MSMS Tips: 434
GC-TOFMS Application

Qualitative Analysis of Impurities in a Solvent for Semiconductor
Fabrication using msFineAnalysis AI
Product: Mass spectrometer (MS)Introduction
Reliability of semiconductor devices is determined by the level of cleanliness of silicon wafers. Therefore, it is critical to prevent contaminationfrom the impurities in cleaning solutions. To process any cleaning solution to an ultra-pure level, it is important to identify the chemicalcomponents of impurities to be removed. For this purpose, gas chromatography-mass spectrometer (GC-MS) is widely used.
Recently, techniques used for qualitative analysis are increasingly sophisticated, including exact mass analysis using GC-high resolution mass
spectrometer (GC-HRMS), NIST database of electron ionization (EI) mass spectra, and molecular ion analysis using soft ionization (SI).
Meanwhile, volumes of data acquired from exact mass analysis are enormous, requiring expertise in MS data analysis and vast amounts of time
for interpretation.
JEOL’s latest analytical software, msFineAnalysis AI, is designed to provide speedy analysis of GC-HRMS data acquired by both EI and SI,
determine chemical formulas, and predict chemical structures. In this work, we used msFineAnalysis AI to identify impurities in 2-methoxy-1methylethyl acetate (PGMEA), a cleaning solution for wafer surfaces.

Measurement
A commercial PGMEA (≥99.5%) was used as a sample. As a GC
column, Rtx-BAC PLUS1 was used because impurities wereexpected to be highly polar, similarly to PGMEA. EI and FI (FieldIonization) were used as ionization methods. msFineAnalysis AIwas subsequently used for analysis of the acquired data. Table 1
shows the measurement conditions.

Results and Discussion
Figure 1 shows the total ion current chromatograms (TICCs) of EIand FI. Other than air and PGMEA, a total of 12 components,
considered to be impurities, were detected. These components
other than air and water were verified in both EI and FI TICCs. For
some components, their formulas predicted from the molecular ionsdid not agree with the results of NIST database search.
However, msFineAnalysis AI contains an AI database of EI massspectra estimated from the chemical structures in addition to theNIST database. These components, when examined against the AI
database, turned out to be the compounds, which were in goodagreement with fragment ions patterns and had the chemical
formulas predicted by molecular ions.
Water molecules, which can be easily mixed with PGMEA, as wellas 1-methoxypropan-2-ol[1], which is used as a synthetic raw
material for PGMEA, were identified as impurities.
2-methoxypropyl acetate, a structural isomer of PGMEA, was also
identified as an impurity.

Table 1. Measurement conditions
GC-HRMS
Gas Chromatograph8890 GC (Agilent Technologies, Inc.)

Mode

Split 3:1

Inlet temperature

200 °C

ColumnRtx-BAC PLUS1, 30m x 0.32mm, 1.8μm(Restek Corporation)

Oven

80°C (1min) →10°C/min →200°C (5min)

Carrier gas

He, 1.0mL/min

Injection volume

1 μL

TOFMS
Ionization

JMS-T2000GC (JEOL Ltd.)
EI+: 70eV, 300μA
FI+: -10 kV, 40 mA

Monitor ion range
Analysis software

m/z 10-800
msFineAnalysis AI (JEOL Ltd.)

EIFI

Figure 1. EI and FI TICCs of PGMEA

EI

M+・FI

Figure 2. EI and FI mass spectra of the component at a retention time of 6.61 minutesUpper: EI, Lower: FI
Figures 2 and 3 respectively show the mass spectra and predicted chemical structures of the peak marked by ▼ in Figure 1, which wasdetected at a retention time of 6.61 minutes.
No molecular ion was detected in the EI mass spectrum in Figure 2. The molecular ion of this component was detected in the FI massspectrum, demonstrating the importance of using soft ionization as well. The exact mass of the molecular ion detected suggested C8H18O3 as
its chemical formula. NIST database search for the EI mass spectrum did not result in any compounds showing a similarity of 750 or more.
However, the AI structural analysis in Figure 3 resulted in 3-(3-hydroxybutan-2-yloxy)butan-2-ol, which had a chemical formula of C8H18O3
and also showed good agreement between the measured and AI predicted EI fragment patterns.

Measured

PredictedFigure 3. EI and FI mass spectra of the component at a retention time of 6.61 minutes

Summery
The results of this work demonstrate the effectiveness of msFineAnalysis AI. It is a powerful and efficient tool for qualitative analysis,saving time and labor in chemical formula determination and chemical structure prediction. In addition to qualitative analysis of impurities inorganic solvents including PGMEA, the GC-HRMS system with msFineAnalysis is expected to be effective for qualitative analysis of organic
contaminants on semiconductor surfaces by examining ROSE test solutions before and after cleaning semiconductor devices.

Reference[1] Arif Hussain, Yus Donald Chaniago, Amjad Riaz, Moonyong Lee,. Ind. Eng. Chem. Res. 2019, 58, 6, 2246−2257.
DOI: 10.1021/acs.iecr.8b04052