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Article

Effects of Plasma Power on By-Product Gas Formation from CHF3 and CH2F2 Process Gases in Semiconductor Etching Processes

1
Department of Statistics, Duksung Women’s University, Seoul 01369, Republic of Korea
2
Climate Change & Environment Research Center, Sejong University, Seoul 05006, Republic of Korea
3
Department of Climate and Energy, Sejong University, Seoul 05006, Republic of Korea
4
Korea Testing & Research Institute (KTR), Gwacheon-si 13810, Republic of Korea
5
Department of Climate and Environment, Sejong University, Seoul 05006, Republic of Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(22), 12296; https://doi.org/10.3390/app152212296
Submission received: 7 October 2025 / Revised: 8 November 2025 / Accepted: 12 November 2025 / Published: 19 November 2025
(This article belongs to the Section Environmental Sciences)

Abstract

In semiconductor manufacturing, fluorinated gases such as CHF3 and CH2F2 are widely used as process gases for plasma etching and cleaning. However, their decomposition within the plasma environment leads to the formation of secondary fluorinated by-products with high global warming potential (GWP). Understanding how plasma intensity affects the generation characteristics of these by-products under realistic process conditions is essential for developing country-specific emission factors and improving inventory accuracy. This study analyzes the by-product formation behavior of CHF3 and CH2F2 under three plasma power conditions (500 W, 600 W, and 700 W), based on process data representative of domestic semiconductor facilities. The quantitative analysis revealed distinct reaction trends between the two gas systems. In the CHF3 process, a reaction-pathway bifurcation was observed at 700 W, where the formation of high-GWP perfluorocarbons (PFCs, e.g., CF4, C2F6) decreased, while the production of low-GWP fluorinated compounds such as C4F6 increased, resulting in an overall 18% reduction in CO2eq. emissions. Conversely, CH2F2 showed a continuous increase in fluoromethane (CH3F) generation with higher plasma power due to the higher hydrogen content in its molecular structure, leading to an 18.4% net reduction in total GWP emissions. These results provide scientific evidence for understanding the relationship between plasma intensity and by-product formation in fluorinated gas systems under conditions relevant to the Korean semiconductor industry, and offer a foundation for improving national F-gas emission factor development.

1. Introduction

1.1. Research Background

The remarkable advancement of the modern semiconductor industry has been driven by technologies capable of reducing circuit linewidths to nanometer scales. The core technology for precisely implementing such fine patterns on wafers is plasma-enhanced dry etching processes. Various fluorocarbon gases are employed in these processes, with trifluoromethane (CHF3) and difluoromethane (CH2F2) being the most representative process gases.
CHF3 is primarily used for selective etching of dielectric films such as silicon dioxide (SiO2) and silicon nitride (Si3N4) [1,2]. CHF3 plasma excels in forming polymer layers on wafer surfaces during the etching process, serving as protective films to achieve high aspect ratio vertical etch profiles. In comparison, CH2F2, with its high hydrogen content plays a unique role in controlling chemical reactions within the plasma and is utilized in various etching and deposition processes [3,4]. This difference between these gases stems primarily from the fluorine (F) to hydrogen (H) ratio within the molecules. CHF3 is fluorine-rich (F/H ratio = 3), while CH2F2 is hydrogen-rich (F/H ratio = 1), where hydrogen atoms (H•) generated in the plasma act as fluorine radical (F•) scavengers, fundamentally altering plasma chemistry [5,6]. Owing to these distinct chemical characteristics, several studies have investigated process gas plasma behaviors under different process conditions.
Previous studies on CHF3 and CH2F2 plasma processes have mainly investigated etching performance and plasma stability by adjusting parameters such as gas composition, input power, and pressure [7,8,9]. Several works employing diagnostic tools such as Fourier Transform Infrared Spectroscopy (FTIR) have also examined how variations in plasma power and oxygen addition change the chemical composition of exhaust gases [10,11]. However, only a limited number of studies have specifically focused on by-product formation from CHF3 and CH2F2 plasmas, particularly in relation to differences in plasma power. The present study addresses this aspect by analyzing how changes in plasma intensity lead to differences in by-product formation characteristics between the two fluorinated gas systems under practical semiconductor process conditions. The present study investigates how changes in plasma intensity lead to differences in by-product formation characteristics between the two fluorinated gas systems under practical semiconductor process conditions in Korea. Moreover, this analysis has significance not only for process optimization but also for understanding the environmental implications of plasma power variation.
Beyond their technical importance in semiconductor etching, both CHF3 and CH2F2 are environmentally critical gases. CHF3 itself is a potent greenhouse gas with a 100-year Global Warming Potential (GWP) of 14,600, while CH2F2 has a lower but still significant GWP of 771 (IPCC AR6). During plasma processing, incomplete dissociation of these gases or recombination among reactive radicals often generates high-GWP perfluorocarbons (PFCs) such as CF4, C2F6, and c-C4F8. These by-products are extremely stable, with atmospheric lifetimes ranging from hundreds to thousands of years, and they accumulate persistently in the atmosphere. As a result, the semiconductor and display industries have been recognized as major contributors to indirect emissions of fluorinated greenhouse gases.
Accurate quantification of by-product gas emission factors for CHF3 and CH2F2 is therefore essential for establishing a reliable greenhouse-gas inventory. To ensure accurate emission estimation, it is necessary to develop emission factors that reflect domestic process characteristics. This study provides a fundamental basis for such development by deriving plasma power–specific emission factors for two gases that are widely used in semiconductor manufacturing in Korea.

