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Article

Surface Optimization of Additively Manufactured (AM) Stainless Steel Components Using Combined Chemical and Electrochemical Post-Processing

by
Pablo Edilberto Sanchez Guerrero
1,
Andrew Grizzle
1,
Daniel Fulford III
1,
Juan Estevez Hernandez
1,
Lucas Rice
2 and
Pawan Tyagi
1,*
1
Mechanical Engineering, University of the District of Columbia, Washington, DC 20008, USA
2
Honeywell Federal Manufacturing & Technologies, LLC., Kansas City Nuclear Security Campus, Kansas City, MO 64147, USA
*
Author to whom correspondence should be addressed.
Coatings 2025, 15(10), 1197; https://doi.org/10.3390/coatings15101197 (registering DOI)
Submission received: 19 August 2025 / Revised: 27 September 2025 / Accepted: 30 September 2025 / Published: 11 October 2025
(This article belongs to the Special Issue Recent Advances in Surface Functionalisation, 2nd Edition)

Abstract

The design and production of goods have been completely transformed by additive manufacturing (AM), which makes it possible to create components with intricate and complex geometries that were previously impossible or impractical to produce. However, current technologies continue to produce coarse-surfaced metal components that typically exhibit fatigue properties, resulting in component failure and unfavorable friction coefficients on the printed part. Therefore, to improve the surface quality of the fabricated parts, post-processing of AM-created components is required. With emphasis on electroless nickel plating, ChemPolishing (CP), and ElectroPolishing (EP), this study investigates post-processing methods for stainless steel that is additively manufactured (AM). The rough surfaces created by additive manufacturing (AM) restrict direct use. While ElectroPolishing (EP) achieves high material removal rates but may not be consistent, ChemPolishing (CP) offers uniform smoothening. Nickel plating enhances additive manufacturing (AM) products’ resistance to wear and scratches and corrosion protection. To optimize nickel deposition, medium (6%–9%) and high (10%–13%) phosphorus nickel was tested using the L9 Taguchi design of experiments (DOE). Mechanical properties, including scratch resistance and adhesion, were evaluated using the TABER 5900 reciprocating (Taber Industries, North Tonawanda, NY, USA) abraser apparatus, a 5 N scratch test, and ASTM B-733 thermal shock method. Surface analysis was performed with the KEYENCE VHX-7000 microscope (Keyence Corporation, Itasca, IL, USA), and chemical composition before and after nickel deposition was assessed via the ThermoFisher Phenom XL scanning electron microscope (SEM, Thermo Fisher Scientific, Waltham, MA, USA) Optimal processing conditions, determined using Qualitek-4 software, Version 20.1.0 revealed improvements in both surface finish and mechanical robustness. This comprehensive analysis underscores the potential of nickel-coated additive manufacturing (AM) parts for enhanced performance, offering a pathway to more durable and efficient additive manufacturing (AM) applications.

1. Introduction

The development and production of goods have been transformed by additive manufacturing (AM) [1]. The same variables that impact traditional manufactured mechanical components also affect additive manufacturing (AM) parts, including wear, corrosion, fatigue, stress, and shear [2]. Additive manufacturing (AM) components should, in general, be strong, resilient, and impervious to corrosion. Nevertheless, it could also be challenging and complex to obtain all the required mechanical behavior and characteristics with a single material or method. On the other hand, certain materials are highly susceptible to stress and load even though they can withstand corrosion well. While certain materials are resilient and can tolerate stress without breaking, others deteriorate in corrosive or acidic environments [3,4].
The produced part’s surface is typically the cause of engineering noncompliance [3]. A considerable risk of failure exists in components with low surface quality [5]. Quality of surface finishing is critical in determining the sensitivity of an AM component towards crack generation [6], corrosion [7], fatigue property [8] and ease of integration with other components. Due to poor surface finish an as-produced AM metal component may not be functionally acceptable in biomedical implants and high-demand areas like aeronautics, automobile, and defense technologies. Traditional surface-finishing methods, including machining, extrusion honing, and sandblasting, may be unsuitable for intricate additive manufacturing components with extensive internal surface areas [9]. Recently, solution-based electropolishing has been employed for the surface finishing of additive manufacturing components [9,10,11,12,13,14]. From the beginning of engineering, engineers have made efforts to develop a range of solutions and post-processing techniques to deal with these problems. Chemical and heat treatment, spray coating, electroplating, electrodeposition, and electroless plating are among the frequently employed methods in this context [15,16].
Because of additive manufacturing, which has transformed the design and production process, parts that were previously challenging or impossible to construct may now be produced with remarkable accuracy [17]. However, the surface quality of manufactured parts can still be improved. Accordingly, post-processing of parts produced using additive manufacturing (AM) is therefore essential.
This article examines several surface-finishing methods, both separately and in combination. ElectroPolishing (EP), ChemPolishing (CP), and combining those finishing processes with electroless nickel plating are some of the surface-finishing techniques utilized. This range of surface-finishing techniques will be employed in the study to help identify the ideal physical attributes.
A small layer of material is often removed from a metal part during the electroPolishing (EP) process [18]. Highly concentrated acidic electrolytes and DC electric current in a closed circuit are used in the electroPolishing (EP) process. Electrons go from the anode (sample) to the cathode (electrode) because of the power supply during operation, continuously dissolving the sample in the electrolyte [19]. Electropolishing removes small peaks, flaws, and scratches from the surface to efficiently smooth it. It also performs very effectively in removing impurities and imbedded particles, improving the material’s cleanliness. Moreover, electropolishing greatly increases surface brightness and helps to improve corrosion resistance [20].
Chemical polishing, or ChemPolishing (CP), is a versatile method that may be applied to both metal and non-metal elements. This procedure comprises submerging the part in a chemical bath made especially for the material in question [21]. Microscopic imperfections and asperities are eliminated from the surface through the selective interaction of the chemical solution [22]. ChemPolishing (CP) uses a very acidic solution as an electrolyte when there is no power source. The high-stress concentration and crack nucleation zone are anodized and dissolved by the solution as the sample is submerged in the bath [23]. ChemPolishing (CP) is a highly successful method of removing stains, oxides, and surface impurities because it produces a homogeneous and smooth surface. It is the recommended technique for improving the material’s overall appearance, since it provides a polished and attractive finish, and in certain conditions, ChemPolishing can help increase corrosion resistance [24].
The incorporation of electroless coating offers the potential for supplementary improvements in the post-processing of ChemPolished (CP) and electropolished (EP) additive-manufactured (AM) components, performing an outstanding function in surface modification and engineering applications. Brenner and Riddel were the first to attempt electroless nickel plating [25]. Since then, it has been widely used in many different industries, including the textile, automotive, and aircraft industries [26]. The distinctive features of the technique and the characteristics of (Ni-P) coatings are primarily responsible for the commercial success of electroless nickel-phosphorus (Ni-P) plating. By altering the mixes of nickel and phosphorous, many plating surfaces can be used for various situations and purposes [27]. The effects of this method on ChemPolished and electropolished additive-manufactured (AM) steel components, however, have not been thoroughly explored in the literature. Analogous to ChemPolishing (CP), electroless nickel plating is mostly independent of the additive-manufactured (AM) component geometry, does not require a power source, and may be executed without the need for sophisticated equipment. This widely used, very adaptable, regulated, and effective technique of electroless nickel plating improves surface wear resistance, corrosion protection, and hardness [28].
Three surface-finishing techniques are examined in this study in an effort to raise the quality of surfaces made of stainless steel that are additively produced. The electropolishing (EP) and ChemPolishing (CP) processes are the chemical techniques we use to minimize surface roughness. Furthermore, we describe our method for applying electroless nickel coatings on chemically refined surfaces. The paper details the experimental procedures for electroPolishing (EP), ChemPolishing (CP), and electroless nickel coating, along with an analysis of the chemical composition of the specimens before and after nickel deposition. This analysis is conducted under optimal conditions, using the Phenom XL SEM, providing a thorough understanding of the processes involved.
In the prior study [29], we mainly focused on chem-polished and electropolished surfaces for electroless nickel plating. The prior work did not study the role of the nickel strike factor, which is a general process to enhance the quality of electroless plating for stainless steel-like materials. In this study, we include nickel strike steps as a major factor and systematically study the effect on nickel plating. The prior publication also did not study the actual thickness of the electroless nickel film. In this study, we present an extensive discussion of the thickness of the electroless film and investigate the effect of study parameters, including nickel strike factor, on the film thickness. Our prior work did not include thermal shock research to check the durability of electroless coating. In the present study, we conduct a thermal shock test. Our present study also validated the optimum results for thickness and roughness extracted from the Taguchi Design of Experiment by using Nickel Strike as one of the factors.

