From the siloxane band to a value you can act on.
How an immersion Raman probe in the reactor - inline, taken directly in the line with no sample drawn - turns the diagnostic silicone bands into cure state, residual cyclics and chain length on your control system, in seconds.
The questions that define a silicone map onto specific bands.
Shine monochromatic laser light into the silicone medium. 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. Silicones are strong, specific Raman scatterers, so the exact bands a cure or cyclics question needs come back cleanly from one spectrum.
Inelastic scattering carries the information
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.
The three bands a silicone runs on
Cure state reads from the Si-H band at ~2160 cm⁻¹ and the vinyl C=C band at ~1600 cm⁻¹ as they vanish through the addition reaction. Residual cyclics - D4, D5, D6 - separate from linear siloxane at the ~490 cm⁻¹ band. Each band is narrow and characteristic, so several parameters resolve from a single read.
Composition, not a proxy
Raman reads composition directly. Inline viscometry infers a molecular-weight proxy but no composition; NIR bands overlap and do not separate cyclic from linear siloxane. The Raman spectrum carries chain length, functional-group content and cure state at once.
GC/MS and DSC remain the analytical reference. Inline Raman replaces them where decision time and measurement continuity matter - the offline methods become verification, not the bottleneck.
From the reactor wall to the control room.
Four links in the chain: an immersion probe in the process, 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 - the measurement is inline, taken directly in the medium.
Immersion probe in the reactor or line. IP67, ATEX/IECEx Zone 0, self-cleaning module, with a sapphire window option for corrosive chlorosilane and HCl media.
Excitation light travels to the probe and scattered light returns over fiber, so the analyzer can sit away from the process area while the probe stays in the medium.
785 / 1064 nm laser excitation, 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 cure state, residual cyclics and chain-length values plus PASS-FAIL flags, then hand them to your PLC / DCS.
The hardware in the chain
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 |
| Optical window | Fused silica standard, sapphire (Al₂O₃) for corrosive chlorosilane / HCl |
| Calibration | Automatic - reference integrated in probe |
| Communication | PROFIBUS, PROFINET, GSM |
Raman is the core, not the whole toolbox
The core technique and the silicone workhorse - the Si-H, vinyl and siloxane bands read inline, with a CNN doing the interpretation.
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. On silicones it stays a complement - it does not separate cyclic from linear.
Complementary sensing for specific challenges. The technique is chosen for the chemistry, not the other way around.
Curing silicone films optical windows. The probe is built for that.
Curing silicone and siloxane deposits settle on any optical surface left in the process. In strongly 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.
Why optics film
Curing silicone and reaction deposits build on the probe optics as production runs. A filmed window means drifting spectra first, useless spectra later - in strongly fouling media within hours to days.
The cycle preserves measurement geometry
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.
Windows and zones for silicone service
Fused silica is standard; a sapphire (Al₂O₃) window handles corrosive chlorosilane and HCl media. The probe runs ATEX/IECEx Zone 0, on a 30 mW laser where the zone requires it.
A capability, not an accessory
Without self-cleaning, a process probe in silicone service needs manual cleaning - and manual cleaning means breaking a continuous measurement. The module is integrated with Spectrally X1 PROBE and Spectrally X1 INLINE, and it is what makes continuous 24/7 measurement realistic in curing silicone and chlorosilane 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.
Spectrum to a process value, continuously.
Up to 120 minutes of GC/MS wait on residual cyclics, gone.
Trace components resolved down to single ppm across the platform.
From feasibility to a live inline measurement, 3 to 5.5 months.
Spectrally OS turns spectra into operating information.
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.
CNN core - the workhorse
A convolutional network reads the whole band structure at once - is this batch fully cured, does this incoming material match the specification. On complex silicone spectra the CNN core outperforms the PLS/PCA benchmark it is measured against.
Regression to numbers
The model maps the spectrum to numbers - vinyl and silanol content, residual cyclics, chain length and DP - several parameters from a single read.
Anomaly detection
The model reduces a spectrum to its drivers and flags what does not belong - an unexpected fraction in the reactor surfaces as a deviation, not as a customer return.
Models start from feasibility - typically your process data plus samples measured in the Gekko lab. Built on your silicone matrix, not a generic library.
Predictions are checked against your reference method - GC/MS for cyclics, DSC for cure - 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 grade, catalyst or process parameters change. A model change - not a platform redesign.
Spectrally OS at a glance
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 (PLS/PCA benchmark) |
| 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 |
A value counts when it lands in your control system.
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 setpoint correction, an alarm, a quality report or a batch hold.
PLC / DCS
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.
MES / SCADA / LIMS
Configured per site: batch context in MES, trending and supervision in SCADA, reconciliation with lab records in LIMS.
GSM and export
GSM is available across the product line alongside the fieldbus protocols. Data exports in CSV, PDF and RAW for reporting and archive.
Network fit
Segmentation, white-listing, no open ports to the corporate network - typical OT policies are scoped with your automation and IT teams during integration.
Industrial cyber
IEC 62443 expectations for industrial automation systems are addressed in integration scoping, together with backup and recovery of measurement data.
Time-stamped batch record
Measurement and logging run on a local database, so a continuous, time-stamped composition and cure record accrues per batch - and model changes are logged and auditable.
Run the full chain on your own silicone.
A feasibility study starts with representative samples or process data from your silicone stream. Gekko builds the chemometric model on your matrix, benchmarks it against your reference method - GC/MS or DSC - and hands back the spectra, band assignments and the validated numbers behind your Si-H, vinyl and cyclics questions, before any hardware decision.