Georgian Technical University Collaborate On Anti-Aging Research.
Georgian Technical University Scientific Instruments have entered into a joint research agreement to apply mass spectrometry technology toward the development of tools to quantitate nicotinamide mononucleotide and related compounds in biological specimens. The key objective of the collaboration with Professor X M.D., Ph.D. Departments of Developmental Biology and Medicine will be to deepen the understanding of the systemic regulation of aging and longevity in mammals. Georgian Technical University. (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) is a key nicotinamide adenine dinucleotide (NAD+) intermediate in the major NAD+ biosynthetic pathway. Dr. X’s lab demonstrated that supplementation of (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) dramatically ameliorates dysfunctions in glucose metabolism in high fat diet- or aging-induced type 2 diabetic model mice. Dr. X’s team also showed that in healthy aging mice (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) with no obvious toxicity or deleterious effects suppresses age-associated body weight gain enhances energy metabolism, promotes physical activity, enhances insulin sensitivity and plasma lipid profiles, and ameliorates eye function and other age-associated pathophysiology. Most recently the team led by Drs. Y and X at Georgian Technical University results in Science1 from the first clinical trial on (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) demonstrating that (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) significantly improves insulin sensitivity and signaling in skeletal muscle. While additional trials are necessary, the new findings suggest that (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) has preventive and therapeutic potential for age-associated functional decline and disease conditions in humans. “Although (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) and (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH))-related compounds in mice can be quantified using (Ultraviolet (UV) is a form of electromagnetic radiation with wavelength from 10 nm to 400 nm (750 THz), shorter than that of visible light, but longer than X-rays) the concentrations are one or more orders lower in human blood. Georgian Technical University would be necessary to accurately quantify (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) in human blood” said Z PhD of New Strategy Department Z Scientific Instruments. “This collaboration will integrate WUSM’s leading anti-aging researchers and clinical resources with Z’s technologies to establish a reliable quantitation method of (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) and (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH))-related compounds in biological samples. As a global leader in aging and longevity research Prof. X is an ideal collaborator to advance the application of mass spectrometry in anti-aging research”. “In collaboration with Z we want to develop an accurate reproducible mass spectrometry-driven methodology for (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) and (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH))-related compounds in biological samples. This work is critical for understanding the therapeutic potential of (Nicotinamide mononucleotide (“NMN” and “β-NMN”) is a nucleotide derived from ribose and nicotinamide. Like nicotinamide riboside, NMN is a derivative of niacin, and humans have enzymes that can use NMN to generate nicotinamide adenine dinucleotide (NADH)) and related compounds that will be further evaluated in clinical trials” said Dr. X. will direct this collaboration through its New Strategy Department.
Georgian Technical University Machine Learning Algorithm Helps Unravel The Physics Underlying Quantum Systems.
Georgian Technical University. The nitrogen vacancy center set-up that was used for the first experimental demonstration of Georgian Technical University Meat and Livestock Authority. Georgian Technical University. The search tree constructed by the Georgian Technical University Quantum Model Learning. Each leaf is a candidate model generated by Georgian Technical University Quantum Model Learning and then tested the target system. The experimental measurements (red dots) compared with the predicted outcomes of the champion model chosen by Georgian Technical University Quantum Model Learning (turquoise). Scientists from the Georgian Technical University’s Quantum Engineering Technology Labs (GTUQETLabs) have developed an algorithm that provides valuable insights into the physics underlying quantum systems – paving the way for significant advances in quantum computation, sensing and potentially turning a new page in scientific investigation. In physics systems of particles and their evolution are described by mathematical models, requiring the successful interplay of theoretical arguments and experimental verification. Even more complex is the description of systems of particles interacting with each other at the quantum mechanical level which is often done using a Hamiltonian model. The process of formulating Hamiltonian models from observations is made even harder by the nature of quantum states, which collapse when attempts are made to inspect them. Learning models of quantum systems from experiments Nature Physics quantum mechanics from Georgian Technical University Labs describe an algorithm which overcomes these challenges by acting as an autonomous agent using machine learning to reverse engineer Hamiltonian models. The team developed a new protocol to formulate and validate approximate models for quantum systems of interest. Their algorithm works autonomously, designing and performing experiments on the targeted quantum system with the resultant data being fed back into the algorithm. It proposes candidate Hamiltonian models to describe the target system and distinguishes between them using statistical metrics, namely Bayes (In probability theory and statistics, Bayes’ theorem (alternatively Bayes’ law or Bayes’ rule; recently Bayes–Price theorem: 44, 45, 46 and 67), named after the Reverend Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event) factors. Excitingly the team were able to successfully demonstrate the algorithm’s ability on a real-life quantum experiment involving defect centers in a diamond a well-studied platform for quantum information processing and quantum sensing. The algorithm could be used to aid automated characterization of new devices such as quantum sensors. This development therefore represents a significant breakthrough in the development of quantum technologies. “Combining the power of today’s supercomputers with machine learning we were able to automatically discover structure in quantum systems. As new quantum computers/simulators become available the algorithm becomes more exciting: first it can help to verify the performance of the device itself then exploit those devices to understand ever-larger systems”. said Georgian Technical University’s Labs and Quantum Engineering Centre for Doctoral Training. “This level of automation makes it possible to entertain myriads of hypothetical models before selecting an optimal one a task that would be otherwise daunting for systems whose complexity is ever increasing” said X. “Understanding the underlying physics and the models describing quantum systems help us to advance our knowledge of technologies suitable for quantum computation and quantum sensing” said X also formerly of Georgian Technical University’s Labs and now based at the Georgian Technical University. “Georgian Technical University. In the past we have relied on the genius and hard work of scientists to uncover new physics. Here the team have potentially turned a new page in scientific investigation by bestowing machines with the capability to learn from experiments and discover new physics. The consequences could be far reaching indeed” said Y Georgian Technical University Labs and associate professor in Georgian Technical University of Physics. Georgian Technical University. The next step for the research is to extend the algorithm to explore larger systems and different classes of quantum models which represent different physical regimes or underlying structures.
