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Category: chemistry – Page 192

A new program can streamline the process of creating, launching and analysing computational chemistry experiments. This piece of software, called AQME, is distributed for free under an open source licence, and could contribute to making calculations more efficient, as well as accelerating automated analyses.

‘We estimate time savings of around 70% in routine computational chemistry protocols,’ explains lead author Juan Vicente Alegre Requena, at the Institute of Chemical Synthesis and Homogeneous Catalysis (ISQCH) in Zaragoza, Spain. ‘In modern molecular simulations, studying a single reaction usually involves more than 500 calculations,’ he explains. ‘Generating all the input files, launching the calculations and analysing the results requires an extraordinary amount of time, especially when unexpected errors appear.’

Therefore, Alegre and his colleagues decided to code a piece of software to skip several steps and streamline calculations. Among other advantages, AQME works with simple inputs, instead of the optimised 3D chemical structures usually required by other solutions. ‘It’s exceptionally easy,’ says Alegre. ‘AQME is installed in a couple of minutes, then the only indispensable input is as a simple Smiles string.’ Smiles is a system developed by chemist and coder Dave Weininger in the late 1980s, which converts complex chemical structures into a succession of letters and numbers that is machine readable. This cross-compatibility could allow integration with chemical databases and machine-learning solutions, most of which include datasets in Smiles format, explains Alegre.

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Dedicated to ending the HIV epidemic — dr. moupali das, MD, MPH, executive director, HIV clinical research, gilead sciences.

Dr. Moupali Das, MD, MPH, is Executive Director, HIV Clinical Research, in the Virology Therapeutic Area, at Gilead Sciences (https://www.gilead.com/), where she leads the pre-exposure prophylaxis (PrEP) clinical drug development program, including evaluating the safety and efficacy of a long-acting, twice yearly, subcutaneous injection being studied for HIV prevention. Her responsibilities also include expanding the populations who may benefit from PrEP.

Dr. Das has led high-performing teams in academic medicine, public health, implementation science, and cross-functionally in drug development. She has successfully helped develop, implement, and evaluate how to better test, link to care, increase virologic suppression, and improve quality of life for people with HIV, and to prevent HIV in those who may benefit from PrEP.

During the COVID19 pandemic, Dr. Das assisted her colleagues in the COVID-19 treatment program, leading the evaluation of a COVID-19 treatment for use in pregnant women and children from the compassionate use program.

After completing her undergraduate degree in Biochemical Sciences at Harvard College, medical school and internal medicine residency training at Columbia University and New York Presbyterian Hospital, Dr. Das came to University of California, San Francisco (UCSF) for fellowship training in Infectious Diseases and to University of California, Berkeley for her MPH in Epidemiology. She cared for HIV patients at San Francisco General’s storied Ward 86 clinic and attended on the inpatient ID Consult Service. She is recognized internally and externally for her expertise in epidemiology, public health, advocacy, and community engagement.

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Computer models are an important tool for studying how the brain makes and stores memories and other types of complex information. But creating such models is a tricky business. Somehow, a symphony of signals—both biochemical and electrical—and a tangle of connections between neurons and other cell types creates the hardware for memories to take hold. Yet because neuroscientists don’t fully understand the underlying biology of the brain, encoding the process into a computer model in order to study it further has been a challenge.

Now, researchers at the Okinawa Institute of Science and Technology (OIST) have altered a commonly used computer model of called a Hopfield network in a way that improves performance by taking inspiration from biology. They found that not only does the new network better reflect how neurons and other cells wire up in the , it can also hold dramatically more memories.

The complexity added to the network is what makes it more realistic, says Thomas Burns, a Ph.D. student in the group of Professor Tomoki Fukai, who heads OIST’s Neural Coding and Brain Computing Unit. “Why would biology have all this complexity? Memory capacity might be a reason,” Mr. Burns says.

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Wearable devices such as smartwatches, fitness trackers, and virtual reality headsets are becoming commonplace. They are powered by flexible electronics that consist of electrodes with plastic or metal foil as substrates. However, both of these come with their own drawbacks. Plastics suffer from poor adhesion and low durability, while metal foils make the devices bulky and less flexible.

