In recent years, there has been a rise in cynicism about many traditionally well-respected institutions – science, academia, news reporting, and even the concepts of experts and expertise more generally. Many people’s primary – or only – exposure to science is through biological or health science, especially during the COVID-19 pandemic.
In health research, rising cynicism has spawned the anti-vaccine movement, and a growing reliance on advice from peer networks rather than experts. In part, such movements are fuelled by several examples of provably false, so-called “scientific results,” coming about either through fraud or incompetence. While skepticism is crucial to science, cynicism rooted in a lack of trust can devalue scientific contributions.
In her lecture webcast, physicist Catherine Beauchemin will explore the erosion of trust in health research, presenting examples from influenza and COVID-19. …
Two essential ingredients of the scientific method are skepticism and independent confirmation – the ability to glean for oneself whether an established theory or a new hypothesis is true or false. But not everyone has the capacity to perform the experiments to obtain such a confirmation.
Consider, for example, the costs of constructing your own Large Hadron Collider, or your ability as a non-expert to critically read and understand a scientific publication. In practice, acceptance of scientific theories is more often based on trust than on independent confirmation. When that trust is eroded, issues emerge.
In her November 4  Perimeter Public Lecture webcast, Beauchemin will highlight some of the issues that have eroded trust in health research, presenting examples from influenza and COVID-19. She will show why she believes many of these issues have their root in the fact that hypotheses in health research are formulated as words rather than mathematical expressions – and why a dose of physics may be just the prescription we need.
This is fascinating and it’s not a memristor. (You can find out more about memristors here on the Nanowerk website). Getting back to the research, scientists at Hokkaido University (Japan) are training squishy hydrogel to remember according to a July 28, 2020 news item on phys.org (Note: Links have been removed),
Hokkaido University researchers have found a soft and wet material that can memorize, retrieve, and forget information, much like the human brain. They report their findings in the journal Proceedings of the National Academy of Sciences (PNAS).
The human brain learns things, but tends to forget them when the information is no longer important. Recreating this dynamic memory process in manmade materials has been a challenge. Hokkaido University researchers now report a hydrogel that mimics the dynamic memory function of the brain: encoding information that fades with time depending on the memory intensity.
Hydrogels are flexible materials composed of a large percentage of water—in this case about 45%—along with other chemicals that provide a scaffold-like structure to contain the water. Professor Jian Ping Gong, Assistant Professor Kunpeng Cui and their students and colleagues in Hokkaido University’s Institute for Chemical Reaction Design and Discovery (WPI-ICReDD) are seeking to develop hydrogels that can serve biological functions.
“Hydrogels are excellent candidates to mimic biological functions because they are soft and wet like human tissues,” says Gong. “We are excited to demonstrate how hydrogels can mimic some of the memory functions of brain tissue.”
In this study, the researchers placed a thin hydrogel between two plastic plates; the top plate had a shape or letters cut out, leaving only that area of the hydrogel exposed. For example, patterns included an airplane and the word “GEL.” They initially placed the gel in a cold water bath to establish equilibrium. Then they moved the gel to a hot bath. The gel absorbed water into its structure causing a swell, but only in the exposed area. This imprinted the pattern, which is like a piece of information, onto the gel. When the gel was moved back to the cold water bath, the exposed area turned opaque, making the stored information visible, due to what they call “structure frustration.” At the cold temperature, the hydrogel gradually shrank, releasing the water it had absorbed. The pattern slowly faded. The longer the gel was left in the hot water, the darker or more intense the imprint would be, and therefore the longer it took to fade or “forget” the information. The team also showed hotter temperatures intensified the memories.
“This is similar to humans,” says Cui. “The longer you spend learning something or the stronger the emotional stimuli, the longer it takes to forget it.”
The team showed that the memory established in the hydrogel is stable against temperature fluctuation and large physical stretching. More interestingly, the forgetting processes can be programmed by tuning the thermal learning time or temperature. For example, when they applied different learning times to each letter of “GEL,” the letters disappeared sequentially.
The team used a hydrogel containing materials called polyampholytes or PA gels. The memorizing-forgetting behavior is achieved based on fast water uptake and slow water release, which is enabled by dynamic bonds in the hydrogels. “This approach should work for a variety of hydrogels with physical bonds,” says Gong.
