Microelectronic Engineering 134 (2015) 43–46
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Particle adsorption behaviors during solvent cleaning containing NH4F q Nobuyoshi Sato ⇑ Advanced Memory Development Center, Toshiba Corporation, Yokkaichi-Shi, Mie-Prefecture, 512-8550, Japan
a r t i c l e
i n f o
Article history: Received 25 May 2014 Received in revised form 30 January 2015 Accepted 2 February 2015 Available online 7 February 2015 Keywords: Particle adsorption Solvent cleaning Cu
a b s t r a c t Particle adsorption behaviors on to metal lines during cleaning with a solvent containing ammonium fluoride (NH4F) were studied. In this experiment, a conventional batch spin wet tool was used for the cleaning process after dry etching of metal line patterning. Energy dispersive X-ray spectroscopy (EDX) analysis detected metallic particles showing a strong Cu signal (Cu particle) at the wafer center area, and also detected polymeric particles showing strong fluorine and carbon signals (FC particle) at the wafer edge area after solvent clean. Both types of particle were found on the metal lines. An isopropyl alcohol (IPA) rinse prevented the Cu particle growth, but enhanced the FC particle adsorption. Ó 2015 Elsevier B.V. All rights reserved.
1. Introduction
2. Experiment
Recently, several new challenges associated with modern wafer processing are being driven by an increase in the number of processing steps, increasing complexity of device technologies, process integration flows, and new materials incorporation. These challenges also make it more difficult to remove a polymer generated by dry etching during backend of line (BEOL) processing. The impact on yield loss in BEOL will be higher than that in the front end of line (FEOL) only. In the wet process area, there are two groups of wafer process tools: a conventional batch wet tool and a single wafer spin wet tool. The batch wet tool can be categorized as two types of tools: a bath type and a spin type. Use of the single wafer spin wet tool is becoming increasingly popular because of the higher performance and repeatability for the wet processes. However, manufacturing still requires use of the batch type of tool on the wet process area because the batch type has a higher throughput [1]. A hydroxylamine-based (HDA) solvent process is still used during the cleaning processes of BEOL [2–5]. A de-ionized water (DIW) rinse is carried out after an isopropyl alcohol (IPA) rinse on the HDA solvent process [2,3]. On the other hand, it is reported that an ammonium fluoride-based (NHF) solvent process does not require IPA, and DIW is only used for rinsing [6]. This provides a cost savings by not using IPA. In this report, we investigated particle adsorption behaviors on metal lines during NHF solvent process with and without IPA rinse.
2.1. Sample preparation
q
This article was presented at SPCC 2014.
⇑ Tel.: +81 59 330 1336; fax: +81 59 330 1119. E-mail address:
[email protected] http://dx.doi.org/10.1016/j.mee.2015.02.001 0167-9317/Ó 2015 Elsevier B.V. All rights reserved.
An 800 nm plasma chemical vapor deposition (CVD) SiO film (PSiO2 film) was deposited using SiH4 and N2O gases as an underlying layer on bare Si wafers. Metals consisting of 20 nm Ti, 50 nm TiN, 400 nm AlCu (Cu 0.5%), and 0.7 nm TiN were deposited on the PSiO2 film. Metal line patterning was then performed using a photo mask (1500 nm resist thickness) by utilizing BCl3 and Cl2 (in Lam research TCP9600PTX, with O2 plasma inline-ashing). The samples were inspected for wafer defects using a KLA2139 for metal patterning wafers. Particles were analyzed using Energy dispersive X-ray spectroscopy (EDX).
