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Inline means the measurement sits in the process itself - the immersion probe stays in the resin reactor and reads 24/7, with no sampling and no reactor stop. This is the full chain for alkyd, acrylic and composite resins: Raman scattering off the reacting medium into a raw spectrum, a CNN chemometric model in Spectrally OS reading the acid value and viscosity endpoint, and process values handed straight to your control system.
Shine monochromatic laser light into the reacting resin. Most of it scatters back unchanged. A small fraction exchanges energy with molecular vibrations and returns shifted - and those shifts are characteristic of the bonds that caused them. The acid and ester carbonyl groups, the monomer C=C, the crosslinking bonds all leave their mark, so the result is a spectrum that works like a fingerprint of the chemistry building in the reactor.
The laser (785 or 1064 nm) illuminates the medium through the immersion probe. Photons that scatter inelastically shift in wavelength by amounts set by the molecular vibrations they met. Plotting intensity against Raman shift (cm⁻¹) gives the raw spectrum, and band intensity tracks how far the reaction has run.
Raman bands are narrow and characteristic of specific bonds, so acid value, viscosity build and monomer conversion can be read from one spectrum. That is the difference from offline viscometry, which returns a proxy for the build and no chemistry behind the number.
Drying-oil alkyds fluoresce strongly, and that fluorescence is exactly where NIR struggles in these plants. The 1064 nm laser shifts excitation away from the fluorescence, so the resin spectrum reads cleanly. In aqueous emulsion polymerization the complementary point holds: water is a weak Raman scatterer and stays out of the way.
Titration, GC and GPC/SEC remain the analytical reference. Inline Raman is real-time process measurement instead of waiting on the lab, so those methods become verification, not the bottleneck. Acid value has no single dedicated band, so a CNN model reads the whole spectrum - built on the acid/ester carbonyl band ratio - rather than picking one peak.
Four links in the chain: an immersion probe in the reactor, fiber optics to the analyzer, chemometric models in Spectrally OS, and your control system at the end. There is no sampling loop anywhere in it.
Immersion probe in the resin reactor or line. IP67, ATEX/IECEx Zone 0, fitted with the self-cleaning module for viscous, fouling media - drying oils, high-solids resin and pigment.
Excitation light travels to the probe and scattered light returns over fiber, so the analyzer can sit away from the solvent-bearing process area while the probe stays in the medium.
785 / 1064 nm laser excitation - the 1064 nm line for strongly fluorescing drying-oil alkyds - with a back-thinned TEC-cooled CCD detector. Up to 2 measurement channels as standard, more on request.
AI and advanced chemometrics with a CNN core translate the spectrum into acid value, viscosity, conversion and PASS-FAIL flags, then hand them to your PLC / DCS.
The numbers that define the measurement path, probe to analyzer. Calibration is automatic, against a reference integrated in the probe - there is no manual recalibration routine to schedule.
| Measurement principle | Raman spectroscopy |
| Laser wavelength | 785 nm / 1064 nm |
| Detector | Back-thinned CCD, TEC-cooled |
| Acquisition time | 5-300 s |
| Fiber optic reach | Up to 100 m |
| Measurement channels | Up to 2 (expandable on request) |
| Probe | Spectrally X1 PROBE, IP67, ATEX/IECEx Zone 0, self-cleaning |
| Calibration | Automatic - reference integrated in probe |
| Communication | PROFIBUS, PROFINET, GSM |

The core technique - molecular vibrations characteristic of specific bonds. For coatings and resins this is the workhorse: Raman with a CNN model on the full spectrum reads acid value and monomer conversion in the reactor.
Surface-enhanced Raman on metallic nanostructures, typically Ag or Au - used when analyte concentrations sit at ppb-ppm levels, below classical Raman sensitivity.
Near-infrared as a complement where Raman bands are weak - for example some O-H bonds.
Complementary sensing for specific challenges. The technique is chosen for the chemistry, not the other way around.
Drying oils, high-solids resin and pigment settle on any optical surface left in the process. In these viscous, fouling media the Raman signal would degrade within hours to days of operation. The self-cleaning module removes that failure mode with a mechanical cycle: retract, rinse, return - and it does so in an ATEX/IECEx Zone 0 medium carrying flammable solvents such as white spirit and xylene.
Deposits and reaction layers build on the probe optics as the resin cooks - drying oils, pigment and high-solids material coat any surface in the medium. A fouled window means drifting spectra first, useless spectra later, in strongly fouling media within hours to days.
The probe retracts from the medium, the optical window is rinsed, and the probe returns to the same measurement position. Geometry stays fixed, so readings stay comparable across the whole campaign.
