polimeri – Baza de Date

Forța electrostatică preia polimerii bioinpuși(Electrostatic force takes charge in bioinspired polymers)

Acest avans s-ar putea dovedi util în proiectarea de noi materiale bioinpuse și inteligente pentru aplicații variind de la livrarea de medicamente până la sensibilizarea la remedierea contaminanților de mediu. O clasa de polimeri, numite coacervates, care se separa ca ulei si apa si formeaza o substanta asemanatoare cu gelul

Posted: Nov 02, 2017
Electrostatic force takes charge in bioinspired polymers (Nanowerk News) Researchers at the University of Illinois and the University of Massachusetts, Amherst have taken the first steps toward gaining control over the self-assembly of synthetic materials in the same way that biology forms natural polymers. This advance could prove useful in designing new bioinspired, smart materials for applications ranging from drug delivery to sensing to remediation of environmental contaminants.
Proteins, which are natural polymers, use amino acid building blocks to link together long molecular chains. The specific location of these building blocks, called monomers, within these chains creates sequences that dictate a polymer’s structure and function. In the journal Nature Communications („Sequence and entropy-based control of complex coacervates”), the researchers describe how to utilize the concept of monomer sequencing to control polymer structure and function by taking advantage of a property present in both natural and synthetic polymers – electrostatic charge.

Inspired by the principles of natural polymer synthesis, Illinois chemical and biomolecular engineering professor Charles Sing, left, and graduate students Jason Madinya and Tyler Lytle co-authored a study that found they could create new synthetic materials by tuning the electrostatic charge of polymer chains. (Photo by L. Brian Stauffer)
„Proteins encode information through a precise sequence of monomers. However, this precise control over sequence is much harder to control in synthetic polymers, so there has been a limit to the quality and amount of information that can be stored,” said Charles Sing, a professor of chemical and biomolecular engineering at Illinois and a study co-author. „Instead, we can control the charge placement along the synthetic polymer chains to drive self-assembly processes.”
„Our study focuses on a class of polymers, called coacervates, that separate like oil and water and form a gel-like substance,” said Sarah Perry, a study co-author and University of Massachusetts, Amherst chemical engineering professor, as well as an Illinois alumna.
Through a series of experiments and computer simulations, the researchers found that the properties of the resulting charged gels can be tuned by changing the sequence of charges along the polymer chain.
„Manufacturers commonly use coacervates in cosmetics and food products to encapsulate flavors and additives, and as a way of controlling the ‘feel’ of the product,” Sing said. „The challenge has been if they need to change the texture or the thickness, they would have to change the material being used.”
Sing and Perry demonstrate that they can rearrange the structure of the polymer chains by tuning their charge to engineer the desired properties. „This is how biology makes the endless diversity of life with only a small number of molecular building blocks,” Perry said. „We envision bringing this bioinspiration concept full circle by using coacervates in biomedical and environmental applications.”
The results of this research open a tremendous number of opportunities to expand the diversity of polymers used and the scale of applications, the researchers said. „Currently, we are working with materials on the macro scale – things that we can see and touch,” Sing said. „We hope to expand this concept into the realm of nanotechnology, as well.”

Source: University of Illinois at Urbana-Champaign

Creșterea cristalelor perfecte prin umplerea golurilor

Cristalele sunt materiale solide compuse din blocuri microscopice, dispuse în modele foarte ordonat. Ei au nenumărate aplicații, variind de la metalurgie la electronice la bijuterii. Multe dintre proprietățile au făcut cristale utile depind de modelul detaliat al aranjament al constituenților lor, care, la rândul său, este extrem de sensibil la detaliile interacțiunii dintre blocurile de construcție. In cristalele moleculare si atomice forțele interparticule sunt fixate de Natura, iar singura modalitate de tuning aranjament microscopic este de a varia fie condițiile externe (temperatură, presiune, etc.) sau de a modifica particulele Înșiși.amestecurilor de coloizi si particule pe baza de polimeri numiti polimeri stele

