Laser-induced chemical solution synthesis has been recently developed as a new generic method to create porous nanostructured materials for complex and miniaturized devices. The material made by this approach is successfully demonstrated for electrochemical catalytic, nanoscale powders, protective coatings, and other applications. One question has therefore been raised: What are the mechanical properties of the porous materials deposited by the laser-induced chemical solution synthesis? This paper has attempted to explore the mechanical properties of such porous nanostructured materials deposited by this new nanomanufacturing method. This process also offers an innovative opportunity to study the strength of a very simple bonding in additive manufacturing. A thin-film of copper nanoparticles is deposited on copper substrates; then, the microstructure of the deposited film is characterized by scanning electron microscope (SEM), and mechanical properties are investigated by a variety of experiments, such as microhardness test, nano-indentation test, bending test, and adhesion test. The mechanical properties of substrates with surface deposition have been shown to have adequate bond strength (>60 g/mm) to allow effective usage in intended applications. Based on the test results, statistical regression and significant tests have also been carried out. A new model for the nano-indentation of the porous coating (film) is proposed. The empirical results have shown that the effect of coating thickness is more prominent on mechanical properties in the case of thick coating deposition.

Introduction

Physical vapor deposition (PVD) and chemical vapor deposition (CVD) are two deposition techniques used to deposit thin-film or coating architectures onto various substrates. PVD is a vaporization coating technique based upon the vaporized form of the desired coating material and deposition of it onto a substrate. It involves only physical processes, such as thermal evaporation and sputtering. PVD coating is commonly used to improve hardness, wear resistance, or oxidation resistance of products in the fields of semiconductors, tool fabrication, and medical applications. CVD is the formation of solid materials through the reaction of precursors or chemicals that contain the required constituent on the substrate surface to produce a desired coating. CVD is widely used in the semiconductor industry, especially for depositing super-thin (atomic level) coating. Both PVD and CVD have been studied and well developed for many years. Dobrzański et al. compared the properties of different coatings on cemented carbide and cermet substrate when the coating deposition was carried out by the PVD method [1]. Mehrotra and Quinto used a specialized method to measure the adhesion, microhardness, and fracture toughness of CVD coating [2]. They also studied the differences in the microstructure and stress state of CVD and PVD coatings [3]. However, both PVD and CVD have their disadvantages. For PVD, the rate of coating is usually slow, and the homogeneity of deposition thickness is difficult to achieve. Moreover, this process is typically operated at a very high temperature (250–450 °C) or vacuum condition, which requires an appropriate cooling system and special attention for operation. For CVD, the manufacturing process is relatively complex, and there are a variety of toxic or corrosive gases [4] emitted from the reaction of precursors and chemicals since the precursor gases must be highly volatile for the sake of reaction with the substrate. This process is also not efficient in time and cost.

Chemical solution deposition (CSD) or sol–gel process, which uses a liquid phase as a transfer media, has become another dominating deposition technique other than PVD and CVD. CSD process and chemical solution deposition of electronic oxide films have been studied by Schwartz et al. [5]. Schneller et al. also introduced the application of CSD of functional oxide thin-films [6]. In this work, we employ a novel technique of deposition: laser-induced chemical solution synthesis, which is similar to CSD but uses laser-induced thermal shock to accelerate the production rate. During this process, a laser beam is focused on the top surface of the substrate and initiates chemical reactions within a small area. This processing method is both cost and time efficient, producing less heat and less toxic gaseous byproducts than the conventional techniques during the material deposition. Such advantages make the laser-induced chemical solution synthesis attractive and environmentally friendly. This innovative process [7,8] is scalable [9], generic [10], and capable of producing a significant improvement in the material performance [11]. It can greatly aid the development of nanostructured materials for a myriad of applications [712]. Knowledge of mechanical properties for nanostructured material provides crucial information in its selection for diverse structural application, and it must meet the required standard to function properly. Thus, it is important to understand whether the nanostructured materials created have the basic strength for supporting the suitable applications intended. In Secs. 2 and 3, we will investigate the mechanical properties of the nanostructured material deposited by the laser-induced chemical solution synthesis, such as hardness, elastic modulus, and fatigue behavior. A new model is presented for the hardness of deposited coating based on the nano-indentation tests, and it shows that the coating thickness plays an influential role.

