Saturday, March 02, 2024

 21ST CENTURY ALCHEMY

Turning waste into gold


Peer-Reviewed Publication

ETH ZURICH

The gold nugget obtained from computer motherboards in three parts. The largest of these parts is around five millimetres wide. 

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THE GOLD NUGGET OBTAINED FROM COMPUTER MOTHERBOARDS IN THREE PARTS. THE LARGEST OF THESE PARTS IS AROUND FIVE MILLIMETRES WIDE.

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CREDIT: (PHOTOGRAPH: ETH ZURICH / ALAN KOVACEVIC)




Transforming base materials into gold was one of the elusive goals of the alchemists of yore. Now Professor Raffaele Mezzenga from the Department of Health Sciences and Technology at ETH Zurich has accomplished something in that vein. He has not of course transformed another chemical element into gold, as the alchemists sought to do. But he has managed to recover gold from electronic waste using a byproduct of the cheesemaking process.

Electronic waste contains a variety of valuable metals, including copper, cobalt, and even significant amounts of gold. Recovering this gold from disused smartphones and computers is an attractive proposition in view of the rising demand for the precious metal. However, the recovery methods devised to date are energy-​intensive and often require the use of highly toxic chemicals. Now, a group led by ETH Professor Mezzenga has come up with a very efficient, cost-​effective, and above all far more sustainable method: with a sponge made from a protein matrix, the researchers have successfully extracted gold from electronic waste.

Selective gold adsorption

To manufacture the sponge, Mohammad Peydayesh, a senior scientist in Mezzenga’s Group, and his colleagues denatured whey proteins under acidic conditions and high temperatures, so that they aggregated into protein nanofibrils in a gel. The scientists then dried the gel, creating a sponge out of these protein fibrils.

To recover gold in the laboratory experiment, the team salvaged the electronic motherboards from 20 old computer motherboards and extracted the metal parts. They dissolved these parts in an acid bath so as to ionise the metals.

When they placed the protein fibre sponge in the metal ion solution, the gold ions adhered to the protein fibres. Other metal ions can also adhere to the fibres, but gold ions do so much more efficiently. The researchers demonstrated this in their paper, which they have published in the journal Advanced Materials.

As the next step, the researchers heated the sponge. This reduced the gold ions into flakes, which the scientists subsequently melted down into a gold nugget. In this way, they obtained a nugget of around 450 milligrams out of the 20 computer motherboards. The nugget was 91 percent gold (the remainder being copper), which corresponds to 22 carats.

Economically viable

The new technology is commercially viable, as Mezzenga’s calculations show: procurement costs for the source materials added to the energy costs for the entire process are 50 times lower than the value of the gold that can be recovered.

Next, the researchers want to develop the technology to ready it for the market. Although electronic waste is the most promising starting product from which they want to extract gold, there are other possible sources. These include industrial waste from microchip manufacturing or from gold-​plating processes. In addition, the scientists plan to investigate whether they can manufacture the protein fibril sponges out of other protein-​rich byproducts or waste products from the food industry.

“The fact I love the most is that we’re using a food industry byproduct to obtain gold from electronic waste,” Mezzenga says. In a very real sense, he observes, the method transforms two waste products into gold. “You can’t get much more sustainable than that!”

 

AI meets green: The future of environmental protection with ChatGPT


Peer-Reviewed Publication

NANJING INSTITUTE OF ENVIRONMENTAL SCIENCES, MEE

Graphical abstract. 

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GRAPHICAL ABSTRACT.

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CREDIT: ECO-ENVIRONMENT & HEALTH



A recent study introduce a novel paradigm combining ChatGPT with machine learning (ML) to significantly ease the application of ML in environmental science. This approach promises to bridge knowledge gaps and democratize the use of complex ML models for environmental sustainability.

The rapid growth of environmental data presents a significant challenge in analyzing complex pollution networks. While ML has been a pivotal tool, its widespread adoption has been hindered by a steep learning curve and a significant knowledge gap among environmental scientists.

A new study (doi: https://doi.org/10.1016/j.eehl.2024.01.006), published in Eco-Environment & Health on February 3, 2024, has developed a groundbreaking approach that merges ChatGPT with machine learning to streamline its use in environmental science..

This research introduces a user-friendly framework, aptly named "ChatGPT + ML + Environment," designed to democratize the application of machine learning in environmental studies. By simplifying the complex processes of data handling, model selection, and algorithm training, this paradigm empowers environmental scientists, regardless of their computational expertise, to leverage machine learning's full potential. The method involves using ChatGPT's intuitive conversational interface to guide users through the intricate steps of machine learning, from initial data analysis to the interpretation of results.

Highlights
• A new paradigm of “ChatGPT + Machine learning (ML) + Environment” is presented.
• The novelty and knowledge gaps of ML for decoupling the complexity of environmental big data are discussed.
• The new paradigm guided by GPT reduces the threshold of using Machine Learning in environmental research.
• The importance of “secondary training” for using “ChatGPT + ML + Environment” in the future is highlighted.

Lead researcher Haoyuan An states, "This new paradigm not only simplifies the application of ML in our field but also opens up untapped potential for environmental research, making it accessible to a broader range of scientists without the need for deep technical knowledge."

The integration of ChatGPT with ML can dramatically lower the barriers to employing advanced data analysis in environmental science, allowing for more efficient pollution monitoring, policy-making, and sustainability research. It marks a significant step toward more informed environmental decision-making and the potential for groundbreaking discoveries in the field.

