The NSRCs hold joint workshops to share research and user projects that are ongoing at the five centers. These exchanges of information have provided the staff at the NSRCs with the opportunity to learn about topics/thrusts in nanoscience at the other nanocenters and to develop an understanding of the different areas of expertise among the staff members. They have also facilitated discussions towards possible future areas of collaboration between the centers and provided basic information so that potential NSRC users can be directed toward the optimal center and staff to meet their research needs.
Upton, NY 21-May-2018 – 23-May-2018
CINT - 2018 User Meeting
Santa Fe, NM 24-Sep-2018 – 26-Sep-2018
CNMS - 2018 User Meeting
Oak Ridge, TN 13-Aug-2018 – 15-Aug-2018
CNM - 2018 User Meeting
Argonne, IL 7-May-2018 – 10-May-2018
The Foundry - 2018 User Meeting
Berkeley, CA 15-Aug-2018 – 16-Aug-2018
A team of scientists from CFN, Peking University, and Soochow University designed and characterized a new fuel cell catalyst — a platinum-lead core/shell structure, shaped as a nanoplate. The catalyst shape and chemical composition dramatically enhances the oxygen evolution reaction — important for fuel cell performance — while providing stability during operation.
Femtosecond laser etching is fast enough that the material vaporizes material rather than melting or burning it. Consequently, cuts made with this laser are cleaner than other nanosecond lasers that may leave ragged edges or cause material scarring. The image demonstrates this capability by etching the CINT logo onto a human hair.
This etching enables highly accurate study of microfluidic processes in a variety of materials. At Los Alamos National Lab, rock samples are etched with the femtosecond laser to create a microfluidic device specific to the rock of interest and liquids within these devices are tested under conditions of extreme heat and pressure. Accordingly, earth scientists are able to study the movement of fluids through rock similar to deep earth conditions. It would be very difficult to study these exact conditions in the natural system.
The precise cuts made by a femtosecond laser provide enhanced precision in applications such as microfluidics. Lasers with longer exposure burn the substrate and may cause scarring, but the ultrashort pulses from the femtosecond laser vaporize the unwanted material to create etching while causing very little heat transfer to the remaining material. Further, this laser is able to etch into a wider variety of materials than previous lasers and thus provides a wider range of possible applications.
Foundry industry users developed a multinozzle emitter array (MEA), a silicon chip that can dramatically shorten the time it takes to identify proteins, peptides, and other molecular components within small volumes of biological samples. This patented technology is now being commercialized by Newomics Inc., to further develop the product and build a platform for personalized health care. Some of the early work on multinozzle emitters was done at the Molecular Foundry.
Newomics’ product, which is based on the core technology developed at Berkeley Lab, is designed to work with mass spectrometers, a machine commonly used by research scientists, the pharmaceutical industry, and increasingly in clinical labs, to measure the structure and concentration of molecules. Once molecular parts are isolated, scientists can begin to understand how they work together as a system, a field known as systems biology, which holds great promise for better medicines and diagnostics as well as a host of other applications.
The dominant method for analyzing biological molecules such as peptides and proteins in a complex mixture is electrospray ionization mass spectrometry (ESI-MS), a technique in which molecular samples are delivered to the machine as an ionized mist, propelled by an electric current. But there is a bottleneck at the front end of ESI-MS, making it slow and expensive. Each sample has to be loaded, lined up, and sprayed one at a time.
Instead of a single capillary, Newomics’ M3 emitter has eight or more nozzles working together to split a single large flow into smaller flows. For the MEA, up to 96 M3 emitters are packaged on a single chip. The development of these technologies involved a blend of microfluidic, microelectronic, and electrochemical innovations.
By clearing up the bottleneck and increasing throughput, Newomics’ emitter could dramatically reduce the cost of testing each sample. And by improving the sensitivity, it will also be possible to detect very low concentrations of molecules. For example, they showed they could analyze many different modified forms of proteins such as glycated albumin and apolipoproteins, in addition to the conventional glucose and HbA1c in diabetes monitoring, using a single drop of blood. Such tests have the potential to enable better long-term monitoring and disease management of diabetes.
