Urban Air Port has chosen to build its first Air-One transport hub for autonomous delivery drones and electric flying cars next to the Ricoh Arena in Coventry, UK. The futuristic facility will launch later this year. It will support delivery drone and air taxi technology and eventually transport cargo and people across cities.
A supermassive black hole is speeding across the galaxy, and astronomers are baffled as to why.
The Research Group on Synthetic Biology for Biomedical Applications at Pompeu Fabra University in Barcelona, Spain, has designed a cellular device capable of computing by printing cells on paper. For the first time, they have developed a living device that could be used outside the laboratory without a specialist, and it could be produced on an industrial scale at low cost. The study is published in Nature Communications and was carried out by Sira Mogas-Díez, Eva Gonzalez-Flo and Javier Macía.
We currently have many electronic devices available to us such as computers and tablets whose computing power is highly efficient. But, despite their power, they are very limited devices for detecting biological markers, such as those that indicate the presence of a disease. For this reason, a few years ago ‘biological computers’ began to be developed—in other words, living cellular devices that can detect multiple markers and generate complex responses. In them, the researchers leverage biological receptors that allow detecting exogenous signals and, by means of synthetic biology, modify them to emit a response in accordance with the information they detect.
So far, cellular devices have been developed that must operate in the laboratory, for a limited time, under specific conditions, and must be handled by a specialist in molecular biology. Now, a team of researchers from Pompeu Fabra University has developed new technology to ‘print’ cellular devices on paper that can be used outside the laboratory.
Research papers come out far too rapidly for anyone to read them all, especially in the field of machine learning, which now affects (and produces papers in) practically every industry and company. This column aims to collect some of the most relevant recent discoveries and papers — particularly in but not limited to artificial intelligence — and explain why they matter.
This week brings a few unusual applications of or developments in machine learning, as well as a particularly unusual rejection of the method for pandemic-related analysis.
Continue reading “Deep science: AI is in the air, water, soil and steel” »
Researchers at the University of Ottawa have debunked the decade-old myth of metals being useless in photonics – the science and technology of light – with their findings, recently published in Nature Communications, expected to lead to many applications in the field of nanophotonics.
“We broke the record for the resonance quality factor (Q-factor) of a periodic array of metal nanoparticles by one order of magnitude compared to previous reports,” said senior author Dr. Ksenia Dolgaleva, Canada Research Chair in Integrated Photonics (Tier 2) and Associate Professor in the School of Electrical Engineering and Computer Science (EECS) at the University of Ottawa.
“It is a well-known fact that metals are very lossy when they interact with light, which means they cause the dissipation of electrical energy. The high losses compromise their use in optics and photonics. We demonstrated ultra-high-Q resonances in a metasurface (an artificially structured surface) comprised of an array of metal nanoparticles embedded inside a flat glass substrate. These resonances can be used for efficient light manipulating and enhanced light-matter interaction, showing metals are useful in photonics.”
Astroscale’s ELSA-d mission is set to launch into orbit to demonstrate technologies that could help clean up space debris around Earth.
In this work, we carry out KS-MD simulations for a range of elements, temperatures, and densities, allowing for a systematic comparison of three RPP models. While multiple RPP models can be selected, 7–11 7. J. Vorberger and D. Gericke, “Effective ion–ion potentials in warm dense matter,” High Energy Density Phys. 9, 178 (2013). https://doi.org/10.1016/j.hedp.2012.12.009 8. Y. Hou, J. Dai, D. Kang, W. Ma, and J. Yuan, “Equations of state and transport properties of mixtures in the warm dense regime,” Phys. Plasmas 22, 022711 (2015). https://doi.org/10.1063/1.4913424 9. K. Wünsch, J. Vorberger, and D. Gericke, “Ion structure in warm dense matter: Benchmarking solutions of hypernetted-chain equations by first-principle simulations,” Phys. Rev. E 79, 010201 (2009). https://doi.org/10.1103/PhysRevE.79.010201 10. L. Stanton and M. Murillo, “Unified description of linear screening in dense plasmas,” Phys. Rev. E 91, 033104 (2015). https://doi.org/10.1103/PhysRevE.91.033104 11. W. Wilson, L. Haggmark, and J. Biersack, “Calculations of nuclear stopping, ranges, and straggling in the low-energy region,” Phys. Rev. B 15, 2458 (1977). https://doi.org/10.1103/PhysRevB.15.2458 we choose to compare the widely used Yukawa potential, which accounts for screening by linearly perturbing around a uniform density in the long-wavelength (Thomas–Fermi) limit, a potential constructed from a neutral pseudo-atom (NPA) approach, 12–15 12. L. Harbour, M. Dharma-wardana, D. D. Klug, and L. J. Lewis, “Pair potentials for warm dense matter and their application to x-ray Thomson scattering in aluminum and beryllium,” Phys. Rev. E 94, 053211 (2016). https://doi.org/10.1103/PhysRevE.94.053211 13. M. Dharma-wardana, “Electron-ion and ion-ion potentials for modeling warm dense matter: Applications to laser-heated or shock-compressed Al and Si,” Phys. Rev. E 86, 036407 (2012). https://doi.org/10.1103/PhysRevE.86.036407 14. F. Perrot and M. Dharma-Wardana, “Equation of state and transport properties of an interacting multispecies plasma: Application to a multiply ionized al plasma,” Phys. Rev. E 52, 5352 (1995). https://doi.org/10.1103/PhysRevE.52.5352 15. L. Harbour, G. Förster, M. Dharma-wardana, and L. J. Lewis, “Ion-ion dynamic structure factor, acoustic modes, and equation of state of two-temperature warm dense aluminum,” Phys. Rev. E 97, 043210 (2018). https://doi.org/10.1103/PhysRevE.97.043210 and the optimal force-matched RPP that is constructed directly from KS-MD simulation data.
