NIR specrtoscopy

8/9/2019 NIR specrtoscopy

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MOISTURE CONTENT DETERMINATION IN FLUID BED DRYER BY

NEAR INFRARED SPECTROSCOPY (NIRS)

Kaushal P. Bhalani

PG Scholar, Production Engineering Department, VJTI, Mumbai University

Abstract: Current direct techniques for moisture determination in dryers are off-line (Karl Fischer, LOD)and require stopping the drying process to remove samples, which significantly increase cycle times.

Manually collected samples are susceptible to changes in physical conditions like humidity and

segregation, which will lead to inaccurate moisture analysis. Samples typically are withdrawn from the

fluid bed with a thief during processing and analyzed off-line in a laboratory for moisture content.

Commonly there is a delay before analysis results are available to the operator that causes processing

decisions, like end-point determination, to be made without optimal product moisture information. NIR

(Near infrared) spectroscopy can be a used to determine moisture content in fluid bed drying operations

accurately, on-line and in real time. NIRS is safe, non-invasive and requires minimal operator

involvement. NIRS provides information on the process, both physical and chemical, while it is going on.

This provides the ability to monitor critical parameters, and end-point is determined when the desired

state is achieved. Knowing exactly when a dryer has reached its endpoint will save companies energy,

eliminate the destruction of product due to over-drying, and increase the overall efficiency of the drying

process. Over or under drying of granules can be avoided thoroughly. NIR fits in well with the Process

Analytical Technology (PAT) initiative as developed by FDA.

Keywords: LOD (loss on drying), NIRS (Near infrared spectroscopy), Fluid bed dryer, moisture

measurement.

Introduction of Fluid Bed Dryer (FBD):

Dryer: It is an assembly of equipments used for removal of moisture from solids by evaporation.

Drying is defined as the removal of small amounts of water or other liquid from a material by the

application of heat.

Fluid bed dryers are found throughout all industries, from heavy mining through food, fine chemicals and

pharmaceuticals. They provide an effective method of drying relatively free flowing particles with a

reasonably narrow particle size distribution. In general, fluid bed dryers operate on a through-the-bed

flow pattern with the gas passing through the product perpendicular to the direction of travel. The dry

product is discharged from the same section.


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Principle of operation FBD:

The required volume of air is produced by means of high capacity statically and dynamically balanced

fan. The fresh air is passed through Pre-Filter which removes traces of impurities from air. The purified

air is heated by means of electrical/steam heaters. The temperature of air is controlled by means of

digital temperature indicator-cum-controller. The hot air passes through the product container. The air is

passed from the bottom of the container, which has got perforations and S.S. fine mesh. Due to the airstream the wet product gets fluidized and as the material is surrounded by hot air in fluidization chamber

its gets quickly & uniformly dried, due to rapid heat transfer. The moist air passes through Air Discharge

Bag to exhaust duct. A typical Dry Process involves the following steps:

1. Preheat (to prevent product from sticking to sides of fluid bed)

2. Loading

3. Drying (Fluidizing)

4. Cool down (Heat off)

5. Unloading

Photographic view of FBD


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Conventional or existing practice for moisture measurement:

With the sample taken out from the bowl an operator used to measure the moisture value in LOD (loss

on drying) instrument. LOD can measure the value of moisture in the granule. How much moisture left in

the product is known by LOD device.

Based on the moisture value given by LOD, operator restarts the FBD machine. After some time based

on assumption operator turns off the FBD & remove the product. He finally used to measure the value of

moisture in the product & enters moisture value in log sheet.

Loss on drying method:

In this method, wet slab of material of sufficient high moisture content to be dried is placed in a tray

whose bottom & sides are insulated. The air is blown over the solid under constant drying conditions (air

velocity, temperature, humidity, pressure are maintained constant). The superficial water diffuses

through the surrounding stationary air film & is carried away rapidly by the moving air stream.

Periodically the slab is weighed. The weights of successive periods gives the loss of moisture content

i.e. amount of dried. The moisture present in the solid can be expressed on a wet weight or dry weight

basis. Then the following calculations are made.

Loss on drying % (LOD) = mass of water in sample in kg / total mass of wet sample kg *100 %

Drying rate = weight of water in sample kg / time in hr./ weight of dry solid kg.

Data collection & analysis:

Samples collected from different 8 batches at the end of drying process.

Desire LOD% Actual LOD% Deviation Remark

Batch 1 3.4 3.2 0.2 Under dry


Batch 3 2.5 2.6 0.1 Over dry







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From above data, I can say that every time product is under dry or over dry. Operator cant have

the exact moisture value in the granules.

