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Lawrence Livermore National Laboratory (LLNL) scientists are scaling up the production of vertically aligned single-walled carbon nanotubes (SWCNT) that could revolutionize diverse commercial products ranging from rechargeable batteries, automotive parts and sporting goods to boat hulls and water filters. The research appears in the journal Carbon.

Most CNT production today is used in bulk composite materials and thin films, which rely on unorganized CNT architectures. For many uses, organized CNT architectures such as vertically aligned forests provide important advantages for exploiting the properties of individual CNTs in macroscopic systems.

“Robust synthesis of vertically-aligned carbon nanotubes at large scale is required to accelerate deployment of numerous cutting-edge devices to emerging ,” said LLNL scientist and lead author Francesco Fornasiero. “To address this need, we demonstrated that the structural characteristics of single-walled CNTs produced at wafer scale in a growth regime dominated by bulk diffusion of the gaseous carbon precursor are remarkably invariant over a broad range of process conditions.”

Thin films made of carbon nanotubes hold a lot of promise for advanced optoelectronics, energy and medicine, however with their manufacturing process subject to close supervision and stringent standardization requirements, they are unlikely to become ubiquitous anytime soon.

“A major hindrance to unlocking the vast potential of nanotubes is their multiphase which is extremely difficult to manage. We have suggested using (ANN) to analyze and predict the efficiency of single-walled carbon nanotubes synthesis,” explains one of the authors of the study and Skoltech researcher, Dmitry Krasnikov.

In their work published in the prestigious Carbon journal, the authors show that machine learning methods, and, in particular, ANN trained on experimental parameters, such as temperature, gas pressure and , can help monitor the properties of the carbon nanotube films produced.

Discusses the possibility of Femtotech and the technological possibilities it may unlock. Not long ago nanotechnology was a fringe topic; now it’s a flourishing engineering field, and fairly mainstream. For example, while writing this article, I happened to receive an email advertisement for the “Second World Conference on Nanomedicine and Drug Delivery,” in Kerala, India. It wasn’t so long ago that nanomedicine seemed merely a flicker in the eyes of Robert Freitas and a few other visionaries!

But nano is not as small as the world goes. A nanometer is 10–9 meters – the scale of atoms and molecules. A water molecule is a bit less than one nanometer long, and a germ is around a thousand nanometers across. On the other hand, a proton has a diameter of a couple femtometers – where a femtometer, at 10–15 meters, makes a nanometer seem positively gargantuan. Now that the viability of nanotech is widely accepted (in spite of some ongoing heated debates about the details), it’s time to ask: what about femtotech? Picotech or other technologies at the scales between nano and femto seem relatively uninteresting, because we don’t know any basic constituents of matter that exist at those scales. But femtotech, based on engineering structures from subatomic particles, makes perfect conceptual sense, though it’s certainly difficult given current technology.

The nanotech field was arguably launched by Richard Feynman’s 1959 talk “There’s Plenty of Room at the Bottom.” As Feynman wrote there.

“It is a staggeringly small world that is below. In the year 2000, when they look back at this age, they will wonder why it was not until the year 1960 that anybody began seriously to move in this direction.

Why cannot we write the entire 24 volumes of the Encyclopedia Brittanica on the head of a pin? ”

Bio: Hugo de Garis (born 1947, Sydney, Australia) is a researcher in the sub-field of artificial intelligence (AI) known as evolvable hardware. He became known in the 1990s for his research on the use of genetic algorithms to evolve neural networks using three dimensional cellular automata inside field programmable gate arrays. He claimed that this approach would enable the creation of what he terms “artificial brains” which would quickly surpass human levels of intelligence.

Year 2019 😁 nanoscale fusion.


A research team of fusion scientists has succeeded in developing “the nano-scale sculpture technique” to fabricate an ultra-thin film by sharpening a tungsten sample with a focused ion beam. This enables the nano-scale observation of a cross-section very near the top surface of the tungsten sample using the transmission electron microscope. The sculpture technique developed by this research can be applied not only to tungsten but also to other hard materials.

Hardened materials such as metals, carbons and ceramics are used in automobiles, aircraft and buildings. In a fusion reactor study, “tungsten,” which is one of the hardest metal materials, is the most likely candidate for the armour material of the device that receives the plasma heat/particle load. This device is called divertor. In any hardened materials, nanometer scale damages or defects can be formed very near the top surface of the materials. For predicting a material lifetime, it is necessary to know the types of the damages and their depth profiles in the material. To do this, we must observe a cross-section of the region very near the top surface of the material with nano-scale level.

