Making an overview presentation of the scaling relations

The following video-presentation – for the CHEAC Summer school 2025 – retells our review on the scaling relations electrocatalysis https://chemrxiv.org/engage/chemrxiv/article-details/67ed469081d2151a02b33a98

The final video

From the beginning I decided to try AI to prepare the presentation. Eventually the only to record the video turned out to be by the traditional way. Together with co-authors Ritums and Nadezda, we used PowerPoint with its slide-by-slide recording feature. As we were in 3 different locations, we exchanged the presentation several time while recording. I used chatgpt 4o and 5 to write lecturer’s notes for every slide. In particular, I gave the chat our article’s pdf-file and then discussed every slide-text using canvas-feature to polish it iteratively. Nadezda also used chatgpt to refined her slides before reading them aloud. Overall, I have spend over two weeks planning the presentation. Then a week polishing the slides. Then several days to record and re-record slides. And finally I have got this the final video-presentation.

Adding voice to a ready presentation

app.pictory.ai does a relatively good job on reading the lecturer’s notes in a ready presentation. Thought, it reads “Jan” and “OOH” in a funny way. And it adds a lot of 10–20 second pauses. Also the slide numbering is off as well as all animation. The picture is also cut from below. But overall, it takes around 2 hours to generate this voiced video and process it.

Use NotebookLM to make a podcast

In the prompt I have specified to avoid banned tells, see https://doublelayer.eu/vilab/2024/12/17/list-of-banned-tells-for-gpt/ Well, I have forbidden to use “pivotal”, but AI still uses “pivotal”.

I am not responsible for the result 🙂 I have heard it and it sounds OK-ish.

Using Gemini in Google Slides

Does not work for me. Gemini wants to draw images. I just want to enter my own figures.

All I need is to convert Figures to Slides

https://www.magicslides.app promises to do exactly that but I failed with a notice that below 5 Mb files are allowed.

SlideAI extension also does not do what I want.

Ufff … manual upload is still the fastest and most robust. Well, it is not so simple, as most of my figures are in pdf, so I wrote this script to convert everything to png. When it took me 2 mins to drag-and-drop all png figure to my presentation. Hurray!

#!/bin/bash

# Create output folder
mkdir -p png

# List of input files
files=(
"Figure 1 mechanisms.png"
"Figure 18 Timeline.png"
"FIgure 14 distances.pdf"
"Figure 11 relative.pdf"
"Figure 6 3dvolcano_withscaling.pdf"
"Figure 2 publications.pdf"
"Figure 5 3dvolcano.pdf"
"Figure 17 perspectives.pdf"
"Figure 16 O_bypassing.pdf"
"Figure 15 O_pushing.pdf"
"Figure 12 O_breaking.pdf"
"Figure 13 O_switching.png"
"Figure 10 O_tuning.pdf"
"Figure 7 projection_potential.pdf"
"Figure 9 projection_ads.pdf"
"Figure 8 timeline.pdf"
"Figure 3 ass_diss.png"
"Figure 4 scalings.png"
)

# Loop through files
for f in "${files[@]}"; do
  base=$(basename "$f")
  name="${base%.*}"
  ext="${base##*.}"
  
  if [[ "$ext" == "pdf" ]]; then
    convert -density 300 "$f" -quality 100 "png/${name}.png"
  elif [[ "$ext" == "png" ]]; then
    cp "$f" "png/${name}.png"
  else
    echo "Unsupported file type: $f"
  fi
done

Use NotebookLM to create FAQ

Pretty cool – NotebookLM make a FAQ.

What are scaling relations in electrocatalysis, and why are they important?

Scaling relations are correlations between the adsorption energies of reaction intermediates on a catalyst’s surface. They are crucial in multi-step electrocatalytic reactions, such as the oxygen reduction reaction (ORR), carbon dioxide reduction (CO2R), and nitrogen reduction (N2RR). The concept emerged in 2005 with the discovery of linear relations between adsorption energies of intermediates like OH, OOH, and O on metal surfaces. Understanding these relations is vital because they define fundamental chemical limitations in electrocatalytic reactions, impacting the design of more efficient catalysts for energy conversion technologies like electrolysers, fuel cells, and metal-air batteries.

How do scaling relations limit the efficiency of oxygen electrocatalysis?

In oxygen electrocatalysis, particularly the oxygen reduction reaction (ORR), the adsorption energies of key intermediates (OOH, OH, O) are correlated by scaling relations. These correlations constrain the achievable catalytic activity, often visualised on “volcano plots.” The OOH-OH and O-OH scaling relations, for instance, mean that if a catalyst binds one intermediate optimally, it might bind another too strongly or too weakly, preventing it from reaching the ideal catalytic activity (the “volcano top”). This limitation is significant, as experimental results have shown catalytic overpotentials converging to a limit set by these relations for over two decades, hindering progress in sustainable energy solutions.

What are the main reaction mechanisms in oxygen electrocatalysis, and how does catalyst geometry influence them?

