Characterization and Modelling of Nanomaterials Synthesized by Chemical Vapor Deposition

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Introduction
Nanomaterials, with their unique properties stemming from their reduced dimensions, have been at the forefront of material science research over the past few decades [1].Their ability to exhibit quantum effects, high surface-to-volume ratios, and tailored electronic, optical, and mechanical properties have rendered them indispensable in a plethora of applications ranging from electronics and photonics to biomedicine and energy storage [2].As the demand for highperformance materials with specific functionalities grows, so does the need for advanced synthesis techniques that can produce nanomaterials with precision, scalability, and reproducibility [3].CVD has emerged as one such technique, offering a promising route for the synthesis of a wide array of nanomaterials, including but not limited to, graphene, carbon nanotubes, metal-oxide nanoparticles, and semiconductor quantum dots [4].The allure of CVD lies in its ability to produce high-quality, uniform thin films and nanostructures with controlled properties, often at scales unattainable by other methods [5].The CVD process involves the chemical reaction of gaseous precursors on a substrate, leading to the deposition of the desired material.By judiciously selecting the precursors, adjusting the process parameters such as temperature, pressure, and flow rates, and employing suitable catalysts, researchers can fine-tune the morphology, composition, and crystallinity of the resulting nanomaterials [6]. Figure 1 illustrates a flowchart showing the general steps involved in the Chemical Vapor Deposition process.
While the potential of CVD in nanomaterial synthesis is undeniable, a comprehensive understanding of the underlying mechanisms, the role of various process parameters, and their interplay is crucial for harnessing its full potential [7].The relationship between the CVD process conditions and the properties of the synthesized nanomaterials is often non-linear and multifaceted.Factors such as precursor decomposition rates, surface diffusion of adatoms, nucleation and growth kinetics, and interactions with the substrate can all influence the final material characteristics.Thus, a systematic characterization of nanomaterials produced under varying CVD conditions becomes imperative to decipher these complex relationships [8].In recent years, advancements in characterization techniques have provided researchers with tools of unparalleled resolution and sensitivity.Techniques such as Transmission Electron Microscopy (TEM), XPS, and Raman Spectroscopy have enabled insights into the nanoscale morphology, chemical composition, and vibrational properties of materials, respectively [9][10][11][12].These tools, when applied to CVD-synthesized nanomaterials, can unravel the intricate details of their structure and properties, paving the way for a more deterministic approach to material synthesis.Furthermore, with the advent of computational power and machine learning algorithms, there is an opportunity to move beyond empirical observations and towards predictive modeling.By feeding the vast datasets obtained from characterization studies into sophisticated algorithms, it is now conceivable to develop models that can predict the outcome of a CVD process based on the input parameters.Such models can serve as invaluable tools for researchers and industries, allowing for real-time optimization of CVD processes and tailoring of nanomaterial properties for specific applications.
Our goal in this study is to integrate CVD synthesis, cutting-edge evaluation, and optimistic modelling.To pave the way for the next generation of nanomaterials optimized for state-of-the-art applications, we offer thorough research of CVDsynthesized nanomaterials with the goal of providing a holistic knowledge of the process-structure-property linkages.Ultimately, we hope that our efforts will add to the rich variety of material science, where the creation of new materials is both an art and a well-regulated science.

