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X-ray topography diffraction measurement device set up for measuring battery discharge rates

The Future of Energy Technology as Seen Through X-Ray Eyes

“Batteries are complicated.” This was the unrehearsed refrain I heard repeatedly from Mike Toney and the researchers who make up the Toney research team at the Stanford Synchrotron Radiation Lightsource (SSRL), part of the SLAC National Accelerator Laboratory in Menlo Park, Calif.

During a visit to to their laboratories, I learned that not only are the complex inner workings of batteries being revealed by the assortment of X-ray microscopy tools used at SSRL, but that the latest innovations in photovoltaics are being examined and characterized with the aim of making sure that both energy storage and energy generation technologies can meet the demands of future generations.

“Characterization is perhaps an underappreciated term,” explains Toney. His take on it?

I see it as more that we’re involved in characterization directed at understanding how things work, or how they're put together. One example of this is batteries, which are presently a quite popular topic. We’re involved in understanding how the lithium ions shuttle back and forth between the anode and cathode and the resulting changes on a very small level. Right now, we are looking at an atom-sized level and how those changes make an impact on the nanoscale level and then eventually understanding how that leads to changes on the electrode level that lead to failure.

While Toney’s team does spend some time working in collaboration with other groups at Stanford—such as the researchers at Yi Cui lab at Stanford Institute for Materials and Energy Sciences—another big part of their research is working with commercial battery and photovoltaics manufacturers who need to know how their devices work on the atomic scale. These measurements are often only possible with the X-rays that are produced when high-energy electrons speed around the synchrotron at SLAC.

Toney calls this work “foundational science research” and involves determining the scientific underpinnings of how batteries and photovoltaics work. This kind of work can take the form of looking at a nanostructure electrode, mixed together with a bunch of carbon in an electrolyte and then reducing that down to a single crystal.

While this structure is not a realistic battery geometry, it does make it possible to simulate a realistic environment in which lithium would move in and out of the nanostructured electrode and reaction layers would form. Combining it with highly sensitive X-ray probes makes it possible to acquire detailed information on how the battery would operate in a real-world conditions. This makes it possible to determine what kinds of charging protocols or chemistries in the electrolyte can be used to basically encapsulate—or passivate—the surface. 

Chris Takacs, a post-doc research fellow at SLAC who is a member of Toney’s team, has been testing one company’s batteries using one of these small battery packages and the X-rays from SLAC’s synchrotron. Takacs has devised a special measurement technique using X-ray topography diffraction that he has dubbed depth-resolved X-ray diffraction.

You can see Takacs describe his measurement arrangement in the video below.

“We’re trying to understand how Li-ion concentration gradients build up on commercial battery cells as you charge and discharge them fast,” says Takacs. “We are trying to uncover the limits in these types of performances. So, right now we're just looking at the cathode. We're trying to understand if there is an enrichment of the lithium ions near the separator or near the current collector when you’re charging very quickly. This is considered one of the major limitations for the rate at which you charge.”

One of the most promising materials for improving the charge life of Li-ion batteries has been nanostructured silicon.  Silicon has been discovered to improve the charge capacity of anodes (negative electrodes) in lithium-ion batteries by as much as ten times over standard graphite-based anodes. Unfortunately, silicon anodes crack and become unusable after a few charge/discharge cycles. This occurs because the material swells and shrinks as the ions shuttle back and forth. It has been hoped that nanostructuring the silicon can reduce or eliminate this rapid cracking. Toney and his team are looking at this problem and others assocated with silicon in batteries.

“One of the problems with silicon is you grow this all-electrolyte interface right at the surface of the silicon that consumes the electrolyte and consumes lithium,” says Toney. “If that grows uncontrollably, all the lithium ends up there and not in silicon where you want it. So we want a passivating layer there that is compliant in the sense that it can stretch. And so we’re in the process of providing some knowledge to guide people and get other researchers to think about what additives we want to add to electrolyte to kind of tune the properties of this layer.”

While polymers have been used as a passivating layer, Toney says that you can also tune the reactions that form to serve as an extremely effective passivating layer.

A great example of this is not in the battery space, but in stainless steel manufacturing, where the the alloying elements are designed to create a passive film on the surface that basically prevents the stainless steel from corroding and gives long life, according to Toney. “This passivating layer has allowed stainless steel to be used ubiquitously in our society,” he adds.