2. Materials and Methods

2.1. Sample Material

The stainless steel 316 molybdenum-alloyed austenitic steel was used as the 3D printing sample material. This alloy has a chromium content of 17%–19%, a nickel content of 13%–15%, a molybdenum content of 2%–3%, a carbon content of 6%–8%, a high iron content of 55%–57%, and minor amounts of other elements, such as manganese and silicon, as shown in Figure 1.
Typically, the production process of powdered stainless steel 316 molybdenum-alloyed austenitic steel raw materials for metal 3D printing includes the following crucial phases:
  • Selection of Raw Materials: To guarantee quality, high-purity stainless steel scrap and alloying elements (such as molybdenum) are selected.
  • Melting: An electric arc furnace or an induction furnace is used to melt the chosen materials together. As a result, a uniform liquid alloy is produced.
  • Atomization: Next, the molten steel is broken up into fine particles by introducing it into a high-pressure gas or water stream [30]. This method yields powders with a range of sizes, usually between 10 and 50 μm.
  • Sieve and Classify: To guarantee a consistent particle size distribution, which is essential for reliable printing outcomes, the atomized powder is sieved and categorized.
  • Passivation: By creating a protective oxide layer on the surface, the powder may go through a passivation procedure to improve its resistance to corrosion [31].
  • Packaging: To keep the powder from oxidizing and becoming contaminated, it is lastly packaged in an inert atmosphere before being used in metal 3D printers.
The resulting procedure produces a fine powder possessing superior mechanical and corrosion-resistant properties suitable for additive manufacturing applications [32].

2.2. Sample Fabrication

The samples were created at the Kansas City National Security Campus utilizing the Electro Optical System EOS® M280 laser sintering-based additive manufacturing equipment, manufactured by EOS GmbH (Electro Optical Systems) in Krailling, Germany. Careful analysis of key parameters is necessary to optimize the EOS® M280 3D printing process for stainless steel 316L samples. The layer thickness of 40 microns, the laser power of 400 Watts, and the scanning speed of 7 m/s are all adjusted throughout this fine-tuning procedure. Achieving ideal sintering conditions also requires keeping the temperature of the Powder Building Platform and the Chamber at 40 degrees Celsius. To keep the finished product from oxidizing when printing, a nitrogen gas environment is used, which improves the overall quality. The manufacturing of premium stainless steel is ensured by the meticulous use of these requirements or protocol.

2.3. Sample Preparation

A set of consecutive procedures was used during sample preparation to guarantee that all impurities and contaminants were removed from the test specimens’ surfaces. The Standard Guide for Cleaning Metals Prior to Electroplating Designation: B322-99 [33] was used for sample preparation guidance. Scratches, oils, fingerprints, oxides, and other organic and inorganic components must all be removed from the sample via meticulous cleaning to remove any chemicals or impurities from the component’s surface. The process of preparing the sample is broken down into several sequential parts. Pre-cleaning, the initial stage, is intended to remove a substantial amount of extra oil, particularly grease or buffing chemical residues. Samples were immersed in acetone for three minutes at this point. The paint, glue, permanent marker, grease, oil, and ink were all dissolved by the acetone. Following that, the samples are cleaned with distilled water and allowed to air-dry. The samples are then cleaned for three minutes using 99% isopropyl alcohol in a digital ultrasonic cleaner device (IPA). This technique dissolves any remaining pollutants on the sample. Electro cleaning and intermediate alkaline cleaning are the next steps in the cleaning process. For intermediate alkaline cleaning, a solution bath containing sodium hypochlorite (bleach) is utilized at 180 °F for approximately two minutes. It removes any oil or solvent that might have conditioned or softened during the pre-cleaning procedure. The sample is then dried and cleaned. Electro-cleaning (EC) is the following stage. Direct current (DC) and an alkaline electrolyte are used in this electrochemical cleaning method. The heavy-duty ready-to-use solution from Krohn Industrial Inc (Carlstadt, NJ, USA). was utilized in the tests that were conducted. The bath temperature was maintained at 180 °F with a 10 V bias voltage for a period of one and a half minutes. The electro-cleaning process helps to remove both organic and inorganic contaminants from the steel surface. Throughout this procedure, the titanium anode was positioned within the container. The steel part undergoing cleaning functions as the cathode and is linked to the anode through a power supply, and both the anode and cathode are submerged into the electro-cleaning solution. The sample surface develops an oxide layer as a result of the electro-cleaning process, leading to the need for an additional acid dip in 3M HCL for 40 s to remove the oxide layer and neutralize the sample. The highest possible adherence and effectiveness of the next electroless plating process are secured by this pre-treatment stage. The flowchart in Figure 2 below shows the sample preparation cleaning process.
After the pre-cleaning, intermediate cleaning, electro-cleaning, and acid-dipping processes are completed on a regular basis, the sample becomes ready for the ElectroPolishing and ChemPolishing (CP) processes.

