Ep 52 — Commercial Software Review: OMNIC, OPUS, Spectrum, etc.

Series: Infrared Spectroscopy Encyclopedia: From Principles to Practice
Chapter: Part 5 · Instruments and Tools — Software Ecosystem (Ep 46–55 later)
Target Audience: Instrument purchasing decision makers, lab managers, QC/QA supervisors, technicians seeking to improve data processing efficiency, new graduate students in labs
Prerequisite Knowledge: Ep 17 (Instrument Operation), Ep 18 (Spectrum Processing), Ep 19 (Library Search), Ep 46–47 (Main Brand Comparison), Ep 51 (Troubleshooting)
Reading Time: ~42 minutes

Introduction: Same Sample, Four Software, Four Experiences

An analytical center at a university owns four instruments: Thermo Nicolet iS50, Bruker INVENIO R, PerkinElmer Spectrum 3, and Shimadzu IRSpirit. Graduate student Li is conducting a cross-platform comparison experiment, needing to export the same polystyrene film spectrum as CSV and import it into Python for further analysis.

• On OMNIC: File → Export → CSV, done in 5 seconds. CSV directly has two columns (wavenumber, absorbance);
• On OPUS: File → Export → ASCII XY, dialog requires selecting "Abscissa" start/end, number of points, whether to include header; wrong parameter selection results in data without wavenumbers;
• On Spectrum: File → Save As → select CSV format, but default export is transmittance (%T); need to switch to Absorbance first;
• On LabSolutions IR: Exporting CSV requires first "Print to File", and default uses Japanese comma separator, causing garbled text in some Chinese Excel.

"The functional matrix of FTIR software goes far beyond 'spectrum acquisition' and 'processing'. Data export capability, macro programming ecosystem, accessory auto-recognition, and third-party format compatibility are the true keys to daily efficiency."
— Adapted from Spectroscopy magazine software review [1]

This episode systematically compares four major commercial FTIR software (Thermo OMNIC, Bruker OPUS, PerkinElmer Spectrum, Shimadzu LabSolutions IR), providing a functional matrix comparison table, data export and format conversion practical tips, and introducing online tools like ftir.fun as supplements. Whether you are a purchasing decision maker or daily user, you will find ways to optimize your workflow.

💡 Positioning Note: Ep 46–47 reviews hardware; this episode reviews software. Hardware determines "whether you can measure"; software determines "whether you measure comfortably".

I. Thermo OMNIC: Mature and Comprehensive "Industry Standard"

1.1 Software Overview

OMNIC is the standard software for Thermo Fisher (formerly Nicolet) FTIR series, currently holding the highest market share among FTIR software in China [1][2]. From early OMNIC 5.x to the current OMNIC Paradigm, it has undergone over 20 years of iteration.

Compatible Instruments: Nicolet iS5, iS20, iS50, Nicolet Continuμm micro-FTIR, Nicolet iN10 MX imaging, etc. [2].

Figure 1: OMNIC main interface (Source: Thermo Fisher official website, https://www.thermofisher.com/…)

1.2 Core Advantages

① Smart Accessory Auto-Recognition [1][2]

• When Thermo's Smart accessories (e.g., Smart iTR ATR, Smart Orbit DRIFTS, Smart Spretter specular reflectance) are inserted, OMNIC automatically identifies the model and switches parameters;
• Users do not need to manually set optical path, gain, or default scan number;
• This is one of OMNIC's most praised features, significantly reducing the risk of operational errors.

② Comprehensive Functionality [1][2]

• Acquisition: Transmission, reflection, ATR, DRIFTS, photoacoustic, micro-imaging;
• Processing: Baseline correction (Linear, Rubber Band, Polynomial), smoothing (SG), normalization, ATR correction, derivative, spectral subtraction, addition;
• Analysis: Library search (built-in Aldrich, Hummel, Polymer packaging, etc.), peak detection, quantification (peak height/area/PLS), multivariate analysis;
• Reporting: Auto-generate audit reports compliant with 21 CFR Part 11.