Highly stable single photon emission (SPE) from sp3 defect sites introduced to carbon nanotubes (CNT) via chemical functionalization. Wavelength tunable quantum light emission is enabled by varying CNT diameters. Room-temperature SPE achieved for first time at 1550 nm telecom band at the largest diameters.
First known material to act as a single photon emitter at telecom wavelengths and at room temperature. Critical advance for quantum light source applications in quantum information processing and metrology.
What is the scientific achievement?
We have fabricated highly-porous, highly-uniform silicon nitride membranes by replicating features from self-assembled block copolymer films. With porosities over 30% and thickness <100 nm, the membranes are designed for high throughput. Pore sizes are controllably tuned to molecular scales, for selective gas permeation. Capillary condensation within nanoscale pores enhances selectivity beyond that expected from molecule size differences.
Why does this achievement matter?
Membranes underlie integral separation processes in energy production, water purification, medicine, environmental cleanup, and chemical processing. These highly-uniform, highly-porous inorganic membranes may provide durability for high temperature operation in extreme environments.
What is the scientific achievement?
CFN users from Rutgers University worked with CFN staff to perform high-resolution, 3D imaging of metallic nanostructures by scanning transmission electron microscopy (STEM). The measured 3D structure of these ‘nanostars’ was used as input for finite element simulations of the material physical and optical properties, in remarkable agreement with experimental measurements.
Why does this achievement matter?
Nanomaterials can have enhanced optical properties stemming from plasmonic effects — giving them promise for advanced sensors and diagnostic applications. This study represents the first time that information from STEM tomography has been used to predict nanomaterial physical and optical properties.
At the Center for Integrated Nanotechnology (CINT), researchers discovered an efficient way to make combined solar panels and light-emitting devices. Rather than using blocks of hybrid perovskite materials, they layered several thin sheets on top of each other. In this new layered pattern, they discovered important “layer-edge states.” In these states, energy is highly conserved. When excited by light or other sources, the material produces energy that doesn’t instantly dissipate and can be used to charge batteries or do other work. That is, it creates long-lived, free charge carriers that can be harvested and manipulated.
Quasicrystals made of Penrose tilings are fascinating structural arrangements with small repeating units but without any overall pattern periodicity. They are mesmerizing, because the human eye seeks to find patterns that do not quite exist. In this work, the researchers observed that quasicrystals made of nanomagnets form magnetic states having both an ordered, rigid ‘skeleton’ spanning the entire network, and smaller domains with configurations that are switchable without energy cost.
Bistable magnetic elements can naturally represent bits of stored digital information, and interactions between elements can be used to perform logical operations. In magnetic quasicrystals, different groups of nanomagnets can play each role.
Although polymer self-assembly offers a cost-effective method for creating nanoscale patterns across wide areas, slow ordering kinetics typically result in self-assembled patterns that are riddled with defects. In this work, CFN scientists discovered that mixtures self-assembling block copolymers combined with small homopolymers can speed the process of nanoscale pattern formation by more than 10 times and improve their quality — providing a material for efficient, wide-area nanopatterning in a fraction of the time compared to block copolymers alone.
The dramatically improved pattern quality and reduced processing time afforded by these composite polymer blends enhances the practicality for using self-assembly in design of next-generation energy materials.
“Advanced Nanomaterials for Energy Conservation and Temperature Regulation”
The Federal Laboratory Consortium for Technology Transfer congratulates the winners of its 2018 Awards. A total of 30 awards will be presented to 24 laboratories representing 10 federal agencies. We thank our winners, and their competitors, for a great job in realizing the technology transfer potential within their laboratories.The awards will be presented on Wednesday, April 25, 2018 at the FLC National Meeting in Philadelphia, PA.
Atom-level deactivation processes in industrial zeolite catalysts are revealed in atom probe tomography (APT), which yields the first direct observations of chemical distributions. J. E. Schmidt, R. Oord, W. Guo, J. D. Poplawsky, B. M. Weckhuysen.