2.4. ElectroPolishing (EP)

The fundamental principle of the electroPolishing (EP) procedure focuses on the utilization of remarkably concentrated acidic electrolytes, which dissolve the sample continually as it is being electropolished. The electrolyte formulation consists of 70% phosphoric acid (H3PO4) and 30% sulfuric acid (H2SO4). The electropolishing procedure requires 30 min to complete, after which an alkaline solution is employed to neutralize the sample. Strong bases like potassium or sodium hydroxide are often present in alkaline cleaning solutions. Conventional alkaline cleaning solutions are composed of ammonia (pH 11) and bleach (pH 12). For the electropolishing procedure, the optimal bath temperature is 75 °C. Once the solution reaches this specified temperature, the sample and the lead electrode are connected to the power source. The positive terminal (anode) is connected to the sample, while the negative terminal (cathode) is linked to the lead electrode. A current density of 70 A/dm2 is utilized throughout the process.

2.5. ChemPolishing (CP)

The essential principle of ChemPolishing (CP) centers on the lack of use of electricity and the employment of extremely concentrated acidic electrolytes, which dissolve the regions where the sample, immersed in the chemical bath, has a substantial stress concentration and fissure nucleation. The chemical composition of the bath or electrolyte is 10%–30% phosphoric acid, 1%–10% hydrochloric acid, 1%–10% nitric acid, and 1%–10% proprietary surfactants, i.e., surface-active agents added to liquids to reduce surface tension. Seventy-five degrees Celsius (75 °C) is the optimal bath temperature, and it is imperative to ensure that this temperature remains consistent throughout the process. Any temperature increase has the potential to start an exothermic reaction that could contaminate the chemical bath and jeopardize its integrity. Agitation is essential also to the ChemPolishing (CP) process, as it facilitates the maintenance of a uniform temperature throughout the chemical bath and ensures that the chemical agents are evenly distributed around the workpiece, promoting uniform chemical reactions on the material’s surface. Maintaining this uniformity is essential in achieving the best polishing results. These studies used a 20 mm magnetic stirrer that was set to agitate at 200 rpm. Following a half-hour dissolving period, the sample was cleaned with distilled water and air-dried using an apparatus.

2.6. Electroless Nickel Plating

Electroless nickel plating is a chemical process that deposits a smooth layer of nickel-phosphorus alloy on a substrate’s surface [34]. Equation (1) represents the chemical reaction for electroless nickel plating, also referred to as autocatalytic nickel deposition or nickel-phosphorus deposition.
2Ni2+ + 8H2PO2 + 2H2O —> 2Ni (s) + 6H2PO3 + 2H+ + 2P (s) + 3H2 (g)
In this method, hypophosphite ions (H2PO2) function as a reducing agent, facilitating the deposition of nickel ions (Ni2+) from solution onto a substrate without requiring an external electric current. This reaction is extensively employed in surface finishing to generate homogeneous nickel-phosphorus coatings on diverse materials. Generally, three types of electroless nickel solutions are commonly used, with phosphorus concentration being a critical factor in the deposition process [35]. In this study, two types of electroless plating solutions were employed: the mid-phosphorus ONE PLATE 1001, containing 6%–9% phosphorus by weight, with a pH of 5.8, operating at 90 °C and with a plating rate of 17 μm per hour; and the high-phosphorus ONE PLATE 2001, containing 10%–13% phosphorus by weight, with a pH of 5.0, operating at 85 °C and with a plating rate of 10 μm per hour. The chemicals were supplied by Plating International Inc. (Franklin Park, IL, USA).
Proper sample cleaning is essential to ensure high-quality deposition and strong adhesion of the nickel layer. Thus, the organic or standard cleaning procedure was applied to ensure the substrate was free from grease, oil, debris, and oxide coatings before the plating process. Cleaning with acetone and isopropyl alcohol effectively removes these impurities, followed by a rinse with distilled water to prepare the sample for activation. Certain metals, such as zinc, stainless steel, and tungsten, require specific pretreatment or activation to enhance adhesion [36]. In this study, the samples were activated using a Woods nickel strike solution and 5V DC for 30 s. After activation, the samples were rinsed with distilled water before plating.
Temperature control is crucial in the electroless nickel plating process. A slight increase above the recommended bath temperature can initiate an exothermic reaction, potentially damaging the samples. A hot plate with a feedback loop was used to precisely maintain the bath temperature. The optimal temperature for the mid-phosphorus solution bath was set at 90 °C, while the high-phosphorus solution bath was maintained at 85 °C. The deposition duration for all samples was fixed at 30 min.

2.7. Taguchi Design of Experiment (TDOE)

A statistical technique called Taguchi Design of Experimentation (TDOE) can optimize a system or process with the least number of experiments necessary. Three phases are involved: design, analysis, and optimization.
Design Stage: Using input variables (control factors) and output responses (quality features), experimental settings are set up. Different combinations of input factor levels are arranged, using an orthogonal array. Analysis Step: After measuring the system’s performance in each experimental scenario, the data is examined to determine which input parameters have the most influence on the output and how much of an impact they have. Phase of optimization: Using the signal-to-noise (S/N) ratio to assess output quality in respect to data variability, the ideal values of input components are found to produce the intended result with the least amount of variability.
This research used the Taguchi Design of Experiment (TDOE) technique, which, as shown in Table 1, offers a predetermined number of feasible experiments with four parameters or factors and three levels. The following were the selected factors: the nickel strike time of the bath exposure, the surface preparation or pre-surface polishing, the orientation or 3D coordinate plane, and the bath’s phosphorous content.
Table 2 shows how the trials and experiment designs were created. As indicated in Table 2, the number of trials is reduced to nine by using the L9 TDOE orthogonal array. The results of TDOE include high-quality trials and efficiency regarding time and resources while offering a thorough comprehension of the relationship between various parameters and their effects.

