1. Introduction
Polyurethanes (PU) are prominent polymers globally, owing to their versatility and wide range of applications [
1]. Ranked as the sixth most important polymer, PUs are highly favored due to their ability to be tailor-made for specific purposes, well-established synthesis technology, and exceptional properties, such as thermal insulation, diverse densities, and load-bearing capabilities for applications in elastomers, foams, coatings, and adhesives, to name a few [
2,
3,
4]. In 2021, they represented 8.2% of the total polymers demand [
5]. Notably, the PU market surged to approximately USD 80 billion in 2022, with projections indicating a rise to USD 110 billion by 2030 [
6,
7]. Additionally, polyurethanes offer cost-effective solutions, including energy efficiency, durability, and versatility, leading to reduced maintenance costs, lower energy bills, and increased productivity [
8,
9].
The synthesis of PU involves the reaction between isocyanates and reactive hydrogen from polyols [
10]. Several sustainability-focused studies have employed urethane reaction research [
11,
12,
13]. These include the design of self-healing PU materials for application in integrated smart wearable devices, the lever functionalization of cellulose nanocrystal hydroxyls with isocyanate for improved adhesion sensing platforms, and the development of smart PU biocoatings for the enhanced biocompatibility of metal scaffolds.
Moreover, the properties of PUs are intricately linked to the type of polyol used and the specific formulation employed during their synthesis [
14,
15,
16]. In response to the growing need for sustainable production practices, researchers have delved into exploring alternative polyols as replacements for conventional petroleum-based ones [
17]. These alternative polyols can be sourced from renewable feedstock such as vegetable oil through various functionalization methods, such as oxirane ring-opening, transesterification, and transamidation [
18,
19,
20]. Notably, transamidation has emerged as one of the most widely used functionalization methods for saturated vegetable oil because it is relatively straightforward, leading to the production of amine–hybrid polyols [
21,
22].
The increasing demand for these amine hybrid system polyols has underscored the necessity for efficient polyol characterization methods. Researchers have already achieved significant advancements in developing polyols, such as tertiary amine-induced autocatalysis and amino esters in equilibrium with diethanolamide to synthesize PU foam with improved mechanical and thermal properties [
23,
24]. Polyol has also been produced with diverse hydroxyl and amine moieties, resulting in an improved polyol chain structure and overall reactivity for coating applications [
25,
26].
With this, analytical techniques for determining fractional moieties offer valuable insights for improving the resulting PU properties, as these factors significantly impact the distinctive characteristics of the resulting PU networks [
27]. Primary hydroxyl groups lead to denser PU networks [
28]. Secondary hydroxyl groups introduce unfavorable dangling chains that function as plasticizers within the PU structure, while hindered-secondary hydroxyls in the carbon chain cause significant steric hindrance, limiting urethane crosslinking [
29]. Furthermore, amines induce more hydrogen in polymer matrix bonding, contributing to providing more intermolecular forces, thereby enhancing the PU mechanical properties [
30].
Despite these strides, there are existing challenges in characterizing hydroxyl functional moieties. While the total hydroxyl number, primary amines, and secondary amines in polyol compounds have a standard quantitative characterization procedure, there is a notable gap that exists regarding an established standard method for quantitatively characterizing specific fractions for primary, secondary, and hindered-secondary hydroxyls [
31,
32,
33]. Hence, in exploring both traditional and hybrid polyols, there is a need to delve into comprehensive characterization methods for both hydroxyl and amine moieties.
Furthermore, understanding the reaction kinetics is crucial for tailoring material properties to meet specific requirements in various applications [
34,
35,
36]. Alfeche et al. (2023) and Dingcong et al. (2023) conducted a simulation for the PU polymerization process using traditional hydroxyl-based polyols [
27,
37]. Their findings revealed that the kinetics of polymerization in terms of the gel time were significantly affected by the chemical characteristic inputs of the polyol, such as the fractions of hydroxyls moieties. However, a gap still exists in the identification of the thermo-kinetic properties associated with hybrid polyols, particularly concerning their distinct amine moieties and reactions with isocyanates.
