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Research Papers

# Atomic Layer Deposition Process Modeling and Experimental Investigation for Sustainable Manufacturing of Nano Thin FilmsOPEN ACCESS

[+] Author and Article Information
Dongqing Pan, Dongsheng Guan

Department of Mechanical Engineering,
University of Wisconsin-Milwaukee,
Milwaukee, WI 53201

Tien-Chien Jen

Department of Mechanical Engineering Science,
University of Johannesburg,
Auckland Park 2006, South Africa

Chris Yuan

Department of Mechanical Engineering,
University of Wisconsin-Milwaukee,
Milwaukee, WI 53201
e-mail: cyuan@uwm.edu

1Corresponding author.

Manuscript received January 9, 2016; final manuscript received July 27, 2016; published online September 13, 2016. Assoc. Editor: Moneer Helu.

J. Manuf. Sci. Eng 138(10), 101010 (Sep 13, 2016) (9 pages) Paper No: MANU-16-1019; doi: 10.1115/1.4034475 History: Received January 09, 2016; Revised July 27, 2016

## Abstract

This paper studies the adverse environmental impacts of atomic layer deposition (ALD) nanotechnology on manufacturing of Al2O3 nanoscale thin films. Numerical simulations with detailed ALD surface reaction mechanism developed based on density functional theory (DFT) and atomic-level calculations are performed to investigate the effects of four process parameters including process temperature, pulse time, purge time, and carrier gas flow rate on ALD film deposition rate, process emissions, and wastes. Full-cycle ALD simulations reveal that the depositions of nano thin films in ALD are in essence the chemisorption of the gaseous species and the conversion of surface species. Methane emissions are positively proportional to the film deposition process. The studies show that process temperature fundamentally affects the ALD chemical process by changing the energy states of the surface species. Pulse time is directly related to the precursor dosage. Purge time influences the ALD process by changing the gas–surface interaction time, and a higher carrier gas flow rate can alter the ALD flow field by accelerating the convective heat and mass transfer in ALD process.

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## Introduction

As a vapor-phase additive nanomanufacturing technique capable of depositing ultrathin films at atomic scale with superior uniformity and conformity, atomic layer deposition (ALD) has attracted enormous attention from both academia and industry in the context of miniaturization of electronic devices driven by the consumer electronic products in recent years [13]. Initially being developed and adopted in the microelectronics industry, now ALD technology is on a rapid expansion to other manufacturing sectors, including energy conversion and storage, medical devices, and environmental systems [49].

However, ALD technology has significant sustainability issues, especially for large-scale industrial applications. One major issue of ALD technology is the low throughput as defined by its nature of alternating the exposure of the substrate to each precursor material, which have been extensively investigated in our previous studies [1013]. Another major issue of ALD technology is the adverse environmental impacts associated with its manufacturing processes, largely due to the highly toxic chemicals being used and the greenhouse gas emissions and novel nanoparticles generated from ALD operations [1416].

Taking the ALD of Al2O3 model process as an example, the precursor, trimethylaluminium (TMA) is extremely flammable and highly toxic and can cause severe skin and eye damage [14,15]. Those unreacted TMA molecules can pose a high risk to the public health and environment when purged out of the ALD system. The by-product, methane, is a major greenhouse gas with global warming potential 21 times that of CO2 [15]. Nanoparticles can also be formed in the ALD process, and the nanoparticle emissions might be hazardous to both occupational and public health [16]. Such ALD process wastes and emissions are grave concerns for both industry and society and must be completely understood to support its sustainable scale-up and applications in future large-scale industrial processes [15].

Previous studies show that the ALD process features low material utilization efficiency. For instance, in Al2O3 ALD, only 50.4% of TMA is deposited on wafers [14,15]. ALD process is also highly energy-intensive. During the ALD of Al2O3 process, about 4.09 MJ energy is consumed for deposition of a 30 nm film [15]. Our previous experimental study on nanoparticle emissions in Al2O3 ALD process shows that the total nanoparticle emissions with diameter less than 100 nm range between 6.0 × 105 and 2.5 × 106 particles from 25 cycles of Al2O3 ALD [16].

Since the process mechanisms of waste and emission generation from ALD operations have not yet been investigated, this paper focuses on the numerical and experimental investigations of the gaseous material wastes and emissions from the Al2O3 ALD process. In this study, the Al2O3 ALD process is characterized, and the methane emissions in the process are investigated numerically and experimentally. Our previously established ALD numerical model is further developed with detailed surface chemical kinetics and reaction mechanism achieved by DFT calculations [10]. Using the developed model, the effects of four process parameters including process temperature, pulse time, purge time, and carrier gas flow rate on the deposition rate and material wastes and emissions are investigated systematically in this study to support the sustainable manufacturing of nanoscale thin films with ALD technology.

## ALD of Al2O3 Process Model With Detailed Chemical Kinetics

###### Physical Process Modeling.

As a vapor film fabrication technology, ALD is a strongly coupled physical and chemical process. The physical thermal-fluid process of ALD includes momentum transport, mass transport, and heat transfer. The modeling process is described in great detail in our previous papers [10,11,13]. The mathematical modeling equations are listed as follows: Display Formula

(1)$∂ρ∂t+∇⋅(ρV⇀)=0$
Display Formula
(2)$∂∂t(ρV⇀)+∇⋅(ρV⇀V⇀)=−∇P+∇⋅τ̃+ρg⇀+F⇀$
Display Formula
(3)$∂∂t(ρci)+∇⋅(ρciV⇀)=−∇⋅J⇀m,i+Ri$
Display Formula
(4)$∂∂t(ρE)+∇⋅[V⇀(ρE+P)]=∇⋅[k∇T−∑ihiJ⇀h,i+(τ̃⋅V⇀)]$

where $ρ$ is the density; $V⇀$ is the velocity vector; $P$ is the static pressure; $ρg⇀$ and $F⇀$ are the gravitational body force and external body forces, respectively; $τ̃$ is the stress tensor; $ci$ is the local molar fraction of species $i$; $Ri$ is the net rate of production of species $i$ during its chemical reaction; $J⇀m,i$ is the mass diffusive flux of mixture species i; $k$ is the material thermal conductivity; $hi$ is the enthalpy of mixture species i; and $J⇀h,i$ is the energy diffusive flux of mixture species i.