3. Results and Discussion

Figure 3A shows an image from a KEYENCE Digital Microscope VHX-7000, supplied by KEYENCE Corporation of America, Itasca, IL, USA, of an as-built Additive Manufacturing (AM) sample that was pre-treated with standard cleaning and subsequently post-treated with a medium phosphorus solution. Figure 3B presents an as-built AM sample that underwent standard cleaning followed by electroPolishing and was then post-treated with a medium phosphorus solution. Figure 3C displays an as-built AM sample pre-treated with standard cleaning, followed by ChemPolishing (CP), and finally post-treated with a medium phosphorus solution.
It was determined that all three substrates had consistent Ni deposition from the medium phosphorus nickel solution. Figure 4 illustrates how the electropolishing (EP) technique reduces surface roughness by 63.8%. This technique has the ability to remove a significant amount of material efficiently. According to our roughness measurements, the absolute average in relation to the base length Ra value, or Arithmetic Average Roughness, decreased from 16.81 µm to 6.09 µm. However, compared to the ChemPolishing (CP) approach, the experimental electropolishing process has more dependent variables. These variables include sample type, electrode proximity, current density, and electrolyte concentration. This could lead to non-uniform and uneven surface polishing. ChemPolishing (CP) depends only on a few variables, including concentration and process time, and is easy to conduct experimentally. For half an hour, three samples underwent ChemPolishing (CP). This method produced uniform surface polishing for all samples. However, because of the slow rate of material removal (anodization), the surface was not completely smooth. After 30 min of ChemPolishing (CP), the as-built sample’s absolute average Ra value, which was around 16.81 µm, decreased to 10.72 µm. Figure 4 and Figure 5 also illustrate several key surface roughness parameters, including: Rz (Average Maximum Height), the average of multiple peak-to-valley heights within a given sampling length; RzJIS (Ten-Point Mean Roughness), the average of the five highest peaks and five deepest valleys, based on Japanese Industrial Standards; Rp (Maximum Peak Height), the height of the single highest peak above the mean line; Rv (Maximum Valley Depth), the depth of the single deepest valley below the mean line; Rc (Mean Height of Profile Elements), a measure of the average feature height, which filters out minor irregularities; Rt (Total Profile Height), the total vertical distance from the highest peak to the lowest valley across the entire evaluation length; and Rq (Root-Mean-Square Roughness), the square root of the average of the squared deviations from the mean line. It is more sensitive to significant deviations than (Average Roughness) [37].
Figure 5 shows the preliminary surface-finishing results after nickel deposition. For both the electropolishing (EP) and ChemPolishing (CP) techniques, we can observe an improvement in the absolute average in relation to the base length Ra value from 6.09 µm to 5.99 µm and from 10.72 µm to 8.96 µm, respectively. Nevertheless, there was an increase in the surface finishing as-built from 16.81 µm to 17.30 µm, most likely because of the particular section area that was analyzed.
Table 3 illustrates the experimental nickel deposition layer thickness average (µm) measured from the samples.
On average, the plating rate of the midphosphorus solution was 15 µm per hour. The phosphorus content on the sample surface, as determined by elemental analysis, was 8.5% per deposition. This coating option is an excellent plating choice for achieving a balance between hardness and corrosion resistance. Nevertheless, the as-built sample has a high nickel content per deposition and good adherence.

3.1. Scratch Test Analysis

Applying uniform, well-defined scratches is essential for testing a surface’s resistance to mechanical wear or treatment. Mechanical wear and coatings were analyzed and characterized using the scratch test. The thickness of the coating, the mechanical properties of the substrate, the strength of the interfacial bond, and test parameters like the speed at which the scratch occurs, the load it is subjected to, and the indenter tip’s radius all affect the outcome. The scratch test protocol used is aligned with ASTM G171-03, “Standard Test Method for Scratch Hardness of Materials Using a Diamond Stylus” [38]. The Test Conditions were the following: Instrument: TABER 5900 reciprocating abraser device (Taber Industries, North Tonawanda, NY, USA); Load (normal force): 5 N; Indenter: Conical diamond tip, 3 mil (~0.076 mm) radius, apex angle 90°, Taber model 139-55, Stroke Length (scratch path length): 15 mm; Test Speed: 75 cycles/min; Number of Cycles: 1 Cycles.
Figure 6 exhibits an illustration of a scratch performed on an Additive Manufacturing (AM) stainless steel sample.
A scatter plot of electroless nickel plating before and after nickel deposition is shown in Figure 7. After nickel deposition, it is evident that the scratch depth diminishes. Examined were DOE 1 (A019)—ChemPolished (CP), DOE 6 (A016) As-Built, and DOE 8 (A013)—ElectroPolished (EP). DOE 1 (A019) result values for the scratch depths before and after nickel deposition decreased from 7.53 to 2.13 microns, DOE 6 (A016) from 19.13 to 14.51 microns, and DOE 8 (A013) from 3.56 to 1.36 microns, respectively. These outcomes support the efficacy of electroless nickel plating as an alloy treatment technique projected to improve the hardness and surface resistance to corrosion of Additive Manufacturing (AM) components.

3.2. Taguchi Design of Experiment (TDOE) Analysis, and Optimization

In the Taguchi Desing of Experiment (TDOE) analysis step, after measuring the system’s performance in each experimental scenario, the data was examined statistically to determine which input factors had the most influence on the output responses and how much of an impact they had, and the optimal combination of input factor levels was determined in the optimization stage to achieve the desired output responses with the least variation. This was accomplished by employing a signal-to-noise (S/N) ratio, which is a measure of the quality of output responses in relation to data variability; it combines both the mean and the variability of the results into a single metric, making it easier to compare different factor settings. A higher S/N ratio indicates a more robust design that delivers consistent performance despite the presence of noise or uncontrollable factors. Negative S/N values may occur when the response values are relatively large, because the logarithmic transformation in the S/N formula yields negative numbers whenever the noise term exceeds unity. We use “smaller is better” for surface roughness determination and “bigger is better” for the deposition layer thickness study. Table 4 indicates the Qualitek-4 Ra roughness surface result analysis. It shows that the optimal condition for roughness improvements would be reached at phosphorus level medium-level 1, Nickel Strike 60 s-level 3, Surface Preparation Chem Polishing-level 1, and Orientation YZ-level 2.
The optimal condition will also improve the S/N ratio from −20.733 in the current condition to −11.081 improved condition, and the standard deviation from 10.762 current condition to 3.542 improved condition with a target of 12.279. Figure 8 illustrates the ANOVA analysis of individual factors and interactions among factors for Ra roughness surface, determining that the surface preparation is the most critical factor to take into consideration.
Figure 9 illustrates a multi-plot analysis: (a) nickel striking time; (b) surface preparation; (c) orientation; (d) phosphorus. Multi-plots function as a potent visualization instrument for exhibiting the effects of various factors on a response variable, as depicted in Figure 9. These graphs illustrate both the main effects, indicating the individual influence of each factor, and the interaction effects, reflecting the combined impact of two or more factors on the response variable. Figure 9b illustrates the substantial impact of surface preparation on surface roughness.
Correspondingly, the study of the Qualitek-4 nickel deposition layer thickness results, as illustrated in Table 5, indicates that the optimal condition will be achieved at phosphorus level medium-level 1, Nickel Strike 60 s-level 3, Surface Preparation Electro Polishing-level 2, and Orientation YZ-level 2.
The optimal condition will enhance the S/N ratio from 23 in the present state to 36.38 in the improved state, and the standard deviation will decrease from 15.857 in the current state to 3.397 in the improved state, with a target of 21.746. Figure 10 depicts the ANOVA analysis of individual factors and interaction among factors regarding nickel deposition layer thickness, indicating that orientation is the most significant aspect to consider.
Figure 11 depicts a multi-plot analysis: (a) nickel striking duration; (b) surface treatment; (c) orientation; (d) phosphorus content. Multi-plots serve as an effective visualization tool for demonstrating the influence of multiple factors on a response variable, as illustrated in Figure 11. These graphs display both the main effects, indicating the unique influence of each element, and the interaction effects, representing the cumulative impact of two or more factors on the response variable. Figure 11b reveals the significant effect of surface orientation on the nickel layer deposition thickness.

