Rapid Analysis of Key Chemical Products in the Haber-Bosch Ammonia Synthesis Process

Significance of the topic

Ammonia is a foundational chemical in agriculture, chemicals and materials production, with over 80% used for fertilizers. Accurate, rapid and safe determination of ammonia concentration in process streams is critical for optimizing the Haber-Bosch synthesis loop, reducing raw material and energy costs, and minimizing environmental and safety risks. Replacing slow, hazardous laboratory assays (for example, wet titrations or density-based Baume tests) with a fast spectroscopic technique enables real-time process control and improved plant efficiency.

Objectives and study overview

This application study evaluated the use of FT-NIR spectroscopy (Thermo Scientific Antaris II MDS analyzer) for rapid quantification of aqueous ammonia in samples taken from storage tanks prior to reaction. Goals were to build a robust calibration across 0.1–7.0% ammonia, demonstrate prediction accuracy using independent validation samples, and assess suitability for transfer into an online/process environment.

Used instrumentation

• Thermo Scientific Antaris II Method Development Sampling (MDS) FT-NIR analyzer.
• 1 mm pathlength transmission fiber-optic probe (dip probe) used for laboratory spectral collection.
• Acquisition parameters: spectral range 10,000–4,000 cm-1, 32 scans per spectrum, 8 cm-1 resolution, air background measured through the probe.
• Software: Thermo Scientific TQ Analyst for PLS model development and validation.

Methodology

• Samples: 85 spectra collected from aqueous ammonia standards and process-derived samples; concentration range 0.1 to 7.0% NH3. Sixty-four spectra used for calibration and 21 retained for independent validation.
• Spectral regions selected for modelling: 6718–6365 cm-1 and 4705–4290 cm-1, corresponding to the N–H 1st overtone and N–H combination bands, respectively. These regions were chosen to focus on spectral features specific to ammonia and to avoid unrelated correlations elsewhere in the NIR.
• Preprocessing: second derivative (to sharpen peaks and remove baseline effects) combined with a Norris derivative smoothing filter (segment length = 11, gap length = 10) to reduce random noise.
• Chemometrics: Partial Least Squares (PLS) regression was used. Model complexity was evaluated via the Predicted Residual Error Sum of Squares (PRESS) plot to avoid overfitting.

Main results and discussion

• The optimal PLS model used three latent factors, as indicated by the PRESS curve; additional factors increased cross-validation error (overfitting).
• Performance metrics: calibration RMSEC = 0.127% NH3; cross-validation RMSECV = 0.143% NH3; independent validation RMSEP = 0.079% NH3. Correlation coefficients (R or Pearson) were approximately 0.998 for calibration and 0.997 for cross-validation, indicating excellent linear fit across the entire concentration range.
• Residual and loading analyses showed randomly distributed prediction errors across concentrations and no evident outliers. The first PLS factor captured the majority of spectral variance (>99%) and concentration variance (~97%), confirming that ammonia-related N–H spectral information dominates the model.
• Independent validation samples demonstrated low bias (reported bias ≈ -0.017% NH3) and small standard error of prediction (SEP ≈ 0.079% NH3), supporting good transferability of the laboratory transmission-probe model to unknown samples.
• Spectral behavior: because aqueous ammonia lacks the dense matrix of overlapping C–H bands typical for organic analytes, the N–H overtone/combination features are distinct and allow straightforward calibration development.

Benefits and practical applications

• Speed and safety: FT-NIR provides results in seconds (approx. 15 s per spectrum) without reagents or hazardous waste, eliminating subjective endpoints associated with titrations.
• Operator independence and reproducibility: multivariate calibration removes operator bias and yields consistent quantitative predictions across operators and instruments with shared optical designs.
• Real-time process monitoring: use of transmission or immersion probes enables inline or at-line measurement, facilitating reaction optimization, reduced rework, and chemical cost savings.
• Scalability and transfer: models developed on Antaris instruments can be transferred between instruments with minimal loss of performance due to consistent optical engineering.

Future trends and opportunities

• Inline and online deployment: moving from dip-probe laboratory use to robust flow-through or immersion probes for continuous monitoring and feedback control within the Haber-Bosch loop.
• Multicomponent process analytics: simultaneous monitoring of ammonia alongside other nitrogen-containing process species or impurities using expanded multivariate models.
• Model transfer and calibration maintenance: application of standardization approaches (e.g., calibration transfer, domain adaptation) and automated model updating to sustain accuracy in changing process conditions.
• Integration with PAT and digital control systems: combining NIR data with process historians and advanced control (APC) to drive automated optimization and predictive maintenance.
• Advances in chemometrics: robust outlier detection, nonlinear modelling where necessary, and cloud-based model management to scale deployments across multiple sites.

Conclusion

FT-NIR spectroscopy using the Antaris II MDS platform provides a rapid, accurate and reagent-free method for quantifying aqueous ammonia across a representative industrial concentration range (0.1–7.0% NH3). The study produced a compact PLS model (three factors) with excellent calibration and prediction statistics, low bias, and demonstrated practical suitability for at-line or online process implementation. Deploying FT-NIR for ammonia control can reduce analysis time, improve safety, and enable tighter process optimization in ammonia production and downstream operations.

References

• Heil C. Rapid Analysis of Key Chemical Products in the Haber-Bosch Ammonia Synthesis Process. Thermo Fisher Scientific Application Note 51677, 2008.