For the observation of the internal structure of materials with nano-scale level, transmission electron microscope (TEM), in which accelerated electrons are transmitted through the target materials, is commonly used as a powerful tool. In order to observe a cross-section very near the top surface of the tungsten with TEM, we firstly extract a small piece of the tungsten sample from its surface and then fabricate an ultra-thin film by cutting the extracted sample. The thickness of the film must be below ~100 nm (nanometer) to obtain high resolution due to the high-transmission of the electron beam (IMAGE 1). However, it has been extremely difficult to fabricate such an ultra-thin film for the hard materials such as a tungsten. Therefore, it has been almost impossible to obtain the ~100 nm thickness level by using conventional thin-film fabrication technique.

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In the future humanity may build enormous structures, feats of mega-engineering that may rival planets or even be of greater scope. This episode catalogs roughly 100 major types of Megastructure, from those that are cities in space to those that rival galaxies.

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▬ Megastructure Index ▬▬▬▬▬▬▬▬▬▬
0:00 — Intro.
03:23 — Active Support.
04:30 — Alderson Disc.
08:30 — Arcology Megatower.
09:48 — Arkship.
10:49 — Artificial Sun.
11:49 — Asteroid Colonies.
13:02 — Atlas Pillars.
14:19 — Banks Orbital.
16:29 — Bernal Sphere.
17:34 — Birch Planet.
20:48 — Bishop Ring.
22:55 — Black Hole Gravity Generator.
23:54 — Black Hole Power Generator.
25:40 — Bubble Hab.
26:36 — Buckyhabs.
28:12 — BWC Megastructures.
29:08 — Caplan Thruster.
29:46 — Carbon Nanotubes.
30:31 — Chainworlds.
31:07 — Chandelier Cities.
31:45 — Clarketech.
32:30 — Cube Worlds.
33:24 — Cylinder Habitat.
36:09 — Dark Sky Station.
36:37 — Disc Worlds & Flat Earths.
38:01 — Dyson Spheres.
40:04 — Dyson Spike.
40:45 — Dyson Swarm.
42:14 — Ecumenopolis.
42:44 — Edersphere/Ederworld.
43:52 — Fusion Candle.
44:29 — Graphene.
44:49 — Grav Plating.
45:20 — Hammer Hab.
45:48 — Helios Drive.
46:43 — Hoop World or Donut World.
47:27 — Hydroshell.
48:13 — Interstellar Black Hole Highway.
48:48 — Interstellar Laser Highway.
50:06 — Jenkins Swarm.
50:27 — Kalpana 1
51:28 — Kipping Terrascope.
52:08 — Lagite.
52:57 — Lofstrom Loop.
53:52 — Magmatter.
54:50 — Matrioshka Brain.
56:45 — Matrioshka Shellworld.
57:53 — McKendree Cylinder.
58:36 — Megatelescope Arrays.
59:25 — Mini Earth.
1:00:30 — Mushroom Habitat.
1:01:26 — Neptunian Chainsaw.
1:01:55 — Nicoll-Dyson Beam.
1:02:52 — Nova Drive.
1:03:16 — O’Neill Cylinder.
1:03:57 — Orbital Plates.
1:04:42 — Orbital Ring.
1:07:22 — Paperclip Maximizer & Grey Goo.
1:08:26 — Parabolic Habitat.
1:10:08 — Planet Brain / Jupiter Brain.
1:10:35 — Planet Ships.
1:11:25 — Planet Swarm.
1:12:21 — Planetary Cycler/Aldrin Cycler.
1:13:10 — Power Beamers.
1:13:55 — Quasar drive.
1:15:25 — Quasite.
1:16:00 — Red Globular Cluster.
1:17:14 — Relativistic Kill Missile.
1:17:55 — Ribbon Worlds.
1:19:12 — Ring Habitat.
1:20:06 — Ringworld.
1:21:36 — Rotacity or Bowl Hab.
1:22:19 — Rungworld.
1:23:25 — Shell World.
1:24:53 — Shkadov Thrusters.
1:25:37 — Sky Cities & Cloud Cities.
1:26:38 — Skyhooks.
1:27:24 — Smoke Ring.
1:28:26 — Solar Mirrors.
1:29:21 — Solar Shades.
1:30:29 — Sombrero Planet.
1:30:51 — Space Elevetors.
1:32:18 — Space Farms.
1:33:27 — Spin Gravity.
1:34:05 — Space Towers.
1:34:50 — Stanford Torus.
1:35:45 — Starlifting.
1:36:55 — Statite.
1:38:31 — Stellar Pinwheel.
1:39:00 — Stellaser.
1:40:34 — Suntower.
1:41:51 — Supramundane Worlds.
1:42:57 — Terran Ring.
1:43:58 — Topopolis.
1:45:07 — Unobtainium.
1:45:35 — Valley House.
1:45:55 — World House.
1:46:26 — Wormhole.
1:53:00 — Credits.

Credits:
The Megastructure Compendium.
Science & Futurism with Isaac Arthur.
Episode 346, June 9, 2022
Written & Produced by Isaac Arthur.
Narrated by Isaac Arthur & Sarah Fowler Arthur.