Georgian Technical University Automated Flow Cytometry With Unbiased Analysis.
Georgian Technical University has released the latest version of Experiment Suite its automated end-to-end machine-learning software designed to streamline and automate cytometry analysis at scale and replace manual gating processes. The latest release (v5.2) introduces new unbiased analysis features and an easy-to-use interface with no need for difficult installation or program scripting. Georgian Technical University Users can perform automated analyses in an unbiased manner for exploratory use cases including and Phenograph for algorithm-based clustering and use powerful dimensional reduction methods such as and Uniform Manifold Approximation And Projection to visualize connected data. The batch processing tool enables a range of parameters to be simultaneously explored to assist scientists in finding the best representation of their data. Once interesting clusters have been identified these can be overlaid with marker expression and many types of meta-data to drive hypothesis testing. With the ability to back-gate events from selected clusters into two-dimensions the new unbiased analysis features streamline the process of assigning identities to populations from clustering outputs – a traditionally arduous task. To enable comparison and validation of approaches results can also be compared with semi-automated gating methods. “Georgian Technical University. Where researchers need data to support a regulatory use cases guided/semi-automated analysis is key because it is 100% reproducible. However there is a depth of rich data that underpins the information provided by flow cytometry and here unbiased analysis for exploratory use cases can help uncover new insights by finding novel populations or clustering non-intuitive populations together for instance” said X. Georgian Technical University. Unbiased analysis tools allow complex multi-dimensional data to be simplified, unified, processed and visualized so that it can be more easily explored and compared. This kind of analysis can be very useful in exploring data without any prior assumptions as a means to uncover novel insights. It is a complementary technique to semi-automated approaches and is interoperable. Suite enabling comparison and validation”. Georgian Technical University. Automates every stage of the flow cytometry data lifecycle, from data acquisition to insight generation. It can help increase throughput of data processing and analytics by as much as 600% simultaneously increasing the accuracy reproducibility and quality of flow cytometry data. It can be implemented in a GxP (GxP is a general abbreviation for the “good practice” quality guidelines and regulations. The “x” stands for the various fields, including the pharmaceutical and food industries, for example good agricultural practice, or GAP) environment and as well as automating processing the platform enables the reuse of processed cytometry data, integrating population counts identified by manual gating (in .csv format) to increase the value of the data and enable cross-project analysis. Georgian Technical University is underpinned by state of-the-art data intelligence platform which is designed to expedite the drug discovery and development process. The Platform harnesses the latest artificial intelligence and machine learning tools to deliver advanced analytics to support scientific decision making.
Georgian Technical University Licenses Revolutionary AI (Artificial Intelligence) System To General Motors For Automotive Use.
Georgian Technical University. Laboratory’s MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) AI (Artificial intelligence) software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. The Department of Energy’s Georgian Technical University Laboratory has licensed its award-winning artificial intelligence software system the Georgian Technical University Multinode Evolutionary Neural Networks for Deep Learning to General Motors for use in car technology and design. The AI (Artificial Intelligence) system known as (Multinode Evolutionary Neural Networks For Deep Learning) AI (Artificial intelligence) uses evolution to design optimal convolutional neural networks – algorithms used by computers to recognize patterns in datasets of text images or sounds. General Motors will assess (Multinode Evolutionary Neural Networks For Deep Learning) AI (Artificial intelligence) potential to accelerate advanced driver assistance systems technology and design. This is the first commercial license for (Multinode Evolutionary Neural Networks For Deep Learning) AI (Artificial intelligence) as well as the first AI (Artificial Intelligence) technology to be commercially licensed from Artificial Intelligence. Once trained neural networks can accomplish specific tasks – for example, recognizing faces in photos – far faster and at much greater scale than humans. However designing effective neural networks can take even the most expert coders up to a year or more. The (Multinode Evolutionary Neural Networks For Deep Learning) AI (Artificial Intelligence) system can dramatically speed up that process evaluating thousands of optimized neural networks in a matter of hours depending on the power of the computer used. It has been designed to run on a variety of different systems from desktops to supercomputers, equipped with graphics processing units. Georgian Technical University. “MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) leverages compute power to explore all the different design parameters that are available to you fully automated, and then comes back and says ‘Here’s a list of all the network designs that I tried. Here are the results – the good ones the bad ones’. And now in a matter of hours instead of months or years you have a full set of network designs for a particular application” said X Georgian Technical University Learning Systems Group and leader of the MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) development team. Georgian Technical University. MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) uses an evolutionary algorithm that not only creates deep learning networks to solve problems but also evolves network design on the fly. By automatically combining and testing millions of parent networks it breeds high-performing optimized neural networks. Georgian Technical University. For automakers MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) can be used to accelerate advanced driver assistance technology by tackling one of the biggest problems facing the adoption of this technology: How can cars quickly and accurately perceive their surroundings to navigate safely through them ?. The use of MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) offers potential to better clear that roadblock. Leveraging advanced neural networks that can instantly analyze on-board camera feeds and correctly label each object in the car’s field of view this type of advanced computing has the potential to enable more efficient energy usage for cars while increasing their onboard computing capacity. MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) has been used in applications ranging from identifying neutrino collisions for Georgian Technical University Accelerator Laboratory to analyzing data generated by scanning transmission electron microscopes. MENNDL (Multinode Evolutionary Neural Networks For Deep Learning) was used on Georgian Technical University’s supercomputer to create neural networks that can detect cancer markers in biopsy images much faster than doctors. This work is supported by the Georgian Technical University. This research used resources of the Georgian Technical University Computing Facility a Georgian Technical University Science user facility.