“The hydrogel’s brain-like memory system could be explored for some applications, such as disappearing messages for security,” Cui added.
Here’s a link to and a citation for the paper,
Hydrogels as dynamic memory with forgetting ability by Chengtao Yu, Honglei Guo, Kunpeng Cui, Xueyu Li, Ya Nan Ye, Takayuki Kurokawa, and Jian Ping Gong. PNAS August 11, 2020 117 (32) 18962-18968 DOI: https://doi.org/10.1073/pnas.2006842117 First published July 27, 2020
An optical fiber made of agar has been produced at the University of Campinas (UNICAMP) in the state of São Paulo, Brazil. This device is edible, biocompatible and biodegradable. It can be used in vivo for body structure imaging, localized light delivery in phototherapy or optogenetics (e.g., stimulating neurons with light to study neural circuits in a living brain), and localized drug delivery.
Another possible application is the detection of microorganisms in specific organs, in which case the probe would be completely absorbed by the body after performing its function.
An article on the study is published) in Scientific Reports, an online journal owned by Springer Nature.
Agar, also called agar-agar, is a natural gelatin obtained from marine algae. Its composition consists of a mixture of two polysaccharides, agarose and agaropectin. “Our optical fiber is an agar cylinder with an external diameter of 2.5 millimeters [mm] and a regular inner arrangement of six 0.5 mm cylindrical airholes around a solid core. Light is confined owing to the difference between the refraction indices of the agar core and the airholes,” Fujiwara told.
“To produce the fiber, we poured food-grade agar into a mold with six internal rods placed lengthwise around the main axis,” he continued. “The gel distributes itself to fill the available space. After cooling, the rods are removed to form airholes, and the solidified waveguide is released from the mold. The refraction index and geometry of the fiber can be adapted by varying the composition of the agar solution and mold design, respectively.”
The researchers tested the fiber in different media, from air and water to ethanol and acetone, concluding that it is context-sensitive. “The fact that the gel undergoes structural changes in response to variations in temperature, humidity and pH makes the fiber suitable for optical sensing,” Fujiwara said.
Another promising application is its simultaneous use as an optical sensor and a growth medium for microorganisms. “In this case, the waveguide can be designed as a disposable sample unit containing the necessary nutrients. The immobilized cells in the device would be optically sensed, and the signal would be analyzed using a camera or spectrometer,” he said.
About São Paulo Research Foundation (FAPESP)
The São Paulo Research Foundation (FAPESP) is a public institution with the mission of supporting scientific research in all fields of knowledge by awarding scholarships, fellowships and grants to investigators linked with higher education and research institutions in the State of São Paulo, Brazil. FAPESP is aware that the very best research can only be done by working with the best researchers internationally. Therefore, it has established partnerships with funding agencies, higher education, private companies, and research organizations in other countries known for the quality of their research and has been encouraging scientists funded by its grants to further develop their international collaboration. You can learn more about FAPESP at http://www.fapesp.br/en and visit FAPESP news agency at http://www.agencia.fapesp.br/en to keep updated with the latest scientific breakthroughs FAPESP helps achieve through its many programs, awards and research centers. You may also subscribe to FAPESP news agency at http://agencia.fapesp.br/subscribe.
As per my usual practice, here’s a link to and a citation for the paper,
Agarose-based structured optical fibre by Eric Fujiwara, Thiago D. Cabral, Miko Sato, Hiromasa Oku & Cristiano M. B. Cordeiro. Scientific Reports volume 10, Article number: 7035 (2020) DOI: https://doi.org/10.1038/s41598-020-64103-3 Published: 27 April 2020
This paper is open access.
Should you have a problem accessing the English language version of the FAPESP website, the Portuguese language version of the site seems more accessible (assuming you have the language skills).
A July 1, 2020 news item on ScienceDaily announces work which researchers are hopeful will allow them exert more control over neuromorphic devices’ speed of response,
“Neuromorphic” refers to mimicking the behavior of brain neural cells. When one speaks of neuromorphic computers, they are talking about making computers think and process more like human brains-operating at high-speed with low energy consumption.
Despite a growing interest in polymer-based neuromorphic devices, researchers have yet to establish an effective method for controlling the response speed of devices. Researchers from Tohoku University and the University of Cambridge, however, have overcome this obstacle through mixing the polymers PSS-Na and PEDOT:PSS, discovering that adding an ion conducting polymer enhances neuromorphic device response time.