1.2. Environmental Necessity and Research Relevance

The widespread use of fluorocarbon gases causes serious environmental problems [12,13,14,15]. Unreacted process gases emitted during processing and various by-product gases generated by high-energy plasma are often potent greenhouse gases. Particularly, perfluorocarbon (PFC) by-products such as carbon tetrafluoride (CF4), hexafluoroethane (C2F6), and octafluorocyclobutane (c-C4F8) are subject to strict regulation under international environmental treaties such as the Kyoto Protocol [16].
The severity of these gases is clearly demonstrated through their global warming potential (GWP) values, which indicate greenhouse effects relative to carbon dioxide (CO2). For example, on a 100-year basis, CHF3 has a GWP of approximately 14,600, while CF4 has a GWP of approximately 7350 [17]. This means that 1 kg of these gases emitted into the atmosphere causes the same greenhouse effect as 14.6 tons and 7.35 tons of CO2, respectively.

1.3. Research Objectives

This study aims to rigorously compare and analyze how plasma power, a core variable in semiconductor etching processes, affects by-product gas formation from two important injection gases, CHF3 and CH2F2, based on empirically collected data. Specific research objectives were established as follows:
  • To quantitatively measure and compare profiles of major by-product gases emitted from each gas system under three plasma power conditions: 500 W, 600 W, and 700 W;
  • To elucidate dominant reaction mechanisms according to the different levels of plasma power based on observed emission changes, particularly clarifying the point where reaction pathways bifurcate between the two chemical systems;
  • To calculate CO2eq. indices representing the overall greenhouse effect of each process condition using volume ratios of all emission gases and established GWP values for quantitative environmental impact assessment; and
  • To analyze complex interrelationships among process efficiency, stability, and environmental burden and propose optimal process operation strategies for sustainable semiconductor manufacturing

2. Experimental Methods and Analysis

2.1. Experimental Equipment and Conditions

This study was conducted using CHF3 and CH2F2 plasma process data collected from a Quadrupole mass spectrometer (QMS) and Fourier transform infrared spectrometer (FTIR) equipment at existing semiconductor manufacturing facilities. The rate of by-product gas generation used in our analysis was measured in accordance with the Korean Industrial Standard KS I 0587 (Measurement Method for Volumetric Flow Rate of Non-CO2 Greenhouse Gases (CF4, NF3, SF6, N2O) Used in Semiconductor and Display Processes) and ES 13501 (N2O, HFCs, PFCs, SF6, NF3 of Greenhouse Gas in Industrial Process) [18,19]. The main specifications of the equipment used are provided in Table 1. To ensure the measurement accuracy and reproducibility of both instruments, the QMS (isepa-S, EL, Daejeon, Republic of Korea) and FTIR (DX4000, Gasmet, Vantaa, Finland) were calibrated before each measurement cycle in accordance with the manufacturers’ procedures. For the QMS, the detection limit was 5 ppm ± 3% per 1 amu, which ensured sufficient sensitivity for trace-level gas analysis. Calibration was conducted on-site using a certified standard gas (1% Kr, 99.999%) as a tracer gas, introduced through a mass flow controller (M3030V, LINE TECH, Daejeon, Republic of Korea). Five calibration points were established from a 2.01% Kr-mixed gas, and each point was determined by averaging at least 20 measurement data values. The calibration curve exhibited a coefficient of determination (R2) of 0.98 or higher, and the relative error for five repeated measurements of each concentration used in the calibration curve was verified to be within ±5%. For the FTIR, the system was equipped with a DLATGS detector and a ZnSe beamsplitter, and operated under a constant cell and sample pump temperature of 180 °C to prevent condensation and maintain stable signal intensity. Linearity verification using CHF3 and CH2F2 gases across five concentration levels yielded R2 = 0.9999, confirming excellent detection sensitivity and reproducibility. Each concentration level was measured at least five times, and the mean value was used for the final analysis.
The plasma power was configured under three operating conditions, namely 500 W, 600 W, and 700 W. The plasma power range of 500–700 W was selected to reflect the actual operating conditions commonly applied in semiconductor etching and cleaning processes in Korea. This range represents the typical power window used in domestic manufacturing facilities for both CHF3- and CH2F2-based plasma systems, ensuring realistic representation of by-product formation characteristics. The rate of by-product gas generation emitted under each condition was measured through continuous monitoring for one hour. Gas composition data were collected at 1 s intervals throughout the entire process period to ensure comprehensive temporal analysis and statistical reliability.

