Lifeboat Foundation

Proteins are essential to cells, carrying out complex tasks and catalyzing chemical reactions. Scientists and engineers have long sought to harness this power by designing artificial proteins that can perform new tasks, like treat disease, capture carbon or harvest energy, but many of the processes designed to create such proteins are slow and complex, with a high failure rate.

In a breakthrough that could have implications across the healthcare, agriculture, and energy sectors, a team lead by researchers in the Pritzker School of Molecular Engineering at the University of Chicago has developed an artificial intelligence-led process that uses big data to design new proteins.

By developing machine-learning models that can review protein information culled from genome databases, the researchers found relatively simple design rules for building artificial proteins. When the team constructed these artificial proteins in the lab, they found that they performed chemical processes so well that they rivaled those found in nature.

A test firing of Europe’s Helicon Plasma Thruster, developed with ESA by SENER and the Universidad Carlos III’s Plasma & Space Propulsion Team (EP2-UC3M) in Spain. This compact, electrodeless and low voltage design is ideal for the propulsion of small satellites, including maintaining the formation of large orbital constellations.

While traditional chemical propulsion have fundamental upper limits, electric propulsion pumps extra energy into the thrust reaction to reach much higher propellant velocities by accelerating propellant using electrical energy. There are many methods of electric propulsion, many of which require electrodes to apply a current, increasing thruster cost and complexity.

By contrast the Helicon Plasma Thruster uses high power radio frequency waves to excite the propellant into a plasma.

Biochemists use protein engineering to transfer photocaging groups to DNA.

DNA (deoxyribonucleic acid) is the basis of life on earth. The function of DNA is to store all the genetic information, which an organism needs to develop, function and reproduce. It is essentially a biological instruction manual found in every cell.

Biochemists at the University of Münster have now developed a strategy for controlling the biological functions of DNA with the aid of light. This enables researchers to better understand and control the different processes which take place in the cell – for example epigenetics, the key chemical change and regulatory lever in DNA.

AUSTIN, Texas — Producing clean water at a lower cost could be on the horizon after researchers from The University of Texas at Austin and Penn State solved a complex problem that had baffled scientists for decades, until now.

Desalination membranes remove salt and other chemicals from water, a process critical to the health of society, cleaning billions of gallons of water for agriculture, energy production and drinking. The idea seems simple — push salty water through and clean water comes out the other side — but it contains complex intricacies that scientists are still trying to understand.

The research team, in partnership with DuPont Water Solutions, solved an important aspect of this mystery, opening the door to reduce costs of clean water production. The researchers determined desalination membranes are inconsistent in density and mass distribution, which can hold back their performance. Uniform density at the nanoscale is the key to increasing how much clean water these membranes can create.

Scientists at Freie Universität Berlin develop a deep learning method to solve a fundamental problem in quantum chemistry.

A team of scientists at Freie Universität Berlin has developed an artificial intelligence (AI) method for calculating the ground state of the Schrödinger equation in quantum chemistry. The goal of quantum chemistry is to predict chemical and physical properties of molecules based solely on the arrangement of their atoms in space, avoiding the need for resource-intensive and time-consuming laboratory experiments. In principle, this can be achieved by solving the Schrödinger equation, but in practice this is extremely difficult.

Up to now, it has been impossible to find an exact solution for arbitrary molecules that can be efficiently computed. But the team at Freie Universität has developed a deep learning method that can achieve an unprecedented combination of accuracy and computational efficiency. AI has transformed many technological and scientific areas, from computer vision to materials science. “We believe that our approach may significantly impact the future of quantum chemistry,” says Professor Frank Noé, who led the team effort. The results were published in the reputed journal Nature Chemistry.

An international research team that included three scientists from the University of Rhode Island’s Graduate School of Oceanography has discovered single-celled microorganisms in a location where they didn’t expect to find them.

“Water boils on the (Earth’s) surface at 100 degrees Celsius, and we found organisms living in sediments at 120 degrees Celsius,” said URI Professor of Oceanography Arthur Spivack, who led the geochemistry efforts of the 2016 expedition organized by the Japan Agency for Marine-Earth Science and Technology and Germany’s MARUM–Center for Marine and Environmental Sciences at the University of Bremen. The study was carried out as part of the work of Expedition 370 of the International Ocean Discovery Program.

The research results from a two-month-long expedition in 2016 were published in December 2020 in the journal Science.

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A desalination membrane acts as a filter for salty water: push the water through the membrane, get clean water suitable for agriculture, energy production and even drinking. The process seems simple enough, but it contains complex intricacies that have baffled scientists for decades—until now.

Researchers from Penn State, The University of Texas at Austin, Iowa State University, Dow Chemical Company and DuPont Water Solutions published a key finding in understanding how membranes actually filter minerals from water, online today (Dec. 31) in Science. The article will be featured on the print edition’s cover, to be issued tomorrow (Jan. 1).

“Despite their use for many years, there is much we don’t know about how water filtration membranes work,” said Enrique Gomez, professor of chemical engineering and materials science and engineering at Penn State, who led the research. “We found that how you control the density distribution of the membrane itself at the nanoscale is really important for water-production performance.”

Digital data storage is a growing need for our society and finding alternative solutions than those based on silicon or magnetic tapes is a challenge in the era of “big data.” The recent development of polymers that can store information at the molecular level has opened up new opportunities for ultrahigh density data storage, long-term archival, anticounterfeiting systems, and molecular cryptography. However, synthetic informational polymers are so far only deciphered by tandem mass spectrometry. In comparison, nanopore technology can be faster, cheaper, nondestructive and provide detection at the single-molecule level; moreover, it can be massively parallelized and miniaturized in portable devices. Here, we demonstrate the ability of engineered aerolysin nanopores to accurately read, with single-bit resolution, the digital information encoded in tailored informational polymers alone and in mixed samples, without compromising information density. These findings open promising possibilities to develop writing-reading technologies to process digital data using a biological-inspired platform.

DNA has evolved to store genetic information in living systems; therefore, it was naturally proposed to be similarly used as a support for data storage (1–3), given its high-information density and long-term storage with respect to existing technologies based on silicon and magnetic tapes. Alternatively, synthetic informational polymers have also been described (5–9) as a promising approach allowing digital storage. In these polymers, information is stored in a controlled monomer sequence, a strategy that is also used by nature in genetic material. In both cases, single-molecule data writing is achieved mainly by stepwise chemical synthesis (3, 10, 11), although enzymatic approaches have also been reported (12). While most of the progress in this area has been made with DNA, which was an obvious starting choice, the molecular structure of DNA is set by biological function, and therefore, there is little space for optimization and innovation.