Within the process model above, the continuity equation (1) conserves mass in the ALD surface reaction. The Navier–Stokes equations (2) are adopted to model the process of momentum transport in the gaseous flow of ALD reactor. The species transport process is governed by the convection–diffusion equation (3), which is coupled by the chemical kinetics. The energy equation (4) is modeling the overall heat transfer in ALD reactor. The detailed numerical model setup including the 3D geometry, meshing, and boundary condition definitions can be found in our previous papers [1012]. In this paper, we focus on the reaction mechanism and chemical kinetic modeling for ALD process emission and waste generations.

###### Surface Reaction Modeling.

The surface chemical kinetics of ALD is of critical importance to characterize the film deposition process, emissions, and wastes. However, it is extremely challenging to obtain the detailed information regarding the surface reactions at the atomic level by in situ experimental characterizations [17]. Computational quantum chemistry approaches, such as the DFT method, provide a satisfactory alternative to study the ALD surface reaction mechanism and obtain the energetic and structural information about the molecular interactions essential to understand the surface chemical reactions of ALD process [17]. Several studies on the molecular interactions of Al2O3 ALD using DFT methods have been reported in the literature [1723]. This paper aims to integrate these DFT reaction calculations and chemical kinetic data into our numerical ALD model to understand the ALD surface chemical reaction mechanism. In this study, the overall Al2O3 ALD using TMA and water can be expressed as Display Formula

(5)$2Al(CH3)3g+3H2Og⇒Al2O3b+6CH4g↑$

where superscripts g and b represent gas and bulk (solid) species, respectively. This overall reaction equation cannot be directly used in the chemical kinetic model because it does not reveal the ALD pulse process in Al2O3 ALD operations.

A more complex chemisorption reaction mechanism in Al2O3 ALD depicting the actual sequential ALD pulse and reaction steps is modeled by the following two half reactions: Display Formula

(6)$2Al(CH3)3g+3OH*⇒Al-CH3*+Al-(CH3)2*+3Ob+3CH4g↑$
Display Formula
(7)$3H2Og+Al-CH3*+Al-(CH3)2*⇒3OH*+2Alb+3CH4g↑$

where superscripts * represents surface site species. These two irreversible equations reveal the actual Al2O3 ALD reaction sequences. With sufficient chemical kinetic information, these two half reactions are able to simplify and approximate the actual surface reaction and material deposition processes in ALD reactor [10]. However, the above two half reactions do not include the information regarding the elementary reaction steps as well as the kinetic information of ALD process, which are important in modeling the ALD process wastes and emissions.

With the aid of DFT quantum chemistry calculations, much more detailed chemical deposition mechanism can be revealed and investigated for the ALD of Al2O3 process [1723]. For the ALD of Al2O3, the Al2O3 nano thin films are deposited on the Si (100) surface using the TMA and H2O precursors. Accordingly, in the DFT studies, Si9H12 cluster is used to investigate the chemical reactivity and vibrational properties of the Si (100) surface [19].

In the literature, Delabie et al. studied the possible CH3 and OH-terminated surface species on silicon surface using DFT approach [21]. Their work shows that the hydrolysis of the SiCH3 is kinetically unfavorable due to the five coordinated Si atoms in the transition state structure, which makes the following surface reaction with water difficult [21]. Their studies imply that it is unlikely to have methyl-covered surface on Si (100) surface in actual Al2O3 ALD. Meanwhile, they found that the OH-terminated Si (100) surface reacts with TMA, which is consistent with experimental results. Hence, it is reasonable to presume that the silicon surface is hydroxylated with OH groups initially during ALD process.

In TMA pulse step, with OH-terminated silicon surface, the ALD deposition begins by interacting with gaseous TMA molecules forming a bond between O and Al atoms [1719]. The formation is reversible and generates an intermediate surface species as shown in reaction R1 Display Formula

(8)$R1:Al(CH3)3g+O⊥H*⇔bf(CH3)3AlO⊥H*$

where f and b represent the forward and backward reactions, respectively, and the symbol $⊥$ denotes the surface bond linkage with surface group.

The above intermediate surface group $(CH3)3AlO⊥H*$ further proceeds to a transition state structure by forming a bond between the O atom and a H atom from one of the three methyl ligands and finally evolves into a more stable structure with two methyl-terminated ligands by releasing a methane molecule. This process is represented by reaction R2 Display Formula

(9)$R2:(CH3)3AlO⊥H*⇔(CH3)3AlO⊥H‡⇒(CH3)2AlO⊥*+CH4g↑$

where the superscript $‡$ represents the transition state. The energy profiles of these two reactions can be found in Ref. [19]. The emission of gaseous methane makes this process irreversible.

The energy profile of DFT study [19] shows that the formed surface species $(CH3)2AlO⊥*$ is in a high energy state and is kinetically inclined to interact with the nearby OH* group resulting in an intermediate surface group, as shown in following reaction R3: Display Formula

(10)$R3:(CH3)2AlO⊥*+O⊥H*⇔bf(CH3)2AlO2⊥H*$

In the complex of $(CH3)2AlO2⊥H*$, a linkage between the Al atom and the hydroxyl O atom is formed. A transition structure is readily formed when the stand-alone hydroxyl H atom is attached to one of the two methyl ligands. As a result, a methane molecule is emitted as shown in reaction R4 Display Formula

(11)$R4:(CH3)2AlO2⊥H*⇔(CH3)2AlO2⊥H‡⇒CH3AlO2⊥*+CH4g↑$

At this point, a much more stable species AlCH3* terminates the surface evolutions in TMA pulse step. The initial OH-terminated substrate surface in R1 is transformed to Al (CH3)2* by R2, and AlCH3* by R4, leaving O and Al atoms anchored in the formed surface structures. Since the double-methyl-mounted species (Al (CH3)2*) is kinetically unstable, most surface area of the silicon substrate is covered by AlCH3* and only a small portion by Al (CH3)2* after TMA pulse.