2.2. Target Gases for Analysis

The process gases used in this study were CHF3 and CH2F2. During plasma reactions, these process gases underwent decomposition and recombination, leading to the formation of various by-products. The analyzed gas species included unreacted process gases (CHF3, CH2F2), perfluorocarbons (CF4, C2F6, c-C4F8), unsaturated fluorocarbons (C4F6), hydrogen-containing by-products (CH3F), and other compounds such as HF, CO, and CO2. For each plasma power condition, the Rate of by-product gas generation was quantified to evaluate the formation characteristics of these gases under different process settings.

2.3. Environmental Impact Assessment Method

To quantitatively assess the environmental impact of each process condition, a ‘Relative Environmental Impact Index (REII)’ is introduced. REII is calculated by the following Equation (1).
R E I I = ( V R g a s × G W P g a s )
For calculation of REII, we used 100-year Global Warming Potential (GWP) values from the IPCC Sixth Assessment Report (AR6) [17], as it provides the most recent and internationally recognized dataset. The AR6 values incorporate updated information on radiative efficiencies and atmospheric lifetimes of greenhouse gases, ensuring improved accuracy and consistency in the quantitative environmental impact assessment.

2.4. Statistical Analysis

Statistical analyses were conducted using Python 3.11 with the following major libraries: pandas 2.2.2, statsmodels 0.14.2, and SPSS Statistics version 28.0 (IBM Corp., Armonk, NY, USA). All experimental measurements were performed in triplicate for each process condition to ensure reproducibility. Data are presented as mean ± standard deviation (SD) throughout this study.
To evaluate the effects of plasma power on by-product gas formation, one-way analysis of variance (ANOVA) was performed with plasma power (500 W, 600 W, 700 W) as the independent variable and gas concentration as the dependent variable. The homogeneity of variances was tested using Levene’s test prior to ANOVA. When significant differences were detected (p < 0.05), Tukey’s honestly significant difference (HSD) post hoc test was applied for pairwise comparisons between power levels. The coefficient of variation (CV%) was calculated as (SD/mean) × 100 to assess measurement precision and process stability. Statistical significance was set at p < 0.05 for all analyses, with p < 0.01 considered highly significant and p < 0.001 considered extremely significant. All p-values reported are two-tailed.

3. Results and Discussion

3.1. Comparison of By-Product Gas Profiles by the Level of Plasma Power

3.1.1. Process Gas Dissociation Kinetics

Plasma power is the primary variable directly determining process gas dissociation efficiency, with dissociation rates improving as power increases in both CH2F2 and CHF3 produced in the process increasing with higher power [20,21]. In the CH2F2 process, the rate of by-product gas generation of unreacted CH2F2 decreased from 0.170 ± 0.008 at 500 W to 0.147 ± 0.006 at 700 W, corresponding to an approximately 13.7% reduction (p < 0.01). Notably, the reduction rate accelerated to 10.8% when increasing plasma power from 600 W to 700 W. Similarly, in the CHF3 process, the average rate of by-product gas generation of unreacted CHF3 decreased from 0.347 ± 0.015 at 500 W to 0.284 ± 0.012 at 700 W, representing an approximately 18.1% reduction (p < 0.001). These results indicate an increase in the dissociation rate from 65.3% at 500 W to 71.6% at 700 W. A detailed comparison of process gas dissociation rates under different plasma power conditions is provided in Table 2.

