Impact of water and oleic acid on glycerol monooleate phase transition and bi-continuous structure formation in white oil†

Ngoc A. Nguyen ^a, Deborah Y. Liu ^ab and Daniel V. Krogstad *^ab
aIllinois Applied Research Institute, University of Illinois Urbana Champaign, IL 61801, USA. E-mail: dkrogsta@illinois.edu
^bDepartment of Materials Science and Engineering, University of Illinois Urbana Champaign, IL 61801, USA

First published on 30th August 2024

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Introduction

There is a critical need to transition away from fossil fuels towards increased utilization of biofeedstocks for fuel production.^1–3 While there has been demonstrated success in creating biofuels from a variety of biofeedstocks, the natural macromolecular complexity of these feedstocks, which commonly contain various functional groups such as ester linkages, carboxylic acids, and alcohols, results in significant differences in the molecular interactions and potential chemical reactions of these biomolecules relative to traditional petroleum feedstocks. A detailed understanding of these potential interactions is needed to increase the efficiency and safety of these production pathways.

Current methods of biofuel production, which focus on the co-processing of glyceride-based biofeedstocks with traditional feedstocks, require that the glycerides undergo hydrolysis reactions to create linear molecules. Triglycerides, which are the primary form found in food-grade oils such as soybean oil, undergo hydrolysis at high temperature resulting in the eventual breakdown of the triglycerides into three fatty acid molecules and a glycerol molecule. Our previous study showed that the hydrolysis reactions were found to occur over a 10-hour period when held in an autoclave at 325 °C without catalysts.⁴ However, as a consequence of these hydrolysis reactions, a large amount of fatty acids are created which can result in significant corrosion to the steel refinery infrastructure. Indeed, the corrosion rate of steel specimens held within the autoclaves peaked at approximately 10 hours, when the fatty acid concentration was highest. Our work also showed that the hydrolysis reactions resulted in the formation of diglyceride and monoglyceride molecules as intermediate products during the hydrolysis reactions. These molecules, especially the monoglycerides, are highly amphiphilic and are known to be able to self-assemble into reverse micelles in nonpolar solvents under some conditions.^5–11

Micelles are formed through the self-assembly of amphiphilic molecules in various solvent systems.^12–14 These amphiphilic molecules typically comprise a hydrophilic headgroup and one or two hydrophobic tails. Depending on how these heads and tails assemble, micelles can take on various shapes, sizes, and distributions commonly influenced by factors such as molecular structure, solvent characteristics, concentrations, temperatures, and the presence of additives.¹⁴ Normal phase micelles, in which the hydrophobic tails point to the core of the micelles, form when the amphiphiles are dissolved in water. Reverse micelles, which have hydrophilic headgroups pointing towards the center, form when the amphiphiles are dissolved in nonpolar solvents (see Fig. 1a and 2). Micelles find diverse applications in industries such as biomedicine,^15–17 food processing,^18–20 paints and coatings,^21,22 the oilfield sector,^23,24 catalysis,^25–27 and corrosion protection.^28–30

Several existing studies have explored the phase boundaries of monoglyceride reverse micelles.^7–10 For example, Shrestha et al. found that swapping the nonpolar solvent from hexane to hexadecane induced changes in the shape of a glycerol monooleate (GMO) micelle.¹⁰ Additional research with various monoglycerides found that aggregation numbers increased with increased polar solvent or decreased temperature.^7–9 However, there has been limited experimental work in studying the self-assembly and stability of the molecules in white oil over broad concentration and temperature ranges. Indeed, many of the previous studies used volatile organic solvents as the nonpolar solution, preventing elevated temperature studies.