Literature Review
Due to its scalability and adaptability, CVD is a commonly utilised technique to produce nanomaterials.Numerous investigations have been carried out throughout the years to comprehend, enhance, and broaden the capabilities of CVD in nanomaterial creation.This review of the literature tries to provide an overview of some of the key contributions made in this area.The Carbon Nanotube (CNT) is one of the most promising carbon nanomaterials because of its distinct physical and chemical characteristics.Research that focused on the environmental advantages of employing biogas rather than conventional hydrocarbons obtained from fossil fuels emphasised the synthesis of CNT using biogas as a carbon precursor [13].Because of its extraordinary electrical characteristics, graphene, a single sheet of carbon atoms, has attracted a lot of interest.According to a research, Microwave Plasma CVD may be used to directly synthesise huge areas of graphene on insulating substrates [14].
Cu2O nanoparticles adorned with tungsten disulfide nanostructures were used to create a brand-new hybrid material.Regarding hydrogen sulphide gas, this hybrid nanomaterial demonstrated excellent gas detecting properties [15].Using a CVD procedure, a new pot-shaped carbon nanomaterial known as "carbon nanopot" was made thanks to an inventive synthesis technique that was created [16].Research created carbon nanowall (CNW) tetrapods connected with nanocrystalline diamond in a 3D hybrid network structure using hot filament CVD [17].Plasma CVD has shown promise for low-temperature synthesis and SWNT structural control [18].Boron Nitride in Hexagons (h-BN) Synthesis, sometimes known as "white graphene," differs from graphene in its characteristics.A thorough analysis included CVD's use in the synthesis, growth process, and adjustable characteristics of h-BN [19].Using CVD, wafer-scale graphene was created, and its compatibility with Si-based electronic device integration methods was emphasised in a review [20].
Research showed how to synthesise a continuous layer of WS2 for gas sensing applications by combining atmospheric pressure CVD with aerosol-assisted CVD [21].Due to their distinct coil form, carbon nanocoils have potential uses in MEMS and microelectronics.Microwave CVD was used in a work to demonstrate the production of carbon nanocoils [22].The synthesis of different nanomaterials has shown to be made possible by the adaptable and scalable nature of CVD.The ongoing developments in this area are enabling the creation of innovative nanomaterials with improved characteristics and capabilities, which have potential uses in a variety of industries, from electronics to environmental sensing.

CVD Setup
The CVD system employed in this study was a low-pressure, hot-wall reactor.The system comprised a quartz tube furnace, a gas delivery system, and a vacuum pump to maintain the desired pressure during deposition [23].The pressure equation is given by ( 1) (1) Where, P is the pressure, n is the number of moles of gas, R is the universal gas constant, T is the temperature, and V is the volume of the reactor.

Precursors and Substrates
The precursors selected for the synthesis were based on their volatility, reactivity, and purity.For the deposition of carbonbased nanomaterials, methane (CH₄) was used.For metal-oxide nanoparticles, metalorganic precursors such as ferrocene and molybdenum hexacarbonyl were employed [24].Substrates used included silicon wafers (Si(100) and Si(111)) and copper foils.Prior to deposition, substrates were cleaned using a standard RCA cleaning procedure to ensure a contaminant-free surface.

CVD Process Parameters
The deposition process was carried out at varying temperatures ranging from 500°C to 1000°C.The pressure inside the reactor was maintained between 1 to 10 Torr using the vacuum pump and controlled gas inlet [25].The flow rates of the precursors were adjusted between 10 sccm to 100 sccm using mass flow controllers.The deposition rate is given by ( 2) Where r is the deposition rate, k is the rate constant, P is the pressure, T is the temperature,   is the activation energy, and a and b are empirical constants.

Transmission Electron Microscopy (TEM )
TEM analyses were conducted using a JEOL JEM-2100F microscope operating at 200 kV.Samples for TEM were prepared by scraping the nanomaterials off the substrate and dispersing them in ethanol, followed by ultrasonication and drop-casting onto a carbon-coated copper grid [26].

X-ray Photoelectron Spectroscopy (XPS)
XPS measurements were performed using a Thermo Scientific K-Alpha spectrometer with Al Kα radiation.The binding energies were calibrated using the C 1s peak at 284.6 eV as a reference.

Raman Spectroscopy
Raman spectra were obtained using a Renishaw inVia Raman microscope with a 532 nm laser excitation source.The laser power was kept below 1 mW to prevent sample damage.

Data Preprocessing
The data obtained from the characterization techniques were preprocessed to remove noise and normalize the values.Principal Component Analysis (PCA) was employed to reduce dimensionality and retain the most significant features [27].The transformed data is given by ( 3) ′ =  (3) Where, X′ is the transformed data, X is the original data, and W is the weight matrix obtained from PCA.

