# On the Design of Aqueous Emulsions of Colophony Resin

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Equipment Characterization

#### 2.1. Materials

#### 2.2. Experimental Equipment and Procedure

#### 2.3. Quality Characterization Equipment

^{TM}pH meter, Mettler Toledo, Greifensee, Switzerland. The solid content was measured using gravimetric analysis with a precision balance. The particle size was measured using a Malvern Zetasizer Nano ZS, Malvern, Worcestershire, United Kingdom system, which provided both the particle size distribution (PSD) and the cumulative distribution curves.

## 3. Development Approach and Related Tools

#### 3.1. Overall Quality Performance Metric

#### 3.2. Design Procedure

`JMP`

^{®}can be used for the design and data analysis [43]. The results of Stage 1 included a set of primary factors and levels that could optimize quality performance and this combination of factors and levels was fixed in the second stage.

## 4. Results

#### 4.1. The Design Problem

#### 4.2. Screening of Primary Factors

#### 4.3. Optimization of Secondary Factors

#### 4.4. Formulations’ Repeatability

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Conflicts of Interest

## References

- Zhang, L.; Mao, H.; Liu, Q.; Gani, R. Chemical product design—Recent advances and perspectives. Curr. Opin. Chem. Eng.
**2020**, 27, 22–34. [Google Scholar] [CrossRef] - Harmsen, J.; de Haan, A.B.; Swinkels, P.L. Product and Process Design; De Gruyter: Berlin, Germany, 2018. [Google Scholar]
- Cussler, E.L.; Moggridge, G.D. Chemical Product Design, 2nd. ed.; Cambridge University Press: Cambridge, UK, 2011. [Google Scholar]
- Lee, J.; Suckling, J.R.; Lilley, D.; Wilson, G.T. What is ‘value’and how can we capture it from the product value chain? In Sustainability through Innovation in Product Life Cycle Design; Springer: Berlin/Heidelberg, Germany, 2017; pp. 297–313. [Google Scholar] [CrossRef] [Green Version]
- Zinkel, D.; Russell, J. Naval Stores. Production, Chemistry, Utilization. Pulp Chemicals Association; Pulp Chemicals Association Inc.: New York, NY, USA, 1989; 1059p. [Google Scholar]
- Kugler, S.; Ossowicz, P.; Malarczyk-Matusiak, K.; Wierzbicka, E. Advances in rosin-based chemicals: The latest recipes, applications and future trends. Molecules
**2019**, 24, 1651. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Panda, H. Handbook on Oleoresin and Pine Chemicals (Rosin, Terpene Derivatives, Tall Oil, Resin & Dimer Acids); Asia Pacific Business Press Inc.: Delhi, India, 2008. [Google Scholar]
- Aldas, M.; Ferri, J.; Lopez-Martinez, J.; Samper, M.D.; Arrieta, M.P. Effect of pine resin derivatives on the structural, thermal, and mechanical properties of Mater-Bi type bioplastic. J. Appl. Polym. Sci.
