Ensuring that automotive components meet the highest quality standards is critical to vehicle safety and performance. Metals and protective coatings used in automotive manufacturing must withstand extreme conditions such as mechanical stresses, corrosion, and wear during a vehicle’s lifespan. Here, Prerna Sudera at Thermo Fisher Scientific explores how scanning electron microscopy techniques can elevate defect detection and analysis during quality assurance to improve the strength, safety, and longevity of vehicles.

Metals such as aluminum and steel are widely used in the automotive industry due to their strength and durability. Aluminum is lightweight, which helps improve fuel efficiency and reduce emissions, making it a popular choice for body panels and engine components. Steel, on the other hand, provides essential structural support for safety features such as the frame and chassis, thanks to its strength and stiffness.

However, steel’s vulnerability to corrosion is a significant concern. Rust, which forms when steel is exposed to moisture and oxygen, can compromise the material’s mechanical structure, weakening components and potentially contributing to early structural failure. To combat this, protective coatings are applied to steel to preserve both vehicle appearance and structural performance over time.

To ensure that both metals and coatings meet safety and performance standards, rigorous quality checks are essential. A scanning electron microscope (SEM) often plays a pivotal role in this process by enabling the detection of the smallest defects at micro/nano scales. This helps to identify issues such as surface defects, material weaknesses, and coating adhesion inconsistencies early in the manufacturing process, ensuring that both metals and coatings perform optimally throughout the vehicle’s life.

Detecting impurities in aluminum alloys

In aluminum alloys, impurities such as iron can form intermetallic particles that could lead to microcracking and fracturing, ultimately compromising material strength. However, the size and distribution of intermetallic particles significantly influence their effect on the alloy’s performance. In some cases, smaller and more evenly distributed intermetallic particles may help mitigate cracking risks, because they can strengthen the alloy without causing excessive brittleness. This is why controlling the size, distribution, and composition of these intermetallic particles is critical.

To achieve this level of control, advanced analytical techniques like automated SEM imaging are essential. The Phenom ParticleX Steel, a desktop SEM from Thermo Fisher Scientific, for example, offers a reliable and efficient method for quantifying intermetallic particles. By scanning defined areas of the sample and using backscattered electron (BSE) imaging, the system identifies particles with compositional differences from the base aluminum matrix based on image contrast. Subsequent energy-dispersive X-ray spectroscopy (EDS) analysis of each detected intermetallic particle enables precise detection, classification, and measurement of these particles.

A case study on two batches of 6xxx-series aluminum alloys highlights how automated SEM can enhance quality assurance. In this study, the baseline batch underwent standard thermomechanical processing, while the trial batch was subjected to the same processing with nickel microalloying. 

Results showed that nickel microalloying influenced the size, number, and distribution of intermetallic particles in the alloy. The trial sample exhibited a 17% increase in intermetallic particles larger than 1 µm, while the average particle size decreased from 3.15 µm in the baseline to 2.56 µm in the trial sample. The shift toward smaller particles suggests that nickel influences the formation process of iron-rich intermetallic particles, leading to a finer distribution that could help reduce the risk of microcracking and improve the alloy’s fracture resistance.

Automated SEM imaging and EDS analysis provided precise quantification of these changes in intermetallic particles by efficiently covering large surface areas and quickly providing statistically relevant data. This eliminated the inconsistencies and time constraints associated with labor-intensive manual microscopy, allowing for a more thorough and accurate analysis.

Ensuring effective coating adhesion

Like the metals themselves, protective coatings must also undergo quality analysis. Metallic coatings are often used to enhance the corrosion resistance of steel by forming a bonded zinc layer through hot-dip galvanization or electrogalvanization. However, for these coatings to be effective they must adhere properly to the steel surface. Surface imperfections, contaminants, or process-related residues can interfere with adhesion, leading to defects such as flaking, peeling, or premature wear.

This was the case in another study by Thermo Fisher Scientific, where researchers investigated the root cause of a coating defect affecting adhesion to steel used for a car door. To determine the factors behind the adhesion failure, Axia ChemiSEM, a tungsten filament-based SEM with integrated EDS technology from Thermo Fisher Scientific, was used to analyze both the coating and the underlying steel surface. Integrating EDS to SEM provided much faster and more reliable detection.

SEM imaging provided a detailed view of the coating’s structure, revealing areas where adhesion had failed. Integrated EDS analysis detected an unexpected foreign particle at the defect site. Further elemental mapping showed that the particle contained calcium, silicon, and fluorine, matching the composition of mold powder residue, a byproduct of the steel manufacturing process.

Mold powder is used in continuous casting to prevent oxidation, control heat transfer, and lubricate the mold. However, if residual mold powder isn’t properly removed before coating application, it can create surface inhomogeneities that prevent the zinc layer from bonding effectively to the steel. This results in weak adhesion, which can cause the coating to flake and eventually detach.

The presence of mold powder also meant that liquid mold powder droplets could be present in the steel. To confirm this, a cross-sectional analysis of the steel was conducted using the Axia ChemiSEM. This revealed the presence of subsurface inclusions, likely formed by entrapped liquid mold powder droplets. These inclusions can not only disrupt the surface smoothness required for effective coating adhesion but also introduce localized weaknesses that could contribute to long-term coating degradation.

By providing both surface and cross-sectional analysis in a single workflow using special sample holders, the Axia ChemiSEM enabled a rapid and comprehensive failure analysis, identifying the root cause of the defect. Unlike traditional SEM and EDS workflows, which require switching between imaging and compositional analysis software, the Axia ChemiSEM’s real-time elemental mapping allowed for immediate detection and interpretation of the foreign particles, significantly reducing analysis time and improving diagnostic accuracy.

The automotive industry demands the highest standards of material integrity and durability, making thorough quality assurance crucial. By detecting and analyzing microscopic defects efficiently, advanced SEM systems enable manufacturers to address potential issues early, ultimately driving improvements in the strength, reliability, and performance of automotive metals and protective coatings. As the industry embraces more advanced materials and manufacturing processes, scanning electron microscopy will continue to play a vital role in enhancing the safety of vehicles on roads.

BSE images illustrating bright, iron-rich intermetallic particles dispersed throughout the aluminum matrix in the trial (A) and baseline (B) samples of the 6xxx-series aluminum alloys.

Particle-size histogram for the trial sample of the 6xxx-series aluminum alloys.

ChemiSEM images of the foreign particle at the defect site of the steel used for a car door. Top left image: ChemiSEM map of calcium; top right image: ChemiSEM map of silicon; bottom left image: ChemiSEM map of the defect surface; and bottom right image: ChemiSEM map of fluorine.

Cross-section of the steel used for a car door, revealing the coatings and subsurface inclusions. (Acceleration voltage 15 keV, beam current 0.44 nA).