Tag Archives: Lawrence Livermore National Laboratory (LLNL)

Carbon nanotubes for water desalination

In discussions about water desalination and carbon nanomaterials,  it’s graphene that’s usually mentioned these days. By contrast, scientists from the US Department of Energy’s Lawrence Livermore National Laboratory (LLNL) have turned to carbon nanotubes,

There are two news items about the work at LLNL on ScienceDaily, this first one originated by the American Association for the Advancement of Science (AAAS) offers a succinct summary of the work (from an August 24, 2017 news item on ScienceDaily,

At just the right size, carbon nanotubes can filter water with better efficiency than biological proteins, a new study reveals. The results could pave the way to new water filtration systems, at a time when demands for fresh water pose a global threat to sustainable development.

A class of biological proteins, called aquaporins, is able to effectively filter water, yet scientists have not been able to manufacture scalable systems that mimic this ability. Aquaporins usually exhibit channels for filtering water molecules at a narrow width of 0.3 nanometers, which forces the water molecules into a single-file chain.

Here, Ramya H. Tunuguntla and colleagues experimented with nanotubes of different widths to see which ones are best for filtering water. Intriguingly, they found that carbon nanotubes with a width of 0.8 nanometers outperformed aquaporins in filtering efficiency by a factor of six.

These narrow carbon nanotube porins (nCNTPs) were still slim enough to force the water molecules into a single-file chain. The researchers attribute the differences between aquaporins and nCNTPS to differences in hydrogen bonding — whereas pore-lining residues in aquaporins can donate or accept H bonds to incoming water molecules, the walls of CNTPs cannot form H bonds, permitting unimpeded water flow.

The nCNTPs in this study maintained permeability exceeding that of typical saltwater, only diminishing at very high salt concentrations. Lastly, the team found that by changing the charges at the mouth of the nanotube, they can alter the ion selectivity. This advancement is highlighted in a Perspective [in Science magazine] by Zuzanna Siwy and Francesco Fornasiero.

The second Aug. 24, 2017 news item on ScienceDaily offers a more technical  perspective,

Lawrence Livermore scientists, in collaboration with researchers at Northeastern University, have developed carbon nanotube pores that can exclude salt from seawater. The team also found that water permeability in carbon nanotubes (CNTs) with diameters smaller than a nanometer (0.8 nm) exceeds that of wider carbon nanotubes by an order of magnitude.

The nanotubes, hollow structures made of carbon atoms in a unique arrangement, are more than 50,000 times thinner than a human hair. The super smooth inner surface of the nanotube is responsible for their remarkably high water permeability, while the tiny pore size blocks larger salt ions.

There’s a rather lovely illustration for this work,

An artist’s depiction of the promise of carbon nanotube porins for desalination. The image depicts a stylized carbon nanotube pipe that delivers clean desalinated water from the ocean to a kitchen tap. Image by Ryan Chen/LLNL

An Aug. 24, 2017 LLNL news release (also on EurekAlert), which originated the second news item, proceeds

Increasing demands for fresh water pose a global threat to sustainable development, resulting in water scarcity for 4 billion people. Current water purification technologies can benefit from the development of membranes with specialized pores that mimic highly efficient and water selective biological proteins.

“We found that carbon nanotubes with diameters smaller than a nanometer bear a key structural feature that enables enhanced transport. The narrow hydrophobic channel forces water to translocate in a single-file arrangement, a phenomenon similar to that found in the most efficient biological water transporters,” said Ramya Tunuguntla, an LLNL postdoctoral researcher and co-author of the manuscript appearing in the Aug. 24 [2017]edition of Science.

Computer simulations and experimental studies of water transport through CNTs with diameters larger than 1 nm showed enhanced water flow, but did not match the transport efficiency of biological proteins and did not separate salt efficiently, especially at higher salinities. The key breakthrough achieved by the LLNL team was to use smaller-diameter nanotubes that delivered the required boost in performance.

“These studies revealed the details of the water transport mechanism and showed that rational manipulation of these parameters can enhance pore efficiency,” said Meni Wanunu, a physics professor at Northeastern University and co-author on the study.