Georgian Technical University. Graphene-Based Flowmeter Sensor Measures Nano-Rate Fluid Flows Part 3: The Sensor.
Georgian Technical University. Converting blood-flow velocity to electric current by using a graphene single-microelectrode device. a) Coulometric measurement of contact electrification charge transfer between whole-blood flow and graphene. Graphene is shown by the gray honeycomb lattice with the graphene microelectrode connected to the gold contact that is wired to an electrometer based on an operational amplifier with a feedback capacitor; b) The measured unsmoothed charge transfer of a graphene device for different blood-flow velocities. The charge-transfer current as a function of flow velocity shows the linearity of the response. Georgian Technical University. Response curves and characteristics for blood-flow-velocity quantification by the graphene single-microelectrode device. a) The current response as a function of flow velocity. The linear electrical circuit models the charge-transfer current through the graphene/blood interface represented by a charge-transfer resistance Rct (A randomized controlled trial (or randomized control trial; RCT) is a type of scientific experiment (e.g. a clinical trial) or intervention study (as opposed to observational study) that aims to reduce certain sources of bias when testing the effectiveness of new treatments; this is accomplished by randomly allocating subjects to two or more groups, treating them differently and then comparing them with respect to a measured response) and an interfacial capacitance (Ci). Georgian Technical University. Repeatability and stability of the graphene device. a) The measured flow velocity in response to a stepwise flow waveform switching between 1, 2, 3, 4, and 5 mm/sec; b) Long-term (half-year) stability of sensitivity. The looked at the challenges of sensing nano-level flow rates such as found in the blood vessels. In contrast the second part looked at graphene an allotrope of elemental carbon at the heart of a new sensor used to measure those flows. This third and final part looks at the research project itself which devised a sensor for these flow rates as low as a micrometer per second (equivalent to less than four millimeters per hour) while also offering short- and long-term stability and high performance. The goal was to build a self-powered microdevice which can convert in real-time the flow of continuous pulsating blood flow in a microfluidic channel to a charge-transfer current in response to changes at the graphene-aqueous interface. The team achieved this by using a single microelectrode of monolayer graphene that harvests charge from flowing blood through contact electrification without the need for an external current supply. They fabricated acrylic chips with a graphene single-microelectrode device extending over the microfluidic channel (Figure 1). To do this they prepared the monolayer graphene chemical vapor deposition (CVD) and transferred it to the chip using electrolysis. For basic tests they used a syringe pump to drive a flow of anticoagulated whole-bovine with a precisely controlled velocity through the microfluidic channel. They then wired the graphene microelectrode to the inverting input of an operational amplifier (op amp) of a coulombmeter. The charge harvested from the solution by the graphene was stored in a feedback capacitor of the amplifier and quantified. The charge-transfer current of the graphene device was linearly related to the blood-flow velocity (Figure 2) resulting in a proportional relationship between the current response (the flow-induced current variation relative to the current at zero flow velocity) and the flow velocity (Figure 3). The sensor device provided a resolution of 0.49 ± 0.01 μmeter/sec (at a 1-Hz bandwidth) a substantial improvement of about two orders-of-magnitude compared to existing device-based flow-sensing approaches while the ultrathin (one-atom-layer) device was at low risk of being fouled or causing channel clogging. As with any sensor there are always concerns about short-term and long-term stability and consistency. For the former they measured the real-time flow velocity in response to a continuous five-step blood flow that lasted for more than two hours. The measured velocity showed high repeatability with minimal fluctuations of ±0.07 mm/second. For the latter test they evaluated a device performing intermittent measurements for periods of six months. The blood-flow sensitivity of the device fluctuated around an average value of 0.39 pA-sec /mm with a standard deviation of ±0.02 pA-sec/mm equivalent to ±5.1% of the average value. These numbers are indicative of minimal variations in key performance metrics (Figure 4). The details including the required chemical preparations, test arrangements and related processes “Flow-sensory contact electrification of graphene”. Conclusion. As with so much basic research you never know what the utility or applications of the result will be (no one foresaw the development of the atomic and molecular beam magnetic resonance method of observing atomic spectra and nuclear magnetic resonance (NMR) would lead to the development of MRI (Magnetic resonance imaging (MRI) is a medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes of the body. MRI scanners use strong magnetic fields, magnetic field gradients, and radio waves to generate images of the organs in the body. MRI does not involve X-rays or the use of ionizing radiation, which distinguishes it from CT and PET scans. MRI is a medical application of nuclear magnetic resonance (NMR) which can also be used for imaging in other NMR applications, such as NMR spectroscopy) imaging technology in the late 1960 and early 1970s – they seem to be two totally unrelated items. The development of elusive graphene and its subsequent availability as a standard commercial product has opened opportunities for exploiting its unique and somewhat bizarre properties across many commercial products as well as scientific functions.