**2020**, 137, 48236. [Google Scholar] [CrossRef] - Yan, J.; Chen, G.X.; Wen, S.S.; Cui, X.M.; Qu, Z.C. Study on Synthesis and Paper-Plastic Composite Property of Maleic Rosin Modified Acrylic Resin. Adv. Mater. Res.
**2011**, 174, 462–465. [Google Scholar] [CrossRef] - Dehm, K.E.; Walter, T.; Weichselgartner, M.; Crisp, R.W.; Wommer, K.; Aust, M.; Vogel, N. Sustainable repellent coatings based on renewable drying and nondrying oils. Adv. Mater. Interfaces
**2022**, 10, 2202032. [Google Scholar] [CrossRef] - Haapakorva, E.; Holmbom, T.; von Wright, A. Novel aqueous oil-in-water emulsions containing extracts of natural coniferous resins are strongly antimicrobial against enterobacteria, staphylococci and yeasts, as well as on bacterial biofilms. J. Appl. Microbiol.
**2018**, 124, 136–143. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Hayashi, S.; Kim, H.J.; Kajiyama, M.; Ono, H.; Mizumachi, H.; Zufu, Z. Miscibility and pressure-sensitive adhesive performances of acrylic copolymer and hydrogenated rosin systems. J. Appl. Polym. Sci.
**1999**, 71, 651–663. [Google Scholar] [CrossRef] - Petrie, E.M. Handbook of Adhesives and Sealants; McGraw-Hill Education: New York, NY, USA, 2007. [Google Scholar]
- Unger, A.; Schniewind, A.P.; Unger, W. Adhesives and gap fillers. In Conservation of Wood Artifacts: A Handbook; Springer: Berlin/Heidelberg, Germany, 2001; pp. 541–560. [Google Scholar] [CrossRef]
- Creton, C. Pressure-Sensitive Adhesives: An introductory course. MRS Bull.
**2003**, 28, 434–439. [Google Scholar] [CrossRef] [Green Version] - Satas, D. Handbook of Pressure Sensitive Adhesive Technology; Springer: Berlin/Heidelberg, Germany, 1989; Volume 1. [Google Scholar]
- Korpman, R. Hot Melt Adhesive Composition and Tape. US Patent US19501571A, 17 October 1973. [Google Scholar]
- Czech, Z.; Kowalczyk, A. Pressure-Sensitive Adhesives for Medical Applications. In Wide Spectra of Quality Control; Akyar, I., Ed.; IntechOpen: Rijeka, Croatia, 2011; Chapter 17. [Google Scholar] [CrossRef] [Green Version]
- Schmid, J.J.; Booth, J.W. Method for Producing Tackifier Resins. US Patent US5051481, 24 September 1991. [Google Scholar]
- Kim, B.J.; Kim, S.E.; Do, H.S.; Kim, S.; Kim, H.J. Probe tack of tackified acrylic emulsion PSAs. Int. J. Adhes. Adhes.
**2007**, 27, 102–107. [Google Scholar] [CrossRef] - Aydin, O.; Kroner, H.; Wistuba, E.; Fickeisen, P. Preparation of Solvent-Free Aqueous Polymer and Tackifier Dispersions. US Patent US5534571A, 30 May 1995. [Google Scholar]
- Geoghegan, J.T.; Wang, L.S. Surfactant for Forming Stable Dispersions of Rosin Esters. US Patent US6274657B1, 14 August 2001. [Google Scholar]
- Boonstra, L.J.; Adriaanse, C.C.A.; Hofbauer, M.; Maas, J.H. Emulsifiers for Use in Water-Based Tackifier Dispersions. EU Patent EP1957595A2, 20 August 2008. [Google Scholar]
- Miller, P.J. Tackifier Dispersions with Improved Humid Age Performance. WO Patent WO2007124049A3, 24 April 2008. [Google Scholar]
- Aarts, P.P.M.; Houben, L.J.H.; Hazen, J. Tackifier Dispersion. US Patent US9023929B2, 5 May 2015. [Google Scholar]
- Yang, M.; Gu, W.; Qu, Z.; Liang, Y. A Tackifier and a Continuous Process for Producing the Tackifier. US Patent US20170313913A1, 28 January 2020. [Google Scholar]
- Ulrich, K.T.; Eppinger, S.D. Product Design and Development, 6th ed.; McGraw-Hill: New York, NY, USA, 2016. [Google Scholar]
- Rodrigues, A.; Cussler, E.L. Teaching chemical product design. Educ. Chem. Eng.
