Free instrument-data tool

Rheology data files, read and analyzed — free

How rheometer data is stored (TA TRIOS, Anton Paar, Malvern), how to read/convert flow curves and frequency sweeps — upload to Matflow free, or parse in Python.

Formats: TA Instruments TRIOS exports, Anton Paar (RheoCompass) exports, Malvern .rproj exports, CSV/Excel · For: Formulation & polymer labs

The format

What the format actually is

Where the data hides, and what a naive parser loses.

Rheometry data is almost always exported as CSV/Excel from the vendor analysis suite (TRIOS, RheoCompass…) — but the column layout changes per measurement type: flow curves (η vs γ̇), frequency sweeps (G′/G″ vs ω), amplitude sweeps (γ-strain), thixotropy loops.

The analysis-relevant metadata — geometry (cone/plate vs parallel plate), temperature protocol, gap — is often in header rows above the data or lost in export, which breaks comparability across sessions.

Downstream needs are consistent: viscosity curves, Cox–Merz checks, yield-stress fits (Herschel–Bulkley), G′/G″ crossover — all currently redone by hand per file.

Watch out

Vendor quirks that break naive parsers

Each of these has produced a silently wrong number in a real workflow.

Multi-column exports interleave measurement types; one "file" may hold several experiments.
Header rows above data (metadata) break default CSV parsing — and often get deleted, losing conditions.
Shear-rate vs stress conventions (log spacing) trip plotting defaults and fitted models alike.
Open source

Do it yourself in Python

We would rather you succeed with or without us. The open-source path:

pandas with explicit header/skiprow handling per export template; assert columns at load.
Herschel–Bulkley fitting: scipy curve_fit on τ = τ0 + K·γ̇^n — check the residual plot before quoting the yield stress.
Cox–Merz: overlay η(γ̇) with |η*|(ω) to validate the complex-viscosity comparison.
Upload path

What happens if you use Matflow

The parser is only step one — the value is the review and the provenance that follow.

01

Upload on the Ingestion page

Excel, CSV, PDF, SDS images and instrument files are parsed into evidence-tagged rows — the original file is retained as provenance.

02

Review before promotion

Column roles and types are proposed for a reason; correcting a mislabeled column here is the highest-leverage five minutes in the workflow.

03

Promote to a governed dataset

The accepted rows become a versioned dataset any stage can use — every row keeps its source and extraction status.

Docs: ingestion & extraction · column roles · instrument parsers

Stop parsing by hand

Upload your TA Instruments TRIOS exports, Anton Paar file to Matflow and it lands as a governed, validated dataset — original file preserved as provenance, every column documented. Free tier, no card.