It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Phosphorus is a critical raw material that should be recycled more efficiently. There is also a need for more environmentally friendly production methods for organic phosphorus compounds. A recently published review article examines the potential of green chemistry to contribute to these goals in the production and use of multifunctional phosphorus compounds, phosphonates.
Organic phosphorus compounds play a crucial role in several scientific fields, such as chemistry, biology, medicine and pharmacy. These compounds include phosphonates, which have particularly important applications as drugs for the treatment of osteoporosis and other calcium metabolism related diseases, and as corrosion and scale inhibitors, among other things.
The EU has listed phosphorus as one of the critical raw materials, i.e., raw materials ofgreat economic importance and with a high risk of supply disruption due to the concentration of their sources and the lack of good, affordable substitutes.
“Therefore, one can ask whether it is even relevant to talk about green chemistry for any compound containing non-recycled phosphorus,” notes one of the authors of the review, Staff Scientist Petri Turhanen from the School of Pharmacy at the University of Eastern Finland.
Green chemistry is an area of chemistry and chemical engineering focusing on the design of products and processes that minimise or eliminate the use and generation of hazardous substances. Green chemistry methods are increasingly expected to provide solutions to the world's major environmental problems.
The recently published review article focuses on green methods in the synthesis of phosphonates, as well as the wide range of their applications. In addition, the review discusses the degradation, recovery and recycling of phosphonates.
“Feasible green chemistry methods have already been developed for the synthesis of phosphonates; however, the efficient recovery and recycling of phosphonates or phosphorus still requires a great deal of research,” Turhanen sums up.
The article was an invited paper for Green Chemistry, which is the flagship journal in the field, and it was co-authored with Turhanen by University Researchers Santosh Kumar Adla and Juri Timonen from the School of Pharmacy as well as by a long-term collaborator, Professor Konstantinos D. Demadis from the University of Crete.
New study improves the trustworthiness of wind power forecasts
By applying techniques from explainable artificial intelligence, engineers can improve users’ confidence in forecasts generated by artificial intelligence models. This approach was recently tested on wind power generation by a team that includes experts
Explainable artificial intelligence (XAI) is a branch of AI that helps users to peek inside the black-box of AI models to understand how their output is generated and whether their forecasts can be trusted. Recently, XAI has gained prominence in computer vision tasks such as image recognition, where understanding model decisions is critical. Building on its success in this field, it is now gradually being extended to various fields where trust and transparency are particularly important, including healthcare, transportation, and finance.
Researchers at EPFL’s Wind Engineering and Renewable Energy Laboratory (WiRE) have tailored XAI to the black-box AI models used in their field. In a study appearing in Applied Energy, they found that XAI can improve the interpretability of wind power forecasting by providing insight into the string of decisions made by a black-box model and can help identify which variables should be used in a model’s input.
“Before grid operators can effectively integrate wind power into their smart grids, they need reliable daily forecasts of wind energy generation with a low margin of error,” says Prof. Fernando Porté-Agel, who’s the head of WiRE. “Inaccurate forecasts mean grid operators have to compensate at the last minute, often using more expensive fossil fuel-based energy.”
More credible and reliable predictions
The models currently used to forecast wind power output are based on fluid dynamics, weather modeling, and statistical methods – yet they still have a non-negligible margin of error. AI has enabled engineers to improve wind power predictions by using extensive data to identify patterns between weather model variables and wind turbine power output. Most AI models, however, function as "black boxes," making it challenging to understand how they arrive at specific predictions. XAI addresses this issue by providing transparency on the modeling processes leading to the forecasts, resulting in more credible and reliable predictions.
Most important variables
To carry out their study, the research team trained a neural network by selecting input variables from a weather model with a significant influence on wind power generation – such as wind direction, wind speed, air pressure, and temperature – alongside data collected from wind farms in Switzerland and worldwide. “We tailored four XAI techniques and developed metrics for determining whether a technique’s interpretation of the data is reliable,” says Wenlong Liao, the study’s lead author and a postdoc at WiRE.