Polymers are materials composed of long molecular chains and play a fundamental aspect in modern life from the rubber in tires, to water bottles, to polystyrene. Mixing polymers together results in the creation of new materials with their own distinct physical properties.
Most studies on neuromorphic devices based on polymer focus exclusively on the application of PEDOT: PSS, a mixed conductor that transports both electrons and ions. PSS-Na, on the other hand, transports ions only. By blending these two polymers, the researchers could enhance the ion diffusivity in the active layer of the device. Their measurements confirmed an increase in device response time, achieving a 5-time shorting at maximum. The results also proved how closely related response time is to the diffusivity of ions in the active layer.
“Our study paves the way for a deeper understanding behind the science of conducting polymers.” explains co-author Shunsuke Yamamoto from the Department of Biomolecular Engineering at Tohoku University’s Graduate School of Engineering. “Moving forward, it may be possible to create artificial neural networks composed of multiple neuromorphic devices,” he adds.
According to the British Royal Automobile and the French Automobile clubs, the first car was created in 1770 by the Frenchman Joseph Cugnot. This “Fardier” (French name for a trolley used to transport heavy loads) was a car propelled by a steam engine and powered by a boiler. This 7 m long self-propelled machine reached a speed of 4 km/h, for an average autonomy of 15 min. 250 years later, researchers at the Nara Institute of Science and Technology (NAIST), Japan, in partnership with colleagues in the University Paul Sabatier (Toulouse, France), report in Chemistry – A European Journal a new family of nanocars integrating a dipole to speed up their motion in the nanoworld.
After the first nanocar race organized in spring 2017, in Toulouse (France) we designed a new family of molecules to behave as cars in the nanoworld. When I established my laboratory in NAIST in April 2018, Toshio Nishino (Assistant Professor) and Hiroki Takeuchi (Master student) started the synthesis. Two years later, we are reporting the results in a publication presenting the synthesis of 9 dipolar nanocars. The result is amazing. In every flask, about 100 mg of green or blue powders (i.e. 60 x 1018 nanocars) stick to the walls. These are the Franco-Japanese racing cars that sleep wisely in the garage waiting for the next Grand Prix in 2021.
“To hope to win the race, nanocars have to be fast but they need also to be controllable,” emphasizes Gwénaël Rapenne. The design of the molecules has long been thought to need a compromise between opposite requirements. Consistently, the nanocar Rapenne and his colleagues designed is made up of 150 atoms (chemical formula C85H59N5Zn). A planar chassis made from porphyrin, a fragment already used in nature for many processes like oxygen transportation (hemoglobin) or photosynthesis (chlorophyl). Ultimately, the presence of a zinc atom could allow transportation of small molecules on the car body. “The nanocar is 2 nm long and surrounded by four wheels designed to minimize contact with the ground and has two legs which are able to donate or accept electrons making the nanocar dipolar” specifies the researcher.
What kind of application could be envisioned with such small vehicles?
“Honestly, today, we do not know yet what this technology will be used for. But just like the liquid crystals discovered in 1910 and not used until half a century later in calculator screens and now in all our LCD supports, the manipulation of molecules could well be revolutionary, ” dreams Gwénaël Rapenne. One of the directions of the research could be to carry a load to transport reactants or drugs from one place to another.
Here’s a link to and a citation for the paper,
Dipolar Nanocars Based on a Porphyrin Backbone by Toshio Nishino, Colin J. Martin, Hiroki Takeuchi, Florence Lim, Kazuma Yasuhara, Yohan Gisbert, Seifallah Abid, Nathalie Saffon-Merceron, Claire Kammerer, Gwénaël Rapenne. Chemistry Europe DOI: https://doi.org/10.1002/chem.202001999 First published: 12 June 2020
This paper is behind a paywall.
For anyone curious about the 2017 race, I found this May 9, 2017 posting, which notes that a US-Austrian team won.
I always appreciate a reference to Star Trek and three-dimensional chess was one of my favourite concepts. You’ll find that and more in a May 19, 2020 news item on Nanowerk,
Researchers at The Institute of Scientific and Industrial Research at Osaka University [Japan] introduced a new liquid-phase fabrication method for producing nanocellulose films with multiple axes of alignment. Using 3D-printing methods for increased control, this work may lead to cheaper and more environmentally friendly optical and thermal devices.