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References

DOI

10.1016/j.eehl.2024.01.006

Original Source URL

https://doi.org/10.1016/j.eehl.2024.01.006

Funding information

This work was financially supported by the National Key R&D Program of China (No. 2023YFF0614200), National Natural Science Foundation of China (Nos. 22222610, 22376202, 22193051), and the Chinese Academy of Sciences (Nos. ZDBS-LY-DQC030, YSBR-086). D. L. acknowledges the support from the Youth Innovation Promotion Association of CAS.

About Eco-Environment & Health

Eco-Environment & Health (EEHis an international and multidisciplinary peer-reviewed journal designed for publications on the frontiers of the ecology, environment and health as well as their related disciplines. EEH focuses on the concept of "One Health" to promote green and sustainable development, dealing with the interactions among ecology, environment and health, and the underlying mechanisms and interventions. Our mission is to be one of the most important flagship journals in the field of environmental health.

EGYPTOLOGY/ENTOMOLGY

Dung beetles show their love by sharing the load


MERDE LA'AMOUR 💩

Before mating, some male and female dung beetles work together to move their brood balls to a location unknown to either.


Peer-Reviewed Publication

UNIVERSITY OF THE WITWATERSRAND

Before mating, some male and female dung beetles work together to move their brood balls to a location unknown to either. 

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BEFORE MATING, SOME MALE AND FEMALE DUNG BEETLES WORK TOGETHER TO MOVE THEIR BROOD BALLS TO A LOCATION UNKNOWN TO EITHER.

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CREDIT: WITS UNIVERSITY




Dung beetles share the load when it comes to showing their affection for each-other, when transporting a “brood ball”.

Dung Beetles are known for collecting piles of dung for various uses. One of these is called a “brood ball”, where they lay an egg in each ball, after they have buried it. When the egg hatches, the larva uses the ball as a nursery, eating the ball from the inside out, shaving off layers to keep the ball intact.

“The brood ball is a vehicle that the adult beetles use to get their genes into the next generation,” says Professor Marcus Byrne of the School of Animal, Plant and Environmental Studies at the University of the Witwatersrand (Wits University), in Johannesburg, South Africa. 

Byrne and Professor Marie Dacke of the Vision Group at Lund University, Sweden, have studied the navigational behaviour of dung beetles for over two decades. They have found that dung beetles’ source of food is never at the same location, and consequently they have an extremely limited way of memorising environmental cues around the dung. Instead they make use of the stars, wind and the sun and moon, among others, to find their way away from dung sources to avoid competition.

Ball-rolling dung beetles transport balls of dung and bury them in the soil, for feeding or breeding. After carefully constructing a dung ball at the dropping site, these beetles immediately roll it away along a linear path avoiding intra- and interspecific competition for food and nesting sites. 

In their latest study, published in The Proceedings of the Royal Society B, Byrne, Dacke and  lead author Dr Claudia Tocco (formerly at Wits and now at Lund University, Sweden)  found that when transporting a brood ball, male and female dung beetles work together transporting the ball to a location that neither of them know about beforehand.

“It is important to note that each individual ant or spider involved in the cooperative transport of food strives towards the same final known destination; either a nest or a tightly spun shelter, in which to store the food,” says Tocco. “In contrast, pairs of male and female dung beetles fluently collaborate to transport food to a location unknown to either party at the start of their common journey.”

For their study, Byrne and colleagues studied the transport behaviour of brood balls by pairs of the Southern African Sisyphus fasciculatus and European Sisyphus schaefferi. Both these species of dung beetles are small in size and associated with woodland habitats, where they commonly encounter obstacles on their rolling paths, usually plant material that falls from the trees.

The team found that pairs of Sisyphus beetles cooperate in the transportation of brood balls, resulting in greater transport efficiency in the face of obstacles. This cooperation is driven by coordinated movements where the male steers while the female primarily assists in lifting the ball whenever obstacles need to be climbed.

The characteristic straight-line escape not only guarantees that the ball-rolling beetles will not inadvertently return to the competition at the dropping site, but also effectively maximizes the beetles’ distance from it with every step taken.

When paired up for mating, the exact location at which the pair chooses to stop and bury their brood ball is also selected on the go, on the basis of the properties of the terrain being traversed.

“To ensure smooth and effective transport, efficient communication must be taking place between the male and female of the beetle pair. However, the mechanism that allows the beetle pair to communicate and coordinate their joint actions is currently not known,” says Byrne. This opens up opportunities to investigate collaboration in many other fields, such as robotics.


Japanese wolves are most closely related to dogs and share DNA with East Eurasian dogs

NEWS RELEASE 

THE GRADUATE UNIVERSITY FOR ADVANCED STUDIES, SOKENDAI

Phylogenetic relationships between Japanese wolves and other wolves/dogs. 

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PHYLOGENETIC RELATIONSHIPS BETWEEN JAPANESE WOLVES AND OTHER WOLVES/DOGS.

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CREDIT: NATURE COMMUNICATIONS




In this study, we determined nine genomes of Japanese wolves and 11 genomes of modern Japanese dogs at high coverage and analyzed with one hundred dog and wolf genomes in the public database. The analyses showed that 1) the Japanese wolf was a unique subspecies of the gray wolf that is genetically distinct from both extant and ancient gray wolves known to date, 2) the Japanese wolf is most closely related to the monophyletic group of dogs. Furthermore, 3) Japanese wolf ancestry has introgressed into the ancestor of East Eurasian dogs at an early stage of the dog’s history after diverging from the West Eurasian lineages. The genome derived from Japanese wolf ancestry has been inherited by many modern dogs (at most 5.5%), even in the West Eurasian lineages, through admixture with East Eurasian lineages. Based on phylogenetic and geographic relationships, the dog lineage has originated most likely in East Asia, where it diverged from a common ancestor with the Japanese wolf.

JOURNAL

DOI

CREDIT