The launch was expected to encounter many technical and engineering challenges, including simplified procedures for pre-launch testing, the rocking motion of the ship and heat dissipation in a confined space.
China has become the first nation to fully own and operate a floating launch platform for its space missions.
Atomic BECs were first achieved in 1995. Although it has become easier to realize atomic BECs since their discovery, they still require very low temperatures for operation. For most purposes, this is too expensive and impractical. Alternatively, negatively charged quatrons are quasi-particles composed of a hole and three electrons which form a stable BEC when coupled to light in triple quantum layer structures in semiconductor microcavities. This allows for both the greater experimental control found in quantum optics, and the benefits of matter wave systems, such as superconductivity and coherence. Moreover, due to the extremely small effective mass of the quasi-particles, quatrons can be used to achieve superconducting BECs at room temperature.
The Create the Future Design Contest was launched in 2002 by the publishers of NASA Tech Briefs magazine to help stimulate and reward engineering innovation. The annual event has attracted more than 8,000 product design ideas from engineers, entrepreneurs, and students worldwide.
Researchers, from biochemists to material scientists, have long relied on the rich variety of organic molecules to solve pressing challenges. Some molecules may be useful in treating diseases, others for lighting our digital displays, still others for pigments, paints, and plastics. The unique properties of each molecule are determined by its structure—that is, by the connectivity of its constituent atoms. Once a promising structure is identified, there remains the difficult task of making the targeted molecule through a sequence of chemical reactions. But which ones?
Organic chemists generally work backwards from the target molecule to the starting materials using a process called retrosynthetic analysis. During this process, the chemist faces a series of complex and inter-related decisions. For instance, of the tens of thousands of different chemical reactions, which one should you choose to create the target molecule? Once that decision is made, you may find yourself with multiple reactant molecules needed for the reaction. If these molecules are not available to purchase, then how do you select the appropriate reactions to produce them? Intelligently choosing what to do at each step of this process is critical in navigating the huge number of possible paths.
Researchers at Columbia Engineering have developed a new technique based on reinforcement learning that trains a neural network model to correctly select the “best” reaction at each step of the retrosynthetic process. This form of AI provides a framework for researchers to design chemical syntheses that optimize user specified objectives such synthesis cost, safety, and sustainability. The new approach, published May 31 by ACS Central Science, is more successful (by ~60%) than existing strategies for solving this challenging search problem.
Continue reading “Deep learning techniques teach neural model to ‘play’ retrosynthesis” »
Thanks to a team of researchers from the University of Illinois at Urbana-Champaign and the University of Massachusetts Amherst, scientists are able to read patterns on long chains of molecules to understand and predict behavior of disordered strands of proteins and polymers. The results could, among other things, pave the way to develop new materials from synthetic polymers.
The lab of Charles Sing, assistant professor of chemical and biomolecular engineering at Illinois, provided the theory behind the discovery, which was then verified through experiments conducted in the lab of Sarah Perry, assistant professor of chemical engineering at UMass Amherst, and Illinois alumna. The collaborators detailed their findings in a paper titled “Designing Electrostatic Interactions via Polyelectrolyte Monomer Sequence” published in ACS (American Chemical Society) Central Science.
The colleagues set out to understand the physics behind the precise sequence of charged monomers along the chain and how it affects the polymer’s ability to create self-assembling liquid materials called complex coacervates.
Continue reading “Researchers can now predict properties of disordered polymers” »
. The lectures introduce our current understanding of computational intelligence and ways in which strong AI could possibly be achieved, with insights from deep learning, reinforcement learning, computational neuroscience, robotics, cognitive modeling, psychology, and more.
Ray Kurzweil is one of the world’s leading inventors, thinkers, and futurists, with a thirty-year track record of accurate predictions. Called “the restless genius” by The Wall Street Journaland “the ultimate thinking machine” by Forbes magazine, Kurzweil was selected as one of the top entrepreneurs by Inc. magazine, which described him as the “rightful heir to Thomas Edison.” PBS selected him as one of the “sixteen revolutionaries who made America.”
The ability to confine water in an enclosed compartment without directly manipulating it or using rigid containers is an attractive possibility. In a recent study, Sara Coppola and an interdisciplinary research team in the departments of Biomaterials, Intelligent systems, Industrial Production Engineering and Advanced Biomaterials for Healthcare in Italy, proposed a water-based, bottom-up approach to encase facile, short-lived water silhouettes in a custom-made adaptive suit.