3.1.2. Perfluorocarbon (PFC) Formation Trends

Formation trends of representative PFC by-products gas with very high GWP (CF4, C2F6, and c-C4F8) exhibited fundamental differences between the two plasma systems. In the CH2F2 process, CF4 emission showed a stable pattern with minimal influence from plasma power changes (0.082 ± 0.004). However, C2F6 decreased from 0.004 ± 0.0002 to 0.0035 ± 0.0002, and c-C4F8 decreased from 0.044 ± 0.002 to 0.039 ± 0.002 with increasing power. In the CHF3 process, CF4 and c-C4F8 emissions maintained high levels at 500 W and 600 W but showed distinct nonlinear decreases of 20.0% and 18.4%, respectively, at 700 W. C2F6 remained relatively stable under all plasma power conditions, as summarized in Table 3.

3.1.3. Unsaturated and Hydrogen-Containing By-Product Behavior

The behavior of unsaturated and hydrogen-containing by-products exhibited distinct trends depending on the process gas used. For C4F6 emission, the CH2F2 process showed a significant decrease in the rate of by-product gas generation from 0.00052 ± 0.00003 to 0.00033 ± 0.00002 with increasing plasma power, corresponding to a 36.5% reduction (p < 0.01). In contrast, the CHF3 process displayed the most dramatic variation: while the rate of by-product gas generation remained minimal at 0.00008 ± 0.00001 at 500 W and 600 W, it increased more than 20-fold to 0.0016 ± 0.0001 at 700 W (p < 0.001). For CH3F emission, different trends were observed. In the CH2F2 process, CH3F was the only by-product that steadily increased with plasma power, with the rate of by-product gas generation rising from 0.0495 ± 0.0025 to 0.0554 ± 0.0028 (11.9% increase, p < 0.05). By contrast, in the CHF3 process, CH3F was barely generated, with levels remaining below 0.001, as shown in Table 4. Detailed temporal stability data and statistical analysis results are provided in Appendix A and Appendix B.

3.2. Reaction Mechanism Elucidation

3.2.1. CHF3 Plasma: Reaction Pathway Bifurcation at High Power

A key observation from the CHF3 process data is the change in chemical reaction pathways under the 700 W condition, which represents a case of ‘mechanism bifurcation’. This transition is fundamentally consistent with established plasma dissociation kinetics, where increased power enhances electron energy and density [21,22,23]. Table 5 summarizes the reactions associated with low to medium power conditions (500–600 W). The dominant pathway involves process gas dissociation, followed by carbon radical formation and subsequent perfluorocarbon (PFC) recombination. This sequence of reactions—process gas dissociation, carbon radical formation, and PFC recombination—is illustrated in Equations (2)–(6) and further includes the polymerization for c-C4F8 formation, a key high-GWP by-product [24,25,26].
At high power (700 W), the increased energy promotes secondary dissociation reactions that re-dissociate even previously formed stable PFC by-products as detailed in Table 6. This high-power phenomenon, the re-dissociation of primary, stable by-products, is a known characteristic of high-density plasma regimes, which fundamentally adheres to the principles of fluorocarbon etching chemistry [27,28,29,30]. These reactions include both secondary dissociation and polymerization processes, as illustrated in Equations (7)–(10). Consequently, CHF3 plasma undergoes a major pathway transition from PFC-centered reactions to low-GWP polymerization compound formation-centered reactions at 700 W.

3.2.2. CH2F2 Plasma: Role of Hydrogen and CH3F Formation

The behavior of the CH2F2 system is determined by another key factor, the role of hydrogen. The phenomenon in which CH3F formation continuously increases with plasma power clearly demonstrates the unique chemical characteristics of CH2F2 plasma. The underlying reason for this behavior is the difference in the H:C ratio between the process gases (CH2F2: 2:1, CHF3: 1:1). The detailed reaction pathways for radical formation and subsequent CHF3 generation are summarized in Table 7 and illustrated in Equations (11)–(14).
CH3F formation mainly results from recombination reactions between methyl radicals (CH3•) and fluorine atoms (F•). This pathway is less favorable in CHF3 plasma, which lacks sufficient hydrogen sources to generate CH3• radicals [15,27]. Trace c-C4F8 detected in the CH2F2 process is likely formed through limited CF2-radical recombination, similar to the minor polymerization–cyclization pathway observed in the CHF3 system [31,32,33].

3.3. Environmental Impact Assessment

3.3.1. Relative Environmental Impact Index (REII) Analysis

The results of the REII under different plasma power conditions are compared in Table 8. Analysis results show that the total REII value of the CHF3 process significantly decreases with increasing plasma power. The 700 W condition achieved approximately 18.2% reduction in total CO2eq. emissions compared to the 500 W condition. This is because high power conditions (700 W) effectively reduce emissions of high-GWP unreacted CHF3, CF4, and c-C4F8, while the increase in essentially GWP-free C4F6 has minimal impact on overall environmental burden. Conversely, the CH2F2 process showed relatively limited environmental impact improvement with increasing plasma power (5.4% reduction). This suggests that the by-product gas profile of the CH2F2 process is less sensitive to plasma power changes, compared to the CHF3 process.

