensively in the past two decades. The most common cations for their design are imidazolium, ammonium, pyridinium, pyrrolidinium, and phosphonium. As for the anions, the most common are Cl^-, [BF4]^-, [PF6]^-, Br^- and trifluoromethyl sulfonate, to mention a few (Abramenko et al., 2020).

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Other examples of the uses for ILs are:

The antisolvent crystallization for the polymorphic design of active pharmaceutical ingredients (An & Kim, 2013).

Derivatives of ILs, known as supported ionic liquids, can be used as purification platforms for proteins and enzymes (Bento et al., 2021).

Electrode modification, for their hydrophobicity, ionic structure, and appropriate viscosity (Opallo & Lesniewski, 2011)

The synthesis of metal sulfide nanoparticles (Balischewski et al., 2021).

When incorporated with nanomaterials, ionanofluids obtain properties as reliable energy storage for solar systems (Das et al., 2021).

When using ILs as solvents, it is vital to develop liquid-phase-equilibrium data. This information can enrich future research in the uses of ILs in liquid-liquid extraction processes and solvents for reactions. Studies like the one conducted by Crosthwaite help select ILs best suited for specific processes.

Another critical factor to consider in the usage of ILs is their toxicity. ILs are not entirely safe, and research shows that they can be safer for the environment and human health by design.

In a toxicity review for ILs, the research team found that the disposal of ILs takes place in wastewater and landfills, and there is little concern for pollution on aquatic and terrestrial ecosystems (Gonçalves et al., 2021). A meta-analysis of publications in ILs concluded that only 3% of the academic articles are concerned with toxicity (Heckenbach et al., 2016).

The structural modification of ILs could also influence the toxicity of the substance, as stated in the conclusions for a review and compilation of transport and transformation of ILs in environmental systems (Amde et al., 2015). These conclusions suggested that the design and tailor-made possibilities in ILs could also include the chance to create a less

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polluting solvent by modifying its structure and analyzing its effects in model species and humans.

According to their review of the different models for toxicity assessment of ILs, Abramenko and colleagues found the following conclusions:

Toxicity depends predominantly on the nature of the cation.

Toxicity increases with the cation alkyl chain length.

ILs with the same cation and different anion show no statistical difference in toxicity.

High correlation of toxicity with lipophilicity.

A polar group (hydroxyl, nitrile) or short polar sidechains in the cationic substituent reduce toxicity and increase biodegradation efficiency.

According to the review, the ILs with the lowest toxicity should be morpholinium or pyridinium cations with short linear and polar alkyl chains (Abramenko et al., 2020).

However, recently cholinium [Cho] and amino acid-based [AA] ILs have been characterized as the new low toxicity ILs.

The discovery of fully biocompatible ILs came about when choline chloride was coupled with succinic and oxalic acids, both naturally occurring substances, and produced an ionic salt with melting points below 100°C (Le Donne & Bodo, 2021). These biocompatible ILs pose a new set of possibilities for the usage and applications of these chemicals.

The most common route for the synthesis of biocompatible ILs is by the neutralization of a water solution of [Cho][OH] and the [AA]. The obtention of these ILs can also occur through an ionic metathesis between potassium AA salts and [Cho][Cl] in ethanol (Le Donne & Bodo, 2021). This alternate route presents a higher efficiency and the usage of [Cho][Cl], a cheaper reagent.

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Between the properties for biocompatible ILs, the obtained densities are between a limited range (1.1 and 1.2 g/cm3). Glass transition temperatures range between -74 to - 10°C. Furthermore, decomposition temperatures are comparable to those for traditional ILs.

According to the review by Le Donne & Bodo, [Cho][AA], ILs

compounds whose molecular components feature only minor differences but present huge differences in the resulting bulk properties Giving way for an extensive array of possible applications for these compounds, like:

Potential drug carriers.

Their use as solvents can ease the extraction and separation of proteins.

They could be used to produce biomass-based energy sources as solvents for lignin, xylan, and cellulose.

Use as lubricants, losing the possible corrosive effects of traditional ILs.

CO2 absorption. Biocompatible and recyclable ILs can be designed for the selectivity and trapping of CO2.

