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Frequently asked questions in near-infrared spectroscopy analysis – Part 2

Frequently asked questions in near-infrared spectroscopy analysis – Part 2

Whether you are new to the technique, a seasoned veteran, or merely just curious about near-infrared spectroscopy (NIRS), Metrohm is here to help you to learn all about how to perform the best analysis possible with your instruments.

In this series, we will cover several frequently asked questions regarding both our laboratory NIRS instruments as well as our line of Process Analysis NIRS products.

Did you miss Part 1 in this series? Find it here!

1. What are typical detection limits for liquid samples and for solid samples?

The detection limit varies depending on the substance analyzed, the complexity of the sample matrix, and the sensitivity of both the reference and NIR technology used. NIR spectroscopy systems using dispersive technology are the most sensitive. Using such a system to analyze a simple sample in which the parameter of interest is a strong absorber will allow low detection limits.

For example, water in solvents can be detected down to about 10 mg/L in both offline and online/inline measurements. For more complex matrices (e.g., solids and slurries), detection limits are about 1000 mg/L (0.1%).

For more information about the differences between solid and liquid samples for NIRS analysis, as well as the different methods best suited for such matrices, read our blog post «Benefits of NIR spectroscopy: Part 1» here!

2. What accuracy can I achieve with NIR spectroscopy?

The accuracy of a near-infrared spectroscopic method depends on the accuracy of the reference/primary method. A highly accurate primary method will result in the development of a highly accurate NIR method, while a less accurate primary method lowers the accuracy of the related NIR method. This is because the NIR data and primary data are correlated in the prediction model. A good prediction model will have approximately 1.1x the accuracy of the primary method over the prediction range.

The development of prediction models has been described in detail in our previous blog article: «Benefits of NIR spectroscopy: Part 3».

3. How are instruments calibrated and how often do I need to recalibrate an instrument?

Instruments are calibrated using certified NIST standards. For dispersive systems measuring in reflection mode, NIST SRM 1920 standards are used to calibrate the wavelength / wavenumber axis. Certified reflection standards with a defined reflectance made of ceramic can be used to calibrate the absorbance axis.

In transmission mode, typically NIST SRM 2065 or 2035 are used for the wavelength / wavenumber calibration, and air for the absorbance axis.

A calibration should be performed after each hardware modification (e.g., lamp exchange) and annually as part of a service interval. Ideally, the spectroscopy software guides user through the complete calibration processes.

Find the calibration tools for your Metrohm NIRS instruments here!

Metrohm NIRS reflection standard, set of 2.

4. How do I validate my instrument and how frequently should validation be done?

The Metrohm NIRS DS2500 Solid Analyzer.

NIR spectroscopy software offers different tests to validate the performance of the instrument. The most common one is a basic performance test, which tests some crucial hardware parts as well as the wavelength/wavenumber calibration and the signal to noise (S/N) of the system.

For the regulated environment, further tests according to the USP <856> guidelines are typically implemented, including photometric linearity and noise at high and low light fluxes. Instrument performance tests should be performed on a regular basis, with the frequency depending on risk assessment.

5. What sample types or parameters are not suitable for analysis with NIR spectroscopy?

Samples containing a high amount of carbon black cannot be analyzed by NIR spectroscopy because carbon black absorbs almost all NIR light.

Further, most inorganic substances have no absorbance bands in the NIR spectral region and are therefore not suitable for NIR analysis.

Find out more about the molecules and functional groups which are active in the NIR region of the electromagnetic spectrum in our previous blog post: «Benefits of NIR spectroscopy: Part 2».

Carbon black is not a suitable sample to be measured by NIR technology.

Are you looking for more spectroscopy applications? Check out the Metrohm Application Finder to download free applications across a variety of industries!

6. My industrial process is full of harsh chemicals, so manual sampling is not desirable. Is it possible to perform inline NIR analysis in hazardous areas?

Yes, and we have the right solutions for you. Metrohm not only manufactures instruments for laboratory analysis, but we also cater to the industrial process world! Metrohm Process Analytics offers two versions of process NIRS systems: the NIRS Analyzer Pro and the NIRS XDS Process Analyzer, the latter being the ideal solution for hazardous environments.

Metrohm Process Analytics offers two lines of near-infrared spectroscopic process analyzers: the NIRS Analyzer PRO and the NIRS XDS Process Analyzer.

NIRS is a robust and extremely versatile method, which enables simultaneous, «real-time» monitoring of diverse process parameters with a single measurement. The use of fiber-optics in NIRS means that the process analyzer and measuring point can be spatially separated – even by hundreds of meters if required. In fact, remote monitoring can be achieved at large distances without significant impact to S/N ratios. This is a huge advantage in environments with challenging explosion protection requirements. Fiber-optic probes and flow cells can be placed in very harmful working environments, while the spectrometer and analysis PC remain safe and secure in a shelter. When a shelter is not available, the NIRS XDS Process Analyzer can be directly placed in the hazardous area (ATEX Zone 2 or Class1Div2).