In addition to technical challenges, the experimental methods for determining the polyol properties and thermo-kinetic information for PU polymerization consume considerable time and financial resources, and may be limited to some laboratories. Moreover, the use of organic solvents and exposure to toxic chemicals during PU formation studies pose health and environmental risks and result in expensive waste management [
38,
39]. Unsystematic experimental errors may also arise due to the effects of fluctuating environmental conditions, such as ambient temperature and humidity, on the polyurethane polymerization reaction and its rate of heat transfer [
40,
41,
42].
To address these concerns, researchers have turned to computational studies to simulate PU physical formation. Ferkl et al. (2018) simulated PU foam polymerization via the mathematical modeling of reaction kinetics, foam expansion, and wall evolution [
43]. Hu et al. (2021) simulated the same process via a numerical study on bubble nucleation and bubble growth [
44]. Nonetheless, validating these simulations with accurate experimental results remains a formidable task.
Computational simulations based on heat transfer and reaction kinetics differential equations have been performed on polyurethane foaming processes based on Baser and Kakhar’s models, which employ thermal energy balance and polyurethane reaction kinetics [
45]. Zhao et al. (2013) modeled and simulated the temperature profiles during the rigid polyurethane foaming process of hydroxyl-based single and multi-polyol mixture polyurethane formulation systems [
46]. Al-Moameri et al. (2015) used the same approach in simulating the effects of different physical blowing agents on the polymerization temperature and height profiles during the polymerization process, with the consideration of parameters based on the type of alcohol moieties present in the polyol [
47]. The aforementioned kinetic simulations and modeling utilized only the reaction between hydroxyls and isocyanate for the prepolymerization processes. Considering this, modeling all possible exothermic polymerization kinetics using diverse polyol systems such as amine moieties has been largely unexplored.
The previously mentioned gaps warrant this study, which adopts a computational approach via MATLAB R2021b to simulate temperature profiles that describe the polyurethane prepolymerization and foaming reactions involving hydroxyls and amine-functionalized polyols. It simultaneously solves numerous differential equations based on PU thermodynamic and kinetics principles and heuristics from the established literature [
37,
46,
48,
49,
50]. Through curve fitting comparisons with experimental data, it determines the fractions of the functional amine and hydroxyl moieties present in the polyol and addresses the lack of available thermo-kinetic parameters for reactions involving secondary amines and isocyanates. The characterization of PU starting materials, particularly polyols, and PU polymerization studies via computational methods using MATLAB requires fewer resources and yields insights in a shorter timeframe in comparison with conventional experimental methods. Furthermore, MATLAB is an appropriate tool for the simultaneous solutions to the multiple differential equations involved in the thermo-kinetic studies of polymerization [
51]. Specifically, the current study uses the latest differential equation solver function, ode89 of MATLAB, to enhance the accuracy of previous PU thermo-kinetic simulation studies [
24,
37,
46,
52].
Additionally, the study seeks to investigate the effects of different polyol moieties on the reaction kinetics and temperature profiles during polyurethane formations. The insights obtained from this study will contribute to the groundwork for further research, the development of formulations based on existing and developing polyol systems with diverse functionalities, and ultimately, to advancing sustainable polyurethane and polyurea production.
The application of simulations on polyurethane polymerization kinetics using developing polyol systems promises to provide ease and sustainability in improving polyurethane formulations and parameter optimization studies. Understanding the synthesis information obtained through these computational approaches will significantly aid in process development and the engineering of polymeric materials with advanced properties tailored to meet specific application demands, especially when time and resource constraints are critical considerations.