During the water pulse step, due to the coexistence of the two possible methyl-terminated surface species, the surface reaction mechanism is twofold. In the case of the double-methyl-terminated species Al (CH3)2*, a water molecule is chemisorbed by the Al atom resulting in two stand-alone H atoms as shown in reaction R5. One of the H atoms is attracted by the C atom of the methyl group resulting in a temporary O–H–C linkage. The transitional bond is finally broken at the O–H bond leaving the surface site terminated with a heterogeneous mixture of OH and CH3. As presented in reaction R6, a methane molecule is then emitted in the process Display Formula

(12)$R5:(CH3)2AlO⊥*+H2Og⇔bf(CH3)2O⊥AlOH2*$
Display Formula
(13)$R6: (CH3)2O⊥AlOH2*⇔(CH3)2O⊥AlOH2‡⇒CH3O⊥AlOH*+CH4g↑$

Contacting with another water molecule, the surface site further evolves to an intermediate structure denoted as $CH3O⊥AlOHOH2*$ shown in the following reaction R7. A transition state structure is further generated in R8 when a similar transitional O–H–C bond is formed. The transition state structure $CH3O⊥AlOHOH2‡$ is the barrier before reaching the final stable OH-terminated structure Display Formula

(14)$R7:CH3O⊥AlOH*+H2Og⇔bfCH3O⊥AlOHOH2*$
Display Formula
(15)$R8: CH3O⊥AlOHOH2*⇔CH3O⊥AlOHOH2‡⇒O⊥Al(OH)2*+CH4g↑$

With breakage of the transitional bond, a methane molecule is generated, which leaves the surface sites fully covered by two OH groups. The structure has no more place for extra water molecules, and the transformation of the double-methyl-terminated species Al (CH3)2* to double-hydroxyl-terminated species $Al(OH)2*$ is finalized.

The reaction process of single-methyl-terminated species AlCH3* with water molecules is similar to Eqs. (12)(15) and is presented in the following reactions R9 and R10: Display Formula

(16)$R9:Al⊥CH3*+H2Og⇔bfCH3Al⊥OH2*$
Display Formula
(17)$R10: CH3Al⊥OH2*⇔CH3Al⊥OH2‡⇒Al⊥OH*+CH4g↑$

Water molecule is first adsorbed by the Al atom resulting in an intermediate species denoted as $CH3Al⊥OH2*$. With extra energy, the species further evolves into a transition state structure by forming the O–H–C bond. The excited structure is finally transformed to a single-hydroxyl-terminated species by emitting a methane molecule. During the process, an extra Al–O is formed.

As described in the above deposition reactions with Eqs. (8)(17), the ALD process is actually involved with the transformations of different surface species. TMA pulse leaves the substrate surface with O–Al bonds and methyl-terminated surface sites, which are further converted in water pulse step by forming Al–O bonds leaving the surface covered by hydroxyl-terminated sites. Within one ALD cycle, the silicon surface is reconstructed with the O–Al–O bonds, which represents a single layer of Al2O3 film. Revealed by the DFT energy profiles of the mechanism [1822], the success of these atomic-level transformations heavily depends on the energy conditions, the availability of gaseous species. and the surface species. The reaction conditions are defined by the macrolevel process parameters, such as the process temperature, pulse time, purge time, and carrier gas flow rate.

###### Physical and Chemical Model Coupling.

With the reaction mechanism described by Eqs. (1)(17) above, the chemical kinetics of Al2O3 ALD is then coupled with the thermal-fluid dynamics model by chemical kinetics rate law [24]. The reaction rate $ℜr$ (mol/m3 s) of rth surface reaction Rr is obtained from the chemical rate Eq. (19)Display Formula

(18)$Rr: ∑i=1Nggi′Gi+∑i=1Nbbi′Bi+∑i=1Nssi′Si⇔kbkf∑i=1Nggi″Gi+∑i=1Nbbi″Bi+∑i=1Nssi″Si$
Display Formula
(19)$ℜr=kf∏i=1Ng[Gi]wgi′∏j=1Ns[Sj]wsj′$

where G, B, and S are the gaseous, bulk, and surface species; $gi′$, $bi′$, and $si′$ are the stoichiometric coefficients for the ith species as a reactant; $gi″$, $bi″$, and $si″$ are the stoichiometric coefficients for the ith species as a product; Ng, Nb, and Ns are the number of gaseous, bulk, and surface species involved in that specific reaction; and [ ]w represents surface coverage of surface species and concentrations of gaseous species on the wafer surface, respectively.

For an irreversible reaction, the reaction rate constant of rth surface reaction is determined by the Arrhenius expression Display Formula

(20)$kr=A exp(−EaRT)$

where $A$ is the pre-exponential factor, $Ea$ is the activation energy, T is the temperature in Kelvin, and R is the universal gas constant.

The pre-exponential factor, A, represents the frequency of collisions between the reactant molecules. It is practically unfeasible to obtain the pre-exponential factor empirically by experiments, and the collision theory estimation is not accurate for gas–solid surface interactions [25,26]. From literature, the transition state theory can provide an accurate representation of the pre-exponential factor through the Eyring equation [26]. Detailed descriptions of the following pre-exponential factor can be found in Refs. [26] and [27]: Display Formula

(21)$A=(kBTh)exp(ΔS0‡R)$

where h and kB are the Planck's constant and Boltzmann's constant, respectively, and $ΔS0‡$ is the change in standard entropy of forming the transition state.

The activation energy, $Ea$, in Arrhenius expression is the change in standard enthalpy of forming the transition state as expressed below Display Formula

(22)$Ea=ΔH0‡$

The activation energy is the energy barrier, which can be characterized from the energy profiles achieved from DFT calculations, while the entropy change $ΔS0‡$ is evaluated through the equilibrium constant of forming the transition state, which can be expressed as [27] Display Formula

(23)$ΔS0‡=RlnK‡+ΔH0‡T$

where the equilibrium constant is computed using statistical mechanics methods and the molecular partition functions [17].

The backward reaction constant kb in the ALD reversible reactions can be evaluated by the equilibrium constant KDisplay Formula

(24)$kb=kfK$

The equilibrium constants pertaining to these ALD reactions are listed in Ref. [17].The reaction energy data, such as change of enthalpy, can be found in the cited DFT studies [1822].

With the developed ALD chemical kinetic model, three levels of four process parameters—process temperature (150 °C, 200 °C, and 250 °C), pulse time (0.015, 0.02, and 0.025 s), purge time (5, 10, and 15 s), and carrier gas flow rate (10, 20, and 30 sccm)—are simulated to study their effects on the surface deposition, process wastes, and emissions.

## Experiments

Based on the same ALD system in the numerical model, experiments to characterize the surface reaction process and emissions in Al2O3 ALD are carried out using the Cambridge NanoTech Savannah 100 ALD reactor. To benchmark the numerical model, especially the chemical kinetics in terms of film growth rate, Al2O3 films are deposited on Si wafer substrate using 99.9% TMA and 99.0% distilled water under three levels of deposition temperatures: 150 °C, 200 °C, and 250 °C. The ALD cycle starts with 300 s stabilization followed by 0.02 s pulse and 10 s purge procedures for both TMA and water. The Al2O3 films are deposited with 500 cycles, and the film thickness is characterized by the UVISEL Spectroscopic Ellipsometer (HORIBA, Ltd., Japan).