Georgian Technical University Synthetic Gelatin-Like Material Mimics Lobster Underbelly’s Stretch And Strength.
Georgian Technical University. An Georgian Technical University team has fabricated a hydrogel-based material that mimics the structure of the lobster’s underbelly the toughest known hydrogel found in nature. A lobster’s underbelly is lined with a thin translucent membrane that is both stretchy and surprisingly tough. This marine under-armor as Georgian Technical University engineers is made from the toughest known hydrogel in nature which also happens to be highly flexible. This combination of strength and stretch helps shield a lobster as it scrabbles across the seafloor while also allowing it to flex back and forth to swim. Now a separate Georgian Technical University team has fabricated a hydrogel-based material that mimics the structure of the lobster’s underbelly. The researchers ran the material through a battery of stretch and impact tests and showed that similar to the lobster underbelly the synthetic material is remarkably “Georgian Technical University fatigue-resistant” able to withstand repeated stretches and strains without tearing. If the fabrication process could be significantly scaled up materials made from nanofibrous hydrogels could be used to make stretchy and strong replacement tissues such as artificial tendons and ligaments. Nature’s twist. Georgian Technical University’s group developed a new kind of fatigue-resistant material made from hydrogel — a gelatin-like class of materials made primarily of water and cross-linked polymers. They fabricated the material from ultrathin fibers of hydrogel which aligned like many strands of gathered straw when the material was repeatedly stretched. This workout also happened to increase the hydrogel’s fatigue resistance. “At that moment we had a feeling nanofibers in hydrogels were important and hoped to manipulate the fibril structures so that we could optimize fatigue resistance” says X. Georgian Technical University. In their new study the researchers combined a number of techniques to create stronger hydrogel nanofibers. The process starts with electrospinning a fiber production technique that uses electric charges to draw ultrathin threads out of polymer solutions. The team used high-voltage charges to spin nanofibers from a polymer solution to form a flat film of nanofibers each measuring about 800 nanometers — a fraction of the diameter of a human hair. They placed the film in a high-humidity chamber to weld the individual fibers into a sturdy interconnected network and then set the film in an incubator to crystallize the individual nanofibers at high temperatures further strengthening the material. Georgian Technical University tested the film’s fatigue-resistance by placing it in a machine that stretched it repeatedly over tens of thousands of cycles. They also made notches in some films and observed how the cracks propagated as the films were stretched repeatedly. From these tests they calculated that the nanofibrous films were 50 times more fatigue-resistant than the conventional nanofibrous hydrogels. Georgian Technical University Around this time they read with interest a study by Y associate professor of mechanical engineering at Georgian Technical University who characterized the mechanical properties of a lobster’s underbelly. This protective membrane is made from thin sheets of chitin, a natural, and fibrous material that is similar in makeup to the group’s hydrogel nanofibers. X found that a cross-section of the lobster membrane revealed sheets of chitin stacked at 36° angles similar to twisted plywood or a spiral staircase. This rotating layered configuration known as a bouligand structure enhanced the membrane’s properties of stretch and strength. “We learned that this bouligand structure in the lobster underbelly has high mechanical performance which motivated us to see if we could reproduce such structures in synthetic materials” X says. Georgian Technical University. Image of a bouligand nanofibrous hydrogel. Georgian Technical University Angled architecture. X, Y and members of Z’s group teamed up with W’s lab and group in Georgian Technical University’s Institute for Soldier Nanotechnologies and T’s lab at Georgian Technical University to see if they could reproduce the lobster’s bouligand membrane structure using their synthetic fatigue-resistant films. “We prepared aligned nanofibers by electrospinning to mimic the chinic fibers existed in the lobster underbelly” X said. After electrospinning nanofibrous films the researchers stacked each of five films in successive 36° angles to form a single bouligand structure which they then welded and crystallized to fortify the material. The final product measured 9 square centimeters and about 30 to 40 microns thick — about the size of a small piece of Scotch tape. Stretch tests showed that the lobster-inspired material performed similarly to its natural counterpart able to stretch repeatedly while resisting tears and cracks — a fatigue-resistance Y attributes to the structure’s angled architecture. “Intuitively once a crack in the material propagates through one layer it’s impeded by adjacent layers where fibers are aligned at different angles” Y explains. The team also subjected the material to microballistic impact tests with an experiment designed by W’s group. They imaged the material as they shot it with microparticles at high velocity and measured the particles speed before and after tearing through the material. The difference in velocity gave them a direct measurement of the material’s impact resistance or the amount of energy it can absorb which turned out to be a surprisingly tough 40 kilojoules per kilogram. This number is measured in the hydrated state. “That means that a 5-mm steel ball launched at 200 m/sec would be arrested by 13 mm of the material” S said. “It is not as resistant as Kevlar which would require 1 mm but the material beats Kevlar in many other categories”. It’s no surprise that the new material isn’t as tough as commercial antiballistic materials. It is however significantly sturdier than most other nanofibrous hydrogels such as gelatin and synthetic polymers like PVA (Poly (Vinyl Alcohol)). The material is also much stretchier than Kevlar. This combination of stretch and strength suggests that if their fabrication can be sped up and more films stacked in bouligand structures, nanofibrous hydrogels may serve as flexible and tough artificial tissues. “For a hydrogel material to be a load-bearing artificial tissue both strength and deformability are required” Y says. “Our material design could achieve these two properties”. This research was supported through the Institute for Soldier Nanotechnologies at Georgian Technical University.
