Automotive Coatings Research Articles

Influence of Reclaimed Water on the Visual Quality of Automotive Coating.

In the present study, the possibility of recovering water in a car wash station was presented. The resistance of automotive coatings to washing water recovered at 50% and 70% from wastewater generated at car wash was tested. Wastewater treatment was carried out by ultrafiltration (UF) using tubular polyvinylidene fluoride (PVDF) membranes (100 and 200 kDa) manufactured by the PCI company. The membranes retained oil contamination, suspended solids, and over 60% of surfactants. For comparison, the 0.5% Turbo Active Green solution, used at professional car washes, was also applied in paint resistance studies. The tested solutions washed the painted surfaces of samples taken from car doors for 8 days. The resistance of automotive coatings to washing solutions was assessed by measuring gloss, Log Haze, RIQ, and Rspec parameters. Scratch resistance was also assessed. The results obtained in the current study indicated that the use of water recovered from wastewater did not deteriorate the quality of the car paint coating.

Detection of topology freezing transition temperature of vitrimers based on photonic coatings from photonic crystals and vitrimers

There are a few methods to measure topology freezing transition temperature (Tv) of vitrimers while the samples are needed to be under external force or additional substances. The novel photonic coatings from the lower photonic crystals (PCs) and the upper vitrimers are fabricated and used to detect Tv of vitrimers. The photonic coatings have photonic stopbands (or structural colors) because of PCs. When photonic coatings are heated, PCs from SiO2 spheres are stable, vitrimers are transformed from solid state to fluid state, light would be easily pierced through vitrimers and reflect off PCs, the intensities of reflection peaks of photonic coatings increase slowly, increase sharply and keep unchanged at three stages. So Tv of vitrimers are directly observed and obtained according to these great changes. The values of Tv of the vitrimers from different synthesis conditions are different. The novel method is simple, intuitive and without external force and additional substances. The photonic coatings also have good toluene-resistance and self-healing property. They have potential applications in detection of Tv of other vitrimers, displays, anti-counterfeiting and automotive coatings.

Design of dark-colored acrylic coatings for increased LiDAR detection in autonomous vehicles

Light Detection and Ranging (LiDAR) is the major sensor for autonomous vehicles. It emits near-infrared (NIR) pulsed light at 905 nm and detects the reflected portion of this light from the surrounding objects. Location and surface determination of the surrounding objects is performed using the time-of-flight (the elapsed time from launch of a pulsed beam to detection of the reflected returned beam). Solvent borne acrylic paints gained wide currency for the exterior automotive coatings over the years and topcoats with conventional dark-colored pigment dispersions exhibit low reflectivity in the NIR region. The formulation of innovative topcoats with high reflectivity in this region is an urgent task for leading paint manufacturers. In this study, pigment dispersions to be incorporated in LiDAR-detectable solvent borne acrylic automotive topcoats were designed considering the surface charges of individual pigment particles for dispersant selection. Stability of designed dispersions was demonstrated and color matching studies were realized. Three dark colors encoded RAL 9011 (Graphite black), RAL 5017 (Traffic blue), and RAL 5015 (Sky blue) from the RAL 841-GL color chart were formulated as acrylic topcoats with NIR reflective pigments. Based on the surface properties of the dry films, such as gloss, haze and distinctness of image, a significant increase in LiDAR detection was achieved for each color. The results affirmed the potential use of the developed formulations as end-product paints for coating the exterior surfaces of autonomous vehicles.

