Quantitation of Hydrogen and Methane Dissolved in Hexanes, Toluene and Water
Applications | 2020 | ShimadzuInstrumentation
Precise measurement of dissolved inorganic gases is critical because trace levels of hydrogen and methane can impact chemical reactions, solution stability, and product safety. A high‐sensitivity analytical approach is necessary to monitor these gases in various liquid matrices.
The primary goal was to develop and validate a gas chromatography method employing a barrier discharge ionization detector (BID) to quantify hydrogen and methane dissolved in hexanes, toluene, and water. Key aims included:
Sample Preparation:
Instrument Configuration:
The BID‐2030 GC method demonstrates high sensitivity and reliable quantitation of dissolved hydrogen and methane in hexanes, toluene, and water. Implementation of rapid injection cycles and routine column aging ensures consistent performance and robust repeatability.
GC
IndustriesEnvironmental, Energy & Chemicals
ManufacturerShimadzu
Summary
Importance of the Topic
Precise measurement of dissolved inorganic gases is critical because trace levels of hydrogen and methane can impact chemical reactions, solution stability, and product safety. A high‐sensitivity analytical approach is necessary to monitor these gases in various liquid matrices.
Objectives and Study Overview
The primary goal was to develop and validate a gas chromatography method employing a barrier discharge ionization detector (BID) to quantify hydrogen and methane dissolved in hexanes, toluene, and water. Key aims included:
- Establishing calibration curves over a wide concentration range for both gases
- Evaluating method repeatability across different solvents
- Investigating sample and column integrity during multiple injections
Methodology and Instrumentation
Sample Preparation:
- Calibration standards of H₂ and CH₄ prepared at concentrations from 10 to 5 000 ppm (v/v) by diluting certified gases with indoor air
- Dissolution achieved by repeated mixing of 2 mL solvent (hexanes, toluene, or water) with 2 mL gas in gas‐tight syringes
Instrument Configuration:
- Gas chromatograph: Shimadzu Nexis™ GC-2030 with AOC-20i Plus autosampler
- Column: SH-Rt™-MSieve 5A (30 m × 0.53 mm I.D., 50 µm film) with a 2.5 m particle trap
- Detector: BID-2030 operated at 300 °C with 50 mL/min detector gas flow
- Injection conditions: split mode (1:5), injection temperature 250 °C; carrier gas helium at constant linear velocity of 50 cm/s
Main Results and Discussion
- Calibration linearity for hydrogen (R²=0.9996) and methane (R²=0.9960) confirmed over nanoliter injection volumes
- Repeatability (%RSD) ranged from 0.43 % to 4.84 %, depending on gas and solvent matrix
- Progressive decline in peak area upon continuous injection attributed to gas–liquid partitioning; short measurement cycles are recommended
- Retention time shifts caused by solvent buildup in the column were mitigated by periodic aging at 250 °C for 30 minutes
Benefits and Practical Application of the Method
- Superior sensitivity for trace gas analysis compared to conventional FID techniques
- Applicability to both nonpolar (hexanes, toluene) and polar (water) solvents
- High repeatability suitable for quality control in research and industrial laboratories
- Relatively simple sample preparation without complex headspace systems
Future Trends and Potential Applications
- Automation of headspace sampling to further improve reproducibility and reduce drift
- Extension of the method to other dissolved gases such as CO₂, N₂O, and volatile organics
- Development of shorter, low‐retention columns to expedite analyses and minimize carryover
- Coupling BID‐GC with mass spectrometry for enhanced selectivity and confirmation
Conclusion
The BID‐2030 GC method demonstrates high sensitivity and reliable quantitation of dissolved hydrogen and methane in hexanes, toluene, and water. Implementation of rapid injection cycles and routine column aging ensures consistent performance and robust repeatability.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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