Oxygen electrocatalysis primarily proceeds via two mechanisms: associative and dissociative. The associative mechanism, which dominates most known catalysts, involves intermediates like OOH, OH, and O adsorbing at a single active site. Geometrically, this requires only one atom in the active site. The dissociative mechanism, conversely, requires at least two neighbouring atoms to accommodate dissociation products (O and OH). On metal surfaces, a spatial mismatch often prevents the dissociative mechanism, as O preferentially adsorbs on hollow sites and OH on top sites. However, dual-atom site catalysts (DACs) can facilitate dissociative pathways by providing two adjacent sites, allowing for the adsorption of dissociation products. The inter-atomic distance within these active sites is a critical geometric parameter that influences the energy barrier for dissociation, balancing thermodynamics and kinetics.

What is the “volcano plot” in electrocatalysis, and how do scaling relations affect it?

The “volcano plot” is a theoretical framework used to understand electrocatalysis, typically representing overpotential or activity as an “altitude” against adsorption energy descriptors. For ORR, it correlates adsorption energies with deviations from the thermodynamic equilibrium potential. Scaling relations define the “paths” or “fixed climbing routes” on this volcano plot that are accessible to catalysts. For example, the OOH-OH scaling relation appears as a plane on the three-dimensional volcano, and catalysts following this relation are confined to a specific line on the volcano’s surface. This means that while an “ideal catalyst” (the volcano’s apex) might exist theoretically, scaling relations prevent most catalysts from reaching it, limiting the search for optimal catalysts to a two-dimensional projection.

What are the five general strategies for “manipulating” scaling relations in electrocatalysis?

The review outlines five general strategies for manipulating scaling relations to enhance electrocatalytic performance:

  1. Tuning: Adjusting the adsorption energy of a key intermediate (e.g., ∆GOH) to optimise catalyst performance within the constraints of an existing scaling relation, adhering to the Sabatier principle.
  2. Breaking: Decreasing the intercept (β) of a scaling relation by selectively stabilising one intermediate over another (e.g., OOH relative to OH), often by introducing spectator groups that induce stabilising interactions.
  3. Switching: Changing the slope (α) of a scaling relation by enabling an alternative reaction mechanism (e.g., switching from an associative to a dissociative mechanism in ORR) to avoid problematic intermediates. This usually requires dual active sites.
  4. Pushing: A combined strategy that changes the slope and adjusts the intercept, simultaneously switching to an alternative mechanism and using stabilising interactions (similar to breaking).
  5. Bypassing: Completely decoupling adsorption energies by switching between two distinct states of the catalyst (e.g., geometric or electronic) during the reaction cycle, with each state having optimal adsorption energies for specific intermediates. This strategy aims to eliminate all scaling relation constraints.

How does the “breaking” strategy specifically aim to overcome the OOH-OH scaling relation?

The “breaking” strategy focuses on reducing the intercept of the OOH-OH scaling relation (from approximately 3.2 eV to an ideal value of 2.46 eV) by selectively stabilising the OOH intermediate relative to OH. This typically involves introducing spectator groups or a second adsorption site near the active site. These spectators can form hydrogen bonds or other stabilising interactions with OOH, effectively shifting its adsorption energy without proportionally affecting OH. While challenging to achieve experimentally, this strategy has been demonstrated in oxygen evolution reactions (OER) and more recently in ORR using dual-atom catalysts (DACs) with specific active sites like PN3FeN3, where the phosphorus acts as a spectator to stabilise OOH through hydrogen bonding.

What role do Single-Atom Site Catalysts (SACs) and Dual-Atom Site Catalysts (DACs) play in manipulating scaling relations?

Single-Atom Site Catalysts (SACs) and Dual-Atom Site Catalysts (DACs) are crucial in manipulating scaling relations due to their distinct geometric and electronic properties. SACs typically allow for “on-top” adsorption, primarily favouring the associative mechanism in ORR. DACs, with their two neighbouring active sites, offer the possibility of accommodating two dissociation products simultaneously, thereby enabling the dissociative mechanism. This ability to switch mechanisms is key to the “switching” strategy, where DACs can replace the OOH intermediate with two distinct O and OH intermediates adsorbed at separate sites. Furthermore, the precise control over inter-atomic distances and curvature in DACs allows for fine-tuning of electronic structures and promoting specific interactions (like hydrogen bonding), contributing to “breaking” and “pushing” strategies.

What is the ultimate goal of manipulating scaling relations, and how does the “bypassing” strategy contribute to this vision?

The ultimate goal of manipulating scaling relations is to achieve ideal catalyst performance, ideally with zero overpotential, by overcoming the fundamental limitations imposed by these correlations. The “bypassing” strategy represents the most ambitious approach towards this goal. It seeks to completely decouple the adsorption energies of reaction intermediates by allowing the catalyst to switch between two or more distinct states (e.g., geometric, electronic, or photonic) during the reaction cycle. Each state would be optimally configured to bind specific intermediates at the ideal energy values required for efficient catalysis. While seemingly challenging in practice, this concept, inspired by natural enzymes like cytochrome c oxidase, offers a theoretical pathway to eliminate all scaling constraints and achieve the theoretical apex of the volcano plot, pushing the boundaries of what is currently achievable in electrocatalysis.