③ Macros [1][3]

• OMNIC has a built-in macro recorder that can record operation sequences and save as .mac files;
• Suitable for repetitive QC tasks (e.g., collect background → collect sample → baseline correction → library search → export report);
• Advanced users can write complex logic using OMNIC Macros language.

Example Macro (pseudo-code) [3]:

Macro "Daily_QC"
  Collect Background, scans=32, resolution=4
  Collect Sample, scans=32, name="QC_sample"
  Baseline Correct, method=RubberBand
  Search Library, libraries=["Aldrich", "InHouse"]
  Export, format=CSV, path="C:\QC\"
  Print Report, template="QC_template.rpt"
End Macro

④ Software Ecosystem [1][2]

• TQ Analyst: Advanced quantitative analysis software (multivariate statistics, PLS, CLS), seamlessly integrated with OMNIC;
• OMNIC Specta: Intelligent spectrum interpretation, automatically identifies mixture components;
• OMNIC for Dispersive Raman: Unified interface with Raman software.

1.3 Limitations

• Advanced features (e.g., Macros, Specta) require additional license purchase;
• Large software size (> 2 GB), slow startup;
• Windows only;
• Some older versions (before OMNIC 8.x) have poor compatibility with new operating systems [1].

II. Bruker OPUS: Powerful but Steep Learning Curve

2.1 Software Overview

OPUS (Optical User Software) is Bruker Optics' flagship software, covering the entire FTIR, FT-Raman, and NIR product lines [1][4]. From ALPHA II to VERTEX 70v, from IFS 66 to INVENIO R, all use OPUS.

Compatible Instruments: ALPHA II, Tensor II, INVENIO R/S, VERTEX 70v, HYPERION micro-FTIR, etc. [4].

Figure 2: OPUS main interface (Source: Bruker official website, https://www.bruker.com/en/pro…)

2.2 Core Advantages

① Measurement Macros [4][5]

• OPUS macro programming capability is the strongest among the four commercial software;
• Based on a dedicated OPUS Macro language, controlling acquisition, processing, and reporting workflows;
• Supports conditional statements, loops, variables, file operations;
• Suitable for automated QC and batch sample testing.

OPUS Macro Example (pseudo-code) [5]:

MACRO Batch_QC
  LOAD METHOD "QC_Method.opm"
  LOOP i = 1 TO 96
    MOVE STAGE TO POSITION i
    ACQUIRE BACKGROUND
    ACQUIRE SAMPLE
    BASELINE CORRECT RUBBERBAND
    EVALUATE QUANT METHOD "Calibration.opu"
    EXPORT RESULT "Sample_" + i + ".csv"
  END LOOP
END MACRO

② Rich Algorithms [1][4]

• OPUS built-in baseline correction algorithms include more than 10 types: Rubber Band, Convex Hull, Polynomial, ALS, Load/Save Point, etc.;
• Differentiation supports SG, Norris, etc.;
• Multivariate analysis (PCA, PLS, CLS) is natively integrated into the OPUS software package.

③ 3D data processing [4]

• OPUS has native support for FPA (Focal Plane Array) imaging data;
• Hyperion 3000 micro-IR + 64×64 FPA acquires 4096 spectra at once, and OPUS can directly process them into a data cube;
• Supports chemical imaging (Chemigram), PCA decomposition, and component extraction.

④ Cross-platform Linux version [4]

• OPUS has a Linux version (for some instrument models), suitable for industrial online applications;
• This is the only one among the four major commercial software suites that supports Linux.

2.3 Disadvantages

• Steep learning curve: interface terminology is abstract (e.g., "AB", "TR" are not intuitive), menu hierarchy is deep [1];
• Chinese support is incomplete; some version menus are still primarily in English;
• Accessory recognition is less intelligent than OMNIC, requiring manual selection;
• High software cost, with advanced modules charged separately.