Posted: May 31, 2016
Growing perfect crystals by filling the gaps (Nanowerk News) Be it in phyics, metallurgy, gemology or engineering, the applications of crystals are very broad. A research team including Christos Likos and Lorenzo Rovigatti from the Faculty of Physics of the University of Vienna, in collaboration with the National Institute of Standards and Technology (NIST, USA) and Princeton University (USA) has developed a new method to assemble large, periodic crystals. The results have been published in the Journal ACS Nano („Bottom-Up Colloidal Crystal Assembly with a Twist”).

The scientists have shown that long-range order can be restored by employing mixtures of colloids and polymer-based particles called star polymers (Image: Christos Likos, Universität Wien)
Crystals are solid materials composed of microscopic building blocks arranged in highly ordered patterns. They have countless applications, ranging from metallurgy to jewellery to electronics. Many of the properties that make crystals useful depend on the detailed pattern of arrangement of their constituents, which, in turn, is highly sensitive to the details of the interaction between the building blocks. In molecular and atomic crystals the interparticle forces are fixed by Nature, and the only way of tuning the microscopic arrangement is to either vary the external conditions (temperature, pressure, etc.) or change the particles themselves.
By contrast, insoft matter Physics , where the building blocks are orders of magnitude larger and much more complex than atoms, it is possible to design and engineer building blocks with extremely tunable properties. Consequently, much effort has been devoted to the synthesis of colloids that self-assemble into highly symmetric patterns with technologically relevant properties. For instance, there exist specific crystal lattices that exhibit very exciting optical properties, the so-called photonic crystals – periodic structures that allow certain bands of wavelengths of light to propagate through their interior while blocking other ones.
A natural example of a photonic crystal is the opal, whose fascinating coloration is due to the way the light interacts with its microscopic structure of colloidal particles arranged on a regular lattice. The multicolored iridescence of the precious opal, the source of its charming appearance, is due to the presence of several small crystals, known as crystallites, which are randomly oriented with respect to the one another.
In addition, the assembly of colloidal crystals is often confounded by polymorphism: „Different structures are characterised by comparable thermodynamic stabilities, making it difficult to produce a single morphology at will”, says Christos Likos from the Faculty of Physics of the University of Vienna.
The resulting lack of long-range order is detrimental for many applications. Accordingly, strategies need to be developed that enhance the growth of long-ranged, monocrystalline samples in (real or numerical) experiments. Accordingly, scientists have been working hard to deveop strategies that enhance the growth of large, monocrystalline structures. Employing computer simulations, a new method has now been developed that allows the assembly of technologically relevant, non-polymorphic crystals.
„The system crystallises into a mixture of difference micocrystals. However, the competing structures assembled by the colloids have different geometries and different internal void distributions. This difference can be exploited by tuning the size of polymer additive to interact uniquely with the void symmetry of the desired crystal, effectively stabilising it against the competitor”, explains Lise-Meitner Fellow Lorenzo Rovigatti, working at the group of Christos Likos.
The results of the research team serve not only to illustrate an alternative to existing approaches which, in many cases, produce unsatisfactory results, but also to guide experimental realizations of highly-ordered colloidal open crystals in the near future.

Source: Universität Wien

Construirea unei capcane mai bune a mouse-ului, de la atomi în sus

Pentru proiectul lor, grupul Ramprasad sa uitat la polimeri din doar șapte blocuri: CH 2 , C 6 H 4 , CO, O, NH, CS și C 4 H 2 S (S este sulf). Acestea se găsesc în materiale plastice obișnuite, cum ar fi polietilenă, poliesteri și poliuree. O varietate enormă de polimeri ar putea fi construită teoretic folosind doar aceste blocuri de construcție; Grupul Ramprasad a decis la început să analizeze doar 283, fiecare compus dintr-o unitate repetată de patru blocuri.