“Carbon nanotubes are a unique platform for studying molecular transport and nanofluidics,” said Alex Noy, LLNL principal investigator on the CNT project and a senior author on the paper. “Their sub-nanometer size, atomically smooth surfaces and similarity to cellular water transport channels make them exceptionally suited for this purpose, and it is very exciting to make a synthetic water channel that performs better than nature’s own.”

This discovery by the LLNL scientists and their colleagues has clear implications for the next generation of water purification technologies and will spur a renewed interest in development of the next generation of high-flux membranes.

Here’s a link to and a citation for the paper,

Enhanced water permeability and tunable ion selectivity in subnanometer carbon nanotube porins by Ramya H. Tunuguntla, Robert Y. Henley, Yun-Chiao Yao, Tuan Anh Pham, Meni Wanunu, Aleksandr Noy. Science 25 Aug 2017: Vol. 357, Issue 6353, pp. 792-796 DOI: 10.1126/science.aan2438

This paper is behind a paywall.

And, Northeastern University issued an August 25, 2017 news release (also on EurekAlert) by Allie Nicodemo,

Earth is 70 percent water, but only a tiny portion—0.007 percent—is available to drink.

As potable water sources dwindle, global population increases every year. One potential solution to quenching the planet’s thirst is through desalinization—the process of removing salt from seawater. While tantalizing, this approach has always been too expensive and energy intensive for large-scale feasibility.

Now, researchers from Northeastern have made a discovery that could change that, making desalinization easier, faster and cheaper than ever before. In a paper published Thursday [August 24, 2017] in Science, the group describes how carbon nanotubes of a certain size act as the perfect filter for salt—the smallest and most abundant water contaminant.

Filtering water is tricky because water molecules want to stick together. The “H” in H2O is hydrogen, and hydrogen bonds are strong, requiring a lot of energy to separate. Water tends to bulk up and resist being filtered. But nanotubes do it rapidly, with ease.

A carbon nanotube is like an impossibly small rolled up sheet of paper, about a nanometer in diameter. For comparison, the diameter of a human hair is 50 to 70 micrometers—50,000 times wider. The tube’s miniscule size, exactly 0.8 nm, only allows one water molecule to pass through at a time. This single-file lineup disrupts the hydrogen bonds, so water can be pushed through the tubes at an accelerated pace, with no bulking.

“You can imagine if you’re a group of people trying to run through the hallway holding hands, it’s going to be a lot slower than running through the hallway single-file,” said co-author Meni Wanunu, associate professor of physics at Northeastern. Wanunu and post doctoral student Robert Henley collaborated with scientists at the Lawrence Livermore National Laboratory in California to conduct the research.

Scientists led by Aleksandr Noy at Lawrence Livermore discovered last year [2016] that carbon nanotubes were an ideal channel for proton transport. For this new study, Henley brought expertise and technology from Wanunu’s Nanoscale Biophysics Lab to Noy’s lab, and together they took the research one step further.

In addition to being precisely the right size for passing single water molecules, carbon nanotubes have a negative electric charge. This causes them to reject anything with the same charge, like the negative ions in salt, as well as other unwanted particles.

“While salt has a hard time passing through because of the charge, water is a neutral molecule and passes through easily,” Wanunu said. Scientists in Noy’s lab had theorized that carbon nanotubes could be designed for specific ion selectivity, but they didn’t have a reliable system of measurement. Luckily, “That’s the bread and butter of what we do in Meni’s lab,” Henley said. “It created a nice symbiotic relationship.”

“Robert brought the cutting-edge measurement and design capabilities of Wanunu’s group to my lab, and he was indispensable in developing a new platform that we used to measure the ion selectivity of the nanotubes,” Noy said.

The result is a novel system that could have major implications for the future of water security. The study showed that carbon nanotubes are better at desalinization than any other existing method— natural or man-made.

To keep their momentum going, the two labs have partnered with a leading water purification organization based in Israel. And the group was recently awarded a National Science Foundation/Binational Science Foundation grant to conduct further studies and develop water filtration platforms based on their new method. As they continue the research, the researchers hope to start programs where students can learn the latest on water filtration technology—with the goal of increasing that 0.007 percent.