Obtain «real-time» results of your process without the need to take samples, reduce the risks of handling chemicals, and increase your profitability. Download our free brochure here for more information about safe operation of NIRS process analyzers in hazardous areas!

7. How is the maintenance of a NIRS process analyzer performed?

Maintenance is easy, fast, and not necessary to perform very often. NIRS is a reagentless analytical technique, so the only consumable to be replaced is the lamp, which needs replacement once per year.

Compared to other techniques like chromatography  (e.g., GC, IC) or titration, and also because NIR spectroscopic analysis does not degrade samples, there is no chemical waste which is produced. Additionally, thanks to our all-in-one software, automatic performance tests are performed regularly to guarantee that the analyzer is operating according to process specifications. The instrument can be left in the process without any further operator involvement. 

Metrohm Process Analytics NIRS process analyzers are maintenance-free systems that have been designed to guarantee high uptimes and low operational costs.

Are you searching for more process NIRS applications? Check out the Metrohm Application Finder to download them for free!

Want to learn more about NIR spectroscopy and potential applications? Have a look at our free and comprehensive application booklet about NIR spectroscopy.

Download our Monograph

A guide to near-infrared spectroscopic analysis of industrial manufacturing processes

Post written by Dr. Nicolas Rühl (Product Manager Spectroscopy at Metrohm International Headquarters, Herisau, Switzerland) and Dr. Alexandre Olive (Product Manager Process Spectroscopy at Metrohm Applikon, Schiedam, The Netherlands).

Frequently asked questions in near-infrared spectroscopy analysis – Part 1

Frequently asked questions in near-infrared spectroscopy analysis – Part 1

Whether you are new to the technique, a seasoned veteran, or merely just curious about near-infrared spectroscopy (NIRS), Metrohm is here to help you to learn all about how to perform the best analysis possible with your instruments.

In this series, we will cover several frequently asked questions regarding both our laboratory NIRS instruments as well as our line of Process Analysis NIRS products.

1. What is the difference between IR spectroscopy and NIR spectroscopy?

IR (infrared) and NIR (near-infrared) spectroscopy utilize different spectral ranges of light. Light in the NIR range is higher in energy than IR light (Figure 1), which affects the interaction with the molecules in a sample.

Electromagnetic Spectrum
Figure 1. The electromagnetic spectrum.

This energy difference has both advantages and disadvantages, and the selection of the ideal technology depends very much on the application. The higher energy NIR light is absorbed less than IR light by most organic materials, broadening the resulting bands and making it difficult to assign them to specific functional groups without mathematical processing.

However, this same feature makes it possible to perform analysis without sample preparation, as there is no need to prepare very thin layers of analyte or use ATR (attenuated total reflection). Additionally, NIRS can quantify the water content in samples up to 15%.

Want to learn more about how to perform faster quality control at lower operating costs by using NIRS in your lab? Download our free white paper here: Boost Efficiency in the QC laboratory: How NIRS helps reduce costs up to 90%.

The weaker absorption of NIR light leads to using long pathlengths for liquid measurements, which is particularly helpful in industrial process environments. Speaking of such process applications, with NIR spectroscopy, you can use long fiber optic cables to connect the analyzer to the measuring probe, allowing remote measurements throughout the process due to low absorbance of the NIR light by the fiber (Figure 2).

Electromagnetic Spectrum
Figure 2. Illustration of the long-distance measurement possibility of a NIRS process analyzer with the use of low-dispersion fiber optic cables. Many sampling options are available for completely automated analysis, allowing users to gather real-time data for immediate process adjustments.

For more information, read our previous blog post outlining the differences between infrared and near-infrared spectroscopy.

2. NIR spectroscopy is a «secondary technology». What does this mean?

To create prediction models in NIR spectroscopy, the NIR spectra are correlated with parameters of interest, e.g., the water content in a sample. These models are then used during routine quality control to analyze samples.

Values from a reference (primary) method need to be correlated with the NIR spectrum to create prediction models (Figure 3). Since NIR spectroscopy results depend on the availability of such reference values during prediction model development, NIR spectroscopy is therefore considered a secondary technology.

Electromagnetic Spectrum
Figure 3. Correlation plot of moisture content in samples measured by NIRS compared to the same samples measured with a primary laboratory method.

For more information about how Karl Fischer titration and NIR spectroscopy work in perfect synergy, download our brochure: Water Content Analysis – Karl Fischer titration and Near-Infrared Spectroscopy in perfect synergy.

Read our previous blog posts to learn more about NIRS as a secondary technique.

3. What is a prediction model, and how often do I need to create/update it?

In NIR spectroscopy, prediction models interpret a sample’s NIR spectrum to determine the values of key quality parameters such as water content, density, or total acid number, just to name a few. Prediction models are created by combining sample NIR spectra with reference values from reference methods, such as Karl Fischer titration for water content (Figure 3).