Morever when operator does the moisture measurement in Loss On Drying (LOD) device, it

takes time based on the content of moisture presence in the product. Approximate time to

measure the moisture value varies from 15 to 30 minutes.

So for 15 to 30 minutes FBD machine is idle. There is productivity loss.

Moreover, Continuous monitoring is required. One well experienced operator presence is

essential.

Concerns or Limitations in existing process:

Well experienced operator needed.

Real time moisture % value cant be measure.

Every time material is over dry or under dry. We dont have the exact moisture value.

In certain cases many times machine turn off & on to get the sample & to measure moisture

value.

Heat sensitive material cant be treated well.

There is personal error to measure the moisture % because it depends on operator that how he

is doing exercise to measure the moisture.

There is no standardized practice in drying cycle.

Material movement is increasing.

No data log is available.

Continuous monitoring is required.

Process time is increasing.

Untouched product transfer can maintain highest level of operational hygiene.

Problems with current method:

Conventional process has no consistency in drying procedure, Morever it is carried out by

randomly.

Over or under drying can lead to loss of the entire batch.

Improper amounts of moisture can also alter physical properties like hardness and friability in

tablets.

To treat heat sensitive materials successfully, the temperatures and exposure time must be

carefully controlled.

Current direct techniques for moisture determination in dryers are off-line (Karl Fischer, LOD)

and require stopping the drying process to remove samples, which significantly increase cycle

times.


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Manually collected samples are susceptible to changes in physical conditions like humidity and

segregation, which will lead to inaccurate moisture analysis.

Physical handling of highly potent samples can raise safety and hygiene issues.

If the granules are not dry enough the product will not flow properly and can cake and cause

problems with subsequent processing, including product sticking to the faces of the tablet press

punches and problems with product stability during storage.

Commonly there is a delay before analysis results are available to the operator that causes

processing decisions, like end-point determination, to be made without optimal product moisture

information.

Methodology employed to solve problems:

NIR (Near infrared) spectroscopy can be a used to determine moisture content in fluid bed drying

operations accurately, on-line and in real time. NIRS is safe, non-invasive and requires minimal operatorinvolvement. NIRS provides information on the process, both physical and chemical, while it is going on.

This provides the ability to monitor critical parameters, and end-point is determined when the desired

state is achieved. Knowing exactly when a dryer has reached its endpoint will save companies energy,

eliminate the destruction of product due to over-drying, and increase the overall efficiency of the drying

process. Over or under drying of granules can be avoided thoroughly.


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Introduction of Near Infrared Spectroscopy:

Near-infrared (NIR) spectroscopy is a rapid non-destructive technique often used for in-process analysis

of moisture in the manufacturing environment. Real-time measurements can be made with no sample

preparation and the data can be analyzed and stored automatically. NIR fits in well with the Process

Analytical Technology (PAT) initiative as developed by FDA. One of the elements of the PAT initiative is

to use in-line analysis to increase process understanding and control to verify product quality and

release it for subsequent processing without delay. Using NIR, the process can be monitored for residual

moisture and yield better process control and end-point determination.

Definition of NIRS:

Near-infrared spectroscopy is the measurement of the wavelength and intensity of absorption of near-

infrared light by a sample. Near-infrared spectroscopy (NIRS) is a spectroscopic method that uses the

near-infrared region of the electromagnetic spectrum (from about 800 nm to 2500 nm). Typicalapplications include pharmaceutical, medical diagnostics (including blood sugar and oximetry), food and

agrochemical quality control, as well as combustion research.

Wavelength in nanometer

Principles of NIR spectroscopy:

Infrared energy is the electromagnetic energy of molecular vibration. Molecules have several common

quantized vibration and rotation states that can occur separately or in combination. A molecule with an

electric dipole moment can go through one or more transitions between various vibro-rotational states, if

enough electromagnetic radiation at a specific frequency is absorbed by the molecule. The energy levels

of different vibration and rotation states are quantized, and energy levels can be determined using the

following equation:


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Where:

n is the vibrational quantum number

h is the Planck's constant

f is a bond's force constant, and

is the reduced mass of the vibrating nucleus.

These transitions can occur with high probability for n equal to 1, whereas such absorption is referred to

as fundamental absorption when n=1 or overtone when n=2, 3, 4 m. respectively. The electromagnetic

radiation absorbed for vibration state changes are in the infrared region, while NIR spectroscopy

utilizes absorption bands whose absorption is mostly due to overtones. NIR instruments can usually

operate with electromagnetic radiation wavelengths between 700 nm and 2500 nm.

