Lifeboat Foundation

The synthesis of plastic precursors, such as polymers, involves specialized catalysts. However, the traditional batch-based method of finding and screening the right ones for a given result consumes liters of solvent, generates large quantities of chemical waste, and is an expensive, time-consuming process involving multiple trials.

Ryan Hartman, professor of chemical and biomolecular engineering at the NYU Tandon School of Engineering, and his laboratory developed a lab-based “intelligent microsystem” employing machine learning, for modeling chemical reactions that shows promise for eliminating this costly process and minimizing environmental harm.

In their research, “Combining automated microfluidic experimentation with machine learning for efficient polymerization design,” published in Nature Machine Intelligence, the collaborators, including doctoral student Benjamin Rizkin, employed a custom-designed, rapidly prototyped microreactor in conjunction with automation and in situ infrared thermography to study exothermic (heat generating) polymerization—reactions that are notoriously difficult to control when limited experimental kinetic data are available. By pairing efficient microfluidic technology with machine learning algorithms to obtain high-fidelity datasets based on minimal iterations, they were able to reduce chemical waste by two orders of magnitude and catalytic discovery from weeks to hours.

Scientists at the University of Alberta have shown that the drug remdesivir is highly effective in stopping the replication mechanism of the coronavirus that causes COVID-19, according to new research published today in the Journal of Biological Chemistry.

The paper follows closely on research published by the same lab in late February that demonstrated how the drug worked against the Middle East Respiratory Syndrome (MERS) virus, a related coronavirus.

“We were optimistic that we would see the same results against the SARS-CoV-2 virus,” said Matthias Götte, chair of medical microbiology and immunology at U of A.

High vibrational states of the Magnesium dimer (Mg₂) are an important system in studies of fundamental physics, although they have eluded experimental characterization for half a century. Experimental physicists have so far resolved the first 14 vibrational states of Mg_2, despite reports that the ground-state may support five additional levels. In a new report, Stephen H. Yuwono and a research team in the departments of physics and chemistry at the Michigan State University, U.S., presented highly accurate initial potential energy curves for the ground and excited electron states of Mg₂. They centered the experimental investigations on calculations of state-of-the-art coupled-cluster (CC) and full configuration interaction computations of the Mg₂ dimer. The ground-state potential confirmed the existence of 19 vibrational states with minimal deviation between previously calculated rovibrational values and experimentally derived data. The computations are now published on Science Advances and provide guidance to experimentally detect previously unresolved vibrational levels.

Background

Weakly bound alkaline-earth (AE₂) dimers can function as probes of fundamental physics phenomena, such as ultracold collisions, doped helium nanodroplets, binary reactions and even optical lattice clocks and quantum gravity. The magnesium dimer is important for such applications since it has several desirable characteristics including nontoxicity and an absence of hyperfine structure in the most abundant ²⁴ Mg isotope that typically facilitates the analysis of binary collisions and other quantum phenomena. However, the status of Mg₂ as a prototype heavier AE₂ species is complicated since scientists have not been able to experimentally characterize its high vibrational levels and ground-state potential energy curve (PEC) for so long.

Since the original work on Bose–Einstein condensation^1,2, the use of quantum degenerate gases of atoms has enabled the quantum emulation of important systems in condensed matter and nuclear physics, as well as the study of many-body states that have no analogue in other fields of physics³. Ultracold molecules in the micro- and nanokelvin regimes are expected to bring powerful capabilities to quantum emulation⁴ and quantum computing⁵, owing to their rich internal degrees of freedom compared to atoms, and to facilitate precision measurement and the study of quantum chemistry⁶. Quantum gases of ultracold atoms can be created using collision-based cooling schemes such as evaporative cooling, but thermalization and collisional cooling have not yet been realized for ultracold molecules. Other techniques, such as the use of supersonic jets and cryogenic buffer gases, have reached temperatures limited to above 10 millikelvin^7,8. Here we show cooling of NaLi molecules to micro- and nanokelvin temperatures through collisions with ultracold Na atoms, with both molecules and atoms prepared in their stretched hyperfine spin states. We find a lower bound on the ratio of elastic to inelastic molecule–atom collisions that is greater than 50—large enough to support sustained collisional cooling. By employing two stages of evaporation, we increase the phase-space density of the molecules by a factor of 20, achieving temperatures as low as 220 nanokelvin. The favourable collisional properties of the Na–NaLi system could enable the creation of deeply quantum degenerate dipolar molecules and raises the possibility of using stretched spin states in the cooling of other molecules.

In an effort to make highly sensitive sensors to measure sugar and other vital signs of human health, Iowa State University’s Sonal Padalkar figured out how to deposit nanomaterials on cloth and paper.

Feedback from a peer-reviewed paper published by ACS Sustainable Chemistry and Engineering describing her new fabrication technology mentioned the metal-oxide nanomaterials the assistant professor of mechanical engineering was working with—including zinc oxide, cerium oxide and copper oxide, all at scales down to billionths of a meter—also have antimicrobial properties.

“I might as well see if I can do something else with this technology,” Padalkar said. “And that’s how I started studying antimicrobial uses.”

200+ user-developed early quantum applications on D-Wave systems, including airline scheduling, election modeling, quantum chemistry simulation, automotive design, preventative healthcare, logistics, and much more.

A Nobel Prize winning biology professor has provided a bit of good news amidst the coronavirus gloom; the US may see a downturn in new cases sooner than some models have predicted.

Michael Levitt, a Stanford University biology professor and a 2013 Nobel Prize winner in chemistry, said his models predict the virus is not likely to dwindle on for months or years and – most importantly – is not likely to cause millions of deaths.

Mr Levitt previously predicted – correctly – when China would experience and endure the worst of its coronavirus crisis.

The race toward the first practical quantum computer is in full stride. Companies, countries, collaborators, and competitors worldwide are vying for quantum supremacy. Google says it’s already there. But what does that mean? How will the world know when it’s been achieved?

Using classical computers, computational scientists at PNNL have set a mark that a quantum system would need to surpass to establish quantum supremacy in the realm of chemistry.

That’s because the fastest classical computers available today are getting better and better at simulating what a quantum computer will eventually be expected to do. To prove itself in the real world, a quantum computer will need to be able to outdo what a fast supercomputer can do. And that’s where the PNNL-led team have set a benchmark for quantum computers to beat.

Quantum computing isn’t yet far enough along that it could have helped curb the spread of this coronavirus outbreak. But this emerging field of computing will almost certainly help scientists and researchers confront future crises.

“Can we compress the rate at which we discover, for example, a treatment or an approach to this?” asks Dario Gil, the director of IBM Research. “The goal is to do everything that we are doing today in terms of discovery of materials, chemistry, things like that, (in) factors of 10 times better, 100 times better,”

And that, he says, “could be game-changing.”