Simulation Description
The synthesis of polyurethane prepolymer involves an exothermic reaction between isocyanates and polyol, as shown in
Figure 1a. First, isocyanates react with the reactive hydrogen of polyols to form polyurethane prepolymer [
1]. For the reaction of traditional polyol (hydroxyl-based polyol) and isocyanates, polyurethanes are formed exclusively. As for the reaction between hybrid polyol (amine-based polyol), polyurea forms along with polyurethane. On the other hand, the synthesis of polyurethane foam involves the addition of water as a blowing agent [
53]. Blowing proceeds as the isocyanate reacts with the water present to form an unstable product, carbamic acid, which, consequently, decomposes to amine and carbon dioxide, as shown in
Figure 1b.
The reactivity of the prepolymerization process is influenced by the degree of hydroxyls, which can be classified as primary, secondary, and hindered-secondary/tertiary, and amines that participated in the reactions [
54,
55]. Additionally, the heat generated from these exothermic reactions is attributed to the type of functional moieties present in polyol and further plays a critical role in providing the efficient energy needed for curing and cross-linking [
56]. With this, the concentrations of the different types of hydroxyl and amine moieties were considered in the computational method to accurately capture the influence of the polyol type on the thermo-kinetic behavior of the PU during the prepolymerization process.
The internal temperature during the polymerization reaction at a given time, t, is computed using an energy balance equation derived from previous work by Zhao et al. (2013) [
46], as represented in Equation (1):
where
is the summation of the products of the heat and reaction rates of the polymerization reactions,
UAT is the product of the overall heat transfer coefficient, the surface area of foam, and temperature difference, and
is the summation of the products of the molar concentration and heat capacities of the reactants [
46]. Instantaneous molar concentrations of the reactants and products were obtained using the elementary reaction rates presented in
Table 1.
Furthermore, research conducted by Zhao et al. (2014) examining the influence of catalysts on PU foam polymerization confirmed that Equation (2) offers an accurate estimation of catalyzed reaction rate constants, with cat denoting the specific catalysts utilized [
58].
where
ki represents the overall rate constant for every reaction,
i, in
Table 1,
kuncat,i represents the uncatalyzed reaction rate constant, and
kcat,i represents the reaction rate constant in the presence of a catalyst.
Additionally, the catalyzed and uncatalyzed rate constants varying at different temperatures,
k(
T), were calculated via the Arrhenius equation in Equation (3):
where
Ea is the activation energy of the reaction,
k0 is the pre-exponential factor,
R is the gas constant, and
T is temperature.
The thermo-kinetic parameters, including the pre-exponential factor (
k0) at 25 °C, heat of reactions (Δ
H), and activation energy (
Ea) related to hydroxyl–isocyanate reactions, were derived from the findings of Ghoreishi et al. (2014) [
57]. These thermo-kinetic parameters are summarized in
Table 2.
2. Materials and Methods
2.1. Materials
The rigid polyurethane prepolymers were synthesized using the following materials. The isocyanate, methylene diphenyl diisocyanate (MDI) PAPI
TM 27 with an NCO functionality of 2.7, molecular weight of 340 g/mol, specific heat capacity of 1.8 J/g-K, and density of 1.23 g/mL, was manufactured by Dow Chemical Co., Hayward, CA, USA [
59]. The polyol based on petroleum, Voranol
® 490 (V490), was also manufactured by Dow Chemical Co. while the amine-based polyol used was Coconut oil Diethanolamine from the Center for Sustainable Polymers of Mindanao State University–Iligan Institute of Technology, Iligan City, Philippines, according to the methods of Dingcong et al. (2023) [
24]. The blowing agent used was distilled water. The catalyst, Polycat
® 8, was obtained from Evonik Industries AG, Essen, Germany. The surfactant, INV 690, was obtained from Guangzhou Innovate Chemical Co., Ltd., Guangzhou, China. N-tert-butoxycarbonyls, dichloromethane, and anhydrous sodium sulfate were purchased from Merck, Darmstadt, Germany.