Posted: Mar 04, 2016
Building a better mouse trap, from the atoms up (Nanowerk News) For most of human history, the discovery of new materials has been a crapshoot. But now, UConn researchers have systematized the search with machine learning that can scan millions of theoretical compounds for qualities that would make better solar cells, fibers, and computer chips. The search for new materials may never be the same.
No one knows why an early metallurgist decided to smelt a hunk of tin into some copper, but the resulting bronze alloy was harder and more durable than any material previously known. Most materials experimentation over the ensuing 7,000 years has been similarly random, guided largely by philosophy and chemical intuition.
But in a world that contains at least 95 stable elements – the basic building blocks of matter – the number of possible combinations is enormous, and experimentation is an awfully inefficient way to find what you’re looking for.
Enter UConn materials scientist Ramamurthy ‘Rampi’ Ramprasad. Instead of randomly mixing chemicals to see what they do, Ramprasad designs them rationally, using machine learning to figure out which atomic configurations make a polymer a good electrical conductor or insulator.

The Ramprasad Lab is employing machine learning to design new materials without having to pre-test each one. (Schematic by Chiho Kim, Ramprasad Lab)
A polymer is a large molecule made of many repeating building blocks. Polymers are very common in both living and man-made materials. Probably the most familiar example is plastics, and the wide variation in plastics – which can be hard, soft, stretchy, brittle, spongy, clear, opaque or translucent – gives an inkling of how diverse polymers in general can be.
Polymers can also have diverse electronic properties. For example, they can be very good insulators – preventing electrons, and thus electric current, from traveling through them – or good conductors, allowing electricity to pass through them freely. And what controls all these properties is mainly how the atoms in the polymer connect to each other. But until recently, no one had systematically related properties to atomic configurations.
So Ramprasad and his colleagues decided to do just that. First, they would analyze known polymers, using laborious but accurate quantum mechanics-based calculations to figure out which arrangements of atoms confer which properties, and quantify those atomic-level relationships via a string of numbers that fingerprint each polymer. Once they had those, they could have a computer search through any number of theoretical polymers to figure out which ones might have which properties. Then anyone looking for a polymer with a certain property could quickly scan the list and decide which theoretical polymers might be worth trying.
Many polymers are made of building blocks containing just a few atoms. For instance, polyurea, a common plastic, has as the basic structure a repeating sequence of nitrogen (N), hydrogen (H) and oxygen (O): NH-O-NH-O. Most polymers look like that, made of carbon (C), H, N and O, with a few other elements thrown in occasionally.
For their project, Ramprasad’s group looked at polymers made of just seven building blocks: CH2, C6H4, CO, O, NH, CS, and C4H2S (the S is sulfur). These are found in common plastics such as polyethylene, polyesters, and polyureas. An enormous variety of polymers could theoretically be constructed using just these building blocks; Ramprasad’s group decided at first to analyze just 283, each composed of a repeated four-block unit.

