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Article

Ignition Delay and Burning Rate Analysis of Diesel–Carbon Nanotube Blends Stabilized by a Surfactant: A Droplet-Scale Study

by
Anderson Gallego
1,2,*,
Karen Cacua
1,
David Gamboa
1,
Jorge Rentería
1 and
Bernardo Herrera
1
1
Advanced Materials and Energy Group (MATyER), Instituto Tecnológico Metropolitano, Street 54A No 30-01, Medellín 050536, Colombia
2
Group of Research and Innovation in Energy (GIIEN), Institución Universitaria Pascual Bravo, Street 73 No 73a-226, Medellín 050034, Colombia
*
Author to whom correspondence should be addressed.
Energies 2023, 16(23), 7740; https://doi.org/10.3390/en16237740
Submission received: 13 October 2023 / Revised: 3 November 2023 / Accepted: 4 November 2023 / Published: 23 November 2023
(This article belongs to the Special Issue Nanotechnology for Energy Applications)
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Abstract

:
In this study, the effects of pristine carbon nanotubes (CNTs), sodium dodecylbenzene sulfonate (SDBS), and diesel blends on the ignition delay and burning rate are examined experimentally. For this purpose, single-droplet combustion tests were conducted in a combustion system for 21 days using CNTs at concentrations of 50 ppm and 100 ppm, which were dispersed in Colombian commercial diesel and stabilized by SDBS. Videos of the diesel droplet burning were obtained using a high-speed camera, and the Shadowgraph optical technique was used to observe the development of the droplet size during combustion. Thus, records of the process were collected, and the treatment was carried out using a MATLAB algorithm. The measurements and processing were carried out along with a stability study, which included measurements of dynamic light scattering (DLS), pH, potential Zeta, and properties such as thermal conductivity and surface tension. The results demonstrated that the temporal stability has a direct impact on the single-droplet combustion tests because a concentration of CNTs of 100 ppm showed a higher stability than those achieved by 50 ppm. Consequently, improvements were found with a concentration of 100 ppm—for instance, the thermal conductivity increased by about 20%, the ignition delay time increased by 16.2%, and the burning rate increased by 30.5%.

1. Introduction

Compression ignition engines (MEC) are pieces of technology that use the diesel cycle as their basic operating principle, admitting air first and then injecting high-pressure diesel when the piston is close to the top dead center. The temperature and pressure conditions generate combustion, which encourages the piston to generate work [1,2]. They have a significant impact on several oil-based economic sectors, including transportation, electricity production, and agricultural machines, among others. Compared to other technologies like gasoline engines, they are more durable, more cost-effective, and have higher thermal efficiency [3]. However, a problem with this technology is the release of pollutants and their impact on the environment and public health. As a result, there are government laws, such as those provided by the EURO 6 standard, which have established minimum pollutant gas emissions from the automotive industry [4]. Although the EURO regulation was introduced in 1992, work is still being carried out on the EURO 7 to take drastic action and control the operations of internal combustion engines [5]. In fact, it is predicted that the production of fossil fuel-based engines would cease in the near future due to efforts to move to a fossil fuel-free economy and energy transition [6].
However, internal combustion engines have advantages over other technologies such as electric and hybrid automotive technologies. Therefore, a number of alternatives are being offered with the goal of preserving the technology of actual engines. Research has concentrated on several alternatives, including the use of biodiesel [7,8], the utilization of natural gas for dual-mode operation [9], and the usage of nanofuels by dispersing nanomaterials in diesel, biodiesel, or a combination of both [10,11]. The use of nanofuels is one of the methods that try to lessen the environmental impact of internal combustion engines, especially compression ignition engines. These materials provide a high energy density, low sulfur content, and high volatility [12,13]. Additionally, they serve as thermal bridges inside the fuel during combustion, speeding up the chemical reaction and improving parameters such as the ignition delay, the combustion rate, and the oxidation of pollutants like unburned hydrocarbons (HC) and carbon monoxide (CO) [14].
However, there have been increasing concerns regarding the use of metallic and metallic oxide nanomaterials, such as titanium dioxide (TiO2) [8], cerium oxide (CeO2) [15], copper (Cu), and copper oxide (CuO) [16], among others. This is because these nanomaterials have negative effects on human health due to their high chemical reactivity and biological activity. They can generate genotoxicity and biochemical toxicity, as they can easily penetrate the skin or enter the body through inhalation or the ingestion of water or food [17]. Therefore, some researchers have justified the use of carbonaceous nanomaterials. For example, Heidari-Maleni, et al. [16] highlighted the biocompatibility and non-toxicity of graphene quantum dots (GQDs), which also helped to reduce the duration of combustion and improved the rate of heat release when used in a diesel engine.
Moreover, Alenezi et al. [18] used mixtures of diesel and biodiesel with multi-walled carbon nanotubes (MWCNTs). They discovered that their application in a diesel engine resulted in the better atomization of the fuel and, as a result, higher pressures inside the cylinder, which were 4.67% higher than the maximum pressure reached with the operation in diesel mode. Bello et al. [19] also used nanomaterials made of GO, TiO2, and GO doped with TiO2 (GO-TiO2). They found decreased emissions of particulate matter (PM) and an increase in the thermal performance of the engine by up to 8.36%, owing to the fuel’s higher reactivity and improved combustion caused by the presence of nanomaterials. Manigandana et al. [16] employed a dual-mode compression ignition engine with 20% hydrogen and nanomaterials of TiO2, CNT, Al2O3, CuO, and CeO2 dispersed in the fuel. They revealed that employing CNT, Al2O3, and CeO2 improved the thermal efficiency of the brake by 1.2%, 2.5%, and 4.3%, respectively. However, one of the most interesting outcomes was with the use of CNT, because they reported decreases of 33% in NOX emissions. Similarly, Kolli et al. [20] found that employing graphene nanosheets improved the thermal performance of a diesel engine by 3% while decreasing CO, NOX, particulate matter, and UHC emissions by 41%, 13.5%, 45%, and 39%, respectively. The use of carbonaceous nanoparticles in diesel engines has a higher environmental potential due to a variety of advantageous chemical, physical, and combustion properties. For these reasons, nanomaterials are currently employed, since they have the potential to reduce harmful emissions such as PM, UHC, and CO [21,22].
Furthermore, diesel, biodiesel, and their blends are well known to be injected as atomized droplets. The phenomena that these fuel droplets undergo inside the combustion chamber are probably what determine the emissions and performance of a diesel engine. Therefore, the study of individual droplet combustion characteristics can explain phenomena such as those obtained with the presence of nanomaterials because they may benefit combustion due to increases in thermal conductivity, radiation absorption [23], the formation of layers of nanoparticles that improve heat conduction to the interior of the droplet, and microexplosions [24]. Consequently, a phenomenological approach to droplet combustion can be applied to approximate the impact of nanomaterials on the performance and emissions of a compression ignition engine.
For instance, Ooi et al. [14] demonstrated improvements in fuel drop combustion characteristics such as the ignition delay, combustion temperature, and combustion duration when graphite oxide (GO), aluminum oxide (Al2O3), and cerium oxide (CeO2) were used. As a result, improved thermal efficiency and lower emissions of pollutants like NOX, PM, and CO were predicted when those nanomaterials were used in a diesel engine. Additionally, Ooi et al. [25] found similar results in another of their works using GO nanomaterials dispersed in diesel and biodiesel. They claimed that GO can aid in reducing the ignition delay and increasing the burning rate due to the properties already mentioned and, additionally, the oxygen-supplying capacity and exothermic reactions. Also, Abdul Rasid and Zhang [26] underlined the existence of a nanoparticle shell on the droplet surface during the evaporation process when dispersed soot nanoparticles were in the fuel, which favors heat transfer towards the core of the droplet. Likewise, Singh et al. [27] confirmed that, by using multi-walled carbon nanotubes (MWCNTs), the evaporation rate can be accelerated due to the radiation absorption.
Despite the advantages, nanomaterial aggregation and sedimentation have a detrimental impact on the expected benefits of nanomaterials dispersed in liquid fuels, which are the main concerns with their usage [28]. Accordingly, some studies have employed the functionalization [29] and surfactant [30] approaches. For instance, surfactant addition has been shown to increase the stability of the dispersions while maintaining the features of the nanomaterials dispersed in diesel without altering the fuel’s characteristics [31,32]. Furthermore, when nanofuels are used in diesel engines, adding a surfactant reduced nanoparticle deposition on injectors, valves, and fuel lines [33].
According to Wang et al. [34], the evaporation of single droplets of diesel and biodiesel is comparable when surfactants (span80 and tween80) are used with those fuels. As a result, using nanomaterials of CNTs and a surfactant may improve the droplet evaporation rate in those fuels. Likewise, Kannaiyan et al. [35] noted that the use of Span80 had no impact on the experiment’s outcomes, which were exclusively related to the usage of Al2O3 nanoparticles and their stability, which is due to the fact that surfactant molecules attach to the nanoparticle surfaces and create an absorption layer around them. Consequently, nanoparticle collisions undergo electrostatic repulsive forces that overcome Van der Waals attraction [36]. Thermal conductivity, viscosity, and surface tension, for example, remain unchanged at lower surfactant concentrations [37,38]. Nonetheless, Liang et al. [39] found that using a blend of bioethanol and oleic acid as a surfactant improves combustion parameters such as the ignition delay, burning rate, and temperature, which are improved with respect to only bioethanol. Nevertheless, surfactants have only been utilized in experimental research to keep nanofuels chemically stable [40], and their effects on single-droplet combustion and temporal stability, as well as those carbonaceous nanomaterials like CNTs dispersed in diesel fuel, have not been thoroughly studied in the literature.
Therefore, this study performs, for the first time, an experimental analysis of combustion parameters like the ignition delay and burning rate of a single droplet from a dispersion of pristine carbon nanotubes in Colombian commercial diesel, which has been stabilized with sodium dodecyl benzene sulfonate (SDBS). The use of this surfactant has been reported in the literature; however, its effect on the combustion and the stability of the nanofuels has been poorly described from a phenomenological point of view. The experiments were conducted by recording videos using a high-speed camera and the Shadowgraph optical technique. The resulting videos were analyzed through an algorithm developed in MATLAB. These results have been related to a stability analysis across a period of 21 days, as determined by measurements of dynamic light scattering (DLS), pH, and potential Zeta, among others, and properties such as thermal conductivity and surface tension. In terms of combustion efficiency and pollutant emissions, the characterization of the ignition delay and burning rate of these blends offers helpful information about how they would function in actual ignition compression engines.