Ever since appearing on the original Star Trek TV show in the 1960s, the game of “three-dimensional chess” has been used as a metaphor for sophisticated thinking. Now, researchers at Osaka University can say that they have added their own version, with potential applications in advanced optics and inexpensive smartphone displays.
It’s not exactly three-dimensional chess but this nanocellulose film was produced by 3D printing methods,
Many existing optical devices, including liquid-crystal displays (LCDs) found in older flat-screen televisions, rely on long needle-shaped molecules aligned in the same direction. However, getting fibers to line up in multiple directions on the same device is much more difficult. Having a method that can reliably and cheaply produce optical fibers would accelerate the manufacture of low-cost displays or even “paper electronics”–computers that could be printed from biodegradable materials on demand.
Cellulose, the primary component of cotton and wood, is an abundant renewable resource made of long molecules. Nanocelluloses are nanofibers made of uniaxially aligned cellulose molecular chains that have different optical and heat conduction properties along one direction compared to the another.
In newly published research from the Institute of Scientific and Industrial Research at Osaka University, nanocellulose was harvested from sea pineapples, a kind of sea squirt. They then used liquid-phase 3D-pattering, which combined the wet spinning of nanofibers with the precision of 3D-printing. A custom-made triaxial robot dispensed a nanocellulose aqueous suspension into an acetone coagulation bath.
“We developed this liquid-phase three-dimensional patterning technique to allow for nanocellulose alignment along any preferred axis,” says first author Kojiro Uetani. The direction of the patterns could be programmed so that it formed an alternating checkerboard pattern of vertically- and horizontally-aligned fibers.
To demonstrate the method, a film was sandwiched between two orthogonal polarizing films. Under the proper viewing conditions, a birefringent checkerboard pattern appeared. They also measured the thermal transfer and optical retardation properties.
“Our findings could aid in the development of next-generation optical materials and paper electronics,” says senior author Masaya Nogi. “This could be the start of bottom-up techniques for building sophisticated and energy-efficient optical and thermal materials.”
I’ve been meaning to get to this news item from late 2019 as it features work from a team that I’ve been following for a number of years now. First mentioned here in an October 17, 2011 posting, James Gimzewski has been working with researchers at the University of California at Los Angeles (UCLA) and researchers at Japan’s National Institute for Materials Science (NIMS) on neuromorphic computing.
This particular research had a protracted rollout with the paper being published in October 2019 and the last news item about it being published in mid-December 2019.
UCLA scientists James Gimzewski and Adam Stieg are part of an international research team that has taken a significant stride toward the goal of creating thinking machines.
Led by researchers at Japan’s National Institute for Materials Science, the team created an experimental device that exhibited characteristics analogous to certain behaviors of the brain — learning, memorization, forgetting, wakefulness and sleep. The paper, published in Scientific Reports (“Emergent dynamics of neuromorphic nanowire networks”), describes a network in a state of continuous flux.
“This is a system between order and chaos, on the edge of chaos,” said Gimzewski, a UCLA distinguished professor of chemistry and biochemistry, a member of the California NanoSystems Institute at UCLA and a co-author of the study. “The way that the device constantly evolves and shifts mimics the human brain. It can come up with different types of behavior patterns that don’t repeat themselves.”
The research is one early step along a path that could eventually lead to computers that physically and functionally resemble the brain — machines that may be capable of solving problems that contemporary computers struggle with, and that may require much less power than today’s computers do.
The device the researchers studied is made of a tangle of silver nanowires — with an average diameter of just 360 nanometers. (A nanometer is one-billionth of a meter.) The nanowires were coated in an insulating polymer about 1 nanometer thick. Overall, the device itself measured about 10 square millimeters — so small that it would take 25 of them to cover a dime.
Allowed to randomly self-assemble on a silicon wafer, the nanowires formed highly interconnected structures that are remarkably similar to those that form the neocortex, the part of the brain involved with higher functions such as language, perception and cognition.
One trait that differentiates the nanowire network from conventional electronic circuits is that electrons flowing through them cause the physical configuration of the network to change. In the study, electrical current caused silver atoms to migrate from within the polymer coating and form connections where two nanowires overlap. The system had about 10 million of these junctions, which are analogous to the synapses where brain cells connect and communicate.