When using traditional ILs, it is vital to consider the separation methods knowns to be helpful for this type of substance. For the separation of ILs from other substances, the following options are the most useful (Zhou et al., 2018):

Distillation. For the separation from volatile compounds or neutral species.

Force field. For hydrophobic or magnetic ILs.

Crystallization. For the purification of ILs.

Aqueous two-phase extraction. For the recovery of hydrophilic ILs.

Membrane separation. While ILs remain in the feed side or permeated.

Adsorption. Recovery of ILs from diluted solutions, there is known difficulty for the desorption of ILs.

Extraction. For the separation of non-volatile or thermally sensitive species.

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Combined methods, when needed. Usually, for recovery of ILs, first, go through extraction with organic solvents and then distillation.

ILs are generally considered a green option for substituting common solvents, given their low flammability and vapor pressure. Nevertheless, how is a green process or chemical characterized?

2.4 Green Chemistry: Methods and metrics based on its principles

Green Chemistry is the design of more efficient processes that use less hazardous and polluting substances. The EPA launched the Green Chemistry Program

promote the research, development, and implementation of innovative chemical technologies that accomplish pollution prevention in both a scientifically sound and cost- effective manner (P. Dicks & Hent, 2015).

Anastas also published the twelve principles of Green Chemistry: (Anastas & Eghbali, 2010)

1. Prevention of waste 2. Atom economy 3. Safer synthesis 4. Safer chemicals

5. Safer solvents and auxiliaries 6. Energy efficiency

7. Renewable feedstock 8. Fewer derivatives 9. Catalysis

10. Design for degradation 11. Real-time analysis

12. Safer chemistry for accident prevention

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The green chemistry principles are to help the achievement of sustainability in processes. The main objective is to achieve synergies, not merely trade-offs (Anastas

& Eghbali, 2010). By adopting this perspective on process efficiency, scientists can improve the quality and sustainability of processes (P. Dicks & Hent, 2015). These principles also facilitate the improvement and innovation of existing processes.

Other than sustainability, green chemistry centers the management of risks in its principles. According to Anastas and Eghbali, the risk is the sum of exposure and hazard.

When hazard increases and exposure control fails, injury or death may ensue. Applying the green chemistry principles allows advantages like reducing the hazard and limiting the risk of accidents and damages.

2.4.1 Green Metrics

Green metrics were created gradually in response to the needs for evaluation or measurement of the Green Chemistry principles. This section includes a review of the most popular metrics.

The E Factor was one the firsts of the metrics based on Green Chemistry. The E Factor is used to evaluate compliance to the first principle of Green Chemistry, the prevention of waste (R. A. Sheldon, 2000). The E factor measures the waste produced per kilogram of the desired product. Zero is the ideal value for this metric.

For a generic reaction A + B C + D + Waste (2)

where,

m1 is the mass of A, m2 is the mass of B,

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m3 is the mass of C, m4 is the mass of D, m5 is the mass of Waste,

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Atom Economy is a green metric proposed to evaluate the second principle of Green Chemistry, the same as the metric (P. Dicks & Hent, 2015). Atom economy tells us how much of the original reactants are present in the final product of the process. For the evaluation of atom economy, there must be a balanced chemical equation, then, account for all the materials incorporated into the process, except for catalysts and solvents, divide the molar mass of the products by the molar mass of the reactants, and the result is the ratio of reactants included in the product. Sometimes, this approach is not the most suitable to evaluate the greenness of a process since it does not take the solvents or catalysts into account (R. A. Sheldon, 2018). The main advantage of this metric is the possibility to use it without experimental procedures (P. Dicks & Hent, 2015).