Spectroscopic ellipsometry is an optical technique commonly used to characterize the dielectric properties of thin films, e.g., complex refractive index or dielectric function. Typically, the information about the composition, roughness, thickness, crystalline nature, doping concentration, electrical conductivity, and other material properties of thin films can be achieved through ellipsometry.

The UVISEL Spectroscopic Ellipsometry system used in our study is operated by measuring the change in polarization of the incident radiation (with spectral range of 190–2100 nm in the UVISEL system) after interacting (reflection, absorption, scatter, or transmission) with the sample thin films. Since the detected signal is dependent on thickness as well as the film properties, ellipsometry is an excellent tool to determine the thickness and optical constants of thin films [28]. The UVISEL Spectroscopic Ellipsometer used in this study is capable of measuring thin film thickness from 1 Å to 45 μm with a high precision, sensitivity, and resolution.

In the proceeding of ALD cycles, an in situ gas analyzer is used to characterize methane emissions in Al2O3 ALD as shown in the scheme of Fig. 1. The TMA and H2O precursors stored in two separate cylinders are pulsed alternatively into the ALD chamber. Si wafer substrates with a 10 × 20 mm size are placed in the ALD chamber for deposition. A residual gas analyzer (Extorr XT Series RGA) is connected to the outlet of the ALD system behind a gas particulate filter with 100 nm pore size filtration. RGA is a type of mass spectrometer based on quadrupole technology for process control and contamination monitoring and is typically used in high vacuum systems, e.g., ∼1 × 10−7 Torr for the Extorr XT 100 RGA system used in our experiments. It measures the pressure of gases by sensing the weight of each atom as they pass through the quadrupole mass analyzer. RGA is able to characterize the chemical species involved in gas phase reactions and can also be used to monitor the stability of the gaseous environment.

The Extorr XT 100 RGA system can detect gases with mass up to 100 amu and their concentrations. The emissions are sampled through a capillary tube into the RGA device. In our ALD experimental setup, it is extremely difficult to accurately characterize either TMA waste or water vapor in our ALD system due to the possible condensation of water vapor in the ALD outlet and RGA tubing and the possible reactions of TMA waste with the condensed water in the outlet pipe. In our experiments, we focus only on measurement of methane emissions from the ALD process.

## Results and Discussion

###### Al2O3 ALD Deposition Process.

Using the reaction mechanism and the chemical kinetic model, a full cycle of Al2O3 ALD with 0.02 s pulse time and 10 s purge time is simulated under the chamber temperature of 200 °C. The contour plots of gaseous species distributions and the bulk species deposition rates in the entire ALD system are presented in Figs. 2(a) and 2(b) at the end of the two pulse steps, 0.02 s and 10.04 s, respectively. Figure 3 shows the gaseous species distributions in the full ALD cycle with the data probed in the center area of the ALD chamber.

At the initial state, only carrier gas N2 exists in the chamber. As the ALD valve is open for TMA pulse, TMA concentration increases steadily, while N2 concentration decreases as observed in Fig. 3. The increasing methane concentration shows that the surface reaction is activated and the material deposition is initiated. Methane concentration reaches its peak during the 0.02 s pulse step and then declines slightly after that. The declined methane concentration is mainly due to the fact that the reaction rate decreases as the reactive surface sites OH* are being consumed.

The methane generation rate decreases further as the TMA pulse process ends. As the TMA concentration declines during the purge step, the low level of methane concentration in the center area of chamber is maintained by the TMA residuals during the first half of purge step. The increasing carrier gas concentration shows that N2 dominates the chamber space again during the purge step. The materials are not evenly distributed in the entire ALD geometry, and along the flow field, the inlet area encounters the precursor flow first as shown in Fig. 2.

The material concentration during water pulse process has similar variations as seen in the TMA pulse step. As water is being pulsed into the chamber, methane concentration increases steadily and reaches a higher peak. In the second purge process, as water concentration declines promptly, much less methane can be detected in the center area. The gaseous material distribution variations in the center area are profoundly related to the surface species coverage as presented in Fig. 4.

The contour plots of surface coverage and precursor distributions in the entire ALD system for TMA and water pulse steps are shown in Figs. 5(a) and 5(b), respectively. A full coverage of OH* is assumed initially, and its coverage declines slightly in the first few milliseconds, as shown in Fig. 4, and the deceases promptly until it reaches ∼20% at the end of the TMA pulse step. To be specific, 21.8% OH* species is left on the surface and is further consumed in the following purge step. This indicates that within TMA pulse step, the surface reactions are not saturated as shown by the contour plots in Fig. 5(a), especially in the outlet area. Part of the surface reaction is completed during the following purge step.

Meanwhile, the two types of methyl-terminated species, Al (CH3)2* and AlCH3*, are being generated on the surface. At the end of TMA pulse step as shown in Fig. 5(a), the majority of the surface area is covered by AlCH3* (∼77.5% in the center area), while only ∼1.7% is covered by Al (CH3)2*. Other intermediate surface species involved in R1–R10 has much lower level coverage (in the level of 10−6) as indicated in Fig. 5. This is consistent with conclusions from previous DFT studies in literature that Al (CH3)2* is not stable [19]. At the end of the first purge step, 98% substrate surface in the center area is covered by AlCH3* and less than 2% is covered by Al (CH3)2*. During the water pulse, both methyl-terminated surface species are converted back to OH* species as shown in Figs. 4 and 5(b). At the end of the water pulse, ∼96.7% surface sites are covered by the hydroxyl-terminated species. A very small portion of surface reactions are completed in the second purge step.

Figure 6 presents the bulk species deposition rate correlated with the precursor concentrations during the full ALD cycle in the center area. It is found that the bulk species deposition rate is proportional to the corresponding precursor concentration. As shown in Fig. 6, both of the Al and O deposition rates take the parabolic shape with peak values in the pulse process. This is due to the fact that deposition process is not only dependent on the gaseous species concentration but also influenced by the reactive surface species. Although the precursor concentrations are increasing during the pulse steps, the increased deposition rate is balanced by the deceasing reactive surface sites.

Together with the analysis of the elementary chemical reactions in Sec. 2.2, the full-cycle ALD simulations confirm the chemisorption of the gaseous species and conversion of the surface species bulk material depositions in ALD process. Accompanying the deposition process, methane emissions are generated, and process wastes are produced. The actual deposition process is heavily dependent on the interactions of the gaseous, surface, and bulk species, which are essentially influenced by the process parameters such as temperature, pulse, and purge procedures as well as the carrier gas flow rate. In Sec. 4.2, these influential factors are investigated systematically.

