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Simulating KH-, RT-, or RM-driven mixing using direct numerical simulations (DNS) can be prohibitively expensive because all the spatial and temporal scales have to be resolved, making approaches such as Reynolds-averaged Navier–Stokes (RANS) often the more favorable engineering option for applications like ICF. To this day, no DNS has been performed for ICF even on the largest supercomputers, as the resolution requirements are too stringent.⁸ However, RANS approaches also face their own challenges: RANS is based on the Reynolds decomposition of a flow where mean quantities are intended to represent an average over an ensemble of realizations, which is often replaced by a spatial average due to the scarcity of ensemble datasets. Replacing ensemble averages by space averages may be appropriate for flows that are in homogenous-, isotropic-, and fully developed turbulent states in which spatial, temporal, and ensemble averaging are often equivalent. However, most HED hydrodynamic experiments involve transitional periods in which the flow is neither homogeneous nor isotropic nor fully developed but may contain large-scale unsteady dynamics; thus, the equivalency of averaging can no longer be assumed. Yet, RANS models often still require to be initialized in such states of turbulence, and knowing how and when to initialize them in a transitional state is, therefore, challenging and is still poorly understood.

The goal of this paper is to develop a strategy allowing the initialization of a RANS model to describe an unsteady transitional RM-induced flow. We seek to examine how ensemble-averaged quantities evolve during the transition to turbulence based on some of the first ensemble experiments repeated under HED conditions. Our strategy involves using 3D high-resolution implicit large eddy simulations (ILES) to supplement the experiments and both initialize and validate the RANS model. We use the Besnard–Harlow–Rauenzahn (BHR) model,^9–12 specifically designed to predict variable-density turbulent physics involved in flows like RM. Previous studies have considered different ways of initializing the BHR model.

Year 2017 face_with_colon_three

Tissue Nanotransfection (TNT), that can generate any cell type of interest for treatment within the patient’s own body. This technology may be used to repair injured tissue or restore function of aging tissue, including organs, blood vessels and nerve cells.

“By using our novel nanochip technology, injured or compromised organs can be replaced. We have shown that skin is a fertile land where we can grow the elements of any organ that is declining,” said Dr. Chandan Sen, director of Ohio State’s Center for Regenerative Medicine & Cell Based Therapies, who co-led the study with L. James Lee, professor of chemical and biomolecular engineering with Ohio State’s College of Engineering in collaboration with Ohio State’s Nanoscale Science and Engineering Center.

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Scientists and engineers have been pushing for the past decade to leverage an elusive ferroelectric material called hafnium oxide, or hafnia, to usher in the next generation of computing memory. A team of researchers including the University of Rochester’s Sobhit Singh published a study in the Proceedings of the National Academy of Sciences outlining progress toward making bulk ferroelectric and antiferroelectric hafnia available for use in a variety of applications.

In a specific crystal phase, hafnia exhibits ferroelectric properties —that is, electric polarization that can be changed in one direction or another by applying an external electric field. This feature can be harnessed in data storage technology. When used in computing, ferroelectric memory has the benefit of non-volatility, meaning it retains its values even when powered off, one of several advantages over most types of memory used today.

“Hafnia is a very exciting material because of its practical applications in computer technology, especially for data storage,” says Singh, an assistant professor in the Department of Mechanical Engineering. “Currently, to store data we use magnetic forms of memory that are slow, require a lot of energy to operate, and are not very efficient. Ferroelectric forms of memory are robust, ultra-fast, cheaper to produce, and more energy-efficient.”

A team of researchers from Tohoku University and Okinawa Institute of Science and Technology (OIST) has achieved significant advancement in the field of microfluidics, allowing for precise and efficient manipulation of fluids in three-dimensional microscale environments. This work opens up new possibilities for bioanalytical applications, such as cell separations in the realm of medical diagnostics.

Details of their breakthrough were published in the journal Microsystems & Nanoengineering on January 22, 2024.

Microfluidic devices are designed to handle minuscule fluid volumes, allowing researchers to perform analyses and processes with remarkable precision and efficiency.

http://www.tedxathens.com/1080p HD mode available. About speaker: Andreas Mershin is a Research Scientist at the MIT Center for Bits and Atoms. He leads the L…

A research team led by Lynden Archer, professor and dean of Cornell Engineering, has developed a new lithium battery that can charge in as little as five minutes. This could help address anxiety associated with the charging time of electric vehicles (EVs) and increase their adoption.

In their bid to reduce emissions from transportation, countries worldwide are looking to electrify various modes of transport. Road-based transport such as cars, buses, and trucks have led this transformation, aiming to even ban the sale of fossil fuel-powered cars in the next decade.

With technological advances, the fastest commercial charger can charge up an EV in no less than 30 minutes. While this might be a major improvement over the 8-hour charge cycles of a typical home-based charger, it still needs to be improved for large-scale adoption of EVs.

Quantum gates require controlled interactions between different degrees of freedom. A tunable coupling has now been demonstrated between the phonon modes of a mechanical resonator designed for storing and manipulating quantum information.

How can clean drinking water be produced in the simplest most cost-effective way possible? This is what a recent study published in Nature Sustainability hopes to find out as an international team of researchers led by The University of Texas at Austin (UT Austin) have developed a novel method for producing clean drinking water using only a syringe and a hydrogel filter. This study holds the potential to develop cheaper and simpler methods for producing clean drinking water for individuals around the world.

“The pressing concern of particle-polluted water, particularly in remote and underdeveloped regions where people frequently rely on contaminated water sources for consumption, demands immediate attention and recognition,” said Dr. Guihua Yu, who is a professor of materials science in the Walker Department of Mechanical Engineering at UT Austin and a co-author on the study. “Our system, with its high efficiency in removing diverse types of particles, offers an attractive yet practical solution in improving freshwater availability.”

For the study, the researchers developed their water purification system that incorporates a biodegradable hydrogel filter capable of removing particles as small as approximately 10 nanometers (0.0000003937 inches) from water that is injected into the hydrogel using a syringe. Once injected, the water passes through the hydrogel and into any drinking or storage water apparatus. Along with filtering out particles at 10 nanometers, the researchers also noted the filter efficiency rate is 100 percent, both of which surpass commercially available filters. For context, the researchers note that commercial filter efficiency rates for particles larger than 10 nanometers are approximately 40 percent and 80 percent, respectively. Additionally, the device can be scaled at various sizes and is reusable, resulting in both reduced cost and environmental impact.

Year 2021 Biocomputing is the future for the biological singularity because we could control all inputs and outputs of our bodies even evolve them eventually.

A silicon device that can change skin tissue into blood vessels and nerve cells has advanced from prototype to standardized fabrication, meaning it can now be made in a consistent, reproducible way. As reported in Nature Protocols, this work, developed by researchers at the Indiana University School of Medicine, takes the device one step closer to potential use as a treatment for people with a variety of health concerns.

The technology, called tissue nanotransfection, is a non-invasive nanochip device that can reprogram tissue function by applying a harmless electric spark to deliver specific genes in a fraction of a second. In laboratory studies, the device successfully converted skin tissue into blood vessels to repair a badly injured leg. The technology is currently being used to reprogram tissue for different kinds of therapies, such as repairing brain damage caused by stroke or preventing and reversing nerve damage caused by diabetes.

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