Model Architecture and Training
A neural network model was developed using TensorFlow and Keras libraries.The architecture comprised three dense layers with 128, 64, and 32 neurons, respectively, and ReLU activation functions.The output layer used a linear activation function to predict the properties of the nanomaterials [28].The model was trained using the Adam optimizer and Mean Squared Error (MSE) as the loss function given by (4).
(4) Where, N is the number of samples,   is the actual value, and   ̂ is the predicted value.Training was conducted for 100 epochs with a batch size of 32, using 80% of the data for training and 20% for validation.

Validation and Testing
The trained model was validated using the reserved 20% of the dataset.The performance metrics used included the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and the coefficient of determination (R²).In this section, we have detailed the materials, methods, and tools employed in our study.The subsequent sections will delve into the results and insights derived from these methodologies

Characterization Results
The synthesized nanomaterials, derived from the CVD process under varying conditions, underwent rigorous characterization to ascertain their morphological, compositional, and structural attributes.The results from each characterization technique are presented and discussed in detail below.

Transmission Electron Microscopy (TEM) Results
TEM imaging revealed the morphology and crystalline nature of the synthesized nanomaterials [29].For carbon-based nanomaterials, the images showcased layered graphene-like structures with an average layer count of 3-5 layers.Metaloxide nanoparticles exhibited a spherical morphology with an average diameter of 20 nm.High-resolution TEM (HRTEM) further confirmed the crystalline nature of the nanoparticles, with interplanar spacings corresponding to specific crystallographic planes.The measured d-spacing for the metal-oxide nanoparticles was found to be 0.35 nm, aligning with the (101) plane of the standard crystal structure.

XPS Results
XPS analysis provided insights into the elemental composition and chemical states of the nanomaterials.The carbonbased nanomaterials exhibited two prominent peaks: C 1s at 284.6 eV, indicative of sp² hybridized carbon, and a minor peak at 286.5 eV, corresponding to sp³ hybridized carbon or defects.For metal-oxide nanoparticles, peaks corresponding to the metal (M) and oxygen (O) were observed (See Table 1).The binding energy of the metal peak, M 2p, was consistent with its oxidized state, confirming the formation of metal-oxide.Figure 2 illustrates the XPS spectra showing peaks corresponding to different elements.

Raman Spectroscopy Results
Raman spectroscopy further elucidated the structural quality and defects in the synthesized nanomaterials.For the carbonbased materials, two dominant peaks were observed: the G-band at ~1580 cm⁻¹, characteristic of graphitic materials, and the D-band at ~1350 cm⁻¹, indicative of defects or disorders.The intensity ratio     provides insights into the defect density.

An average
ratio of 0.9 was observed, suggesting a moderate defect density in the synthesized graphene-like structures.
For metal-oxide nanoparticles, Raman peaks corresponding to their specific vibrational modes were observed, confirming their crystalline phase.The intensity ratio can be written as ( 5

Structural Analysis
Selected Area Electron Diffraction (SAED) patterns from TEM analysis confirmed the crystallinity of the synthesized nanomaterials.The diffraction rings were indexed to specific planes of the respective crystal structures.For metal-oxide nanoparticles, the observed rings matched well with the standard diffraction pattern, confirming their phase purity.

Summary of Characterization Results
The combined results from TEM, XPS, and Raman spectroscopy provided a comprehensive understanding of the synthesized nanomaterials.The carbon-based materials exhibited layered structures with moderate defect densities, while the metal-oxide nanoparticles showcased a crystalline, phase-pure nature.The consistency in results across different characterization techniques affirms the reliability of the CVD process parameters employed and sets the stage for subsequent modeling and application-based studies.

Mechanical and Functional Properties Analysis
Beyond the fundamental characterization of the synthesized nanomaterials, understanding their mechanical and functional properties is paramount, especially when considering their potential applications in various domains.This section delves into the mechanical robustness, elasticity, and specific functional attributes of the nanomaterials derived from the CVD process.