**2016**, 14, 43–48. [Google Scholar] [CrossRef] - Fowlkes, W.; Creveling, C. Engineering Methods for Robust Design. Using Taguchi Methods in Tecnology and Product Development, 1st ed.; Addison Wesley Publishing Company: Boston, MA, USA, 1995. [Google Scholar]
- Taguchi, G.; Elsayed, E.A.; Hsiang, T.C. Quality Engineering in Production Systems; McGraw-Hill College: New York, NY, USA, 1989. [Google Scholar]
- Standard ASTM D1525-17; Standard Test Method for Vicat Softening Temperature of Plastics. ASTM International: West Conshohocken, PA, USA, 2017.
- Sheth, J.N.; Sethia, N.K.; Srinivas, S. Mindful consumption: A customer-centric approach to sustainability. J. Acad. Mark. Sci.
**2011**, 39, 21–39. [Google Scholar] [CrossRef] - Mitra, A. Fundamentals of Quality Control and Improvement; Wiley: Hoboken, NJ, USA, 2016. [Google Scholar]
- Liao, C.N.; Kao, H.P. Supplier selection model using Taguchi loss function, analytical hierarchy process and multi-choice goal programming. Comput. Ind. Eng.
**2010**, 58, 571–577. [Google Scholar] [CrossRef] - Dupačová, J.; Gaivoronski, A.; Kos, Z.; Szántai, T. Stochastic programming in water management: A case study and a comparison of solution techniques. Eur. J. Oper. Res.
**1991**, 52, 28–44. [Google Scholar] [CrossRef] - Belton, V.; Stewart, T.J. Value Function Methods: Practical Basics. In Multiple Criteria Decision Analysis: An Integrated Approach; Springer: Boston, MA, USA, 2002; pp. 119–161. [Google Scholar] [CrossRef]
- Liesiö, J. Measurable multiattribute value functions for portfolio decision analysis. Decis. Anal.
**2014**, 11, 1–82. [Google Scholar] [CrossRef] [Green Version] - Keeney, R.L. Value-Focused Thinking: A Path to Creative Decision Making; Harvard University Press: Cambridge, MA, USA, 1996. [Google Scholar]
- Duarte, B.P.M.; Reis, A. Developing a projects evaluation system based on multiple attribute value theory. Comput. Oper. Res.
**2006**, 33, 1488–1504. [Google Scholar] [CrossRef] - Wang, Y.F.; Roohi, S.F.; Hu, X.M.; Xie, M. Investigations of human and organizational factors in hazardous vapor accidents. J. Hazard. Mater.
**2011**, 191, 69–82. [Google Scholar] [CrossRef] [PubMed] - Cox, D.R.; Reid, N. The Theory of the Design of Experiments; Chapman and Hall/CRC: Boca Raton, FL, USA, 2000. [Google Scholar]
- Montgomery, D.C. Design and Analysis of Experiments; John Wiley & Sons: Hoboken, NJ, USA, 2017. [Google Scholar]
- Institute, S.A.S. JMP Statistical Discovery from SAS Version 14 JSL Syntax Reference; JMP, A Business Unit of SAS: Cary, NC, USA, 2018. [Google Scholar]
- Box, G.E.P.; Hunter, W.G. Sequential design of experiments for nonlinear models. In Proceedings of the IBM Scientific Computing Symposium: Statistics; Kort, J.J., Ed.; IBM: White Plains, NY, USA, 1965; pp. 113–137. [Google Scholar]
- Goujot, D.; Meyer, X.; Courtois, F. Identification of a rice drying model with an improved sequential optimal design of experiments. J. Process. Control.
**2012**, 22, 95–107. [Google Scholar] [CrossRef] [Green Version] - Fox, J. Applied Regression Analysis and Generalized Linear Models; Sage Publications: Singapore, 2015. [Google Scholar]
- Duarte, B.P.M.; Atkinson, A.C.; Granjo, J.F.O.; Oliveira, N.M.C. A model-based framework assisting the design of vapor-liquid equilibrium experimental plans. Comput. Chem. Eng.
**2021**, 145, 107168. [Google Scholar] [CrossRef]