The effects of contaminant species, such as water and fatty acids, on the micelle formation are also underexplored in the literature. These molecules are present in biofeedstock processing and potentially affect the self-assembly of other amphiphilic systems due to their natural hydrophilicity.^4,31 For example, water is critically important in controlling the self-assembled structures, and is the primary factor determining whether small reverse micelles or larger microemulsions are formed.³² Specifically, the primary differentiation of the systems is the freedom of the water molecules that are in the polar core of the assemblies, which is a function of the water concentration.³² Additionally, fatty acids are frequently incorporated into water in oil emulsions as co-surfactants to adjust the material properties such as morphological and rheological properties.³³

The objective of this study was to identify the monoglyceride concentrations and temperatures at which reverse micelles form in white oil and explore how those conditions changed with the addition of water or fatty acids, as typically exist during biofeedstock processing. By investigating these conditions, we aim to understand and inform the future design of biofeedstock mixtures and processing conditions to reduce the corrosivity of the intermediate solutions during feedstock processing. Specifically, if the conditions could be designed so that the polar and reactive species can be sequestered within reverse micelles, they become unavailable for reaction with their surroundings and are thus neutralized from acting as corrosive agents. By utilizing an amphiphile already present in a biofeedstock, we can inform the design of blends that do not require new considerations for process chemistry.

Experimental

Materials

GMO containing over 95% of 1-oleyol glycerol was purchased from Sigma-Aldrich and Cayman Chemical and used interchangeably. Oleic acid and white mineral oil were obtained from Sigma-Aldrich and bp, respectively. The materials were used as received.

Sample preparation

GMO and white oil were placed in a vial, heated, and stirred on a hot plate at approximately 60 °C until the GMO was completely melted and dissolved in the white oil. Additional materials, such as water or fatty acids, were then added to the GMO/white oil mixture and stirred continuously on the hot plate until the sample appeared homogeneous. The samples were subsequently loaded into quartz capillaries using a syringe fitted with a long 22 Ga needle for characterization by small-angle X-ray scattering (SAXS).

Small-angle X-ray scattering (SAXS)

Small-angle X-ray scattering (SAXS) experiments were conducted using beamline 12-ID-C at the advanced photon source, Argonne National Laboratory. The beamline was operated at a wavelength of 18 keV, a sample-to-detector distance of 2.215 m, a q range of 7.75 × 10⁻³ to 1.1 Å⁻¹, and a measurement time of 1 s. The experiments were conducted in a temperature-controlled environment, enabling the study of the morphological characteristics of the GMO solutions across various temperatures. The heating and cooling processes were managed using a resistance-heated block and a nitrogen-cooled block, respectively. Each composition was tested at different temperatures during a temperature ramp-up (from 15 °C to 150 °C at 1.5 °C min⁻¹) and a cooling process (from 150 °C to 15 °C). The specific sample compositions and testing temperatures are discussed appropriately in the Results and discussion section.

The data were processed and integrated into 1-D line scans using custom Matlab scripts written by the beamline staff of Sector 12 at the Argonne APS. The scattering of empty cells and white oil was measured and used for background subtraction of the data used for fitting. Fitting of the experimental data to Guinier–Porod and Teubner–Strey models was performed using the SasView.³⁴

The Guinier–Porod model is used to determine the shape and size of scattering objects, ranging from symmetric to asymmetric objects, including spheres, rods, and platelets or their intermediate shapes (additional details can be found in SasView documentation).³⁴ The scattering intensity of objects is determined by eqn (1).

	(1)

where

	(2)

and

	(3)

The parameter s represents the dimension variable, R_g stands for the radius of gyration, and m denotes the Porod exponent. Spherical or three-dimensional globular objects are characterized by s equal to 0. Rods and platelets correspond to s equal to 1 and 2, respectively.

In some conditions, the Porod model did not produce a good fit for the data, and instead, we used the Teubner–Strey model (eqn (4)) to analyze the morphology formation of a two-component system. One characteristic feature of this model is the presence of a peak in the scattering data (additional details can be found in SasView documentation).³⁴

	(4)

where

	(5)

The domain size or periodicity of the two-component morphology system is defined by d, and xi is the correlation length.

Results and discussion

In situ SAXS measurements on a wide range of GMO (Fig. 1a) compositions in white oil, ranging from 0.01 wt% to 25 wt%, with temperatures varying from 15 °C to 150 °C were performed to understand the structural formation of GMO in white oil. Examples provided in Fig. 1b and c show the SAXS results of two selected compositions: 0.1 wt% GMO and 5 wt% GMO in white oil, presenting line scans of intensity as a function of scattering vector Q. Line scans of the pure white oil and other GMO concentrations at various temperatures are presented in Fig. S1 and S2, respectively (see the ESI†).

