Nanomaterials  

Structural nanomaterials have been developed by researchers using 3D laser lithography to create lightweight, high-strength material inspired by the the structure of bones, wood and bees' honeycombs.

Researchers have developed new bio-inspired lightweight microstructured materials with very high stability. Although the density of these materials is below that of water, their stability relative to their weight exceeds that of massive materials, such as high-performance steel or aluminum.

Natural lightweight materials, such as bone, are cellular solids with optimized architecture. They are structured hierarchically and actually consist of nanometer-size building blocks, providing a benefit from mechanical size effects.

"The novel lightweight construction materials resemble the framework structure of a half-timbered house with horizontal, vertical, and diagonal struts. Our beams, however, are only 10 µm in size."

The researchers demonstrated that materials with a designed micro-architecture, providing both structural advantages and size-dependent strengthening effects, can be fabricated. Using 3D laser lithography, they produced micro-truss and -shell structures from ceramic–polymer composites that exceed the strength-to-weight ratio of all engineering materials.

The lightweight construction materials are inspired by the framework structure of bones and the shell structure of the bees’ honeycombs. The results have been published in the journal PNAS.

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“The novel lightweight construction materials resemble the framework structure of a half-timbered house with horizontal, vertical, and diagonal struts,” says Jens Bauer, Karlsruhe Institute of Technology (KIT). “Our beams, however, are only 10 µm in size.” In total, the lightweight construction elements are about 50 µm long, wide, and high.

Microstructured materials are often used for insulation or as shock absorbers. Open-pore materials may be applied as filters in chemical industry.

“Nature also uses open-pore, non-massive structures for carrying loads,” Oliver Kraft, KIT, explains. Examples are wood and bones. At the same density, however, the novel material produced in the laboratory can carry a much higher load. A very high stability was reached by a shell structure similar to the structure of honeycombs. It failed at a pressure of 28 kg/mm2 only and had a density of 810 kg/m3. This exceeds the stability / density ratio of bones, massive steel, or aluminum. The shell structure produced resembles a honeycomb with slightly curved walls to prevent buckling.

To produce the lightweight construction materials, 3D laser lithography was applied. In the procedure laser beams harden the desired microstructure in a photoresist. Then, this structure is coated with a ceramic material by gas deposition. The structures produced were subjected to compression via a die to test their stability.




SOURCE  KIT

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 Hacking Biology  

Nanotechnology implanted into plants could turn them into supercharged energy producers or sensors for pollutants.

AMIT research team wants to make plants even more useful by augmenting them with nanomaterials that could enhance their energy production and give them completely new functions, such as checking for environmental pollutants.

The research has been published in Nature Materials.  The researchers report boosting plants’ ability to capture light energy by 30 percent, embedding carbon nanotubes in the chloroplast, the plant organelle where photosynthesis takes place.

They also modified plants to detect the gas nitric oxide, using another type of carbon nanotube.

"The potential is really endless."

Together, these represent the first steps in launching a scientific field the researchers have dubbed “plant nanobionics.”

“Plants are very attractive as a technology platform,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering and leader of the MIT research team. “They repair themselves, they’re environmentally stable outside, they survive in harsh environments, and they provide their own power source and water distribution.”

Strano and the paper’s lead author, postdoc and plant biologist Juan Pablo Giraldo, envision turning plants into self-powered, photonic devices such as detectors for explosives or chemical weapons. The researchers are also working on incorporating electronic devices into plants. “The potential is really endless,” Strano says.

The idea for nanobionic plants grew out of a project in Strano’s lab to build self-repairing solar cells modeled on plant cells. As a next step, the researchers wanted to try enhancing the photosynthetic function of chloroplasts isolated from plants, for possible use in solar cells.

Chloroplasts host all of the machinery needed for photosynthesis, which occurs in two stages. During the first stage, pigments such as chlorophyll absorb light, which excites electrons that flow through the thylakoid membranes of the chloroplast. The plant captures this electrical energy and uses it to power the second stage of photosynthesis — building sugars.

Chloroplasts can still perform these reactions when removed from plants, but after a few hours, they start to break down because light and oxygen damage the photosynthetic proteins. Usually plants can completely repair this kind of damage, but extracted chloroplasts can’t do it on their own.