3.3.2. Process Stability Assessment

Process stability assessment results using the coefficient of variation are presented in Table 9. The CHF3 process showed the highest coefficient of variation under 700 W conditions, indicating process instability due to reaction pathway bifurcation phenomena occurring at high power.

3.3.3. Optimization Trade-Offs: Efficiency, Stability, and Environmental Burden

The results of this study together indicate that optimization of CHF3 plasma etching process involves complex trade-offs among efficiency, stability, and environmental burden, making simultaneous optimization impossible. In terms of efficiency (throughput), the 700 W condition is optimal, as it provides the highest process gas dissociation rate. Regarding environmental impact (low emissions), the 700 W condition is also favorable, since it yields the lowest total REII value. However, when considering process stability (reproducibility), the 600 W condition proves to be the most stable due to the lowest process variability coefficient, while the 700 W condition is the least stable. Therefore, no single absolute optimal condition exists, and the choice of operating conditions should depend on the specific objectives and priorities of the manufacturing facility.

3.4. Process Optimization and Environmental Strategies

3.4.1. Process-Specific Optimization Strategies

For the CHF3 process, optimization strategies vary according to application requirements. In regions with strict environmental regulations, high-power operation at 700 W is preferable to minimize greenhouse gas emissions. For high-volume production, a 600 W condition provides a practical balance between stability and efficiency. In the R&D stage, low-power operation at 500 W followed by a gradual increase is recommended to optimize process parameters.
In the case of the CH2F2 process, the system exhibits stable behavior in general, allowing flexible power selection depending on process objectives. When the minimization of CH3F formation is prioritized, low-power operation at 500 W is optimal, whereas high-power operation at 700 W is advantageous when maximizing process gas dissociation efficiency is required.

3.4.2. Environmental Management Strategies

Environmental management strategies for plasma etching processes can be structured around three key approaches. First, the construction of a real-time monitoring system enables environmental impact prediction by continuously tracking the composition of by-product gases. Second, adaptive process control allows dynamic power adjustment in response to changes in environmental regulations. Finally, by-product gas treatment system optimization involves the development of customized treatment technologies tailored to the specific characteristics of each by-product gas.

4. Conclusions and Future Research

4.1. Key Findings

This study comprehensively compared and analyzed the effects of plasma power on by-product gas formation from CHF3 and CH2F2 injection gases in semiconductor etching processes. The results show that the two plasma systems respond fundamentally differently to power increases. Our key findings are as follows: (i) the identification of the CHF3 plasma mechanism bifurcation, a phenomenon where traditional pathways generating high-GWP PFCs bifurcate into pathways primarily producing unsaturated compounds such as C4F6 with essentially no GWP at high power (700 W); (ii) paradoxical environmental improvement, quantitatively demonstrating that increasing plasma power actually reduces total greenhouse gas emissions by up to 18.2%; (iii) the hydrogen-dominated chemistry of CH2F2 plasma, elucidating unique chemical reaction mechanisms in which CH3F formation increases at high power due to the abundant hydrogen content in the process gas; and (iv) the process optimization triple dilemma, quantifying the complex trade-offs among efficiency, stability, and environmental burden, and emphasizing the importance of situational strategic selection rather than absolute optimization.

4.2. Academic and Practical Implications

This study provides several important academic contributions. First, it offers a novel reaction mechanism elucidated through the first systematic analysis of reaction pathway bifurcation phenomena occurring in CHF3 plasma under high power conditions. Second, it presents a quantitative environmental assessment methodology for plasma processes by introducing environmental impact quantification using the REII. Third, it delivers a comparative chemical analysis by elucidating, at the molecular level, the fundamental differences between the two gas systems.
This study also carries significant industrial implications. In the short term, the results demonstrate an immediately applicable potential for reducing greenhouse gas emissions by approximately 18% through high-power (700 W) operation in CHF3 processes. Also importantly, the findings provide a scientific foundation for establishing process-specific optimization strategies and offer data-driven decision support for achieving compliance with environmental regulations.
In the longer term, this work lays the foundation for the development of next-generation environmentally sustainable plasma process technologies. It also strengthens the proactive response capability of the semiconductor industry to increasingly stringent international environmental regulations and contributes to the construction of a sustainable semiconductor manufacturing ecosystem.