3. PerkinElmer Spectrum: Intuitive and User-Friendly

3.1 Software Overview

Spectrum (upgraded versions Spectrum 10 / Spectrum LIVE) is the software for PerkinElmer's FTIR product line (now partly merged into Horiba) [1][6].

Instruments supported: Spectrum Two, Spectrum 3, Frontier, Spotlight 200i/400i micro-IR, etc. [6].

Figure 3: PerkinElmer Spectrum software (Source: PerkinElmer official website, https://www.perkinelmer.com/p…)

3.2 Core Advantages

① Intuitive interface [1][6]

• Spectrum software is known for its "large buttons, clear icons, and workflow-oriented" design;
• Suitable for beginners and teaching scenarios;
• "Spectrum LIVE" real-time display mode allows viewing while acquiring, suitable for dynamic process monitoring.

② Good compatibility [1][6]

• Spectrum has good compatibility with third-party data formats;
• Can directly read some Thermo and Bruker data (via plugins);
• Rich data export formats (CSV, JCAMP-DX, SPC, DPT).

③ Spotlight micro-IR integration [6]

• Spotlight 200i/400i micro-IR is deeply integrated with Spectrum software;
• Visual sample stage control, automatic point selection, chemical imaging;
• Powerful automatic mixture identification (AVI) function.

④ 21 CFR Part 11 compliance [1][6]

• Spectrum 11+ version natively supports GMP / FDA 21 CFR Part 11;
• Audit trail, electronic signatures, permission levels;
• Suitable for pharmaceutical industry QC.

3.3 Disadvantages

• PerkinElmer instrument market share is declining, and software update pace has slowed [1];
• Advanced quantitative analysis module (Spectrum Quant) is less powerful than TQ Analyst;
• Some older versions have poor compatibility with new Windows systems.

4. Shimadzu LabSolutions IR: Unified with Chromatography Software

4.1 Software Overview

LabSolutions IR is Shimadzu's FTIR software, a module of the LabSolutions series (including a unified framework for GC, HPLC, FTIR) [1][7].

Instruments supported: IRSpirit, IRAffinity-1S, IRTracer-100, AIMsight micro-IR, etc. [7].

Figure 4: LabSolutions IR main interface (Source: Shimadzu official website, https://www.shimadzu.com/an/p…)

4.2 Core Advantages

① Unified with chromatography software [1][7]

• One LabSolutions platform controls GC, HPLC, and FTIR simultaneously;
• Unified data management, suitable for comprehensive analysis laboratories;
• Reduces training costs (same interface for multiple instrument types).

② Compact design support [7]

• IRSpirit portable FTIR works well with LabSolutions IR;
• Suitable for on-site testing and teaching scenarios.

③ Japanese market share [1]

• Shimadzu FTIR holds a leading market share in Japan;
• LabSolutions IR has high penetration in Japanese laboratories.

④ Macro commands [7]

• LabSolutions IR supports Macro programming;
• Simple batch processing can be achieved via Macro Recorder.

4.3 Disadvantages

• Algorithm richness is less than OMNIC and OPUS;
• Internationalization support is incomplete (some versions default to Japanese punctuation);
• Third-party format compatibility is average [1].

5. Common Functions and Comparison Table

Below is a functional matrix comparison of the four major software suites (based on [1][2][4][6][7]).

Table 1: Function matrix comparison of four major commercial FTIR software suites (based on [1][2][4][6][7])

Selection recommendations [1]:

• Teaching / Routine QC: OMNIC or Spectrum (ease of use priority);
• Research / Complex automation: OPUS (strongest macro programming);
• Microscopy imaging / FPA data: OPUS (best cooperation with Hyperion);
• Multi-instrument comprehensive laboratory: LabSolutions IR (unified with chromatography);
• GMP pharmaceutical: All four supported, depends on company SOP compatibility.

6. Data Export Practice: How to Export to Common Formats

Data export is the most overlooked aspect of FTIR software yet most impactful for subsequent workflows [1][8]. The export format determines whether you can further analyze with Python, R, MATLAB, or other tools.