2. Methodology

2.1. Nanofuels Preparation and Characterization

Commercial pristine carbon nanotubes (CNTs) from the company SkySpring Nanomaterials, Inc. (Houston, TX, USA) were used for the preparation of the nano-fuels. The technical specifications of the CNTs are found in Table 1. Additionally, scanning electron microscopy (FE-SEM) in a JEOL JSM7100F (JEOL Ltd., Tokyo, Japan) was also used to confirm the morphology and size of the CNT nanoparticles (Figure 1). In the first phase, nanomaterials were dispersed in Colombian commercial diesel (B10, 90% diesel, and 10% palm oil biodiesel) in a vessel with 50 mL of nanofuel. The nano-fuels were prepared using the two-step method [16], and two concentrations of CNTs were used: 50 ppm and 100 ppm. To maintain the stability of the dispersion, the anionic surfactant sodium dodecylbenzene sulfonate (SDBS, Sigma–Aldrich Pty. Ltd., Burlington, MA, USA) was used as a dispersing agent at a concentration of 0.02 w/v%. A Precisa EP225-DR microbalance (Precisa, Dietikon, Switzerland) was used to weigh the nanomaterials and the surfactant. SDBS and diesel blends were homogenized through a Branson 1800 ultrasonic bath before CNTs were added. A UP400St sonicator (24 kHz, Hielscher, Wanaque, NJ, USA) served to break agglomerates and disperse the nanomaterials in the diesel. During this procedure, the ultrasound equipment was set to 50% amplitude for 1 h. The main steps of this method are outlined in Figure 2, and the physicochemical properties of the base fuel and the resultant nanofuels are shown in Table 2.
On the other hand, after the nanofuels were made, they were tested to see how stable they were. The first parameter measured was the Zeta potential, which is the net surface charge of the nanomaterials in suspension. This measurement was carried out on a Nanoplus Particle Analyzer (Micromeritics Instrument Corporation, Norcross, GA, USA) after each time the nanofuels were made. Likewise, a dynamic light scattering (DLS) analysis was performed over the course of 21 days, with measurements being taken every 7 days. This was carried out to identify variations in the sizing of the nanomaterials in suspension. At the same time, photographs were taken to visually detect the sedimentation of the nanofuels at the moment of preparation and during the same days that the DLS measurements were made.
Additionally, thermal conductivity measurements were performed using a KD2 Pro Thermal Properties Analyzer (Decagon Devices, Inc., Pullman, WA, USA). This device uses the transient hot-wire approach as the basis for its operation. Such property was obtained at two temperatures, 20 °C and 60 °C, which were adjusted using a thermostatic bath. For each nanofuel, about ten experiments were performed right away after their preparation, ensuring that at least 15 min were given between measurements to allow for temperature stability. Under the identical conditions, the surface tension of the blends was measured using the Du Noüy ring method, utilizing a surface tensiometer Attention Sigma 701 (Biolin Scientific, Västra Frölunda, Sweden) and a thermostatic bath for temperature control. Furthermore, an ORION A325 pH/conductivity potable meter (Thermo Scientific™, Waltham, MA, USA) was used to measure the pH change of nanofuels in relation to commercial diesel. Once the nanofluids were prepared, measurements were made at room temperature. Finally, the thermal behavior of the nanofuel samples was characterized using a thermogravimetric analyzer (Discovery 550—TA Instruments, New Castle, DE, USA). A 50 mg sample was heated in a nitrogen atmosphere between 25 and 250 °C at a rate of 10 °C/min. Thermogravimetric analysis was conducted under these conditions to examine the influence of carbon nanotubes on fuel evaporation rates, which have a substantial impact on the reactant mixing inside the cylinder. This affects the ignition delay and fuel burning rates [8,41]. Furthermore, this test is commonly conducted to verify that the additive under consideration lacks a negative impact on fuel boiling points, which can be problematic in internal combustion engines [42,43].

