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Category: nanotechnology

One step closer to a light into matter molecular synthesizer: 3.

Molecular machine-track conjugate 1 (Figure 1) was designed to use iterative Wittig reactions to form carbon-carbon double bonds between a macrocycle and building blocks abstracted one at a time and in sequence from a track. The Wittig reaction 24, 25, 26 was chosen as it is robust and structurally tolerant, lending itself to exploitation in a range of contexts, including dynamic DNA-template synthesis.9 Our machine is based on a rotaxane architecture, in which the macrocycle has a reactive aldehyde attachment and the axle has the building-block sequence encoded as phosphonium salts during its synthesis. The 2, 2-diphenylpropane phosphonium units act both to restrict the position of the ring on the track and, upon deprotonation, as reactive ylide functionalities. Each ylide is large enough to block the passage of the macrocycle, trapping the ring within a compartment defined by the bulky stopper at the terminus of original threading and the next ylide along the track. Once a reactive building block can be reached by the macrocycle-appended aldehyde, it can be removed from the track through a Wittig reaction that adds it to the terminus of the growing chain. Each barrier also contains an aldehyde unit, so that once the building block is added to the end of the chain, it is able to react with the next barrier on the track that the macrocycle can access, enabling the alkene-connected oligomer to grow through successive Wittig reactions.

The specific size and constitution of the 2, 2-diphenylpropane motif of the building blocks proved important for successful machine operation. Early track designs in which the ylide and aldehyde were attached to the same aromatic ring or extended conjugated system proved insufficiently reactive (see Section S7 for a brief discussion of initial designs). Embedding the phosphorus atoms within the vector of the track allowed synthetically accessible triaryl phosphines to be the basis of the track design, expediting the synthesis (see Sections S2 and S3). The phenyl substituent at each phosphorus center (e.g., 4a–4D) also proved important: when a tolyl (4-methylphenyl) linking group was investigated, it proved difficult to develop macrocycles that could both thread during the rotaxane-forming reaction and, subsequently, pass over the phosphine oxide in the track formed from the Wittig reaction.

Each phosphorus center is attached to a methylene group bearing a diarylpropane building block derivatized with a different pair of substituents (H, Ph, C6H4CH2CHMe2, or C6H4OMe). These provide different sidechains in the machine product, the same role that different amino acids play in proteins. However, two (identical) sidechains are present per monomer using this artificial molecular machine design compared with one sidechain per amino acid in proteins. This was chosen partly to illustrate how artificial machines and their products are not subject to the same constraints as biomolecular synthesizers but, conveniently, the symmetry of the building blocks also makes their synthesis more straightforward. Each phosphonium moiety is separated from the next by rigid spacers that prevent folding of the track and so ensure that the phosphonium salts can only react with the aldehyde group at the end of the chain attached to the macrocycle rather than others on the track.

Continue reading “A Track-Based Molecular Synthesizer that Builds a Single-Sequence Oligomer through Iterative Carbon-Carbon Bond Formation” | >

How electrons move together as a group inside cylindrical nanoparticles?

Scientists from the University of Exeter seems to find out the answer to this question. They even have made a breakthrough in the field of electromagnetism, with perspectives for metamaterials research.

In collaboration with the University of Strasbourg, scientists hypothesized how electrons move collectively in tiny metal nanoparticles shaped like cylinders.

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Graphene, one of the most important nanomaterials developed so far, continues to surprise the scientific community. This time, thanks to the extraordinary phenomena found by a group of physicists from the University of Arkansas. We are talking specifically about the capacity to use the thermal motion of atoms in graphene as a source of energy!

In this recent work, published in Physical Review E under the title Fluctuation-induced current from freestanding graphene, the team of researchers have successfully developed a circuit capable of capturing graphene’s thermal motion and converting it into an electrical current.

As it is said in this article : “The idea of harvesting energy from graphene is controversial because it refutes physicist Richard Feynman’s well-known assertion that the thermal motion of atoms, known as Brownian motion, cannot do work. Thibado’s team found that at room temperature the thermal motion of graphene does in fact induce an alternating current (AC) in a circuit, an achievement thought to be impossible.”

