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Category: nanotechnology – Page 142

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A liquid hard drive containing a suspension of nanoparticles could be used to store impressive amounts of data: 1 terabyte per tablespoon.

Researchers from the University of Michigan and New York University have been simulating wet information storage techniques which uses clusters of nanoparticles suspended in liquid. These clusters of particles can store more data than conventional computer bits which have just two storage states: 0 and 1. The clusters of particles work a bit like Rubik’s Cubes to reconfigure in different ways to represent different storage states. A 12-particle memory cluster connected to a central sphere can have almost eight million unique states, which is equivalent to 2.86 bytes of data.

The system works by having nanoparticles attached to a central sphere. When the sphere is small, the outer particles trap each other into place, storing data. If the sphere is a bit larger, the particles can be reconfigured to store different information. The team created a cluster involving four particles on a central sphere — all made of polymers. By heating the liquid up, the spheres expand and the particles can rearrange themselves in predictable ways. Although the four-particle clusters have only two distinguishable configurations (i.e. like a regular bit), the plan is create clusters with many more particles.

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Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices.

Neuromorphic computing aims to realize (AI) by mimicking the mechanisms of neurons and that make up the . Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices.

Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency.

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After a 10-year research study that started by accident and was met with skepticism, a team of Northeastern University mechanical engineers was able to synthesize highly dense, ultra-narrow silicon nanowires that could revolutionize the semiconductor industry. Their research appears in Nature Communications.

Yung Joon Jung, Northeastern professor of mechanical and industrial engineering, says it might have been his favorite research project.

“Everything is new, and it required a lot of perseverance,” says Jung, who specializes in engineering and application of nanostructure systems and previously studied carbon nanotubes.

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Accurate detection and manipulation of endogenous proteins is essential to understand cell biological processes, which motivated laboratories across cell biology to develop highly efficient CRISPR genome editing methods for endogenous epitope tagging (Auer et al., 2014; Nakade et al., 2014; Lackner et al., 2015; Schmid-Burgk et al., 2016; Suzuki et al., 2016; Nishiyama et al., 2017; Artegiani et al., 2020; Danner et al., 2021). Multiplex editing using NHEJ-based CRISPR/Cas9 methods remains limited because of the high degree of cross talk that occurs between two knock-in loci (Gao et al., 2019; Willems et al., 2020). In the current study we present CAKE, a mechanism to diminish cross talk between NHEJ-based CRISPR/Cas9 knock-ins using sequential activation of gRNA expression. We demonstrate that this mechanism strongly reduces cross talk between knock-in loci, and results in dual knock-ins for a wide variety of genes. Finally, we showed that CAKE can be directly applied to reveal new biological insights. CAKE allowed us to perform two-color super-resolution microscopy and acute manipulation of the dynamics of endogenous proteins in neurons, together revealing new insights in the nanoscale organization of synaptic proteins.

The CAKE mechanism presented here creates a mosaic of CreON and CreOFF knock-ins, and the number of double knock-in cells depends on the efficacy of each knock-in vector. Therefore, to obtain a high number of double knock-in cells, the efficacy of both the CreON and CreOFF knock-in vector must be optimized. We identified three parameters that regulate the efficacy for single and double knock-ins in neurons. First, the efficacy of gRNAs varies widely, and even gRNAs that target sequences a few base pairs apart in the same locus can have dramatically different knock-in rates (Willems et al., 2020; Danner et al., 2021; Fang et al., 2021; Zhong et al., 2021). Thus, the efficacy of each individual gRNA must be optimized to increase the chance of successful multiplex labeling in neurons. gRNA performance is dependent on many factors, including the rate of DNA cleavage and repair (Rose et al., 2017; Liu et al., 2020; Park et al.

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Carnegie Mellon University researchers have pioneered the CMU Array—a new type of microelectrode array for brain computer interface platforms. It holds the potential to transform how doctors are able to treat neurological disorders.

The ultra-high-density microelectrode (MEA), which is 3D-printed at the nanoscale, is fully customizable. This means that one day, patients suffering from epilepsy or limb function loss due to stroke could have personalized medical treatment optimized for their individual needs.

The collaboration combines the expertise of Rahul Panat, associate professor of mechanical engineering, and Eric Yttri, assistant professor of biological sciences. The team applied the newest microfabrication technique, Aerosol Jet 3D printing, to produce arrays that solved the major design barriers of other brain computer interface (BCI) arrays. The findings were published in Science Advances.

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Additive manufacturing techniques used to produce metal alloys have gained popularity due to their ability to be fabricated in complex shapes for use in various engineering applications. Yet the majority of studies conducted have centered around developing single-phase materials.

Dr. Kelvin Xie’s team in the Department of Materials Science and Engineering at Texas A&M University employed advanced characterization techniques to reveal the microstructure of the 3D-printed dual-phase multi-principal elements, also known as (HEAs), that display ultra-strong and ductile properties. This work is a collaboration with Dr. Wen Chen from the University of Massachusetts at Amherst and Dr. Ting Zhu from the Georgia Institute of Technology.

This study was recently published in Nature.

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We demonstrate reversible cycle stability for up to 200 000 cycles with 94–96% average Coulombic efficiency for symmetrical δ-MnO2 nanowire capacitors operating across a 1.2 V voltage window in a poly(methyl methacrylate) (PMMA) gel electrolyte. The nanowires investigated here have a Au@δ-MnO2 core@shell architecture in which a central gold nanowire current collector is surrounded by an electrodeposited layer of δ-MnO2 that has a thickness of between 143 and 300 nm. Identical capacitors operating in the absence of PMMA (propylene carbonate (PC), 1.0 M LiClO4) show dramatically reduced cycle stabilities ranging from 2000 to 8,000 cycles. In the liquid PC electrolyte, the δ-MnO2 shell fractures, delaminates, and separates from the gold nanowire current collector. These deleterious processes are not observed in the PMMA electrolyte.

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The last decade has brought a lot of attention to the use of microscopic robots (microrobots or nanorobots) for biomedical applications. Now, nanoengineers have developed microrobots that can swim around in the lungs and deliver medication to be used to treat bacterial pneumonia. A new study shows that the microrobots safely eliminated pneumonia-causing bacteria in the lungs of mice and resulted in 100% survival. By contrast, untreated mice all died within three days after infection.

The results are published Nature Materials in the paper, “Nanoparticle-modified microrobots for in vivo antibiotic delivery to treat acute bacterial pneumonia.”

The microrobots are made using click chemistry to attach antibiotic-loaded neutrophil membrane-coated polymeric nanoparticles to natural microalgae. The hybrid microrobots could be used for the active delivery of antibiotics in the lungs in vivo.

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Scientists have been able to direct a swarm of microscopic swimming robots to clear out pneumonia microbes in the lungs of mice, raising hopes that a similar treatment could be developed to treat deadly bacterial pneumonia in humans.

The microbots are made from algae cells and covered with a layer of antibiotic nanoparticles. The algae provide movement through the lungs, which is key to the treatment being targeted and effective.

In experiments, the infections in the mice treated with the algae bots all cleared up, whereas the mice that weren’t treated all died within three days.

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