6.1 Common Formats Overview

|------|------|------|--------|
| CSV / TXT | Comma-Separated Values | Plain text, two columns (wavenumber, absorbance) | ⭐⭐⭐⭐⭐ Universal |
| JCAMP-DX | Joint Committee on Atomic and Molecular Physical Data | International standard spectral format with metadata | ⭐⭐⭐⭐⭐ Universal |
| SPC | Galactic Industries | Older universal binary format | ⭐⭐⭐⭐ Semi-universal |
| OPUS (.opu) | Bruker proprietary | Bruker specific | ⭐ OPUS only |
| OMNIC (.spa) | Thermo proprietary | Thermo specific | ⭐ OMNIC only |
| Spectrum (.sp) | PE proprietary | PE specific | ⭐ Spectrum only |
| DPT | Data Pointer Table | Supported by some software | ⭐⭐⭐ Semi-universal |

Table 2: FTIR data format comparison (compiled from [1][8])

💡 Key Principle: Proprietary formats carry long-term storage risks. Vendor discontinuation, software upgrades, or format deprecation can render data unreadable. It is recommended to also export every important dataset as CSV or JCAMP-DX as a "safety backup" [1][8].

6.2 Exporting CSV from OMNIC [2]

1. Open the spectrum, ensure it is in absorbance mode (not %T);
2. File → Export → CSV;
3. Select save path, enter filename;
4. Default output format: two columns, first column wavenumber (high to low), second column absorbance;
5. Verify with a text editor:

4000.000000,0.012345
3999.000000,0.012456
3998.000000,0.012567
...
400.000000,0.087654

6.3 Exporting ASCII XY from OPUS [4]

1. Open the spectrum;
2. File → Export → ASCII XY;
3. Dialog settings:
   • "Abscissa Start": 4000
   • "Abscissa End": 400
   • "Number of Points": 3601 (or select "Resolution" for automatic)
   • "Separator": Comma or Space
   • "Header": Checked (includes metadata comments)
4. Example output:

   # OPUS Version 8.5
   # Data block: AB
   # X-axis: Wavenumbers (cm-1)
   # Y-axis: Absorbance
   4000.0,0.012345
   3999.0,0.012456
   ...
   

6.4 Exporting CSV from Spectrum [6]

1. Open the spectrum;
2. Confirm Y-axis is Absorbance (Tools → Y-axis → Absorbance);
3. File → Save As → Select "CSV Files (*.csv)";
4. Save;
5. Note: Default export may include metadata rows (first few lines non-data), skip with Python:

import numpy as np
data = np.loadtxt("sample.csv", delimiter=",", skiprows=5)
wavenumber = data[:, 0]
absorbance = data[:, 1]

6.5 Exporting CSV from LabSolutions IR [7]

1. Open the spectrum;
2. File → Print to File → Select CSV;
3. Note: Default may use Japanese commas (、) or full-width characters, check;
4. When processing with Python, perform encoding conversion if necessary:

# Handle possible Shift-JIS encoding
with open("sample.csv", "r", encoding="shift_jis") as f:
    lines = f.readlines()
# Replace full-width characters
text = "".join(lines).replace("、", ",").replace("　", " ")
with open("sample_utf8.csv", "w", encoding="utf-8") as f:
    f.write(text)

6.6 Batch Export Tips

For dozens or hundreds of spectra, manual export is impractical. Each software supports batch export [1][2][4]:

• OMNIC: File → Batch Process → Select Export action → Select spectrum folder;
• OPUS: Use macro programming (e.g., example in Section 6.2) for batch processing;
• Spectrum: Tools → Macro Recorder → Record export action → Loop execution;
• LabSolutions IR: Use Macro commands for batch processing.

7. Data Format Conversion Tools

If data is already saved in proprietary formats (e.g., .spa, .opu), how to convert? Below are common tools [1][8][9].

7.1 Vendor Tools

① OMNIC to JCAMP-DX [2]

• OMNIC built-in: File → Save As → Select JCAMP-DX (.jdx);
• Includes metadata, good cross-platform compatibility.

