1. Photonics and microelectromechanical systems fabricated separately on different wafers can now be aligned precisely by finishing with a single processing step. Microelectromechanical systems (MEMS), which consist of tiny moving parts driven by electrical signals, have found ready applications in optical communication systems. They are attractive in part because they can be integrated with other electrical and optical components to create a multifunctional device in a single package, which reduces fabrication costs and allows for greater performance.
A schematic view of the MEMS actuators integrated with silicon photonics on a silicon-on-insulator substrate. Red arrows indicate the direction of light or mechanical motion.
Researchers have now performed the first-ever theoretical modeling of copper-catalyzed atom transfer radical polymerization (ATRP) to explain quantitatively how radical polymerization rates are influenced by molecular structures and properties—laying out a critical roadmap for the production of next-generation polymer materials.
Fine-tuning ATRP rates is tricky because researchers must simultaneously optimize many diverse factors such as catalyst and radical geometries, solvents and reaction conditions.
To solve this problem, di Lena and Chai turned to computer-aided molecular design, a technique widely employed in the pharmaceutical drug discovery. They first performed theoretical calculations to extract hundreds of numerical parameters or ‘molecular descriptors’ corresponding to specific structural and chemical properties for a series of ATRP copper catalysts and organic radicals. They then conducted sophisticated statistical analyses on the data to reveal subsets of principal descriptors that had the most influence over polymerization rates.
Next, the team combined their chemical intuition with stringent testing to further narrow the list of descriptors. Finally, biology-inspired artificial intelligence techniques called genetic function algorithms were used to produce mathematical models that relate ATRP rates to algebraic combinations of descriptors like energy levels, molecular volumes and bond lengths. According to di Lena, these models are striking because they agree with the generally accepted mechanistic picture of ATRP and can provide unprecedented predictive insights.
“This method should facilitate the design of new ATRP catalysts by screening, in a virtual way, hundreds of metal complexes at time,” says di Lena. “Labs will only need to prepare the most promising candidates, saving time and money.” Di Lena is also confident that the method will become a powerful tool for developing polymers with tailored properties and functions.
3. caffolds that are able to support stem-cell proliferation and differentiation in culture may not have the same effects in the human body Their research highlights the need to develop better benchmarking standards prior to transplantation.
Researchers have now developed a fully automated portable desktop system for rapidly diagnosing infectious diseases and successfully applied it for the diagnosis of influenza.
The researchers have shown experimentally that their system can efficiently detect influenza viruses in samples that contain as few as 100 viral particles per milliliter. It does so by applying the real-time polymerase chain reaction (RT-PCR) process to amplify the viral RNA before molecular analysis.
All the operator has to do is to take a swab from the patient, add a solution, and inject it with a syringe needle into a disposable self-contained cartridge (pictured) holding all of the necessary RT-PCR reactants. The entire preparation and diagnostic process is thereafter fully automated and takes just 2.5 hours to complete. The sealed cartridge containing all of the waste products can then be safely disposed of.
The researchers have successfully used their automated system to type and subtype seasonal H1N1 influenza viruses, and showed that the system has comparable sensitivity to that of conventional diagnostic methods. In principle, the system could be used to diagnose other infectious diseases caused by viruses that have many subtypes leading to similar patient symptoms.
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Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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