As is usual in these cases there’s a fair degree of repetition but there’s always at least one nugget of new information, in this case, a link to Israel. As I noted many times, the Middle East is experiencing serious water issues. My most recent ‘water and the Middle East’ piece is an August 21, 2017 post about rainmaking at the Masdar Institute in United Arab Emirates. Approximately 50% of the way down the posting, I mention Israel and Palestine’s conflict over water.

IBM to build brain-inspired AI supercomputing system equal to 64 million neurons for US Air Force

This is the second IBM computer announcement I’ve stumbled onto within the last 4 weeks or so,  which seems like a veritable deluge given the last time I wrote about IBM’s computing efforts was in an Oct. 8, 2015 posting about carbon nanotubes,. I believe that up until now that was my  most recent posting about IBM and computers.

Moving onto the news, here’s more from a June 23, 3017 news item on Nanotechnology Now,

IBM (NYSE: IBM) and the U.S. Air Force Research Laboratory (AFRL) today [June 23, 2017] announced they are collaborating on a first-of-a-kind brain-inspired supercomputing system powered by a 64-chip array of the IBM TrueNorth Neurosynaptic System. The scalable platform IBM is building for AFRL will feature an end-to-end software ecosystem designed to enable deep neural-network learning and information discovery. The system’s advanced pattern recognition and sensory processing power will be the equivalent of 64 million neurons and 16 billion synapses, while the processor component will consume the energy equivalent of a dim light bulb – a mere 10 watts to power.

A June 23, 2017 IBM news release, which originated the news item, describes the proposed collaboration, which is based on IBM’s TrueNorth brain-inspired chip architecture (see my Aug. 8, 2014 posting for more about TrueNorth),

IBM researchers believe the brain-inspired, neural network design of TrueNorth will be far more efficient for pattern recognition and integrated sensory processing than systems powered by conventional chips. AFRL is investigating applications of the system in embedded, mobile, autonomous settings where, today, size, weight and power (SWaP) are key limiting factors.

The IBM TrueNorth Neurosynaptic System can efficiently convert data (such as images, video, audio and text) from multiple, distributed sensors into symbols in real time. AFRL will combine this “right-brain” perception capability of the system with the “left-brain” symbol processing capabilities of conventional computer systems. The large scale of the system will enable both “data parallelism” where multiple data sources can be run in parallel against the same neural network and “model parallelism” where independent neural networks form an ensemble that can be run in parallel on the same data.

“AFRL was the earliest adopter of TrueNorth for converting data into decisions,” said Daniel S. Goddard, director, information directorate, U.S. Air Force Research Lab. “The new neurosynaptic system will be used to enable new computing capabilities important to AFRL’s mission to explore, prototype and demonstrate high-impact, game-changing technologies that enable the Air Force and the nation to maintain its superior technical advantage.”

“The evolution of the IBM TrueNorth Neurosynaptic System is a solid proof point in our quest to lead the industry in AI hardware innovation,” said Dharmendra S. Modha, IBM Fellow, chief scientist, brain-inspired computing, IBM Research – Almaden. “Over the last six years, IBM has expanded the number of neurons per system from 256 to more than 64 million – an 800 percent annual increase over six years.’’

The system fits in a 4U-high (7”) space in a standard server rack and eight such systems will enable the unprecedented scale of 512 million neurons per rack. A single processor in the system consists of 5.4 billion transistors organized into 4,096 neural cores creating an array of 1 million digital neurons that communicate with one another via 256 million electrical synapses.    For CIFAR-100 dataset, TrueNorth achieves near state-of-the-art accuracy, while running at >1,500 frames/s and using 200 mW (effectively >7,000 frames/s per Watt) – orders of magnitude lower speed and energy than a conventional computer running inference on the same neural network.

The IBM TrueNorth Neurosynaptic System was originally developed under the auspices of Defense Advanced Research Projects Agency’s (DARPA) Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program in collaboration with Cornell University. In 2016, the TrueNorth Team received the inaugural Misha Mahowald Prize for Neuromorphic Engineering and TrueNorth was accepted into the Computer History Museum.  Research with TrueNorth is currently being performed by more than 40 universities, government labs, and industrial partners on five continents.