ResearchCOMP – the European Competence Framework for Researchers

The new Framework for Researchers is a cool tool for planning your career. However, it is so hard to understand and remember. That is why I suggest using the following tree analogy.

ResearchCOMP is an essence like a tree. Roots of critical thinking (1) with trunk of self-management (2) and branches of collaboration (3) hold leaves as research (4) and fruits as impact (5). Water = management 6) and sun = tools (7) nourish the research tree.
The following illustration has been prepared by my son:

Art created by Naran Pavanello, 9 years old

ResearchCOMP, Like a Tree

Roots of critical thinking, deep and strong,
The trunk of self-management keeps you moving along.
Branches of collaboration, reaching far,
Leaves of research, showing who you are.

Fruits of impact, growing bright,
Water of management keeps it right.
Sunlight from tools makes it thrive,
Nourishing the research, keeping it alive.

“Content created with assistance from ChatGPT, an AI language model by OpenAI.”

With this analogy it is now easy to explain what a PhD. student should focus on.

Cognitive Abilities (Roots):
As a Ph.D. student, you first build your thinking skills like problem-solving and creativity. These skills are like roots that hold you on the ground.

Self-Management (Trunk):
You need to manage your time and stress, set goals, and balance your workload. This helps you stay focused and handle challenges, like a trunk.

Working with Others (Branches):
Collaboration is key. Branch with supervisors and teams, seek feedback, and build connections to grow your research.

Managing Research (Water):
You manage your PhD project. This includes organizing resources, meeting deadlines, and planning your work. It is like a flow.

Managing Research Tools (Sun):
Learn to use research tools like data management and software. These help keep your work organized. It is like external source of energy = sunlight.

Doing Research (Leaves):
This is your core work – running experiments, analyzing data, and writing papers to build expertise in your field. Leaves are as dynamic as your research.

Making an Impact (Fruits):
Your research creates impact. Publish, attend conferences, and share your findings as fruits to the society.

And now you can compare a young tree to a mature one. The difference is that the young one is expected to “bloom”, whether the mature one is expected to give “fruits”, as illustrated below.

Fonts for grant proposals

The reference font for the body text of European proposals is Times New Roman (Windows platforms), Times/Times New Roman (Apple platforms) or Nimbus Roman No. 9 L (Linux distributions). The Roman family is from a pre-digital age and has well-recognizable features.

Is it the best font in terms of readability? On the one hand, there is a tendency to move from Times-type fonts to plainer fonts, like Calibri. On the other hand, many studies (with controversial results) account for aspects like Dyslexia, typeface anatomy, and Display vs. Print. The effect of font choice on readability and compression on big numbers seems small or insignificant. However, my point is that a proposal must be clear to a few reviewers, who might have difficulties understanding the proposal due to age, Dyslexia, and colour vision deficiency. These few people will have some feelings about how the text is formatted. For that reason and also because of my artistic education in caligraphy, I have been looking for and playing with font combinations for a long time. Here is what I have tried and liked.

1. STIX two and Source Sans form a pair of Serif and Sans fonts. STIX two resulted from a collaborative effort from the most prominent academic publishing companies. Its predecessor (STIX one) has exactly the same metrics as Times New Roman. STIX two is somewhat bigger, which is not prohibited by the EU funding agencies. The main benefit of using STIX fonts is that these are mathematical fonts and, thus, can be natively used in MS Equation Editor (instead of Cambria) and LaTeX (as XITS or STIX2).

2. An excellent substitution for Times New Roman is Zilla Slab – a unique font by the Mozilla foundation – which has the same metrics as Times New Roman, is a Sans font, yet looks like a monospace one, does have features of a Dyslexia-friendly typeface, and looks great in print and on screen. It is freely available from Google fonts. It can be used with Times New Roman (or similar) as a pair of Serif and Sans fonts.

3. Libertinus Serif + Gill Sans is my favourite Serif and Sans pair. You can see Linux Libertine in the Wikipedia logo. Gill Sans Nova is commonly fond in the University of Tartu (Estonia) press. Although Libertinus Serif has an original Sans counterpart, its combination with Gill Sans looks most natural. I love Libertinus because of its amazingly looking ligatures, and it is also compatible with MS Equation Editor and LaTeX.

PS One can play with fonts in the EU projects to make their proposal more appealing. Like Estonian grants, I prefer calls, where applicants fill out online forms without changing the text appearance. Of course, the text looks ugly due to nasty line breaks, horrible chemical formulas and mathematical equations, and poor typography. Still, the competition is more fair because everyone is in the same conditions. 

Feedback from a Sci & Tech student

It was a pleasure to work with Ahmed Helmi. That is what he wrote after finishing a project with me and Jaanus:
“Thanks a lot for you and for Jaanus, now I know a lot about linux commands and technical details about graphs and how to make a good report. Have a nice day.”
Usually Ahmed ends his emails with a citation:
“Most of the important things in the world have been accomplished by people who have kept on trying when there seemed to be no hope at all”
Indeed, for Ahmed there were a lot new things to learn. He managed very well, as he is a quick learner and a great person.