###### Effects of Process Parameters on ALD Wastes and Emissions.

In this section, the four process parameters, process temperature, pulse time, purge time, and carrier gas flow rate, are systematically investigated to explore their effects on the gaseous wastes and emissions generated from ALD process. The aim is to reduce the process wastes and emissions while maintaining a high material deposition rate in the studied ALD process.

Temperature is a critical factor in ALD chemical reaction process as defined by the Arrhenius equation, see Eq. (20). In this study, the temperature of the inlet and outlet pipeline of the ALD system is set at 150 °C, and chamber temperature is adjusted at three levels of 150 °C, 200 °C, and 250 °C, respectively, in both the numerical model and experimental tests. The effects of chamber temperature on the total precursor supplied, precursor wastes, and methane emissions are presented in Fig. 7 with 0.02 s pulsing time and 10 s purging time for a ALD cycle and 30 sccm carrier gas flow rate. The experimental results are also plotted in Fig. 7 to benchmark with the numerical results. It is found that precursor dosage is barely affected by the process temperature. In fact, precursor dosage is mainly determined by the pressure difference between the precursor cylinder and the vacuum chamber, which is rarely influenced by the chamber temperature [10].

As described in the reaction mechanism, methane emissions are closely related to the deposition process. The actual ALD involves both chemisorption and desorption or decomposition (backward reactions). A higher temperature of 200 °C accelerates both chemisorption and desorption, but the overall effect as shown in Fig. 7 is the enhancement result of chemisorption process. Methane emissions are increased as shown in Fig. 7(a) from 150 °C to 200 °C. This is consistent with the film growth rate as presented in Fig. 7(b). When the chamber is further heated to 250 °C, however, the growth rate is shown to decrease in both experimental and numerical results. This is mainly due to the fact that the enhanced desorption process dominates the chemisorption process at a higher temperature of 250 °C. Taking reactions R1 and R5 as examples, the extra energy at 250 °C in the system can be sufficient to overcome the energy barriers of the reverse reactions which are 0.6 eV and 0.85 eV for R1 and R5, respectively [19]. This leads to the breakage of the formed O–Al bond in R1 and Al–O bond in R5. With the enhanced desorption process, surface reactions cannot proceed to form O or Al atom depositions on the substrate surface, and as an undesirable result, the precursor molecules are returned to chamber and then purged out as wastes. As shown in Fig. 7(a), the total precursor wastes are increased from 200 °C to 250 °C. Figure 7(b) shows that the precursor wastes are reversely correlated to the deposition rate.

The experimental data of methane emissions from 500 cycles of ALD Al2O3 processes are also plotted in Fig. 7 to validate the numerical results. The results show that at a moderate temperature of 200 °C, most precursors are utilized for Al2O3 film depositions with the lowest precursor waste rate (65.4%), and in the meantime, the highest growth rate of 1.17 Å/cycle is achieved.

Precursor dosage is directly proportional to the pulse time as shown in Fig. 8, in which the ALD process is simulated at three levels of pulse time 0.015 s, 0.02 s, and 0.025 s with 10 s purge time under 200 °C temperature and 30 sccm carrier gas flow rate. As shown in the result, the precursor dosage in an ALD cycle is increased from 0.187 mg to 0.308 mg as pulse time is prolonged from 0.015 s to 0.025 s. With more precursor molecules injected into the reactor, the reactions are driven to the forward direction, and the reverse reactions are restrained, which results in increased material deposition and methane generation. As shown in Fig. 8(a), methane emissions per cycle are increased from 4.5 × 10−3 mg to 6.3 × 10−3 mg, and the growth rate presented in Fig. 8(b) is significantly increased from 0.91 Å/cycle to 1.17 Å/cycle when the pulse time is increased to 0.02 s from 0.015 s.

When the pulse time is further increased to 0.025 s, slight increments are observed for both methane emission and the Al2O3 growth rate. In the case of 0.025 s pulse time when an excessive amount of precursors is supplied to the substrate surface, the extra materials cannot be absorbed in a limited time and are finally purged out of the system after the saturated surface reactions. As revealed in Fig. 8(a), a significant increment of precursor wastes is observed at 0.025 s pulse. In such a case, precursors are greatly overdosed, which deteriorates the sustainability performance of ALD. As presented in Fig. 8(b), the precursor waste rate is as high as 86.2% at 0.025 s pulse time, compared to 70% at 0.02 s pulse time. In this point, less precursors are wasted at 0.015 s pulse time, but the growth rate is also low, only 0.91 Å/cycle, as shown in Fig. 8(b). As a trade-off, 0.02 s is the best pulse time that yields a high growth rate with a relatively higher material usage efficiency.

Figure 9 shows the effects of purge time on the process wastes and emissions at three levels (5 s, 10 s, and 15 s) under 0.02 s pulse time, 200 °C temperature, and 30 sccm carrier gas flow rate. The effect of purge time on precursor dosage is found weak as shown in Fig. 9(a), while it can increase the precursor waste, especially from 5 s purging time to 10 s. With a longer purge time, more precursor residuals in the chamber are purged out by the carrier gas. With the majority of precursor residuals purged out within 10 s, there is not a significant increase of the precursor wastes with a 15 s purge time.

Methane emissions are found to increase as purge time increases from 5 s to 10 s, and a slight increment is observed at 15 s as shown in Fig. 9(a). Similar effect of purge time on material deposition rate is observed in Fig. 9(b). Methane generation is positively related to the material deposition process, and a longer purge time implies more surface reactions on the substrate surface due to the longer contact of precursor molecules with the surface sites. As a result, the growth rate is increased from 1.15 Å/cycle at 5 s purge time to 1.17 Å/cycle at 10 s purge time.

When the purge process is further prolonged to 15 s, the growth rate is observed at the same level as 10 s. This is mainly due to the fact that in the first 10 s, majority of the reactive surface species has already been consumed. Lack of reactive surface species has inhibited the material chemisorption. The material waste rate shown in Fig. 9(b) is higher in a longer purging process. From the results in Fig. 9, a shorter purging process, e.g., 5 s, generates less precursor wastes, but also results in a lower growth rate when compared with a longer purging process. With both deposition rate and sustainability performance taken into account, 10 s is found to be the best choice for the purge time during ALD of Al2O3 process.