There is an IBM video accompanying this news release, which seems more promotional than informational,

The IBM scientist featured in the video has a Dec. 19, 2016 posting on an IBM research blog which provides context for this collaboration with AFRL,

2016 was a big year for brain-inspired computing. My team and I proved in our paper “Convolutional networks for fast, energy-efficient neuromorphic computing” that the value of this breakthrough is that it can perform neural network inference at unprecedented ultra-low energy consumption. Simply stated, our TrueNorth chip’s non-von Neumann architecture mimics the brain’s neural architecture — giving it unprecedented efficiency and scalability over today’s computers.

The brain-inspired TrueNorth processor [is] a 70mW reconfigurable silicon chip with 1 million neurons, 256 million synapses, and 4096 parallel and distributed neural cores. For systems, we present a scale-out system loosely coupling 16 single-chip boards and a scale-up system tightly integrating 16 chips in a 4´4 configuration by exploiting TrueNorth’s native tiling.

For the scale-up systems we summarize our approach to physical placement of neural network, to reduce intra- and inter-chip network traffic. The ecosystem is in use at over 30 universities and government / corporate labs. Our platform is a substrate for a spectrum of applications from mobile and embedded computing to cloud and supercomputers.
TrueNorth Ecosystem for Brain-Inspired Computing: Scalable Systems, Software, and Applications

TrueNorth, once loaded with a neural network model, can be used in real-time as a sensory streaming inference engine, performing rapid and accurate classifications while using minimal energy. TrueNorth’s 1 million neurons consume only 70 mW, which is like having a neurosynaptic supercomputer the size of a postage stamp that can run on a smartphone battery for a week.

Recently, in collaboration with Lawrence Livermore National Laboratory, U.S. Air Force Research Laboratory, and U.S. Army Research Laboratory, we published our fifth paper at IEEE’s prestigious Supercomputing 2016 conference that summarizes the results of the team’s 12.5-year journey (see the associated graphic) to unlock this value proposition. [keep scrolling for the graphic]

Applying the mind of a chip

Three of our partners, U.S. Army Research Lab, U.S. Air Force Research Lab and Lawrence Livermore National Lab, contributed sections to the Supercomputing paper each showcasing a different TrueNorth system, as summarized by my colleagues Jun Sawada, Brian Taba, Pallab Datta, and Ben Shaw:

U.S. Army Research Lab (ARL) prototyped a computational offloading scheme to illustrate how TrueNorth’s low power profile enables computation at the point of data collection. Using the single-chip NS1e board and an Android tablet, ARL researchers created a demonstration system that allows visitors to their lab to hand write arithmetic expressions on the tablet, with handwriting streamed to the NS1e for character recognition, and recognized characters sent back to the tablet for arithmetic calculation.

Of course, the point here is not to make a handwriting calculator, it is to show how TrueNorth’s low power and real time pattern recognition might be deployed at the point of data collection to reduce latency, complexity and transmission bandwidth, as well as back-end data storage requirements in distributed systems.

U.S. Air Force Research Lab (AFRL) contributed another prototype application utilizing a TrueNorth scale-out system to perform a data-parallel text extraction and recognition task. In this application, an image of a document is segmented into individual characters that are streamed to AFRL’s NS1e16 TrueNorth system for parallel character recognition. Classification results are then sent to an inference-based natural language model to reconstruct words and sentences. This system can process 16,000 characters per second! AFRL plans to implement the word and sentence inference algorithms on TrueNorth, as well.

Lawrence Livermore National Lab (LLNL) has a 16-chip NS16e scale-up system to explore the potential of post-von Neumann computation through larger neural models and more complex algorithms, enabled by the native tiling characteristics of the TrueNorth chip. For the Supercomputing paper, they contributed a single-chip application performing in-situ process monitoring in an additive manufacturing process. LLNL trained a TrueNorth network to recognize seven classes related to track weld quality in welds produced by a selective laser melting machine. Real-time weld quality determination allows for closed-loop process improvement and immediate rejection of defective parts. This is one of several applications LLNL is developing to showcase TrueNorth as a scalable platform for low-power, real-time inference.