Reaction Mass Efficiency is a metric that includes atom economy, yield, and stoichiometry of the reaction (Constable et al., 2001). RME is the percentage of the reactants present in the final product. There are two methods to obtain this metric, the first one includes molar weights of the reactants and products and the stoichiometric ratios, and the second method is straightforward, as it only uses masses of products and reactants. For

example, , there are two equations for RME:

first,

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The calculation of RME can also follow the subsequent equation:

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Process Mass Intensity, also known as Mass Intensity of Mass Index, PMI is defined as the mass ratio of total input material to the final product (Heinzle et al., 1998). PMI includes in its calculation all the materials present in the input streams of the process (reactants, reagents, solvents, and catalysts (P. Dicks & Hent, 2015). The ideal value for this metric is 1, a number that, according to some authors, is not as clear as other metrics used to avoid waste in the literature (R. A. Sheldon, 2018). This metric is an excellent complement to the life cycle analysis.

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The Environmental Quotient is a metric that includes the E factor and multiplies it by an arbitrarily assigned unfriendliness weighting factor. The advantage of this metric is the inclusion of a measure of the different impacts for the different materials. However, the arbitrary assignment of multipliers leaves the results to the tise (P. Dicks

& Hent, 2015).

Constable defines carbon efficiency as the percentage of carbon in the reactants that remain in the final product. The calculation for this metric includes stoichiometry of the reaction, as well as its yield. For a reaction A + B C

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Carbon efficiency is another mass-based metric, where, according to Constable (Constable et al., 2002), there are no new trends we can find beyond the ones found with the calculation of RME.

Constable mentions RME as the most helpful metric to evaluate the greenness of a process since it includes yield and atom economy. In his review of Green Metrics, Sheldon

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considers the use of the E-Factor and Atom economy as different sides of the same coin and stresses the need to develop reliable and not-so-expensive metrics to evaluate the greenness of a process. Green Metrics are not standardized, so each method or company may require a different set of metrics or even new ones to comply with their interpretation of the Green Chemistry Principles.

2.4.2 Green Evaluation Methods

There are several methods for the evaluation of the greenness of a process. This section reviews the most common evaluation methods based on the principles of Green Chemistry.

2.4.2.1 Environmental Assessment Tool for Organic Synthesis (EATOS)

EATOS is software for measuring the potential environmental impact of various routes to a target molecule (P. Dicks & Hent, 2015; R. A. Sheldon, 2018). This software works with an input, includes data of all raw materials (solvent, catalysts, auxiliaries), and as output, it calculates E Factor for the process. EATOS incorporates the human risk of the process based on the risk phrases and toxicological effects. Some of the advantages of this method include integrating an economic component in the cost of raw materials.

According to its authors, this method compares the different routes for a chemical, considering their resource usage and their potential environmental impact.

This method has two significant disadvantages. First, it does not include the energy of the process in the evaluation (R. A. Sheldon, 2018). According to the Green Chemistry principles, the account of energy requirements of chemical processes is paramount when estimating the environmental and economic impacts (Anastas & Eghbali, 2010). The second disadvantage resides in the outdated software, and there are newer methods for evaluating a process. However, EATOS is an excellent example of the criteria needed to start the evaluation of a chemical process.

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2.4.2.2 Andraos Algorithm

Andraos created an integrated method for depicting efficiency parameters employing radial pentagons. The author proposed a generalized RME that is useful when there are no masses reported for an experiment. This expression for RME can be derived in terms of reaction yield and atom economy (Andraos, 2009).

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2.4.2.3 Green Motion

The metric tool developed by MANE, a company leader in its field, was created to demonstrate the company's efforts to work with green and sustainable processes (Phan et al., 2015). One of the problems they found within existing metrics was the tremendous amount of information needed, and the time it took to perform such analysis. The main objective of this metric is to improve the company's process according to the Green Chemistry principles.

In their own words, Phan and the team at MANE were looking for a straightforward, simple, and appropriate method. They came up with a scoring system that starts with a 100-point score for each product. They reviewed seven key parameters to evaluate the greenness of the products:

Raw material

Type of solvents used

Hazard and toxicity of the reagents

Reaction (yield, number of steps, number of solvents, carbon economy, overall processing time)

Process (heating, cooling, vacuum, or pressure) Hazard and toxicity of the final product

Waste (E-Factor)

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The method turned out to be a quick and easy-to-apply evaluation. The authors concluded that the entire assessment could happen in half an hour and considered the evaluation an excellent tool for improving existing processes and the decision-making in the early stages of the process design.