The molecular overtone and combination bands seen in the near IR are typically very broad, leading to

complex spectra; it can be difficult to assign specific features to specific chemical components.

Multivariate (multiple wavelength) calibration techniques (e.g., principal components analysis, partial

least squares, or artificial neural networks) are often employed to extract the desired chemical

information. Careful development of a set of calibration samples and application of multivariate

calibration techniques is essential for near-infrared analytical methods.

NIR instrumentation:

In a typical NIRS measurement application there are four basic parts to the measurement system:

1. The illumination unit

2. The sample or process interface

3. The dispersive component

4. The detection unit.

The illumination unit provides the light, which is then led to the sample interface in some way, for

example by the use of mirrors or by using fiber-optics. The illumination optics of the sample interface

focuses the light on the sample, and the transmitted or scattered light is then collected with the collection

optics of the sample interface. The detection unit converts the collected radiation into an electrical signal.

In a spectroscopic measurement, the dispersive component has to be included in some point of the

illumination - sample interface - detection chain.


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The operation principle of a spectral camera.

NIR Techniques and theory:

NIR reflectance instruments have detectors that measure the intensity of the NIR radiation that is

reflected from the sample at several key wavelengths. The actual constituent contents can be analyzed

and calculated based on the calibration equation, given the reflectance at the key wavelengths.

However, NIR transmission instruments measure the intensity of NIR radiation transmitted through a

sample at several key wavelengths. A calibration equation is then created to relate log of reflectance

values at several key wavelengths to the actual constituent fractional content values, usually done bycomparing with wet chemistry analysis from a standard sample set using a primary reference method.

Since NIR transmission instruments measure the NIR portion of the electromagnetic radiation that is

actually transmitted through the sample, the path length needs to be kept constant, and also selected for

a high signal-to-noise ratio. NIR spectroscopy instruments can also be referred to as discrete-

region/filter systems, or continuous spectrum detection systems, based on the mechanisms by which

they separate wavelengths. Discrete filter instruments select wavelengths by passing visible white light

(produced, for example, by a tungsten-halogen bulb) through a filter, allowing only a predetermined,

narrow region wavelength to pass through. Discrete filter instruments do not collect data at all

wavelengths, but only at or near the wavelengths of interest. The biggest advantage of a discrete filter

instrument is the high reproducibility of its narrow wavelength ranges. The main limitation of a filter-

based NIR instrument is that absorption data is only collected at a few specified, narrow range

wavelengths, and so the initial wavelength range selection may be difficult if the sample matrix is

unknown. Filter-based, discrete wavelength instruments also tend to be slow if they are not utilized in

conjunction with simultaneous diode-array (DA) detection for several wavelength ranges. Another

limitation of these filter-based instruments is their limited spectral resolution. For broad NIR absorption

bands, the spectral resolution limitation may not be a problem, especially if the selected filters satisfy the

spectral sampling criterion.


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Near-infrared spectroscopic measurements usually deal with inhomogeneous, scattering and absorbing

samples. Such samples are often referred to as turbid samples. This is in contrast to homogeneous

liquid or solid samples, where light scattering does not occur. Nevertheless, the spectroscopic practices

originally developed for non-turbid samples are often employed with turbid samples. Specifically, the

measured reflectance or transmittance signals are converted into absorbance,

Where; I is the measured intensity and IR is the intensity of the reference sample.

The resulting quantity A, is said to be in absorbance units,

If a sample contains more than one absorbing component, then the absorption at a given wavelength will

be the total sum of the proportional contributions from all components in the sample.

EXPERIMENT

Modern Day Near-Infrared Diode Array Spectrometers:

In concept, diode array spectrometers are simple instruments. They consist of a diffraction grating to

disperse the light, a focusing and collimating optical element, which could be the grating itself, and a

diode array and associated electronics as the detector. Figure below shows the essential components ofsuch system.

a. illumination source, b. sample, c. diffuse reflectance, d. input aperture,

e. diffraction grating and collimating optics, f. diode array


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The following are some of the advantages of using a diode array system:

One interrogates all wavelengths simultaneously.

It is a snapshot of your sample, thereby reducing errors.

Fast data acquisition.

High performance, high signal to noise.

No moving parts, rugged, reliable.

Compact, portable.

Diode Array Spectrometer with sampling head

The system included a near infrared spectrometer with a T.E. cooled, 256 element InGaAs diode array

detector, a self referencing probe with two tungsten halogen lamps, a Hg-Ar line source for automatic

wavelength calibration and a spectralon white paddle for acquiring reference, linearity and noise data.

On-line analysis of moisture in the fluid bed dryer was performed through a viewing port on the fluid bed

dryer.