A prediction model, which consists of sufficient representative spectra and reference values, is typically created once and will only need an update if samples begin to vary (for example after a change of production process equipment or parameter, raw material supplier, etc.).

Want to know more about prediction models for NIRS? Read our blog post about the creation and validation of prediction models here.

4. How many samples are required to develop a prediction model?

The number of samples needed for a good prediction model depends on the complexity of the sample matrix and the molecular absorptivity of the key parameter.

For an «easy» matrix, e.g., a halogenated solvent with its water concentration as the measurement parameter, a sample set of 1020 spectra covering the complete concentration range of interest may be sufficient. For applications that are more complex, we recommend using at least 40–60 spectra in order  to build a reliable prediction model.

Find out more about NIRS pre-calibrations built on prediction models and how they can save time and effort in the lab.

5. Which norms describe the use of NIR in regulated and non-regulated industries?

Norms describing how to implement a near-infrared spectroscopy system in a validated environment include USP <856> and USP <1856>. A general norm for non-regulated environments regarding how to create prediction models and basic requirements for near-infrared spectroscopy systems are described in ASTM E1655. Method validation and instrument validation are guided by ASTM D6122 and ASTM D6299, respectively.

Figure 4. Different steps for the successful development of quantitative methods according to international standards.

For specific measurements, e.g. RON and MON analysis in fuels, standards such as ASTM D2699 and ASTM D2700 should be followed.

For further information, download our free Application Note: Quality Control of Gasoline – Rapid determination of RON, MON, AKI, aromatic content, and density with NIRS.

6. How can NIRS be implemented in a production process?

Chemical analysis in process streams is not always a simple task. The chemical and physical properties such as viscosity and flammability of the sample streams can interfere in the analysis measurements. Some industrial processes are quite delicate—even the slightest changes to the process parameters can lead to significant variability in the properties of final products. Therefore, it is essential to measure the properties of the stream continuously and adjust the processing parameters via rapid feedback to assure a consistent and high quality product.

Figure 5. Example of the integration of inline NIRS analysis in a fluid bed dryer of a production plant.

Curious about this type of application? Download it for free from the Metrohm website!

The use of fiber optic probes in NIRS systems has opened up new perspectives for process monitoring. A suitable NIR probe connected to the spectrometer via optical fiber allows direct online and inline monitoring without interference in the process. Currently, a wide variety of NIR optical probes are available, from transmission pair probes and immersion probes to reflectance and transflectance probes, suitable for contact and non-contact measurements. This diversity allows NIR spectroscopy to be applied to almost any kind of sample composition, including melts, solutions, emulsions, and solid powders.

Selecting the right probe, or sample interface, to use with a NIR process analyzer is crucial to successful process implementation for inline or online process monitoring. Depending upon whether the sample is in a liquid, solid or gaseous state, transflectance or transmission probes are used to measure the sample, and specific fitting attachments are used to connect the probes to the reactor, tank, or pipe. With more than 45 years of experience, Metrohm Process Analytics can design the best solutions for your process. 

Visit our website to find a selection of free Application Notes to download related to NIRS measurements in industrial processes.

7. How can product quality be optimized with process NIRS?

Regular control of key process parameters is essential to comply with certain product and process specifications, and results in attaining optimal product quality and consistency in any industry. NIRS analyzers can provide data every 30 seconds for near real-time monitoring of production processes.

Figure 6. The Metrohm Process Analytics NIRS XDS Process Analyzer, shown here with multiplexer option allowing up to 9 measuring channels. Here, both microbundle (yellow) and single fiber (blue) optical cables are connected, with both a reflectance probe and transmission pair configured.

Using NIRS process analyzers is not only preferable for 24/7 monitoring of the manufacturing process, it is also extremely beneficial for inspecting the quality of raw materials and reagents. By providing data in «real-time» to the industrial control system (e.g., DCS or PLC), any process can be automated based on the NIRS data. As a result, downtimes are reduced, unforeseen situations are avoided, and costly company assets are safeguarded.

Furthermore, the included software on Metrohm Process Analytics NIRS instruments has a built-in chemometric package which allows qualification of a product even while it is still being produced. A report is then generated which can be directly used by the QC manager. Therefore, the product quality consistency is improved leading to potential added revenues.

Do you want to learn more about improving product quality with online or inline NIRS analysis? Take a look at our brochure!

In the next part, we cover even more of your burning questions regarding NIRS for lab and process measurements:

Want to learn more about NIR spectroscopy and potential applications? Have a look at our free and comprehensive application booklet about NIR spectroscopy.