The researchers attached two electrodes to the brain-like mesh to profile how the network performed. They observed “emergent behavior,” meaning that the network displayed characteristics as a whole that could not be attributed to the individual parts that make it up. This is another trait that makes the network resemble the brain and sets it apart from conventional computers.
After current flowed through the network, the connections between nanowires persisted for as much as one minute in some cases, which resembled the process of learning and memorization in the brain. Other times, the connections shut down abruptly after the charge ended, mimicking the brain’s process of forgetting.
In other experiments, the research team found that with less power flowing in, the device exhibited behavior that corresponds to what neuroscientists see when they use functional MRI scanning to take images of the brain of a sleeping person. With more power, the nanowire network’s behavior corresponded to that of the wakeful brain.
The paper is the latest in a series of publications examining nanowire networks as a brain-inspired system, an area of research that Gimzewski helped pioneer along with Stieg, a UCLA research scientist and an associate director of CNSI.
“Our approach may be useful for generating new types of hardware that are both energy-efficient and capable of processing complex datasets that challenge the limits of modern computers,” said Stieg, a co-author of the study.
The borderline-chaotic activity of the nanowire network resembles not only signaling within the brain but also other natural systems such as weather patterns. That could mean that, with further development, future versions of the device could help model such complex systems.
In other experiments, Gimzewski and Stieg already have coaxed a silver nanowire device to successfully predict statistical trends in Los Angeles traffic patterns based on previous years’ traffic data.
Because of their similarities to the inner workings of the brain, future devices based on nanowire technology could also demonstrate energy efficiency like the brain’s own processing. The human brain operates on power roughly equivalent to what’s used by a 20-watt incandescent bulb. By contrast, computer servers where work-intensive tasks take place — from training for machine learning to executing internet searches — can use the equivalent of many households’ worth of energy, with the attendant carbon footprint.
“In our studies, we have a broader mission than just reprogramming existing computers,” Gimzewski said. “Our vision is a system that will eventually be able to handle tasks that are closer to the way the human being operates.”
The study’s first author, Adrian Diaz-Alvarez, is from the International Center for Material Nanoarchitectonics at Japan’s National Institute for Materials Science. Co-authors include Tomonobu Nakayama and Rintaro Higuchi, also of NIMS; and Zdenka Kuncic at the University of Sydney in Australia.
An international joint research team led by NIMS succeeded in fabricating a neuromorphic network composed of numerous metallic nanowires. Using this network, the team was able to generate electrical characteristics similar to those associated with higher order brain functions unique to humans, such as memorization, learning, forgetting, becoming alert and returning to calm. The team then clarified the mechanisms that induced these electrical characteristics.
The development of artificial intelligence (AI) techniques has been rapidly advancing in recent years and has begun impacting our lives in various ways. Although AI processes information in a manner similar to the human brain, the mechanisms by which human brains operate are still largely unknown. Fundamental brain components, such as neurons and the junctions between them (synapses), have been studied in detail. However, many questions concerning the brain as a collective whole need to be answered. For example, we still do not fully understand how the brain performs such functions as memorization, learning and forgetting, and how the brain becomes alert and returns to calm. In addition, live brains are difficult to manipulate in experimental research. For these reasons, the brain remains a “mysterious organ.” A different approach to brain research?in which materials and systems capable of performing brain-like functions are created and their mechanisms are investigated?may be effective in identifying new applications of brain-like information processing and advancing brain science.
The joint research team recently built a complex brain-like network by integrating numerous silver (Ag) nanowires coated with a polymer (PVP) insulating layer approximately 1 nanometer in thickness. A junction between two nanowires forms a variable resistive element (i.e., a synaptic element) that behaves like a neuronal synapse. This nanowire network, which contains a large number of intricately interacting synaptic elements, forms a “neuromorphic network”. When a voltage was applied to the neuromorphic network, it appeared to “struggle” to find optimal current pathways (i.e., the most electrically efficient pathways). The research team measured the processes of current pathway formation, retention and deactivation while electric current was flowing through the network and found that these processes always fluctuate as they progress, similar to the human brain’s memorization, learning, and forgetting processes. The observed temporal fluctuations also resemble the processes by which the brain becomes alert or returns to calm. Brain-like functions simulated by the neuromorphic network were found to occur as the huge number of synaptic elements in the network collectively work to optimize current transport, in the other words, as a result of self-organized and emerging dynamic processes..