The Li-ion battery has achieved the same ubiquity. As a result, battery research has continued to take on an ever greater share of Toney’s research. He marks the beginning of this surge in battery research with the introduction of the Tesla all-electric vehicles.

“If you had asked me 10 years ago if electric vehicles were possible at a reasonable price, I think I probably wouldn't have believed it,” says Toney. “But once you start to see the first of the Teslas that came out, you start to realize these are real.  And that is kind of about the same time that I think a lot of people start to get interested in battery technology.”

The Li-ion batteries that are currently used in Tesla cars still have some room for improvement, according to Toney. But those improvements will likely remain incremental.

“Over the next few years, we we will continue to see the same incremental five- to 10-percent per year advancements in terms of capacities,” says Toney.  “The costs actually have been going down much faster than that. So I would expect that some of those will continue over the next few years, but at some point—at least from the cost perspective—you’re going to hit a limit. There are some predictions that this will happen in two or three years. You really can’t get a battery much cheaper with the current chemistries.”

Alternative chemistries to the current dominant Li-ion battery is another line of research that has taken on increasing importance. Most notable among these is lithium-metal batteries. Johanna Nelson Weker, a staff scientist at SSRL, has been examining these chemistries with the aid of a transmission X-ray microscope.

With this device, Weker essentially takes images of anodes in lithium-metal batteries in situ across a 30-micron field of view and is able to get resolutions down to 30 nanometers.

“We can either look at how their chemistry is changing or how their morphology is changing in 3D,” says Weker. “So 3D imaging is very much like a computerized tomography (CT) scan. We rotate our sample, take images at many different angles, put them into an algorithm, and out comes a 3D image.”

In what is essentially spectral micrscopy, the researchers are to see what all the elements in the battery are doing spatially while it’s cycling. “For example, it will show you whether your lithium is going into your cathode in the core-shell manner—from the outside in—or is it going to smaller particles first and ignoring the large particles. Or it will show you whether every particle just transforming simultaneously together both in both large and small particles,” explains Weker.

In the video below, you can see Weker describe what they discovered when looking at how these particles lithiate in a lithium-metal battery sample.

Weker’s work has revealed that a long held assumption about how these particles lithiate was wrong. The core shell of these particles does not always lithiate.

“What we found with lithium-iron phosphate is it doesn't act that way,” she explains. “In the nanoparticles, there's a preferential direction depending not only on the crystalline lattice planes, but also basically one particle will start to lithiate. And all the neighboring particles will not and they actually donate their lithium to that particle so the lithiation occurs one particle at a time.”

Not all the members of Toney’s teams are using X-rays for examining energy storage technologies. Some are looking at the cutting edge materials used in photovoltaics, such as halide perovskites.

Aryeh (Ari) Gold-Parker, a PhD student at Stanford working with Toney’s team, is employing an X-ray absorption spectroscopy technique to identify certain elements that are in the sample and identify the relative quantities of those elements in order to understand something about the chemical environment in which the atoms of those elements reside.

The starting material for halide perovskites involves quite a bit of chlorine in addition to iodine, but it's widely understood that once you’ve fully prepared the film by heating it, almost all of the chlorine is gone. So what you're left with is primarily iodine. What Gold-Parker did was to prepare the film while heating it and keep it on the X-ray beam line.

This arrangement allowed him to monitor the chlorine leaving the film as it was being heated and also discover the fact that the chlorine atoms in the film were going from one local environment to another throughout the heating process. Gold-Parker believes that this will prove extremely useful for trying to understand how these perovskite films form and might eventually help to optimize the actual solar cell performance.

“At the end of the day, the real hope is to make high-efficiency devices,” says Gold-Parker. “There are a lot of engineers who are fine with all these different chemical compositions for this material system, just swapping in all different elements and molecules in the different sites trying to achieve the highest efficiency. But the field has gotten way ahead of the basic science. So the engineers might be two or three years ahead of the actual understanding of why these atoms are making a difference.”

This is what Toney might describe with his term “foundational science research”. Instead of hit-and-miss iterative processes, Toney and his team are trying to uncover the fundamental chemistry and physics that make our next-generation energy storage and generation systems operate. This will likely make them better in just about every performance metric and also make them cheaper to produce.