Nature Communications 8, 1666 (2017). DOI: 10.1038/s41467-017-01765-0
Nanotechnology researchers studying small bundles of carbon nanotubes have discovered an optical signature showing excitons bound to a single nanotube are accompanied by excitons tunneling across closely interacting nanotubes. That quantum tunneling action could impact energy distribution in carbon nanotube networks, with implications for light-emitting films and light harvesting applications. In the study, a collaborative research team from Los Alamos National Laboratory, the Center for Integrated Nanotechnologies and the National Institute of Standards and Technology showed that Raman spectroscopy (a form of light scattering) can provide more extensive characterization of intertube excitons. The team used chemical separations to isolate a sample of a single type of carbon nanotube structure. The nanotubes in these samples were then bundled to force interactions between individual nanotubes.
Nanoparticles of lithium metal formed on the surface of a solid state lithium ion electrolyte by an atomic force microscope. The particle size and height can be controlled by using carefully chosen voltage amplitude and sweep rates. The particles can be as small as 50 nanometers in diameter and a few nanometers high, and can potentially be used in lithium nanobatteries. A. Kumar, T.M. Arruda, A. Tselev, I.N. Ivanov, J.S. Lawton, T.A. Zawodzinski, O. Butyaev, X. Zayats, S. Jesse, and S.V. Kalinin, “Nanometer-scale mapping of irreversible electrochemical nucleation processes on solid Li-ion electrolytes.” Scientific Reports 3, 1621 (2013)
CFN scientists have created a general theoretical model that explains the observed wide diversity of periodic structures formed through nanoparticle self-assembly. The theory applies to a broad portfolio of experimental systems, across nanometer- and micron-length scales. The core interactions dictating the ultimate structure of the assembly are between two types of mutually attractive spherical particles.
A team of CFN users and staff showed that self-assembled, conical-shaped nanotextures expel condensing water droplets with an extremely high efficiency, rendering surfaces impervious to fog and outperforming textures with different shapes and sizes.
Creating materials with anti-fogging abilities requires more than simply endowing them with water-repellency. Here, we investigate the underlying mechanism by which the superhydrophobic properties of structured solids vanish upon exposure to fog. The degradation of water-repellency is characterized by enhanced adhesion of hot water drops to the colder textured surfaces, an effect we explain using a physical model of nucleation and growth of wet patches within textures located beneath the condensing drops. Our results demonstrate the importance of both the texture’s characteristic feature size and shape on its antifogging capacity – nanometer scale textures significantly outperforming micron-scale counterparts, and conical-shaped nanotextures providing an additional ability to expel condensing water with a high efficiency compared to cylindrical textures with the same lateral dimensions.
CFN scientists have reversibly trapped and released single argon atoms inside tiny cages made of silicon, aluminum and oxygen. The single-atom cages are formed in a flat zeolite crystal only 0.5 nanometers thick. The molecular permeability of the 2D zeolites is reversibly tuned by the presence of argon.
Ionic liquids — liquid salts made by combining positively charged cations and negatively-charged anions — have potential uses as advanced battery electrolytes. When the electrolytes contact an electrode, they form a ‘double-layer’ a few nm thick, where important electrochemical reactions take place. CFN scientists have created a technique to observe in real time how ions in the double-layer reconfigure under applied voltage bias.
Ionic liquids (IL) are salts that are liquid at around room temperature. They have a notable set of chemical and electrical properties, making them attractive for use in energy storage devices as electrolytes. A very high capacitance can be achieved when the IL comes into contact with electrified surfaces, giving rise to new possibilities for electrolyte-gated devices and supercapacitors. The structure of ILs at the liquid/solid interface formed between an IL electrolyte and an electrode in such devices is a crucial factor in determining their overall efficiency. This critical interface is confined in a region of nanometers in length and it is called an electric double layer (EDL). Although much work has been done to identify the exact structure of the EDL, acquiring information from a buried interface in real time as the structure is changing in response to applied voltage bias is no trivial task. To date, the data extracted from such buried interfaces typically represent the initial state and the final state of the EDL, rather than the process occurring in-between. In the present work a new strategy to probe the intermediate state in-situ and visualize the motion of ions in real time as a function of applied voltage is devised by utilizing photoemission electron microscopy (PEEM). In addition to the observation of the evolution of the structure of IL/electrode interface, it is also possible to probe both, working and counter electrodes at the same time. This capability enables the real-time observation of correlated responses and investigation of ion transport between the two electrified electrodes.