2.4.2.4 Eco-Scale

Eco-Scale is a tool developed for the selection of the best route for chemical synthesis. It is focused on user-friendliness and transparency (Van Aken et al., 2006). It uses a 100-

A undergoes a reaction with (or in the presence of) inexpensive compounds B to give the desired compound C in 100% yield at room temperature, with a minimal risk for the

The calculation of the Eco-Scale is based on six parameters, considered as the most influential in the quality of the reaction. The parameters are:

Yield of reaction

Price of reaction components to obtain ten mmol of the desired product Safety, based on hazard symbols

Technical setup (common, unconventional activation technique, pressure equipment, unique glassware, inert atmosphere, or glove box)

Temperature/Time. Room temperature, heating, or cooling.

Workup and purification. Cooling, adding solvent, simple filtration, solvent removal, crystallization and filtration, solid-phase extraction, distillation, sublimation, liquid- liquid extraction, or classical chromatography.

Eco-Scale is a method that provides a straightforward approach to the main characteristics of a chemical process. It can be used for educational purposes or the comparison of different obtention routes for a product.

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2.4.2.5 Modified Eco-Scale

In their research, Dach and colleagues proposed a modification of the Eco-Scale and the addition of other parameters for evaluating industrial processes.

The good manufacturing process method includes the following parameters and weightings (Dach et al., 2012):

1. Material cost (15%) 2. Atom economy (5%) 3. Yield (5%)

4. Volume-Time-Output (VTO) (40%) 5. E Factor / PMI (10%)

6. Quality service level (5%)

7. Process excellence index (10%) 8. Eco-Scale Score (10%)

The eight parameters proposed include ideas as residence time in reactors, in-plant

weightings shed light on the interest for the company, VTO and cost are the highest-rated parameters and include the cost of raw materials, and VTO is the nominal volume of all reactors multiplied by the hours per batch, divided by the output per batch. These parameters create an idea for the desired product obtained at a particular time and compare it with the cost for the raw materials.

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2.4.2.6 Eco-efficiency analysis by BASF

This analysis is a tool developed by BASF to create a decision-making aide for the different issues brought up by society, politics, and regulations concerning the greenness of a process. Their main objective was to develop an easy-to-use tool for LCA-experts and understandable by many people without any experience in the field (Saling et al., 2002). The eco-efficiency portfolio is the result of the study, a summary of the ecological data obtained from the analysis. After normalizing the data analyzed, it presents the different routes considered in a plot and organizes the information according to the eco- efficiency resulting from the study.

The eco-efficiency portfolio is helpful for research and development and optimization processes with several potential routes to choose the least damaging to the environment.

2.4.3 Life Cycle Assessment (LCA)

Analysis tool capable of evaluating the environmental impact of products and processes across their entire life cycle (raw material production, manufacture, distribution, use, and disposal). The assessment requires large amounts of data, making this analysis very costly and time-consuming (P. Dicks & Hent, 2015).

The stages for LCA are in figure 2:

Figure 2. Stages of the LCA

Goal definition

and scope Inventory

analysis Impact

assessment Interpretation

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Commonly, there are five types of LCA, shown in figure 3:

Figure 3. Types of LCA

When conducting an LCA, the practice of Green Chemistry principles can positively influence the outcomes of the assessment. Green Chemistry can effect changes in the selection or design at a molecular level (P. Dicks & Hent, 2015).

The main disadvantage for this assessment occurs when trying to reduce the environmental impact for one stage of the process, creating impacts on other stages of the life cycle.

Another disadvantage is the simplifications created for the lack of availability of information, this constraints LCA to a linear model that does not account for changes in the economy, environment, and society (P. Dicks & Hent, 2015). However, LCA is a tool considered to be the most robust and complete for assessing environmental impact.

Cradle-to-grave From the obtention of raw materials to the disposal of the product

Cradle-to-gate From the obtention of raw materials to the end of manufacturing process

Gate-to-gate Manufacturing process of the product, from start to finish

Gate-to-grave From start of manufacturing process to end of life

Cradle-to-cradle From the obtention of raw material until the use as raw material for a new product. Used for recyclable goods

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2.4.4 Solvent selection methods based on Green Chemistry Principles

In the review for the evaluation methods based on Green Chemistry, one can find different methods for selecting and characterizing green solvents. The following sections are a summary of the method encountered during the literature review.