In light of this, paper is a promising alternative. It is porous, light, thin, foldable, and flexible. Moreover, paper has randomly distributed fibers that provide a large surface area for depositing active electrode material, making for excellent electrochemical properties.

Accordingly, researchers have developed various paper-based supercapacitors, devices that store electric charge and energy, by stacking multiple sheets, acting as positive and negative electrodes and separators. However, such an arrangement increases device size and resistance. In addition, they tend to form creases, peel off, and slip over each other, which further deteriorate device performance.

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A joint effort in chemistry has resulted in an innovative method for utilizing carbon dioxide in a positive – even beneficial – manner: through electrosynthesis, it is integrated into a series of organic molecules that play a crucial role in the development of pharmaceuticals.

During the process, the team made an innovative discovery. By altering the type of electrochemical reactor used, they were able to generate two distinct products, both of which are useful in medicinal chemistry.

The team’s paper was recently published in the journal Nature. The paper’s co-lead authors are postdoctoral researchers Peng Yu and Wen Zhang, and Guo-Quan Sun of Sichuan University in China.

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While tunneling reactions are remarkably hard to predict, a group of researchers were able to experimentally observe such an effect, marking a breakthrough in the field of quantum chemistry.

Tunnel Effect

Predicting tunnel effects is very difficult to pull off. The mechanically exact quantum description of chemical reactions that cover over three particles is quite hard. If it covers over four particles, it is almost impossible to pull off. In order to stimulate the reactions, scientists use classical physics but have to push aside the quantum effects. However, EurekAlert reports that there is a limit to classically describing these chemical reactions. What, then, is the limit?

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Tiny insects known as sharpshooters excrete by catapulting urine drops at incredible accelerations. Their excretion is the first example of superpropulsion discovered in a biological system.

Saad Bhamla was in his backyard when he noticed something he had never seen before: an insect urinating. Although nearly impossible to see, the insect formed an almost perfectly round droplet on its tail and then launched it away so quickly that it seemed to disappear. The tiny insect relieved itself repeatedly for hours.

It’s generally taken for granted that what goes in must come out, so when it comes to fluid dynamics in animals, the research is largely focused on feeding rather than excretion. But Bhamla, an assistant professor in the School of Chemical and Biomolecular Engineering at the Georgia Institute of Technology (Georgia Tech), had a hunch that what he saw wasn’t trivial.

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Tunneling reactions in chemistry are difficult to predict. The quantum mechanically exact description of chemical reactions with more than three particles is difficult, with more than four particles it is almost impossible. Theorists simulate these reactions with classical physics and must neglect quantum effects. But where is the limit of this classical description of chemical reactions, which can only provide approximations?

Roland Wester from the Department of Ion Physics and Applied Physics at the University of Innsbruck has long wanted to explore this frontier. “It requires an experiment that allows very and can still be described quantum-mechanically,” says the experimental physicist. “The idea came to me 15 years ago in a conversation with a colleague at a conference in the U.S.,” Wester recalls. He wanted to trace the quantum mechanical tunnel effect in a very simple reaction.

Since the tunnel effect makes the reaction very unlikely and thus slow, its experimental observation was extraordinarily difficult. After several attempts, however, Wester’s team has now succeeded in doing just that for the first time, as they report in the current issue of the journal Nature.

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These peculiar geological structures could explain a long-standing mystery of how Venus loses its heat.

Given Venus and Earth are both rocky planets with roughly the same size and chemistry of their rocks, they should be losing their interior heat to space at a similar rate. How Earth loses its heat is well known, whereas Venus’ flow process remains a mystery.

How does Venus, the hottest planet in the solar system, lose its heat?

NASA/JPL-Caltech/Peter Rubin.

According to a news release from NASA, new research has taken a fresh look at how Venus cools using data from the NASA Magellan mission that spans three decades and discovered that thin parts of the planet’s uppermost layer might provide an answer.

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