Innovative multifunctional nanocomposite coated aluminum alloy for improved mechanical, flame retardant, and corrosion resistance in automobile industries

ABSTRACT Nanocomposites with impermeable two-dimensional materials show promise for metal corrosion protection. A coating matrix incorporating (3-aminopropyl)trimethoxysilane (AMS) functionalized molybdenum nitride (Mo2N) enhances the barrier effect due to its chemical and thermal stability. Further improvement is achieved by adding functionalized Mo2N into graphitic carbon nitride (GCN) within a polyurethane (PU) matrix, enhancing corrosion protection and fire retardancy. Electrochemical techniques evaluated the efficacy of aluminium coated with PU and varying concentrations of functionalized Mo2N/GCN. The resulting PU composite exhibited superior flame retardant capabilities, reducing peak heat release rate (pHRR), total heat release (THR), and total smoke production (TSP) compared to pure PU. Electrochemical impedance spectroscopy (EIS) showed enhanced coating resistance (5.55 × 101 1 Ω.cm2) even after 500 hours of exposure. Additionally, the composite displayed exceptional water repellency with a water contact angle (WCA) of 156° and commendable mechanical properties, including an adhesive strength of 19.2 MPa within the PU substrate. This multifunctional PU composite, incorporating functionalized Mo2N/GCN, presents a promising option for automotive coatings, offering corrosion protection, flame retardancy, water repellency, and mechanical robustness, thus enhancing durability and performance in harsh conditions.

Новітні технології в екологічно безпечних полімерних покриттях: дослідження, технології, перспективи

The scientific work is aimed at the study of environmentally friendly polymer coatings in the automotive industry, which constantly attracts the attention of scientists and practitioners. The article analyzes the current state of technology in this area, reviews the latest research and technological developments, and discusses their prospects for implementation in production. Starting with a review of the latest research on paints and coatings, the paper goes on to discuss self-healing materials and microcapsules that have the potential to create resistant and durable coatings.The paper also discusses anti-corrosion coatings, which are an important part of protecting automotive structures from the effects of negative environmental factors. Particular attention is paid to the development of environmentally friendly polymer coatings that meet the requirements of sustainable development and reduce the environmental impact of the industry on the environment.In addition, the latest trends in the industry are analyzed, which allows us to predict further directions of technology development and implementation of innovative solutions. The work has important practical application in the automotive industry, contributing to improving the quality of automotive coatings protection against corrosion and extending their service life in various operating conditions. The work is aimed at highlighting relevant aspects of research in the field of environmentally friendly polymer coatings and provides a valuable contribution to the development of this important industry. The results will improve the quality and duration of corrosion protection of paintwork, metal structures and other products.The use of the latest materials and technologies in the manufacture of coatings is driven by the need for their environmental friendliness, efficiency and durability. However, the introduction of some new technologies faces limitations, in particular, related to their economic feasibility and scalability. In this regard, further research is needed to optimize technologies and materials to achieve greater efficiency in road transport.

PPG appointed two executive roles for its industrial and automotive coatings divisions

PPG appointed two executive roles for its industrial and automotive coatings divisions

Дослідження методів випробування лакофарбового покриття на стійкість до корозії

This scientific work is aimed at researching the testing methods of paint coatings used for protecting the metal parts of automobiles in order to determine their resistance to corrosion processes. Paint coatings are used to protect the metal surfaces of automobiles from corrosion in various climatic conditions and under the influence of aggressive factors such as atmospheric conditions, chemical substances on the road, polluted air, and other corrosive environments, making their quality and effectiveness of great significance.
 Different methods of testing paint and varnish coatings are considered, such as neutral salt spray test, acetic acid salt spray test (with and without copper acceleration), and cyclic corrosion testing. Attention is also given to parameters such as test duration, temperature regimes, and chemical aggressiveness of the environment to establish the effectiveness of these methods. The analysis of the tests allows determining which methods best meet the requirements for assessing the corrosion resistance of paint coatings. The work also investigates the impact of various factors, such as the type of paint coating, surface preparation, and operating conditions, on the test results. It was determined that the proper selection of test methods and adequate assessment of their effectiveness help in improving the corrosion resistance of the paint coating in various operating conditions.
 The work has important practical applications in the automotive industry by enhancing the quality of protection for automotive coatings against corrosion and extending their service life in various operating conditions. The obtained results will help improve the quality and durability of paint coatings, metal structures, and other products against corrosion by choosing the optimal method for testing paint coatings. This scientific work has practical significance for engineers and manufacturers involved in the development and application of corrosion-resistant coatings.