2.4.4.1 Quick Sustainability Assessment (QSA)

The QSA is a methodology based on LCA. It was designed to simplify the early stages of developing a new pharmaceutical produced in a batch process. The authors considered, as well as Slater et al., that the best way to create a greener process is during the discovery and route selection stages, so they had this process created explicitly for the use of development scientists (Isoni et al., 2016). The method is divided into three stages:

solvent production, solvent use, and end-of-use.

For the first stage, the authors used GaBi Professional 6 to model the life cycle of solvent production. The second stage includes the experimental data needed to compare the solvents in the same process, specifically the mass and energy balance data and extrapolating to the plant-scale process. In the second stage, experiments are designed with ten suggested solvents from the first stage of the method. Afterward, the three best solvents for the process and the balance and energy data from the experiments are entered into the software. This stage includes the mass and type of solvent used for the cleaning of the reactor.

The third stage of the method evaluates the performance of solvent distillation and incineration to treat organic waste. Aspen Hysys (version 7.3) was used to simulate the mass and energy balances of both processes. The final product of the method is a decision table where the three best solvents are compared using the following criteria:

Carbon footprint

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Eutrophication

Human toxicity potential Total energy use per batch

Mass of active pharmaceutical ingredients per batch

QSA is a tool designed for developing new pharmaceuticals when the final decisions of the process are still uncertain.

2.4.4.2 Solvent Selection Table Software

This software is a tool created to simplify selecting a solvent within the 60 solvents included in the software. The program creates an index that compares the solvents. The parameters for the comparison are:

a) Inhalation toxicity TLV (Threshold Limit Value)

b) Ingestion toxicity c) Biodegradation d) Aquatic toxicity e) Carcinogenicity f) Half-Life

g) Ozone depletion

h) Global warming potential i) Smog formation

j) Acidification

k) Soil adsorption coefficient l) Bioconcentration factor

The twelve parameters represent different properties and are expressed in different units, so the authors developed a dimensionless scale. They took the values of the parameters from the 60 solvents in their database, weighted on a log scale with a log base equivalent to the maximum value of that parameter (Slater & Savelski, 2007), and then scaled to a linear tendency using an equation that normalizes the factors. Afterward, there is a summation of all the parameters, and it produces a score where the closest to 0 means the greenest solvent, and the closest to 10 is the least green of the solvents.

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The index includes user-defined weighting factors for each metric. There is no consideration for safety metrics like the flashpoint, or the peroxide formation, which is considered an oversight by some authors (Byrne et al., 2016). This method was designed to compare two or more processes that originate the same final product.

After reviewing the information needed for the study in terms of pharmaceutical production, principles of crystallization, information on organic solvents, and ionic liquids, as well as the information reviewed for the creation of a novel greenness evaluation, the next section will describe the methodology followed to accomplish the objectives of the dissertation.

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3 Methodology

The methodology is divided into four stages. The first stage consisted of narrowing down the substitution options for solvents to three ionic liquids (ILs). The second stage was the experimentation to obtain the solubility curves for acetylsalicylic acid (ASA) in the ILs proposed and determine the conditions for the crystallization design. Thirdly, the technical feasibility of the proposed ILs was tested by conducting crystallization experiments.

Lastly, a new evaluation was created to determine which process would pose a greener option compared to the typical solvents used in the process to obtain ASA.

3.1 Process proposal for the crystallization of ASA in solution using ionic liquids

This study will research the possibility of replacing the typical solvents used in the obtention of ASA, considering the option to use ionic liquids (ILs) instead of said solvents.

In 2012, Jesús Tamez-García completed research where he proposed using ILs as solvents for the crystallization of ASA.

His work included a mathematical model for predicting the possible solutes that could work with ionic liquids. The study used Gibbs free energy to determine the miscibility within ILs. It concluded that ILs in binary and tertiary solutions have fair values to solubilize ASA.