Download our Monograph

A guide to near-infrared spectroscopic analysis of industrial manufacturing processes

Post written by Dr. Nicolas Rühl (Product Manager Spectroscopy at Metrohm International Headquarters, Herisau, Switzerland) and Dr. Alexandre Olive (Product Manager Process Spectroscopy at Metrohm Applikon, Schiedam, The Netherlands).

Forewarned is Forearmed: Error and risk minimization in process analysis – Part 3

Forewarned is Forearmed: Error and risk minimization in process analysis – Part 3

In the course of life, each of us learns to trust our gut feelings or our experiences to avoid situations that seem dangerous or risky. You quite literally sense potential dangers with an uneasy feeling. Who hasn’t painfully learned that touching a hot stove top isn’t a good idea? Or who voluntarily goes outside during a tornado?

While humans can rely on their intuition and learned patterns to avoid dangers or use protective strategies, this is far more complicated with electronic systems or machines. All components of a system must be in a permanently safe state. Failures and malfunctions of individual components can have devastating consequences for production processes and the safety of the operators.

An example of this is the Seveso disaster in 1976, in which highly toxic dioxin TCDD escaped as a result of an uncontrolled reaction, and sustainably poisoned flora and fauna. With regard to other major chemical accidents, the European Seveso III Directive then came into force in 2012 to control major accident hazards to prevent major accidents.

Have you read Part 1 and Part 2 of our «Advantages of PAT (Process Analytical Technology)» series? If not, find them here!

Recognize, master, and avoid errors

Process engineering systems that are operated continuously contain countless components that can wear out or fail during their life cycle. However, if the measuring, control, or regulating circuit is affected, failures can cause immense damage. Under no circumstances should humans nor the environment be exposed to any kind of danger. For this reason, the functional safety of the components must be guaranteed, and their risk and hazard potential must be analyzed in detail.

The service life of mechanical components can be evaluated by observing mechanical wear and tear. However, the aging behavior of electronic components is difficult to assess. A unit of measure that makes risk reduction and thus functional safety quantifiable is the so-called «Safety Integrity Level» (SIL). 

The following procedure is followed:

  1.   Risk analysis
  2.   Realization of risk reduction
  3.   Evidence that the realized risk reduction corresponds at least to the required risk reduction

«Process analysis systems are part of the entire safety cycle of a manufacturing plant and therefore only one component whose risk of malfunctions and failures must be considered in an assessment.»

Risk assessmentA process is considered safe if the current risk has been reduced below the level of the tolerable risk. If safety is ensured by technical measures, one speaks of functional safety.

Significance for process analysis systems

Errors can happen anywhere, and can never be completely excluded. To minimize possible errors, it is therefore necessary to estimate the risk of occurrence and the damage to be expected from it as part of a risk analysis. A distinction must be made here between systematic and random errors.

Systematic errors are potentially avoidable and are caused, for example, by software errors or configuration deficiencies. Accordingly, they already exist during or prior to commissioning.

In contrast, random errors are potentially difficult to avoid because they occur arbitrarily. Nevertheless, the error rate or failure probability can be determined statistically and experimentally.

Random errors usually result from the hardware and occur during operation. Ultimately, systematic errors should be avoided, and random errors should be mastered to ensure trouble-free functionality.

Process analysis systems are the link between manual laboratory analysis and the industrial process. In applications where continuous and fully automatic monitoring of critical parameters is required, process analyzers are indispensable. Due to the different analysis conditions in the laboratory and directly in the process, there are some challenges when transferring the measurement technology from the lab to the process. The decisive factors are the working and environmental conditions (e.g., high temperatures, corrosive atmospheres, moisture, dust, or potentially explosive environments) which the process analyzers have to meet regarding their design, construction materials, and reliability of the components. The analyzer automatically and continuously transmits system and diagnostic data to prevent hardware or software components from failing through preventive measures. This significantly reduces the chance of random errors occurring.

General process analyzer setup

a) Analyzer Setup

Process analyzers have been specially developed for use in harsh and aggressive industrial environments. The IP66 protected housing is divided into two parts, and consists of separate wet and electronic parts. The electronics part contains all components relevant to control and operate the process analyzer. Modular components like burettes, valves, pumps, sampling systems, titration vessels, and electrodes can be found in the analyzer wet part. Representative samples can thus be taken from the process measuring point several meters away. The analysis procedure, the methods to be used, and method calculations are freely programmable.

A touchscreen with intuitive menu navigation allows easy operation, so that production processes can be optimized at any time. The course of the measurement is graphically represented and documented over the entire determination, so that the analysis process is completely controlled. The measurement results can be generated 24/7 and allow close and fully automatic monitoring of the process. Limits, alarms, or results are reliably transferred to the process control system.

