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Experiments are the core notebook unit in FlaskNote. Each experiment lives inside a project and gives you a structured place to capture both the plan and the execution of a piece of lab work.

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What an experiment contains

The current editor supports notebook sections such as:
  • a title and status
  • tags for filtering and organization
  • description and notebook metadata
  • a procedure or protocol written in rich text
  • reaction scheme media
  • stoichiometry data
  • workup and purification notes
  • analytical data and supporting media
  • TLC plates
  • data tables
  • uploaded media and gallery content

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Find experiments with tags

Use Add tag below the experiment title to add a short label such as screening or suzuki. The sidebar search finds notebook entries by title, reference, or tag within the active workspace. Open Notebook to view matching entries.

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Download an experiment report

Choose Export PDF in the notebook toolbar to download a report. It includes the current notebook contents, including unsaved edits, without saving the experiment. The report contains a compact reaction scheme, quantities, procedure, data tables with their graphs, TLC plate drawings with Rf values, results, and an attachment list. Analytical images appear as previews; original source files remain in the notebook. If an image is unavailable, the report identifies the omission.

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Why the notebook structure matters

FlaskNote is trying to keep the daily scientific workflow together instead of splitting it across disconnected tools. That means the notebook is not just a text editor. It is the place where your protocol, calculations, context, and supporting materials stay connected.

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Version history

Version history is one of the product’s core safety features. You should be able to:
  • save meaningful checkpoints
  • review earlier versions
  • restore a previous version when you need to recover from a bad edit
The current app also treats notebook safety as more than a history list. Save validation, local draft recovery, and permission-aware editing are part of keeping experiment data trustworthy. If you are documenting experiments for a team, make version history part of your working habit early.
  • keep titles specific enough that someone else can scan them later
  • use tags consistently across a project
  • write protocols as if another researcher will need to reproduce them
  • treat notebook status as a real operational signal, not decorative metadata