Nanoindentation Analysis
Nanoindentation, a technique to measure hardness and elastic modulus at the nanoscale, was employed using a Berkovich diamond indenter.Load-displacement curves were obtained, and the Oliver-Pharr method was utilized to extract the mechanical properties.The reduced modulus is given by ( 6) Where   is the reduced modulus, S is the stiffness at peak load, and A is the projected contact area at peak load.
The hardness (H) was calculated using (7)  =    (7) Where   is the maximum applied load.The results in Table 1 indicated that the carbon-based nanomaterials exhibited a hardness of 5 GPa and an elastic modulus of 150 GPa.In contrast, the metal-oxide nanoparticles showcased a hardness of 12 GPa and an elastic modulus of 320 GPa (See Table 3)

Tensile Testing
Micro-tensile testing was conducted on thin films of synthesized nanomaterials to determine their tensile strength and strain-to-failure.The stress-strain curves revealed that the carbon-based materials had a tensile strength of 130 MPa with a strain-to-failure of 1.2%.The metal-oxide nanoparticles, when sintered into a cohesive film, exhibited a tensile strength of 400 MPa and a strain-to-failure of 0.8%.The stress is given by ( 8) Where, σ is the stress, F is the applied force, and  0 is the original cross-sectional area.

Functional Properties: Electrical and Thermal Conductivity
Four-point probe measurements were employed to determine the electrical conductivity of the materials.The carbonbased nanomaterials, owing to their graphitic nature, exhibited an impressive electrical conductivity of 6000 S/m.The metal-oxide nanoparticles, being semiconducting in nature, had a conductivity of 50 S/m.For thermal conductivity measurements, the laser flash analysis (LFA) method was used.The carbon-based materials showcased a thermal conductivity of 150 W/m•K, while the metal-oxide nanoparticles had a value of 25 W/m•K.The results are shown in Table 4. ,

Surface Wettability
Contact angle measurements were conducted to understand the wettability and surface energy of the synthesized materials.The carbon-based materials exhibited a contact angle of 75°, indicating a moderately hydrophobic nature.In contrast, the metal-oxide nanoparticles had a contact angle of 50°, suggesting a more hydrophilic surface.

Summary of Mechanical and Functional Properties Analysis
The synthesized nanomaterials, through the CVD process, not only showcased distinct morphological and structural attributes but also exhibited remarkable mechanical robustness and functional properties.The carbon-based materials, with their inherent graphitic nature, demonstrated superior electrical and thermal conductivities, making them suitable for electronic and thermal management applications.On the other hand, metal-oxide nanoparticles, with their higher mechanical strength and semiconducting nature, hold promise for applications in robust sensors, actuators, and microelectromechanical systems (MEMS).The comprehensive analysis presented herein underscores the versatility of the CVD process in tailoring nanomaterial properties, setting the stage for their integration into a myriad of advanced technological applications.

Discussion
The synthesis, characterization, and subsequent analysis of nanomaterials via the CVD process, as presented in the preceding sections, offers a plethora of insights into the realm of advanced material science.This discussion aims to contextualize these findings, drawing connections between the CVD process parameters, the intrinsic properties of the synthesized nanomaterials, and their potential implications in real-world applications.

Correlation between CVD Parameters and Nanomaterial Properties
The CVD process, with its myriad of controllable parameters, has demonstrated a profound influence on the resultant nanomaterial properties.The observed layer count in carbon-based materials, for instance, can be attributed to the specific precursor flow rates and deposition temperatures.Higher temperatures typically favour the formation of few-layer structures due to enhanced mobility of carbon species on the substrate [30].This observation aligns with literature reports where elevated CVD temperatures have been linked to reduced layer counts in graphene and related materials.Similarly, the crystallinity and phase purity of the metal-oxide nanoparticles can be traced back to the choice of precursors and their decomposition kinetics.The observed d-spacing and the indexed crystallographic planes, as revealed by HRTEM, are indicative of a well-controlled CVD process that promotes the growth of phase-pure nanoparticles [31].