Application of Accelerated Light Aging Test in the Quality Evaluation of Automotive Coatings

Application of Accelerated Light Aging Test in the Quality Evaluation of Automotive Coatings

Numerical simulations of stone-chipping resistance behaviors of automotive coatings: A CFD-DEM model and a wear prediction method

Automotive coatings often suffer from high-speed stone impact wear damage. Currently, it remains a significant challenge to evaluate the stone-chipping resistance performance of automotive coatings. The main purpose of this work is to develop a computational approach combining a numerical model with a prediction method to achieve this end. The numerical model is developed based on the Computational Fluid Dynamics (CFD) and the Discrete Element Method (DEM) to account for the moving behaviors of large, irregularly shaped stone chips driven by high-pressure airflow in a multifunctional anti-impact tester. In this model, stone chips are represented using multi-spheres. To address the mismatch issue in the inlet boundary conditions, this study utilizes high-fidelity modeling of the tee pipe in a multi-functional impact tester. Additionally, it takes into account the influence of the high-pressure airflow compressibility on particle behaviors. A wear prediction method is further developed. Within this method, a particle erosion model is utilized to account for short-term coating damage evaluation based on CFD-DEM simulation results. Subsequently, a prediction method is proposed to efficiently estimate long-term damage for a DIN standard multi-particle impact case by using mean-range random functions. With the aid of the developed computational method, single- and multi-particle impact simulations are conducted, and numerical results are found in good agreement with experimental data in terms of the damage distribution trend and impact position distributions.

A graphics processing unit-based computational framework for impact failure of automotive coatings

This paper is the first one to develop a graphics process unit-based computational framework to accelerate impact failure simulations of automotive coatings, which require a considerable computational cost. Such an efficient computational framework considers both intra- and inter-laminar failures, including a multi-mechanism damage model for polymer-ply fracture and a discontinuous Galerkin/cohesive zone model for coating delamination. The cohesive zone model is implemented as a contact algorithm with a cohesive constitutive law, hence maintaining the ability to simulate delamination problems under large deformation. Additionally, a parallel contact algorithm for the cohesive zone model is developed with the simultaneous elimination of bitwise non-reproducibility and unphysical force oscillations occurring when Gauss points transition between segments. After verification via numerical examples, this framework is applied to the impact failure of multi-layered automotive coatings, where experimental failure patterns of the coating are well reproduced. Through parallel computing, a speedup of up to 119.7 times in terms of wall clock time is gained.

Sunflower oil-based polyurethane/graphene composite: Synthesis and properties

Polyurethane/graphene composites have attracted significant attention featuring their wide applications in automotive interiors, coatings, and leather parts to bioengineering. This research focuses on the facile synthesis of biobased polyurethane (PU) by employing sunflower oil as a renewable resource. The synthesized biobased PU was reinforced with graphene nanoplatelets (GNP) and graphene nanoribbons (GNR) to fabricate composite films by solution-casting technique. By changing the filler content (0.01-0.05 wt%), a series of composite films were prepared. The addition of graphene derivatives to the PU matrix improved the mechanical, thermal, and surface properties of the composites compared to the pristine PU film. The incorporation of GNR and GNP fillers enhanced the storage modulus of polymeric film, as for neat PU, was noted maximum at 892 MPa which increased and noticed a maximum of 1121 MPa and 1487 MPa for 0.02 wt % GNP/PU and GNR/PU composite films, respectively. The tensile strength was obtained at 35 MPa and 14 MPa for 0.02 wt % GNP/PU and 0.01 wt % GNR/PU, as compared to 9.45 MPa for the pure PU film. The morphological studies by atomic force microscopy showed a good distribution of GNR and GNP fillers within the polyurethane matrix. The GNP/PU and GNR/PU composite films displayed excellent chemical resistance to different solvents. This work put forward a great utilization of renewable sunflower oil and graphene derivatives to fabricate PU composites with improved properties for potential applications.