3.3. Optimization Experimental Results

To evaluate the optimal condition for Qualitek-4 Ra surface roughness and the thickness of the nickel deposition layer, three new additive manufacturing (AM) specimens were utilized. Sample preparation adhered to the Standard Guide for Cleaning Metals Prior to Electroplating (ASTM B322-99, Reapproved 2014), as previously described in Section 2.2 [33]. The KEYENCE Digital Microscope VHX-7000 was utilized to analyze surfaces before and during nickel deposition, while mechanical characteristics were evaluated using a 5 N scratch test and the ASTM B-733 thermal shock adhesion test [39].
Specimen A002 was designed with an as-built surface finish, A018 underwent chemical polishing (CP), and A009 was subjected to electropolishing (EP), representing the post-processing techniques applied to additively constructed stainless-steel samples before electroless nickel deposition. Figure 12 and Figure 13 illustrate the optimal-condition experimental outcomes for Ra surface roughness before and after nickel deposition, respectively.
Table 6 shows the percentage of improvements expected compared to the improvement achieved. It reflects that the optimum condition was negative in −1.18% for the As-Built specimen, since the Ra value reached before nickel deposition was lower than 16.13 µm, compared to the level reached after deposition, i.e., 16.79 µm. On the other hand, the ChemPolished (A018) and the Electropolished (A009) samples had improvements of 4.34% and 5.31%, respectively. In all cases, the expected Ra improvement (9.65%) was higher than the Ra % achieved.
Table 7 exhibits the optimum experimental nickel deposition layer thickness average (µm) results measured from the As-Built (A002), ChemPolishing (A018), and Electropolishing (A009) samples.
Figure 14 illustrates KEYENCE Digital Microscope VHX-7000 (Keyence Corporation, Itasca, IL, USA) images of the experimental layer thickness average (µm) for optimal condition.
Table 8 displays the percentage of improvements expected compared to the improvement achieved. It indicates a slight positive change (~0.04%) under the optimum condition for the As-Built specimen: the measured layer thickness was ~28.5 µm both before (±12 µm) and after (±8 µm) nickel deposition. Similarly, the ChemPolished (A018) and the Electropolished (A009) sample had an improvement of 2.63% and 4.52%, respectively. In every instance, the layer thickness % improvement expected to be 13.38% was higher than the layer thickness % improvement achieved.

3.4. Adhesion Assessment Using the ASTM B-733 Thermal Shock Method

The ASTM B733 [39] thermal shock test is a comprehensive process outlined in the ASTM B733 standard, evaluating the adherence and endurance of electroless nickel-phosphorus coatings subjected to cyclic temperature stressors. The test entails exposing coated samples to fast temperature fluctuations, simulating extreme operating circumstances to assess the coating’s durability. The following are the key details of the test: (a) Temperature specifications: Samples undergo cycling between elevated and reduced temperatures. This often entails submerging the sample in hot water or inserting it into an oven at 88–99 °C (190–210 °F), subsequently followed by immersion in cold water at 15–25 °C (59–77 °F). This range may fluctuate marginally based on certain material specifications. In our study, we used 100 °C (212 °F). (b) Cycle duration: The test typically comprises 10–20 cycles, each cycle consisting of a phase of exposure to a heated environment followed by a quick transition to a cool one. The precise duration of each immersion typically ranges from 1 to 5 min, contingent upon coating thickness and testing specifications. In our investigation, we used 3 min cycles. (c) Evaluation criteria: Following heat cycling, samples undergo visual examination for the presence of cracking, peeling, blistering, or delamination. Adhesion failure is generally signified by observable separation or any compromise of coating integrity. (d) Pass/fail criteria: A coating must exhibit no evidence of adhesion loss or physical degradation, such as blistering or peeling, to pass the thermal shock test. Any observable flaw renders the sample ineligible for ASTM B733’s quality standards. This test is crucial for evaluating the ability of electroless nickel coatings to endure thermal stress without losing adhesion, rendering it an important assessment instrument for quality assurance in coating applications.
The adhesion assessment ASTM B-733 thermal shock method employed in this study indicated that the electroless nickel plating procedure attained superior adherence, as the coating was evaluated for blistering or other signs of inadequate adhesion, revealing no such evidence. Figure 15 shows representative images for the three categories of surface preparation.
Consequently, electroless nickel deposition offers enhanced plating potential on additively made stainless steel samples. Nickels have exceptional wear resistance. The electroless nickel solution with elevated phosphorus concentration offers enhanced corrosion resistance. It was found that the geometry of the printed component significantly influences the surface-finishing procedure.

3.5. Chemical Composition Before and After Nickel Deposition for Specimens Under Optimal Conditions, Utilizing Thermo Fisher Scientific, Phenom XL, High-Performance Scanning Electron Microscope (SEM)