Four of the nanofabricated silica chips that enable the "Accelerator-on-a-Chip" technology

Nanofabrication Enables "Particle-Accelerator-on-a-Chip" Technology

About 15 months ago, The Gordon and Betty Moore Foundation awarded US $13.5 million to a five-year project involving an international collection of universities and national labs to start work on shrinking particle accelerators so that they could fit on a chip. The project, dubbed “Accelerator on a Chip” could have a profound impact on both fundamental science research and medicine.

In a nutshell, the aim is to use lasers and a piece of nanostructured silicon or glass about the size of a grain of rice to accelerate electrons at a rate up to 30 times higher than typical values for conventional technology. The resulting technology could potentially match the power of SLAC's 3.2-kilometer-long linear accelerator in as little as 100 meters.

In a visit to the offices of Joel England, a fellow at the Advanced Accelerator Research Department at SLAC and one of the leaders of the Accelerator-on-a-Chip project, we got some insights into the science and technology involved  and how it is proceeding.

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Stanford researcher Hao Yan presents models of the diamondoid molecule

Diamondoids on Verge of Key Application Breakthroughs

Ever since Jeremy Dahl of Stanford University first isolated the molecules known as “diamondoids” from crude oil in 2003,  the material science community has been fascinated with their potential. Diamondoids, which are both the smallest and purest form of diamond, have a unique set of properties that have led scientists to consider their use in applications including quantum computation and enabling so-called diamondoid mechanosynthesis (DMS), in which diamondoid structures are built using a programmable molecular positioning approach.

While DMS may still be a long ways off, researchers at Stanford and the U.S. Department of Energy’s SLAC National Accelerator Laboratory in Menlo Park are continuing to experiment with the material. They have developed more short-term applications for the molecule, while still keeping their eyes on the horizon for its long-term potential.

Hao Yan, a postdoc with the Melosh Research Group at the Stanford Institute for Materials and Energy Sciences (SIMES), reported late last year in the journal Nature Materials that diamondoids could help control the self-assembly of nanowires, promising a kind of template for creating a variety of materials with unique properties.

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An image of the inside of Intel's D1X research fab in Hillsboro, Oregon

Intel Now Packs 100 Million Transistors in Each Square Millimeter

I’ll admit it: journalists like milestones. Nice round numbers and anniversaries make for good headlines. So my ears certainly perked up on Tuesday when Intel said that it can now pack more than 100 million transistors in each square millimeter of chip “for the first time in our industry’s history,” said Kaizad Mistry, a vice president and co-director of logic technology at the company. Delivering more transistors in the same area means the circuitry can be made smaller, saving on cost, or it means that more functionality can be added to a chip without having to make it bigger. 

The news came during Intel’s Technology and Manufacturing Day, a behind-the-scenes look at the company’s latest chip classes and packaging technology, and another opportunity for the chipmaker to declare that Moore’s Law is alive and well—at least for Intel. 

The nice round 100 million milestone (100.8 million, to be exact) belongs to Intel’s latest-and-greatest chip generation: 10 nanometers. For those uninitiated in semiconductor lingo, the 10 nm designation is a reference to the “node” or manufacturing technology used to make such chips. As a general rule, the smaller the number, the denser the circuitry. But even though node names look like measurements, today the numbers don’t really correspond to the size of any particular feature and there can be significant variation between companies.

When I wrote about Intel’s 10-nm plans in our January issue previewing the coming year in technology, the company was not yet ready to say much publicly about the specific dimensions of the transistors. This week, they were more forthcoming with figures [pdf]: it’s 34 nm from one fin to the next in the company’s FinFET transistors and 36 nm from one wire to the next in the most dense interconnect layers (down from 42 nm and 52 nm, respectively, in the previous, 14-nm chip generation).

Shorter distances such as these mean that 10nm chips can pack significantly more transistors in a given area. The 100 million density figure comes from a metric that Intel senior fellow Mark Bohr has proposed the industry resurrect, in order to better compare chipmaker offerings. Instead of measuring a chip manufacturing generation by an area taken up by a certain component or set of components, Bohr proposes that we instead measure chip generations by their transistor density—in particular, by the number spit out by an equation that combines the transistor density in a standard 2-input NAND cell and a scan flip-flop logic cell. 