2.2. Cleaning conditions In this experiment, NHF solvent was used in a conventional batch spin wet tool. Table 1 shows the fundamental data, including the etch rate in various films and the pH value of the NHF solvent. Data on the HDA solvent is also shown in Table 1 as a reference. The pH values for NHF and HDA were 9.0 and 11.5, respectively. The etching rates of AlCu, Cu, and P-SiO2 for NHF and HDA were 4.0 and 2.2, 5.2 and 5.0, and 1.4 and 0.1 A/min, respectively. Note: NHF solvent is also including ethylenediamine-tetraacetic acid (EDTA, C10H16O8N2) as the Cu chelate agent [6]. Fifty wafers were arranged in the chamber with a distance of 5 mm between each wafer. The batch spin tool has a total of 6 grippers in the chamber that grip the wafers during wafer spinning. The wafer grippers are made of a fluorocarbon polymer (ACF2ACFClA)n. Table 2 shows the cleaning conditions. A total of 8 runs were carried out in this
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N. Sato / Microelectronic Engineering 134 (2015) 43–46
experiment. The spin speeds and treatment times were as follows: 50 rpm for 90 s during the solvent treatment, 50 rpm for 180 s during the first rinse, 200–1000 rpm for 120 s during the final DIW rinse, and 600 rpm for 300 s in the spin-dry step. Temperature at NHF and HDA solvent treatment were set to 25 and 65 °C, respectively. In the run No. 6, the first rinse consisted of DIW and IPA, respectively, and each rinse time was 90 s. 3. Results and discussion
ticles (Fig. 1b). EDX analysis detected strong carbon and fluorine signal peaks from the particle (FC particle) (Fig. 3c). The FC particles were mostly found on metal lines. Since the wafer grippers in the spin chamber are made of a fluorocarbon polymer (ACF2ACFClA)n, these results indicate that portions of grippers (fluorocarbon polymer) were deposited exactly at the wafer edges during spin processing. FC particle was observed in the cleaning sequence with IPA at the first rinse step, and the particle generation was accelerated with increase of wafer spin speed at the IPA rinse step.
3.1. Particle generation on metal lines
3.2. Possible mechanism of particle adsorption
3.1.1. Cu particle Fig. 1a–c show a defect map, scanning electron microscopy (SEM) top view and EDX analysis result, respectively after the solvent cleaning on #1 as listed in Table 2. The defects were mostly distributed at the wafer center (Fig. 1a). SEM top view at the wafer center (the defect area) showed particles on the metal lines and the particle size was approximately 0.1–0.2 lm (Fig. 1b). The particles were not observed on the underlying SiO2 layer (Fig. 1b). In addition, the brightness of particles in the SEM picture shows up to be indicative for conductivity. EDX analysis detected all signals (Al, Cu, N, Ti, Si, and O); against the compositions of the multi metal lines and the underlying SiO2 layer (Fig. 1c). Since EDX analysis detects the signals from the surfaces and a deep area (about 1–2 lm), it is reasonable to understand that the Al signal was the strongest of all. However Cu signal is almost same intensity (10–12% for Al signal intensity) as the others (N, Ti, Si, and O), and it is too strong against the composition of AlCu (Cu 0.5%). Based on above results, we hypothesize that the particle contains Cu as a main composition and originates from AlCu. Fig. 2 shows effects of a use of IPA and a wafer spin speed during the rinse step in the defect prevention. The defects decreased with increase of the wafer spin speed at the final DIW rinse (flushing step). Fig. 2a-d show SEM top views at wafer center area on run #1, #6, #7, and #8, respectively. Defects were not almost observed when IPA rinse was carried out after solvent treatment steps using NHF (2c) and also HDA (2d). Defects were significantly decreased even though IPA rinse was carried out after 1st DIW rinse (b). Based on these results, the higher spin speed at the final rinse and using of IPA rinse are effective for preventing the Cu particles.