Solid particle erosion evaluation of automotive paint coatings under the influence of artificial weathering

Solid particle erosion (SPE) is one of the most critical tribological problems causing damage to automotive paint coatings. The correct characterization of SPE and resistance against it makes the possible extended service life of the coating, increasing the resale value of cars. Car manufacturers and paint industries have developed new techniques to apply coatings and coatings that improve the initial and long-term appearance, scratch performance, and durability of coatings. Several works have focused on studying the degradation and performance of paint coatings. However, there needs to be more understanding of wear progress under different environmental degradation conditions. This study investigates the mechanisms and resistance of erosive wear of actual automotive paint coatings before and after exposure to an accelerated weathering process. Steel substrate panels with a typical paint coating system were exposed to weathering degradation by UV and immersion in an artificial acid rain solution. The chemical changes induced in the coatings were analyzed by FT-IR spectroscopy. Then erosive tests were carried out using silica sand particles at two different angles of incidence (30° and 90°) and temperatures (25 °C and 60 °C) for both samples (unexposed and weathering conditions). The SPE rate was determined for each coating by mass loss estimation using an analytical balance; meanwhile, wear mechanisms were analyzed in detail by SEM. The results showed decreased SPE resistance promoted by chemical changes in samples exposed to both weathering processes.

Investigation of 3D printed lightweight hybrid composites via theoretical modeling and machine learning

Hybrid composites combine two or more different fillers to achieve multifunctional or advanced material properties, such as lightweight and enhanced mechanical properties. The properties of the composites significantly depend on their microstructures, which can be tailored via advanced 3D printing processes. Understanding the process-structure-property relationships is critical to enable the design and engineering of novel hybrid composites for applications in aerospace, automotive, and protective coatings. Here, we develop 3D printable and lightweight hybrid composites and leverage the conventional design of experiments, a theoretical hybrid model, and an image-driven machine learning (ML) method to investigate their mechanical behaviors. The hybrid composites are formulated with elastomer matrix, microfillers, and thin-shell particles, enabling a significant degree of design freedom of microstructures with densities and mechanical properties varying up to 70% and 91%, respectively. Our statistical analysis indicates that the 3D printing path direction and the microfibers fraction are dominating process parameters with contribution percentages of 45.3% and 57.7% on the specific stiffness and strength, respectively. A hybrid mechanics model is developed based on a simple Weibull distribution function and classical single-filler models to effectively capture the variations in mechanical properties, however, it overestimates the values due to its statistical constraints and idealization of experimental uncertainty. The image-driven ML model leverages the microscale images directly without losing the structural details, shows more accurate predictions with experimental data, and has 48.6% lower root mean square error than the theoretical model.

PPG appoints Alisha Bellezza Vice President, Global Automotive Coatings

PPG appoints Alisha Bellezza Vice President, Global Automotive Coatings

Environment-friendly coating with good weather resistance prepared by amorphous photonic crystals and water-dispersible resin

Traditional coatings are fabricated from chemical colorants and oleoresinous resins. However, chemical colorants and organic solvents as diluents of oleoresinous resins are pollutant for environment. Herein, environment-friendly coatings with good weather resistance are proposed by using amorphous photonic crystals (APC) and water-dispersible resins. Monodispersed silica spheres are used for producing APC and structural color. And the water-dispersible epoxy resin has a good weather resistance property. After environment-friendly coatings are submerged in toluene, acidic solution (pH = 2) and alkaline solution (pH = 12) for 2040, 840 and 840 h, respectively, the coatings are still intact, and they do not fade. The environment-friendly coatings also are able to withstand the test of 336 h under ultraviolet light. The coatings have great potential applications in displays, decorations and automotive coatings.