This work proposes a new crystallization process for the recovery of ASA. To develop this proposal, we performed solubility tests to characterize the thermodynamical behavior of acetylsalicylic acid in different ionic liquids. We also performed crystallization tests to evaluate the performance of the proposed process.

This new process with ILs is expected to improve the overall yield of the crystallization process and the safety of the workers involved. For this study, we will use three different ionic liquids and compare their performance with a crystallization process with toluene,

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one of the most common solvents used in the ASA obtention process. The ILs included in this study are:

a) Name: 1-Butyl-3-methylimidazolium trifluoromethane sulfonate Condensed Formula: C9H15F3N2O3S

Abbreviated name: [bmim][otf]

b) Name: 1-Ethyl-3-methylimidazolium tetrafluoroborate Condensed Formula: C6H11BF4N2

Abbreviated name: [emim][bf4]

c) Name: 1-Ethyl-3-methylimidazolium diethyl phosphate Condensed Formula: C10H21N2O4P

Abbreviated name: [emim][dep]

For the choosing of the ILs, the previous work of Tamez-García was consulted. The requisites for the choosing of the ILs proposed were:

Soluble in water.

No reaction with ASA.

No interference with the quantitative analysis.

Firstly, [bmim][otf] was selected as being the original IL Tamez-García worked.

Furthermore, following those recommendations, this study will use similar ILs, [emim][dep] and [emim][bf4], to compare them and select the IL best suited for the process.

In figure 4, we can see the structural formula for the ionic liquids proposed to replace toluene and other common solvents. In the structure, we can see the bigger cation and the small anion, which gives ILs the physical properties described in chapter 2.

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Figure 4. Structural formulas for a) [bmim][otf], b) [emim][bf4], and c) [emim][dep]

After determining the ILs needed for the experimental procedures, the solubility tests started as described in the next section.

3.2 Creation of solubility curves

The second stage of the methodology is the experimentation needed to determine the feasibility of using ILs as solvents in the recovery of ASA through crystallization.

3.2.1 Materials and experimental system

The chemicals used in the experiments were: acetylsalicylic acid (C9H8O4, laboratory- grade, used as provided), sulfuric acid (H2SO4, 95% v/v concentration), and sodium hydroxide (NaOH, pellets, 98.5% purity).

Ionic liquids were provided by Sigma-Aldrich (Toluca, México). As mentioned before, the liquids were [bmim][otf], [emim][bf4], and [emim][dep].

For the experimental procedures, we used a system consisting of a water bath with a pump and temperature control, a plate with magnetic agitation, a magnetic agitator, a jacketed beaker with water on the inside, and an amber vial.

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The experimental system, shown in Figure 5, was assembled by the crew of the Chemical Engineering Laboratory. We attached the water bath to the jacketed beaker with hoses and secured them with cable ties.

The jacketed beaker was then placed over the magnetic agitator and filled with distilled water. This water would be at the same temperature as the water bath. In the water, we placed a vial containing the study solutions, making sure the water level was above the mixture to keep the whole solution at the same temperature.

This equipment allowed us to perform the experiments at different temperatures and keep them constant or change them at our will.

Figure 5. Diagram of the experimental system

For more clarity, we also present pictures of the experimental system in Figure 6 to see the actual equipment and how it was assembled.

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Figure 6. Pictures of the equipment used during the experimental phase of the project

To proceed with the methodology, we will describe the actual solubility experiments carried out at the Chemical Engineering Laboratory.

3.2.2 Solubility Tests

The solubility experiments were aimed to create the solubility curves for the mixture of ionic liquid, water, and acetylsalicylic acid. For these experiments, we took as a starting point the process developed by Tamez-García from 2012. From his data, we also obtained the solubility of ASA in a ternary solution with water and [bmim][otf] and used it as a reference to create the oversaturation needed for the solubility tests.

These tests were performed using three ILs: [bmim][otf], [emim][dep], and [emim][bf4].