The research team is currently developing a brain-like memory device using the neuromorphic network material. The team intends to design the memory device to operate using fundamentally different principles than those used in current computers. For example, while computers are currently designed to spend as much time and electricity as necessary in pursuit of absolutely optimum solutions, the new memory device is intended to make a quick decision within particular limits even though the solution generated may not be absolutely optimum. The team also hopes that this research will facilitate understanding of the brain’s information processing mechanisms.
This project was carried out by an international joint research team led by Tomonobu Nakayama (Deputy Director, International Center for Materials Nanoarchitectonics (WPI-MANA), NIMS), Adrian Diaz Alvarez (Postdoctoral Researcher, WPI-MANA, NIMS), Zdenka Kuncic (Professor, School of Physics, University of Sydney, Australia) and James K. Gimzewski (Professor, California NanoSystems Institute, University of California Los Angeles, USA).
Here at last is a link to and a citation for the paper,
Emergent dynamics of neuromorphic nanowire networks by Adrian Diaz-Alvarez, Rintaro Higuchi, Paula Sanz-Leon, Ido Marcus, Yoshitaka Shingaya, Adam Z. Stieg, James K. Gimzewski, Zdenka Kuncic & Tomonobu Nakayama. Scientific Reports volume 9, Article number: 14920 (2019) DOI: https://doi.org/10.1038/s41598-019-51330-6 Published: 17 October 2019
A new, cheaper method easily and effectively separates two types of carbon nanotubes. The process, developed by Nagoya University researchers in Japan, could be up-scaled for manufacturing purified batches of single-wall carbon nanotubes that can be used in high-performance electronic devices.
Single-wall carbon nanotubes (SWCNTs) have excellent electronic and mechanical properties, making them ideal candidates for use in a wide range of electronic devices, including the thin-film transistors found in LCD displays. A problem is that only two-thirds of manufactured SWCNTs are suitable for use in electronic devices. The useful semiconducting SWCNTs must be separated from the unwanted metallic ones. But the most powerful purification process, known as aqueous two-phase extraction, currently involves the use of a costly polysaccharide, called dextran.
Organic chemist Haruka Omachi and colleagues at Nagoya University hypothesized that dextran’s effectiveness in separating semiconducting from metallic SWCNTs lies in the linkages connecting its glucose units. Instead of using dextran to separate the two types of SWCNTs, the team tried the significantly cheaper isomaltodextran, which has many more of these linkages.
A batch of SWCNTs was left for 15 minutes in a solution containing polyethylene glycol and isomaltodextrin and then centrifuged for five minutes. Three different types of isomaltodextrin were tried, each with a different number of linkages and a different molecular weight. The team found that metallic SWCNTs separated to the bottom isomaltodextrin part of the solution, while the semiconducting SWCNTs floated to the top polyethylene glycol part.
The type of isomaltodextrin with high molecular weight and the most linkages was the most (99%) effective in separating the two types of SWCNTs. The team also found that another polysaccharide, called pullulan, whose glucose units are connected with different kinds of linkages, was ineffective in separating the two types of SWCNTs. The researchers suggest that the number and type of linkages present in isomaltodextrin play an important role in their ability to effectively separate the carbon nanotubes.
The team also found that a thin-film transistor made with their purified semiconducting SWCNTs performed very well.
Isomaltodextrin is a cheap and widely available polysaccharide produced from starch that is used as a dietary fibre. This makes it a cost-effective alternative for the SWCNT extraction process. Omachi and his colleagues are currently in discussions with companies to commercialize their approach. They are also working on improving the performance of thin-film transistors using semiconducting SWCNTs in flexible displays and sensor devices.
A typical waterproof winter jacket is made with nylon—a material that, like other plastics, is made from petroleum. But a new limited-edition jacket from The North Face Japan uses something called “brewed protein” instead. It’s a material inspired by spider silk that is fermented in giant vats, the same way that breweries make beer.