**Figure 1.**The state of the resin during the process (

**a**) as a (solid) raw material; (

**b**) after heating to the softening point; (

**c**) as a resin-in-water emulsion.

**Figure 2.**Systematic procedure for hierarchically organizing the experimental work in a customer-centric approach.

Resin Designation | ${\mathit{T}}_{\mathbf{soft}}$ (${}^{\circ}\mathbf{C}$) |
---|---|

A | 60 |

B | 70 |

C | 80 |

Quality Characteristic | Lower Specification | Upper Specification | Target Value | Loss Function |
---|---|---|---|---|

Viscosity (@ 25 ${}^{\circ}\mathrm{C}$) | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ | 1000 cP | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ | smaller-is-better |

pH | 7 | 9 | 8 | target-is-best |

Solid content | 54 %wt | 56 %wt | 55 %wt | target-is-best |

Particle diameter | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ | 1000 nm${}^{\phantom{\rule{3.33333pt}{0ex}}\u2021}$ | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ | smaller-is-better |

^{†}undefined;

^{‡}95% of particles below 1000 nm.

Quality Characteristic | Normalized Loss Function | Weight (${\mathit{w}}_{\mathit{i}}$) |
---|---|---|

Viscosity (@ 25 ${}^{\circ}\mathrm{C}$) | ${L}^{\mathrm{norm}}\left({C}_{1}\right)=1\times {10}^{-6}\phantom{\rule{3.33333pt}{0ex}}{C}_{1}^{2}$ | 0.30 |

pH | ${L}^{\mathrm{norm}}\left({C}_{2}\right)={({C}_{2}-8)}^{2}$ | 0.15 |

Solid content | ${L}^{\mathrm{norm}}\left({C}_{3}\right)={({C}_{3}-55)}^{2}$ | 0.05 |

Particle diameter | ${L}^{\mathrm{norm}}\left({C}_{4}\right)=1\times {10}^{-6}\phantom{\rule{3.33333pt}{0ex}}{C}_{4}^{2}$ | 0.50 |

Factor | Level | Characterization | Designat. |
---|---|---|---|

$-1$ | Resin with ${T}_{\mathrm{soft}}=60{}^{\circ}\mathrm{C}$ | A1 | |

${x}_{1}$ | 0 | Resin with ${T}_{\mathrm{soft}}=70{}^{\circ}\mathrm{C}$ | A2 |

$+1$ | Resin with ${T}_{\mathrm{soft}}=80{}^{\circ}\mathrm{C}$ | A3 | |

$-1$ | Surfactant from S1 | S1 | |

${x}_{2}$ | 0 | Surfactant from S2 | S2 |

$+1$ | Surfactant from S3 | S3 |

# Exper. | ${\mathit{x}}_{1}$ | ${\mathit{x}}_{2}$ | Designat. | ${\mathit{C}}_{1}$ (cP) | ${\mathit{C}}_{2}$ (-) | ${\mathit{C}}_{3}$ (%wt) | ${\mathit{C}}_{4}$ (nm) | ${\mathit{d}}_{95}$ (nm) | ${\mathit{C}}_{5}$ | O |
---|---|---|---|---|---|---|---|---|---|---|

1 | $-1$ | $-1$ | A1:S1_1 | 1562 | 11.04 | 54.36 | 209.6 | 310.45 | 0 | 2.161 |

2 | $-1$ | 0 | A1:S2_1 | 265 | 8.63 | 55.11 | 428.2 | 1029.93 | 0 | 0.173 |

3 | $-1$ | $+1$ | A1:S3_1 | 1292 | 11.19 | 54.58 | 614.9 | 1302.51 | 1 | 2.225 |

4 | 0 | $-1$ | A2:S1_1 | 187 | 10.28 | 55.62 | 444.3 | 4246.54 | 1 | 0.908 |

5 | 0 | 0 | A2:S2_1 | 339 | 8.46 | 54.34 | 262.7 | 695.22 | 0 | 0.123 |

6 | 0 | $+1$ | A2:S3_1 | - | - | - | - | - | - | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ |

7 | $+1$ | $-1$ | A3:S1_1 | - | - | - | - | - | - | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ |

8 | $+1$ | 0 | A3:S2_1 | 112 | 8.55 | 54.44 | 615.5 | 1064 | 1 | 0.254 |

9 | $+1$ | $+1$ | A3:S3_1 | - | - | - | - | - | - | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ |

^{†}non-dispersed formulations.

Optimization of Emulsion A1:S1 (${\mathit{x}}_{1}=-1$, ${\mathit{x}}_{2}=-1$) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|

# Exper. | ${\mathit{x}}_{\mathbf{3}}$ (%wt) | ${\mathit{x}}_{\mathbf{4}}$ (rpm) | ${\mathit{x}}_{\mathbf{5}}$ (%wt) | Designat. | ${\mathit{C}}_{\mathbf{1}}$ (cP) | ${\mathit{C}}_{\mathbf{2}}$ (-) | ${\mathit{C}}_{\mathbf{3}}$ (%wt) | ${\mathit{C}}_{\mathbf{4}}$ (nm) | ${\mathit{C}}_{\mathbf{5}}$ | $\mathit{O}$ |