Polyurea, a common plastic. In this diagram, N is nitrogen, H hydrogen, and O oxygen. R stands in for any number of chemicals that could slightly alter the polymer, but the repeating NH-O-NH-O is the basic structure. Most polymers look like that, made of carbon (C), H, N and O, with a few other elements thrown in occasionally. (By Yikrazuul – own work, public domain)
They started from basic quantum mechanics, and calculated the three-dimensional atomic and electronic structures of each of those 283 four-block polymers. This is not trivial: calculating the position of every electron and atom in a molecule with more than two atoms takes a powerful computer a significant chunk of time, which is why they did it for only 283 molecules.
Once they had the three-dimensional structures, they could calculate what they really wanted to know: each polymer’s properties. They calculated the band gap, which is the amount of energy it takes for an electron in the polymer to break free of its home atom and travel around the material, and the dielectric constant, which is a measure of the effect an electric field can have on the polymer. These properties translate to how much electric energy each polymer can store in itself. The researchers used established techniques that have long been known. They take a prohibitive amount of computing time, which is why it’s so hard to evaluate materials this way.
Ramprasad’s group then went one step further. They wanted a shorthand system that a computer could use to look at the building blocks of a polymer and how they connect to each other, and make educated guesses about its properties.
Computers deal with numbers, so first they had to define each polymer as a string of numbers, a sort of numerical fingerprint. Since there are seven possible building blocks, there are seven possible numbers, each indicating how many of each block type are contained in that polymer. But a simple number string like that doesn’t give enough information about the polymer’s structure, so they added a second string of numbers that tell how many pairs there are of each combination of building blocks, such as NH-O or C6H4-CS. Still not quite enough information, so they added a third string that described how many triples, like NH-O-CH2, there were. They arranged these strings as a three-dimensional matrix, which is a convenient way to describe such strings of numbers in a computer.
Then they let the computer go to work. Using the library of 283 polymers they had laboriously calculated using quantum mechanics, the machine compared each polymer’s numerical fingerprint to its band gap and dielectric constant, and gradually ‘learned’ which building block combinations were associated with which properties. It could even map those properties onto a two-dimensional matrix of the polymer building blocks.

Once the machine learned which atomic building block combinations gave which properties, it no longer needed the quantum mechanics calculations of atomic structure. It could accurately evaluate the band gap and dielectric constant for any polymer made of any combination of those seven building blocks, using just the numerical fingerprint of its structure.
Many of the predictions of quantum mechanics and the machine learning scheme have been validated by Ramprasad’s UConn collaborators, chemistry professor Greg Sotzing and electrical engineering professor Yang Cao. Sotzing actually made several of the novel polymers, and Cao tested their properties; they came out just as Ramprasad’s computations had predicted.
„What’s most surprising is the level of accuracy with which we can make predictions of the dielectric constant and band gap of a material using machine learning. These properties are generally computed using quantum mechanical methods such as density functional theory, which are six to eight orders of magnitude slower,” says Ramprasad. The group published a paper on their polymer work in Scientific Reports on Feb. 15 („Machine Learning Strategy for Accelerated Design of Polymer Dielectrics”); and another paper that utilizes machine learning in a different manner, namely, to discover laws that govern dielectric breakdown of insulators, will be published in a forthcoming issue of Chemistry of Materials.
But even if you don’t have access to those academic journals, you can see the predicted properties of every polymer Ramprasad’s group has evaluated in their online data vault, Khazana (khazana.uconn.edu), which also provides their machine learning apps to predict polymer properties on the fly. They are also uploading data and the machine learning tools from their Chemistry of Materials work, and from an additional recent article published in Scientific Reports on Jan. 19 on predicting the band gap of perovskites, inorganic compounds used in solar cells, lasers, and light-emitting diodes.
As a theoretical materials scientist, what Ramprasad wants to know is why materials behave the way they do. What about a polymer makes its dielectric constant just so? Or what makes an insulator withstand enormous electric fields without breaking down? But he also wants this understanding to be put to work to design new useful materials rationally. So he makes the results of his calculations freely available in the hope that someone else might look through them, see one, and go, „Wow. I’m looking for a material with exactly those properties!” and then make it. If it works as predicted, they’re both happy.

Source: University of Connecticut

Un nou răsucire pe tehnologia veche ar putea aduce culoarea vie la putere redusă (New twist on old tech could bring living color at low power

Polimerii electrochromici constituie o clasă specială de materiale care pot trece de la culori la culori și înapoi, când se modifică sarcina electrică. Adoptarea largă a acestora a fost totuși împiedicată deoarece această transformare depinde de cât de repede electronii pot intra și ieși din material, ceea ce poate dura câteva secunde, în funcție de grosimea filmului. De ce nu faceti filmele mai subtiri, astfel incat sa schimbe culoarea mai repede? Idee bună, dar, din păcate, reducerea grosimii peliculei răstoarnă culorile contrastului lor, oferindu-vă o nuanță semitransparentă negru atunci când ceea ce ați dorit a fost un negru impenetrabil, opac.
Un afișaj bazat pe această schemă ar avea o serie de nanograme care acționează ca pixeli cu o singură culoare, ale căror culori, adăugând sau scăzând, ar produce toate culorile curcubeului, pixelii individuali având niveluri reglabile de luminozitate sau contrast.