Materials and Sample Preparation

Materials Selection.

A C110 copper rectangular bar was obtained as a substrate from MSC Industrial Supply Co., Melville, NY. Its thickness was 1.5875 mm, and width was 12.7 mm. The other materials involved in the development of the samples were copper chloride dehydrate (reagent grade), ethylenediaminetetraacetic acid disodium salt dihydrate (EDTA, ACS reagent 99–101%), sodium hydroxide pellet (99%), formaldehyde solution (36.5–38% in H2O), nitric acid (10 mM) obtained from Sigma-Aldrich (St. Louis, MO), and de-ionized water.

Sample Preparation and Processing Method.

The copper substrates were milled to a dog-bone shape (Table 1, Ref. [13]) for uniaxial tensile testing and laser deposition. After milling, all the dog-bone shape samples were annealed in a vacuum chamber at 600 °C for 1 h in order to remove any strain-hardening or residual stress effects and were subsequently polished by sand paper.

Copper nanoparticles were deposited within an aqueous electrolyte solution. Over 0.2 g copper chloride dihydrate, 0.7 g EDTA, 0.3 g sodium hydroxide, and 4.5 ml 36.5% formaldehyde liquid were dissolved in de-ionized water to form a 50 ml aqueous electrolyte solution. Copper chloride dihydrate was used to provide Cu2+ ion. Formaldehyde acted as the reduction agent. EDTA was the complexing agent of Cu2+ ion to prevent the precipitation of copper hydroxide [14]. Before deposition, copper substrates were rinsed with diluted nitric acid (10 mM) and de-ionized water to remove oxide layers.

Laser-assisted electroless deposition of copper nanoparticles was conducted with an ytterbium-pulsed fiber laser with pulse duration 100 ns, pulse repetition rate 50 kHz, and wavelength 1064 nm. The laser light was scanned over the substrate from the top at the speed of 0.5 mm/s to make the deposition. With laser power 5 W and the spot size focused to be 1 mm, copper nanoparticles were successfully deposited on the substrate.

Material Characterization.

After 4 h of laser-assisted electroless deposition, the copper nanoparticles were imaged using a SEM. The nanoparticles were around 50 nm in diameter, and the coating thickness was about 3 μm estimated from the SEM image. And a thickness of 8 μm was achieved after 9 h of deposition.

The samples' number and their morphology of coating are marked as follows: (1) Sample 1 (Fig. 1): rectangular sample with 3 μm coating (40 mm × 12.7 mm); (2) samples 2 and 3: both are dog-bone samples with 3 μm coating; and (3) sample 4 (Fig. 2) and sample 5: both are dog-bone samples with 8 μm coating.

In order to evaluate the Young's modulus of the substrate as a benchmark for subsequent analyses, a uniaxial tensile test was performed on the copper substrate shaped like an ASTM standard [13] dog-bone specimen. The elastic modulus was evaluated to be 105 GPa from the stress–strain curve for the substrate.

Experimental Methods and Results

Microhardness Test.

In order to minimize the penetration depth and effect of substrate, a Leco M-400-H microhardness tester with a Knoop indenter was used. The test specimen was put on a plasticine hold to ensure that its top surface was stable and perpendicular to the axis of the indenter. The pyramidal diamond indenter was indented into the surface of the test specimen under the applied load of 25 gf and a holding time of 10 s. The length of long diagonal of the indentation was measured as 0.1 μm through microscope, and its hardness values were calculated from the indenting force divided by the projected area of resulting indentation. Additional tests were made by spacing the indentations with proper distance so that the adjacent tests did not interfere with each other. In our case, we measured independently ten times and took the average for each specimen.