2.2. Experimental Procedure

The evaluation of fuel properties, including the ignition delay and combustion rate, was carried out to determine the impact of adding carbonaceous nanoparticles to the fuel and their temporal stability. This was carried out by following the methodology presented by Ooi et al. [14], Mosadegh et al. [24], and Wang et al. [44]. Figure 3 shows a schematic representation and experimental setup of droplet combustion. A Chronos 1.4 high-speed camera (1) was used to obtain the images of the combustion of the diesel droplet (6); this camera has an image sensor of 8.45 × 6.76 mm with a Fill rate of 1.4 Gpx/s, which allows you to record up to 38,565 FPS at a resolution of 336 × 96. In this case, because high-quality images are needed for post-processing, the recording configuration used was 1057 FPS at a resolution of 1280 × 1024.
Furthermore, a data acquisition system (2) was used to process the temperature information obtained by the thermocouple (4), as well as to control the recording of the camera. Two biconvex lenses (3) were used to collimate the light rays towards the sample and the camera lens. With this configuration, a uniform background was obtained for the camera, and the light refracted (8) by the droplet allowed images to be taken with a defined droplet outline. Therefore, the shadowgraph optical technique was used to follow the droplet size evolution during the combustion process [45,46].
Each experimental test begins with the aggregation of a droplet of 3 μL of fuel through a micropipette in the middle of two crossed silicon carbide wires. Then, two pneumatic cylinders (7) on the sides each move an electrical resistance (5) that serves as an ignition system of the fuel droplet. A control system run by an Arduino processor was used to finally synchronize the system with the heating of the electrical resistances and the activation of the pneumatic cylinders.
In addition, the results are shown for the normalized area of the drop (A/A0), whose purpose is to show the relationship between the area of the drop at a given moment in time with respect to the initial area. Thus, the work proposed by Law [47] was followed, who proposes models for the transitory heating and combustion processes of fuel droplets, where the phenomenon of ignition and extinction is explained through kinetic models. The model starts from the explanation of the propagation speed of the fuel flame, which can be calculated from the combustion rate constant (K), following the D2 law, as shown in Equation (1).
D2 = DO2 − Kt
The ignition delay was obtained at 95% of the time at which the maximum expansion area occurs [24]. The droplet normalized area variation analysis with respect to time was carried out using the methodology developed in a previous work using a MATLAB code [45]. The algorithm is divided into three stages. In the first stage, the extraction of each video frame of the droplet combustion process is made; in the second stage, for each frame, a cut on the region where the combustion process occurs is made; finally, in the third stage, the image is binarize to obtain the droplet normalized area variation with respect to time.

2.3. Data Reduction

Table 3 shows the uncertainty of the equipment used to perform the TGA, SEM, and DLS analyses and the weigh measurement. In the case of the TGA, the maximum relative uncertainty in the measurement of temperature is 4%, which occurs at the beginning of the analysis, and this relative uncertainty reduces to 0.4% at the highest temperatures. Moreover, the uncertainty of the mass balance introduces a maximum relative uncertainty of 0.002% in the nanofuels concentration, while the maximum relative uncertainty of the hydrodynamic diameter measured with DLS is 0.02%. The uncertainty of the SEM does not introduce uncertainty in the results because we did not measure any variable with this instrument, which was used only for a qualitative characterization of the carbon nanotubes morphology.
Furthermore, as in our previous work [45], the droplet area was determined by counting the pixels in the binarized image. Therefore, our uncertainty analysis is limited to the standard deviation of the tests. Thus, three replicates of each fuel preparation were developed and burnt every week, as indicated above, with each set of tests consisting of burning ten droplets; thereby, the normalized area (A/A0) curve was obtained. The ignition delay and burning rate were then calculated.
The results show that each time step has a distinct standard deviation; therefore, the minimum, maximum, and average coefficients of variation of the A/A0 ratio for each fuel and nanofuel are calculated and displayed in Table 4. Such coefficients express the standard deviation as a percentage of the arithmetic mean, providing a relative interpretation of the degree of variation in the results between each replicate. The highest values achieved, as shown in Table 4, are close to 23.24%. Thus, the A/A0 mean value may be regarded as representative of the dataset, and the measured data for the A/A0 ratio at each time step are considered to be homogenous (less than 30%).
The ignition delay and burning rate uncertainty was calculated using a similar method. However, they lack the uncertainty associated with measurement equipment; therefore, for ignition delay, the period in which the A/A0 ratio is 95% of the highest value of the ratio was chosen as the delay time for this work. As a result, the ignition delay uncertainty was taken as the coefficient of variation for each experimental condition, taking into consideration the replicates included in the standard deviation. Likewise, the burning rate was calculated through the D2 law, which also depends on the A/A0 ratio. Table 5 shows the coefficient of variation (the ratio between the standard deviation and the mean) of the ignition delay and burning rate for each fuel and nanofuel, which are considerably lower than 30%, indicating that the dataset is homogeneous.

