Green Education - The Future Of Sustainability

Personal Note From The Editor

Hey Reader hope you feel great today!

Today … and tomorrow? Are you optimistic or do you await the next struggle?

I think for all of us involved in sustainability this is a tricky question.

And today we ride this rollercoaster again - I wrote up my top 3 predictions for developments that will benefit sustainability.

Do you welcome this change or is it another step towards dehumanization? You decide:

Today's Lesson: The Future Of Sustainability

What Will Await Us Ahead In Science

Number Of The Day

A recent preprint estimated that training ChatGPT-3 might have required 700,000 liters of water for cooling. Microsoft disclosed that the latest supercomputer operates with 10,000 graphics cards and 285,000 processor cores. This suggests that each 30 prompts submitted might consume 500 milliliters of water.

700 000 Liter

Looking Ahead For Sustainability

Admittedly, many scientists still lack the basic knowledge of sustainable practices and university curriculums seldom include green science.

Regardless, the future holds advancements that will transform everyday life in the lab!

1) Leveraging Artificial Intelligence for the Better

Despite concerns about AI's growing capabilities, there are promising applications for sustainability:

While AI can help predicting molecular structures and analyzing extensive datasets, it also offers significant benefits “upstream”.

Imagine this: crawling algorithms locate all relevant literature (aided by Open Access and FAIR publishing principles), and your personal AI bot "reads" and digests the information.

It can then review your experimental design, streamline setups, and reduce replication/sample sizes using advanced statistical models running a multitude of scenarios and assumptions.

For instance, applying Bayesian approaches, which incorporate previous data, have successfully reduced the number of mice needed in experiments.

This reduces the number of necessary experiments and provides you with more certainty as it incentivized and supports long-term planning.

2) Making Recycling Easy

As we know, plastic waste management has always been challenging, particularly in separating different materials. However, solutions are on their way.

Chemical recycling is an innovative approach that dissolves various plastics, separates impurities, and produces high-grade recycled materials.

While many types of chemical recycling exist, some still work only with specific preselected plastics.

Nevertheless, when techniques like solvolysis (that dissolve and break down plastics into monomers, see here for a short introduction) are advanced that would allow you to combine all sorts of waste in one bin and to produce virgin-like high-quality plastic materials from there anyway.

3) Innovations in Equipment

Every mouse in our research facilities costs about $1 per day - we do not need to talk about the ethical and environmental impact ...

Organ-on-a-chip models are interesting innovations to watch. However, when linking them we might see a true advancement when it comes to understanding biological models.

Another experience we all have had ... preparing samples for different analyses is time-consuming and wasteful. Imagine preparing a sample once and conducting all analyses you dream of seamlessly.

With machine learning and AI enhancing analyses, equipment is becoming more autonomous, minimizing errors and allowing researchers to focus on groundbreaking work. For example, a single tissue sample could undergo 3D transcriptomics and microscopy, with laser evaporation on interesting spots for Gas-chromatography/MS analyses.

For now, AI could at least guide microscopes to scan the most promising parts of a sample, taking over entirely after sample insertion.

Applying The Knowledge

It might feel scary at first … it always does. However, getting used to working with AI is certainly important.

No doubt, we shall not forget about the environmental impact. Don’t ask ChatGPT whether you should wear red or blue tomorrow …

But get used to using AI for work related aspects!

Similarly, try to follow up on newer innovations in science, at least superficially. It will cause you headache to learn about it all at once but even more important, because it keeps your mind open and inspired!

Upcoming Lesson:

Addressing Carbon Footprint Analyses

Asking You

How many computation hours were dedicated to science in 2020 alone?

How We Feel Today

If you have a wish or a question, feel free to reply to this Email.
Otherwise, wish you a beatiful week!
See you again the 27th: )

Find the previous lesson click - here -

Edited by Patrick Penndorf
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