The Knoop hardness based upon the load, indent area, and geometry of Knoop indenter is calculated from Eq. (1), where P is the applied load in gram, D is the measured length of the long diagonal in micrometers, and HK is the Knoop hardness. To convert Knoop hardness to gigapascals, we multiply the value by 0.009807. The results of microhardness tests are provided in Table 2  
HK=14,229×PD2(kgf/mm2)
(1)

Nano-Indentation Test.

During a nano-indentation test, a prescribed load is applied to an indenter in contact with the specimen surface, while the applied load and penetration are continuously recorded. If the properties and geometry (e.g., area to depth ratio) of the indenter are known, the indentation hardness and modulus can be derived by the Oliver and Pharr method [15]. For a Berkovich indenter, the indentation hardness and modulus are given by Eqs. (2a) and (2b), where P is the applied load, hc is the contact depth of penetration, and dP/dh is the slope of the initial portion of the unloading curve. Since the modulus of the diamond indenter is very high, and Poisson's ratio is always small, the indentation (reduced) modulus is usually considered as the elastic modulus of the test specimen approximately 
H=P24.5hc
(2a)
 
E=12dPdhπ24.5hc2
(2b)

Our nano-indentation experiments were performed under ambient conditions using a TI-950 TriboIndenter (Hyistron, Inc., Eden Prairie, MN) equipped with a three-sided pyramidal Berkovich probe. A fused quartz sample was used for the standard calibration of its tip area function and instrument frame compliance prior to testing. The nano-indentation tests were load-controlled through a partial load function (Fig. 3), and the samples under such a loading condition would typically behave like as shown in Fig. 4, which was obtained for copper substrate as-received. For each test sample, we designed 49 (7 × 7 array) different indent locations, and each point was 15 μm apart. Five hardness and modulus values were obtained from each location using the loading–unloading curve, a total of 245 hardness and 245 modulus values for each sample. By averaging the hardness and modules, the test results are shown in Table 3 and Fig. 5. Since the trends under five different loading conditions are similar, the comparison results for modulus versus depth of different samples under 4000 μN are demonstrated as an example in Fig. 6. The center region is the middle of the coating which was fully deposited with copper nanoparticle, while the transition region is the edge of the coating which was partially deposited.

Bending Test

Analysis of Two-Layer Composite Beam.

For a traditional three-point bending test, the stress and modulus can be easily obtained from the simple beam theory as in Eqs. (3a)(3c), where σ, ε, and E are the flexural stress, strain, and modulus, respectively, 
σ=3PL2h2b
(3a)
 
ε=6hδL2
(3b)
 
E=PL34h3bδ
(3c)
However, for our case, which uses a composite beam, these expressions should be altered a little due to the inhomogeneity. So, the neutral axis from the bottom of the substrate yc is calculated from Eq. (4a) [16], where h1 and h2 are the thickness of the copper substrate and coating, respectively, b is the width of the cross section, and n is the ratio of substrate's modulus to coating's modulus. The second moment of inertia I can be calculated from yc by using the parallel axis theorem as in Eq. (4b) [16]. Finally, the apparent modulus of the composite beam with two layers can be expressed as Eq. (4c), where Iapparent = bh3/12 [16] 
yc=(h12+h2)(n×b×h1)+h22(b×h2)n×b×h1+b×h2=12nh12+2nh1h2+h22nh1+h2
(4a)
 
I=[bh2312+bh2(ych22)2]+[nbh1312+nbh1(h2+h12yc)2]
(4b)
 
Eapparent=EcoatingIIapparent
(4c)

Static Bending Test.