3. Results and Discussion

In order to estimate the ignition delay and combustion rate, the experimental results are explained in the following subsections. In addition, a brief explanation of the results supported by a nanofuels temporal stability analysis is given.

3.1. Stability Analysis

Figure 4a shows a quantitative description of the stability, which is given by the dynamic light scattering (DLS) measurements. This method analyzes the Brownian motion by detecting the oscillations of the light scattered by nanoparticles moving in the fuel at different speeds. Thus, the DLS relates the nanoparticles’ average speed to their size. In this case, the size increased during 21 days from 540 and 509 nm up to 1317 and 913 nm for CNTs at 50 ppm and 100 ppm, respectively. The size increments are the main consequence of the agglomeration and sedimentation of nanomaterials, which, in turn, occur due to the high surface energy of the nanoparticles, the van der Waals forces, and the collisions between nanoparticles caused by the Brownian motion.
According to the literature, the higher the concentration of nanomaterials, the larger the hydrodynamic size tested using DLS [48]. In this case, however, the addition of the surfactant SDBS produced the opposite effect since the hydrodynamic sizes were lower at 100 ppm than at 50 ppm. This effect can be related to the fact that, under typical surfactant dispersions in diesel, molecules tend to form micelles, which are groupings of molecules that form generally spherical forms when their polar ends interact. However, in certain conditions, particularly when using low quantities of nanomaterials, surfactants will probably form macromolecules (micelles or high quantities of a group of molecules), which leads to a depletion in the stabilization [49].
Therefore, when a CNT concentration of 50 ppm was dispersed with a concentration of SDBS of 0.02 w/v%, the surfactant concentration proved to be too high, and macromolecules were probably formed. In contrast, a concentration of CNTs of 100 ppm results in a high probability of interactions between SDBS and CNTs because SDBS attaches to the surface of CNTs and creates an absorption layer that surrounds the nanomaterials and prevents the creation of macromolecules [36]. Therefore, in the presence of SDBS, a concentration of 50 ppm exhibits worse stability than that of 100 ppm.
The above is validated with the visual inspection shown in Figure 4b, where the nanofuels tested are displayed. A CNT concentration of 100 ppm exhibits dispersed nanoparticles over the course of the visual inspection. Meanwhile, a CNTs concentration of 50 ppm shows sedimentation after fourteen days, as indicated by the blue line. Additionally, a noticeable distinction between the liquid and solid phases can also be seen. This results in a clearer black color due to changes in the colloidal suspension, which are related to the low stability of the concentration.
Figure 5 shows the changes in the pH and zeta potential caused by the addition of SDBS to CNT concentrations of 50 ppm and 100 ppm. The graphs are displayed together because the pH values affect the zeta potential, which alters the electrical charge density on the surface of the nanoparticles and can cause repulsive forces between nanoparticles that are dispersed [50]. The result shows that the pH related to diesel without nanoparticles and SDBS was near 4.8. Thus, with the SBDS addition, the pH was raised to 5.4 and the zeta potential was −28.3 mV. These values are due to the anionic nature of SDBS, and, therefore, the surface charge of nanomaterials should be negative and the pH value should raise [51].
Moreover, with CNTs dispersions, the changes in the Zeta potential and pH can be easily noticed because the number of counter ions close to the CNT nanoparticles surface is increased due to the presence of SDBS, which forms the electrical double layer. With the increase in the concentration from 50 ppm to 100 ppm, an increase in the number of ions getting attached to the particle surface is achieved [48], resulting from the removal of the macromolecules of SDBS. This could explain the superior stability of the nanofuels with a CNT concentration of 100 ppm, which exhibits a zeta potential of −104.5 mV and represents a value 54% higher than a CNT concentration of 50 ppm.
Additionally, the stability obtained with a CNT concentration of 100 ppm also might be explained by the Derjaguin, Verway, Landau, and Overbeek (DVLO) theory [52,53]. DLVO theory refers to the equilibrium between nanoparticle interactions and the double electric layer. In this instance, a CNT concentration of 100 ppm results in the predominance of the double electric layer due to the presence of SDBS, which creates an absorption layer that surrounds the CNTs and allows for the formation of smaller nanoparticles that stay dispersed in the fluid for a longer duration. In contrast, with a CNT concentration of 50 ppm, interactions between the nanoparticles are predominant, mostly mediated by Van der Waals forces, since the SDBS molecules probably formed macromolecules, as previously stated, and, as a result, the nanoparticles are larger and settle more quickly.