When operating the analyzer, there is a risk that software errors can lead to failures. In order to recognize this with foresight, the system delivers self-diagnostic procedures as soon as it is powered on and also during operation. This includes, e.g., checking pumps and burettes, checking for leaks, or checking the communication between the I/O controller, the human interface, and the respective analysis module.

b) Sensors

The central component of a process analyzer is the measurement technique in use. In the case of sensors or electrodes, there are several requirements such as chemical resistance, ease of maintenance, robustness, or precision which they must meet. The safety-related risk arises from the possibility if measurement sensors fail due to aging, or if they become damaged and subsequently deliver incorrect measurement results.

Failure of the electrode, contamination, or damage must be reported immediately. With online analysis systems, the analysis is performed in an external measuring cell. In addition, recurring calibration and conditioning routines are predefined and are performed automatically. The status of the electrode is continuously monitored by the system.

Between measurements, the electrode is immersed in a membrane-friendly storage solution that prevents drying out and at the same time regenerates the swelling layer. The electrode is therefore always ready for use and does not have to be removed from the process for maintenance. This enables reliable process control even under harsh industrial conditions.

c) Analysis

Process analyzers must be able to handle samples for analysis over a wide concentration range (from % down to trace levels) without causing carry-over or cross-sensitivity issues. In many cases, different samples from several measuring points are determined in parallel in one system using different analysis techniques. The sample preparation (e.g., filtering, diluting, or wet chemical digestion) must be just as reliable and smooth as the fully automatic transfer of results to the process control system so that a quick response is possible.

Potential dangers for the entire system can be caused by incorrect measurement results. In order to minimize the risk, a detector is used to notify the system of the presence of sample in the vessel. The testing of the initial potential of the analysis or titration curves / color development in photometric measurements are diagnostic data that are continuously recorded and interpreted. Results can be verified by reference analysis or their plausibility can be clarified using standard and check solutions.

Detect errors before they arise

The risk assessment procedures that are carried out in the context of a SIL classification for process engineering plants are ultimately based on mathematical calculations. However, in the 24/7 operation of a plant, random errors can never be completely excluded. Residual risk always remains. Therefore, the importance of preventive maintenance activities is growing immensely in order to avoid hardware and software failures during operation.

A regular check of the process analyzer and its diagnostic data is the basic requirement for permanent, trouble-free operation. With tailor-made maintenance and service concepts, the analyzer is supported by certified service engineers over the entire life cycle. Regular maintenance plans, application support, calibration, or performance certificates, repairs, and original spare parts as well as proper commissioning are just a few examples.

Advantages of preventive maintenance from Metrohm Process Analytics

  • Preservation of your investment
  • Minimized risk of failure
  • Reliable measurement results
  • Calculable costs
  • Original spare parts
  • Fast repair
  • Remote Support

In addition, transparent communication between the process control system and the analyzer is also relevant in the context of digitalization. The collection of performance data from the analyzer to assess the state of the control system is only one component. The continuous monitoring of relevant system components enables conclusions to be drawn about any necessary maintenance work, which ideally should be carried out at regular intervals. The question arises as to how the collected data is interpreted and how quickly it is necessary to intervene. Software care packages help to test the software according to the manufacturer’s specifications, to perform data backup and software maintenance.

«Remote support is particularly important in times when you cannot always be on site.»

In real emergency situations in which rapid error analysis is required, manufacturers can easily support the operator remotely using remote maintenance solutions. The system availability is increased, expensive failures and downtimes are avoided, and the optimal performance of the analyzer is ensured.

Read what our customers have to say!

We have supported customers even in the most unlikely of places⁠—from the production floor to the desert and even on active ships!

Post written by Dr. Kerstin Dreblow, Product Manager Wet Chemical Process Analyzers, Deutsche Metrohm Prozessanalytik (Germany).

The role of process automation in an interconnected world – Part 2

The role of process automation in an interconnected world – Part 2

The following scenario sounds like a fictional dystopian narrative, but it is a lived reality. A catastrophe, much like the current COVID-19 crisis, is dramatically impacting society. The normality, as was known before, has suddenly changed: streets are swept empty, shops are closed, and manufacturing is reduced or at a complete standstill. But what happens to safety-related systems, e.g. in the pharmaceutical or food industry, which must not stand still and are designed in such a way that they cannot fail? How can the risk of breakdowns and downtimes be minimized? Or in the event of failure, how can the damage to people and the environment be limited or, in general, the operational sequence maintained?

Digitalization: curse or blessing? 

When considering process engineering plants, one is repeatedly confronted with buzzwords such as «Industry 4.0», «digitalization», «digital transformation», «IoT», «smart manufacturing», etc. The topic is often discussed controversially and often it is about an either-or dichotomy: either man or the machine and the associated fears. No matter what name you give to digitalization, each term here has one thing in common: intelligently networking separate locations and processes in industrial production using modern information and communication technologies. Process automation is a small but important building block that needs attention. Data can only be consistently recorded, forwarded, and reproduced with robust and reliable measurement technology.