To prolong the chloroplasts’ productivity, the researchers embedded them with cerium oxide nanoparticles, also known as nanoceria. These particles are very strong antioxidants that scavenge oxygen radicals and other highly reactive molecules produced by light and oxygen, protecting the chloroplasts from damage.

The researchers delivered nanoceria into the chloroplasts using a new technique they developed called lipid exchange envelope penetration, or LEEP. Wrapping the particles in polyacrylic acid, a highly charged molecule, allows the particles to penetrate the fatty, hydrophobic membranes that surrounds chloroplasts. In these chloroplasts, levels of damaging molecules dropped dramatically.

Using the same delivery technique, the researchers also embedded semiconducting carbon nanotubes, coated in negatively charged DNA, into the chloroplasts. Plants typically make use of only about 10 percent of the sunlight available to them, but carbon nanotubes could act as artificial antennae that allow chloroplasts to capture wavelengths of light not in their normal range, such as ultraviolet, green, and near-infrared.

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With carbon nanotubes appearing to act as a “prosthetic photoabsorber,” photosynthetic activity — measured by the rate of electron flow through the thylakoid membranes — was 49 percent greater than that in isolated chloroplasts without embedded nanotubes. When nanoceria and carbon nanotubes were delivered together, the chloroplasts remained active for a few extra hours.

The researchers then turned to living plants and used a technique called vascular infusion to deliver nanoparticles into Arabidopsis thaliana, a small flowering plant. Using this method, the researchers applied a solution of nanoparticles to the underside of the leaf, where it penetrated tiny pores known as stomata, which normally allow carbon dioxide to flow in and oxygen to flow out. In these plants, the nanotubes moved into the chloroplast and boosted photosynthetic electron flow by about 30 percent.

So far, it has not been determined how that extra electron flow influences the plants’ sugar production. “This is a question that we are still trying to answer in the lab: What is the impact of nanoparticles on the production of chemical fuels like glucose?” Giraldo says.

The researchers also showed that they could turn Arabidopsis thaliana plants into chemical sensors by delivering carbon nanotubes that detect the gas nitric oxide, an environmental pollutant produced by combustion.

By adapting the sensors to different targets, the researchers hope to develop plants that could be used to monitor environmental pollution, pesticides, fungal infections, or exposure to bacterial toxins. They are also working on incorporating electronic nanomaterials, such as graphene, into plants.

“Right now, almost no one is working in this emerging field,” Giraldo says. “It’s an opportunity for people from plant biology and the chemical engineering nanotechnology community to work together in an area that has a large potential.”




SOURCE  MIT Top Image - Bryce Vickmark

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 Nanotechnology  

Researchers have developed a new approach to designing novel nanostructured materials through an inverse design framework using genetic algorithms. The study is the first to demonstrate the application of this methodology to the design of self-assembled nanostructures, and could help speed up the materials discovery process. It also shows the potential of machine learning and "big data" approaches.

Researchers at Columbia Engineering, led by Chemical Engineering Professors Venkat Venkatasubramanian and Sanat Kumar, have developed a new approach to designing novel nanostructured materials through an inverse design framework using genetic algorithms. The study, published in the Early Online edition of Proceedings of the National Academy of Sciences (PNAS), is the first to demonstrate the application of this methodology to the design of self-assembled nanostructures, and shows the potential of machine learning and “big data” approaches embodied in the new Institute for Data Sciences and Engineering at Columbia.

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“Our framework can help speed up the materials discovery process,” says Venkatasubramanian, Samuel Ruben-Peter G. Viele Professor of Engineering, and co-author of the paper. “In a sense, we are leveraging how nature discovers new materials—the Darwinian model of evolution—by suitably marrying it with computational methods. It’s Darwin on steroids!”

Using a genetic algorithm they developed, the researchers designed DNA-grafted particles that self-assembled into the crystalline structures they wanted. Theirs was an “inverse” way of doing research. In conventional research, colloidal particles grafted with single-stranded DNA are allowed to self-assemble, and then the resulting crystal structures are examined. “Although this Edisonian approach is useful for a posteriori understanding of the factors that govern assembly,” notes Kumar, Chemical Engineering Department Chair and the study’s co-author, “it doesn’t allow us to a priori design these materials into desired structures. Our study addresses this design issue and presents an evolutionary optimization approach that was not only able to reproduce the original phase diagram detailing regions of known crystals, but also to elucidate previously unobserved structures.”