GMO is a semi-crystalline amphiphilic compound containing a long unsaturated monoglyceride chain as illustrated in Fig. 1a. Pure GMO is white and waxy at room temperature due to its relatively low melting point, approximately 35.5 °C.³⁵Fig. 1b displays the scattering data of 0.1 wt% GMO in white oil, in which no structural or crystalline features are visible at any temperature. This indicates that the GMO molecules are fully dissolved within the white oil at temperatures as low as 15 °C, which is below its melting point (35.5 °C). At low concentrations of GMO, the solubility in white oil is sufficient to prevent the formation of lamellar crystalline structures or self-assembled micelles. The entropic gain from the disordered state of GMO in white oil likely outweighs the interactions between GMO molecules that drive aggregation.

On the other hand, at a higher concentration, 5 wt% GMO in white oil, clear phase changes of the sample at different temperatures are evident as shown in Fig. 1c. Sharp scattering peaks (Q* = 0.1275 Å⁻¹, with a spacing of Q*, 2Q*, 3Q*, etc.) are visible for the sample at 15 °C, indicating that the GMO remains crystalline and in a lamellar configuration. However, when the temperature increases to 30 °C, the long-range structures melt. Instead, the appearance of a shoulder in a Q range from 0.01 to 0.3 Å⁻¹ (see the black arrow) indicates the formation of GMO micelles or aggregates. This transition is defined as the Krafft temperature.³⁶

The micelles remained present up to a temperature of 90 °C (Fig. 1c). No structural features were observed at temperatures above 90 °C (the vanishing of the scattering shoulder within the Q range from 0.01 to 0.3 Å⁻¹), which indicates a critical micelle temperature (CMT) for the reverse micelles. Above the CMT, the GMO is fully soluble in the white oil. We conducted SAXS measurements of the sample during both heating and cooling. The formation and removal of GMO micelles in white oil are reversible with temperatures. Additionally, these scattering results during the temperature ramps demonstrate that GMO micelles can reach an equilibrium state quickly within the examined temperature range since the ramp rates were very quick (∼1.5 °C min⁻¹) and the discrepancies in the transition temperature were within 2–5 °C depending on the temperature ramp direction.

We utilized the in situ SAXS results to construct a phase diagram of GMO in white oil as a function of composition (0.01 wt% to 25 wt% GMO in white oil) and temperature (15 °C to 150 °C) (Fig. 2b). The phase transition of GMO, from a lamellar crystalline state to micelles at the Krafft temperature, and then to dissolution/solution in white oil at the CMT is illustrated in Fig. 2a. The temperatures of these phase transitions depend on the GMO concentration (Fig. 2b). The scattering results show that at low concentrations, ≤0.1 wt%, GMO is completely soluble in the white oil (solution phase), as denoted by the black lines (Fig. 2b). The room temperature solubility limit exists somewhere between 0.1 wt% to 1 wt% GMO. At or above 1 wt% GMO, both crystalline and micelle phases are present depending on the temperature. The Krafft temperature remains relatively stable at ca. 25–30 °C, independent of the GMO concentration. The CMT, however, significantly increased as the GMO content increased. For example, at 5 wt% GMO, the CMT is ca. 90 °C, while the CMT temperature of 10 wt% is around 135 °C. Remarkably, the 25 wt% GMO sample had a CMT above the tested temperature range (150 °C). The abundant GMO molecules provided durable intermolecular interactions that require much higher thermal energy to break down their strong association in white oil.

In this study, we selected a 5 wt% GMO solution as the model composition to understand micelle characteristics and the effects of water and fatty acid on micelle formation. This choice was made because this composition forms micelles over a narrow temperature range, approximately from 30 °C to 90 °C, in comparison to the 10 wt% and 25 wt% GMO samples. It is also worth noting that the 1 wt% GMO sample exhibited a very narrow phase transition region, as illustrated in Fig. 2, which would make it difficult to assess any changes associated with the added fatty acid and water concentrations.