2.2. Characterization of Polyol
The hydroxyl and amine values of the amine-based polyol were characterized following the ASTM D4274-11 and ASTM D2074-07 methods, respectively. The specific heat capacity was obtained using the PerkinElmer differential scanning calorimeter (DSC) model 4000 following ASTM E1269-11, using indium metal as a reference and aluminum as heating pans. Moreover, the heating range was from −30 °C to 300 °C while the heating rate was 10 °C/min under a nitrogen gas atmosphere [
60]. Additionally, the molecular weight of the polyol was analyzed using the Shimadzu gas permeation chromatography (GPC) assembly (Shimadzu, Kyoto, Japan) based on the ASTM D6474-12 guidelines [
61]. Density determination was conducted using the ASTM D4669 [
62] methods and the total functionality of the polyol was calculated using Equation (4):
where
f is the functionality of the polyol,
MW is the molecular weight of the polyol, and
OH and
NH are the hydroxyl value and amine value, respectively.
The Fourier transform infrared (FTIR) spectra of the amine-based polyol, as well as its raw materials—diethanolamide and glycerol—were collected on a Shimadzu IRTracer-100 FTIR (Shimadzu Corp., Kyoto, Japan) equipped with an attenuated total reflectance (ATR) accessory sampling technique. All data were recorded at room temperature, in the range from 4000 to 500 cm
−1, by accumulating 80 scans with a resolution of 4 cm
−1. The validation of the amine value involved estimating the integrated peaks in the
1H nuclear magnetic resonance (NMR) spectra of the polyol [
4].
1H NMR spectra were recorded on Bruker Ascend 600MHZ Cryoprobe NMR Spectrometer (Bruker Corp., Billerica, MA, USA) using deuterated chloroform as a solvent. NMR analysis was conducted at the USA DOST-PCHRD Tuklas NMR Laboratory Visayas, University of San Agustin, Iloilo City.
2.3. Experimentation Design
For the gelling, the amine-based polyol was vacuum-dried at 80 °C for 2 h. A polyol mixture comprising amine-based polyol and Voranol 490 was weighed with catalysts and surfactants in a 300 mL paper cup as the B-side. The mixture of B-side components was mixed at 3450 rpm using an electronic mixer blade for 60 s, and was allowed to degas for 120 s. The A-side comprising isocyanate was weighed beforehand and quickly poured into the cup. The reaction mixture was then mixed for 10–15 s at 3450 rpm. The internal temperature of the rising foam was recorded at 5 s intervals. For the foaming process, the same gelling procedure was utilized, with the only difference being that the B-side consisted of a blowing agent, specifically water. It is worth noting that the foaming procedures performed in the present study were adapted from the previous literature [
24].
Prepolymerization and foaming reaction experiments using a polyol mixture with varied amine-based polyol replacements were conducted to verify the accuracy of the simulation results. The polyurethane prepolymer samples were labeled according to the percent replacement of the amine-based polyol. The polyol mixture comprised a hydroxyl-based polyol (Voranol 490) (
Figure 2a) and amine-based polyol (
Figure 2b). Voranol 490 polyol comprised 100 wt. % Voranol 490. The 50% amine-based polyol consisted of 50 wt. % amine-based polyol and 50 wt. % Voranol 490. The 75% amine-based polyol consisted of 75 wt. % amine-based and 25 wt. % Voranol 490. Lastly, the 100% amine-based polyol was an purely amine-based polyol. The same polyol mixture formulation was also used for polyurethane foam sample labeling, that is, 50%, 75%, and 100% amine-based polyols.
Table 3 and
Table 4 outline the ingredients and proportions used in the prepolymerization and foaming reactions, respectively.
For amine defunctionalization, 1 mol of amine-based polyol was dissolved in 5 mL of dichloromethane. The polyol solution was treated with Boc2O (di-tert-butyl dicarbonate) in a molar ratio of 1.2:1 (Boc2O:amine). The mixture was mixed and maintained at room temperature for 30 min. Afterward, the reaction was quenched with a few drops of water in the mixture. The organic phase was subjected to dehydration using anhydrous sodium sulfate and subsequently concentrated under reduced pressure in a vacuum.