And by that metric, Bohr says, Intel has more than doubled its transistor density in recent years. From 22nm to 14nm, the transistor density jumped by a factor of 2.5x. And in the move from 14-nm to 10-nm chip manufacturing technology, the jump was 2.7x, from 37.5 million transistors per square millimeter to more than 100 million. Crucially, the company says, the 10-nm transistors have the capacity for higher speed and greater energy efficiency than their predecessors (although, when I spoke with Bohr late last year, he said the focus lately has been on the latter). 

It remains to be seen whether the industry will agree that the new metric is a meaningful one. In comments to EE Times, one analyst said transistor count over a larger area, closer to the size of a real chip, would be a more relevant metric. And an unnamed spokesperson from rival chipmaker TSMC told the site: “I have no idea how Intel does its new calculation...for example, its [first-generation 14nm CPU] Broadwell used to have 18.4 million transistors per mm squared, yet under the new measure it suddenly has 37.5 million transistors per mm2. Are they trying to play paper games?”

Not so fast, says Intel. After this story originally posted, a company representative wrote to IEEE Spectrum to stress the difference between talking about a chip’s transistor density and this metric, which is designed to assess the capabilities of a manufacturing node. “Simply taking the total transistor count of a chip and dividing by its area is not meaningful because of the large number of design decisions that can affect it–factors such as cache sizes and performance targets can cause great variations in this value,” Bohr wrote in his proposal, titled “Let’s Clear Up the Node Naming Mess.”

Even if there is room to quibble over that specific 100 million figure, Intel is also saying that it is more than doubling transistor density with each new chip generation—and that this more aggressive level of miniaturization helps to counteract the slower cadence that has recently set in with respect to the introduction of each new generation. On balance, Intel said, the company is still on a pace that roughly corresponds to a doubling of transistor density every couple of years.

Intel calls the suite of strategies it uses to accomplish this more-than-doubling “hyperscaling.” It includes design improvements, but a big piece is the company’s approach to laying down the patterns that ultimately become the chip’s transistors and wiring, which Intel fellow Ruth Brain outlined in her talk [pdf]. 

With its 14-nm chips, Brain said, Intel began using a strategy called self-aligned double patterning (SADP). SADP is a form of multiple patterning, a range of strategies that can be used to make chip features much smaller than the 193-nm light that is used to print them by splitting the patterning process into multiple steps.

Other companies, Brain said, use a simple multiple patterning approach that essentially prints the same pattern multiple times, offset slightly. But that technique relies on a lithography machine’s ability to pinpoint the same spot for each exposure, and variability in this process can degrade chip performance and lower the number of usable chips produced. SADP splits up the patterning in a different way, to sidestep this “overlay” issue.

With 10-nm chips, Intel as adopted self-aligned quadruple patterning (SAQP), a similar approach that requires four passes through a lithography machine. Mistry says SAQP has one more generation in it, which would take Intel down to the feature sizes needed to produce the next generation: 7 nm. 

Somewhere in there, we may just see extreme ultraviolet (EUV) lithography enter the picture. EUV uses 13.5-nm radiation (pretty much X-rays) instead of 193-nm ultraviolet light for feature patterning.

But back to the present and that 100 million transistors per square millimeter figure. It’s easy to underplay the engineering feats that go into making that sort of milestone (assuming it stands the test of time) possible. “You know one of the remarkable things about Moore’s Law is that Moore’s Law’s past seems preordained and ordinary, and Moore’s Law’s future is difficult and requires inventions,” Mistry told IEEE Spectrum. 

Now, he says, the FinFET transistor seems par for the course, but it wasn’t when Intel introduced the technology in 2011. “All these things are difficult, but once they’re done they seem normal,” he adds. “And that’s the magic of Moore’s Law.”

This article was updated on 31 March to add a response from Intel to the comments from TSMC and to correct a caption.

Chong Liu of Stanford University

Nanostructures Move From Water Purification to Uranium Extraction

Last August, we reported on work out of the U.S. Department of Energy’s SLAC National Accelerator Laboratory and Stanford University in which the nanomaterial molybdenum disulfide was used to kill 99.999 percent of bacteria in water within just 20 minutes—a process that would otherwise take up to two days if only the ultraviolet (UV) light from the sun were used as a disinfectant.

