Lifeboat Foundation

PRESS RELEASE — There has been a lot of buzz about quantum computers and for good reason. The futuristic computers are designed to mimic what happens in nature at microscopic scales, which means they have the power to better understand the quantum realm and speed up the discovery of new materials, including pharmaceuticals, environmentally friendly chemicals, and more. However, experts say viable quantum computers are still a decade away or more. What are researchers to do in the meantime?

A new Caltech-led study in the journal Science describes how machine learning tools, run on classical computers, can be used to make predictions about quantum systems and thus help researchers solve some of the trickiest physics and chemistry problems. While this notion has been shown experimentally before, the new report is the first to mathematically prove that the method works.

“Quantum computers are ideal for many types of physics and materials science problems,” says lead author Hsin-Yuan (Robert) Huang, a graduate student working with John Preskill, the Richard P. Feynman Professor of Theoretical Physics and the Allen V. C. Davis and Lenabelle Davis Leadership Chair of the Institute for Quantum Science and Technology (IQIM). “But we aren’t quite there yet and have been surprised to learn that classical machine learning methods can be used in the meantime. Ultimately, this paper is about showing what humans can learn about the physical world.”

Scientists discover that 1 in 5 metal compounds display anti-fungal properties-they are non-toxic too.

Metal compounds could be the answer to the growing problem of drug-resistant fungal infections, according to new research published in the American Chemical Society on Sept .23.

The compounds could help develop much-needed antifungal drugs-particularly for immunocompromised patients susceptible to fungal infections.

Ideally, the nanopore dimensions should be comparable to those of the analyte for the presence of the analyte to produce a measurable change in the ionic current amplitude above the noise level. Nanopores can be formed in several ways, with a wide range of pore diameters. Biological nanopores are formed by the self-assembly of either protein subunits, peptides or even DNA scaffolds in lipid bilayers or block copolymer membranes^1,3,6,17,18. They possess atomically precise dimensions controlled by biopolymer sequences, providing the ability to recognize biomolecules with constriction diameters of ~1–10 nm. Solid-state nanopores are crafted in thin inorganic or plastic membranes (for example, SiN_x), which allows the nanopores to have extended diameters of up to hundreds of nanometres, permitting the entry or analysis of large biomolecules and complexes. The tools for fabricating solid-state nanopores, which include electron/ion milling^4,5, laser-based optical etching^19,20 and the dielectric breakdown of ultrathin solid membranes^21,22, can be used to manipulate nanopore size at the nanometre scale, but allow only limited control over the surface structure at the atomic level in contrast to biological nanopores. The chemical modification and genetic engineering of biological nanopores, or the introduction of biomolecules to functionalize solid-state nanopores²³, can further enhance the interactions between a nanopore and analytes, improving the overall sensitivity and selectivity of the device^{2,17,24,25,26}. This feature allows nanopores to controllably capture, identify and transport a wide variety of molecules and ions from bulk solution.

Nanopore technology was initially developed for the practicable stochastic sensing of ions and small molecules^2,27,28. Subsequently, many developmental efforts were focused on DNA sequencing^1,7,8,9. Now, however, nanopore applications extend well beyond sequencing, as the methodology has been adapted to analyse molecular heterogeneities and stochastic processes in many different biochemical systems (Fig. 1). First, a key advantage of nanopores lies in their ability to successively capture many single molecules one after the other at a relatively high rate, which allows nanopores to explore large populations of molecules at the single-molecule level in reasonable timeframes. Second, nanopores essentially convert the structural and chemical properties of the analytes into a measurable ionic current signal, even achieving enantiomer discrimination²⁹. The technology can be used to report on multiple molecular features while circumventing the need for labelling chemistries, which may complicate the overall analysis process and affect the molecular structures. For example, nanopores can discriminate nearly 13 different amino acids in a label-free manner, including some with minute structural differences³⁰. An important aspect is the ability of nanopores to identify species³¹ that lack suitable labels for signal amplification or whose information is hidden in the noise of analytical devices. Consequently, nanopores may serve well in molecular diagnostic applications required for precision medicine, which achieves the identification of nucleic acid, protein or metabolite analytes and other biomarkers^{11,32,33,34,35}. Third, nanopores provide a well-defined scaffold for controllably designing and constructing biomimetic systems, which involve a complex network of biomolecular interactions. These nanopore systems track the binding dynamics of transported biomolecules as they interact with nanopore surfaces, hence serving as a platform for unravelling complex biological processes (for example, the transport properties of nuclear pore complexes)^36,37,38,39. Fourth, chemical groups can be spatially aligned within a protein nanopore, providing a confined chemical environment for site-selective or regioselective covalent chemistry. This strategy has been used to engineer protein nanoreactors to monitor bond-breaking and bond-making events^40,41.

Here we discuss the latest advances in nanopore technologies beyond DNA sequencing and the future trajectory of the field, as well as the opportunities and main challenges for the next decade. We specifically address the emerging nanopore methods for protein analysis and protein sequencing, single-molecule covalent chemistry, single-molecule analysis of clinical samples and insights into the use of biomimetic pores for analysing complex biological processes.

The new material is far superior to today’s non-stick options.