② OPUS to JCAMP-DX [4]

• OPUS built-in: File → Export → JCAMP-DX.

③ Bio-Rad KnowItAll [9]

• Commercial software, supports conversion between almost all FTIR formats;
• Can read .spa, .opu, .sp, .spc, etc.;
• Suitable for cross-vendor data integration;
• Relatively expensive.

7.2 Open Source Tools

① Python jcamp library [8]

import jcamp
# Read JCAMP-DX
data = jcamp.jcamp_read("sample.jdx")
print(data['x'])  # wavenumber array
print(data['y'])  # absorbance array

② Python pysptools [8]

• Suitable for hyperspectral data;
• Can read some FTIR imaging formats.

③ Python scikit-kinetic etc. [8]

• Can read .spc format (Galactic SPC).

④ fileobj / binview [1]

• Binary viewing tools, useful for parsing proprietary format headers.

7.3 Command-Line Batch Conversion

For batch conversion of many .spa files to CSV, use Python + PyMS steps [1][8]:

import os
import subprocess

# Assuming spa2csv.exe exists (some Thermo tools include it)
spa_files = [f for f in os.listdir(".") if f.endswith(".spa")]
for spa in spa_files:
    csv = spa.replace(".spa", ".csv")
    subprocess.run(["spa2csv.exe", spa, csv])
    print(f"Converted: {spa} → {csv}")

7.4 ftir.fun Online Tool Supplement

🔗 Extension: ftir.fun provides web-based spectral data parsing and visualization, supporting upload of universal formats like JCAMP-DX. No software installation needed for quick viewing and comparison. Suitable for:

• Quick review of client spectra during business trips;
• Cross-device access (phone/tablet);
• Sharing spectra with colleagues (shareable link);
• Combined search with databases such as NIST WebBook.

ftir.fun's core positioning is as a "Chinese-friendly spectral tool supplement," serving as an efficient complement to commercial software [10].

VIII. Macro Programming and Automation: Freeing Yourself from Repetitive Tasks

QC labs process hundreds of samples daily, with repetitive operations taking up a lot of time. Macro programming can automate these operations [1][3][5].

8.1 When to Use Macros

• Batch testing of the same sample type (e.g., 96-well plate ATR screening);
• Standardized QC workflow (fixed background → sample → processing → report);
• Method validation (same standard measured 6 times consecutively + automatic statistics);
• Data archiving (auto-naming, archiving, backup after acquisition).

8.2 OMNIC Macro Example: Daily QC Automation [3]

Macro "Daily_QC_v2"
  ' 1. Instrument self-check
  If Diagnostics.Failed Then
    MsgBox "Instrument diagnostics failed!"
    Exit Macro
  End If

  ' 2. Collect background
  Collect Background
    Scans = 64
    Resolution = 4
    Name = "BG_" + Date$
  End Collect

  ' 3. Prompt to place sample
  MsgBox "Place QC sample on ATR, press OK to start."

  ' 4. Collect sample
  Collect Sample
    Scans = 32
    Resolution = 4
    Name = "QC_" + Date$
    Background = "BG_" + Date$
  End Collect

  ' 5. Spectral processing
  BaselineCorrect Method=RubberBand
  Smooth Method=SG, Window=9, Order=2
  ATRCorrect

  ' 6. Library search
  SearchLibrary
    Libraries = ["Aldrich_Condensed", "InHouse_Polymers"]
    Threshold = 0.85

  ' 7. Export and report
  Export Format=CSV, Path="C:\QC\" + Date$ + "\"
  PrintReport Template="QC_Daily.rpt"

  ' 8. Performance validation (polystyrene)
  If DateDiff("d", LastValidation, Now) > 30 Then
    MsgBox "30-day validation due. Run PS film validation."
  End If
End Macro