In the work, they used a biocompatible polymer that could self-assemble with unprecedented degrees of freedom on the water surface to produce a thin membrane. They custom designed the polymer film as an external container of a liquid core or as a free-standing layer. The scientists characterized the physical properties and morphology of the membrane and proposed a variety of applications for the phenomenon from the nanoscale to the macroscale. The process could encapsulate cells or microorganisms successfully without harm, opening the way to a breakthrough approach applicable for organ-on-a-chip and lab-in-a-drop experiments. The results are now published in Science Advances.
The possibility of isolating, engineering and shaping materials into 2-D or 3D objects from the nanometer to the microscale via bottom-up engineering is gaining importance in materials science. Understanding the physics and chemistry of materials will allow a variety of applications in microelectronics, drug delivery, forensics, archeology and paleontology and space research. Materials scientists use a variety of technical methods for microfabrication including two-photon polymerization, soft interference lithography, replica molding and self-folding polymers to shape and isolate the material of interest. However, most materials engineering protocols require chemical and physical pretreatments to gain the desired final properties.
Quantum information protocols are based on a variety of entanglement modes such as Einstein-Podolsky-Rosen (EPR), Greenberger-Horne-Zeilinger (GHZ) and other cluster states. For on-demand preparation, these states can be realized with squeezed light sources in optics, but such experiments lack versatility as they require a variety of optical circuits to individually realize diverse states of entanglement. In a recent study, Shuntaro Takeda and colleagues at the interdisciplinary departments of Applied Physics and Engineering in Japan addressed the shortcoming by developing an on-demand entanglement synthesizer. Using the experimental setup, the physicists programmably generated entangled states from a single squeezed source of light.
In the work, they used a loop-based circuit dynamically controlled at nanosecond time scales to process optical pulses in the time domain. The scientists generated and verified five different small-scale entangled states and a large-cluster containing more than 1000 modes in a single setup without changing the optical circuit. The circuit developed by Takeda et al. could store and release one part of the generated entangled states to function as a quantum memory. The experimental report published on Science Advances, will open a new way to build general entanglement synthesizers on-demand using a scalable quantum processor.
Entanglement is essential for many quantum information protocols in qubit and continuous variable (CV) regions, where they perform a variety of applications. For instance, the two-mode Einstein-Podolsky-Rosen (EPR) state is the most commonly used, maximally entangled state as a building block for two-party quantum communication and for quantum logic gates based on quantum teleportation. The generalized version of this state is an n-mode Greenberger-Horne-Zeilinger (GHZ) state central to building a quantum network, where the GHZ quantum state can be shared between n participants. For example, the n participants can communicate with each other for quantum secret sharing. For quantum computation on the other hand, a special type of entanglement known as cluster states has attracted much attention as a universal resource to allow one-way quantum computation.
Continue reading “On-demand, photonic entanglement synthesizer” »
Dehgan hopes that the organization’s prizes and other initiatives will bring innovative solutions to conservation’s deepest problems. Hundreds of people have already been lured in through challenges and engineering programmes such as Make for the Planet — a multi-day, in-person event — and an online tech collaboration platform called Digital Makerspace, which matches conservationists with technical talent.
Standard efforts have failed to slow the pace of extinctions, so Conservation X Labs is trying a fresh approach.
Top artificial intelligence (AI) expert and founder and CEO of Fountech.ai Nikolas Kairinos said in a Daily Star interview that within 20 years we could have implants put into our heads that will allow us to learn everything. “You won’t need to memorize anything,” said the specialist to the Daily Star.
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It’s easy to miss the mirror forge at the University of Arizona. While sizable, the Richard F. Caris Mirror Laboratory sits in the shadow of the university’s much larger 56,000-seat football stadium. Even its most distinctive feature—an octagonal concrete prominence emblazoned with the school’s logo—looks like an architectural feature for the arena next door. But it’s that tower that houses some of the facility’s most critical equipment.
Inside the lab, a narrow, fluorescent-green staircase spirals up five floors to the tower’s entrance. I’m a few steps from the top when lab manager Stuart Weinberger asks, for the third time, whether I have removed everything from my pockets.
“Glasses, keys, pens. Anything that could fall and damage the mirror,” he says. Weinberger has agreed to escort me to the top of the tower and onto a catwalk some 80 feet above a mirror 27.5 feet in diameter. A mirror that has already taken nearly six years—and $20 million—to make. “Most people in the lab aren’t even allowed up here,” he says. That explains Weinberger’s nervousness about the contents of my pockets (which are really, truly empty), and why he has tethered my camera to my wrist with a short line of paracord.
Continue reading “The Astounding Engineering Behind the Giant Magellan Telescope” »