For some time already, topics including sensors, automation, and process control have been discussed in the process industry (PAT) with the aim of reducing downtimes and optimizing the use of resources. However, it is not just about the pure collection of data, but also about their meaningful interpretation and integration into the QM system. Only a consequent assessment and evaluation can lead to a significant increase in efficiency and optimization.

This represents a real opportunity to maintain production processes with reduced manpower in times of crisis. Relevant analyses are automatically and fully transferred to the process. This enables high availability and rapid intervention, as well as the assurance of high quality requirements for both process security and process optimization. In addition, online monitoring of all system components and preventive maintenance activities effectively counteracts a failure.

Digitally networked production plants

Even though digitalization is relatively well-established in the private sector under the catchphrase «smart home», in many production areas the topic is still very much in its infancy. In order to intelligently network different processes, high demands are made. Process analysis systems make a major contribution to the analysis of critical parameters. Forwarding the data to the control room is crucial for process control and optimization. In order to correspond to the state-of-the-art, process analysis systems must meet the following requirements:

Transparent communication / operational maintenance

Processes must be continuously monitored and plant safety guaranteed. Downtimes are associated with high expenditure and costs and therefore cannot be tolerated. In order to effectively minimize the risk of failures, device-specific diagnostic data must be continuously transmitted as part of the self-check, or failures must be prevented with the help of preventive maintenance activities. Ideally, the response must be quick, and faults remedied without having to shut down the system (even remotely).

Future-proof automation

If you consider how many years (or even decades) process plants are in operation, it is self-explanatory that extensions and optimizations must be possible within their lifetime. This includes both the implementation of state-of-the-art analyzers and the communication between the systems.

Redundant systems

In order to prevent faults from endangering the entire system operation, redundancy concepts are generally used.

Practical example: Smart concepts for fermentation processes

Fermenters or bioreactors are used in a wide variety of industries to cultivate microorganisms or cells. Bacteria, yeasts, mammalian cells, or their components serve as important active ingredients in pharmaeuticals or as basic chemicals in the chemical industry. In addition, there are also degradation processes in wastewater treatment assisted by using bioreactors. Brewing kettles in beer production can also be considered as a kind of bioreactor. In order to meet the high requirements for a corresponding product yield and the maintenance of the ideal conditions for proper metabolism, critical parameters have to be checked closely, and often.

The conditions must be optimally adapted to those of the organism’s natural habitat. In addition to the pH value and temperature, this also includes the composition of the matrix, the turbidity, or the content of O2 and CO2. The creation of optimal environmental conditions is crucial for a successful cultivation of the organisms. The smallest deviations have devastating consequences for their survival, and can cause significant economic damage.

As a rule, many of the parameters mentioned are measured directly in the medium using inline probes and sensors. However, their application has a major disadvantage. Mechanical loads (e.g., glass breakage) or solids can lead to rapid material wear and contaminated batches, resulting in high operational costs. With the advent of ​​smart technologies, online analysis systems and maintenance-free sensors have become indispensable to ensure the survival of the microorganisms. In this way, reliably measured values ​​are delivered around the clock, and it is ensured that these are transferred directly to all common process control systems or integrated into existing QM systems.

Rather than manual offline measurement in a separate laboratory, the analysis is moved to an external measuring cell. The sample stream is fed to the analysis system by suction with peristaltic pumps or bypass lines. Online analysis not only enables the possibility of 24/7 operation and thus a close control of the critical parameters, but also the combination of different analysis methods and the determination of further parameters. This means that several parameters as well as multiple measuring points can be monitored with one system.

The heart of the analysis systems is the intelligent sensor technology, whose robustness is crucial for the reliable generation of measured values.

pH measurement as a vital key parameter in bioreactors

Knowledge of the exact pH value is crucial for the product yield, especially in fermentation processes. The activity of the organism and its metabolism are directly dependent on the pH value. The ideal conditions for optimal cell growth and proper metabolism are within a limited pH tolerance range, which must be continuously monitored and adjusted with the help of highly accurate sensors.

However, the exact measurement of the pH value is subject to a number of chemical, physical, and mechanical influencing factors, which means that the determination with conventional inline sensors is often too imprecise and can lead to expensive failures for users. For example, compliance with hygiene measures is of fundamental importance in the pharmaceutical and food industries. Pipelines in the production are cleaned with solutions at elevated temperatures. Fixed sensors that are exposed to these solutions see detrimental effects: significantly reduced lifespan, sensitivity, and accuracy.

Intelligent and maintenance-free pH electrodes

Glass electrodes are most commonly used for pH measurement because they are still by far the most resistant, versatile, and reliable solution. However, in many cases changes due to aging processes or contamination in the diaphragm remain undetected. Glass breakage also poses a high risk, because it may result in the entire production batch being discarded.

The aging of the pH-sensitive glass relates to the change in the hydration layer, which becomes thicker as time goes on. The consequence is a sluggish response, drift effects, or a decrease in slope. In this case, calibration or adjustment with suitable buffer solutions is necessary. Especially if there are no empirical values ​​available, short intervals are recommended, which significantly increase the effort for maintenance work.