Editors:

Researchers used deep reinforcement learning to steer atoms into a lattice shape, with a view to building new materials or nanodevices.

In a very cold vacuum chamber, single atoms of silver form a star-like . The precise formation is not accidental, and it wasn’t constructed directly by either. Researchers used a kind of artificial intelligence called learning to steer the atoms, each a fraction of a nanometer in size, into the lattice shape. The process is similar to moving marbles around a Chinese checkers board, but with very tiny tweezers grabbing and dragging each atom into place.

The main application for deep is in robotics, says postdoctoral researcher I-Ju Chen. “We’re also building robotic arms with deep learning, but for moving atoms,” she explains. “Reinforcement learning is successful in things like playing chess or video games, but we’ve applied it to solve at the nanoscale.”

While studying how bio-inspired materials might inform the design of next-generation computers, scientists at the Department of Energy’s Oak Ridge National Laboratory achieved a first-of-its-kind result that could have big implications for both edge computing and human health.

Results published in Proceedings of the National Academy of Sciences show that an artificial is capable of long-term potentiation, or LTP, a hallmark of biological learning and . This is the first evidence that a cell membrane alone—without proteins or other biomolecules embedded within it—is capable of LTP that persists for many hours. It is also the first identified nanoscale structure in which memory can be encoded.

“When facilities were shut down as a result of COVID, this led us to pivot away from our usual membrane research,” said John Katsaras, a biophysicist in ORNL’s Neutron Sciences Directorate specializing in neutron scattering and the study of biological membranes at ORNL.

University of Central Florida researchers have created unique technology for treating osteoporosis that uses nanobubbles to deliver treatment to targeted areas of a person’s body.

The new technology was developed by Mehdi Razavi, an assistant professor in UCF’s College of Medicine and a member of the Biionix Cluster at UCF, and UCF biomedical sciences student Angela Shar at the Biomaterials and Nanomedicine Lab, as part of the lab’s focus on developing tools for diagnostics and therapeutics.

Osteoporosis is a disease marked by an imbalance between the body’s ability to form new , or ossification, and break down, or remove, old , known as resorption.

Two categories of nanofabrication technologies are known as top-down and bottom-up approaches [5]. For the former, nanosized materials are prepared through the rupture of bulk materials to fine particles, and such a process is usually conducted by diverse physical and mechanical techniques like lithography, laser ablation, sputtering, ball milling and arc-discharging [6, 7]. These techniques themselves are simple, and nanosized materials can be produced quickly after relatively short technological process, but expensive specialized equipment and high energy consumption are usually inevitable. Meanwhile, a variety of efficient chemical bottom-up methods, where atoms assemble into nuclei and then form nanoparticles, have been intensively studied to synthesize and modulate nanomaterials with specific shape and size [8].

Indeed, chemical methodologies, including but not limited to, aqueous reaction using chemical reducing agents (e.g. hydrazine hydrate and sodium borohydride), electrochemical deposition, hydrothermal/solvothermal synthesis, sol–gel processing, chemical liquid/vapor deposition, have been developed up to now [5, 6]. These approaches can not only produce diverse nanomaterials with fairly high yields, but also endow fine controllability in tailoring nanostructures and properties of the products. Nevertheless, they have been encountering some serious challenges of harsh reaction conditions (e.g. pH and temperature), potential risks in human health and environment, and low cost-effectiveness. Moreover, there are biosafety concerns on products synthesized chemically using hazardous reagents, which restricts their applications in many areas, particularly in medicines and pharmaceuticals [9].

Impressively, biological methodology is becoming a favourite in nanomaterial synthesis nowadays to address challenges in chemical synthesis. Compared to chemical routes, biosynthesis using natural and biological materials as reducing, stabilizing and capping agents are simple, energy-and cost-effective, mild and environment-friendly, which is termed as “Green Chemistry” [2, 6]. More significantly, the biologically synthesized nanomaterials have much better competitiveness in biocompatibility, compared to those chemically derived counterparts. On the one hand, the biogenic nanomaterials are free from toxic contamination of by-products that are usually involved in chemical synthesis process; on the other hand, the biosynthesis do not need additional stabilizing agents because either the used organisms themselves or their constituents can act as capping and stabilizing agents and the attached biological components in turn form biocompatible envelopes on the resultant nanomaterials, leading to actively interact with biological systems [2]. As one of the most abundant biological resources, some microorganisms have adapted to habitat contaminated with toxic metals, and thus evolved powerful tactics for remediating polluted environment while recycling metal resources [7, 10], and some review articles on the biosynthesis of MNPs using diverse microorganisms including bacteria, yeast, fungi, alga, etc. and their applications have been published in recent years [1, 2, 6, 7, 10].