The Thermo Fisher Scientific Phenom XL scanning electron microscope (SEM), manufactured in Eindhoven, Netherlands, parameters FOV: 52.6 µm; Mode: 15 kV-Map; and Detector: BSD Full were used for image acquisition and analysis. The Field of View (FOV) of a SEM picture is 52.6 µm, which represents the viewable region. A narrower FOV zooms in on the sample. Mode: 15 kV-Map: “Mode” is the electron beam accelerating voltage. A 15-kilovolt (kV) voltage was used to penetrate the sample surface and provide precise surface information. “Map” means this option created a compositional or topographical sample map. BSD detector Full: Backscattered Electron Detector (“BSD”): This detector detects backscattered electrons from the sample, revealing compositional differences (heavier components are brighter). “Full” may mean the detector was utilized to optimize picture detail and contrast. These settings are optimal for high-contrast composition and surface topography studies of tiny structures. The present investigation contains six images with a total of 37 analyses. (1) Thickness Electropolishing_A009—Center-6 analyses: 1× region, 5× spot; (2) Thickness Electropolishing A009—Edge-6 analyses: 1× region, 5× spot; (3) Roughness ChemPolishing A018 Center-6 analyses: 1× region, 5× spot; (4) Roughness ChemPolishing A018 Edge-6 analyses: 1× region, 5× spot; (5) As-Built A002 Center-6 analyses: 1× region, 5× spot; (6) As-Built A002 Edge-7 analyses: 1× region, 6× spot.
The principal findings include:
  • Thickness Electropolishing (A009):
Center: The central composition is predominantly iron (Fe), with weight percentages ranging from 65 to 67% across various regions and locations, succeeded by chromium (Cr) at 16%–18% and nickel (Ni) at 11%–12%. Silicon (Si), molybdenum (Mo), and manganese (Mn) are found in lesser quantities. Figure 16 shows center image capture using the Phenom SEM and Table 9 displays the center chemical composition.
The edge exhibits a similar composition to the middle, comprising 67% iron, followed by chromium and nickel. Trace quantities of erbium (Er) are present in a certain location. Figure 17 exhibits edge image capture using the Phenom SEM, and Table 10 reveals the edge chemical composition.
2.
Roughness ChemPolishing (A018):
Center: The primary element is iron, comprising around 66%, accompanied by a marginal rise in nickel (11%–12%) and modest yttrium (Y) additions in a specific location. Figure 18 shows center image capture using the Phenom SEM, and Table 11 displays the center chemical composition.
Edge: Exhibits variations in iron content (47%–67%) and a significant presence of carbon (C), particularly in certain areas (up to 29%). Figure 19 illustrates edge image capture using the Phenom SEM, and Table 12 displays the edge chemical composition.
3.
As-Built (A002):
Center: Approximately 60% iron, with a localized rise in oxygen (O) concentration reaching 19%. Nickel, chromium, and manganese are secondary elements (%). Figure 20 displays center image capture using the Phenom SEM, and Table 13 shows the center chemical composition.
Edge: Concentrations are comparable to the center; however, one analysis indicates elevated amounts of promethium (Pm), at 19%. Figure 21 displays edge image capture using the Phenom SEM, and Table 14 shows the edge chemical composition.
The analysis revealed how each process impacts the surface roughness, hardness, and resistance to oxidation, by comparing the elemental composition of each sample type.
  • Chemical composition and roughness improvement:
Electropolished Samples: These samples have high concentrations of iron (Fe), chromium (Cr), and nickel (Ni). For example, in the “Electropolishing A009” samples, iron concentration is typically around 66%, chromium around 16%–18%, and nickel around 10%–11%. The consistent high levels of chromium and nickel in these samples suggest that the electropolishing process not only smoothens the surface but also exposes a protective chromium oxide layer that can enhance roughness resistance.
Chemically Polished Samples: Similar to the electropolished samples in elemental composition, but they show slightly lower levels of iron (Fe) and higher levels of carbon (C) and oxygen (O), potentially from organic residues left by the chemical polishing agents. These elements may slightly impair surface smoothness but do enhance roughness.
As-Built Samples: These show much higher variability in elemental concentration, with spots indicating higher oxygen content, suggesting oxidation on the untreated surface. The unmodified surface has significantly higher roughness and less resistance to oxidation.
2.
Impact on hardness and durability:
Nickel and Chromium: Both elements are correlated with hardness and wear resistance. The high nickel concentration in electropolished and chemically polished samples suggests that these processes improve surface hardness.
Molybdenum: Present in low but consistent concentrations in all treated samples, molybdenum contributes to hardness and oxidation resistance. The treated samples, especially those that were electropolished, show slightly higher molybdenum levels, enhancing their hardness over the as-built samples.
As-Built Samples: Show a lower chromium and nickel concentration, which could lead to lower hardness and a more oxidation-prone surface due to the inconsistent presence of protective elements.
3.
Resistance to oxidation:
Electropolished Samples: With their high chromium and nickel content, these samples are more resistant to oxidation, as evidenced by the lower oxygen content compared to as-built samples.
Chemically Polished Samples: Although showing improved oxidation resistance due to chromium, they also exhibit a slightly higher oxygen content, suggesting minimal surface oxidation post-treatment.
As-Built Samples: The significantly higher oxygen concentration implies that the as-built samples are less resistant to oxidation and may develop surface corrosion more quickly without protective finishing.

4. Conclusions

The electrolytic nickel-plating process, when combined with prior electropolishing or chemical polishing, enhances the sample’s roughness, hardness, and oxidation resistance compared to as-built samples. Electropolishing yields the most stable composition, with minimal oxidation and smoother surfaces, followed closely by chemical polishing, which still improves roughness but leaves minor organic residues. As-built samples, with higher oxygen levels and surface variability, show the least improvement in these areas. Among the advanced manufacturing (AM) stainless steel parts, individually, each technique has distinct benefits. In combination, they offer synergistic improvements in surface finish, corrosion and wear resistance, mechanical durability, and esthetic and functional quality. The optimal sequence, ChemPolishing (CP) → ElectroPolishing (EP) → Electroless Nickel Plating (ENP), maximizes performance for critical applications in biomedical, aerospace, tooling, and energy sectors.
The results of the study of Qualitek-4 nickel deposition layer thickness indicate that the predictive equation for performance under optimal and alternative conditions will be attained with a nickel strike duration of 60 s, surface preparation via electro polishing, orientation in the YZ plane, and a mid-level P setting. The primary variables and interactions that influenced the outcomes were direction, followed by P level, surface preparation, and nickel strike duration.
The average plating rate of the mid-phosphorus solution is 15 µm per hour. The elemental analysis of the sample surface indicates a phosphorus concentration of 8.5% per deposition. This is an exemplary plating option for achieving a balance between corrosion resistance and hardness.
The adhesion test ASTM B-733 thermal shock method employed in this study indicates that the electroless nickel plating procedure attained superior adhesion of the layer, as the coating was assessed for blistering or other signs of inadequate adhesion, revealing no such evidence.
Consequently, electroless nickel deposition offers enhanced plating potential on additively made stainless steel samples. Nickel exhibits significant wear resistance. The electroless nickel solution with an elevated phosphorus concentration enhances corrosion resistance. The shape of the printed component significantly influences the surface-finishing procedure.

Author Contributions

Conceptualization, P.T.; methodology, P.E.S.G. and L.R.; resources, P.T.; formal analysis, L.R.; investigation, P.E.S.G., A.G. and D.F.III; writing—original draft, P.E.S.G. and J.E.H.; writing—review and editing, P.E.S.G.; supervision, P.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Science Foundation-CREST Award, grant number HRD-1914751, Department of Energy/National Nuclear Security Agency (DE-FOA-0003945), and The NASA MUREP Institutional Research Opportunity Grant under Cooperative Agreement #80NSSC19M0196. This manuscript has been authored by Honeywell Federal Manufacturing & Technologies, LLC. under Contract No. DE-NA-0002839 with the U.S. Department of Energy/National Nuclear Security Administration. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

This article is a revised and expanded version of a paper accepted for presentation at the ASME 2025 International Mechanical Engineering Congress and Exposition (IMECE2025) [40]. It extends the previous work by providing an expanded discussion, additional experimental data, and analysis. The authors also thank colleagues and collaborators for their valuable discussions and technical support throughout this research.