Our bending test was modified from ASTM E290-14 [17] and performed by using the MTS 810 hydraulic testing system. The annealed copper substrate was tested at a specified load rate of 0.1 mm/min until permanent (plastic) deformation occurred. The results reported some variation or noise of the output signal due to the small thickness of sample and applied load. The apparent flexural modulus calculated from the slope of stress versus strain curve was around 40 MPa for the copper substrate. Based on the yield strength of the copper substrate, we designed a similar static bending test for sample 4 that was deposited with a coating of 8 μm copper nanoparticles. The load was applied below the yield strength so that the sample only deformed within the elastic regime, and its apparent modulus obtained from the slope of stress–strain curve was about 34 MPa, which was slightly lower than that of the copper substrate. This might be attributed to the lower modulus of coating compared to the dense substrate. The modulus computed from curve fitting needs more experiments to verify their repeatability in the future because the applied load and thickness of coating are relatively small, which makes the difference between samples inconspicuous.

Fatigue Bending Test.

Our bending fatigue test was performed on sample 4 by using cyclic displacement control (within elastic regime based on static bending test). The test specimen was placed symmetrically on two supports and then loaded by a loading nose midway between the supports. The span length is 30 mm, displacement range is between 0 and 0.1 mm, and frequency is 10 Hz. After 700,000 cyclic loading, the coating surface was observed through SEM (Fig. 7). Later after 1 × 106 cycles, another image was taken again on the same spot (Fig. 8). Comparing Figs. 7(c) and 7(d) with Fig. 8 (circles), respectively, we can see the peeling-off of some nanoparticles.

Qualitative Adhesion Testing for Nanoparticle Coatings.

The qualitative adhesion test was designed based on ASTM B571 [18]: a hardened steel chisel was used to inscribe a rectangular grid on the coating surface of sample 1 with a distance of 3 mm between the lines. When drawing the lines, sufficient force was applied to cut through the coating until the substrate in a single stroke.

After a satisfactory adhesion was exhibited, we placed a cross-hatch testing (CHT) tape (M.E. Taylor Engineering, Inc., Rockville, MD), which possessed an adhesion bond strength of 60 g/mm, onto a clean grid area with firm finger pressure. Shortly afterward, the tape was removed by grabbing one free end and pulling it off quickly. The adhesion would not have been enough if the tape had deposited particles that came from that grid area adhering to it. From the test result, the adhesion strength was adequate as no coating broke away between the scratched lines and no copper particles adhered to the tape.

Porosity Estimation.

First of all, the weight of the pure copper substrate was measured by XP26 Mettler Toledo microbalance (Mettler-Toledo LLC, Columbus, OH), and the value was 14.817055 g. After deposition, the same sample (sample 5) was measured again, and its weight became 14.821675 g. By subtracting the weight of the copper substrate, we could know that the net weight of the deposited coating was about 4.62 mg. While for a fully dense solid part, the weight should be about 15 mg, which could be roughly calculated by multiplying its volume (1.68 mm3) and copper density (8.96 g/cm3). And the relative density was also approximately estimated as 2.75 g/cm3. This estimation of relative density based on volume was very rough, so a more accurate model is needed to measure the porosity, and this is our future work.

Discussion

Hardness Test.

From the results of nanohardness tests, samples with porous nanoparticle coating have different mechanical properties than the copper substrate as-received. Both 3 μm and 8μm coatings (samples 1 and 4) tend to have higher variation for hardness and modulus. On top of that, the values of hardness and modulus seem to be affected by the indent positions. This phenomenon probably results from the surface roughness of tested areas or the nonuniform coating during the deposition process, especially when the detecting indenter is only dozens of nanometers and comparable with nanoparticle size. While for the solid copper substrate, we can observe relatively consistent values with lower variation in Figs. 5(a) and 6(a).

The porosity is spontaneously involved in the results when modulus and hardness are measured. The average modulus and hardness of coated samples are much lower than that of copper substrate as-received as shown in Figs. 9 and 10, which is an evidence of the porosity [19]. And for the transition region with less coating nanoparticles, these values are even smaller compared with the center region. If we look into each indent location and compare five values of hardness or modulus within one single indentation test, it is easy to find out that both modulus and hardness increase slowly as the penetration depth grows for most indent location. This agrees well with the work of Chen et al. [20] about porous material and suggests that local densification of porous material or redistribution of pores and grain boundaries occurs in the deeper regions underneath the indenter tip during nano-indentation. In other words, mechanical properties (modulus and hardness) increase as expected when porosity decreases. The better convergence of modulus at higher applied load also indicates that homogeneity or the density of the local neighborhood in the vicinity of the indenter has increased as the indentation depth has increased. However, there are few indent locations showing a contrary phenomenon. This might be caused by some intrinsic defects, such as vacancy or surface-connected pores.