In machine learning, metrics are what engineers use to evaluate the model performance. For example, metrics can show whether the relationship between two variables is causation or correlation. They’re developed for specific applications – diagnosing a medical condition, measuring the number of hours lost to traffic congestion or calculating a company’s stock-market valuation. “In our study, we defined various metrics to evaluate the trustworthiness of XAI techniques. Moreover, trustworthy XAI techniques can pinpoint which variables we should factor into our models to generate reliable forecasts,” says Liao. “We even saw that we could leave certain variables out of our models without making them any less accurate.”
More competitive
According to Jiannong Fang – an EPFL scientist and co-author of the study – these findings could help make wind power more competitive. “Power system operators won’t feel very comfortable relying on wind power if they don’t understand the internal mechanisms that their forecasting models are based on,” he says. “But with XAI-based approach, models can be diagnosed and upgraded, hence generate more reliable forecasts of daily wind power fluctuations.”
Mr. Aly Abousabaa, Director General of ICARDA, met with His Excellency Mr. IWAI Fumio, the Japanese Ambassador to Egypt, on 27 January 2025, in Cairo, to commemorate ICARDA’s recent partnership with the Government of Japan to implement the transformative project Reversing Egypt’s Diminishing Food Security.
The project, made possible through a generous US$750,000 grant from Japan, will target the governorates of Qena, Menya, and Kafr El Sheikh to improve agricultural resilience, optimize resource use, and strengthen rural livelihoods. It will be implemented in collaboration with Egypt’s Ministry of Water Resources and Irrigation (MWRI) and the Ministry of Agriculture and Land Reclamation (MALR).
Building on over 40 years of ICARDA’s experience in dryland regions, the Reversing Egypt’s Diminishing Food Security project aims to empower Egypt’s rural communities to withstand the growing challenges of food insecurity caused by climate change, rapid population growth, and resource scarcity. Key components of the project include introducing green energy-powered irrigation systems, restoring saline-affected lands, and promoting high-quality seeds and modern cultivation techniques. These efforts are projected to directly benefit smallholder farmers and build the capacities of agricultural extension agents and irrigation engineers in Egypt.
This project will integrate cutting-edge technologies, such as meska-shading solar panels, buried-pipe and cement-lining lifted marwas (on-farm water-distribution ditches), internal ditch/drain networks for leaching and transforming highly saline fallow into productive agricultural/aquacultural lands, small-scale solar-powered post-harvest units, and ICARDA’s GeoAgro-Misr digital agricultural advisory smartphone application, to increase water and energy efficiency while supporting sustainable agricultural practices. It will also focus on gender inclusion by empowering women farmers through access to training, small-scale food processing units, and decision-making opportunities.
“This partnership underscores the power of international collaboration to address the urgent issues of food security and climate resilience,” said Mr. Aly Abousabaa. “It is always an honor working with the Government of Japan to bring our innovative solutions to life. I am confident in this project’s ability to create sustainable impacts for Egypt’s agricultural sector.”
During their meeting, Mr. Aly Abousabaa and His Excellency Mr. IWAI Fumio, highlighted the collaborative activities that contributed to reducing rural poverty in the Upper Egypt and Nile Delta Regions of Egypt through improving water rationalization, increasing agricultural productivity for smallholder farmers, and creating economic opportunities for poor rural households. They also discussed how ICARDA’s innovations and several complementary interventions bridged the gap between research and scalability.
“Strengthening food security is one of Japan’s priorities, and even under the influence of factors such as increased food demand and climate change, sufficient and safe food must be available to all people, at all times,” said Ambassador IWAI. “This cooperation with ICARDA will contribute to strengthening water and food security in Egypt, and to sustaining peace and stability in the Middle East and Africa region.”
This collaboration draws on Japan’s long-standing partnership with CGIAR, which is pivotal in advancing agricultural research and innovation, particularly in addressing water and land scarcity in dryland regions.
ICARDA will continue to foster strategic collaborations while working closely with national partners and governments to deliver climate-smart agri-solutions for improved food and nutrition security and thriving livelihoods of communities in climate-vulnerable dry regions.
