Swiss researcher builds new system for drying fruit by means of ionic wind

After the summer harvest, fruits are sold as dried products suitable for the current season. However, if fruit or vegetables are dried with heat, nutrients can be destroyed and flavors can be reduced. This is why non-thermal drying of food – i.e. without heating – is preferred by the industry. Among other things, fans are used for this purpose. A new drying process developed at Empa using ionic wind promises to make the non-thermal drying of food much more energy-efficient, faster, and even gentler.

When the blades of a fan rotate, the steady wind is blowing as a result. This phenomenon is well known from everyday life, and so we use the fan on hot summer days to cool us down. An unwanted side effect is the unpleasant feeling in the eyes, which becomes drier and drier due to the artificial wind. The food industry has been taking advantage of this effect for a long time: Fruit and veggies are preferably dried without heat because heat deteriorates nutrients and flavor.

The so-called non-thermal convective drying of food with the help of large fans has a drawback, however: The drying process is time-consuming and requires a lot of energy. This is why the industry has been looking to find a more energy-efficient method for a long time. One alternative technology is based on the so-called ionic wind. Although this already works on a small scale, attempts to upscale the concept for the industry have failed so far. Empa researchers have now developed a more energy-efficient drying system based on ionic wind, which is perfectly suitable for industrial applications.

Wind, without any moving components

The ionic wind is not generated by the rotating blades of a fan; it is created by connecting, for instance, a metal wire to a high-voltage source with a positive voltage of 10,000 to 30,000 volts. This charges the wire positively and ionizes the surrounding air. Air consists of various gases such as oxygen (O2), nitrogen (N2), or carbon dioxide (CO2). Each of these molecules consists of atoms, which in turn consist of positively charged elementary particles – the protons – and negatively charged particles – the electrons. The electrons are attracted by the positively charged wire, while the much heavier protons are repelled by the wire. These electrostatic forces ultimately cause electrons to "split off" from the (electrically neutral) gas molecules, the remaining molecules are now positively charged – or "ionized". The positive ions collide with other air molecules on their way away from the wire towards the grounded collector located below the wire and set them in motion. This impulse, or rather the particle movement triggered by it, then creates the ionic wind, which is also known as electrohydrodynamic airflow.

Small but powerful!

Researchers tried to make use of ionic wind with different approaches for the industrial drying of food – but so far without remarkable success because an upscaling was not possible. Empa researcher Thijs Defraeye from the "Biomimetic Membranes and Textiles" lab and his team pursued the idea further and varied various process parameters. First, the researchers did not place the food to be dried on a tray as it was done previously but used a mesh instead. "Now this isn't exactly rocket science, but so far no one has considered this adaptation for the drying with the ionic wind," says the Empa researcher.

What sounds like a small change makes a huge difference, though: The water can now evaporate from all sides of the fruits or vegetables. As a result, the ionic wind dries the food twice as fast as on an impermeable tray, which was used by researchers over the world so far. But above all, the ionic wind dries fruit and vegetables more uniformly on the mesh. In contrast to the previous approaches of electrohydrodynamic drying, the new design is also easier to scale up – and thus extremely interesting for industry. Drying with ionic wind: If the fruit slices are placed on a mesh, they are dried faster and more evenly. Image: Empa{module INSIDE STORY}

A new system – from supercomputer modeling

In refining their new concept further, Empa researchers relied on complex supercomputer simulations. This allows various dryer device adjustments and their influence on the drying process to be simulated virtually. Hence, the system can be optimized "in silico" without having to physically build new drying equipment each time.

But can the results of the supercomputer calculation be successfully transferred into the real world? Is it really possible to optimize the process in this way? In cooperation with researchers from Dalhousie University in Canada, a first prototype of the new drying system was built in their lab. Initial tests did indeed show considerable improvements: Drying by means of ionic wind is much faster and consumes less than half the energy required by conventional processes. In addition, the food is dried more evenly and the nutrients are preserved much better. Last but not least, the process can be scaled up to an industrial-scale rather easily. Defraeye and his team are currently working with a Swiss retailer to develop the concept further.