The researchers are using “big data” concepts and techniques to discover and design new nanomaterials—a priority area under the White House’s Materials Genome Initiative—using a methodology that will revolutionize materials design, impacting a broad range of products that affect our daily lives, from drugs and agricultural chemicals such as pesticides or herbicides to fuel additives, paints and varnishes, and even personal care products such as shampoo.

“This inverse design approach demonstrates the potential of machine learning and algorithm engineering approaches to challenging problems in materials science,” says Kathleen McKeown, director of the Institute for Data Sciences and Engineering and Henry and Gertrude Rothschild Professor of Computer Science. “At the Institute, we are focused on pioneering such advances in a number problems of great practical importance in engineering.”

Venkatasubramanian adds, “Discovering and designing new advanced materials and formulations with desired properties is an important and challenging problem, encompassing a wide variety of products in industries addressing clean energy, national security, and human welfare.” He points out that the traditional Edisonian trial-and-error discovery approach is time-consuming and costly—it can cause major delays in time-to-market as well as miss potential solutions. And the ever-increasing amount of high-throughput experimentation data, while a major modeling and informatics challenge, has also created opportunities for material design and discovery.

The researchers built upon their earlier work to develop what they call an evolutionary framework for the automated discovery of new materials. Venkatasubramanian proposed the design framework and analyzed the results, and Kumar developed the framework in the context of self-assembled nanomaterials. Babji Srinivasan, a postdoc with Venkatasubramanian and Kumar and now an assistant professor at IIT Gandhinagar, and Thi Vo, a PhD candidate at Columbia Engineering, carried out the computational research. The team collaborated with Oleg Gang and Yugang Zhang of Brookhaven National Laboratory, who carried out the supporting experiments.

The team plans to continue exploring the design space of potential ssDNA-grafted colloidal nanostructures, improving its forward models, and bring in more advanced machine learning techniques. “We need a new paradigm that increases the idea flow, broadens the search horizon, and archives the knowledge from today’s successes to accelerate those of tomorrow,” says Venkatasubramanian.



SOURCE  Columbia Engineering

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Duke University engineers have demonstrated for the first time that they can alter the texture of plastics on demand, for example, switching back and forth between a rough surface and a smooth one.

By applying specific voltages, the team has also shown that it can achieve this control over large and curved surface areas.

"By changing the voltage applied to the polymer, we can alter the surface from bumpy to smooth and back again," said Xuanhe Zhao, assistant professor of mechanical engineering and materials science at Duke's Pratt School of Engineering. "There are many instances, for example, when you'd want to be able to change at will a surface from one that is rough to slippery and back again."

Scientists have long been able to create different patterns or textures on plastics through a process known as electrostatic lithography, in which patterns are "etched" onto a surface from an electrode located above the polymer. However, once the patterns have been created by this method, they are set permanently.

"We invented a method which is capable of dynamically generating a rich variety of patterns with various shapes and sizes on large areas of soft plastics or polymers," Zhao said. The results were published online in the journal Advanced Materials.

"This new approach can dynamically switch polymer surfaces among various patterns ranging from dots, segments, lines to circles," said Qiming Wang, a student in Zhao's laboratory and the first author of the paper. "The switching is also very fast, within milliseconds, and the pattern sizes can be tuned from millimeter to sub-micrometer."

The findings follow Zhao's earlier studies, which for the first time captured on videotape how polymers react to changing voltages. Those experiments showed that as the voltage increases, polymers tend to start creasing, finally leading to large craters. This explained in physical terms, for example, why polymers used to insulate electric wires tend to fail over time. The new lithography strategy takes useful insights from this failure mechanism.

On a more fanciful note, Zhao described the possibility of creating rubber gloves whose fingerprints could be changed on demand.

"The changeable patterns we have created in the laboratory include circles and straight and curved lines, which are basic elements of fingerprints," Zhao said. "These elements can be dynamically patterned and changed on a glove surface that covers fingertips.

"A spy's glove may be cool, but probably not for everyone," Zhao said. "However, the same technology can produce gloves with on-demand textures and smoothness tuned for various applications, such as climbing and gripping. Furthermore, surfaces capable of dynamically changing patterns are also useful for many technologies, such as microfluidics and camouflage."

Other potential usages of the new method include creating surfaces that are self-cleaning and water-repellant, or even as platforms for controlled-release drug-eluting devices.




Duke University