8.3 OPUS Macro Example: FPA Imaging Batch Processing [4][5]

MACRO FPA_Batch_Analysis
  LOAD METHOD "Imaging_Method.opm"
  LOOP sample = 1 TO 10
    LOAD SAMPLE "Sample_" + sample + ".opu"
    ' Extract component 1 (polyester)
    EXTRACT COMPONENT 1
    EXPORT CHEMIGRAM "Polyester_" + sample + ".csv"
    ' PCA decomposition
    PCA COMPONENTS 5
    EXPORT LOADINGS "PCA_loadings_" + sample + ".csv"
  END LOOP
END MACRO

8.4 Pitfalls in Macro Programming

• Version compatibility: Macros often break with software version upgrades; need to re-record [1];
• Hardcoded paths: Macros with hardcoded paths fail on different machines; use relative paths or environment variables;
• Error handling: Simple macros often lack error handling, aborting on exceptions; advanced macros should include try-catch;
• Audit trail: In GMP environments, macros themselves need version control and cannot be modified arbitrarily [1].

IX. Practical Advice for Software Selection

9.1 Selection by Scenario

Table 3: FTIR software selection recommendations (synthesized from [1][2][4][6][7])

9.2 Software Purchase Negotiation Tips

1. Software license types [1]:

   • Standalone perpetual license (recommended): one-time payment, perpetual use;
   • Floating license: shared across multiple instruments, requires server;
   • Subscription (annual): higher long-term cost, but always latest version;
   • Modular: base + advanced modules purchased separately, choose as needed.

2. Essential modules [1]:

   • Basic acquisition + processing (must buy);
   • Library search (must buy, include basic libraries);
   • Quantitative analysis (recommended for QC);
   • Macros/automation (recommended for batch testing);
   • Micro-imaging module (must buy if purchasing micro-FTIR).

3. Hidden costs [1]:

   • Upgrade fees (typically 15%–20% annually);
   • Training fees (negotiate 1–2 free training sessions);
   • Database subscriptions (Sadtler, Aldrich, etc., annual);
   • Service contracts (recommend first 2 years free warranty).

9.3 Compatibility and Future Expansion

• Cross-vendor compatibility [1][8]:

  • Multiple instruments from different brands in the same lab make unified data management difficult;
  • Recommend exporting in JCAMP-DX format for archiving;
  • Online tools like ftir.fun can assist cross-platform viewing [10].

• Third-party software ecosystem [1]:

  • Can it export Python/R-friendly formats (CSV, JCAMP-DX);
  • Does it support interfacing with LIMS systems;
  • Is there an open API (few software support).

X. Common Pitfalls at the Software Level

10.1 Pitfall 1: Exporting %T Instead of Absorbance

Situation: After exporting CSV and importing into Python, peaks appear "inverted" (downward concave) [1].

Cause: The spectrum was in %T mode during export, resulting in Y-axis values 0–100, with peaks pointing downward.

Countermeasure:

# Auto-detect and convert
import numpy as np
data = np.loadtxt("sample.csv", delimiter=",", skiprows=1)
wn, y = data[:, 0], data[:, 1]
if y.max() > 2:  # Looks like %T
    y = -np.log10(y / 100.0)  # Convert to Absorbance
    print("Detected %T, converted to Absorbance.")

10.2 Pitfall 2: Wavenumber Axis Reversed

Situation: After import, the spectrum appears mirrored left-right [1].

Cause: Different software have different default wavenumber directions (OMNIC high-to-low, some Python libraries low-to-high).

Countermeasure:

if wn[0] < wn[-1]:  # Low to high, reverse
    wn = wn[::-1]
    y = y[::-1]

10.3 Pitfall 3: Inconsistent Resolution / Number of Points

Scenario: When merging data from two instruments, the number of points is inconsistent and cannot be aligned [1].

Cause: Different instruments have different resolutions (4 cm⁻¹ vs 8 cm⁻¹) and different numbers of points.

Solution: Interpolation alignment

from scipy.interpolate import interp1d
f = interp1d(wn1, y1, kind='linear', fill_value='extrapolate')
y1_aligned = f(wn2)  # resample to wn2

10.4 Pitfall 4: Private Format Unreadable

Scenario: .spa files collected with OMNIC 5.x five years ago, the new computer does not have OMNIC installed and cannot open them [1].