1 | 2.0 | 100 | 7.0 | A1:S1_1 | 1562 | 11.04 | 54.36 | 209.6 | 0 | 2.161 |

10 | 2.5 | 100 | 7.0 | A1:S1_2 | 5967 | 10.11 | 55.02 | 150.0 | 0 | 11.361 |

11 | 0.0 | 100 | 7.0 | A1:S1_3 | - | - | - | - | - | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ |

12 | 1.0 | 100 | 7.0 | A1:S1_4 | 440 | 10.19 | 54.44 | 261.1 | 0 | 0.827 |

13 | 1.0 | 100 | 6.0 | A1:S1_5 | 429 | 10.14 | 55.92 | 319.0 | 0 | 0.835 |

14 | 0.5 | 100 | 7.0 | A1:S1_6 | - | - | - | - | - | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ |

15 | 0.5 | 100 | 10.5 | A1:S1_7 | 235 | 8.99 | 54.68 | 1007.7 | 1 | 0.676 |

16 | 0.5 | 100 | 14.0 | A1:S1_8 | 172 | 8.28 | 55.46 | 209.4 | 0 | 0.053 |

Optimization of emulsion A1:S2 (${x}_{1}=-1$, ${x}_{2}=0$) | ||||||||||

2 | 2 | 100 | 7.0 | A1:S2_1 | 265 | 8.63 | 55.11 | 428.2 | 0 | 0.173 |

17 | 2.5 | 100 | 7.0 | A1:S2_2 | 352 | 8.36 | 54.30 | 236.2 | 0 | 0.109 |

18 | 2.0 | 50 | 7.0 | A1:S2_3 | 392 | 8.62 | 55.92 | 231.1 | 0 | 0.173 |

19 | 1.0 | 50 | 7.0 | A1:S2_4 | - | - | - | - | - | ns${}^{\phantom{\rule{3.33333pt}{0ex}}\u2020}$ |

20 | 1.5 | 50 | 7.0 | A1:S2_5 | 131 | 8.05 | 54.91 | 205.53 | 0 | 0.027 |

Optimization of emulsion A2:S2 (${x}_{1}=0$, ${x}_{2}=0$) | ||||||||||

5 | 2.0 | 100 | 7.0 | A2:S2_1 | 339 | 8.46 | 54.34 | 262.7 | 0 | 0.123 |

21 | 2.5 | 100 | 7.0 | A2:S2_2 | 308 | 8.35 | 54.58 | 341.3 | 0 | 0.114 |

22 | 2.0 | 50 | 7.0 | A2:S2_3 | 337 | 8.70 | 54.96 | 350.6 | 0 | 0.169 |

23 | 1.0 | 50 | 7.0 | A2:S2_4 | 87 | 6.96 | 54.94 | 245.5 | 0 | 0.195 |

24 | 1.5 | 50 | 7.0 | A2:S2_5 | 118 | 7.94 | 54.98 | 210.5 | 0 | 0.027 |

^{†}non-dispersed formulations.

# Exper. | Designat. | ${\mathit{x}}_{1}$ (-) | ${\mathit{x}}_{2}$ (-) | ${\mathit{x}}_{3}$ (%wt) | ${\mathit{x}}_{4}$ (rpm) | ${\mathit{x}}_{5}$ (%wt) |
---|---|---|---|---|---|---|

16 | A1:S1_8 | $-1$ | $-1$ | 0.5 | 100 | 14.0 |

20 | A1:S2_5 | $-1$ | 0 | 1.5 | 50 | 7.0 |

24 | A2:S2_5 | 0 | 0 | 1.5 | 50 | 7.0 |

Repeatability of Emulsion A1:S1 (${\mathit{x}}_{1}=-1$, ${\mathit{x}}_{2}=-1$, ${\mathit{x}}_{3}=$ $0.5$ %wt, ${\mathit{x}}_{4}=$ 100 rpm, ${\mathit{x}}_{5}=$ $14.0$ %wt) | |||||||
---|---|---|---|---|---|---|---|