When comparing the results of samples 1 and 4, we also learn that the nanohardness value for sample 4 is slightly higher. One possible reason for this phenomenon could be as the thickness of coating increases, localized densification (lower porosity) around the indenter becomes more significant after a longer time of deposition. There are other possible factors like grain size, particle distribution, or substrate effect, and this issue could be further explored.

The Knoop hardness of sample 1 is even higher than that of the copper substrate. This could be ascribed to the substrate interfering. For the optimum accuracy of measurement, the thickness of the coating is usually at least ten times the depth of the indention in order to minimize the substrate effect [21]. For our Knoop hardness test on sample 1, the indentation depth is about 1.5 μm, which is almost half of the 3 μm coating. While for Knoop hardness test on sample 4, the indentation depth is about 1.9 μm, which is only 20% of the 8 μm coating. To some extent, the microhardness values of sample 1 are more likely to be influenced by the presence of copper substrate during the indentation process. In addition, the microhardness values are very sensitive to the shape of indenter and applied load. This could also lead to a large error if the test force is small.

Regression Model for Nano-Indentation Test.

Based on Figs. 5 and 6 and Table 3, we can perceive that the hardness and modulus for the solid copper substrate as-received have lower STD. The data points for solid substrate tend to be more concentrated. While for sample 1 (3 μm coating) and sample 4 (8 μm coating), it appears to have data points spreading out over a wider range of values. To analyze this phenomenon, a statistical hypothesis test (F-test) is used here, and prove that the coating thickness is potentially useful for nanohardness prediction.

In this paper, linear models are applied to simulate the relationship between hardness and other factors. Compared with nonlinear regression model, the linear model has its advantages which are straight forward to understand and interpret. The method of logarithmic transformation of variables is used, which makes relationship of nonlinear, while still preserving the linear model.

In Secs. 4.2.14.2.3, we will compare the results of two models: model 1 (Eq. (5)) excludes coating thickness, and model 2 (Eq. (6)) includes the coating thickness, where Yi is the response variable (hardness), β0 is the intercept, β1,β2, and β3, are the slopes for predictors X1 (load), X2 (depth), and X3 (coating thickness), respectively, and εi are independent normally distributed random errors with mean = 0 and variance = σ2. A statistics software sas has been employed, and a simple linear regression model with confidence interval 95% is designed, where hardness is the response variable. The fitted regression equations that minimize the sum of squared residuals are calculated. By comparing the R square, we can know how well the predictor (depth, load, and coating thickness) can explain the response variable (nanohardness) variation by this linear model 
Yi=β0+β1X1+β2X2+εi
(5)
 
Yi=β0+β1X1+β2X2+β3X3+εi
(6)

Since the main goal of the significance test is to analyze whether coating thickness is an essential factor, and the null hypothesis is a setup to assume β3 = 0. In other works, the null hypothesis (H0) is that coating thickness is not a potential predictor. From F-test, we can infer that when p 0.05, there is no evidence to conclude that the explanatory variable can help to model the hardness. On the other hand, the coating thickness is potentially useful for predicting the response in this linear model when p ≤ 0.05.

Regression Analysis for Sample 1 (3 μm Coating).

The fitted regression lines for sample 1, model 1, and model 2 are shown in Eqs. (7) and (8) (see the Nomenclature section). The relationship between hardness, load, and contact depth is close to Eq. (2a), and we get a high R square for both models, which are 0.9978. By comparing the two models, the R square does not increase when adding a new predictor for a sample with coating thickness only 3 μm. The result shows that F-value is 0.19, and p-value is 0.6618, which is larger than 0.05. In other words, there is no need to consider coating thickness for hardness prediction.

