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Scientific Figures Without the Design Skills? Illustrae Makes It Possible thumbnail

Scientific Figures Without the Design Skills? Illustrae Makes It Possible

Andy Stapleton·
5 min read

Based on Andy Stapleton's video on YouTube. If you like this content, support the original creators by watching, liking and subscribing to their content.

TL;DR

Illustrate generates academic graphical abstracts and posters from pasted research text, using canvases that can hold multiple figures.

Briefing

Academic posters and graphical abstracts have long been a weak spot for AI tools, but Illustrate positions itself as a design-first solution that turns research text into publication-ready layouts. After logging in, users work inside large “canvases” that can hold multiple figures, with options to start from a “brainstorm” flow or create a new canvas from scratch. The interface emphasizes templates, tutorials, and a gallery, while the core workflow centers on pasting research content—titles, author abstracts, and chosen layout preferences—then generating either a graphical abstract or a poster.

In the graphical abstract path, Illustrate takes an abstract and produces a structured visual with editable components. The output shown includes domain-specific elements such as an epoxy transfer method and materials like silver nanowires and carbon nanotubes, plus a “figure of merit” section. Crucially, the generated figure isn’t treated as a single locked image: users can edit parts, replace images (for example, inserting a scanning electron microscope image), and refine the composition. A notable example involves prompting for a “three part” modern circular-flow graphical abstract with text included; the resulting canvas breaks the design into elements that can be rearranged and corrected.

The transcript also highlights a more hands-on approach for building scientific figures from components. Users can generate individual elements—described in the example as a “man eating a burrito”—then edit those elements by sending them into an editable bar (copy/paste into the bar is required rather than drag-and-drop). That same workflow is used to create a roll-to-roll organic photovoltaic device diagram with appropriate layer counts and colors, including a substrate, P.PSS, P3HT/PCBM bulk heterojunction layers, and an aluminium electrode. The tool supports per-element actions like duplicate, delete, crop, and linking, and it offers standard image-manipulation controls such as flipping, layering order (bring forward/send back), and alignment.

Once components are assembled, Illustrate can combine selected elements into a single figure and add callouts—shapes, arrows, and highlighted regions—plus optional frames that keep groups exportable together. Export options include PNG and SVG, with PNG recommended for the generated figure outputs and SVG for scalable components like text and shapes. There’s also an “embed scene” option that preserves scene data for later editing.

Beyond graphical abstracts, Illustrate can generate full posters with layout intelligence. The example poster produced from brainstorm includes convincing scientific styling and even SEM-like details that appear plausible, while the layout itself is presented as a strength compared with other large language model outputs. Users can also generate individual poster components for use elsewhere (such as PowerPoint) by exporting selected elements.

Finally, the transcript notes practical access and pricing: a monthly plan starting at $8.99 AUD and an unlimited option at $24.99 AUD, with the paid tier offering a limited number of image generations per month. Overall, Illustrate is presented as a tool that bridges the gap between scientific content and design execution—turning text prompts into editable, exportable figures and posters without requiring traditional design skills.

Cornell Notes

Illustrate is positioned as an AI design tool for academic graphics, turning pasted research text into graphical abstracts and posters. It works on large canvases that hold multiple editable elements, letting users refine outputs rather than treating them as a single static image. The workflow includes generating a full graphical abstract from an abstract prompt, or building figures from component libraries and custom prompts (including scientific diagrams like an organic photovoltaic layer stack). Users can edit elements, add annotations (arrows, shapes, labels), group items in frames, and export as PNG or SVG for use in papers and slide decks. The appeal is layout competence—especially for posters—plus practical editing and export options.

How does Illustrate turn academic text into a graphical abstract?

Users start a new canvas or choose “brainstorm,” then paste research content such as a title and abstract. They select layout/style options (e.g., portrait vs. landscape, modern vs. other styles, and whether to include text) and click create. The system outputs a graphical abstract on the canvas with multiple elements that can be edited individually, including sections like a “figure of merit” area and domain-relevant visuals derived from the abstract.

What makes the generated figures usable for real revisions instead of being a dead-end image?

The output is built from separate, editable components. Users can click edit on an element, which routes the image into an editable bar (copy/paste into that bar is required rather than drag-and-drop). They can then regenerate or modify that element (for example, removing unwanted parts like the “stomach” from a generated burrito-related figure). Additional per-element actions include duplicate, delete, crop, and linking.

How does Illustrate help with scientific accuracy in diagrams like device layer stacks?

In the example, prompting for an “organic photovoltaic device” produced a diagram with an appropriate number of layers and color coding. The layers shown include P.PSS and a bulk heterojunction stack involving P3HT and PCBM, plus an aluminium electrode. The transcript frames this as impressive because the tool infers a structured layer composition from a short scientific prompt.

What editing and layout tools exist once elements are on the canvas?

Users can select and combine multiple elements into one figure, add shapes and highlights (circle/diamond/square), and insert arrows pointing to specific parts. Frames can group elements so they export together. Standard manipulation controls are available, including bring forward/send back, flip horizontal, and alignment-style actions like center back/center forward.

How does exporting work for using figures in papers or slide decks?

Export is done via “export image,” with options to export only selected items and to remove backgrounds. Outputs can be exported as PNG or SVG. The transcript notes that PNG is the main format that works well for generated figures, while SVG is better suited for scalable components like rectangles, shapes, and text rather than the raster-like generated elements. There’s also an “embed scene” option to preserve scene data.

What’s the advantage of Illustrate for posters compared with other AI outputs?

Poster generation is presented as a layout strength: a brainstorm-created poster is said to include correct layout structure and convincing scientific styling. The example poster includes SEM-like details and electrode/material references that look plausible, and the layout is described as something other large language model outputs often struggle to get right.

Review Questions

  1. When would a user choose “brainstorm” versus starting from scratch with a new canvas in Illustrate?
  2. What are the key steps to edit a generated element, and what limitation is mentioned about drag-and-drop into the edit bar?
  3. Why might PNG and SVG exports behave differently for generated figures versus text and shapes?

Key Points

  1. 1

    Illustrate generates academic graphical abstracts and posters from pasted research text, using canvases that can hold multiple figures.

  2. 2

    Outputs are component-based and editable, enabling targeted revisions (including replacing images like SEMs).

  3. 3

    Users can build scientific diagrams from individual generated elements, then combine them into a single figure with annotations and frames.

  4. 4

    Editing requires specific interactions—copy/paste into the edit bar is needed, and there’s no editing history for undoing to a prior state.

  5. 5

    The tool supports standard layout controls such as cropping, layering order (bring forward/send back), flipping, and alignment.

  6. 6

    Export options include PNG and SVG, with PNG emphasized for generated figure outputs and SVG for scalable components like text and shapes.

  7. 7

    Poster creation is highlighted as a layout advantage, producing structured designs that can be reused in slide decks or papers.

Highlights

Illustrate turns an abstract prompt into a graphical abstract made of editable parts, including sections like a “figure of merit.”
A roll-to-roll organic photovoltaic device diagram was generated with a plausible layer stack and color coding from a short scientific prompt.
Exporting supports both PNG and SVG, with guidance that PNG is the reliable choice for generated figures while SVG fits scalable elements.
Poster generation is framed as a standout capability, producing convincing layouts that many other AI tools struggle to match.

Topics

Mentioned