4.3. Research Limitations and Future Challenges

This study has some limitations that should be noted. First, all experiments were conducted under fixed conditions of temperature (25 °C) and pressure (50 mTorr), and the potential effects of varying these parameters were not considered. Second, although continuous monitoring was performed for one hour under each power condition, changes in by-product gas formation patterns over extended operation periods or across multiple process cycles were not analyzed. Third, the possible influence of actual wafer substrates on by-product gas formation was excluded from this study.
Future research directions can be structured into short-term, medium- to long-term, and long-term tasks. In the short term, further studies should focus on multivariate optimization to analyze the combined effects of variables such as temperature, pressure, and gas flow rate. In addition, the development of real-time diagnostic techniques for monitoring radical species in plasma, as well as investigations into by-product gas formation patterns under different substrate materials, will be essential.
In the medium to long term, research efforts should aim at developing machine learning–based prediction models capable of forecasting by-product gas profiles from process conditions. Exploration of environmentally sustainable alternative gases with low global warming potential to replace CHF3 and CH2F2 will also be crucial, alongside the establishment of integrated process design methodologies that simultaneously optimize etching performance and environmental impact.
Finally, the long-term vision involves the realization of zero-emission plasma processes through innovative technologies that fundamentally eliminate by-product gas emissions. Furthermore, advancing towards a circular economy in semiconductor manufacturing—where by-product gases are recycled into useful chemical feedstocks—will be an important goal for sustainable industry development.
To summarize, we emphasize that a deeper understanding of chemical reactions within plasma is a prerequisite for true process optimization. Particularly, the reaction pathway bifurcation phenomenon discovered in CHF3 processes suggests the necessity of nonlinear approaches beyond conventional linear thinking.
The future semiconductor manufacturing industry must meet the requirements of the ‘Green Moore’s Law’—making technological progress that exponentially reduces environmental burden while improving performance beyond Moore’s Law. We expect the scientific insights and methodologies presented in this study to serve as cornerstones for developing sustainable semiconductor manufacturing technologies responding to these challenges.

Author Contributions

All authors contributed to the research presented in this work. Their contributions are presented as follows. Conceptualization and writing—original draft, investigation, and formal analysis, D.K.M.; data curation, writing—review and editing, J.W.; writing—review and editing, J.L.; resources and funding acquisition, B.-J.L.; project administration and supervision, E.-c.J.; All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Korea Environment Industry & Technology Institute (KEITI) through “Climate Change R&D Project for New Climate Regime”, funded by Korea Ministry of Environment (MOE) (2022003560008).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A. Details of the Temporal Analysis Data

Table A1. Temporal Stability Analysis of CHF3 Process By-product Data.
Table A1. Temporal Stability Analysis of CHF3 Process By-product Data.
Time
Interval
PowerCF4C2F6c-C4F8C4F6
0–600 s500 W0.087 ± 0.0040.0042 ± 0.00020.051 ± 0.0030.00009 ± 0.00001
600–1200 s500 W0.084 ± 0.0040.0041 ± 0.00020.048 ± 0.0020.00008 ± 0.00001
1200–1800 s500 W0.083 ± 0.0030.0040 ± 0.00020.047 ± 0.0020.00007 ± 0.00001
1800–2400 s500 W0.086 ± 0.0040.0041 ± 0.00020.049 ± 0.0030.00008 ± 0.00001
2400–3000 s500 W0.085 ± 0.0040.0041 ± 0.00020.050 ± 0.0020.00008 ± 0.00001
3000–3600 s500 W0.085 ± 0.0030.0040 ± 0.00020.049 ± 0.0020.00008 ± 0.00001
Table A2. Temporal Stability Analysis of CH2F2 Process By-product Data.
Table A2. Temporal Stability Analysis of CH2F2 Process By-product Data.
Time
Interval
PowerCF4C2F6c-C4F8CH3F
0–600 s500 W0.084 ± 0.0040.0041 ± 0.00020.045 ± 0.0020.0488 ± 0.0025
600–1200 s500 W0.082 ± 0.0040.0040 ± 0.00020.044 ± 0.0020.0495 ± 0.0024
1200–1800 s500 W0.081 ± 0.0030.0039 ± 0.00020.043 ± 0.0020.0498 ± 0.0026
1800–2400 s500 W0.082 ± 0.0040.0040 ± 0.00020.044 ± 0.0020.0501 ± 0.0025
2400–3000 s500 W0.083 ± 0.0040.0040 ± 0.00020.044 ± 0.0020.0496 ± 0.0024
3000–3600 s500 W0.082 ± 0.0030.0040 ± 0.00020.044 ± 0.0020.0499 ± 0.0025
Note: Data represent mean ± standard deviation (n = 3) for each 10 min interval during 1 h continuous monitoring. Statistical analysis performed using one-way ANOVA with Tukey’s post hoc test.