Model 1: 
ln(H)=0.996ln(P)1.618ln(hc)+1.118H=P0.996e1.118hc1.618 
(7)
Model 2: 
ln(H)=0.996ln(P)0.033ln(C)1.623ln(hc)+1.407H=P0.996e1.407hc1.623C0.033
(8)

Regression Analysis for Sample 4 (8 μm Coating Center Region).

Based on the output of regression analysis, the fitted lines with least sum of square for models 1 and 2 are shown in Eqs. (9) and (10). Different from sample 1, the R square improves from 0.9936 to 0.9940 when adding coating thickness as explanatory variable. On top of that, the F-test concludes that F-value is 13.28, and p-value is 0.0003 < 0.05, which states that it is not reasonable for null hypothesis that β3 = 0. In other words, for sample 4, the coating thickness is an influential predictor to explain the linear relationship for hardness.

Model 1: 
ln(H)=0.989ln(P)1.616ln(hc)+1.171H=P0.989e1.171hc1.616 
(9)
Model 2: 
ln(H)=0.994ln(P)2.366ln(C)1.718ln(hc)+22.873H=P0.994e22.873hc1.718C2.366
(10)

Conclusion for Regression Analysis.

In conclusion, when the coating thickness becomes thicker, it is essential to take thickness into consideration for nanohardness prediction. The possible reason is that as the thickness increases, the difference of localized density around the indenter becomes more significant, which leads to an influential factor to consider. And a suggested model is presented as Eq. (11) for nanohardness of porous coating. From Table 4, we can find that the coefficient for load and contact depth is similar to Eq. (2a), but a new variable coating thickness (C) is added which may not be neglected for porous material's properties with a thickness of 8 μm

 
H=PaebhccCd
(11)

Conclusion

This paper has proved the feasibility of laser-induced chemical solution deposition of particles on the substrates, which provides a basic strength for various applications. We studied that the mechanical properties of deposited coating consisted of copper nanoparticles on copper substrate. The results have shown that there is a propensity for high scatter and variation in the mechanical response of the nanoparticle coating as observed from the nanohardness tests. The porosity in the localized testing regions and the thickness of the deposited coating have an influence on the mechanical properties of the engineered nanoparticle coating and composite. From the results of nano-indentation test, the difference in elastic modulus between the deposited porous coating and solid copper substrate as-received is about 10–20%. However, in terms of nanohardness, the reduction is distinct compared with the modulus since the hardness of porous coating is only 51% and 67% of that of substrate for 3 μm and 8 μm coatings, respectively. It is also observed that the elastic modulus and hardness of the specimens show a correlation to the indentation depth. As the indentation depth increases, the values of the elastic modulus and hardness increase. This trend can be explained by the fact that the densification of the porous material underneath the indenter increases at higher indentation depth. At small indentation depth (<20%) compared to the deposition thickness, the effect of the substrate material properties is negligible as the coating is predominantly responsible for the mechanical response to the micro-indentation. The fatigue test and adhesion test results have shown that the nanostructured materials deposited by the laser-induced chemical synthesis have good bonding strength with the substrate for the intended applications of high surface to volume ratio. A new analytical model including the coating thickness as a variable is proposed to predict the nanohardness of thus engineered porous nanostructured materials.

Acknowledgment

This project was partially supported by the National Science Foundation (NSF) Award No. CMMI 1562960. The assistance of Professor David Bahr and his student Nannan Tian of the School of Materials Science of the Purdue University in conducting the nano-indentation experiments is appreciated.

Nomenclature

     
  • b =

    specimen width

  •  
  • C =

    coating depth (nm)

  •  
  • L =

    span length

  •  
  • h =

    specimen thickness

  •  
  • H =

    hardness (GPa)

  •  
  • hc =

    contact depth (nm)

  •  
  • P =

    load increment/load (μN)

  •  
  • δ =

    deflection increment

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