[downloaded from https://www.ibm.com/blogs/research/2016/12/the-brains-architecture-efficiency-on-a-chip/] Courtesy: IBM

I gather this 2017 announcement is the latest milestone on the TrueNorth journey.

Understanding how carbon nanotubes grow and self-organize is key to better production

This research may help to commercialize use of carbon nanotubes (CNTs), a  ‘magical’ nanoscale material with great promise and great difficulties (standardizing production being one of the main difficulties). A Feb. 10, 2017 news item on phys.org describes how researchers at the Lawrence Livermore National Laboratory (LLNL) and other collaborators have recorded carbon nanotubes self-organizing,

For the first time, Lawrence Livermore National Laboratory scientists and collaborators have captured a movie of how large populations of carbon nanotubes grow and align themselves.

Understanding how carbon nanotubes (CNT) nucleate, grow and self-organize to form macroscale materials is critical for application-oriented design of next-generation supercapacitors, electronic interconnects, separation membranes and advanced yarns and fabrics.

A Feb. 9, 2017 LLNL news release, which originated the news item, provides more information about the research (Note: Links have been removed),

New research by LLNL scientist Eric Meshot and colleagues from Brookhaven National Laboratory (link is external) (BNL) and Massachusetts Institute of Technology (link is external) (MIT) has demonstrated direct visualization of collective nucleation and self-organization of aligned carbon nanotube films inside of an environmental transmission electron microscope (ETEM).

In a pair of studies reported in recent issues of Chemistry of Materials (link is external) and ACS Nano (link is external), the researchers leveraged a state-of-the-art kilohertz camera in an aberration-correction ETEM at BNL to capture the inherently rapid processes that govern the growth of these exciting nanostructures.

Among other phenomena discovered, the researchers are the first to provide direct proof of how mechanical competition among neighboring carbon nanotubes can simultaneously promote self-alignment while also frustrating and limiting growth.

“This knowledge may enable new pathways toward mitigating self-termination and promoting growth of ultra-dense and aligned carbon nanotube materials, which would directly impact several application spaces, some of which are being pursued here at the Laboratory,” Meshot said.

Meshot has led the CNT synthesis development at LLNL for several projects, including those supported by the Laboratory Directed Research and Development (LDRD) program and the Defense Threat Reduction Agency (link is external) (DTRA) that use CNTs as fluidic nanochannels for applications ranging from single-molecule detection to macroscale membranes for breathable and protective garments.

Here’s a link to and a citation for the both of the papers mentioned in the news release,

Measurement of the Dewetting, Nucleation, and Deactivation Kinetics of Carbon Nanotube Population Growth by Environmental Transmission Electron Microscopy by Mostafa Bedewy, B. Viswanath, Eric R. Meshot, Dmitri N. Zakharov, Eric A. Stach, and A. John Hart. Chem. Mater., 2016, 28 (11), pp 3804–3813 DOI: 10.1021/acs.chemmater.6b00798 Publication Date (Web): May 23, 2016

Copyright © 2016 American Chemical Society

Real-Time Imaging of Self-Organization and Mechanical Competition in Carbon Nanotube Forest Growth by Viswanath Balakrishnan, Mostafa Bedewy, Eric R. Meshot, Sebastian W. Pattinson, Erik S. Polsen, Fabrice Laye, Dmitri N. Zakharov, Eric A. Stach, and A. John Hart. ACS Nano, 2016, 10 (12), pp 11496–11504 DOI: 10.1021/acsnano.6b07251 Publication Date (Web): November 23, 2016

Copyright © 2016 American Chemical Society

Both papers are behind a paywall.