In addition, carrier gas flow rate affects the surface deposition process and emissions by enhancing the convective heat and mass transfer in ALD system as revealed in Fig. 10 in which three levels of carrier gas flow rate (10, 20, and 30 sccm) are investigated with 0.02 s pulsing time and 10 s purging time at 200 °C chamber temperature. As shown in Fig. 10(a), precursor wastes increase with the increasing of the carrier gas flow rate. Total precursor wastes increase from 0.13 mg/cycle at 10 sccm flow rate to 0.18 mg/cycle at 30 sccm flow rate. A higher carrier gas flow rate shortens the contact time of precursors with substrate surface and thus leads to more unreacted precursors purged out of the ALD system.

With more unreacted precursor materials purged out by a higher N2 flow rate, less surface reactions happen in the ALD process due to lower gaseous precursor concentrations on the silicon substrate surface. The growth rate is decreased from 1.19 Å/cycle at 10 sccm carrier gas flow rate to 1.17 Å/cycle at 30 sccm carrier gas flow rate. Methane emissions also decrease due to the reduced surface reactions. As more precursor molecules are purged out without reacting with the surface species on the substrate, the precursor waste rate is found higher at a higher flow rate, as shown in Fig. 10(b). From the results presented, a lower carrier gas flow rate, e.g., 10 sccm, is desirable to achieve a higher growth rate while restraining the precursor waste rate.

## Conclusions

This paper systematically studied the transient deposition process and sustainability performance of the Al2O3 ALD reaction mechanism with the aid of DFT calculations. The detailed ALD surface reaction mechanism including ten elementary surface reactions in Al2O3 ALD process was examined and developed based on the DFT atomic-level investigations. The improved surface reaction mechanism with accurate kinetic data was coupled and integrated into a physical thermal-fluid model. Using the developed numerical model, the transient deposition process was studied and analyzed by probing the distribution variations of the gaseous, surface, and bulk species in a full Al2O3 ALD cycle. The full-cycle ALD simulation revealed that the depositions of bulk material in ALD are in essence the chemisorption of the gaseous species and the conversion of surface species. The actual deposition process is heavily dependent on the interactions of these species, which are essentially influenced by the ALD process parameters.

In this study, the effects of four ALD process parameters—process temperature, pulse time, purge time, and the carrier gas flow rate—are investigated on the Al2O3 material deposition, process waste, and emission generation. Film growth rate on Si substrate has been characterized, and methane emissions were determined through both numerical simulation and experimental testing of the Cambridge Nanotech Savannah S100 ALD system. It is found that ALD process has a very high material waste rate, with about 60% precursors being wasted. It is also concluded that methane emission is positively proportional to the film deposition process. Process temperature fundamentally affects the ALD chemical process by changing the energy states in the surface reactions. Both experimental and numerical results show that a moderate chamber temperature of 200 °C results in a higher growth rate of the Al2O3 thin film and less precursor wastes, while a higher temperature above 200 °C can reduce the film growth rate through enhancing the decomposition process.

In ALD operations, pulse time is directly related to the precursor dosage. A longer pulse time can enhance the deposition process but can also increase the precursor waste, which can undermine the sustainability performance of ALD technology. Purge time and carrier gas flow rate have very weak influences on film growth, precursor waste, and emission generation. Purge time influences the ALD process by changing the gas–surface interacting time, and a high carrier gas flow rate can alter the ALD flow field by enhancing the convective heat and mass transfer in ALD process. For sustainable scale-up of the ALD technology, the effects of the above process parameters presented in this study must be fully considered to minimize the process wastes and emissions while maintaining a high deposition rate for ALD operations.

## Acknowledgements

The financial support from the National Science Foundation (CMMI-1200940) is gratefully acknowledged.