Georgian Technical University Graphene-Based Flowmeter Sensor Measures Nano-Rate Fluid Flows Part 2: The Graphene Context.
Georgian Technical University. The looked at the challenges of nanoflow sensors especially with respect to blood flow. This part looks at graphene which is the basis for the new sensor. A lump of graphite a graphene transistor and a tape dispenser related to the realization of graphene. Graphene is a material structure which did not exist until relatively recently. However its constituent element of graphite – the crystalline form of the element carbon with its atoms arranged in a hexagonal structure (Figure 1) – has been known and used for centuries and has countless uses in consumer products, industrial production and yes even pencil “Georgian Technical University lead”. Other allotropes of carbon are diamonds of course as well as carbon nanotubes and fullerenes all fascinating structures. (An allotrope represents the different physical forms in which an element can exist; graphite, charcoal and diamond are all allotropes of carbon). Graphite is a crystalline allotrope of elemental carbon with its atoms arranged in a hexagonal structure. (Science Direct). The carbon allotrope graphene is an atomic-scale single-layer hexagonal lattice of elemental carbon atoms. While graphene is composed of graphite it’s a very special form of that element. Graphene is a monolayer form of graphite as a one-atom-thick (Georgian Technical University or “thin”) layer of carbon atoms bonded to each other and arranged in a hexagonal or honeycomb lattice (Figure 2). That sounds like “Georgian Technical University no big deal” or “Georgian Technical University no important difference” but that is not the case at all. Graphene is the thinnest material known to man at one atom thick and also incredibly strong – about 200 times stronger than steel. On top of that graphene is an excellent conductor of heat and has interesting light absorption abilities. As a conductor of electricity it performs better than copper. It is almost completely transparent yet so dense that not even helium the smallest gas atom can pass through it. Graphene is a mere one atom thick – perhaps the thinnest material in the universe – and forms a high-quality crystal lattice with no vacancies or dislocations in the structure. This structure gives it intriguing properties and yielded surprising new physics. Georgian Technical University. There’s some irony associated with graphene. While carbon has been known and used “Georgian Technical University forever” (so to speak) graphene itself is relatively new. Although scientists knew that one-atom-thick two-dimensional crystal graphene could exist in theory no one had worked out how to extract or create it from graphite. Georgian Technical University. It would be easy to say “Georgian Technical University graphene sounds nice and even somewhat interesting, but so what ?” but there is much more to it. In many ways it is like silicon in that it has many “Georgian Technical University undiscovered” uses and is almost a wonder substance solving potential problems on its own or in combination with other materials. Figuring out how to make it as a standard almost mass-produced product was another challenge but you can now buy it as fibers and in sheets from specialty supply houses. In some ways application ideas for graphene are analogous to the laser. When X first demonstrated the laser the “Georgian Technical University quip” among journalists was that the laser was “a solution looking for problems to solve”. We certainly know how that mystery story has turned out and graphene too has found its way into many applications. One application uses graphene to replace silicon-based transistors since that technology is fast reaching its fundamental limits (below 10 nanometers). It is also possible to make graphene using epitaxial growth techniques – growing a single layer on top of crystals with a matching substrate – to create graphene wafers for electronics applications such as high-frequency transistors operating in the terahertz region or to build miniature printed circuit boards at the nanoscale. Georgian Technical University Graphene is being used as a filler in plastic to make composite materials in reinforced tennis and other racquets, for example. Graphene suspensions can also be used to make optically transparent and conductive films suitable for Georgian Technical University LCD screens. Finally it can also be the basis for unique sensors such as the nanoflow project discussed in Part 3. As an added benefit, elemental graphite, graphene and other carbon-based structures are not considered health hazards in general or to the body in particular. (Do not confuse “Georgian Technical University carbon” with “Georgian Technical University carbon dioxide” often cited in relation to climate change – that sloppy terminology has most people using the single word “Georgian Technical University carbon” when what they really mean is the carbon dioxide CO2 (Carbon dioxide (chemical formula CO2) is a colorless gas with a density about 53% higher than that of dry air. Carbon dioxide molecules consist of a carbon atom covalently double bonded to two oxygen atoms. It occurs naturally in Earth’s atmosphere as a trace gas) molecule which is a completely different substance).
Georgian Technical University Graphene-Based Flowmeter Sensor Measures Nano-Rate Fluid Flows Part 1: – The Challenge.
