Scientists have been able to observe a common interaction in quantum chemistry for the first time, by using a quantum computer to shadow the process at a speed 100 billion times slower than normal.
Known as a conical intersection, the interactions have long been known about, but are usually over in mere femtoseconds – quadrillionths of a second – making direct observations impossible to carry out.
A molecular assembler, as defined by K. Eric Drexler, is a “proposed device able to guide chemical reactions by positioning reactive molecules with atomic precision”. A molecular assembler is a kind of molecular machine. Some biological molecules such as ribosomes fit this definition. This is because they receive instructions from messenger RNA and then assemble specific sequences of amino acids to construct protein molecules. However, the term “molecular assembler” usually refers to theoretical human-made devices.
Beginning in 2007, the British Engineering and Physical Sciences Research Council has funded development of ribosome-like molecular assemblers. Clearly, molecular assemblers are possible in this limited sense. A technology roadmap project, led by the Battelle Memorial Institute and hosted by several U.S. National Laboratories has explored a range of atomically precise fabrication technologies, including both early-generation and longer-term prospects for programmable molecular assembly; the report was released in December, 2007. In 2008 the Engineering and Physical Sciences Research Council provided funding of 1.5 million pounds over six years for research working towards mechanized mechanosynthesis, in partnership with the Institute for Molecular Manufacturing, amongst others. Likewise, the term “molecular assembler” has been used in science fiction and popular culture to refer to a wide range of fantastic atom-manipulating nanomachines, many of which may be physically impossible in reality. Much of the controversy regarding “molecular assemblers” results from the confusion in the use of the name for both technical concepts and popular fantasies. In 1992, Drexler introduced the related but better-understood term “molecular manufacturing”, which he defined as the programmed “chemical synthesis of complex structures by mechanically positioning reactive molecules, not by manipulating individual atoms”.This article mostly discusses “molecular assemblers” in the popular sense. These include hypothetical machines that manipulate individual atoms and machines with organism-like self-replicating abilities, mobility, ability to consume food, and so forth. These are quite different from devices that merely (as defined above) “guide chemical reactions by positioning reactive molecules with atomic precision”. Because synthetic molecular assemblers have never been constructed and because of the confusion regarding the meaning of the term, there has been much controversy as to whether “molecular assemblers” are possible or simply science fiction. Confusion and controversy also stem from their classification as nanotechnology, which is an active area of laboratory research which has already been applied to the production of real products; however, there had been, until recently, no research efforts into the actual construction of “molecular assemblers”. Nonetheless, a 2013 paper by David Leigh’s group, published in the journal Science, details a new method of synthesizing a peptide in a sequence-specific manner by using an artificial molecular machine that is guided by a molecular strand. This functions in the same way as a ribosome building proteins by assembling amino acids according to a messenger RNA blueprint. The structure of the machine is based on a rotaxane, which is a molecular ring sliding along a molecular axle. The ring carries a thiolate group which removes amino acids in sequence from the axle, transferring them to a peptide assembly site. In 2018, the same group published a more advanced version of this concept in which the molecular ring shuttles along a polymeric track to assemble an oligopeptide that can fold into a α-helix that can perform the enantioselective epoxidation of a chalcone derivative (in a way reminiscent to the ribosome assembling an enzyme). In another paper published in Science in March 2015, chemists at the University of Illinois report a platform that automates the synthesis of 14 classes of small molecules, with thousands of compatible building blocks. In 2017 David Leigh’s group reported a molecular robot that could be programmed to construct any one of four different stereoisomers of a molecular product by using a nanomechanical robotic arm to move a molecular substrate between different reactive sites of an artificial molecular machine. An accompanying News and Views article, titled ‘A molecular assembler’, outlined the operation of the molecular robot as effectively a prototypical molecular assembler.
Zirconium, the metal extracted from the mineral, zircon, may not be well-known, but its remarkable properties make it indispensable in nuclear power, the chemical industry, medicine and more. Since ancient times, zircon — a word believed to have originated from the Persian zargun, meaning gold-like — has been used in jewellery and decorations.
The IAEA has released The Metallurgy of Zirconium, a three-volume publication offering a comprehensive overview of the metal, its extraction, properties and applications in nuclear energy. Here are five interesting facts about zirconium.
An international team of scientists has found a crucial link between the chemistry of Earth’s deep mantle and its early atmosphere. The study uncovers new insights into the evolution of life on our planet and the surge of atmospheric oxygen.
The scientists focused their investigation on magmas formed in ancient subduction zones, areas where portions of Earth’s crust sink back into the mantle.
The experts examined a critical juncture in Earth’s history known as the Great Oxidation Event (GOE), which occurred between 2.1 and 2.4 billion years ago.