The structure of the formation of polyurethane was confirmed by FTIR spectra using a Fourier transform Shimadzu IRTracer-100 FTIR equipped with an ATR accessory sampling technique. All data were recorded at room temperature, in the range from 4000 to 500 cm−1, by accumulating 128 scans with a resolution of 4 cm−1.
Figure 2.
Chemical structure of representative polyols for polyurethane polymerization thermo-kinetic simulation: (
a) Voranol 490 and (
b) amine-based polyol [
24,
63].
Figure 2.
Chemical structure of representative polyols for polyurethane polymerization thermo-kinetic simulation: (
a) Voranol 490 and (
b) amine-based polyol [
24,
63].
Table 3.
Poly(urethane-urea) prepolymer formulation at different amine-based polyol weight percent replacements.
Table 3.
Poly(urethane-urea) prepolymer formulation at different amine-based polyol weight percent replacements.
Prepolymer Formulation | Components | 100% V490 | 50% Amine-Based Polyol a | 75% Amine-Based Polyol b | 100% Amine-Based Polyol |
---|
Polyol | V490 (g) | 20 | 10 | 5 | 0 |
Amine-based polyol (g) | 0 | 10 | 15 | 20 |
Catalyst | Polycat 8 (g) | 0.1 | 0.1 | 0.1 | 0.1 |
Surfactant | INV 690 (g) | 0.2 | 0.2 | 0.2 | 0.2 |
Isocyanate | MDI PAPI 27 (g) | 25.70 | 21.56 | 19.49 | 17.42 |
NCO/OH [64] | 1.11 | 1.07 | 1.04 | 1.01 |
Table 4.
Poly(urethane-urea) foam formulation at different amine-based polyol weight percent replacements.
Table 4.
Poly(urethane-urea) foam formulation at different amine-based polyol weight percent replacements.
Foam Formulation | Components | 100% V490 | 50% Amine-Based Polyol a | 75% Amine-Based Polyol b | 100% Amine-Based Polyol |
---|
Polyol | V490 (g) | 20 | 10 | 5 | 0 |
Amine-based polyol (g) | 0 | 10 | 15 | 20 |
Catalyst | Polycat 8 (g) | 0.1 | 0.1 | 0.1 | 0.1 |
Surfactant | INV 690 (g) | 0.2 | 0.2 | 0.2 | 0.2 |
Blowing Agent | Water (g) | 0.2 | 0.2 | 0.2 | 0.2 |
Isocyanate | MDI PAPI 27 (g) | 28.97 | 24.83 | 22.76 | 20.68 |
NCO/OH [64] | 1.11 | 1.07 | 1.05 | 1.02 |
2.4. Computational Method Approach
The MATLAB computational approach is anchored on the solutions of non-stiff ordinary differential equations (ODE) using the Runge–Kutta (8,9) method via the MATLAB ode89 function for a high accuracy.
The computational algorithm employed in this study for obtaining the temperature profiles and fitted fractions of the moieties of the polyol system is depicted in
Figure 3. The algorithm is composed of six interrelated MATLAB-coded functions provided in
Supplementary Materials S2, namely, User Input, Formulation, Database, Curve Fitting, Prepolymer ODE, and Temperature Profile Generation.
The User Input function comprises four prompts that gather key information: (1) the composition of the isocyanate and polyol mixture, and the percentage replacement of the amine-based polyol; (2) property values of the amine-based polyol, encompassing the hydroxyl value, amine value, molecular weights, functionality, density, and specific heat capacities; (3) property values of isocyanate, and (4) experimental data along with the reaction time and range and intervals for the fractions of the functional moieties. With regard to the property values of the amine-based polyol, the hydroxyl value of the polyol serves as a quantifier for the concentration of hydroxyl functional groups, while the amine value allows for the determination of secondary amine concentrations in the amine-based polyol. The molecular weight is necessary for estimating the molar quantities involved in the prepolymerization reactions. Density, on the other hand, aids in calculating the total volume of the reacting mixture, a critical factor for reaction rate determination. Furthermore, specific heat capacity values are crucial for assessing the heat capacities of chemical species, and pivotal for internal temperature calculation during the polymerization process. Lastly, the inputs for ranges and intervals for the functional moiety fractions were crucial for comprehensive exploration, enabling the identification of functional moiety combinations in the polyol system and ensuring robust, accurate simulation results.