To better understand the nature of the micelle size and shape, the SAXS data obtained at different temperatures of a 5 wt% GMO sample were analyzed. The background data due to scattering from the air and the capillary were subtracted from the raw data, and the background-subtracted data were plotted (vertically shifted) and fit with the Guinier–Porod model using SasView (Fig. 3a). Model details were provided in the Experimental section. The scattering profiles exhibit shoulders within a Q range from 0.1–0.3 Å⁻¹, indicated by a blue arrow in Fig. 3a. There is a peak shift from a low Q to a higher Q value when the temperature increases, corresponding to a decrease in the reverse micelle size as the temperature increases. Our analysis indicated that the Guinier–Porod model is the best-fit model representing the structural characteristics of the micelles. The fit results are presented in Fig. 3b. These results show a decrease in R_g of the micelles, from approximately 9 Å to 7 Å, with an increase in temperature. These values are slightly lower than the R_g values (∼11–17 Å) of GMO in n-heptane and toluene that were determined by Bradley-Shaw et al.¹¹ This difference in R_g likely comes from concentration and structural differences between white oil and n-heptane and toluene that favor different molecular interactions of GMO with the medium solvent. Their study suggested that the swelling effect and the penetration of the solvent into the hydrophobic tails of the reverse micelles influence their size at room temperature. We anticipate that at higher temperatures, GMO molecules had a reduced driving force for assembly and were more soluble in the solution, resulting in a decrease in the number of molecules present within the reverse micelles, and thus a decrease in R_g.³⁷

In our previous study, we demonstrated that the corrosion process during biofeedstock treatment was found to produce water as a byproduct.⁴ Therefore, understanding the role of water in the self-assembly of GMO molecules is vital. Here, we formulated samples containing 5 wt% GMO in white oil with various water content ranging from 0 wt% to 1 wt%. The effect of water on the phase transition characteristics of GMO in white oil is presented in Fig. 4 and Fig S3 (ESI†). Remarkably, the presence of water, even at less than 0.12 wt% water content in the 5 wt% GMO solution, resulted in the dissolution of the crystalline GMO at temperatures (15 °C) well below the GMO melting temperature (35.5 °C). This contrasts with the sample containing 0 wt% added water (see the blue line in Fig. 4). Hydrogen bond formation between water and GMO contributes to breaking the strong intermolecular interaction between GMO molecules in the crystalline structure and increases the driving force for self-assembly of the reverse micelles. Additionally, there is a shift in the CMT of GMO, from approximately 90 °C to 100 °C (see the red lines in Fig. 4). The hydrogen bonding of the water and GMO molecules stabilizes the reverse micelles, resulting in an increase in the CMT.

Fig. 5a and b present examples of scattering profiles collected at different temperatures of 5 wt% GMO samples containing 0.3 wt% water and 1 wt% water, respectively. The micelle characteristics were analyzed by fitting the data with the Guinier–Porod model, as indicated by the black lines overlaid with the experimental data obtained from SAXS measurements. The fit results are presented in Fig. 5c, showing the variation of R_g as a function of temperature with different water content ranging from 0 wt% up to 1 wt%. Overall, R_g of the micelles decreases with increasing temperatures from 30 °C to 90 °C, following a similar trend observed with a 5 wt% GMO sample (0 wt% water). This drop is more pronounced at low water concentrations, from 0.03 wt% to 0.52 wt%, as shown in Fig. 5c. It is intriguing that with the addition of 0.03 wt% water, there is a decrease in R_g (blue) compared to the data of a 0 wt% water sample (red) across the entire temperature range. This decrease in micelle size in the presence of a small amount of water could be attributed to water molecules stabilizing the formation of reverse micelle aggregates with fewer GMO molecules, due to the increased driving force for self-assembly.³⁸ At elevated temperatures, both GMO and water have increased mobility, resulting in increased critical packing parameters which leads to the stabilization of smaller micelles.

However, when increasing the amount of water from 0.03 wt% to 0.52 wt%, R_g increases. This increase is particularly pronounced with the addition of 1 wt% water (see Fig. 5c). For example, at 30 °C, the 5 wt% GMO sample indicates the formation of micelles with an approximate size of 9 Å, while the R_g of micelles in the sample containing 1 wt% water is approximately 13 Å. Interestingly, for the 1 wt% water samples, the R_g does not decrease as significantly with temperature as seen for the samples with lower water content. Additionally, the results for the samples at 1 wt% water also showed changes in the slopes of the low Q region (∼0.02–0.1 Å⁻¹) as a function of temperature (Fig. 5b). These changes in slope at low Q correspond to the s parameter of the Guinier–Porod model (eqn (1)), which is the dimension variable. For spheres, the s parameter would equal 0, while elongated micelles have s parameters greater than 0. Further analysis of the fits showed that the s changes from 0.2 to 0.12, 0.05, and 0.03 as the temperature increases from 30 °C to 40 °C, 50 °C, and 60 °C, respectively, indicating the transformation of micelles from an elongated to a spherical structure with increasing temperature. These analyses show that the micelles at the highest water concentration decrease in size with temperature, but instead of decreasing the radius of the spherical reverse micelles, it shows up as a transition from extended micelles to spherical micelles.