The researchers have also provided this image which allows you to appreciate the difference between a ‘scientific’ version of the work and an artistic version,

This transmission electron microscope image shows growth of a dense carbon nanotube population. Courtesy: LLNL

New elements named (provisionally)

They say it’s provisionally but I suspect it would take an act of god for a change in the proposed names. From a June 8, 2016 blog posting (scroll down about 25% of the way) on the International Union of Pure and Applied Chemistry (IUPAC) website,

IUPAC is naming the four new elements nihonium, moscovium, tennessine, and oganesson

Following earlier reports that the claims for discovery of these elements have been fulfilled [1, 2], the discoverers have been invited to propose names and the following are now disclosed for public review:

  • Nihonium and symbol Nh, for the element 113,
  • Moscovium and symbol Mc, for the element 115,
  • Tennessine and symbol Ts, for the element 117, and
  • Oganesson and symbol Og, for the element 118.

The IUPAC Inorganic Chemistry Division has reviewed and considered these proposals and recommends these for acceptance. A five-month public review is now set, expiring 8 November 2016, prior to the formal approval by the IUPAC Council.

I can’t figure out how someone from the public might offer a comment about the names.

There’s more from the posting about what kinds of names are acceptable and how the names in this set of four were arrived at,

The guidelines for the naming the elements were recently revised [3] and shared with the discoverers to assist in their proposals. Keeping with tradition, newly discovered elements can be named after:
(a) a mythological concept or character (including an astronomical object),
(b) a mineral or similar substance,
(c) a place, or geographical region,
(d) a property of the element, or
(e) a scientist.
The names of all new elements in general would have an ending that reflects and maintains historical and chemical consistency. This would be in general “-ium” for elements belonging to groups 1-16, “-ine” for elements of group 17 and “-on” for elements of group 18. Finally, the names for new chemical elements in English should allow proper translation into other major languages.

For the element with atomic number 113 the discoverers at RIKEN Nishina Center for Accelerator-Based Science (Japan) proposed the name nihonium and the symbol Nh. Nihon is one of the two ways to say “Japan” in Japanese, and literally mean “the Land of Rising Sun”. The name is proposed to make a direct connection to the nation where the element was discovered. Element 113 is the first element to have been discovered in an Asian country. While presenting this proposal, the team headed by Professor Kosuke Morita pays homage to the trailblazing work by Masataka Ogawa done in 1908 surrounding the discovery of element 43. The team also hopes that pride and faith in science will displace the lost trust of those who suffered from the 2011 Fukushima nuclear disaster.

For the element with atomic number 115 the name proposed is moscovium with the symbol Mc and for element with atomic number 117, the name proposed is tennessine with the symbol Ts. These are in line with tradition honoring a place or geographical region and are proposed jointly by the discoverers at the Joint Institute for Nuclear Research, Dubna (Russia), Oak Ridge National Laboratory (USA), Vanderbilt University (USA) and Lawrence Livermore National Laboratory (USA).

Moscovium is in recognition of the Moscow region and honors the ancient Russian land that is the home of the Joint Institute for Nuclear Research, where the discovery experiments were conducted using the Dubna Gas-Filled Recoil Separator in combination with the heavy ion accelerator capabilities of the Flerov Laboratory of Nuclear Reactions.

Tennessine is in recognition of the contribution of the Tennessee region, including Oak Ridge National Laboratory, Vanderbilt University, and the University of Tennessee at Knoxville, to superheavy element research, including the production and chemical separation of unique actinide target materials for superheavy element synthesis at ORNL’s High Flux Isotope Reactor (HFIR) and Radiochemical Engineering Development Center (REDC).

For the element with atomic number 118 the collaborating teams of discoverers at the Joint Institute for Nuclear Research, Dubna (Russia) and Lawrence Livermore National Laboratory (USA) proposed the name oganesson and symbol Og. The proposal is in line with the tradition of honoring a scientist and recognizes Professor Yuri Oganessian (born 1933) for his pioneering contributions to transactinoid elements research. His many achievements include the discovery of superheavy elements and significant advances in the nuclear physics of superheavy nuclei including experimental evidence for the “island of stability”.

“It is a pleasure to see that specific places and names (country, state, city, and scientist) related to the new elements is recognized in these four names. Although these choices may perhaps be viewed by some as slightly self-indulgent, the names are completely in accordance with IUPAC rules”, commented Jan Reedijk, who corresponded with the various laboratories and invited the discoverers to make proposals. “In fact, I see it as thrilling to recognize that international collaborations were at the core of these discoveries and that these new names also make the discoveries somewhat tangible.”