The Formulation function stores property values, including those of isocyanate and polyol, along with catalysts and additives, which are vital for the subsequent calculations.
Meanwhile, the Database function stores essential kinetic and thermodynamic parameters. Arrhenius equation parameters, such as activation energy, pre-exponential factor, and heats of reaction for various reactions, are indispensable for calculating the reaction rates across the temperature range of interest, as well as the heat progression of polymerization reactions.
As for the Prepolymer ODE function, it derives the rate of temperature change (Equation (1)), instantaneous molar concentrations of polyol and isocyanate (reaction rate expressions in
Table 1), and rate constants (Equations (2) and (3)) by employing values from the Formulation and Database functions and adopting heuristics, outlined in
Table 5, based on the established literature.
The Curve Fitting function obtains fractions of the hydroxyl and amine moieties according to a minimized average relative error of less than 5.0% between the experimental and simulated results. The experimental data are fitted with ODE-solved temperature-time data based on the minimized average relative error of the residuals of the predicted and experimental data. Simultaneously, the algorithm enables the fitting of thermo-kinetic parameters or fractions of the moieties of the polyols, encompassing primary, secondary, and hindered-secondary hydroxyls, as well as secondary amines. The selection of fitting targets is contingent upon the availability of prior data regarding these parameters or functionalities.
Lastly, the Temperature Profile Generation function stores the initial conditions of the ordinary differential equations and generates a temperature profile using the MATLAB ode89 function. From here, the function also obtains the gel point of polymerization based on the assumption that the increase in temperature is becoming zero [
65]. Therefore, the peak temperatures observed during the prepolymerization process of polyurethane foams correlate with the gel point, which is the point at which the polymerization reaction stops and the temperature ceases to increase [
37].
4. Conclusions
A computational method was developed to further contribute to the characterization of existing polyol systems, an important precursor material for polyurethane. The method encompasses traditional and hybrid polyol systems, that is, both hydroxyl and amine-comprising polyols. Polyol characterization includes the determination of the fraction of functional moieties and amine thermo-kinetic parameters for exothermic reactions with isocyanates. The utilized method showed excellent agreement with existing reaction rates from the literature. The simulated characterization results and corresponding temperature profiles provide valuable insights into the reactivity and heat progression during the polyurethane prepolymerization process. The computational method also captured the influence of secondary amine and other functional groups on the reaction rate and maximum temperature, demonstrating its ability to predict the thermo-kinetic behavior of the polyols’ corresponding prepolymerization processes.
The computational method employed in the present study realizes the great potential to accelerate polyurethane hybrid foam formulation development and optimization with reaction process simulations, significantly reducing the need for extensive experimental runs. This reduction in experimentation not only saves valuable resources, but also minimizes costs and mitigates exposure to hazardous solvents, promoting a safer and more sustainable research approach.
Furthermore, as new polyol or isocyanate systems are introduced, this method exhibits adaptability in assessing their reactivity and compatibility with other chemical species involved in polyurethane polymerization. By controlling the type and concentration of functional groups in polyols, it is possible to tailor the reactivity and properties of polyurethane materials for specific applications in various industries. The consideration of additional polymeric side reactions, such as the endothermic formations of allophanate and biuret segments in the thermo-kinetic simulation, could potentially improve our understanding in the field while paving a way for future studies on polymeric material development. This adaptability allows for sustainable innovation in polymer chemistry and engineering, driving the field forward.