The 2023 Automotive Coatings Market

The 2023 Automotive Coatings Market

High-fidelity computational modeling of scratch damage in automotive coatings with machine learning-driven identification of fracture parameters

As one of the key components of a vehicle, automotive coating systems are typical micro-size multilayer composites, which normally suffer from intricate scratch damage. Currently, it is a challenging task to reproduce the complex physical phenomena of automotive coatings with micron thickness using numerical simulations. The purpose of this work is to develop a computational framework for an accurate evaluation of such scratch damage. To achieve this end, a high-fidelity finite element (FE) model is proposed, where a rate-dependent cohesive zone model is developed to account for coating crack behaviors. A reverse identification approach based on the machine learning (ML) method is suggested to determine the rate-dependent cohesive parameters that are difficult to be measured via direct experiments. In the course of recognition, this work develops a two-step regional data augmentation strategy based on the existing single-shot recognition method. The developed strategy is capable of reducing the number of training data samples, while improving identification accuracy and robustness. With the identified cohesive parameters, the proposed finite element model is applied to simulate speed-dependent coating scratch behaviors. The good agreement between numerical and experimental results demonstrates the capacity of our developed computational framework for coating scratch problems.

Effects of Interlaminar Failure on the Scratch Damage of Automotive Coatings: Cohesive Zone Modeling.

Interlaminar failure caused by scratches is a common damage mode in automotive coatings and is considered the potential trigger for irreversible destruction, i.e., plowing. This work strives to numerically investigate the mechanisms responsible for the complex scratch behavior of an automotive coating system, considering the interfacial failure. A finite element model is developed by incorporating a large deformation cohesive zone model for scratch-induced debonding simulation, where the mass scaling technique is utilized to minimize computational burden while ensuring accuracy. The delamination phenomenon of the automotive coating is reproduced, and its effects on scratch damage behavior are analyzed. Accordingly, it is revealed that the interlaminar delamination would produce significant stress redistribution, which leads to brittle and ductile damage of the coating and consequently affects the formation of plowing. Eventually, parametric studies on the effects of interfacial properties are performed. They demonstrate that the shear strength and shear fracture energy dominate scratch-induced delamination.

Single-Impact Failure of Multi-Layered Automotive Coatings: A Finite Element-Based Study

Automotive coatings are a multi-layered polymer composite structure whose impact resistance is closely related to the appearance and safety of a vehicle. Since experimental methods are of high cost and poor repeatability, in our work, a finite element model is developed for the single-impact failure of automotive coatings. In this model, a multi-mechanism damage model and a large deformation cohesive zone model are employed to account for the polymer-ply and interlaminar failures of the coating, and some rate-dependent material models are adopted to capture the effect of impact velocity. The simulated results indicate that the proposed model can reproduce the failure patterns of automotive coatings well. In addition, the impact failure mechanisms of the coating are revealed. Numerical findings show that both brittle and ductile failures are found in the coating and there are three stages for the propagation of the delamination crack. Finally, we numerically investigate the effects of primer mechanical properties, i.e., Young’s modulus, yield strength, and re-hardening modulus, on the impact resistance of automotive coatings. Our work is helpful to the design of coating, which can improve the impact resistance of automotive coatings.

Cathodic electrodeposition of organic nanocomposite coatings reinforced with cellulose nanocrystals.

A systematic examination of the structure-property relations to create nanocomposite coatings via electrophoretic deposition (EPD) of a cathodic polymer - for instance, polyacrylate - reinforced with cellulose nanocrystals (CNCs) is discussed in this work. EPD, a scalable and green technique, has also been used in our approach to polymerize dopamine in the presence of CNCs and cathodic polymer to improve adhesion properties. This study investigated the interactions between CNCs, polydopamine (PDA) and the cathodic polyacrylic polymer to elucidate the dispersion state of the nanoparticles in the system by carefully examining ζ-potential, particle size, and electrophoretic mobility dependence in the colloidal suspension. We examined the morphology and structure of the electrodeposited nanocomposites using SEM and XPS, and the results indicate the formation of a compact, homogeneous structure. The incorporation of CNCs or PDA introduces different levels of roughness to the surface as revealed by AFM. Our results indicate improved adhesion, as determined by bond strength, using CNCs (>20%) or CNC-PDA (>30%) relative to the cathodic polymer, as well as significant improvement in hardness. The technique and materials used show promise to develop industrial organic coatings with low emissions for applications in automotive coatings and other applications.