With online process analyzers, the measurement is transferred from the process to an external measuring cell. This enables a long-lasting pH measurement to be achieved with an accuracy that is not possible with classic inline probes.

In many process solutions, measurement with process sensors takes place directly in the medium. This inevitably means that the calibration and maintenance of electrodes is particularly challenging in places that are difficult to access, leading to expensive maintenance work and downtimes. Regular calibration of the electrodes is recommended, especially when used under extreme conditions or on the edge of the defined specifications.

If the measurement is carried out with online process analyzers, then calibration, adjustment and cleaning are carried out fully automatically. The system continuously monitors the condition of the electrode. Between measurements, the electrode is immersed in a membrane-friendly storage solution that avoids drying out, and at the same time prevents the hydration layer from swelling further as it does not contain alkali ions. The electrode is always ready for use and does not have to be removed from the process for maintenance work.

The 2026 pH Analyzer from Metrohm Process Analytics is a fully automatic analysis system, e.g., for determining the pH value as an individual process parameter.

Maintenance and digitalization

In addition to the automatic monitoring of critical process parameters, transparent communication between the system and the analyzer also plays a decisive role in terms of maintenance measures. The collection of vital data from the analyzer to assess the state of the system is only one component. The continuous monitoring of relevant system components enables conclusions to be drawn about any necessary maintenance work. For example, routine checks on the condition of the electrodes (slope / zero point check, possibly automatic calibration) are carried out regularly during the analysis process. Based on the data, calibration and cleaning processes are performed fully automatically, which allow robust measurement even at measuring points that are difficult to access or in aggressive process media. This means that the operator is outside the danger zone, which contributes to increased safety.

Summary

The linking of production processes with digital technology holds a particularly large potential and contributes to the economic security of companies. In addition, the pressure is growing steadily for companies to face the demands of digitalization in production. As an example, in the area of ​​fermentation processes, the survival of the microorganisms is ensured by closely monitoring relevant parameters. Intelligent systems increase the degree of automation and can make the process along the entire value chain more efficient.

Find out in the next installment how functional safety concepts help to act before a worst case scenario comes true where errors occur and systems fail. Check it out here!

Read what our customers have to say!

We have supported customers even in the most unlikely of places⁠—from the production floor to the desert and even on active ships!

Post written by Dr. Kerstin Dreblow, Product Manager Wet Chemical Process Analyzers, Deutsche Metrohm Prozessanalytik (Germany).

Moisture Analysis – Karl Fischer Titration, NIRS, or both?

Moisture Analysis – Karl Fischer Titration, NIRS, or both?

In addition to the analysis of the pH value, weighing, and acid-base titration, measurement of water content is one of the most common determinations in laboratories worldwide. Moisture determination is important for nearly every industry, e.g., for lubricants, food and feed, and pharmaceuticals.

Figure 1. Water drops in a spider web

For lubricants, the water concentration is very important to know because excess moisture expedites wear and tear of the machinery. For food and feed, moisture content must be within a narrow range so that the food does not taste dry or stale, nor that it is able to provide a breeding ground for bacteria and fungi, resulting in spoilage. For pharmaceuticals, the water content in solid dosage forms (tablets) and lyophilized products is monitored closely. For the latter, the regulations state that the moisture content needs to be below 2%.

Karl Fischer Titration

Karl Fischer (KF) Titration for water determination was introduced back in the 1930’s, and to this day remains one of the most tried and trusted methods. It is a fast and highly selective method, which means that water, and only water, is determined. KF titration is based on the following two redox reactions.

In the first reaction, methanol and sulfur dioxide react to form the respective ester. Upon addition of iodine, the ester is oxidized to the sulfate species in a water-consuming reaction. The reaction finishes when no water is left.

Figure 2. Manual sample injection for volumetric KF Titration

KF titration can be used for the determination of the water content in all sample types: liquids, solids, slurries, or even gases. For concentrations between 0.1% and 100%, volumetric KF titration is the method of choice, whereas for lower moisture content between 0.001% and 1%, coulometric KF titration is recommended.

Depending on the sample type, its water content, and its solubility in the KF reagents, the sample can either be added directly to the titration vessel, or would first need to be dissolved in a suitable solvent. Suitable solvents are those which do not react with the KF reagents — therefore aldehydes and ketones are ruled out. In case the sample is dissolved in a solvent, a blank correction with the pure solvent also needs to be performed. For the measurement, the sample is injected directly into the titration vessel using a syringe and needle (Fig. 2). The endpoint is detected by a polarized double Pt pin electrode, and from this the water concentration is directly calculated.

Insoluble or hygroscopic samples can be analyzed using the gas extraction technique with a KF Oven. Here, the sample is sealed in small vial, and the water is evaporated by heat then is subsequently carried to the titration cell.