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Data Analysis:

The data was preprocessed by performing a first derivative on the spectra. The first derivative math

treatment is used commonly in NIR spectroscopy to minimize baseline offset caused by scattering and

enhance absorbance peaks

First Derivative Spectra

Figure 2 shows an enlargement of a spectral region that was used to model the moisture in the samples.

A two-factor partial least squares (PLS) regression model was developed with spectra from a calibration

run and loss-on drying (LOD) reference values (see Table 1).

Table 1


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Figure 1. Second derivative of spectra Figure 2. An analytical wavelength

taken in process in FBD region used for moisture

analysis.

The second derivative intensity over the range 9002100 nm was used to develop a prediction model

with an R2 value of 0.9896 and a standard error of calibration (SEC) of 0.2171. See Figure 3 for a plot of

NIR predicted versus LOD % moisture. Although the prediction model performed well, it would be more

robust with more calibration samples included.

Figure 3. A PLS (partial least square) Figure 4. NIR predicted Vs. LOD values.

Model was developed with Standard error of prediction is

an R value Of 0.9896 & 0.4232.

a SEC (std. error of calibration)

is 0.2171.


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Figure 4 shows the NIR predicted moisture versus LOD value. The standard error of prediction is

0.4232%. The LOD standard error was estimated to be 0.33% moisture. The model accuracy would be

improved with Karl Fischer reference data analyzed in a more timely manner. The endpoint

determination can be made when the moisture level asymptotically approaches a lower limit during the

drying cycle. The change in moisture reaches a minimum when the product is dry.

Result: comparison of values given by NIR & LOD

Advantages of NIR over Laboratory Moisture Analysis:

NIR Karl Fischer / Loss on drying

Non destructive Destructive

Uninterrupted sampling Interrupted sampling

No operator training needed for analysis Chemistry and method training for operator

No sample preparation or solvent Sample preparation or solvent

Results in seconds Results in 15 minutes or more

allows for closed loop control No ability for closed loop controlMulti component analysis on dryer sample Additional tests on samples would take a long time

NIR can be used online, inline or at line Can only be run in the laboratory- cant go online


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Conclusion:

The operator is aided in making the decision to end the drying operation before the product is damaged

or degraded. The delay caused by waiting for lab results before the product can be released for

subsequent processing can be minimized or eliminated. Output from the NIR computer could be used by

the fluid bed dryers programmable logic controller (PLC) for closed loop process control decisions. This

provides the ability to monitor critical parameters, and end-point is determined when the desired state is

achieved. Knowing exactly when a dryer has reached its endpoint will save companies energy, eliminate

the destruction of product due to over-drying, and increase the overall efficiency of the drying process.

NIR fits in well with the Process Analytical Technology (PAT) initiative as developed by FDA. One of the

elements of the PAT initiative is to use in-line analysis to increase process understanding and control to

verify product quality and release it for subsequent processing without delay. NIR has proven to be

excellent across a wide range in moisture (1-23%).

References:

1. A.G. Rogers, Granulation and Drying Principles, Hands-on Postgraduate Course in TabletTechnology, Univ. Tenn., Memphis (2003).

2. S.M. Maggard, D. E. Root, and M. Duell, J. Process Analytical Chemistry 7(1) (2002).

3. K.A. Bakeev, Spectroscopy 19(1) (2004).

4. M.L. Balboni, Pharm. Tech. 27(10) (2003).

5. US FDA Draft Guidance PAT A Framework for Innovative Pharmaceutical Manufacturing andQuality Assurance, August 2003,http://www.fda.gov/cder/OPS/PAT.htm.

6. H. Forcinio, Spectroscopy 18(9) 1624 (2003).

7. R.C. Lyon, E.H. Jefferson, C.D. Ellison, L.F. Buhse, J.A. Spencer, M.M. Nasr, and A.S. Hussain, Am.Pharm. Rev. 6(3) (2003).

8. A.M. Afnan, J. Process Analytical Technology 1(1) (2004).

9. R.A. Mattes, R. Schroeder, V. Dhopeshwarkar, R. Kowal, and W. Randolph, Monitoring GranulationDrying Using Near-Infrared Spectroscopy for In Situ Analysis of Residual Moisture and Methanol,

Pharmaceutical Technology, Process Analytical Technology Supplement, September 2004.

10. T.C. OHaver and T. Begley, Anal. Chem. 53, 18761878 (1981). 11. H. Mark and J. Workman Jr.,Spectroscopy 18(4) (2003).
http://www.fda.gov/cder/OPS/PAT.htmhttp://www.fda.gov/cder/OPS/PAT.htm

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