Research leads to viable solution for polycotton textile waste recycling
Chemical processing of blended fabrics yields renewable feedstock for bio-based plastics
In a paper just published in Nature Communications, researchers at the Industrial Sustainable Chemistry group of the University of Amsterdam (UvA) present a solution to the challenging problem of recycling polycotton textile waste. The process, developed in cooperation with the company Avantium, starts with fully removing all cotton from the fabric using superconcentrated hydrochloric acid at room temperature. The cotton is converted into glucose, which can be used as a feedstock for biobased products such as renewable plastics. The remaining polyester fibres can be reprocessed using available polyester recycling methods.
The research was led by Prof. Gert-Jan Gruter, who heads the Industrial Sustainable Chemistry group at the UvA’s Van ‘t Hoff Institute for Molecular Sciences (HIMS) as a parttime professor. Gruter is Chief Technology Officer at Avantium where he leads the development of renewable and circular polymer materials and technologies that are key to transforming our fossil-based economy into a renewable, bio-based economy. “Being able to recover glucose from the cotton in textile waste is a crucial contribution to this, as glucose is a key bio-based feedstock. Currently, it is produced from starch from corn and wheat. If and when we will be producing plastics from biomass on a large scale, the world will need a lot of non-food glucose.”
Equally important, the process now presented in the Nature Communications paper provides a solution to the mammoth problem of recycling textile waste. According to Gruter, it is the first effective method for recycling both cotton and polyester components of polycotton with high efficiency. Gruter’s PhD student Nienke Leenders, first author of the paper, performed many tests under the four-year MiWaTex project that has been funded by the Dutch Research Council NWO and is now about halfway. The project entails cooperation with textile sorting and recycling company Wieland, workwear producer Groenendijk Bedrijfskleding, Modint, the trade association for the Dutch clothing and textile industry, and CuRe, developer of advanced technology for chemical recycling of polyester.
Scalability and cost-effectiveness
The Nature Communications paper describes how Leenders performed experiments using Avantium’s pilot plant for its proprietary Dawn Technology which was originally developed to convert non-food plant-based feedstock (e.g wood) into glucose and lignin. Its key feature is using highly concentrated hydrochloric acid (43% by weight) at room temperature. Leenders tested batches of actual post-consumer polycotton waste textiles in Avantium’s Dawn pilot plant. It turned out the cotton cellulose could be fully hydrolyzed into glucose under industrially relevant conditions. The polyester part of the fabric remained intact and could be easily separated. The trials demonstrated high glucose yields, indicating scalability and cost-effectiveness.
The cotton-derived glucose from the process can be used in a wide range of industrial applications, including polymers, resins and solvents. It can for example be used by Avantium to produce its lead product 2,5-furandicarboxylic acid (FDCA), a crucial component in the production of the biobased PEF polyester (polyethylene furanoate) that offers a renewable alternative to PET bottles.
The process also enables the complete recycling of polyester from polycotton. It can be chemically recycled to form new virgin polyester, as was established by tests performed by CuRe.
Favorable techno-economic analysis
According to Gruter, the research lays the foundation for actual industrial-scale recycling of polycotton textiles and the first commercial availability of non-food glucose. “Many parties are trying to get either of these things done but no one has succeeded yet. Our techno-economic analysis looks rather favourable and Avantium has already invested substantially in this development. Our ambition is to advance this technology to the next phase of commercialization, together with partners. So we might very well be the first to market non-food glucose obtained through a bio-refinery approach.”
Samples of polycotton waste textile before (left) and after (right) processing. The sample at the right is transparent since all cotton has been removed; only the polyester remains. Image: HIMS / Avantium.
