Lifeboat Foundation

Circa 2018

Digitization results in a high energy consumption. In industrialized countries, information technology presently has a share of more than 10% in total power consumption. The transistor is the central element of digital data processing in computing centers, PCs, smartphones, or in embedded systems for many applications from the washing machine to the airplane. A commercially available low-cost USB memory stick already contains several billion transistors. In the future, the single-atom transistor developed by Professor Thomas Schimmel and his team at the Institute of Applied Physics (APH) of KIT might considerably enhance energy efficiency in information technology. “This quantum electronics element enables switching energies smaller than those of conventional silicon technologies by a factor of 10,000,” says physicist and nanotechnology expert Schimmel, who conducts research at the APH, the Institute of Nanotechnology (INT), and the Material Research Center for Energy Systems (MZE) of KIT. Earlier this year, Professor Schimmel, who is considered the pioneer of single-atom electronics, was appointed Co-Director of the Center for Single-Atom Electronics and Photonics established jointly by KIT and ETH Zurich.

In Advanced Materials, the KIT researchers present the transistor that reaches the limits of miniaturization. The scientists produced two minute metallic contacts. Between them, there is a gap as wide as a single metal atom. “By an electric control pulse, we position a single silver atom into this gap and close the circuit,” Professor Thomas Schimmel explains. “When the silver atom is removed again, the circuit is interrupted.” The world’s smallest transistor switches current through the controlled reversible movement of a single atom. Contrary to conventional quantum electronics components, the single-atom transistor does not only work at extremely low temperatures near absolute zero, i.e.-273°C, but already at room temperature. This is a big advantage for future applications.

Continue reading “Smallest transistor worldwide switches current with a single atom in solid electrolyte” »

Researchers at Aalto University have shown that a nanoparticle suspension can serve as a simple model for studying the formation of patterns and structures in more complicated non-equilibrium systems, such as living cells. The new system will not only be a valuable tool for studying patterning processes but also has a wide range of potential technological applications.

The mixture consists of an oily liquid carrying nanoparticles of iron oxide, which become magnetized in a magnetic field. Under the right conditions, applying a voltage across this ferrofluid causes the nanoparticles to migrate, forming a concentration gradient in the mixture. For this to work, the ferrofluid has to also include docusate, a waxy chemical that can carry charge through the fluid.

The researchers discovered that the presence of docusate and a voltage across the ferrofluid resulted in a separation of electric charges, with the iron oxide nanoparticles becoming negatively charged. “We didn’t expect that at all,” says Carlo Rigoni, a postdoctoral researcher at Aalto. “We still don’t know why it happens. In fact, we don’t even know whether the charges already get split when the docusate is added or if it happens as soon as voltage is turned on.”

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Continue reading “This Boiling Liquid goes in your MONITOR — Facility Tour!” »

Demonstrating that a material thought to be always chemically inert, hexagonal boron nitride (hBN), can be turned chemically active holds potential for a new class of catalysts with a wide range of applications, according to an international team of researchers.

HBN is a layered material and monolayers can be exfoliated like in graphene 0, another two-dimensional material. However, there is a key difference between the two.

“While hBN shares similar structure as graphene, the strong polar bonds between the boron and nitride atoms makes hBN unlike graphene in that it is chemically inert and thermally stable at high temperature,” said Yu Lei, postdoctoral scholar in physics at Penn State and first co-author in the study published in Materials Today.

Drug-target interaction is a prominent research area in drug discovery, which refers to the recognition of interactions between chemical compounds and the protein targets. Chemists estimate that 1,060 compounds with drug-like properties could be made—that’s more than the total number of atoms in the Solar System, as an article reported in the journal Nature in 2017.

Drug development, on average, takes about 14 years and costs up to 1.5 billion dollars. During the journey of drug discovery in this vast “galaxy,” it is apparent that traditional biological experiments for DTI detection are normally costly and time-consuming.

Prof. Hou Tingjun is an expert in computer-aided drug design (CADD) at the Zhejiang University College of Pharmaceutical Sciences. In the past decades, he has been committed to developing drugs using computer technology. “The biggest challenge lies in the interactions between unknown targets and drug molecules. How can we discover them more efficiently? This involves a new breakthrough in method.”

A new study finds the magnetic field generated by a tsunami can be detected a few minutes earlier than changes in sea level and could improve warnings of these giant waves.

Tsunamis generate magnetic fields as they move conductive seawater through the Earth’s magnetic field. Researchers previously predicted that the tsunami’s magnetic field would arrive before a change in sea level, but they lacked simultaneous measurements of magnetics and sea level that are necessary to demonstrate the phenomenon.

The new study provides real-world evidence for using tsunamis’ magnetic fields to predict the height of tsunami waves using data from two real events—a 2009 tsunami in Samoa and a 2010 tsunami in Chile—that have both sets of necessary data. The new study was published in AGU’s Journal of Geophysical Research: Solid Earth, which focuses on the physics and chemistry of the solid Earth.

Method combines quantum mechanics with machine learning to accurately predict oxide reactions at high temperatures when no experimental data is available; could be used to design clean carbon-neutral processes for steel production and metal recycling.

Extracting metals from oxides at high temperatures is essential not only for producing metals such as steel but also for recycling. Because current extraction processes are very carbon-intensive, emitting large quantities of greenhouse gases, researchers have been exploring new approaches to developing “greener” processes. This work has been especially challenging to do in the lab because it requires costly reactors. Building and running computer simulations would be an alternative, but currently there is no computational method that can accurately predict oxide reactions at high temperatures when no experimental data is available.

A Columbia Engineering team reports that they have developed a new computation technique that, through combining quantum mechanics and machine learning, can accurately predict the reduction temperature of metal oxides to their base metals. Their approach is computationally as efficient as conventional calculations at zero temperature and, in their tests, more accurate than computationally demanding simulations of temperature effects using quantum chemistry methods. The study, led by Alexander Urban, assistant professor of chemical engineering, was published on December 1, 2021 by Nature Communications.

Syngas is an important feedstock for modern chemical industries and can be directly used as fuel. Carbon monoxide (CO) is its main component. Direct conversion of widespread renewable biomass resources into CO can help to achieve sustainable development.

Conventionally, bio-syngas is mainly produced through thermal-chemical processes such as pyrolysis, steam reforming or aqueous reforming, which require high temperature and consume a lot of energy.

Recently, a research team led by Prof. Wang Feng from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences, in collaboration with Prof. Wang Min from Dalian University of Technology, developed a new method to directly convert bio-polyols into CO.

Quantum and biological systems are seldom discussed together as they seemingly demand opposing conditions. Life is complex, “hot and wet” whereas quantum objects are small, cold and well controlled. Here, we overcome this barrier with a tardigrade — a microscopic multicellular organism known to tolerate extreme physiochemical conditions via a latent state of life known as cryptobiosis. We observe coupling between the animal in cryptobiosis and a superconducting quantum bit and prepare a highly entangled state between this combined system and another qubit. The tardigrade itself is shown to be entangled with the remaining subsystems. The animal is then observed to return to its active form after 420 hours at sub 10 mK temperatures and pressure of $6\times 10^{-6}$ mbar, setting a new record for the conditions that a complex form of life can survive.