## References

George, S. M. , 2010, “ Atomic Layer Deposition: An Overview,” Chem. Rev., 110(1), pp. 111–131. [PubMed]
Groner, M. D. , Fabreguette, F. H. , Elam, J. W. , and George, S. M. , 2004, “ Low-Temperature Al2O3 Atomic Layer Deposition,” Chem. Mater., 16(4), pp. 639–645.
Scarel, G. , Ferrari, S. , Spiga, S. , Wiemer, C. , Tallarida, G. , and Fanciulli, M. , 2003, “ Effects of Growth Temperature on the Properties of Atomic Layer Deposition Grown ZrO2 Films,” J. Vac. Sci. Technol. A, 21(4), pp. 1359–1365.
Hsueh, Y. C. , Wang, C. C. , Kei, C. C. , Lin, Y. H. , Liu, C. , and Perng, T. P. , 2012, “ Fabrication of Catalyst by Atomic Layer Deposition for High Specific Power Density Proton Exchange Membrane Fuel Cells,” J. Catal., 294, pp. 63–68.
Narayan, R. J. , Adiga, S. P. , Pellin, M. J. , Curtiss, L. A. , Hryn, A. J. , Stafslien, S. , Chisholm, B. , Shih, C. C. , Shih, C. M. , Lin, S. J. , Su, Y. Y. , Jin, C. M. , Zhang, J. P. , Monteiro-Riviere, N. A. , and Elam, J. W. , 2010, “ Atomic Layer Deposition-Based Functionalization of Materials for Medical and Environmental Health Applications,” Philos. Trans. R. Soc. A, 368(1917), pp. 2033–2064.
Niu, W. , Li, X. , Karuturi, S. K. , Fam, D. W. , Fan, H. , Shrestha, S. , Wong, L. H. , and Tok, A. I. Y. , 2015, “ Applications of Atomic Layer Deposition in Solar Cells,” Nanotechnology, 26(6), p. 064001. [PubMed]
Shu, T. , Liao, S. J. , Hsieh, C. T. , Roy, A. K. , Liu, Y. Y. , Tzou, D. Y. , and Chen, W. Y. , 2012, “ Fabrication of Platinum Electrocatalysts on Carbon Nanotubes Using Atomic Layer Deposition for Proton Exchange Membrane Fuel Cells,” Electrochim. Acta, 75(40), pp. 101–107.
Skoog, S. A. , Elam, J. W. , and Narayan, R. J. , 2013, “ Atomic Layer Deposition: Medical and Biological Applications,” Int. Mater. Rev., 58(2), pp. 113–129.
Yu, M. P. , Yuan, W. J. , Li, C. , Hong, J. D. , and Shi, G. Q. , 2014, “ Performance Enhancement of a Graphene-Sulfur Composite as a Lithium-Sulfur Battery Electrode by Coating With an Ultrathin Al2O3 Film Via Atomic Layer Deposition,” J. Mater. Chem. A, 2(20), pp. 7360–7366.
Pan, D. , Ma, L. , Xie, Y. , Jen, T. C. , and Yuan, C. , 2015, “ On the Physical and Chemical Details of Alumina Atomic Layer Deposition: A Combined Experimental and Numerical Approach,” J. Vac. Sci. Technol. A, 33(2), p. 021511.
Pan, D. Q. , Li, T. , Jen, T. C. , and Yuan, C. , 2014, “ Numerical Modeling of Carrier Gas Flow in Atomic Layer Deposition Vacuum Reactor: A Comparative Study of Lattice Boltzmann Models,” J. Vac. Sci. Technol. A, 32(1), p. 01A110.
Xie, Y. , Ma, L. , Pan, D. , and Yuan, C. , 2015, “ Mechanistic Modeling of Atomic Layer Deposition of Alumina Process With Detailed Surface Chemical Kinetics,” Chem. Eng. J., 259, pp. 213–220.
Pan, D. , Ma, L. , Xie, Y. , Wang, F. , Jen, T.-C. , and Yuan, C. , 2015, “ Experimental and Numerical Investigations Into the Transient Multi-Wafer Batch Atomic Layer Deposition Process With Vertical and Horizontal Wafer Arrangements,” Int. J. Heat Mass Transfer, 91, pp. 416–427.
Yuan, C. Y. , and Dornfeld, D. , 2008, “ Environmental Performance Characterization of Atomic Layer Deposition,” IEEE International Symposium on Electronics and the Environment, May 19–22.
Yuan, C. Y. , and Dornfeld, D. A. , 2010, “ Integrated Sustainability Analysis of Atomic Layer Deposition for Microelectronics Manufacturing,” ASME J. Manuf. Sci. Eng., 132(3), p. 030918.
Ma, L. , Pan, D. , Xie, Y. , and Yuan, C. , 2015, “ Atomic Layer Deposition of Al2O3 Process Emissions,” RSC Adv., 5(17), pp. 12824–12829.
Remmers, E. M. , Travis, C. D. , and Adomaitis, R. A. , 2015, “ Reaction Factorization for the Dynamic Analysis of Atomic Layer Deposition Kinetics,” Chem. Eng. Sci., 127, pp. 374–391.
Widjaja, Y. , and Musgrave, C. B. , 2002, “ Quantum Chemical Study of the Mechanism of Aluminum Oxide Atomic Layer Deposition,” Appl. Phys. Lett., 80(18), pp. 3304–3306.
Halls, M. D. , and Raghavachari, K. , 2004, “ Atomic Layer Deposition Growth Reactions of Al2O3 on Si(100)-2 x 1,” J. Phys. Chem. B, 108(13), pp. 4058–4062.
Elliott, S. D. , and Greer, J. C. , 2004, “ Simulating the Atomic Layer Deposition of Alumina From First Principles,” J. Mater. Chem., 14(21), pp. 3246–3250.
Delabie, A. , Sioncke, S. , Rip, J. , Van Elshocht, S. , Pourtois, G. , Mueller, M. , Beckhoff, B. , and Pierloot, K. , 2012, “ Reaction Mechanisms for Atomic Layer Deposition of Aluminum Oxide on Semiconductor Substrates,” J. Vac. Sci. Technol. A, 30(1), p. 01A127.
Hass, K. C. , Schneider, W. F. , Curioni, A. , and Andreoni, W. , 1998, “ The Chemistry of Water on Alumina Surfaces: Reaction Dynamics From First Principles,” Science, 282(5387), pp. 265–268. [PubMed]
Halls, M. D. , and Raghavachari, K. , 2003, “ Atomic Layer Deposition of Al2O3 on H-Passivated Si—I: Initial Surface Reaction Pathways With H/Si(100)-2X1,” J. Chem. Phys., 118(22), pp. 10221–10226.
Steinfeld, J. I. , Francisco, J. S. , and Hase, W. L. , 1999, Chemical Kinetics and Dynamics, Prentice Hall, Upper Saddle River, NJ.
Atkins, P. , and de Paula, J. , 2011, Physical Chemistry for the Life Sciences, W. H. Freeman, New York.
Chang, R. , 2005, Physical Chemistry for the Biosciences, University Science Books, Sausalito, CA.
Davis, M. E. , and Davis, R. J. , 2012, Fundamentals of Chemical Reaction Engineering, Dover Publications, New York.
Tompkins, H. , and Irene, E. A. , 2005, Handbook of Ellipsometry, Elsevier Science, Amsterdam, The Netherlands.
View article in PDF format.