3.2.1. Cu particle Table 3 shows analysis results of the time of flight secondary ion mass spectrometer (ToF-SIMS) on the samples from run #1 (DIW rinse at 200 rpm), #5 (DIW rinse at 1000 rpm), and #7 (IPA rinse at 200 rpm). These numbers show the peak ratios compared to the signals observed on non-treated sample. NH4 (positive ion), C4H12N (positive ion), and F (negative ion) were detected with a high signal intensity in the runs. Since NH4 and F ions are components of ammonium fluoride (NH4F), ToF-SIMS identified the chemical residues on the wafer surface after the NHF solvent cleaning. The C4H12N (TMA) could be included as C4H12N+ + OH (Tetramethylammonium hydroxide, TMAH) in the solvent, because TMAH is highly effective in stripping photoresist, and it has some phase transfer catalyst properties [7]. These ion intensities at the wafer center were higher than the signals from the wafer edges (Table 3 #1). Since the NHF solvent etches Cu and AlCu (Table 1), the chemical residues clarify the Cu particle generation on the wafer center. These ion intensities decreased with increase of the spin speed on the final DIW rinse (Table 3 #5) and they also decreased with IPA rinse (Table 3 #7). The increase of the chemical residues matches to increase of the Cu particle density (Fig. 2). We previously reported that the relationship between a liquid flow rate and a cleaning efficiency as shown in Fig. 4a and b [8]. Batch wet tool (bath type) was used for the particle removals. Initially particles were coated to the wafers, and then they were dipped in a bath with an ammonium hydroxide peroxide mixture (APM). The liquid flow simulation on the wafer in the bath (Fig. 4a) matched the distribution of particle residues after the APM clean (Fig. 4b). We concluded that the particle residue caused by the low flow rate of liquid during cleaning [8]. When the DIW rinse efficiency is low, the NHF solvent may remain mostly on the surface of the wafer center as a stagnant liquid layer (carryover liquid layer) [9–11]. In batch spin tool, liquid flow rate at the wafer edge is higher than that at the wafer center, since it is supplied from the wafer edge during wafer rotation. With increase of wafer spin speed, the flushing at wafer center becomes more enhanced, even though the liquid is supplied from the wafer edge. In contrast, the flushing at wafer center becomes worse with decrease of the wafer spin speed, and then the stagnant liquid layer generates and stays the wafer center area (Fig. 4c). Morinaga et al. reported Cu particle deposition on Si substrate in a copper chloride aqueous solution [12]. They concluded that Cu was deposited on Si substrate by a reduction reaction (1):
3.1.2. FC particle In order to investigate other possible particles, we carefully inspected the wafer edge areas because the wafers are clamped with the grippers during spin processing, and the wafer edge could become a particle source. Fig. 3 shows an analysis of wafer edge particles after the solvent process on #7 (IPA is used instead of DIW at first rinse step): (a) defect map, (b) SEM image, and (c) EDX analysis of the wafer edge particle. As shown in Fig. 3a, the defects were mostly observed at the wafer edge. The SEM image for the particle (Fig. 3b) showed a different shape from the Cu par-
Table 1 Characteristics of the NHF and HDA solvents.
Composition ; ; pH value AlCu (A/min) Cu (A/min) SiO2 (A/min) Solvent temp. (°C)
Cu2 þ 2e ðfrom Si sub:Þ ! Cu
NHF
HDA
Ammonium fluoride (NH4F) H2O Others (including EDTA) 9.0 4.0 5.2 1.4 25
Hydroxylamine (NH2OH) H2O Others 11.5 2.2 5.0 0.1 65
ð1Þ
and Cu particle grows via this successive electron-transfer. In the NHF solvent process, NHF solvent becomes an aqueous solution during DIW rinse, and then Cu is deposited and grows on the metal surface through the same reaction as above (Fig. 5a). When wafer spin speed during the final DI water rinse (flushing step) is low, Cu deposition is enhanced due to the generation of the stagnant liquid layer (Fig. 4c). In the NHF solvent process, both Cu and Al could be removed from AlCu (0.5% Cu) metal line during the NHF
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N. Sato / Microelectronic Engineering 134 (2015) 43–46 Table 2 Cleaning conditions used in this experiment. Run No.
Solvent (50 rpm, 90 s)
1st rinse (50 rpm, 180 s)
Final rinse using DIW [rpm] (200–1000 rpm, 120 s)
1 2 3 4 5 6
NHF NHF NHF NHF NHF NHF
200 400 600 800 1000 200
7 8
NHF HDA
DIW DIW DIW DIW DIW DIW ? IPA (2 step) IPA IPA
200 200
Fig. 3. Analysis of the wafer edge particle: (a) defect map, (b) SEM image and EDX analysis on the particle. Run #7 was used in this cleaning.
Table 3 ToF-SIMS analysis of the wafer surface after being cleaned by solvent. Ion
Ratios in reference to the signals observed on nontreated sample Run #1 (wafer edge)
2.2 NH4 (positive ion) C4H12N (positive ion) 3.4 F (negative ion) 1.7
Fig. 1. Cu particle generation after NHF solvent clean: (a) defect map, (b) SEM top view, and (c) EDX analysis. Run #1 was used in this cleaning.
solvent cleaning however Al deposition (particle) was not observed in all runs. This is explained as the followings; the order of the ionization tendency is Cu < Ti < Al. Cu can grow on both Ti and Al surface as shown in Fig. 1a, since the ionization tendency of Cu is lower
Fig. 2. Effect of a wafer spin speed and IPA rinse in the defect prevention. (a), (b), (c) and (d) show SEM top views at wafer center area after solvent clean in #1, #6, #7, and #8, respectively.