3.2. Thermal Conductivity and Surface Tension of Nanofuels

Figure 6 shows the measured thermal conductivities of diesel, diesel and SDBS, and nanofuels with CNTs at 20 °C and 60 °C after their preparation. A baseline using diesel was performed prior to the experimental design and compared to those suggested by the National Institute of Standards and Technology (NIST) [54]. In this case, standards for dodecane were taken into consideration, and a maximum error of 7% was found. According to the tests made at 20 °C, the addition of SDBS to diesel resulted in a negligible increase in thermal conductivity, which would provide comparable outcomes during heat transfer processes. On the other hand, the dispersion of CNT at 50 ppm and 100 ppm exhibits thermal conductivity enhancements of approximately 2% and 4%, respectively. However, in terms of thermal conductivity, diesel and SDBS exhibit a negligible difference when compared to a CNT concentration of 50 ppm.
Nevertheless, the thermal conductivity of the base fluid decreases at 60 °C, and the findings can exhibit a closer relationship with what happens throughout the heating and evaporation processes. In this case, the diesel thermal conductivity at 60 °C is 12% lower than that of diesel at 20 °C as a result of the rise in thermal resistance with temperature. At 60 °C, the thermal conductivity increased by 4% with the SDBS addition to diesel. Although the inclusion of nanoparticles at a concentration of 50 ppm encouraged the decrease in thermal conductivity measurements, the large nanoparticle sizes and instability promoted measurement error. This is due to the many nanoparticles that are continuously subjected to Van der Waals forces and Brownian motion, which might have favored this negative effect [55], as was previously described. However, a CNT concentration of 100 ppm improved the thermal conductivity by about 20% compared to diesel at 60 °C. This improvement may be attributed to the construction of thermal conductive grids for the avoidance of agglomeration due to the presence of SDBS because SDBS is attracted to the CNT surface and the weakening of van der Waals forces at a suitable concentration [56]. Additionally, the stability provided for SDBS also inhibits large sedimentation rates, which improves the thermal conductivity by allowing Brownian motion [57] and reducing surface resistance at the nanoparticle–liquid and nanoparticle–nanoparticle interfaces [58].
Figure 7 shows the surface tension obtained for diesel and the nanofuels with CNTS at 20 °C and 60 °C after their preparation. Surface tension is a determinant factor because it can affect the atomization, spray tip penetration, evaporation, and combustion processes of the fuel [59]. Diesel and SDBS blends were also examined in order to analyze the effect of the addition of SDBS independently. Thus, adding SDBS to diesel lowers the surface tension because this surfactant is located at the liquid–air interface and produces a thin layer that lowers the surface energy [60]. However, Figure 7 shows results for diesel and SDBS blends that might be statistically comparable to those obtained with only diesel. This is because the concentration of the surfactant used in this study is minimal enough to have an impact on surface tension, but it is enough to enhance the dispersion stability of CNTs in diesel, as was previously mentioned.
Additionally, as the temperature rose, the surface tension decreased linearly because of weakening attractive interactions between diesel molecules. This is because they are subjected to a process of thermal expansion [61,62]. The findings show statistically that the surface tension has negligible changes in comparison to diesel and diesel–SDBS blends at a temperature of 20 °C when CNTs are added in concentrations of 50 ppm and 100 ppm. Likewise, the results reveal similar values between both concentrations at a temperature of 60 °C.
These findings are comparable to those of Mei et al. [62], who demonstrate graphically that, when utilizing CTAB surfactant and CNT concentrations of 50 ppm and 100 ppm at 60 °C, the surface tension suffers a negligible increase of close to 2.5% and 4.6%, respectively. However, they point out that these minor changes result in an improvement in surface tension because this depends on the balance between the attractive force and the repulsive force, and the addition of nanoparticles implies that the attractive forces are significantly greater than the electrostatic repulsive force.
Nevertheless, the little variations depicted in Figure 7 indicate that the impact of surface tension is insignificant throughout the droplet combustion process since the utilization of SDBS and CNTs at the chosen concentrations is insignificant relative to the amount of diesel.

3.3. Evolution of the Normalized Area and Ignition Delay

Figure 8 shows the evolution of the normalized area analysis of several samples employing diesel, SDBS, and CNTs at concentrations of 50 ppm and 100 ppm. The study was performed for 21 days to evaluate the impact of the nanofuels’ temporal stability. In this instance, tests were conducted utilizing four replicas of diesel, diesel–SDBS, and diesel–SDBS–CNTs. Additionally, at least ten drops of each fluid were burned and assessed in order to guarantee the accuracy of the findings. Thus, in Figure 8, each curve is surrounded by a shadow of a similar color to the center line, which represents the standard deviation between each replica.
It should be noted that the normalized area increases over one in the early parts of the lines as a consequence of the droplet expansion, which is a result of the volatile diesel components evaporation [30]. Then, there is a process where a maximum area peak is reached, and this is attributed to the ignition point, after which the sudden reduction in area is attached to the burning of the fuel. A detailed explanation of the characteristics of the curve is given in our previous work [45]. In the case of the area reduction of diesel and diesel–SDBS droplets, similar results were obtained, which is related to the negligible effect of the SDBS during combustion.
The burning time is predicted to decrease with the use of nanomaterials [32]. Nevertheless, the combustion duration increased with the inclusion of CNTs at a concentration of 50 ppm (Figure 8a) in comparison to diesel and diesel–SDBS blends. In fact, the test on the preparation day (green line) indicates a prolonged combustion process and a hard start to the droplet burning. The findings of the normalized area after seven days reveal that there are negligible changes in combustion with regard to diesel and diesel–SDBS because the addition of CNTs at such concentrations could cause the ignition to take longer to start because of its slower burning rate. This is likely due to the CNTs tendency to be thermally resistant because of the high agglomeration rate caused by poor stability. That is, during combustion, the nanomaterials are positioned at the interface of the droplet, where they form a layer [28]. Thus, the thick multi-wall structure of the CNTs and the large agglomerates cause the temperature of the layer to rise more slowly during the heating and combustion processes, which prevents heat transfer to the fuel within the droplet [24]. As a result, the overall duration of the combustion process is expanded, which could result in a longer ignition delay, a consequence of the nanofuels’ stability at a CNT concentration of 50 ppm [48].
On the contrary, a CNT concentration of 100 ppm has shown better results during the combustion process, as shown in Figure 8b, since it has been observed that the combustion process for diesel and diesel–SDBS takes less time after each period of seven days after the preparation. In this situation, a porous layer is similarly anticipated to form on the droplet surface. However, the layer is anticipated to be thinner at this concentration as a result of the stability depicted in Figure 4 and Figure 5 above, which favors the rate of heat transfer towards the inner of the droplet. This is due to the fact that when the particle size is reduced, the porosity tends to be higher than that of big agglomerates [63,64], since the formation of the agglomerates might induce instability in the nanofuels and a decrease in porosity [65]. Therefore, at a CNT concentration of 100 ppm, the slower agglomeration of nanoparticles with time and the higher porosity relative to a concentration of 50 ppm provide enough time for the nanoparticles within the droplet to enhance the burning rate, with sufficient nanoparticles acting as thermal bridges and multiple heterogeneous nucleation sites within the droplet [26].
Otherwise, ignition delay refers to the amount of time required for the ignition to begin after the heating process has taken place (in this work, the activation of the electrical resistances). Physical and chemical delays are usually responsible for ignition delays. The physical delay is caused by the time required for the fuel to vaporize and the creation of combustible blends, whereas the chemical delay is caused by the hold-up in the fuel and air combustion reactions [66].
Figure 9 shows the ignition delay results after considering the temporal stability of the nanofuels. The ignition delay was determined at 95% of the time when the maximum peak expansion area occurred for each test. However, because droplet combustion is a very unexpected and difficult-to-replicate phenomenon, certain differences can be seen, such as those indicated by the standard deviation, because processes including heat transfer, thermal expansion, and evaporation are subject to rapid changes [67].
Thus, after preparation, the findings from using CNTs are comparable to those from using diesel and diesel–SDBS, although when a concentration of 50 ppm is tested, the ignition delay rises by around 7.6% in comparison to using diesel and diesel–SDBS. In fact, during the course of the 21-day test period, the ignition delay using nanofuels at a concentration of 50 ppm got worse. The limited stability of the nanofuels at such a concentration has an impact on the ignition time, indicating that this finding is closely connected to those in Figure 8a.
As was already explained, this outcome is linked to the formation of large agglomerates, which act as thermal resistances within the droplet and obstruct heat transfer. Additionally, the layer that forms at the interface encircles the droplet and absorbs additional heat, slowing the heating process. As a result, there is limited internal bubble nucleation, and the majority of burning only happens close to layer formation [26].
However, the use of CNTs at 100 ppm had the opposite effect, because improvements in the ignition delay of about 3.5%, 11%, 16.2%, and 15.3% were observed with respect to diesel, at the day of preparation, and after 7, 14, and 21 days, respectively. In this approach, the high stability and improvements in thermal conductivity demonstrated by the presence of these nanomaterials may be used to explain the improvement achieved by the addition of 100 ppm of CNTs to diesel. Furthermore, the characteristics mentioned by other research were reached with this concentration, such as high reactivity, fast burning, and a lower temperature required for ignition [30,67]. These factors together produced superior results with the use of CNTs at 100 ppm. Therefore, nanofuels may potentially be employed in practical applications and have superior properties compared to diesel throughout time, since improvements in the ignition delay may directly impact the efficiency and emissions of harmful gases from diesel engines [68,69].