The operation of photonics technologies such as lasers and detectors relies on confining light within structured materials such as photonic crystals and metamaterials. In this work, the team demonstrates a new class of artificial optical media called a photonic hypercrystal, which simultaneously outputs light with high efficiency and across a broad range of wavelengths.
The team of scientists developed and implemented a ‘physics-aware’ algorithm to correct for missing information in experimental X-ray scattering datasets. Because the algorithm relies on well-understood physics of X-ray scattering, the ‘healing’ operation provides robust and physically-rigorous results and outperforms all other conventional image interpolation methods.
Experimental X-ray scattering images always contain missing data and artifacts, which complicate further analysis, especially rapid, automated analysis. This healing operation is an essential pre-processing step for machine-learning interpretation of scientific data.
X-ray scattering is a powerful way to measure the structure of materials at the molecular- and nano-scale. Scattering images contain features, such as peaks and rings, which encode structural information. As with most scientific data, collected X-ray scattering images are inevitably ‘incomplete,’ with missing data being due to limits of the measurement, or experimental considerations. These missing data render automated data analysis of the datasets much more difficult. In this work, the team developed an image healing algorithm designed for X-ray scattering/diffraction datasets. Because the algorithm is ‘physics-aware’ (incorporating known properties of an X-ray scattering measurement), it outperforms all other image healing methods when applied to X-ray scattering data. The healed images can then be easily fed into existing data analysis pipelines. Importantly, the image healing is also a crucial pre-processing step for input to machine-learning methods — which would otherwise tend to focus on the high-intensity — but ultimately irrelevant — image defects.
A team of users from the Stony Brook University m2M EFRC developed an efficient, ‘one-pot’ synthesis strategy for composite silver-iron battery materials, capable of delivering 2.4 times the energy density of the same composite formed by conventional mixing. Intimate contact between the two material components is the reason for the boost in energy density.
New material solutions are required to meet the growing demand for energy storage. Composites can have desirable properties, but often lack efficient preparation methods. This scalable approach provides a potential solution using an environmentally abundant material (iron).
Researchers have created a new catalyst that brings them one step closer to artificial photosynthesis — a system that would use renewable energy to convert carbon dioxide (CO2) into stored chemical energy.
As in plants, their system consists of two linked chemical reactions: one that splits water (H2O) into protons and oxygen gas, and another that converts CO2 into carbon monoxide (CO). The CO can then be converted into hydrocarbon fuels through an established industrial process. The system would allow both the capture of carbon emissions and the storage of energy from solar or wind power.
Foundry scientists Yufeng Liang and David Prendergast performed theoretical modeling work used to interpret X-ray spectroscopy measurements made in the study, published Nov. 20 in Nature Chemistry. This work was done in support of a project originally proposed by a team from the University of Toronto.
Last year, the team developed catalysts for such reactions. But while one of their catalysts worked under neutral conditions, the other required high pH levels in order to be most active. That meant that when the two were combined, the overall process was not as efficient as it could be: energy was lost when moving charged particles between the two parts of the system.
The team has now overcome this problem by developing a new catalyst for the first reaction – the one that splits water into protons and oxygen gas. Unlike the previous catalyst, this one works at neutral pH, and under those conditions it performs better than any other catalyst previously reported.
The new catalyst is made of nickel, iron, cobalt and phosphorus, all elements that are low-cost and pose few safety hazards. It can be synthesized at room temperature using relatively inexpensive equipment, and the team showed that it remained stable as long as they tested it, a total of 100 hours.
The team employed X-ray experiments at the Canadian Light Source and Berkeley Lab’s Advanced Light Source (ALS) to reveal the working principle behind this new catalyst, mainly focusing on the nickel chemistry during the reaction itself. The Theory Facility at Berkeley Lab’s Molecular Foundry specializes in the interpretation of such X-ray results, connecting chemical intuition to the atomic and electronic structure models of working materials.