Strongly fouling reactors - alkyd, acrylic and composite resins - with pigment and high solids, and long production campaigns with no service window in sight. The same probe operates in ATEX/IECEx Zone 0 with a 30 mW laser for the solvent-bearing medium.
Without self-cleaning, a process probe in resin service needs manual cleaning - and manual cleaning means breaking a continuous measurement and opening a hot, solvent-bearing reactor. The module is integrated with Spectrally X1 PROBE and Spectrally X1 INLINE, and it is what makes continuous 24/7 measurement realistic in viscous alkyd and acrylic chemistry.
The cycle runs automatically during production, so there is no manual optics service in the middle of a campaign and no gap in the data your control system sees. For the solvent-bearing media white spirit and xylene bring into the reactor, the probe runs in ATEX/IECEx Zone 0 with the 30 mW ATEX laser.
Spectrum to a process value, continuously.
Up to 60 minutes of titration and GC wait, gone.
Model vs ISO 3682 titration, R 0.982-0.998, MAE about 0.015 mg KOH/g on real resin.
Read from the same spectrum, R 0.988-0.998 on real resin.
Raw spectra are useless to an operator. Spectrally OS translates them into concentrations, ratios, PASS-FAIL classifications and alarms - and keeps a logged, auditable history of the models doing the translating.
Spectrally OS runs on AI and advanced chemometrics with a convolutional-neural-network core. Traditional PLS and PCA chemometrics are the industry benchmark it is measured against. Acid value has no single dedicated band, so the CNN model reads the whole spectrum - built on the acid/ester carbonyl band ratio - where simple peak picking would fail.
The regression role maps the spectrum to values: acid value, hydroxyl value, viscosity build, monomer conversion and solids content - the numbers your specification runs on, several from one read, in seconds.
The classification role flags what does not belong. An endpoint about to overshoot or an off-spec batch surfaces as a deviation and a PASS-FAIL alarm, not as a solvent correction or scrap after the fact.
Models start from feasibility - typically your R&D data plus samples measured in the Gekko lab. Built on your matrix - alkyd, acrylic or composite resin - not a generic library.
Predictions are checked against reference measurements - ISO 3682 titration, GC, GPC/SEC - on your matrix before the model is trusted in production.
Models are reinforced with your production data as it accumulates. Updates deploy without stopping the analyzer or the line.
Scheduled when the recipe, drying-oil batch or process parameters change. A model change - not a platform redesign.

One model layer runs across Spectrally X1 LAB, X1 PORTABLE and X1 INLINE, so a model built during feasibility migrates to the process instrument. Routine operation uses no reagents and no consumables.
| Supported instruments | Spectrally X1 LAB / PORTABLE / INLINE |
| Predictive models | AI / advanced chemometrics, CNN core |
| Spectra database | Proprietary + public, ~28,000 spectra |
| Operator interface | SpectrallyUI |
| Operating system | Debian GNU/Linux 13.2 |
| Calibration | Automatic, from a built-in reference signal |
| Data export | CSV, PDF, RAW |
| User management | Role-based access control (RBAC) |
| Data storage | Local database - logging continues without a network |
| Model updates | Deployed without stopping the analyzer |
Spectrally streams process values - not raw spectra - into the plant's control and data layers. SpectrallyUI shows trends and alerts at the analyzer; the same values reach your PLC / DCS, where a reading can drive a solvent-correction setpoint, hold an off-spec resin batch, or raise an acid-value alarm before the endpoint is overshot.
Values arrive as process signals over PROFIBUS or PROFINET - unified across all Spectrally products. To the operator, the analyzer reads like any other instrument on the loop.
Configured per site: batch context in MES, trending and supervision in SCADA, reconciliation with lab records in LIMS.
GSM is available across the product line alongside the fieldbus protocols. Data exports in CSV, PDF and RAW for reporting and archive.
Segmentation, white-listing, no open ports to the corporate network - typical OT policies are scoped with your automation and IT teams during integration.
IEC 62443 expectations for industrial automation systems are addressed in integration scoping, together with backup and recovery of measurement data.
Measurement and logging run on a local database, so readings continue when the network does not. A continuous, time-stamped inline record strengthens the quality and environmental dossier, and model changes are logged and auditable.
A feasibility study starts with representative samples or R&D data from your alkyd, acrylic or composite resin process. We build and validate the chemometric model in the Gekko lab and show you exactly what the probe-to-DCS chain would read on your reactor - before any hardware decision. Your feasibility study puts the exact numbers for your matrix on the table, validated against your reference method.