Solutions:

• Export JCAMP-DX archives in advance;
• Use Bio-Rad KnowItAll for conversion [9];
• Contact the vendor for older software versions (some vendors provide them free of charge);
• Prevention: Establish a "Data Archiving SOP", saving each raw data simultaneously as CSV + JCAMP-DX.

10.5 Pitfall 5: Macros Fail in New Versions

Scenario: After upgrading OMNIC 9 → 10, old macro commands throw errors [1].

Solutions:

• Test macros in a virtual machine before upgrading;
• Keep the older software version (some vendors support dual-version installation);
• Avoid using undocumented commands in macros;
• Maintain communication with vendor technical support to obtain upgrade documents in advance.

Summary of This Episode

Questions for Thought

1. You need to batch export 100 OMNIC spectra as CSV, ensuring each spectrum has Y-axis in absorbance, X-axis from high to low wavenumber, and 3601 points. Design a complete batch export solution, including an OMNIC macro and a Python post-processing script.

2. The same polystyrene film is measured on a Bruker OPUS and a Thermo OMNIC, each producing one spectrum. After exporting as CSV, the peak intensity differs by 20%. List all possible software factors (excluding hardware differences) that could cause this discrepancy.

3. A company decides to migrate all FTIR data from the past 5 years into a unified database, but the data are scattered in three private formats: .spa, .opu, and .sp. Design a migration plan covering three stages: format conversion, metadata preservation, and data integrity verification.

4. Write an automated QC workflow using OPUS macros: automatically collect background at 9:00 AM daily, prompt to load sample, collect sample, perform Rubber Band baseline correction, library search, generate report, and send via email. List the main steps of the macro and key commands for each step.

5. Compare the 21 CFR Part 11 compliance capabilities of the four major commercial software packages. If you are a QC manager in a pharmaceutical company planning to purchase a new FTIR, which features would you prioritize in software selection?

References

[1] Smith B C. "Choosing and Using FTIR Software." Spectroscopy, 2018, 33(5): 18–24.
https://www.spectroscopyonlin…

[2] Thermo Fisher Scientific. "OMNIC Spectroscopy Software: User's Guide." Version 10.
https://www.thermofisher.com/…

[3] Thermo Fisher Scientific. "OMNIC Macros: Programming Guide." Technical Note.
https://www.thermofisher.com/…

[4] Bruker Optics. "OPUS Spectroscopy Software: User Manual." Version 8.5.
https://www.bruker.com/en/pro…

[5] Bruker Optics. "OPUS Macro Programming: Reference."
https://www.bruker.com/en/pro…

[6] PerkinElmer. "Spectrum 10 Software: User's Guide."
https://www.perkinelmer.com/p…

[7] Shimadzu. "LabSolutions IR: User's Manual."
https://www.shimadzu.com/an/p…

[8] IUPAC. "JCAMP-DX: Standard for Infrared Spectral Data Exchange." Pure and Applied Chemistry, 1995, 67(12): 1955–1984. DOI:10.1351/pac199567121955.

[9] Bio-Rad. "KnowItAll Informatics System: Spectral Data Management."
https://www.knowitall.com/

[10] ftir.fun. "Online Infrared Spectroscopy Tool."
https://ftir.fun

Next Episode Preview: Ep 53 — Open-Source Tools (Part 1): SpectroChemPy, pybaselines
Commercial software is good but expensive and closed. In the next episode, we turn to the open-source world, reviewing SpectroChemPy (NDDataset data structure, multi-vendor format reading), pybaselines (200+ baseline correction algorithms), and spectrapepper (entry-level spectral analysis package). Each comes with GitHub links, star counts, practical code examples, and a decision framework for "when to choose open-source and when to still need commercial software".

This article is licensed under CC BY-NC-SA 4.0. Images are from public domain or attributed online sources; copyright belongs to the original authors.