Researchers at Tufts University have developed a method for developing silk-based materials that refuse to stick to water and exhibit non-stick properties that surpass those of current non-stick surfaces, according to a press release by the institution published on Friday.

“The success we had with modifying silk to repel water extends our successes with chemically modifying silk for other functionalities—such as the ability to change color, conduct electrical charge, or persist or degrade in a biological environment,” said David Kaplan, Stern Family Professor of Engineering at Tufts.

Continue reading “Scientists break down silk to invent extremely efficient non-stick material” »

Skoltech scientists modeled the behavior of nanobubbles appearing in van der Waals heterostructures and the behavior of substances trapped inside the bubbles. In the future, the new model will help obtain equations of state for substances in nano-volumes, opening up new opportunities for the extraction of hydrocarbons from rock with large amounts of micro-and nanopores. The results of the study were published in the Journal of Chemical Physics.

The van der Waals nanostructures hold much promise for the study of tiniest samples with volumes from 1 cubic micron down to several cubic nanometers. These atomically thin layers of two-dimensional materials, such as graphene, hexagonal boron nitride (hBN) and dichalcogenides of transition metals, are held together by weak van der Waals interaction only. Inserting a sample between the layers separates the upper and bottom layers, making the upper layer lift to form a nanobubble. The resulting structure will then become available for transmission electron and atomic force microscopy, providing an insight into the structure of the substance inside the bubble.

The properties exhibited by substances inside the van der Waals nanobubbles are quite unusual. For example, water trapped inside a nanobubble displays a tenfold decrease in its dielectric constant and etches the diamond surface, something it would never do under normal conditions. Argon which typically exists in liquid form when in large quantities can become solid at the same pressure if trapped inside very small nanobubbles with a radius of less than 50 nanometers.

In molecules, the atoms vibrate with characteristic patterns and frequencies. Vibrations are therefore an important tool for studying molecules and molecular processes such as chemical reactions. Although scanning tunneling microscopes can be used to image individual molecules, their vibrations have so far been difficult to detect.

Physicists at Kiel University (Christian-Albrechts-Universität zu Kiel, CAU) have now invented a method with which the vibration signals can be amplified by up to a factor of 50. Furthermore, they increased the frequency resolution considerably. The new method will improve the understanding of interactions in molecular systems and further simulation methods. The research team has now published the results in the journal Physical Review Letters.

Continue reading “Physicists make molecular vibrations more detectable” »

Molecules of the rare metallic element niobium can be used as molecular building blocks to design electrochemical energy storage materials. Mark Rambaran, Department of Chemistry at Umeå University, presents in his thesis a method for producing solid materials from aqueous solutions containing nano-sized niobium molecules, called polyoxoniobates.

“These polyoxoniobates are water-soluble and can be synthesized in large volumes. They act as molecular building blocks, in the same way as when a child stacks Lego bricks,” Mark Rambaran says. “They can be used to make a wide range of materials, including supercapacitors that facilitate lithium-ion storage.”

Synthesis of polyoxoniobates can be done with microwave irradiation, because it is a rapid and efficient alternative to conventional hydrothermal methods, Mark Rambaran shows in his thesis.

There has been a lot of buzz about quantum computers and for good reason. The futuristic computers are designed to mimic what happens in nature at microscopic scales, which means they have the power to better understand the quantum realm and speed up the discovery of new materials, including pharmaceuticals, environmentally friendly chemicals, and more. However, experts say viable quantum computers are still a decade away or more. What are researchers to do in the meantime?

A new Caltech-led study in the journal Science describes how machine learning tools, run on classical computers, can be used to make predictions about quantum systems and thus help researchers solve some of the trickiest physics and chemistry problems. While this notion has been shown experimentally before, the new report is the first to mathematically prove that the method works.

“Quantum computers are ideal for many types of physics and materials science problems,” says lead author Hsin-Yuan (Robert) Huang, a graduate student working with John Preskill, the Richard P. Feynman Professor of Theoretical Physics and the Allen V. C. Davis and Lenabelle Davis Leadership Chair of the Institute for Quantum Science and Technology (IQIM). “But we aren’t quite there yet and have been surprised to learn that classical machine learning methods can be used in the meantime. Ultimately, this paper is about showing what humans can learn about the physical world.”

Strenuous cognitive work leads to an accumulation of glutamate in the prefrontal cortex, according to new research published in the journal Current Biology. The new findings suggest that mental fatigue is a neuropsychological mechanism that helps to avert the build up of potentially toxic byproducts of prolonged cognitive activity.

“Nobody knows what mental fatigue is, how it is generated and why we feel it,” said study author Antonius Wiehler, a member of the Motivation, Brain and Behavior Lab at Pitié Salpêtrière Hospital in Paris. “It has remained a mystery despite more than a century of scientific research. Machines can do cognitive tasks continuously without fatigue, the brain is different and we wanted to understand how and why. Mental fatigue has important consequences: for economic decisions, for management at work, for education at school, for clinical cure, etc.”

The researchers were particularly interested in the role of glutamate, an excitatory neurotransmitter that is involved in a variety of cognitive functions, including learning and memory. In addition, glutamate plays a role in controlling the strength of synaptic connections. Too much or too little glutamate can lead to neuronal dysfunction, so it is critical that this neurotransmitter is tightly regulated.