Appendix B. Statistical Analysis Results

Table A3 presents the results of one-way ANOVA testing the null hypothesis that mean gas concentrations are equal across all three plasma power levels (500 W, 600 W, 700 W). The F-statistic was calculated as the ratio of between-group variance to within-group variance, with degrees of freedom df = (2, 6) for three groups with triplicate measurements. p-values were computed using the F-distribution, where p < 0.05 indicates statistically significant differences between power levels.
Table A3. One-way ANOVA Results for Power-dependent Changes.
Table A3. One-way ANOVA Results for Power-dependent Changes.
Gas TypeF-Valuep-ValueSignificanceEffect Size (η2)
CHF3
(unreacted)
15.23<0.001***0.741
CF48.940.003**0.598
C4F645.67<0.001***0.884
CH2F2
(unreacted)
12.87<0.001***0.692
CH3F7.330.007**0.523
Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
Table A4 shows pairwise comparisons using Tukey’s HSD test to identify which specific power levels differ significantly from each other. The test controls for Type I error rate across multiple comparisons. p-values are adjusted for multiple testing, with significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001. The standard error for each comparison was calculated as SE = √(MSE × (1/n1 + 1/n2)), where MSE is the mean square error from ANOVA and n is the sample size per group.
Table A4. Tukey Post Hoc Test Results for CHF3 Process.
Table A4. Tukey Post Hoc Test Results for CHF3 Process.
ComparisonCHF3 (Unreacted)CF4C4F6
500 W vs. 600 Wp = 0.045 *p = 0.892p = 0.967
500 W vs. 700 Wp < 0.001 ***p = 0.002 **p < 0.001 ***
600 W vs. 700 Wp = 0.008 **p = 0.003 **p < 0.001 ***
Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
Table A5. Tukey Post Hoc Test Results for CHF3 Process.
Table A5. Tukey Post Hoc Test Results for CHF3 Process.
Process ConditionOverall CV (%)Trend StabilityTemporal Drift
CHF3—500 W4.3 ± 0.2HighMinimal
CHF3—600 W4.1 ± 0.2HighMinimal
CHF3—700 W5.8 ± 0.4ModerateNotable
CH2F2—500 W4.7 ± 0.3HighMinimal
CH2F2—600 W4.5 ± 0.3HighMinimal
CH2F2—700 W4.9 ± 0.3HighMinimal

