Templates, tools, and shared files for the group. Everything here is meant to be downloaded and used in your own work.
How we plan experiments — start from what you want to know, then let the question set the design.
The habit the group is built on: decide what you want to know, phrase it so it could come out either way, and choose the experiment that most directly separates the possible answers. Use the AI prompt pack to think a design through — or to check a write-up. Worked case studies will be added here over time.
Design the experiment from the question, not from the instrument. Decide what you want to know first; the right experiment is whatever separates the possible answers most directly. A technique you happen to have is not a reason to run it.
Before you plot a battery result, make sure it can be trusted and compared. This is a simple summary of what every battery figure and Methods section must disclose, distilled from the reporting guidelines of Joule, ACS Energy Letters, Advanced Energy Materials, and the Nature journals — the same items most journals expect.
A reader should be able to rebuild your cell and reproduce your plot from the Methods and SI alone, and compare your numbers to anyone else's on equal terms. If they can't, something below is missing. Full version and printable copy: download the file at the bottom.
Big areal capacity from a tiny loading · half-cell shown as a full cell · CE quoted as "~100 %" · no electrolyte amount · "high rate" from an unrealistically thin electrode · only % retention with no absolute numbers · only the single best cell.
Distilled from the reporting guidelines of Joule (Battery Checklist required at submission), ACS Energy Letters, Advanced Energy Materials, and the Nature journals — which most journals, including Materials Today Energy, expect too. Full sources are in the download.
Colour, style, and templates for figures, posters, and slide decks.
The colour system for every figure we publish: papers, theses, posters, and slides. Drawing every figure from the same colours — in the same order and with the same meanings — is what makes our output recognisable, and it keeps figures readable for colour-blind readers and in greyscale, which most journals require. Start with the style guide, pin up the reference sheet, and apply it with the Python module or the AI prompt.
#0F6E6Bcontrol / baseline#E29A2Dthe effect of interest#BE654C3rd condition#5A91BE4th condition#83A4625th condition#995A906th condition#333F4Aaxes, ticks, text#DFC98Ffills / CI bands#1C242B#333F4A#66727C#B9C1C6#F3F0EBDrop labpalette.py beside your script, then one line applies the whole house style:
import labpalette as lp
lp.apply() # colours, fonts, 600 dpi
ax.plot(x, y, label="control") # cycles teal, amber, rust, ...
ax.imshow(Z, cmap=lp.cmap("teal"))
Open the AI prompt pack below, copy the block, and paste it into ChatGPT / Claude / Gemini before asking for a plot, diagram, or figure. It makes the AI use these exact colours and rules.
Full rationale, accessibility validation, and setup for R, Illustrator, LaTeX and CSS are in the style guide below.