Is my data kept private?

Files are stored scoped to your account, never used to train models for other users, and fully exportable. Original raw files are retained as provenance.

Free instrument-data tool

NMR data files, read and converted — free

Q: How do I open a Bruker fid/ser + acqus/blocks, JEOL .jdf, Varian/Agilent fid + procpar, JCAMP-DX exports file?

Upload it to Matflow (free tier) and it is parsed into a structured, validated dataset automatically — or parse it yourself in Python with the open-source options listed on this page.

Q: Can I convert Bruker fid/ser + acqus/blocks, JEOL .jdf, Varian/Agilent fid + procpar, JCAMP-DX exports to CSV?

Yes. Matflow normalises the file into a governed dataset you can export as CSV with all metadata preserved. The DIY Python route on this page also converts to CSV.

How NMR data is stored (Bruker fid/ser + acqus, JEOL .jdf, Varian/Agilent fid), how to process/convert 1D and 2D NMR — upload to Matflow free, or parse in Python.

Formats: Bruker fid/ser + acqus/blocks, JEOL .jdf, Varian/Agilent fid + procpar, JCAMP-DX exports · For: Synthetic chemistry & materials labs

The format

What the format actually is

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

Bruker stores FIDs as raw binary (fid/ser) with acquisition parameters in the acqus text file and processed data in 1r/2rr — a directory, not a file, so "just open the NMR" is really "open the experiment folder".

JEOL .jdf is a single-file binary container; Varian/Agilent pairs fid with a procpar text file. Three vendors, three mental models.

Processing (Fourier transform, phase correction, baseline, referencing to TMS/residual solvent) is where spectra become data — and where vendor GUIs currently hold the only record.

Watch out

Vendor quirks that break naive parsers

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

Bruker byte order differs between X32 and X64 acquisitions (endianness flips).

2D data (ser + 2rr) needs both dimensions processed — many quick parsers are 1D-only.

Referencing: residual solvent shifts move with solvent and temperature; store the reference, not just the ppm axis.

Open source

Do it yourself in Python

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

NMR parser guide →

nmrglue is the standard: reads Bruker, Varian, JEOL, pipe, and Sparky; provides FT, phasing, and nddata utilities.

Minimal 1D pipeline: nmrglue.bruker.read → read_binary → process (DI, ZF, FT, phasing) → save as CSV/NPY.

For publication exchange, export JCAMP-DX from your processing software, or convert to mzML-style open containers where supported.

Upload path

What happens if you use Matflow

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

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.

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.

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 Bruker fid/ser + acqus/blocks, JEOL .jdf, Varian/Agilent fid + procpar, JCAMP-DX exports file to Matflow and it lands as a governed, validated dataset — original file preserved as provenance, every column documented. Free tier, no card.

Keep reading

Other formats we parse

This guide covers one of 10 instrument formats.

.mpr .nda / .ndax .res .xye / .xy .jdx / .dx Agilent .D directory with .ms / .dpi files, Thermo .raw, Shimadzu .qgd, JCAMP-DX exports Bruker .0 Agilent/Varian .ads/.dsw, Shimadzu .spc/.uvd, Thermo .usd, CSV/Excel exports TA Instruments TRIOS exports, Anton Paar