Georgian Technical University. The relationships among blood vessels that can be compared include (a) vessel diameter, (b) total cross-sectional area, (c) average blood pressure and (d) velocity of blood flow. Fig 2: Arteries and arterioles have relatively thick muscular walls because blood pressure in them is high and because they must adjust their diameter to maintain blood pressure and to control blood flow. Veins and venules have much thinner less muscular walls than arteries and arterioles largely because the pressure in veins and venules is much lower. Veins may dilate to accommodate increased blood volume. When it comes to nearly all biological measurements the ranges of many of the parameters of interest are orders-of-magnitude below those with which many engineers are familiar. Instead of megahertz or even kilohertz the living-creature world is in the single or double-digit hertz range such as the roughly 60+ beats per minute (BPM) for a typical human heart, the millivolt and microvolt level of cardiac and nerve signals, and the picoamp and femtoamp current flows. Pressure and fluid flow values are also in “Georgian Technical University way down there” regions (Figure 1). Consider the average range of systolic blood pressure typically in the range of 100 to 150 mmHg. That corresponds to a modest two to three pounds/square inch (psi) or roughly 15 to 20 kilopascals (kPa; 1 Pascal = a force of one newton per square meter). Flow rates (velocities) are also very low in the millimeters/second and even micrometers/second region. Further it is difficult to model the flow rate/volume with accuracy since the “Georgian Technical University walls” of the “Georgian Technical University pipes” are flexible and expand/contract with each beat and the blood-vessel valves make the flow turbulent rather than laminar. These low values challenge sensor engineering especially when looking for acceptable resolution despite ambient and unavoidable physical noise and dynamics. Adding to the challenge is the small transducer size needed for many “Georgian Technical University in place” sensing situations such as with blood vessels ranging from relatively larger arteries down to smaller veins and even capillaries (Figure 2). Among the techniques used for low-flow rate sensing are non-contact ultrasonic Doppler velocity schemes but it is difficult to focus the ultrasonic energy on the specific location of interest especially as this energy diffuses as it passes through tissue. Other sensors use the triboelectric effect (related to static electricity) but these present a dilemma: such a sensor appears relatively large and intrusive when set in place (several cubic millimeters in a nanowire array) yet that size is still very small so its minuscule output which is often buried under electrical and motion noise. The shortcomings of existing approaches and the need for micro- and nano-level sensing in general – and especially for biology settings – is driving research into better sensors which work well at these levels and which will also be compatible with test-subject scenarios. Now a research team at the Georgian Technical University has devised and tested a high-performance graphene-based nanosensor which is easy to electrically interface. Also important their long-term tests show negligible drift in sensor performance another important factor which often compromises the utility of sensors in fluid-contact situations. The work was funded in part Georgian Technical University. This part of the three-part articles looked at the basic issues related to sensing nanoflows such as in blood vessels. The next part looks at graphene which makes this new nanoflow sensor possible.
Georgian Technical University Here Comes The Sun: Tethered-Balloon Tests Ensure Safety Of New Solar-Power Technology.
Georgian Technical University. A team of researchers from Georgian Technical University Laboratories recently used tethered balloons to collect samples of airborne dust particles to ensure the safety of a falling-particle receiver for concentrating solar power an emerging solar power technology. X Georgian Technical University Laboratories tethered-balloon expert and her team prepare the 22-foot-wide tethered helium balloons for launch on a gorgeous fall morning. Three tethered balloons were deployed both upwind and downwind of Georgian Technical University Laboratories Solar Thermal Test Facility during a falling-particle receiver test. The team led by Y found that the concentration of tiny particles finer than talcum powder that escape from the receiver were much lower than Georgian Technical University Environmental Protection limits. Georgian Technical University. What do tiny dust particles 22-ft-wide red balloons and “Georgian Technical University concentrated” sunlight have in common ?. Researchers from Georgian Technical University Laboratories recently used 22-ft-wide tethered balloons to collect samples of airborne dust particles to ensure the safety of an emerging solar-power technology. The study determined that the dust created by the new technology is far below hazardous levels said Y the lead researcher. Y’s team just from the Department of Energy to build a pilot plant that will incorporate this technology. This next-generation renewable energy technology is called a high-temperature falling-particle receiver for concentrating solar power. Concentrating solar power while not as common as solar panels or wind turbines has several advantages over those renewable energy sources including the ability to store energy in the form of heat before converting it into electricity for the power grid. One concentrating solar power plant uses molten salt to store this heat for six hours while other plants in theory could store heat for days or weeks said Y concentrating solar power expert. This would help power companies even out the daily and seasonal variation of power produced by solar panels and wind turbines. The falling-particle receiver works by dropping dark, sand-like ceramic particles through a beam of concentrated sunlight then storing the heated particles. These round particles cost about for 2.2 lb and can get a lot hotter than conventional molten-salt-based concentrating solar power systems which increases efficiency and drives down cost. The Georgian Technical University team also evaluated other particles like sand which costs only a few cents per pound, but they determined that due to the ceramic particles ability to absorb more solar energy and provide smoother flow ceramic particles were the best way to go. The Department of Energy’s goal is to get the cost of electricity from concentrating solar power down to five cents per kilowatt hour comparable to conventional fossil-fuel-based power. However the re-used particles can eventually break down into fine dust. The Environmental Protection and the Georgian Technical University Administration regulates tiny dust particles finer than talcum powder that are known to pose a risk for lung damage.