We conducted further studies on the effects of fatty acid on the phase transition and micelle formation of 5 wt% GMO in white oil, with and without the addition of water. The phase diagram of 5 wt% GMO samples with various fatty acid concentrations are presented in Fig. 6a (linescans in Fig. S4, ESI†). We note that the addition of oleic acid behaves similarly to adding water in 5 wt% GMO solutions. Specifically, at lower (<0.5 wt%) fatty acid content, GMO exists in the crystalline phase at temperatures below 30 °C, as indicated by the blue lines in Fig. 6a, while micelle formation occurs within a temperature window of 30–90 °C (red lines). The addition of oleic acid at and above 0.5 wt% resulted in the dissolution of the crystalline structure of GMO even at 15 °C. Additionally, at higher acid concentrations (>1 wt%), the CMT (micelles to solution) decreases from approximately 90 °C to approximately 80 °C. This decrease suggests that oleic acid breaks down GMO assembly and facilitates GMO solubility in white oil at lower temperatures than the sample without fatty acid (which is opposite to the effect of water concentration). Lehtinen et al. showed that the critical micelle concentration (CMC) of lecithin increases with the increase of oleic acid concentration in rapeseed oil at 80 °C, indicating that oleic acid inhibited the micelle formation,³⁹ similar to what we are observing here. For the samples of 5 wt% GMO containing 1 wt% water with the addition of various oleic acid contents (Fig. 6b and Fig S5, ESI†), there is no crystalline phase formed in the range of investigated temperatures, which is consistent with the results in Fig. 4. The combination of water with 0.16 wt% fatty acid promotes micelle formation at low temperatures (15 °C) and stabilizes micelles up to a temperature above approximately 110 °C, an increase of 20 °C compared to neat 5 wt% GMO in white oil (see Fig. 4 and 6b - the first phase transition data on the left). At higher fatty acid concentrations (above 0.16 wt%), there are no significant changes in the CMT (micelles to solution), which is approximately 90 °C. A higher acid content could disrupt the equilibrium state of these micelles, resulting in a less stable GMO assembly. These results are consistent with our morphological analysis discussed in the following section that there is a change of the system from micelles to a bi-continuous structure.

Fitting the scattering data revealed a significant change in the morphology of 5 wt% GMO with the addition of oleic acid. The fitting results indicate a transition of two morphological characteristics from reverse micelles into a bi-continuous structure when the oleic acid content increases from 0.54 wt% to 1.15 wt% (see Fig. 7a and b). The Guinier–Porod model is the best fit for solutions with a lower fatty acid concentration, 0.16 wt% and 0.54 wt% oleic acid (red fitting lines). In contrast, the Teubner–Strey model is the best fit for the other two solutions with a higher acid content, as presented by the black fitting lines in Fig. 7a. The model details are presented in the Experimental section. The formation of a bi-continuous structure and the utilization of the Teubner–Strey model to fit the scattering data were also studied in similar systems.⁴⁰ For example, the microemulsion of water in an oil-rich phase formed a bi-continuous structure having a periodic oil–water distance of 7.5 nm and a correlation length of 1.8 nm.⁴¹ The Teubner–Strey model was also used to analyze the formation of bi-continuous microemulsions of sugar in oil with domain sizes varied from 25 nm to 28 nm and a correlation length of approximately 10 nm.⁴²