3.4. Burning Rate Analysis

The rate of diffusion-controlled combustion between air and fuel in the vaporized state is referred to as the burning rate of a droplet. When examined in detail, as in the case of diesel engines, this parameter has a significant impact on performance and emission characteristics [66]. In this work, the burning rate constant of each droplet was assessed inside the burning zone of the droplet, using the D2 law provided in Equation (1).
The transient burning rate curves of the tested nanofuels with respect to time are shown in Figure 10. The curves have a direct relationship with the ignition delay (Figure 9) and the area reduction curves (Figure 8). In fact, the findings are consistent across all analyses. For instance, negligible changes are found using SDBS in comparison to diesel. Likewise, the results obtained with the usage of CNTs at a concentration of 50 ppm are unpromising, as previously mentioned. This is a consequence of the increase in ignition delay up to 7% with respect to diesel. Therefore, the curves are shown starting at much longer time values than the diesel and diesel–SDBS curves. In fact, over the 21-day test period, the maximum burning rate was never larger than the maximum for diesel and diesel + SDBS. On the contrary, the results show that at concentrations of 50 ppm, the value of the combustion rate is reduced by up to 16%, which is consistent with the findings of the ignition delay (Figure 9) and is attributed to the decrease in stability that the nanofuels exhibit at such concentrations, the limited increase in thermal conductivity, and the decrease in CNT porosity.
Figure 10 also shows the burning rate for the use of CNTs at a concentration of 100 ppm in comparison with diesel and diesel–SDBS. The findings are coherent with the area reduction curves (Figure 8) and the ignition delay results (Figure 9), since it is clear that using nanomaterials at this concentration enhances the burning rate over diesel and diesel–SDBS. The burning rate increases between 18% and 30.5%, which implies that the droplet lifetime is constantly lower. According to the result, the highest burning rate (2.33 mm2/s) was reached after 7 days of preparation. Figure 9 demonstrates that while the nanofuels had a longer ignition delay at 7 days than at 14 days and 21 days, the burning rate upon ignition was substantially greater. That result is a consequence of the following features: First, the colloidal stability of the dispersion of CNTs with adsorbed molecules on their surface is guaranteed by the electrostatic repulsion given the presence of SDBS [70]. Second, this electrostatic repulsion restricts the agglomeration of the nanoparticles, and, as a result, the porosity is maintained [63,64] and the active nucleation sites are preserved. Third, the concentration of 100 ppm has smaller particle sizes than the concentration of 50 ppm, which avoids the development of porous layers that prevent heat transfer toward the drop core and diffusion between the air and fuel [24]. Finally, research has demonstrated that the presence of nanomaterials can increase the thermal conductivity of the fuels (as shown in Figure 6), leading to higher combustion and evaporation rates [36]. However, since the best performance is demonstrated by a concentration of 100 ppm, after 21 days of preparation, the results must be evaluated broadly, since both the ignition delay and the burning rate impact the lifetime of the droplet.
As a special remark about the precedent results, the study of the ignition delay and burning that we performed in this work was conducted in a combustion chamber at atmospheric pressure, while combustion in compression ignition engines occurs at higher pressures. However, since some researchers have linked the properties of combustion or evaporation with the outcomes of applying nanofuels to diesel engines [36,71,72], the behavior in the ignition delay and burning rate for a diesel engine may be comparable with the trends and implications of the present results. Those researchers claim that the increase in the rate of heat transfer and the high surface area/volume ratio that nanomaterials provide are likely the cause of the results found in this research, which may show the possibility of introducing nanomaterials in real engines.

3.5. Thermogravimetric Analysis

Figure 11 shows the nanofuels thermogravimetric analysis (TGA), which included commercial diesel, SDBS, and CNTs blends at two concentrations, 50 ppm and 100 ppm. Figure 11 shows the evaporation process by heating at a rate of 10 °C/min in a nitrogen atmosphere between 25 and 250 °C. As a result, Figure 11a,c display the weight percentage decreasing in relation to the rise in the temperature. Tests were carried out every week for 21 days after the nanofuels preparation, and at least three replicates were performed weekly. The same mass loss curve applies to all fuels. However, this loss occurs at different temperatures because different factors may have an impact on the apparent heat of vaporization. As a consequence, the presence of SDBS and CNTs causes changes in physical properties (such as viscosity and nanofuels’ stability [73]) that affect the rate of vaporization.
In this case, adding SDBS accelerates the rate of evaporation, since the weight loss percentage occurs at lower temperatures than for diesel. This could be because diesel and SDBS have different thermophysical properties [74]; therefore, using SDBS, the evaporation process is faster than when only diesel is evaporated. For instance, small droplets, such as those typical of micro-explosions, may thus separate from the fluid and enhance weight loss because, first, the small and detached droplets evaporate more quickly and, second, this surface separation produces a greater heat transfer area [75]. Nevertheless, when CNTs are added to the diesel–SDBS blend at a concentration of 50 ppm, the weight loss with respect to temperature demonstrates that the nanofuels require a higher temperature for their evaporation, as shown by the derivative of weight with respect to temperature (Figure 11b). This result was expected because of the poor stability (Figure 4 and Figure 5) and the droplet combustion results (Figure 8) at such concentration. As was previously stated, this might be caused by the possibility of thick surface layers of nanomaterials at the fuel interface, which would produce an additional heat resistance that prevents the evaporation process.
Contrary to the findings of the area reduction and burning rate, a CNT concentration of 100 ppm cannot enhance the evaporation process of the nanofuels (Figure 11c,d). This is likely to be a consequence of the fact that properties like the surface tension, density, viscosity, and evaporation temperature are determining factors in the decomposition process in an inert atmosphere [76]. Additionally, the improvement in the evaporation process requires the presence of an oxidizing environment [33,77] because the heat released during oxidation enhances the evaporation rate of the unburned fuel. Therefore, future research might focus on the influence of CNTs on the evaporation process, both in inert and oxidizing atmospheres, which could be linked to a detailed stability study, giving more precise information about the phenomenology that occurred in the diesel engine when nanoparticles dispersed in the fuel are used.