Kavli IPMU research reveals history of temperature changes in the Universe

First measurement using the Sunyaev-Zeldovic

How hot is the Universe today? How hot was it before? A new study by an international team of researchers, including members of the Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU), suggests that the mean temperature of gas in large structures of the Universe has increased about 3 times in the last 8 billion years, to reach about two million Kelvin today.

The large-scale structure of the Universe refers to the global pattern of how galaxies and galaxy clusters are distributed in space. This cosmic net formed from tiny irregularities in the matter distribution in the early Universe, which were amplified through gravitational attraction. "As the Universe evolves, gravity pulls dark matter and gas in space together into galaxies and clusters of galaxies," said Yi-Kuan Chiang, the lead author of the study, and a research fellow at the Ohio State University Center for Cosmology and AstroParticle Physics. "The drag is violent--so violent that more and more gas is shocked and heated up." CAPTION supercomputer simulation of the evolution of the large-scale structure (bottom) and the temperature (top) of the Universe. The time flows from the left to the right panels, with the rightmost panel showing the present-day epoch.  CREDIT D. Nelson / Illustris Collaboration.{module INSIDE STORY}

This heated gas can then be used to measure the mean temperature of the Universe over cosmic time. In particular, the researchers used the so-called "Sunyaev-Zeldovich" effect, named after Rashid Sunyaev, director emeritus at the Max Planck Institute for Astrophysics, and Soviet-era physicist Yakov Zeldovich, who first predicted this phenomenon theoretically. This effect arises when low-energy photons of the cosmic microwave background radiation are scattered by hot electrons in the large-scale structure of the Universe. The scattering transfers energy from electrons to photons, making the hot electron gas visible. The intensity of the Sunyaev-Zeldovich effect is proportional to the thermal pressure of the gas, which, in turn, is proportional to the temperature of electrons.

While this measurement is straightforward in principle, collecting the necessary data was a major undertaking. The study, which has been published in the Astrophysical Journal, was done in a collaboration of researchers at the Kavli IPMU, the Ohio State University, the Johns Hopkins University, and the Max Planck Institute for Astrophysics.

The researchers used data collected by two observatories, the Planck satellite and the Sloan Digital Sky Survey (SDSS). Planck is the European Space Agency mission which measured the cosmic microwave background radiation. SDSS collected detailed images and light spectra of galaxies. Combining the two data sets, the scientists were able to measure the amount of thermal pressure around the locations of galaxies and clusters of galaxies.

"It took astronomers more than 15 years to collect the necessary data using a telescope on the ground and one in space," said Brice Ménard who led the analysis with Chiang. Ménard, who has been a visiting scientist at the Kavli IPMU since 2011, added: "On the analysis side, our team spent four years developing the algorithms necessary to extract the signal from these data."

What's more, interpretation of the data required a physical model, which was provided by Ryu Makiya, a research fellow at the Kavli IPMU. "Combining the latest data with a state-of-the-art theoretical model, we were able to reveal how the temperature of the Universe evolved, and how it was linked to formation of the large-scale structure of the Universe," Makiya said. "The next goal is to understand details of the physics of thermal and non-thermal phenomena."

Chiang, from the Ohio Stated University, added: "Our new measurement provides a direct confirmation of the seminal work by Jim Peebles--the 2019 Nobel Laureate in Physics--who laid out the theory of the emergence of large-scale structure of the Universe."

The study determined that about eight billion years ago (at a redshift z=1), the mean electron temperature was some 700,000 Kelvin, rising to about two million Kelvin today. Furthermore, the scientists determined that its evolution is almost entirely driven by the growth of structures, as gas is shock heated in collapsing large-scale structures.

Back in 2000, Eiichiro Komatsu, a Principal Investigator at the Kavli IPMU and Director at the Department of Physical Cosmology at the Max Planck Institute for Astrophysics, was also involved in a previous effort to calculate how the temperature of the Universe evolved. "For 20 years, we have been studying how to measure this using the Sunyaev-Zeldovich effect," he remembered. "We now have finally measured the temperature of the Universe, not only thanks to the remarkable progress in observational data, but also due to the dedicated efforts of brilliant young scientists such as Yi-Kuan Chiang and Ryu Makiya. This is very satisfying," Komatsu added.