Conflicts of Interest

Author Lucas Rice was employed by the company Honeywell Federal Manufacturing & Technologies, LLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Sample stainless steel 316 molybdenum.
Figure 1. Sample stainless steel 316 molybdenum.
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Figure 2. Sample preparation flow chart.
Figure 2. Sample preparation flow chart.
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Figure 3. (A) The left side is a 3D view, and the right side is a top 2D view of scratching on an as-built AM sample after the standard cleaning. The depth of the scratch along the crosse section, marked between the orange point that acts as the primary reference and the green point used to determine the vertical distance or differential between two points, is 19.13 µm. The blue line shows the start and end of the measurement and the red dots are two specific points. (B) The left side is a 3D view, and the right side is a top 2D view of scratching on an electropolished AM sample after the standard cleaning. The depth of the scratch along the crosse section marked between the orange and green points is 3.56 µm. The blue line shows the start and end of the measurement and the red dots are the middle and the end points. (C) The left side is a 3D view, and the right side is a top 2D view of scratching on a ChemPolished AM sample after the standard cleaning. The depth of the scratch along the crosse section marked between the orange and green points is 7.53 µm. The Purple Points facilitate more advanced analyses, like measuring angles, distances between features, and the height of multiple elements simultaneously. These reference points, usable in both 2D and 3D views, offer a robust method for the detailed surface analysis essential for quality control and research in additive manufacturing.
Figure 3. (A) The left side is a 3D view, and the right side is a top 2D view of scratching on an as-built AM sample after the standard cleaning. The depth of the scratch along the crosse section, marked between the orange point that acts as the primary reference and the green point used to determine the vertical distance or differential between two points, is 19.13 µm. The blue line shows the start and end of the measurement and the red dots are two specific points. (B) The left side is a 3D view, and the right side is a top 2D view of scratching on an electropolished AM sample after the standard cleaning. The depth of the scratch along the crosse section marked between the orange and green points is 3.56 µm. The blue line shows the start and end of the measurement and the red dots are the middle and the end points. (C) The left side is a 3D view, and the right side is a top 2D view of scratching on a ChemPolished AM sample after the standard cleaning. The depth of the scratch along the crosse section marked between the orange and green points is 7.53 µm. The Purple Points facilitate more advanced analyses, like measuring angles, distances between features, and the height of multiple elements simultaneously. These reference points, usable in both 2D and 3D views, offer a robust method for the detailed surface analysis essential for quality control and research in additive manufacturing.
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Figure 4. Bar diagram of the Roughness measurement of DOE 6 (A016)—As-Built, DOE 1 (A019)—ChemPolishing (CP), and DOE 8 (A013)—ElectroPolishing (EP) samples before nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
Figure 4. Bar diagram of the Roughness measurement of DOE 6 (A016)—As-Built, DOE 1 (A019)—ChemPolishing (CP), and DOE 8 (A013)—ElectroPolishing (EP) samples before nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
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Figure 5. Bar diagram of the Roughness measurement of DOE 6 (A016)—As-Built, DOE 1 (A019)—ChemPolishing (CP), and DOE 8 (A013)—Electropolishing (EP) samples after nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
Figure 5. Bar diagram of the Roughness measurement of DOE 6 (A016)—As-Built, DOE 1 (A019)—ChemPolishing (CP), and DOE 8 (A013)—Electropolishing (EP) samples after nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
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Figure 6. Illustration of a scratch test performed on an Additive Manufacturing (AM) stainless steel sample. The bold and thin pink lines represent depth measurements.
Figure 6. Illustration of a scratch test performed on an Additive Manufacturing (AM) stainless steel sample. The bold and thin pink lines represent depth measurements.
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Figure 7. Scratch test results before and after nickel deposition performed on Additive-Manufactured (AM) samples. The red lines indicate the standard deviation (σ) associated with the experimental data set.
Figure 7. Scratch test results before and after nickel deposition performed on Additive-Manufactured (AM) samples. The red lines indicate the standard deviation (σ) associated with the experimental data set.
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Figure 8. Bar diagram showing (a) the ANOVA analysis of individual factors; (b) interaction among factors.
Figure 8. Bar diagram showing (a) the ANOVA analysis of individual factors; (b) interaction among factors.
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Figure 9. Taguchi multi-plot analysis for surface roughness study: (a) nickel strike time; (b) surface preparation; (c) orientation; (d) phosphorus.
Figure 9. Taguchi multi-plot analysis for surface roughness study: (a) nickel strike time; (b) surface preparation; (c) orientation; (d) phosphorus.
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Figure 10. Bar diagram showing the ANOVA analysis of individual factors and interaction among factors thickness.
Figure 10. Bar diagram showing the ANOVA analysis of individual factors and interaction among factors thickness.
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Figure 11. Taguchi multi-plot analysis for layer deposition thickness: (a) nickel strike time; (b) surface preparation; (c) orientation; (d) phosphorus.
Figure 11. Taguchi multi-plot analysis for layer deposition thickness: (a) nickel strike time; (b) surface preparation; (c) orientation; (d) phosphorus.
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Figure 12. Bar diagram of the roughness measurement in the optimum experiment of the As-Built (A002), ChemPolishing (A018), and Electropolishing (A009) samples before nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
Figure 12. Bar diagram of the roughness measurement in the optimum experiment of the As-Built (A002), ChemPolishing (A018), and Electropolishing (A009) samples before nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
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Figure 13. Bar diagram of the roughness measurement in the optimum experiment of the As-Built (A002), ChemPolishing (A018), and Electropolishing (A009) samples after nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
Figure 13. Bar diagram of the roughness measurement in the optimum experiment of the As-Built (A002), ChemPolishing (A018), and Electropolishing (A009) samples after nickel deposition. The red lines indicate the standard deviation (σ) associated with the experimental data set.
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Figure 14. KEYENCE Digital Microscope VHX-7000 images of the experimental layer thickness average (µm) for the optimal condition. Image (A)—As-Built − A002 − Ave. = 28.52 ± 7.66 µm, image (B)—ChemPolishing (CP) − A018 − Ave. = 43.45 ± 9.34 µm, and image (C)—ElectroPolishing (EP) − A009 − Ave. = 50.87 ± 11.58 µm.
Figure 14. KEYENCE Digital Microscope VHX-7000 images of the experimental layer thickness average (µm) for the optimal condition. Image (A)—As-Built − A002 − Ave. = 28.52 ± 7.66 µm, image (B)—ChemPolishing (CP) − A018 − Ave. = 43.45 ± 9.34 µm, and image (C)—ElectroPolishing (EP) − A009 − Ave. = 50.87 ± 11.58 µm.
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Figure 15. Representative images for the three categories of surface preparation.
Figure 15. Representative images for the three categories of surface preparation.
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Figure 16. Phenom SEM Center image capture.
Figure 16. Phenom SEM Center image capture.
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Figure 17. Phenom SEM Edge image capture.
Figure 17. Phenom SEM Edge image capture.
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Figure 18. Phenom SEM Center image capture.
Figure 18. Phenom SEM Center image capture.
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Figure 19. Phenom SEM Edge image capture.
Figure 19. Phenom SEM Edge image capture.
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Figure 20. Phenom SEM Center image capture.
Figure 20. Phenom SEM Center image capture.
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Figure 21. Phenom SEM Edge image capture.
Figure 21. Phenom SEM Edge image capture.
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Table 1. TDOE with levels 1, 2, 3 for various impact factors.
Table 1. TDOE with levels 1, 2, 3 for various impact factors.
FactorsLevel 1Level 2Level 3
Nickel Strike Time304560
Surface PreparationChem-PoElectro-PoAs produced
OrientationXYYZXZ
P LevelMidHighN/A
Table 2. Design of experiments and trial conditions.
Table 2. Design of experiments and trial conditions.
DOEFactorsLevelsLevels #
1Nickel Strike Time301
Surface PreparationChem-Polishing1
OrientationXY1
P Level (Nickel Solution)Mid1
2Nickel Strike Time301
Surface PreparationElec-Polishing2
OrientationYZ2
P Level (Nickel Solution)High2
3Nickel Strike Time301
Surface PreparationAs-Built3
OrientationXZ3
P Level (Nickel Solution)Mid1
4Nickel Strike Time452
Surface PreparationChem-Polishing1
OrientationYZ2
P Level (Nickel Solution)Mid1
5Nickel Strike Time452
Surface PreparationElec-Polishing2
OrientationXZ3
P Level (Nickel Solution)Mid1
6Nickel Strike Time452
Surface PreparationAs-Built3
OrientationXY1
P Level (Nickel Solution)High2
7Nickel Strike Time603
Surface PreparationChem-Polishing1
OrientationXZ3
P Level (Nickel Solution)High2
8Nickel Strike Time603
Surface PreparationElec-Polishing2
OrientationXY1
P Level (Nickel Solution)Mid1
9Nickel Strike Time603
Surface PreparationAs-Built3
OrientationYZ2
P Level (Nickel Solution)Mid1
Table 3. Layer Thickness Average (µm).
Table 3. Layer Thickness Average (µm).
DOE 6 (A016) As-BuiltDOE 1 (A019) ChemPolishedDOE 8 (A013) Electropolished
28.49 ± 12.4440.82 ± 4.5346.35 ± 9.32
Table 4. Ra roughness surface optimum conditions result analysis.
Table 4. Ra roughness surface optimum conditions result analysis.
FactorLevelLevel #Contribution
Nickel Strike Time6032.237
Surface PreparationChem13.954
OrientationYZ21.956
P LevelMid11.503
Table 5. Ra thickness optimum conditions result analysis.
Table 5. Ra thickness optimum conditions result analysis.
FactorLevelLevel #Contribution
Nickel Strike Time6030.778
Surface PreparationElectro22.770
OrientationYZ24.808
P LevelMid15.022
Table 6. Ra % Improvement Expected vs. % Improvement Achieved.
Table 6. Ra % Improvement Expected vs. % Improvement Achieved.
StatusParameterAs-Built
(A002)
ChemPolished (A018)ElectroPolished (A009)
% Improvement expectedRa9.659.659.65
% Improvement reachedRa−1.184.345.31
Table 7. Layer Thickness Average (µm) Optimal Condition.
Table 7. Layer Thickness Average (µm) Optimal Condition.
As-Built (A002)ChemPolished (A018)Electropolished (A009)
28.53 ± 7.5343.45 ± 9.34 50.87 ± 11.58
Table 8. Layer Thickness % Improvement Expected vs. % Improvement Achieved.
Table 8. Layer Thickness % Improvement Expected vs. % Improvement Achieved.
StatusParameterStandard CleaningChemPolishedElectroPolished
% Improvement Expected Thickness13.3813.3813.38
% Improvement Reached Thickness0.042.634.52
Table 9. Center Chemical Composition.
Table 9. Center Chemical Composition.
Element
Number
Element
Symbol
Element
Name
Atomic
Conc.
Weight
Conc.
26FeIron65.866.1
24CrChromium17.916.7
28NiNickel10.911.5
14SiSilicon2.21.1
42MoMolybdenum1.93.3
25MnManganese1.31.3
Table 10. Edge Chemical Composition.
Table 10. Edge Chemical Composition.
Element
Number
Element
Symbol
Element
Name
Atomic
Conc.
Weight
Conc.
26FeIron66.966.9
24CrChromium18.016.8
28NiNickel10.811.4
42MoMolybdenum1.83.1
25MnManganese1.31.2
14SiSilicon1.20.6
Table 11. Center Chemical Composition.
Table 11. Center Chemical Composition.
Element
Number
Element
Symbol
Element
Name
Atomic
Conc.
Weight
Conc.
26FeIron65.865.9
24CrChromium17.816.6
28NiNickel11.412.0
42MoMolybdenum2.03.5
14SiSilicon1.60.8
25MnManganese1.31.3
Table 12. Edge Chemical Composition.
Table 12. Edge Chemical Composition.
Element
Number
Element
Symbol
Element
Name
Atomic
Conc.
Weight
Conc.
26FeIron67.467.3
24CrChromium18.016.6
28NiNickel11.111.6
42MoMolybdenum2.13.6
14SiSilicon1.40.7
Table 13. Center Chemical Composition.
Table 13. Center Chemical Composition.
Element
Number
Element
Symbol
Element
Name
Atomic
Conc.
Weight
Conc.
26FeIron50.760.1
8OOxygen19.96.8
24CrChromium14.415.9
28NiNickel8.310.3
14SiSilicon3.82.2
25MnManganese1.61.8
42MoMolybdenum1.53.0
Table 14. Edge Chemical Composition.
Table 14. Edge Chemical Composition.
Element
Number
Element
Symbol
Element
Name
Atomic
Conc.
Weight
Conc.
26FeIron54.662.9
8OOxygen16.25.3
24CrChromium15.316.4
28NiNickel7.89.4
14SiSilicon3.62.1
25MnManganese1.41.6
42MoMolybdenum1.22.4
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MDPI and ACS Style