# Exper. | Designat. | ${\mathit{C}}_{\mathbf{1}}$ (cP) | ${\mathit{C}}_{\mathbf{2}}$ (-) | ${\mathit{C}}_{\mathbf{3}}$ (%wt) | ${\mathit{C}}_{\mathbf{4}}$ (nm) | ${\mathit{C}}_{\mathbf{5}}$ | $\mathit{O}$ |

16 | A1:S1_8 | 172 | 8.25 | 55.46 | 209.43 | 0 | 0.051 |

25 | A1:S1_9 | 236 | 8.61 | 54.27 | 460.97 | 0 | 0.205 |

26 | A1:S1_10 | 231 | 8.42 | 54.43 | 448.80 | 0 | 0.159 |

27 | A1:S1_11 | 237 | 8.39 | 55.07 | 449.25 | 0 | 0.141 |

${\overline{x}}_{{C}_{i}}$ | 219.00 | 8.42 | 54.81 | 392.11 | |||

${s}_{{C}_{i}}$ | 31.44 | 0.15 | 0.56 | 121.92 | |||

${C}_{v,i}\phantom{\rule{3.33333pt}{0ex}}(\%)$ | 14.36 | 1.76 | 1.01 | 31.09 | |||

Repeatability of emulsion A1:S2 (${x}_{1}=-1$, ${x}_{2}=0$, ${x}_{3}=$ $1.5$ %wt, ${x}_{4}=$ 50 rpm, ${x}_{5}=$ $7.0$ %wt) | |||||||

20 | A1:S2_5 | 131 | 8.05 | 54.91 | 205.53 | 0 | 0.027 |

28 | A1:S2_6 | 132 | 7.96 | 55.26 | 206.35 | 0 | 0.030 |

29 | A1:S2_7 | 132 | 8.04 | 54.84 | 202.35 | 0 | 0.027 |

30 | A1:S2_8 | 128 | 8.01 | 54.87 | 196.25 | 0 | 0.025 |

${\overline{x}}_{{C}_{i}}$ | 130.75 | 8.02 | 54.97 | 202.62 | |||

${s}_{{C}_{i}}$ | 1.89 | 0.04 | 0.20 | 4.58 | |||

${C}_{v,i}\phantom{\rule{3.33333pt}{0ex}}(\%)$ | 1.45 | 0.50 | 0.36 | 2.26 | |||

Repeatability of emulsion A2:S2 (${x}_{1}=0$, ${x}_{2}=0$, ${x}_{3}=$ $1.5$ %wt, ${x}_{4}=$ 50 rpm, ${x}_{5}=$ $7.0$ %wt) | |||||||

24 | A2:S2_5 | 118 | 7.94 | 54.98 | 210.5 | 0 | 0.027 |

31 | A2:S2_6 | 108 | 7.89 | 55.31 | 208.57 | 0 | 0.032 |

32 | A2:S2_7 | 112 | 7.95 | 54.66 | 219.48 | 0 | 0.034 |

33 | A2:S2_8 | 106 | 7.82 | 54.15 | 215.65 | 0 | 0.068 |

${\overline{x}}_{{C}_{i}}$ | 111.00 | 7.90 | 54.78 | 213.55 | |||

${s}_{{C}_{i}}$ | 5.29 | 0.06 | 0.49 | 4.96 | |||

${C}_{v,i}\phantom{\rule{3.33333pt}{0ex}}(\%)$ | 4.77 | 0.75 | 0.90 | 2.32 |

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## Share and Cite

**MDPI and ACS Style**

Ingrez, I.B.D.; Ferreira, P.C.N.; Gameiro, D.; Duarte, B.P.M.
On the Design of Aqueous Emulsions of Colophony Resin. *Polymers* **2023**, *15*, 1691.
https://doi.org/10.3390/polym15071691

**AMA Style**

Ingrez IBD, Ferreira PCN, Gameiro D, Duarte BPM.
On the Design of Aqueous Emulsions of Colophony Resin. *Polymers*. 2023; 15(7):1691.
https://doi.org/10.3390/polym15071691

**Chicago/Turabian Style**

Ingrez, Isa B. D., Paula C. N. Ferreira, Davide Gameiro, and Belmiro P. M. Duarte.
2023. "On the Design of Aqueous Emulsions of Colophony Resin" *Polymers* 15, no. 7: 1691.
https://doi.org/10.3390/polym15071691