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Table 1. Specifications of the gas analysis system.
Table 1. Specifications of the gas analysis system.
CategoryContext
QMSModelisepa-S, EL, Korea
Flow rate range(0.01~5.0) L/min
mass range0 to 200 amu
FTIRModelDX4000, Gasmet, Finland
Wavenumber rangeFull Range: 200~1050 nm
Device operates4200–900 cm−1
Process time1 h (3600 s)
Table 2. Comparison of Process Gas Dissociation Rates.
Table 2. Comparison of Process Gas Dissociation Rates.
Process GasPlasma PowerTotal Reduction
500 W600 W700 W
CH2F20.170 ± 0.0080.165 ± 0.0070.147 ± 0.006−13.7%
CHF30.347 ± 0.0150.320 ± 0.0130.284 ± 0.012−18.1%
Table 3. Perfluorocarbon (PFC) Formation Trends.
Table 3. Perfluorocarbon (PFC) Formation Trends.
By-Product GasProcess GasRate of By-Product Gas Generation
by Plasma Power
Change Rate
500 W600 W700 W
CF4CH2F20.082 ± 0.0040.082 ± 0.0040.083 ± 0.004+1.2%
CHF30.085 ± 0.0040.085 ± 0.0040.068 ± 0.003−20.0% *
C2F6CH2F20.004 ± 0.00020.0038 ± 0.00020.0035 ± 0.0002−12.5%
CHF30.0041 ± 0.00020.0040 ± 0.00020.0041 ± 0.00020%
c-C4F8CH2F20.044 ± 0.0020.042 ± 0.0020.039 ± 0.002−11.4%
CHF30.049 ± 0.0020.048 ± 0.0020.040 ± 0.002−18.4% *
Note: * p < 0.05.
Table 4. Special By-product Formation Trends.
Table 4. Special By-product Formation Trends.
By-Product GasProcess GasRate of By-Product Gas Generation
by Plasma Power
Change Rate
500 W600 W700 W
C4F6CH2F20.00052 ± 0.000030.00043 ± 0.000020.00033 ± 0.00002−36.5% *
CHF30.00008 ± 0.000010.00009 ± 0.000010.0016 ± 0.0001+1900% **
CH3FCH2F20.0495 ± 0.00250.0520 ± 0.00260.0554 ± 0.0028+11.9% *
CHF3<0.001<0.001<0.001---
Note: * p < 0.05, ** p < 0.001.
Table 5. Reactions associated with CHF3 plasma under low to medium power conditions (500–600 W).
Table 5. Reactions associated with CHF3 plasma under low to medium power conditions (500–600 W).
ReactionEquation
CHF3 + e → CF3• + H• + e(2)
CHF3 + e → CF2• + HF + e(3)
CF3• + CF3• → C2F6(4)
CF2• + CF2• → C2F4 → CF4 + C(5)
2C2F4 → c-C4F8(6)
Table 6. Reactions associated with CHF3 plasma under high power conditions.
Table 6. Reactions associated with CHF3 plasma under high power conditions.
ReactionEquation
CF4 + e → CF2• + 2F• + e (secondary dissociation)(7)
c-C4F8 + e → 2C2F4 + e(8)
C2F4 + e → C2F2 + 2F• + e(9)
C2F2 + C2F4 → C4F6 (polymerization reaction)(10)
Table 7. Reactions associated with CH2F2 plasma under high power conditions.
Table 7. Reactions associated with CH2F2 plasma under high power conditions.
ReactionEquation
CH2F2 + e → CH2• + 2F• + e(11)
CH2F2 + e → CHF• + H• + F• + e(12)
CH2• + H• → CH3(13)
CH3• + F• → CH3F(14)
Table 8. Comparison of Relative Environmental Impact Index (REII) by Plasma Power.
Table 8. Comparison of Relative Environmental Impact Index (REII) by Plasma Power.
By-Product GasGWPCHF3 Process REIICH2F2 Process REII
500 W600 W700 W500 W600 W700 W
CF47350602.7602.7610.1624.8624.8499.8
C2F612,40049.647.143.450.849.650.8
c-C4F810,200448.8428.4397.8499.8489.6408.0
C4F6<10.050.040.030.0080.0090.16
CHF314,600---5066.24672.04146.4
CH2F2771131.1127.2113.3---
CH3F1356.77.07.5<0.1<0.1<0.1
Total REII1238.91212.51172.16241.65836.05105.2
Change RateBaseline−2.1%−5.4% *Baseline−6.5% *−18.2% **
Note: * p < 0.05, ** p < 0.001.
Table 9. Process Stability Assessment (Coefficient of Variation, %).
Table 9. Process Stability Assessment (Coefficient of Variation, %).
Plasma PowerCH2F2 ProcessCHF3 Process
500 W4.7 ± 0.34.3 ± 0.2
600 W4.5 ± 0.34.1 ± 0.2
700 W4.9 ± 0.35.8 ± 0.4
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Min, D.K.; Woo, J.; Lee, J.; Lee, B.-J.; Jeon, E.-c. Effects of Plasma Power on By-Product Gas Formation from CHF3 and CH2F2 Process Gases in Semiconductor Etching Processes. Appl. Sci. 2025, 15, 12296. https://doi.org/10.3390/app152212296

AMA Style

Min DK, Woo J, Lee J, Lee B-J, Jeon E-c. Effects of Plasma Power on By-Product Gas Formation from CHF3 and CH2F2 Process Gases in Semiconductor Etching Processes. Applied Sciences. 2025; 15(22):12296. https://doi.org/10.3390/app152212296

Chicago/Turabian Style

Min, Dae Kee, Jiyun Woo, Joohee Lee, Bong-Jae Lee, and Eui-chan Jeon. 2025. "Effects of Plasma Power on By-Product Gas Formation from CHF3 and CH2F2 Process Gases in Semiconductor Etching Processes" Applied Sciences 15, no. 22: 12296. https://doi.org/10.3390/app152212296

APA Style

Min, D. K., Woo, J., Lee, J., Lee, B.-J., & Jeon, E.-c. (2025). Effects of Plasma Power on By-Product Gas Formation from CHF3 and CH2F2 Process Gases in Semiconductor Etching Processes. Applied Sciences, 15(22), 12296. https://doi.org/10.3390/app152212296

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