The solubility experiments were repeated 2 to 3 times at each of the temperatures included in Table 1. According to the setup temperature, the solution contained 2 mL of water, 2 mL of ionic liquid, and a varying amount of acetylsalicylic acid. We placed the solution in the water bath at the desired temperature and left it 8 hours for the acetylsalicylic acid to dissolve and reach equilibrium.

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Table 1. Experimental conditions for solubility experiments

Ionic Liquid Temperature, °C [bmim][otf] 5, 15, 25, 30, 40 [emim][dep] 5, 10, 20, 30,40, 50

[emim][bf4] 5, 10, 20, 30,40, 50

After 8 hours, we vacuum filtered the whole solution, solids from the vacuum filtration where the crystals formed in the process. We titrated the liquid from the filtration following the procedure explained in the next section.

3.2.3 Analysis of the amount of acetylsalicylic acid present in the solutions

The titration procedure required the previous preparation of both acid and base solutions.

In this subsection, first, we will explain how those solutions were prepared, and afterward, the titration process used to analyze the amount of ASA present in the solution.

3.2.3.1 Preparation of titration solutions

For the experimental procedures, we needed 0.5 N solutions of both sodium hydroxide and sulfuric acid. The sodium hydroxide solution was prepared by adding 500 mL of distilled water into a 1 L volumetric flask. Then we added 20.4237 g of sodium hydroxide pellets with a 98.5% purity. Afterward, we filled the flask with more distilled water to complete the total volume of the container. The sulfuric acid solution was prepared by adding 500 mL of distilled water into another volumetric flask. We added 13.4 mL of 95%

concentrate of sulfuric acid provided by the Laboratory, and finally, we added more distilled water to complete the volume of the new solution.

3.2.3.2 Titration procedure

The titration procedure we used gave us the information needed to calculate the solubilities and the crystallization kinetics. The information from the titrations was also

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valuable for calculating the different concentrations of acetylsalicylic acid at different times in the crystallization tests.

After the vacuum filtration, we added phenolphthalein as an indicator and 30 mL of the 0.5N solution of sodium hydroxide to the liquid taken from the reactor. We titrated the solution with a 0.5N sulfuric acid solution until the indicator changed its color from transparent to light pink.

After obtaining the data from the experiments, we used the method described in the U. S.

Pharmacopeia to determine the amount of acetylsalicylic acid dissolved in the liquid.

According to the method, there are two reactions taking place during the titration:

C9H8O4 7H4O-3 + 2Na⁺ + H2O + C2H4O2 (9)

H2SO4 2SO4 + H2O (10)

Equation (9) represents the dimerization reaction of ASA with two moles of sodium hydroxide yielding salicylate and sodium ions, water, and acetic acid.

Equation (10) is the titration reaction, where the sulfuric acid neutralizes the sodium hydroxide in the sample, which is an excess remaining from the previous reaction.

We used the data of H2SO4 needed to neutralize the solution to know how much NaOH was left in the beaker after the dimerization. This NaOH was a leftover from the first reaction, the dimerization when adding NaOH to our filtered mixture. With this information, we then knew by stoichiometry the moles of acetylsalicylic acid present in the liquid, obtaining the mass percentage of acetylsalicylic acid saturating the liquid.

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3.3 Validation of the proposed process for the purification of ASA by crystallization

The crystallization tests started by creating an oversaturation in the systems to generate solid crystals. We prepared a 5 g solution containing ASA, [bmim][otf], and distilled water for the first round of tests. The sample contained 10 g of the ternary solution consisting of 2.85 g of ASA, 3.11 g of water, and 3.99 g of ionic liquid, these masses for the solvents are equivalent to 3.1 mL of each, maintaining the 50% v/v. We placed the mixture in the experimental system and waited until the complete dissolution of the solid at 50°C. We then started the cooling in the system with a target temperature of 5°C. During the cooling time, we took samples of 1 mL every 15 minutes.

Each sample taken from the crystallizer was vacuum filtered. After the vacuum filtration, we measured the mass of both solid and liquid from the sample. Subsequently, we characterized the solid crystals with the optic microscope to reference the morphology and size of the crystals. Finally, we characterized the liquid from the filtration with the titration procedure mentioned in the previous section.