Each of the models we chose impacts our physics understanding and has clear computational consequences. For example, success of the Yukawa model reveals the insensitivity to choices in the pseudopotential and screening function and allows for the largest-scale simulations. Large improvements are expected from the NPA model, which makes many fewer assumptions with a modest cost of pre-computing and tabulating forces. (See the Appendix for more details on the NPA model.) The force-matched RPP requires KS-MD data and is therefore the most expensive to produce, but it reveals the limitations of RPPs themselves since they are by definition the optimal RPP.
Using multiple metrics of comparison between RPP-MD and KS-MD including the relative force error, ion–ion equilibrium radial distribution function g (r), Einstein frequency, power spectrum, and the self-diffusion transport coefficient, the accuracy of each RPP model is analyzed. By simulating disparate elements, namely, an alkali metal, multiple transition metals, a halogen, a nonmetal, and a noble gas, we see that force-matched RPPs are valid for simulating dense plasmas at temperatures above fractions of an eV and beyond. We find that for all cases except for low temperature carbon, force-matched RPPs accurately describe the results obtained from KS-MD to within a few percent. By contrast, the Yukawa model appears to systematically fail at describing results from KS-MD at low temperatures for the conditions studied here validating the need for alternate models such as force-matching and NPA approaches at these conditions.
It’s another step on the road to developing quantum information processing applications: A key experiment succeeded in going beyond the previously defined limits for photon applications. Anahita Khodadad Kashi and Prof. Dr. Michael Kues from the Institute of Photonics and the Cluster of Excellence PhoenixD at Leibniz University Hannover (Germany) have demonstrated a novel interference effect. The scientists have thus shown that new color-coded photonic networks can be tapped, and the number of photons involved can be scaled. “This discovery could enable new benchmarks in quantum communication, computational operations of quantum computers as well as quantum measurement techniques and is feasible with existing optical telecommunication infrastructure,” says Kues.
The decisive experiment was successfully performed in the newly established Quantum Photonics Laboratory (QPL) of the Institute of Photonics and the Hannover Centre for Optical Technologies at Leibniz University Hannover. Anahita Khodadad Kashi succeeded in quantum-mechanically interfering independently generated pure photons with different colors, i.e., frequencies. Khodadad Kashi detected a so-called Hong-Ou-Mandel effect.
Hong-Ou-Mandel interference is a fundamental effect of quantum optics that forms the basis for many quantum information processing applications—from quantum computing to quantum metrology. The effect describes how two photons behave when they collide on a spatial beam splitter and explains the phenomenon of quantum mechanical interference.
The regeneration of damaged central nervous system (CNS) tissues is one of the biggest goals of regenerative medicine.
Most stroke victims don’t receive treatment fast enough to prevent brain damage. Scientists at The Ohio State University Wexner Medical Center, College of Engineering and College of Medicine have developed technology to “retrain” cells to help repair damaged brain tissue. It’s an advancement that may someday help patients regain speech, cognition and motor function, even when administered days after an ischemic stroke.
Engineering and medical researchers use a process created by Ohio State called tissue nanotransfection (TNT) to introduce genetic material into cells. This allows them to reprogram skin cells to become something different—in this case vascular cells—to help fix damaged brain tissue.