Fig. 7b illustrates an example of the application of the two models with the SAXS data of a 5 wt% GMO in white oil containing 3.56 wt% fatty acid. The best-fitting result of the Guinier–Porod model (red line) in Fig. 7b shows a significant deviation from the data within a Q region from approximately 0.1–0.3 Å⁻¹. The presence of a hump in the data indicates a domain period (d), 2π/Q, showing the repeating distance between neighboring GMO-FA domains illustrated in Fig. 7c featured by the Teubner–Strey model. Examples in Fig. 7d and e show the Teubner–Strey modeling results of a 5 wt% GMO in white oil with 3.56 wt% oleic acid, showing a bi-continuous structure of GMO in the presence of fatty acid, with a fixed domain size (d) or a fixed correlation length (xi) while varying the other dimension, respectively. The correlation length is defined as the distance at which the structural correlations exist. A short correlation length indicates a rippling surface. We consider that the addition of oleic acid molecules may result in their intercalation into the reverse micelles through hydrogen bonding or dipole–dipole interactions with GMO and water. We observed a transition from micelles with low oleic acid content to a bi-continuous phase at higher acid content. The micelles at low acid content may exist as mixed reverse micelles, as fatty acids also behave like surfactants, contributing to GMO reverse micelle formation. At high acid content, the intercalation of the fatty acid may disrupt the micelle packing geometry, which leads to the pinching of the micelle ends and the formation of the bi-continuous structures. SAXS scattering profiles of these samples indicate features consistent with the Teubner–Strey model, suggesting the formation of a bi-continuous phase.⁴³ Maccarrone et al. reported that the addition of telechelic polymer in a system of oil-in-water droplet microemulsions resulted in bridging the droplets due to the effective attractive interaction.⁴⁴ Anchoring and bridging formation of bi-continuous microemulsions was also reported.

Conclusions

We utilized SAXS to investigate and develop different phase diagrams of monoglycerides (GMO) in a nonpolar long-chain alkyl oil (white oil), elucidating the role of composition, temperature, and additives, including water and fatty acids, on the structural and morphological transition of GMO. We also revealed the effects of these factors on the size and stability of the reverse micelles. A critical micelle concentration (CMC) is observed, below which the GMO directly dissolves in white oil with no observable crystalline particles or micelles. Above the CMC, crystalline aggregates of GMO can exist, and the reverse micelle phase exists above a melting temperature and below the CMT. Fitting of the SAXS data reveals that the reverse micelle size shrinks steadily as the temperature is increased, which is consistent with the understanding of the increased solubility of the GMO in white oil with increased temperature. The addition of a small amount of water initially shrinks the average micelle size, but with additional water, the micelle grows again and eventually transitions to form elongated micelles at high water concentrations and low temperatures. In addition, the CMT rises slightly with added water. In contrast, the addition of fatty acid lowers the CMT. Interestingly, the fatty acid is incorporated into the reverse micelles as a co-surfactant, rather than dissolving into white oil. This is especially notable at intermediate fatty acid concentrations where the intercalation within the micelles results in the formation of a bi-continuous structure.

The conclusions from this work lay the foundation for future design strategies for the reduction of the corrosivity of biofeedstocks solutions. Our study demonstrates that there is a significant opportunity to design micelle solutions stable to high temperatures. For instance, incorporating small amounts of surfactants with a larger polar headgroup (e.g. lecithin) may alter the phase boundaries in the same way as increasing the amount of GMO. Small amounts of such surfactants are expected to be present in biofeedstocks as residues of the purification process. In addition, our work has demonstrated that the presence of a polar solvent (water) alters the micellization behavior of the GMO. Future work may explore the effect of different polar solvents on reverse micelle stability and morphology and whether a reverse-micelle-forming solution is less corrosive than a homogeneous solution.

Data availability

The data supporting this article were included in the manuscript and the ESI.†

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

The authors would like to acknowledge the funding and technical support from bp through the bp International Centre for Advanced Materials (bp-ICAM), which made this research possible. We thank the helpful discussions and feedback from the larger project team at Illinois including Prof. Jessica Krogstad, Prof. Qian Chen, Samyukta Shrivastav, Zhiheng Lyu, and Jiahui Li, as well as the bp mentors, including Dr John Shabaker, and Dr Eric Doskocil. This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science user facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. We specifically thank Dr Soenke Seifert and Dr Sungsik Lee at Argonne for their assistance with the experiments.