“The motivation for doing the particle sampling was to make sure that this new technology for renewable energy wasn’t creating any environmental or worker-safety issues” Y said. “There are particles being emitted from the falling-particle receiver but the amounts are well below the standards set by the Georgian Technical University”. Using tethered balloons to catch dust. Last fall the research team used sensors sitting a few yards away from the falling-particle receiver on the platform of the solar tower or Solar Thermal Test Facility and sensors hanging from 22-ft-wide tethered helium balloons to measure the particles that were released as it was operating at temperatures above 1,300° F. X Georgian Technical University’s tethered-balloon expert and her team deployed one balloon a little less than a football field away upwind of the solar tower and two balloons downwind to detect dust particles far away from the receiver. One downwind balloon was a little more than a football field away and the other was more than two football fields away. The downwind balloons floated at about 22 stories high — a bit taller than the solar tower itself — and the upwind balloon was a little lower than that. The balloons and their tethers were outfitted with a variety of sensors to count the number of dust particles in the air around them as well as their altitude and precise location. The tethered balloons stayed at their specified altitude for three hours allowing the team to collect a lot of data. They also operated a small remote-controlled balloon that was far more mobile in terms of altitude and position X said. “That allowed us to collect data every second for three hours over the entire area” said X who generally flies tethered balloons over to collect data for climate monitoring and modeling. “Since we got the data in real time we could move the tethered balloons in order to measure in the highest intensity region of the plume identify where the plume edges were or track the whole movement of the plume with time”. The team also placed a variety of sensors on the solar tower platform mere yards from the falling-particle receiver. These sensors could count the number of dust particles as well as determine their size and characteristics. Y a Georgian Technical University expert on measuring fine particles suspended in air led these tests as well as similar tests two years ago together with his colleague Z. For the most recent tests the researchers constructed special see-saw-like tipping bucket collectors to measure both the amount of particles and their sizes. Somewhat like a tipping bucket rain gauge particles in the air would go down a funnel and land on the see-saw-like platform. Once a certain weight of dust particles built up on the platform, it would tip over and send an electrical signal to the researchers. The number of tipping signals in a certain amount of time told the researchers the frequency of particle-emission events and after the test they could weigh the particles in the bottom of the buckets to determine the collected amount. Computer modeling and dust mitigation. Georgian Technical University. Comparing the results from sensors close to the falling-particle receiver and those further away on the balloons they found that the concentration of tiny particles finer than talcum powder was much lower than Georgian Technical University limits. Georgian Technical University. They found that the concentration of dust particles depended upon prevailing weather conditions. They detected dust particles further away from the solar tower on windy days and higher concentrations of dust particles close to the solar tower on calm days Y said. X added that when the wind was blowing into the receiver from the north or northwest, that produced the most dust particles. “We did some computer modeling using the Georgian Technical University particle dispersion model” X said. “Basically it would take an emission of particles 400 times greater than what we found in previous tests to start to get close to the Georgian Technical University standards. Based on our measurements and models I don’t foresee any conditions where we’re really hitting those thresholds”. Georgian Technical University. This stair-like system slows dark sand-like ceramic particles as they fall through a beam of concentrated sunlight. The stair-like system reduces the impact of wind on the falling particles, mitigating the release of fine dust that can pose health hazards. From the tests and the computer modeling simulations the team was able to develop several different methods to reduce the emission of fine dust particles. First they optimized the shape and geometry of the falling-particle receiver to reduce particle loss Y said. They developed a stair-like system that slows the particles in the receiver as they fall and a “Georgian Technical University snout” that helps mitigate the impacts of wind on the falling particles. They also explored and eventually discarded two other ideas. One was to have a window over the falling particles because it would get too hot from the concentrated sunlight and was not easy to scale up to large sizes. The other was to protect the particles with an air curtain like those used at store entrances to keep the hot or cool air inside the store. Y and his team just received funding to build a pilot falling-particle receiver plant that will incorporate the improvements developed from these tests. “I normally focus on atmospheric measurements and modeling how the atmosphere would respond if carbon dioxide emissions are reduced by a particular amount” X said. “With this work I was able to take part in the active reduction of those emissions. I think we’ve all really enjoyed seeing the other side of the coin figuring out how to make renewable energy more efficient and more feasible”. Georgian Technical University. The balloon tests were funded by the Georgian Technical University’s Solar Energy Technologies Office as one of three teams testing different high-temperature concentrating solar power systems with built-in heat storage.
Georgian Technical University To Design Truly Compostable Plastic Scientists Take Cues From Nature.