Sanchez Guerrero, P.E.; Grizzle, A.; Fulford, D., III; Hernandez, J.E.; Rice, L.; Tyagi, P. Surface Optimization of Additively Manufactured (AM) Stainless Steel Components Using Combined Chemical and Electrochemical Post-Processing. Coatings 2025, 15, 1197. https://doi.org/10.3390/coatings15101197

AMA Style

Sanchez Guerrero PE, Grizzle A, Fulford D III, Hernandez JE, Rice L, Tyagi P. Surface Optimization of Additively Manufactured (AM) Stainless Steel Components Using Combined Chemical and Electrochemical Post-Processing. Coatings. 2025; 15(10):1197. https://doi.org/10.3390/coatings15101197

Chicago/Turabian Style

Sanchez Guerrero, Pablo Edilberto, Andrew Grizzle, Daniel Fulford, III, Juan Estevez Hernandez, Lucas Rice, and Pawan Tyagi. 2025. "Surface Optimization of Additively Manufactured (AM) Stainless Steel Components Using Combined Chemical and Electrochemical Post-Processing" Coatings 15, no. 10: 1197. https://doi.org/10.3390/coatings15101197

APA Style

Sanchez Guerrero, P. E., Grizzle, A., Fulford, D., III, Hernandez, J. E., Rice, L., & Tyagi, P. (2025). Surface Optimization of Additively Manufactured (AM) Stainless Steel Components Using Combined Chemical and Electrochemical Post-Processing. Coatings, 15(10), 1197. https://doi.org/10.3390/coatings15101197

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