Posted: Feb 04, 2016
New twist on old tech could bring living color at low power (Nanowerk News) By marrying state-of-the-art nanometer-scale gratings with a Space Age-era thin-film polymer, researchers working at the National Institute of Standards and Technology (NIST) have developed a new technology for building power-sipping full-color video displays, switches and routers for optical signals, as well as smart windows and coatings (Nature Communications, „High-contrast and fast electrochromic switching enabled by plasmonics”).

In this schematic, light enters from above and encounters a nanometer-scale grating made of aluminum and coated with a special ‘electrochromic’ material. Light passes through the nanograting as surface plasmons, oscillations that travel at the interface of a metal and a dielectric (insulating) material. The spacing of the slits serves to filter out all but one color of light, and an additional layer of silicon nitride further spectrally purifies the escaping light. (Image: T. Xu and A. Agrawal/NIST) (click on image to enlarge)
Electrochromic polymers make up a special class of materials that can switch from clear to colored and back again when their electrical charge changes. Their wide adoption, however, has been hindered because this transformation depends on how quickly electrons can get into and out of the material, which can take several seconds depending on the thickness of the film. Why not just make the films thinner so they’ll change color faster? Good idea, but unfortunately, reducing the film’s thickness robs the colors of their contrast, giving you a semitransparent black tint when what you wanted was an impenetrable, opaque black.
If the choice between being slow or weakly colored weren’t bad enough, an electrochromic display using an additive color scheme—in which red, green and blue are mixed to achieve full color—would need up to six transparent electrically conducting layers to work, adding substantially to the cost of manufacturing.
Using some clever engineering, the researchers overcame this impasse by layering a thin film of electrochromic polymer over an aluminum nanograting. In their setup, the light first encounters the nanograting which, depending on the spacing of the slits, filters out all but one color of light. The electrochromic coating serves to modulate that light by allowing all or some (or none) of it to pass. A display based on this scheme would have an array of nanogratings acting as single-color pixels whose colors would, by adding or subtracting them, produce all the colors of the rainbow, with the individual pixels having adjustable levels of brightness or contrast.
But how does combining a thin film of electrochromic polymer with a nanograting make up for the just-described deficiencies of using said thin film? According to co-lead author Amit Agrawal, it’s all about the architecture.
“Because the electrochromic film that coats the sidewalls of the nanograting is so thin, it’s very easy for electrons to make their way through and change its opacity,” Agrawal says. “The slits are much narrower (about 60 nanometers) than the wavelengths of light they are transmitting (from about 400 to 700 nanometers). This forces the incoming light to cling to the interface between the metal and the electrochromic layer on its way down the slits. And because the grating is so much deeper (about 250 nanometers) than it is wide, and the walls of the slits are coated with electrochromic polymer all the way down, it can reduce the light’s intensity to the same degree as if the light were passing through a much thicker layer of electrochromic film, enabling a great amount of control.”
NIST Fellow Henri Lezec, an author of the paper, says the setup they have now uses a liquid electrolyte, a chemical that facilitates the proper flow of electrons, which is not ideal for manufacturability and reliability, but that it could easily be replaced with a more physically stable and compact solid-state electrolyte.
Alec Talin, a co-author based at Sandia National Laboratories, says that the next step in extending this principle would be toward reflective, sunlight-readable displays that do not require an energy-consuming backlight.

Source: The National Institute of Standards and Technology

Electrostatic force takes charge in bioinspired polymers

Growing perfect crystals by filling the gaps

Building a better mouse trap, from the atoms up

New twist on old tech could bring living color at low power