In a meeting last week with Chong Liu, the post-doc in Yi Cui’s lab at Stanford who was the lead author of that research, it appears water purification is just the start for the capabilities of this line of research that has had a number of incarnations.

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In a proof-of concept experiment the researchers attached a CS-FET chip with H2 sensors to a drone, creating an aerial chemical sensing probe.

Nanochip Gas Sensors Promise Personal Air Quality Monitors in Our Pockets

An international team of researchers has developed a low-power gas sensor chip that can operate at room temperature, making possible the development of personal air-quality monitoring devices that we could carry around with us.

In research described in the journal Science Advances, the team of researchers fabricated a chemical-sensitive field-effect transistor (CS-FET) platform based on 3.5-nanometer-thin silicon channel transistors. The platform, which is highly sensitive but consumes a small amount of power, can detect a wide range of different gases.

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Solution of quantum dots glows bright red when in absorbs light from a UV lamp underneath.

Flying Saucer Quantum Dots: The Secret to Better, Brighter Lasers

Ted Sargent and his team at the University of Toronto have done many things with quantum dots: boost solar cell efficiency, invent infrared imagers, optoelectronics you can apply with a paint brush. Now Sargent and his team have added a new spice to their recipe for colloidal quantum dots that promises to change the struggling prospects of quantum dot-based lasers. If the new approach lives up to its promise, it could lead to brighter, less expensive, and tunable lasers for video projectors and medical imaging among other applications.

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A reconstruction of the wiring and transistors of an Intel G3260 processor

X-rays Map the 3D Interior of Integrated Circuits

A team of researchers based in Switzerland is on the way to laying bare much of the secret technology inside commercial processors. They pointed a beam of X-rays at a piece of an Intel processor and were able to reconstruct the chip’s warren of transistors and wiring in three dimensions. In the future, the team says, this imaging technique could be extended to create high-resolution, large-scale images of the interiors of chips. 

The technique is a significant departure from the way the chip industry currently looks inside finished chips, in order to reverse engineer them or check that their own intellectual property hasn’t been misused. Today, reverse engineering outfits progressively remove layers of a processor and take electron microscope images of one small patch of the chip at a time.

But “all it takes is a few more years of this kind of work, and you'll pop in your chip and out comes the schematic,” says Anthony Levi of the University of Southern California. “Total transparency in chip manufacturing is on the horizon. This is going to force a rethink of what computing is”, he says, and what it means for a company to add value in the computing industry.

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Symbolic image of light interacting with a gold surface with 4-fold symmetric Archimedean spirals: Plasmons with orbital angular momentum are excited and swirl towards the center.

Combining Twisted Light and Plasmons Could Supercharge Data Storage

Research that started out with the humble aim of growing an atomically flat, single crystalline gold surface, ultimately morphed into a team of German and Israeli scientists using the gold surface they came up with for a novel form of data storage.

In research published in the journal Science, a team of scientists from Technion-Israel Institute of Technology and the German universities of Stuttgart, Duisburg-Essen, and Kaiserslautern and the University of Dublin in Ireland has developed a way to exploit the orbital angular momentum of light in a confined device using plasmonics.

Prior to this work, some scientists suggested using the orbital angular momentum of photons as a means for data storage in the open air or in optical fibers. This latest research makes it possible to envision it being used in confined, chip-scale devices.

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Molecules self assembling

The Nobelists and Their Molecular Machines

While the prospects of molecular nanotechnology—the catch-all term for molecular manufacturing in which nanoscale machines are programmed to build macroscale objects from the bottom up—has remained mostly in the realm of science fiction, the awarding of last year’s Nobel Prize in chemistry to a trio of scientists who pioneered the development of nanomachines has buoyed hope that at least we should begin to see more research in the field.

More of this research is already trickling in since the Nobel Prize announcement. Two teams of researchers from the University of Santiago de Compostela (USC) in Spain have cited this most recent Nobel Prize as a context for their work in developing self-assembling materials based on peptides (compounds consisting of two or more amino acids linked together in a chain) that can stack themselves on top of each other to form nanotubes.

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Nanoclast

IEEE Spectrum’s nanotechnology blog, featuring news and analysis about the development, applications, and future of science and technology at the nanoscale.

 
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Dexter Johnson
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