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Emerging and reemerging infections present an ever-increasing challenge to global health. Here, we report a nanoparticle-enabled smartphone (NES) system for rapid and sensitive virus detection. The virus is captured on a microchip and labeled with specifically designed platinum nanoprobes to induce gas bubble formation in the presence of hydrogen peroxide. The formed bubbles are controlled to make distinct visual patterns, allowing simple and sensitive virus detection using a convolutional neural network (CNN)-enabled smartphone system and without using any optical hardware smartphone attachment. We evaluated the developed CNN-NES for testing viruses such as hepatitis B virus (HBV), HCV, and Zika virus (ZIKV). The CNN-NES was tested with 134 ZIKV-and HBV-spiked and ZIKV-and HCV-infected patient plasma/serum samples. The sensitivity of the system in qualitatively detecting viral-infected samples with a clinically relevant virus concentration threshold of 250 copies/ml was 98.97% with a confidence interval of 94.39 to 99.97%.

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Smartphone systems can also benefit from the recent unprecedented advancements in nanotechnology to develop diagnostic approaches. Catalysis can be considered as one of the popular applications of nanoparticles because of their large surface-to-volume ratio and high surface energy (11–16). So far, numerous diagnostic platforms for cancer and infectious diseases have been developed by substituting enzymes, such as catalase, oxidase, and peroxidase with nanoparticle structures (17–20). Here, we adopted the intrinsic catalytic properties of platinum nanoparticles (PtNPs) for gas bubble formation to detect viruses on-chip using a convolutional neural network (CNN)–enabled smartphone system.

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Super-fast quantum computers and communication devices could revolutionize countless aspects of our lives—but first, researchers need a fast, efficient source of the entangled pairs of photons such systems use to transmit and manipulate information. Researchers at Stevens Institute of Technology have done just that, not only creating a chip-based photon source 100 times more efficient that previously possible, but bringing massive quantum device integration within reach.

“It’s long been suspected that this was possible in theory, but we’re the first to show it in practice,” said Yuping Huang, Gallagher associate professor of physics and director of the Center for Quantum Science and Engineering.

To create , researchers trap light in carefully sculpted nanoscale microcavities; as light circulates in the cavity, its photons resonate and split into entangled pairs. But there’s a catch: at present, such systems are extremely inefficient, requiring a torrent of incoming laser light comprising hundreds of millions of photons before a single entangled photon pair will grudgingly drip out at the other end.

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Circa 2007

Robocops could soon leave the realm of science fiction thanks to a new bullet-proof material proposed by engineers in Australia. According to computer simulations done by the team, bullets would be no match for vests made of the material, and would simply bounce off owing to the high elasticity of the nanotubes. The researchers claim that the material, which has not been made yet, would be a great improvement on existing anti-ballistic clothing that stop bullets from penetrating by spreading the bullet’s force — something that can still cause serious injury (Nanotechnology 18 475701).

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Circa 2006 o.,o.

Researchers at the National Institute of Standards and Technology and the University of Colorado at Boulder have designed a carbon nanotube knife that, in theory, would work like a tight-wire cheese slicer.

In a paper presented this month at the 2006 International Mechanical Engineering Congress and Exposition, the research team announced a prototype nanoknife that could, in the future, become a tabletop tool of biology, allowing scientists to cut and study cells more precisely than they can today.

For years, biologists have wrestled with conventional diamond or glass knives, which cut frozen cell samples at a large angle, forcing the samples to bend and sometimes later crack. Because carbon nanotubes are extremely strong and slender in diameter, they make ideal materials for thinly cutting precise slivers of cells. In particular, scientists might use the nanoknife to make 3D images of cells and tissues for electron tomography, which requires samples less than 300 nanometers thick.

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A joint study led by City University of Hong Kong (CityU) has built an ultralow-power consumption artificial visual system to mimic the human brain, which successfully performed data-intensive cognitive tasks. Their experiment results could provide a promising device system for the next generation of artificial intelligence (AI) applications.

The research team is led by Professor Johnny Chung-yin Ho, Associate Head and Professor of the Department of Materials Science and Engineering (MSE) at CityU. Their findings have been published in the scientific journal Science Advances, titled “Artificial visual system enabled by quasi-two-dimensional electron gases in oxide superlattice .”

As the advances in semiconductor technologies used in digital computing are showing signs of stagnation, neuromorphic (brain-like) computing systems have been regarded as one alternative. Scientists have been trying to develop the next generation of advanced AI computers, which could be as lightweight, energy-efficient and adaptable as the human brain.

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