New Cambridge Centre connects AI, medicine, UK life sciences sectors

A new center at the University of Cambridge, in collaboration with AstraZeneca and GSK, aims to use AI to make medical discoveries, accelerate the development of precision medicine and develop new treatments


On 10 November the University of Cambridge announced a five-year agreement with AstraZeneca and GSK to fund the Cambridge Centre for AI in Medicine (CCAIM). For the 5-year duration, AstraZeneca and GSK will support five new Ph.D. studentships per year. This program will enable the best and brightest young minds in machine learning and bioscience to partner with leaders in industry and academia, wherever they may be in the world.

CCAIM has been set up as a cutting-edge research group. Its faculty of 10 University of Cambridge researchers – in addition to world-class Ph.D. students, currently being recruited – have united to develop AI and machine learning (ML) technologies aiming to transform clinical trials, personalized medicine, and biomedical discovery. {module INSIDE STORY}

The center’s Director is Professor Mihaela van der Schaar, a world-leading researcher in machine learning (ML), and the Co-Director is researcher-clinician Professor Andres Floto (bios below). The faculty also includes Dr. Sarah Teichmann FMedSci FRS, Head of Cellular Genetics at the Wellcome Sanger Institute and founder and principal leader of the Human Cell Atlas international consortium.

Successfully bridging the gap between the disparate and complex fields of AI and medicine requires building from both sides simultaneously. CCAIM brings together a diverse coalition of leading Cambridge scientists and clinicians, with expertise in machine learning, engineering, mathematics, medicine, computer science, genetics, computational biology, biostatistics, clinical research, healthcare policy and more.

These multi-disciplinary experts from the University of Cambridge will work in close collaboration with scientists and leaders from AstraZeneca and GSK to identify critical challenges facing drug discovery and development that have the potential to be solved through cutting-edge academic research.

The centre’s research output and the implementation of its ML tools could be transformational not only for the pharmaceutical industry – including in clinical trials and drug discovery – but also for the clinical delivery of healthcare to patients. The CCAIM team already has deep research links with the NHS, and four of the centre’s members are NHS doctors.

Professor Mihaela van der Schaar said:
“Machine learning has the potential to truly revolutionize the delivery of healthcare, to the great benefit of patients, clinicians, and the wider medical ecosystem. But to realize this potential requires true and deep cross-disciplinary understanding – a great challenge because we speak different languages. CCAIM is designed to break down the barriers between machine learning and medical science, to create a unique forum in which we can work together to truly understand the challenges, formalize the problems, and develop practical solutions that can be readily implemented in healthcare.”

Professor Andre Floto said:
“We are thrilled that the Cambridge Centre for AI in Medicine is taking off. From tackling the immediate threats of COVID-19 to the long-term transformation of healthcare systems, our network of experts and incoming Ph.D. students will bring next-level AI to bear on the most pressing medical issues of our time.”

Professor Andy Neely OBE, Pro-Vice-Chancellor for Enterprise and Business Relations, University of Cambridge, said:
“The Cambridge Centre for AI in Medicine is a terrific and timely venture that builds on the strong relationships between the University of Cambridge and global leaders in the pharmaceutical industry, AstraZeneca and GSK.
“The depth and diversity of the CCAIM faculty’s expertise mean it is uniquely positioned to deliver and accelerate the breakthroughs in medical science and healthcare that AI has long promised. I anticipate the center’s impact will be nothing less than transformational.”
Jim Weatherall, Vice President, Data Science & AI, R&D, AstraZeneca, said:
“We know the best science doesn’t happen in isolation which is why collaboration is essential to the way we work. This new center combines world-class academia with real-world industrial challenges and will help to develop cutting-edge AI to potentially transform the way we discover and develop medicines.”

Kim Branson, Senior Vice President and Global Head of AI/ML, GSK, said:
“The new Cambridge Centre for AI in Medicine will recruit and train the next generation of practitioners at the intersection of AI, industry, and academia. The work of this institute will be critical to translating AI methods from theory to practice, so that we can keep improving our therapeutic discovery efforts and so that together we can make a tangible impact on patients, from diagnosis to treatment and beyond.”