#1 (center)
#5 (center)
#7 (center)
3.3 5.7 3.1
1.2 2.3 1.3
0.7 1.2 1.1
than Ti and Al. However Al cannot grow on Ti surface due to the higher ionization tendency than Ti. On the other hand, Cu particle dramatically decreased with the IPA rinse after NHF solvent step (Fig. 2c). This is because the NHF solvent is replaced with IPA which does not dissociate (Fig. 5b). In this experiment, many sizes (under 0.1–over 0.2 lm) of Cu particle were observed in Fig. 2a (run #1), however the limited size (under 0.1 lm) of Cu particle was observed in Fig. 2b (run #6) and 2c (run #7). Cu particle density decreased in order of run 1#, #6, and #7. DIW rinse time on #1, #6, and #7 is 180 s (1st rinse) + 120 s (final rinse), 180 s + 120 s, and 0 s + 120 s, respectively under the constant value of the spin speeds of 50 rpm on the 1st rinse and 200 rpm on the final rinse. The 200 rpm is the lowest spin speed in all final rinse. Since NHF solvent is effectively replaced (removed) with IPA which does not dissociate (Table 3 #7), the DIW rinse time after IPA rinse could be negligible. Note; HDA solvent is more effectively replaced with IPA (Fig. 2d). DIW rinse time which is related to Cu generation on #1, #6, and #7 can be 180 s + 120 s, 180 s + 0 s, and 0 s + 0 s, respectively. This order matches to the decrease of the Cu particle density and its size (Fig. 2). Cu particle density and its size on the wafer center increase with increase of the DIW rinse time at the low spin speed. Cu particle density and its growth could depend on the Cu ion concentration in the aqueous solution and its sitting time on the metal line. The increase of the spin speed on the final rinse also works for removing the aqueous solution (Table 3 #5). 3.2.2. FC particle We hypothesize that FC particles generate from the wafer grippers, which are composed of (ACF2ACFClA)n, during wafer rotation. FC particle could be electrostatically charged during the wafer rotation (Fig. 5b). IPA penetrates into the details in the tool and carries the FC particle because it has a low viscosity (surface tension) as well as a low relative permittivity compared to water. The static electricity is discharged in the aqueous solution, but it remains in IPA. FC particle is electrostatically attracted to the metal surface during an IPA rinse (Fig. 5b).
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Fig. 4. Effect of liquid flow rate: (a) simulation of liquid flow and (b) particle remaining after APM cleaning in a bath type of wet tool, and (c) schematic drawings of possible liquid flow in the batch-spin wet tool. Note: 4a and b refer [8]. Reproduced by permission of ECS – The Electrochemical Society.
Fig. 5. Particle adsorption behaviors during a solvent cleaning: (a) DIW rinse and (b) IPA rinse.
4. Conclusion We clarified particle adsorption behaviors on to metal lines during cleaning with a solvent containing NH4F. EDX analysis detected metallic particles showing a strong Cu signal (Cu particle), and also polymeric particles showing strong carbon and florin signals (FC particle) on the metal line after the solvent clean. IPA rinse prevented Cu particle growth, but it enhanced the FC particle adsorption. Ionized Cu in an aqueous solution or an electrostatically charged polymeric particle could have been adsorbed on to the metal lines. Acknowledgments The author wishes to extend their special thanks to Sallie Hose, Tom McFadden, Chris Bowker and Matthew Trattles in LSI Logic’s process engineering for suggestions and supports in this experiment, Roger Young and Khaldoun Barakat in LSI Logic’s ILM engineering for defect analysis, and also Mark Giewont in LSI Logic’s yield engineering for yield analysis. The author especially appreciate his efforts of Greg Piatt in LSI Logic’s Equipment Engineering for their assistance in tool setup and also Peter Scott (Senior IP
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