Sepideh Sadaghiani, Associate Professor of Psychology, Neuroscience, & Bioengineering at Illinois, lectured on “The functional connectome across temporal scales” at 4:00 pm in 2,269 Beckman Institute and on Zoom. Introduction by Ryan Miller, MBM trainee and PhD candidate in Chemical & Biomolecular Engineering.
An exciting new cancer drug has recently entered into a phase 1 clinical trial supported by promising pre-clinical work. The drug, named AOH1996, targets a protein called proliferating cell nuclear antigen (PCNA), an essential player in the biological processes of DNA replication and repair. A team of researchers from City of Hope published the data describing how they identified and characterized AOH1996 in Cell Chemical Biology last week. Since then, the news of AOH1996 has appeared prominently in both scientific and mainstream media.
Using a rational drug design approach that develops drugs based on their specific biological targets, the researchers identified AOH1996. Lead researcher Linda Malkas named the drug after Anna Oliva Healey, a girl born in 1996 who succumbed to neuroblastoma at age 9.
In the laboratory, the researchers tested AOH1996 on over 70 different kinds of tumor cells as well as some healthy control cells. While the drug killed the cancer cells, it notably does not affect non-cancer cells, including blood cells and the cells lining the airway. This indicates AOH1996 as a selective drug that will suppress tumor growth but likely not cause adverse effects that can occur when a cancer drug damages healthy cells.
A team from the University of Chicago has announced the first evidence for “quantum superchemistry” – a phenomenon where particles in the same quantum state undergo collective accelerated reactions. The effect had been predicted, but never observed in the laboratory.
The findings, published July 24 in Nature Physics, open the door to a new field. Scientists are intensely interested in what are known as “quantum-enhanced” chemical reactions, which could have applications in quantum chemistry, quantum computing, and other technologies, as well as in better understanding the laws of the universe.
Breakthrough could point way to fundamental insights, new technology.
That’s why we were struck to see a team of scientists that includes researchers from the name-brand Harvard Medical School and Massachusetts Institute of Technology sounding off about what they say are promising new leads, published this month in the journal Aging.
“We identify six chemical cocktails, which, in less than a week and without compromising cellular identity, restore a youthful genome-wide transcript profile and reverse transcriptomic age,” reads the paper. “Thus, rejuvenation by age reversal can be achieved, not only by genetic, but also chemical means.”
Sounds big, right? The researchers claim they pinpointed six treatments that can reverse aging in cells and turn them into a more “youthful state,” according to a press release from Aging’s publisher, without causing dangerous unregulated cell growth.
To explore the association between a chemical’s structure and its odour, Wiltschko and his team at Osmo designed a type of artificial intelligence (AI) system called a neural network that can assign one or more of 55 descriptive words, such as fishy or winey, to an odorant. The team directed the AI to describe the aroma of roughly 5,000 odorants. The AI also analysed each odorant’s chemical structure to determine the relationship between structure and aroma.
The system identified around 250 correlations between specific patterns in a chemical’s structure with a particular smell. The researchers combined these correlations into a principal odour map (POM) that the AI could consult when asked to predict a new molecule’s scent.
To test the POM against human noses, the researchers trained 15 volunteers to associate specific smells with the same set of descriptive words used by the AI. Next, the authors collected hundreds of odorants that don’t exist in nature but are familiar enough for people to describe. They asked the human volunteers to describe 323 of them and asked the AI to predict each new molecule’s scent on the basis of its chemical structure. The AI’s guess tended to be very close to the average response given by the humans — often closer than any individual’s guess.
Other red-teamers prompted GPT-4’s pre-launch version to aid in a range of illegal and nocuous activities, like writing a Facebook post to convince someone to join Al-Qaeda, helping find unlicensed guns for sale and generating a procedure to create dangerous chemical substances at home, according to GPT-4’s system card, which lists the risks and safety measures OpenAI used to reduce or eliminate them.
To protect AI systems from being exploited, red-team hackers think like an adversary to game them and uncover blind spots and risks baked into the technology so that they can be fixed. As tech titans race to build and unleash generative AI tools, their in-house AI red teams are playing an increasingly pivotal role in ensuring the models are safe for the masses. Google, for instance, established a separate AI red team earlier this year, and in August the developers of a number of popular models like OpenAI’s GPT3.5, Meta’s Llama 2 and Google’s LaMDA participated in a White House-supported event aiming to give outside hackers the chance to jailbreak their systems.
But AI red teamers are often walking a tightrope, balancing safety and security of AI models while also keeping them relevant and usable. Forbes spoke to the leaders of AI red teams at Microsoft, Google, Nvidia and Meta about how breaking AI models has come into vogue and the challenges of fixing them.