After the initial crystallization tests, we carried out tests with other ILs [emim][dep] and [emim][bf4], and the original ionic liquid in the process, [bmim][otf]. We prepared 6 g samples consistent with 0.9 g of acetylsalicylic acid and 5.1 g of solvent, 50% v/v of distilled water, and ionic liquid for these experiments. Afterward, the sample was placed in the crystallizer and cooled at 5° C for 2, 5, and 10 minutes. Finally, the samples were vacuum-filtered and characterized according to the procedures of titration and photography described in the previous section.

After the experiments, we used the information to measure the performance of the processes. This performance was calculated using (11):

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With the solubility graphs obtained from the solubility experiments and using (3), we calculated the maximum yield expected for each of the ILs in the temperatures considered for the proposed process.

As part of the evaluation, we could also estimate how long it would take for the system to reach the maximum yield, assuming the crystallization rates remained constant. The Results of these evaluations will be presented in the next chapter. Before the results, we need to review the final phase of the methodology, the proposal of an evaluation method for the greenness of the solvent.

3.4 Greenness Evaluation for the Proposed Process

For evaluating the proposed process, we started with a review of green metrics and different methods to evaluate chemical processes. From those, we took ideas to create an evaluation checklist that would provide a quick and accurate idea of the greenness of the solvent considered for the crystallization in question. For this study, the evaluation will not include the whole production process of the solvents, only the origin and its impact within the crystallization process.

The evaluation includes parameters that can be classified within the green chemistry and sustainability principles. We can see in figure 7 the categorization of the parameters into some of the principles of green chemistry and, in figure 8, how we can categorize them into the sustainability dimensions.

As mentioned in chapter 2, green chemistry has twelve main principles. From those, we took out the ones related to chemical reactions, atom economy, design of safer chemicals, use of renewable feedstocks, reduced derivatives, catalysis, and design for degradation.

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The parameters chosen for the green evaluation of the solvents used in the crystallization of ASA are yield, the origin of solvent, reuse and recycle potential, the energy required, price of solvent, cost of energy required, CO2 emissions, toxicological effects, and safety pictograms.

Figure 7. Parameters of the evaluation are sorted into the Green Chemistry principles.

The same parameters used to evaluate the greenness of the solvents can also be categorized within the dimensions of sustainable development mentioned in the second chapter. In figure 8, we can see this proposed categorization for the parameters chosen for the evaluation.

Waste Prevention

Yield of cristallization

Less hazardous chemical synthesis

GHS Pictograms Toxicological effects

Pollution Prevention

CO2 Emissions Origin of solvent

Reuse and recycle of solvent

Energy Efficiency

Energy required Price of solvent Cost of energy

Use of renewable feedstocks

Origin of solvent

Safer Solvents and Auxiliaries

GHS Pictograms

Safer Chemistry for Accident Prevention

Toxicological effects

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Figure 8. Parameters of the evaluation are sorted into the Sustainable Development principles.

The parameters are listed below, along with a short explanation of its relevance for the evaluation method developed.

The yield of crystallization. To compare different solvents for the crystallization of ASA, we need to know its overall performance in the process. This parameter represents the amount of ASA recovered during the process and will serve as a measurement for the Green Chemistry Principle of waste prevention.

Origin of solvent. The production of the solvent is included in the study using this parameter. The parameter will favor the use of renewable feedstocks, complying with its correspondent Green Chemistry principle.

Reuse and recycle potential. This parameter includes the possibility of not disposing of the solvent right after its use, therefore reducing waste and pollution within the process. The parameter will favor faster separation methods for the reuse of the solvent.

Energy required. This parameter will compare and quantify the amount of energy needed for the heating or cooling needed in the crystallization process. The Green Chemistry principle included within this parameter is the design for energy efficiency.

Environmental

Origin of Solvent Reuse and recycle CO2 emissions Yield of crystallization Energy Efficiency

Social

Toxicological effects GHS Pictograms

Economical

Price of solvent Energy cost Energy efficiency

List of figures

Abstract

List of figures

List of tables

Contents

1 Introduction

2 Theoretical Framework

3 Methodology