Figure 3. Fully automated KF Titration with the Metrohm 874 KF Oven Sample Processor

For more information, download our free Application Bulletins: AB-077 for volumetric Karl Fischer titration and AB-137 for coulometric Karl Fischer analysis.

If you would like some deeper insight, download our free monograph: “Water determination by Karl Fischer Titration”. 

Near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) is a technique that has been used for myriad applications in the areas of food and feed, polymers, and textiles since the 1980’s. A decade later, other segments began using this technique, such as for pharmaceutical, personal care, and petroleum products.

NIRS detects overtones and combination bands of molecular vibrations. Among the typical vibrations in organic molecules for functional groups such as -CH, -NH, -SH, and -OH, it is the -OH moiety which is an especially strong near infrared absorber. That is also the reason why moisture quantification is one of the key applications of NIR spectroscopy.

For a further explanation, read our previous blog entry on this subject: Benefits of NIR spectroscopy: Part 2.

NIR spectroscopy is used for the quantification of water in solids, liquids, and slurries. The detection limit for moisture in solids is about 0.1%, whereas for liquids it is in the range of 0.02% (200 mg/L), However, in special cases (e.g., water in THF), moisture detection limits of 40–50 mg/L have been achieved.

This technique does not require any sample preparation, which means that samples can be used as-is. Solid samples are measured in high quality disposable sample vials, whereas liquids are measured in high quality disposable cuvettes. Figure 4 displays how the different samples are positioned on the analyzer for a measurement.

Detailed information about the NIRS technique has been described in our previous blog article: Benefits of NIR spectroscopy: Part 1.

Figure 4. Solid (left) and liquid (right) sample positioning for NIR measurements

NIRS is a secondary technique, meaning it can only be used for routine analysis for moisture quantification after a prediction model has been developed. This can be understood by an analogy to HPLC, for which measuring standards to create a calibration curve is among the initial steps. The same applies to NIRS: first, spectra with known moisture content must be measured and then a prediction model is created.

The development of prediction models has been described in detail in our previous blog article: Benefits of NIR spectroscopy: Part 3.

The schematic outline is shown in Figure 5.

Figure 5. Workflow for NIR Method implementation for moisture analysis

For creation of the calibration set, around 30–50 samples need to be measured with both NIRS and KF titration, and the values obtained from KF titration must be linked to the NIR spectra. The next steps are model development and validation (steps 2 and 3 in Figure 5), which are quite straightforward for moisture analysis. Water is a strong NIR absorber, and its peaks are always around 1900–2000 nm (combination band) and 1400–1550 nm (first overtone). This is shown in Figure 6 below.

Figure 6. NIR Spectra of moisturizing creams, showing the absorptions related to H2O at 1400–1550 nm and 1900–2000 nm

After creation and validation of the prediction model, near-infrared spectroscopy can be used for routine moisture determination of that substance. The results for moisture content will be obtained within 1 minute, without any sample preparation or use of chemicals. Also, the analyst does not need to be a chemist, as all they need to do is place a sample on the instrument and press start.

You can find even more information about moisture determination by near-infrared spectroscopy in polyamides, caprolactam, lyophilized products, fertilizers, lubricants, and ethanol/hydrocarbon blends below by downloading our free Application Notes.

Your choice for moisture measurements: KF Titration, NIRS, or both!

As summarized in Table 1, KF Titration and NIR Spectroscopy each have their advantages. KF Titration is a versatile method with a low level of detection. Its major advantage is that it will always work, no matter if you have a sample type that you measure regularly or whether it is a sample type that you encounter for the first time.

Table 1. Overview of characteristics of moisture determination via titration and NIR spectroscopy

NIR spectroscopy requires a method development process, meaning it is not suitable for sample types that always vary (e.g., different types of tablets, different types of oil). NIRS however is a very good method for sample types that are always identical, for example for moisture content in lyophilized products or for moisture content in chemicals, such as fertilizers.

For the implementation of a NIR moisture method, it is required that samples are measured with KF titration as the primary method for the model development. In addition, during the routine use of a NIR method, it is important to confirm once in a while (e.g., every 50th or every 100th sample) with KF Titration that the NIR model is still robust, and to ensure that the error has not increased. If a change is noticed, extra samples need to be added to the prediction model to cover the observed sample variation.

In conclusion, both KF Titration and NIR spectroscopy are powerful techniques for measuring moisture in an array of samples. Which technique to use depends on the application and the individual preference of the user.

For more information

Download our free white paper:

Karl Fischer titration and near-infrared spectroscopy in perfect synergy

Post written by Dr. Dave van Staveren (Head of Competence Center Spectroscopy), Dr. Christian Haider (Head of Competence Center Titration), and Iris Kalkman (Product Specialist Titration) at Metrohm International Headquarters, Herisau, Switzerland.