4. Conclusions

In this study, an experimental investigation of combustion parameters, such as the ignition delay and burning rate, was conducted through the optical analysis of the combustion evolution of a single drop of commercial Colombian diesel containing a dispersion of pristine carbon nanotubes (CNT) and stabilized with sodium dodecyl benzene sulfonate (SDBS), using the shadowgraph technique. According to the results, the following conclusions were reached:
  • Through the use of DLS, visual inspection, pH, and Zeta potential measurement, the nanofuels at a concentration of CNTs at 100 ppm were demonstrated to be more stable than those at 50 ppm. These findings might be explained by the presence of SDBS, which at a CNTs concentration of 50 ppm probably creates macromolecules which promote a decrease in stability. On the other hand, there is possibly the existence of interactions between CNTs and SDBS at a concentration of 100 ppm because SDBS attaches to the surface of CNTs and forms an absorption layer that surrounds the nanomaterials and inhibits the formation of macromolecules, which significantly enhances temporal stability at this concentration.
  • The SDBS at a concentration of 0.02 w/v% in commercial diesel had a minimal impact on the thermal conductivity at 20 °C, while by utilizing CNTs at a concentration of 50 ppm and 100 ppm, the thermal conductivity increased by 2% and 4%, respectively. However, at 60 °C, a concentration of 50 ppm showed negative effects on thermal conductivity, whereas with a concentration of 100 ppm, the thermal conductivity increased by around 20%. On the other hand, the results indicate that when diesel–SDBS–CNTs blends are used at temperatures between 20 °C and 60 °C, the surface tension has negligible changes in comparison to commercial diesel.
  • The duration of the combustion process is influenced by the stability of nanofuels at a concentration of 50 ppm, with greater durations for the first day and minimal changes after seven days for diesel and diesel–SDBS. However, a concentration of 100 ppm provided better results, since the combustion of diesel and diesel–SDBS took less time after each interval of seven days. This is because, compared to a concentration of 50 ppm, nanoparticles aggregate more slowly and have higher porosity, giving them more time to improve combustion by acting as thermal bridges and having numerous heterogeneous nucleation sites within the droplet. Therefore, adding 50 ppm of CNTs to diesel causes the ignition delay time to increase by roughly 7.6%, and adding 100 ppm causes a decrease by roughly 16.2%.
  • According to the data, the combustion rate is lowered by up to 16% at concentrations of 50 ppm. This is a result of the nanofuels’ decreased stability at this concentration, their limited increase in thermal conductivity, and their decreased porosity. On the contrary, at a concentration of 100 ppm of CNT, the burning rate of diesel and diesel–SDBS was improved by between 18% and 30.5%.
  • A fundamental study, such as the one described in this work, may demonstrate the impact of carbon nanotubes in fuel dispersions and their subsequent usage in diesel engines, which can influence polluting gas emissions and performance. Therefore, future research may link the application of CNTs in diesel engines and combine the findings with a comprehensive stability study demonstrating the influence of fuel storage in tanks.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/en16237740/s1.

Author Contributions

A.G.: Methodology, Validation, Investigation, Formal analysis, Data curation, Writing—original draft. K.C.: Conceptualization, Formal analysis. J.R.: Methodology, Software, Formal analysis, Data curation. D.G.: Validation, Formal analysis, Investigation, Data curation. B.H.: Conceptualization, Methodology, Formal analysis, Writing—review and editing, Supervision, Project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This research and the APC was funded by Ministerio de Ciencia, Tecnología e Innovación de Colombia—Minciencias. The research program is titled as “Use of carbon nanomaterials as additives in diesel for internal combustion engines working in dual mode with natural gas and their effects on yield, pollutant emissions, and cell damage”, and the grant number is “508 program”.

Data Availability Statement

The primary data used for the main calculations are included in the publication and Supplementary Materials.

Conflicts of Interest

The authors declare no conflict of interest.

Nomenclature

A/A0Normalized area of the drop
CNTCarbon nanotubes
DLSDynamic light scattering
KBurning rate constant
SDBSSodium dodecylbenzene sulfonate
TGAThermogravimetric analysis