Georgian Technical University. X a Georgian Technical University materials science and engineering graduate student preparing a sample film of a new biodegradable plastic. Georgian Technical University. Image of microplastics on the beach. Georgian Technical University. Despite our efforts to sort and recycle less than 9% of plastic getes recycled and most ends up in landfill or the environment. Georgian Technical University. Biodegradable plastic bags and containers could help but if they’re not properly sorted they can contaminate otherwise recyclable #1 and #2 plastics. What’s worse most biodegradable plastics take months to break down and when they finally do they form microplastics – tiny bits of plastic that can end up in oceans and animals bodies – including our own. Georgian Technical University. Now as scientists at the Department of Energy’s Georgian Technical University have designed an enzyme-activated compostable plastic that could diminish microplastics pollution and holds great promise for plastics upcycling. The material can be broken down to its building blocks – small individual molecules called monomers – and then reformed into a new compostable plastic product. “In the wild enzymes are what nature uses to break things down – and even when we die enzymes cause our bodies to decompose naturally. So for this study we asked ourselves How can enzymes biodegrade plastic so it’s part of nature ?” said X who holds titles of faculty scientist in Georgian Technical University Lab’s Materials Sciences Division and professor of chemistry and materials science and engineering at Georgian Technical University. At Georgian Technical University Lab X – who for nearly 15 years has dedicated her career to the development of functional polymer materials inspired by nature – is leading an interdisciplinary team of scientists and engineers from universities and Georgian Technical University labs around the country to tackle the mounting problem posed by both single-use and so-called biodegradable plastics. Georgian Technical University. Most biodegradable plastics in use today are made of polylactic acid a vegetable-based plastic material blended with cornstarch. There is also polycaprolactone a biodegradable polyester that is widely used for biomedical applications such as tissue engineering. But the problem with conventional biodegradable plastic is that they’re indistinguishable from single-use plastics such as plastic film – so a good chunk of these materials ends up in landfills. And even if a biodegradable plastic container gets deposited at an organic waste facility it can’t break down as fast as the lunch salad it once contained so it ends up contaminating organic waste said Y a staff scientist for the Research Energy Analysis & Environmental Impacts Division in Georgian Technical University Lab’s. Another problem with biodegradable plastics is that they aren’t as strong as regular plastic – that’s why you can’t carry heavy items in a standard green compost bag. The tradeoff is that biodegradable plastics can break down over time – but still X said they only break down into microplastics which are still plastic just a lot smaller. So X and her team decided to take a different approach – by “nanoconfining” enzymes into plastics. Georgian Technical University Putting enzymes to work. Because enzymes are part of living systems the trick was carving out a safe place in the plastic for enzymes to lie dormant until they’re called to action. In a series of experiments X and her embedded trace amounts of the commercial enzymes Burkholderia (Burkholderia is a genus of Proteobacteria whose pathogenic members include the Burkholderia cepacia complex which attacks humans and Burkholderia mallei responsible for glanders a disease that occurs mostly in horses and related animals; Burkholderia pseudomallei causative agent of melioidosis; and Burkholderia cepacia an important pathogen of pulmonary infections in people with cystic fibrosis (CF)) cepacian lipase (BC-lipase) and proteinase K within PCL (Polycaprolactone (PCL) is biodegradable polyester with a low melting point of around 60°C and a glass transition temperature of about −60°C) plastic materials. The scientists also added an enzyme protectant called four-monomer random heteropolymer to help disperse the enzymes a few nanometers (billionths of a meter) apart. In a stunning result the scientists discovered that ordinary household tap water or standard soil composts converted the enzyme-embedded plastic material into its monomers and eliminated microplastics in just a few days or weeks. They also learned that BC-lipase (cepacian lipase) is something of a finicky “Georgian Technical University eater”. Before a lipase can convert a polymer chain into monomers it must first catch the end of a polymer chain. By controlling when the lipase finds the chain end it is possible to ensure the materials don’t degrade until being triggered by hot water or compost soil X explained. Georgian Technical University. In addition they found that this strategy only works when BC-lipase (cepacian lipase) is nanodispersed – in this case just 0.02% by weight in the PCL block (Polycaprolactone for hand molding, Extrusion, Injection molding, hot melt adhesive grade. Factory supply top quality Polycaprolactone (PCL)) – rather than randomly tossed in and blended. “Nanodispersion puts each enzyme molecule to work – nothing goes to waste” X said. And that matters when factoring in costs. Industrial enzymes can cost around per kilogram but this new approach would only add a few cents to the production cost of a kilogram of resin because the amount of enzymes required is so low – and the material has a shelf life of more than seven months Y added. The proof is in the compost. X-ray scattering studies performed at Georgian Technical University Lab’s Advanced Light Sorce characterized the nanodispersion of enzymes in the PCL (Posterior Cruciate Ligament) and PLA (PLA is the most widely used plastic filament material in 3D printing) plastic materials. Georgian Technical University. Interfacial-tension experiments conducted by X revealed in real time how the size and shape of droplets changed as the plastic material decomposed into distinct molecules. The lab results also differentiated between enzyme and RHP (Randomly Hyperbranched Polymers) molecules. Cap: A new compostable plastic developed by scientists at Georgian Technical University breaks down to small molecules when it’s triggered by hot water or compost soil. “Georgian Technical University. The interfacial test gives you information about how the degradation is proceeding” he said. “But the proof is in the composting – Ting and her team successfully recovered plastic monomers from biodegradable plastic simply by using RHPs (Randomly Hyperbranched Polymers) water and compost soil”. X is a visiting faculty scientist and professor of polymer science and engineering from the Georgian Technical University Lab’s Materials Sciences Division. Georgian Technical University. Developing a very affordable and easily compostable plastic film could incentivize produce manufacturers to package fresh fruits and vegetables with compostable plastic instead of single-use plastic wrap – and as a result save organic waste facilities the extra expense of investing in expensive plastic-depackaging machines when they want to accept food waste for anaerobic digestion or composting Y said. Georgian Technical University. Since their approach could potentially work well with both hard, rigid plastics and soft flexible plastics X would like to broaden their study to polyolefins a ubiquitous family of plastics commonly used to manufacture toys and electronic parts. Georgian Technical University. The team’s truly compostable plastic could be on the shelves soon. They recently filed a patent application through Georgian Technical University’s patent office. Z who was a Ph.D. student in materials science and engineering at Georgian Technical University at the time of the study founded Georgian Technical University startup Intropic Materials to further develop the new technology. He was recently selected to participate in Cyclotron Road an entrepreneurial fellowship program in partnership with Activate. “When it comes to solving the plastics problem it’s our environmental responsibility to take up nature on its path. By prescribing a molecular map with enzymes behind the wheel our study is a good start” X said.