References

1. B. Zhang, J. Wu, C. Yang, Q. Qiu, Q. Yan, R. Li, B. Wang, J. Wu and Y. Ding, BioEnergy Res., 2018, 11, 689–702 CrossRef CAS .
2. H. Wang, M. Zhang, X. Han, Y. Zeng and C. C. Xu, Biomass Bioenergy, 2023, 173, 106810 CrossRef CAS .
3. K.-W. Jeon, J.-H. Gong, M.-J. Kim, J.-O. Shim, W.-J. Jang and H.-S. Roh, Renewable Sustainable Energy Rev., 2024, 195, 114325 CrossRef CAS .
4. D. Liu, S. Shrivastav, S. Daraydel, N. Levandovsky, H. An, S. Shevade, Q. Chen, J. A. Krogstad and D. V. Krogstad, Corros. Sci., 2023, 216, 111088 CrossRef CAS .
5. N. M. Correa, J. J. Silber, R. E. Riter and N. E. Levinger, Chem. Rev., 2012, 112, 4569–4602 CrossRef CAS PubMed .
6. A. J. Armstrong, R. F. Apóstolo, T. M. McCoy, F. J. Allen, J. Doutch, B. N. Cattoz, P. J. Dowding, R. J. Welbourn, A. F. Routh and P. J. Camp, Nanoscale, 2024, 16, 1952–1970 RSC .
7. L. Shrestha, R. Shrestha, D. Varade and K. Aramaki, Langmuir, 2009, 25, 4435–4442 CrossRef CAS PubMed .
8. L. K. Shrestha, M. Dulle, O. Glatter and K. Aramaki, Langmuir, 2010, 26, 7015–7024 CrossRef CAS PubMed .
9. L. K. Shrestha, R. G. Shrestha, M. Abe and K. Ariga, Soft Matter, 2011, 7, 10017–10024 RSC .
10. L. K. Shrestha, R. G. Shrestha and K. Aramaki, Langmuir, 2011, 27, 5862–5873 CrossRef CAS PubMed .
11. J. L. Bradley-Shaw, P. J. Camp, P. J. Dowding and K. Lewtas, J. Phys. Chem. B, 2015, 119, 4321–4331 CrossRef CAS PubMed .
12. A. Ray, Nature, 1971, 231, 313–315 CrossRef CAS .
13. X. Cui, S. Mao, M. Liu, H. Yuan and Y. Du, Langmuir, 2008, 24, 10771–10775 CrossRef CAS PubMed .
14. S. Perumal, R. Atchudan and W. Lee, Polymers, 2022, 14, 2510 CrossRef CAS PubMed .
15. Z. Chu, C. A. Dreiss and Y. Feng, Chem. Soc. Rev., 2013, 42, 7174–7203 RSC .
16. D. Wan, C. Li and J. Pan, ACS Appl. Bio Mater., 2020, 3, 1139–1146 CrossRef CAS PubMed .
17. C. H. Cavalcante, R. S. Fernandes, J. de Oliveira Silva, C. M. R. Oda, E. A. Leite, G. D. Cassali, I. Charlie-Silva, B. H. V. Fernandes, L. A. M. Ferreira and A. L. B. de Barros, Biomed. Pharmacother., 2021, 134, 111076 CrossRef CAS PubMed .
18. X. Sun and N. Bandara, Trends Food Sci. Technol., 2019, 91, 106–115 CrossRef CAS .
19. M. Esmaili, S. M. Ghaffari, Z. Moosavi-Movahedi, M. S. Atri, A. Sharifizadeh, M. Farhadi, R. Yousefi, J.-M. Chobert, T. Haertlé and A. A. Moosavi-Movahedi, LWT–Food Sci. Technol., 2011, 44, 2166–2172 CrossRef CAS .
20. M.-J. Sáiz-Abajo, C. González-Ferrero, A. Moreno-Ruiz, A. Romo-Hualde and C. J. González-Navarro, Food Chem., 2013, 138, 1581–1587 CrossRef .
21. T. Wu, M. Xie, J. Huang and Y. Yan, ACS Appl. Mater. Interfaces, 2020, 12, 39578–39585 CrossRef CAS .
22. R. G. Larson, A. K. Van Dyk, T. Chatterjee and V. V. Ginzburg, Prog. Polym. Sci., 2022, 129, 101546 CrossRef CAS .
