Lifeboat Foundation

Researchers in the UK claim to have developed a microfluidic chip that can rapidly tell whether someone has suffered a traumatic brain injury from a finger-prick blood sample. The optofluidic device detects a biomarker linked to brain injury, based on the way that it scatters light (Nat. Biomed. Eng. 10.1038/s41551-019‑0510-4).

An optofluidic device uses Raman spectroscopy to detect a biomarker in blood associated with traumatic brain injury.

Physicists at Purdue University and the University of New South Wales have built a transistor from a single atom of phosphorous precisely placed on a bed of silicon, taking another step towards the holy grail of tech research: the quantum computer.

Revealed on Sunday in the academic journal Nature Nanotechnology, the research is part of a decade-long effort at the University of New South Wales to deliver a quantum computer – a machine that would use the seemingly magical properties of very small particles to instantly perform calculations beyond the scope of today’s classical computers.

Continue reading “Physicists Foretell Quantum Computer With Single-Atom Transistor” »

https://youtube.com/watch?v=zXSsd7uXjt8

Engineers at the University of Washington are working on a new type of rocket engine that holds the promise of being lighter, more efficient, and simpler to make than conventional liquid-fuel rockets. Called a Rotational Detonation Engine (RDE), one of the biggest hurdles to making it practical is to develop mathematical models that can describe how the very unpredictable engine design works in order to make it more stable.

An RDE is a rocket engine that is similar to the pulse jet engines that powered the infamous German V1 cruise missile of the Second World War, which used a simple combustion chamber with an exhaust pipe at one end and spring-mounted slats on the front face. In operation, air would come in through the slats, mix with fuel, which was then detonated, producing a pulse of thrust. An RDE takes this idea one step further.

Continue reading “Computer modeling brings simple, efficient rocket engine closer to reality” »

A bionic revolution is brewing, as recent advancements in bioengineering have brought about scientific breakthroughs in rehabilitation for people with disabilities. The most cutting edge research is happening inside the human brain, where implanted technology allows people to communicate directly with computers, using their thoughts.

VICE’s Wilbert L. Cooper travels to Zurich to see the first-ever bionic Olympics and discovers a host of technologies that are expanding what it means to be human.

Continue reading “How Bionic Limbs Are Changing Lives | VICE on HBO” »

Today’s defense electronics systems rely on radio frequency (RF) mixed-mode electronics – those that integrate RF, analog, and digital circuits onto a single chip – to interface RF signals with digital processors. This technology supports critical communications, radar, and electronic warfare (EW) capabilities, as well as being widely used to support commercial telecommunications. The Department of Defense (DoD) has capability demands that far exceed the requirements of the commercial world in terms of speed, fidelity, capacity, and precision. Current commercial RF mixed-mode systems on a chip (SoCs) are implemented on digital complementary metal oxide semiconductor (CMOS) platforms, a technology that has been used for decades to construct integrated circuits, highly integrated transceivers, microprocessors, and beyond. Despite continued advancement and scaling along the trajectory of Moore’s Law for high integration density, these CMOS platforms are unable to support operations at higher frequencies with larger signal bandwidths and higher resolutions, essentially limiting their use in next-generation mixed-mode interfaces needed for emerging defense RF applications.

To advance RF mixed-mode interfaces beyond current limitations, DARPA established the Technologies for Mixed-mode Ultra Scaled Integrated Circuits (T-MUSIC) program. T-MUSIC was first announced in January 2019 as a part of the second phase of DARPA’s Electronics Resurgence Initiative (ERI). One area of research under ERI Phase II focuses on the integration of photonics and RF components directly into advanced circuits and semiconductor manufacturing processes, enabling unique and differentiated domestic manufacturing capabilities. As such, T-MUSIC will explore the integration of mixed-mode electronics into advanced onshore semiconductor manufacturing processes. The goal is to develop highly integrated RF electronics with an unprecedented combination of wide spectral coverage, high resolution, large dynamic range, and high information processing bandwidth.

Quantum computing might initially sound like a far-fetched futuristic idea, but companies such as Amazon, Google, and IBM are putting their weight behind it and preparations have begun. With quantum computing potentially within our reach, what will happen to our current security models and modern-day encryption? See what security experts are doing to prepare for quantum threats.

The future is here. Or just about. After a number of discoveries, researchers have proven that quantum computing is possible and on its way. The wider world did not pause long on this discovery: Goldman Sachs, Amazon, Google, and IBM have just announced their own intentions to embark on their own quantum developments.

Now that it’s within our reach we have to start seriously considering what that means in the real world. Certainly, we all stand to gain from the massive benefits that quantum capabilities can bring, but so do cybercriminals.

Competition between the U.S. and China in quantum computing revolves, in part, around the role such a system could play in breaking the encryption that makes things secure on the internet.

Truly useful quantum computing applications could be as much as a decade away, Aaronson says. Initially, these tools would be highly specialized.

“The way I put it is that we’re now entering the very, very early, vacuum-tube era of quantum computers,” he says.

Massive-scale particle physics produces correspondingly large amounts of data – and this is particularly true of the Large Hadron Collider (LHC), the world’s largest particle accelerator, which is housed at the European Organization for Nuclear Research (CERN) in Switzerland. In 2026, the LHC will receive a massive upgrade through the High Luminosity LHC (HL-LHC) Project. This will increase the LHC’s data output by five to seven times – billions of particle events every second – and researchers are scrambling to prepare big data computing for this deluge of particle physics data. Now, researchers at Lawrence Berkeley National Laboratory are working to tackle high volumes of particle physics data with quantum computing.

When a particle accelerator runs, particle detectors offer data points for where particles crossed certain thresholds in the accelerator. Researchers then attempt to reconstruct precisely how the particles traveled through the accelerator, typically using some form of computer-aided pattern recognition.

This project, which is led by Heather Gray, a professor at the University of California, Berkeley, and a particle physicist at Berkeley Lab, is called Quantum Pattern Recognition for High-Energy Physics (or HEP.QPR). In essence, HEP.QPR aims to use quantum computing to speed this pattern recognition process. HEP.QPR also includes Berkeley Lab scientists Wahid Bhimji, Paolo Calafiura and Wim Lavrijsen.

Single-purpose quantum computers are helping physicists build simulations of nature’s greatest hits and observe them up close.