## References

George, S. M. , 2010, “ Atomic Layer Deposition: An Overview,” Chem. Rev., 110(1), pp. 111–131. [PubMed]
Groner, M. D. , Fabreguette, F. H. , Elam, J. W. , and George, S. M. , 2004, “ Low-Temperature Al2O3 Atomic Layer Deposition,” Chem. Mater., 16(4), pp. 639–645.
Scarel, G. , Ferrari, S. , Spiga, S. , Wiemer, C. , Tallarida, G. , and Fanciulli, M. , 2003, “ Effects of Growth Temperature on the Properties of Atomic Layer Deposition Grown ZrO2 Films,” J. Vac. Sci. Technol. A, 21(4), pp. 1359–1365.
Hsueh, Y. C. , Wang, C. C. , Kei, C. C. , Lin, Y. H. , Liu, C. , and Perng, T. P. , 2012, “ Fabrication of Catalyst by Atomic Layer Deposition for High Specific Power Density Proton Exchange Membrane Fuel Cells,” J. Catal., 294, pp. 63–68.
Narayan, R. J. , Adiga, S. P. , Pellin, M. J. , Curtiss, L. A. , Hryn, A. J. , Stafslien, S. , Chisholm, B. , Shih, C. C. , Shih, C. M. , Lin, S. J. , Su, Y. Y. , Jin, C. M. , Zhang, J. P. , Monteiro-Riviere, N. A. , and Elam, J. W. , 2010, “ Atomic Layer Deposition-Based Functionalization of Materials for Medical and Environmental Health Applications,” Philos. Trans. R. Soc. A, 368(1917), pp. 2033–2064.
Niu, W. , Li, X. , Karuturi, S. K. , Fam, D. W. , Fan, H. , Shrestha, S. , Wong, L. H. , and Tok, A. I. Y. , 2015, “ Applications of Atomic Layer Deposition in Solar Cells,” Nanotechnology, 26(6), p. 064001. [PubMed]
Shu, T. , Liao, S. J. , Hsieh, C. T. , Roy, A. K. , Liu, Y. Y. , Tzou, D. Y. , and Chen, W. Y. , 2012, “ Fabrication of Platinum Electrocatalysts on Carbon Nanotubes Using Atomic Layer Deposition for Proton Exchange Membrane Fuel Cells,” Electrochim. Acta, 75(40), pp. 101–107.
Skoog, S. A. , Elam, J. W. , and Narayan, R. J. , 2013, “ Atomic Layer Deposition: Medical and Biological Applications,” Int. Mater. Rev., 58(2), pp. 113–129.
Yu, M. P. , Yuan, W. J. , Li, C. , Hong, J. D. , and Shi, G. Q. , 2014, “ Performance Enhancement of a Graphene-Sulfur Composite as a Lithium-Sulfur Battery Electrode by Coating With an Ultrathin Al2O3 Film Via Atomic Layer Deposition,” J. Mater. Chem. A, 2(20), pp. 7360–7366.
Pan, D. , Ma, L. , Xie, Y. , Jen, T. C. , and Yuan, C. , 2015, “ On the Physical and Chemical Details of Alumina Atomic Layer Deposition: A Combined Experimental and Numerical Approach,” J. Vac. Sci. Technol. A, 33(2), p. 021511.
Pan, D. Q. , Li, T. , Jen, T. C. , and Yuan, C. , 2014, “ Numerical Modeling of Carrier Gas Flow in Atomic Layer Deposition Vacuum Reactor: A Comparative Study of Lattice Boltzmann Models,” J. Vac. Sci. Technol. A, 32(1), p. 01A110.
Xie, Y. , Ma, L. , Pan, D. , and Yuan, C. , 2015, “ Mechanistic Modeling of Atomic Layer Deposition of Alumina Process With Detailed Surface Chemical Kinetics,” Chem. Eng. J., 259, pp. 213–220.
Pan, D. , Ma, L. , Xie, Y. , Wang, F. , Jen, T.-C. , and Yuan, C. , 2015, “ Experimental and Numerical Investigations Into the Transient Multi-Wafer Batch Atomic Layer Deposition Process With Vertical and Horizontal Wafer Arrangements,” Int. J. Heat Mass Transfer, 91, pp. 416–427.
Yuan, C. Y. , and Dornfeld, D. , 2008, “ Environmental Performance Characterization of Atomic Layer Deposition,” IEEE International Symposium on Electronics and the Environment, May 19–22.
Yuan, C. Y. , and Dornfeld, D. A. , 2010, “ Integrated Sustainability Analysis of Atomic Layer Deposition for Microelectronics Manufacturing,” ASME J. Manuf. Sci. Eng., 132(3), p. 030918.
Ma, L. , Pan, D. , Xie, Y. , and Yuan, C. , 2015, “ Atomic Layer Deposition of Al2O3 Process Emissions,” RSC Adv., 5(17), pp. 12824–12829.
Remmers, E. M. , Travis, C. D. , and Adomaitis, R. A. , 2015, “ Reaction Factorization for the Dynamic Analysis of Atomic Layer Deposition Kinetics,” Chem. Eng. Sci., 127, pp. 374–391.
Widjaja, Y. , and Musgrave, C. B. , 2002, “ Quantum Chemical Study of the Mechanism of Aluminum Oxide Atomic Layer Deposition,” Appl. Phys. Lett., 80(18), pp. 3304–3306.
Halls, M. D. , and Raghavachari, K. , 2004, “ Atomic Layer Deposition Growth Reactions of Al2O3 on Si(100)-2 x 1,” J. Phys. Chem. B, 108(13), pp. 4058–4062.
Elliott, S. D. , and Greer, J. C. , 2004, “ Simulating the Atomic Layer Deposition of Alumina From First Principles,” J. Mater. Chem., 14(21), pp. 3246–3250.
Delabie, A. , Sioncke, S. , Rip, J. , Van Elshocht, S. , Pourtois, G. , Mueller, M. , Beckhoff, B. , and Pierloot, K. , 2012, “ Reaction Mechanisms for Atomic Layer Deposition of Aluminum Oxide on Semiconductor Substrates,” J. Vac. Sci. Technol. A, 30(1), p. 01A127.
Hass, K. C. , Schneider, W. F. , Curioni, A. , and Andreoni, W. , 1998, “ The Chemistry of Water on Alumina Surfaces: Reaction Dynamics From First Principles,” Science, 282(5387), pp. 265–268. [PubMed]
Halls, M. D. , and Raghavachari, K. , 2003, “ Atomic Layer Deposition of Al2O3 on H-Passivated Si—I: Initial Surface Reaction Pathways With H/Si(100)-2X1,” J. Chem. Phys., 118(22), pp. 10221–10226.
Steinfeld, J. I. , Francisco, J. S. , and Hase, W. L. , 1999, Chemical Kinetics and Dynamics, Prentice Hall, Upper Saddle River, NJ.
Atkins, P. , and de Paula, J. , 2011, Physical Chemistry for the Life Sciences, W. H. Freeman, New York.
Chang, R. , 2005, Physical Chemistry for the Biosciences, University Science Books, Sausalito, CA.
Davis, M. E. , and Davis, R. J. , 2012, Fundamentals of Chemical Reaction Engineering, Dover Publications, New York.
Tompkins, H. , and Irene, E. A. , 2005, Handbook of Ellipsometry, Elsevier Science, Amsterdam, The Netherlands.

## Figures

Fig. 5

Contour plots of surface coverage and precursor distributions in the entire ALD system: (a) 0.02 s at the end of TMA pulse and (b) 10.04 s at the end of water pulse

Fig. 1

Experimental ALD system with residual gas analyzer (RGA) to characterize the methane emissions

Fig. 2

Contour plots of gaseous species distributions and the bulk species deposition rates: (a) 0.02 s at the end of TMA pulse and (b) 10.04 s at the end of water pulse

Fig. 3

Gaseous species distributions during the full Al2O3 ALD cycle

Fig. 4

Surface coverage for the main surface species during the full ALD cycle

Fig. 6

Correlation of the bulk species deposition rate and precursors concentration during the ALD cycle

Fig. 9

Effects of purge time on the process wastes and emissions: (a) precursor dosage, precursor wastes, and methane emissions and (b) film growth rate and precursor waste rate

Fig. 10

Effects of carrier gas flow rate on the process wastes and emissions: (a) precursor dosage, precursor wastes, and methane emissions and (b) film growth rate and precursor waste rate

Fig. 7

Effects of chamber temperatures on the process wastes and emissions: (a) precursor dosage, precursor wastes, and methane emissions and (b) film growth rate and precursor waste rate

Fig. 8

Effects of pulse time on the process wastes and emissions: (a) precursor dosage, precursor wastes, and methane emissions and (b) film growth rate and precursor waste rate

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