23. B. Sohrabi and F. Ameli, in Magnetic Surfactants: Design, Chemistry and Utilization, ACS Publications, 2023, pp. 107–125 Search PubMed .
24. A. M. Atta, M. M. Abdullah, H. A. Al-Lohedan and A. K. Gaffer, Energy Fuels, 2018, 32, 4873–4884 CrossRef CAS .
25. G. La Sorella, G. Strukul and A. Scarso, Green Chem., 2015, 17, 644–683 RSC .
26. M. Cortes-Clerget, N. Akporji, J. Zhou, F. Gao, P. Guo, M. Parmentier, F. Gallou, J.-Y. Berthon and B. H. Lipshutz, Nat. Commun., 2019, 10, 2169 CrossRef PubMed .
27. P. Qu, M. Kuepfert, E. Ahmed, F. Liu and M. Weck, Eur. J. Inorg. Chem., 2021, 1420–1427 CrossRef CAS .
28. M. A. Malik, M. A. Hashim, F. Nabi, S. A. Al-Thabaiti and Z. Khan, Int. J. Electrochem. Sci., 2011, 6, 1927–1948 CrossRef CAS .
29. Y. Zhu, M. L. Free, R. Woollam and W. Durnie, Prog. Mater. Sci., 2017, 90, 159–223 CrossRef CAS .
30. M. Ghorbani, J. Soto Puelles, M. Forsyth, R. A. Catubig, L. Ackland, L. Machuca, H. Terryn and A. E. Somers, J. Phys. Chem. Lett., 2020, 11, 9886–9892 CrossRef CAS PubMed .
31. M. Al-Sabawi and J. Chen, Energy Fuels, 2012, 26, 5373–5399 CrossRef CAS .
32. M.-L. Arsene, I. Răut, M. Călin, M.-L. Jecu, M. Doni and A.-M. Gurban, Processes, 2021, 9, 345 CrossRef .
33. J. L. Bradley-Shaw, P. J. Camp, P. J. Dowding and K. Lewtas, Phys. Chem. Chem. Phys., 2018, 20, 17648–17657 RSC .
34. SasView version 5.0.6, (https://www.sasview.org/) Search PubMed .
35. E. M. Ericsson, L. Faxälv, A. Weissenrieder, A. Askendal, T. L. Lindahl and P. Tengvall, Colloids Surf., B, 2009, 68, 20–26 CrossRef CAS PubMed .
36. H. Lu, I. Pezron, T. Gaudin and A. Drelich, Colloids Surf., A, 2018, 540, 167–176 CrossRef CAS .
37. M. E. Mahmood and D. A. Al-Koofee, Glob. J. Sci. Front. Res. Chem., 2013, 13, 1–7 Search PubMed .
38. I. Amar-Yuli, E. Wachtel, D. E. Shalev, H. Moshe, A. Aserin and N. Garti, J. Phys. Chem. B, 2007, 111, 13544–13553 CrossRef CAS PubMed .
39. O.-P. Lehtinen, R. W. N. Nugroho, T. Lehtimaa, S. Vierros, P. Hiekkataipale, J. Ruokolainen, M. Sammalkorpi and M. Österberg, Colloids Surf., B, 2017, 160, 355–363 CrossRef CAS PubMed .
40. Y. Xi, R. S. Lankone, L.-P. Sung and Y. Liu, Nat. Commun., 2021, 12, 910 CrossRef CAS PubMed .
41. H. Kim, M. Han, S. R. Bandara, R. M. Espinosa-Marzal and C. Leal, Soft Matter, 2019, 15, 9609–9613 RSC .
42. H. Dave, F. Gao, J.-H. Lee, M. Liberatore, C.-C. Ho and C. C. Co, Nat. Mater., 2007, 6, 287–290 CrossRef CAS PubMed .
43. S. Maccarrone, J. r Allgaier, H. Frielinghaus and D. Richter, Langmuir, 2014, 30, 1500–1505 CrossRef CAS PubMed .
44. S. Maccarrone, H. Frielinghaus, J. Allgaier, D. Richter and P. Lindner, Langmuir, 2007, 23, 9559–9562 CrossRef CAS PubMed .

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Footnote

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4sm00809j

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