It’s one of the first uses of a material produced by the Japanese startup Spiber, a company that has spent more than a decade developing a new process to make high-performance textiles and other products that don’t rely on fossil fuels, animals, or natural fibers like cotton, all of which have environmental issues. …
The company designs genes that code for a specific protein—the first was an exact replica of natural spider silk, known for its extreme strength—and then introduces the genes into microorganisms that can produce the protein efficiently. Inside giant tanks, the microorganisms are fed sugar, grow and multiply, and produce the protein through fermentation. …
Spiber first started collaborating with Goldwin, a Japanese outdoor brand that owns the Japanese rights to The North Face, in 2015, and created an early prototype of a jacket then. But it quickly realized that an exact replica of spider silk wouldn’t work well for the application; the material sucks up water, and the jacket needed to be waterproof.
“We spent the last four years going back to the drawing board, redesigning our protein molecule—the very order of the amino acids in the molecule,” says Meyer [Daniel Meyer, Spiber’s head of corporate global marketing]. “And we created our own hydrophobic [water repellent] version of spider silk. It’s inspired by natural spider silk, but we have made our own design changes such that it would be more hydrophobic and meet the performance requirements of The North Face Japan.”
The jacket is available for purchase but only by a lottery, which has now closed. According to Peters, a large, commercial production facility is being built in Thailand so that at some point a Moon Parka will be affordable. For reference, the lottery jackets were priced at ¥150,000 (about $1,377 US).
Weaving a quantum processor from light is a jaw-dropping event (as far as I’m concerned). An October 17, 2019 news item on phys.org makes the announcement,
An international team of scientists from Australia, Japan and the United States has produced a prototype of a large-scale quantum processor made of laser light.
Based on a design ten years in the making, the processor has built-in scalability that allows the number of quantum components—made out of light—to scale to extreme numbers. The research was published in Science today [October 18, 2019; Note: I cannot explain the discrepancy between the dates]].
Quantum computers promise fast solutions to hard problems, but to do this they require a large number of quantum components and must be relatively error free. Current quantum processors are still small and prone to errors. This new design provides an alternative solution, using light, to reach the scale required to eventually outperform classical computers on important problems.
“While today’s quantum processors are impressive, it isn’t clear if the current designs can be scaled up to extremely large sizes,” notes Dr Nicolas Menicucci, Chief Investigator at the Centre for Quantum Computation and Communication Technology (CQC2T) at RMIT University in Melbourne, Australia.
“Our approach starts with extreme scalability – built in from the very beginning – because the processor, called a cluster state, is made out of light.”
Using light as a quantum processor
A cluster state is a large collection of entangled quantum components that performs quantum computations when measured in a particular way.
“To be useful for real-world problems, a cluster state must be both large enough and have the right entanglement structure. In the two decades since they were proposed, all previous demonstrations of cluster states have failed on one or both of these counts,” says Dr Menicucci. “Ours is the first ever to succeed at both.”
To make the cluster state, specially designed crystals convert ordinary laser light into a type of quantum light called squeezed light, which is then weaved into a cluster state by a network of mirrors, beamsplitters and optical fibres.
The team’s design allows for a relatively small experiment to generate an immense two-dimensional cluster state with scalability built in. Although the levels of squeezing – a measure of quality – are currently too low for solving practical problems, the design is compatible with approaches to achieve state-of-the-art squeezing levels.
The team says their achievement opens up new possibilities for quantum computing with light.
“In this work, for the first time in any system, we have made a large-scale cluster state whose structure enables universal quantum computation.” Says Dr Hidehiro Yonezawa, Chief Investigator, CQC2T at UNSW Canberra. “Our experiment demonstrates that this design is feasible – and scalable.”
The experiment was an international effort, with the design developed through collaboration by Dr Menicucci at RMIT, Dr Rafael Alexander from the University of New Mexico and UNSW Canberra researchers Dr Hidehiro Yonezawa and Dr Shota Yokoyama. A team of experimentalists at the University of Tokyo, led by Professor Akira Furusawa, performed the ground-breaking experiment.
Here’s a link to and a citation for the paper,
Generation of time-domain-multiplexed two-dimensional cluster state by Warit Asavanant, Yu Shiozawa, Shota Yokoyama, Baramee Charoensombutamon, Hiroki Emura, Rafael N. Alexander, Shuntaro Takeda, Jun-ichi Yoshikawa, Nicolas C. Menicucci, Hidehiro Yonezawa, Akira Furusawa. Science 18 Oct 2019: Vol. 366, Issue 6463, pp. 373-376 DOI: 10.1126/science.aay2645