RamanIdentityQualityChecker

Raman Identity

LabEx laboratory QC CSV→JSON URS & FS spectroscopy utilities / cleanroom
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Raman Identity Quality Checker — Substance Identification by Raman Spectroscopy

ℹ️  Utility checks critical parameters of Raman spectral identification:
   • Hit Quality Index (HQI / Correlation): ≥0.95
   • Identification: Matched material name must strictly equal expected material
   • Signal-to-Noise Ratio (S/N): >10
   • Fluorescence: Absence of strong background fluorescence (Flag = 0)

⚠️  CRITICAL: Low HQI (<0.95) or presence of fluorescence → BATCH REJECTION or need for alternative method!
   Raman spectroscopy is sensitive to fluorescent impurities.

Usage:
 RamanIdentityQualityChecker.exe                            → demo mode (console output)
 RamanIdentityQualityChecker.exe input.csv output.json      → evaluate your data

Input format:
BatchNumber,ExpectedMaterial,CorrelationIndex,MatchedMaterial,SignalToNoiseRatio,HighFluorescenceFlag

Example:
 RAMAN-API-2026-001,Ibuprofen,0.98,Ibuprofen,50.0,0

— WHY IS THIS NEEDED?
Raman spectroscopy is a powerful tool for non-destructive control and identification.
• Allows analysis through transparent packaging (glass, plastic), accelerating incoming QC.
• Less sensitive to water, making it ideal for aqueous solutions and hydrates.
• Complementary to IR spectroscopy: different types of vibrations are active.
• Using spectral libraries automates the process and reduces operator error risk.

⚠️  CRITICAL:
• HQI ≥0.95 — standard threshold for confident identification.
• Sample or packaging fluorescence can completely "swamp" the Raman signal.
• Strict name matching (Expected == Matched) eliminates method selection error risk.
• Laser power must be adjusted to avoid thermal degradation of the sample.

Key features:
• Automatic check of spectrum compliance with library reference.
• Control of signal quality (S/N) and presence of fluorescence.
• Integration with warehouse management systems and LIMS.

Critical parameters:
• Correlation Index (HQI): >= 0.95
• Name Match: True
• Signal-to-Noise: > 10
• Fluorescence: None (Flag 0)

💡 Usage tips:
1. Regularly update spectral library by adding references from different suppliers.
2. For fluorescent samples, try using a laser with different wavelength (e.g., 785 nm or 1064 nm instead of 532 nm).
3. Clean probe window before each measurement.
4. If HQI is low, visually inspect sample and repeat measurement at different spot.
5. Use this utility for primary screening; confirm results with IR method if in doubt.

⚠️ Note: Unlike IR spectroscopy, Raman is weakly affected by water but suffers greatly from fluorescence. This makes the methods complementary.

input.csv

BatchNumber,ExpectedMaterial,HQI,MatchedMaterial,SN_Ratio,FluorescenceFlag
RAMAN-API-2026-001,Ibuprofen,0.98,Ibuprofen,50.0,0
RAMAN-EXC-2026-001,Microcrystalline_Cellulose,0.97,Microcrystalline_Cellulose,45.0,0
RAMAN-FAIL-FLUO-001,Some_Dye,0.85,Unknown,5.0,1

URS & FS — Raman Identity

This document describes the user requirements and functional specification for RamanIdentityQualityChecker. The utility is intended for QC laboratory use as a rule-based check of data prepared from an instrument, LIMS, ELN, MES or an approved input.csv.

URS — User Requirements Specification

IDRequirementCriticalityAcceptance criterion
URS-001The utility shall accept input.csv with approved columns: BatchNumber, ExpectedMaterial, HQI, MatchedMaterial, SN_Ratio, FluorescenceFlag.HighThe CSV file is processed without manual header editing.
URS-002The utility shall perform deterministic evaluation for “Raman Identity” without machine learning.HighThe same input data produce the same JSON result.
URS-003The utility shall validate mandatory fields, numeric formats, flags, ranges and domain plausibility.HighSchema and conversion errors are explicitly reported.
URS-004The utility shall generate output.json with PASS / WARNING / FAIL statuses, source values, warnings and failures.HighThe JSON result is suitable for review, deviation investigation and integration.
URS-005The documentation shall support IQ/OQ/PQ or CSV/CSA verification.MediumURS/FS, CSV/JSON contract and test scenarios are supplied with the utility.

input.csv contract

#FieldSamplePurpose
1BatchNumberRAMAN-API-2026-001Input parameter for deterministic QC evaluation.
2ExpectedMaterialIbuprofenInput parameter for deterministic QC evaluation.
3HQI0.98Input parameter for deterministic QC evaluation.
4MatchedMaterialIbuprofenInput parameter for deterministic QC evaluation.
5SN_Ratio50.0Input parameter for deterministic QC evaluation.
6FluorescenceFlag0Input parameter for deterministic QC evaluation.

FS — Functional Specification

IDFunctionImplementation
FS-001CSV importRead input.csv; validate header, column count and encoding.
FS-002Schema validationCheck required fields and permitted input values.
FS-003Rule engineApply domain rules, limits and system suitability/specification checks described in the source utility description.
FS-004Status aggregationProduce final status: FAIL for critical failure, WARNING for non-critical deviation, PASS for conformance.
FS-005JSON exportWrite machine-readable output.json for LIMS/ELN/MES and QA/QC review.

OQ/PQ scenarios

  • OQ-001: a valid sample row shall be processed without schema error.
  • OQ-002: a missing mandatory column shall produce a schema error.
  • OQ-003: a non-numeric value in a numeric field shall produce a conversion error.
  • OQ-004: a critical parameter outside the limit shall produce FAIL or a critical finding.
  • PQ-001: user real batches shall be checked with retention of input.csv, output.json, utility version and checksum.

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