Mechanical Robustness and Functional Attributes
The impressive mechanical properties of the synthesized nanomaterials, especially the high tensile strengths and moduli, can be attributed to their nano-scale dimensions and inherent crystal structures.At the nanoscale, materials often exhibit enhanced mechanical properties due to a reduction in defect sites and grain boundaries.The observed values, especially for the metal-oxide nanoparticles, are consistent with their bulk counterparts but with enhanced performance due to nano structuring.The functional properties, particularly the electrical and thermal conductivities, are inherently tied to the morphology and defect density of the materials.The high conductivity observed in the carbon-based materials underscores their graphitic nature, with a minimal sp³ hybridized carbon or defect presence, as corroborated by the XPS and Raman results.Such properties make them prime candidates for applications in high-frequency electronics, energy storage, and thermal interface materials.

Implications for Advanced Applications
The synthesized nanomaterials, with their tailored properties, hold immense promise for a range of applications.The carbon-based materials, given their electrical and thermal attributes, could revolutionize next-generation electronics, offering faster, more efficient devices with enhanced thermal management capabilities.Their moderate hydrophobicity, as indicated by the contact angle measurements, also suggests potential use in anti-fouling coatings or as components in composite materials to impart water-resistance.The metal-oxide nanoparticles, with their semiconducting nature and mechanical robustness, can find applications in sensors, actuators, and other MEMS devices [32].Their hydrophilic nature further suggests potential use in catalysis or as drug delivery agents in biomedical applications.Figure 4 illustrates the heatmap showcasing the correlation between different CVD parameters and resultant nanomaterial properties.

Future Perspectives and Recommendations
While the current study provides a comprehensive understanding of nanomaterials synthesized via CVD, there remains a vast landscape to explore.Future studies could delve deeper into the role of catalysts in the CVD process, aiming to achieve even finer control over nanomaterial properties.Additionally, integrating machine learning models with real-time CVD process monitoring could pave the way for on-the-fly adjustments, ensuring optimal material synthesis [33].The CVD process, with its versatility and precision, stands as a beacon in the realm of nanomaterial synthesis.The insights gleaned from this study not only advance our understanding of the process-structure-property relationships but also chart a course for the future, where the boundaries between material design and application needs become increasingly blurred [34].The horizon of material science, illuminated by such endeavours, promises innovations that could reshape our technological landscape.

Conclusion
Nanomaterials, with their immense potential and many uses, have been a focus of material science study for decades.This work on the synthesis, characterisation, and analysis of nanomaterials using CVD has shown the complex relationship between process factors and material characteristics.We started with CVD synthesis, carefully varying settings to produce a variety of nanomaterials.State-of-the-art TEM, XPS, and Raman spectroscopy revealed these materials' morphological, compositional, and structural details.The mechanical and functional characteristics investigation exposed the synthesised nanomaterials' adaptability and potential, demonstrating extraordinary qualities that hold great promise for real-world applications.
Drawing linkages between the synthesis process, observable qualities, and prospective applications, the discussion part was comprehensive.Carbon-based materials provide high-frequency electronics and heat control, whereas metal-oxide nanoparticles have sensing, actuation, and biological potential [35].Synthesised materials promise technological breakthroughs.The CVD process's-controlled parameters allow nanomaterial creation with unmatched precision.The capacity to modify nanoscale characteristics may change material design from discovery to purposeful design.Advanced characterisation methods combined with computational tools like machine learning demonstrate the strength of an interdisciplinary approach.Synergy increases comprehension and enables previously impossible ideas.Nanomaterials is wide and ever-changing, yet this research provides a complete review.The insights gained here may be used to explore novel materials, refine synthesis methods, and reveal industry-changing applications.This discovery proves that little is powerful in materials.Though small, the nanoscale offers the answer to solving some of our biggest problems.We continue our exploration of this intriguing field with the aim that tomorrow's materials will only be restricted by our creativity.

Figure 3 Fig. 3
Figure 3 illustrates the Raman spectra showcasing the D-band and G-band.