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Figure 1. SEM images of CNT nanoparticles.
Figure 1. SEM images of CNT nanoparticles.
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Figure 2. Nanofuels preparation method. Created with Biorender.
Figure 2. Nanofuels preparation method. Created with Biorender.
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Figure 3. Schematic representation and experimental setup of droplet combustion.
Figure 3. Schematic representation and experimental setup of droplet combustion.
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Figure 4. Characterization of the hydrodynamic size of CNTs in the nanofuels. (a) DLS results and (b) visual inspection for different days after nanofuels preparation. The size increases because CNT nanomaterials were agglomerating inside the fuel over the days, which causes sedimentation.
Figure 4. Characterization of the hydrodynamic size of CNTs in the nanofuels. (a) DLS results and (b) visual inspection for different days after nanofuels preparation. The size increases because CNT nanomaterials were agglomerating inside the fuel over the days, which causes sedimentation.
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Figure 5. Zeta potential and pH measurements after nanofuels preparation at a CNT concentration of 100 ppm.
Figure 5. Zeta potential and pH measurements after nanofuels preparation at a CNT concentration of 100 ppm.
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Figure 6. Thermal conductivity of nanofuels at 20 °C and 60 °C after preparation with CNTs at 50 ppm and 100 ppm, stabilized with SDBS.
Figure 6. Thermal conductivity of nanofuels at 20 °C and 60 °C after preparation with CNTs at 50 ppm and 100 ppm, stabilized with SDBS.
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Figure 7. Surface tension of nanofuels at 20 °C and 60 °C after preparation with CNTs at 50 ppm and 100 ppm stabilized with SDBS.
Figure 7. Surface tension of nanofuels at 20 °C and 60 °C after preparation with CNTs at 50 ppm and 100 ppm stabilized with SDBS.
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Figure 8. Evolution of the normalized area of nanofuels during droplet combustion with diesel, SDBS, and CNTs at concentrations of (a) 50 ppm and (b) 100 ppm.
Figure 8. Evolution of the normalized area of nanofuels during droplet combustion with diesel, SDBS, and CNTs at concentrations of (a) 50 ppm and (b) 100 ppm.
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Figure 9. Temporal analysis of the ignition delay of nanofuels during droplet combustion with diesel, SDBS, and CNTs at concentrations of 50 ppm and 100 ppm.
Figure 9. Temporal analysis of the ignition delay of nanofuels during droplet combustion with diesel, SDBS, and CNTs at concentrations of 50 ppm and 100 ppm.
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Figure 10. Effect of the CNT and SDBS nanofuels’ temporal stability on the diesel droplet burning rate at CNT concentrations of 50 ppm and 100 ppm.
Figure 10. Effect of the CNT and SDBS nanofuels’ temporal stability on the diesel droplet burning rate at CNT concentrations of 50 ppm and 100 ppm.
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Figure 11. Temporal thermogravimetric analysis of diesel, SDBS, and CNT blends at concentrations of 50 ppm (a,b) and 100 ppm (c,d). Circle A (in (a,c)) indicates an expanded region in the miniature detail graphs.
Figure 11. Temporal thermogravimetric analysis of diesel, SDBS, and CNT blends at concentrations of 50 ppm (a,b) and 100 ppm (c,d). Circle A (in (a,c)) indicates an expanded region in the miniature detail graphs.
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Table 1. Technical specifications of the carbon nanotubes used in this study.
Table 1. Technical specifications of the carbon nanotubes used in this study.
TypeSpecification
Purity>95%
External diameter20–30 nm
Internal diameter5–10 nm
Length10–30 µm
Surface area>110 m2/g
Density2.1 g/cm3
Table 2. Physicochemical properties of the fuels and nanofuels.
Table 2. Physicochemical properties of the fuels and nanofuels.
PropertyUnitDieselDiesel + SDBSDiesel + SDBS + CNT 100 ppmStandard
Kinematic viscosity at 40 °Cmm2/s3.7714.3744.469ASTM D445
Cetane index-48.6848.9048.80ASTM D976
Heating valueMJ/kg45.1444.9444.92ASTM D240
API gravity of petroleum products at 15.6 °C°API33.231.831.8ASTM D287
Gum content in fuel by evaporation jetmg/100 mL49.535.515.5ASTM D381
Pour point°C−15−12−12ASTM D97
Flashpoint°C717273ASTM D93
Cloud point°C2−1−6ASTM D2500
Table 3. Uncertainty of the instruments used in the characterization and preparation of the nanofuels.
Table 3. Uncertainty of the instruments used in the characterization and preparation of the nanofuels.
ParameterInstrumentUncertainty
Thermogravimetric analysisTA Instrument SDTQ 600±1 × 10−7 g and ±1 °C
Scanning Electron MicroscopyJEOL JSM-7100F±1.2 nm
Dynamic Light Scattering (DLS)Micromeritics Nanoplus HD±0.1 nm
Carbon nanotubes weightPrecisa EP225-DR±1 × 10−6 g
Table 4. Maximum, minimum, and average coefficients of variation for each fuel and nanofuel during the course of the test.
Table 4. Maximum, minimum, and average coefficients of variation for each fuel and nanofuel during the course of the test.
Fuel/NanofuelDay of the TestsCoefficient of Variation of A/A0
MaximumMinimumMean
Diesel-19.63%0.04%2.11%
Diesel + SDBS-12.70%0.01%1.56%
Diesel + SDBS + CNT 50 ppmPreparation day20.40%0.02%2.49%
7 days18.64%0.01%2.21%
14 days18.76%0.01%1.93%
21 days15.46%0.01%1.86%
Diesel + SDBS + CNT 100 ppmPreparation day19.52%0.02%2.86%
7 days14.86%0.02%1.89%
14 days23.24%0.02%3.50%
21 days12.92%0.02%1.96%
Table 5. Coefficients of variation of the ignition delay and burning rate for every fuel and nanofuel during the test.
Table 5. Coefficients of variation of the ignition delay and burning rate for every fuel and nanofuel during the test.
Fuel/NanofuelDay of the TestsCoefficient of Variation of the Ignition DelayCoefficient of Variation of the Burning Rate
Diesel-1.76%5.98%
Diesel + SDBS-2.17%3.16%
Diesel + SDBS + CNT 50 ppmPreparation day1.87%4.03%
7 days3.89%2.92%
14 days1.12%7.00%
21 days2.13%8.18%
Diesel + SDBS + CNT 100 ppmPreparation day3.22%5.16%
7 days2.41%2.80%
14 days2.59%4.33%
21 days3.30%4.92%
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MDPI and ACS Style

Gallego, A.; Cacua, K.; Gamboa, D.; Rentería, J.; Herrera, B. Ignition Delay and Burning Rate Analysis of Diesel–Carbon Nanotube Blends Stabilized by a Surfactant: A Droplet-Scale Study. Energies 2023, 16, 7740. https://doi.org/10.3390/en16237740

AMA Style

Gallego A, Cacua K, Gamboa D, Rentería J, Herrera B. Ignition Delay and Burning Rate Analysis of Diesel–Carbon Nanotube Blends Stabilized by a Surfactant: A Droplet-Scale Study. Energies. 2023; 16(23):7740. https://doi.org/10.3390/en16237740

Chicago/Turabian Style

Gallego, Anderson, Karen Cacua, David Gamboa, Jorge Rentería, and Bernardo Herrera. 2023. "Ignition Delay and Burning Rate Analysis of Diesel–Carbon Nanotube Blends Stabilized by a Surfactant: A Droplet-Scale Study" Energies 16, no. 23: 7740. https://doi.org/10.3390/en16237740

APA Style

Gallego, A., Cacua, K., Gamboa, D., Rentería, J., & Herrera, B. (2023). Ignition Delay and Burning Rate Analysis of Diesel–Carbon Nanotube Blends Stabilized by a Surfactant: A Droplet-Scale Study. Energies, 16(23), 7740. https://doi.org/10.3390/en16237740

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