So, let’s welcome Tennessine, Muscovium, Nihonium, and Oganesson to the table of periodic elements. I imagine Don Lehrer’s Elements Song will be updated soon. In the meantime we have this from ASAP Science, which includes the new elements under their placeholder names (when the addition was first publicized in January 2016. All of the placeholder names start with U,


Carbon nanotubes transport protons faster than bulk water

An April 4, 2016 news item on Science Daily focuses on carbon nanotubes that measure eight-tenths of a nanometre and transport protons more quickly than bulk water by an order of magnitude,

For the first time, Lawrence Livermore National Laboratory (LLNL) researchers have shown that carbon nanotubes as small as eight-tenths of a nanometer in diameter can transport protons faster than bulk water, by an order of magnitude.

The research validates a 200-year old mechanism of proton transport.

A US Department of Energy Lawrence Livermore National Laboratory (LLNL) news release on EurekAlert, which originated the news item, provides more explanation,

The transport rates in these nanotube pores, which form one-dimensional water wires, also exceed those of biological channels and man-made proton conductors, making carbon nanotubes the fastest known proton conductor. …

Practical applications include proton exchange membranes, proton-based signaling in biological systems and the emerging field of proton bioelectronics (protonics).

“The cool thing about our results is that we found that when you squeeze water into the nanotube, protons move through that water even faster than through normal (bulk) water,” said Aleksandr Noy, an LLNL biophysicist and a lead author of the paper. (Bulk water is similar to what you would find in a cup of water that is much bigger than the size of a single water molecule).

The idea that protons travel fast in solutions by hopping along chains of hydrogen-bonded water molecules dates back 200 years to the work of Theodore von Grotthuss and still remains the foundation of the scientific understanding of proton transport. In the new research, LLNL researchers used carbon nanotube pores to line up water molecules into perfect one-dimensional chains and showed that they allow proton transport rates to approach the ultimate limits for the Grotthuss transport mechanism.

“The possibility to achieve fast proton transport by changing the degree of water confinement is exciting,” Noy said. “So far, the man-made proton conductors, such as polymer Nafion, use a different principle to enhance the proton transport. We have mimicked the way biological systems enhance the proton transport, took it to the extreme, and now our system realizes the ultimate limit of proton conductivity in a nanopore.”

Of all man-made materials, the narrow hydrophobic inner pores of carbon nanotubes (CNT) hold the most promise to deliver the level of confinement and weak interactions with water molecules that facilitate the formation of one-dimensional hydrogen-bonded water chains that enhance proton transport.

Earlier molecular dynamic simulations showed that water in 0.8 nm diameter carbon nanotubes would create such water wires and predicted that these channels would exhibit proton transport rates that would be much faster than those of bulk water. Ramya Tunuguntla, an LLNL postdoctoral researcher and the first author on the paper, said that despite significant efforts in carbon nanotube transport studies, these predictions proved to be hard to validate, mainly because of the difficulties in creating sub-1-nm diameter CNT pores.

However, the Lawrence Livermore team along with colleagues from the Lawrence Berkeley National Lab and UC Berkeley was able to create a simple and versatile experimental system for studying transport in ultra-narrow CNT pores. They used carbon nanotube porins (CNTPs), a technology they developed earlier at LLNL, which uses carbon nanotubes embedded in the lipid membrane to mimic biological ion channel functionality. The key breakthrough was the creation of nanotube porins with a diameter of less than 1 nm, which allowed researchers for the first time to achieve true one-dimensional water confinement.

Here’s a link to and a citation for the paper,

Ultrafast proton transport in sub-1-nm diameter carbon nanotube porins by Ramya H. Tunuguntla, Frances I. Allen, Kyunghoon Kim, Allison Belliveau, & Aleksandr Noy. Nature Nanotechnology (2016) doi:10.1038/nnano.2016.43 Published online 04 April 2016

This paper is behind a paywall.