Residue after processing of pure cotton shirts. Only the polyester labels and seams remain. Image: HIMS / Avantium
Polycotton waste textile recycling by sequential hydrolysis and glycolysis
Article Publication Date
29-Jan-2025
Even quantum physics obeys the law of entropy
Is there a contradiction between quantum theory and thermodynamics? On the surface, yes - but at TU Wien, researchers have now shown how the two fit together perfectly
It is one of the most important laws of nature that we know: The famous second law of thermodynamics says that the world gets more and more disordered, when random chance is at play. Or, to put it more precisely: That entropy must increase in every closed system. Ordered structures lose their order, regular ice crystals turn into water, porcelain vases are broken up into shards. At first glance, however, quantum physics does not really seem to adhere to this rule: Mathematically speaking, entropy in quantum systems always remains the same.
A research team at TU Wien has now taken a closer look at this apparent contradiction and has been able to show: It depends on what kind of entropy you look at. If you define the concept of entropy in a way that it compatible with the basic ideas of quantum physics, then there is no longer any contradiction between quantum physics and thermodynamics. Entropy also increases in initially ordered quantum systems until it reaches a final state of disorder.
Entropy and the direction of time
Equating ‘entropy’ with ‘disorder’ is not entirely correct. After all, what you understand by ‘disorder’ may be subjective, but entropy can be clearly defined with mathematical equations.
“Entropy is a measure of whether a system is in a special, very particular state, in which case the system has low entropy, or whether it is in one of many states that look more or less the same, in which case it has high entropy,” explains Prof Marcus Huber from the Institute for Atomic and Subatomic Physics at TU Wien. If you start with a very specific state, for example a box full of balls that are sorted exactly by colour, then if you shake the box a little, a higher entropy mixed state will develop over time. This is simply due to the fact that only a few ordered states exist, but many that are similarly disordered.
“From a physical point of view, this is what defines the direction of time,” says Max Lock (TU Wien). “In the past, entropy was lower; the future is where entropy is higher.” However, quantum physics encounters a problem here: the mathematician and physicist John von Neumann was able to show: according to the laws of quantum physics, the entropy in a quantum system cannot change at all. If you have the full information about a quantum system, the so-called ‘von Neumann entropy’ always stays the same; it is impossible to say whether time is running forwards or backwards, each point in time is physically as good as any other.
We only ever know part of the information
“But this view leaves out something important,” says Tom Rivlin (TU Vienna). "In quantum physics you can never actually have full information about a system. We can choose a property of the system that we want to measure – a so-called observable. This can be, for example, the location of a particle or its speed. Quantum theory then tells us the probabilities to obtain different possible measurement results. But according to quantum theory, we can never have full information about the system."
Even if we know the probabilities, the actual result of a specific measurement remains a surprise. This element of surprise must be included in the definition of entropy. Instead of calculating the von Neumann entropy for the complete quantum state of the entire system, you could calculate an entropy for a specific observable. The former would not change with time, but the latter might.
This type of entropy is called ‘Shannon entropy’. It depends on the probabilities with which different possible values are measured. ‘You could say that Shannon entropy is a measure of how much information you gain from the measurement,’ says Florian Meier (TU Wien). "If there is only one possible measurement result that occurs with 100% certainty, then the Shannon entropy is zero. You won't be surprised by the result, you won't learn anything from it. If there are many possible values with similarly large probabilities, then the Shannon entropy is large."
Quantum disorder increases after all
The research team has now been able to show that if you start with a state of low Shannon entropy, then this kind of entropy increases in a closed quantum system until it levels off around a maximum value – exactly as is known from thermodynamics in classical systems. The more time passes, the more unclear the measurement results become and the greater the surprise that can be experienced when observing. This has now been proven mathematically and also confirmed by computer simulations that describe the behaviour of several interacting particles.
"This shows us that the second law of thermodynamics is also true in a quantum system that is completely isolated from its environment. You just have to ask the right questions and use a suitable definition of entropy," says Marcus Huber.
If you are investigating quantum systems that consist of very few particles (for example, a hydrogen atom with only a few electrons), then such considerations are irrelevant. But today, especially with regard to modern technical applications of quantum physics, we are often faced with the challenge of describing quantum systems that consist of many particles. “To describe such many-particle systems, it is essential to reconcile quantum theory with thermodynamics,” says Marcus Huber. “That's why we also want to use our basic research to lay the foundation for new quantum technologies.”
