A new exciting life detection toolset for exploration of an alien planet or moon.
Life detection on Mars and the icy moons of the outer Solar System looks more and more feasible.
For the past 70 years, most of humanity’s rockets have been chemical rockets- with either liquid or solid fuel. However, it may be possible for future rockets to use different fuel sources.
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Circa 2017
Imagine materials strong enough to use in building airplanes or motor cars, yet are literally lighter than air. Soon, that may not be so hard to do because a team of researchers from MIT and Lawrence Livermore National Laboratory (LLNL) have developed new ultra-lightweight materials that are as light as aerogel, but 10,000 times stiffer, and may one day revolutionize aerospace and automotive designs.
Aerogels are incredibly light, so light that the record holder, aerographene, boasts a density of just 0.16 mg/cm3. Currently, aerogels are used for insulation, tennis racquets, as a means of controlling oil spills, and were used on the NASA Stardust mission to collect samples from a comet’s tail. Unfortunately, despite its seemingly ephemeral nature, its very much a solid and will shatter if pressed hard enough, so its use is limited.
Continue reading “New materials developed that are as light as aerogel, yet 10,000 times stronger” »
With moral purity inserted as a component to the internal processes for all academic publications, it will henceforth become impossible to pursue the vital schema of conjecture and refutation.
Shocked that one of their own could express a heterodox opinion on the value of de rigueur equity, diversity and inclusion policies, chemistry professors around the world immediately demanded the paper be retracted. Mob justice was swift. In an open letter to “our community” days after publication, the publisher of Angewandte Chemie announced it had suspended the two senior editors who handled the article, and permanently removed from its list of experts the two peer reviewers involved. The article was also expunged from its website. The publisher then pledged to assemble a “diverse group of external advisers” to thoroughly root out “the potential for discrimination and foster diversity at all levels” of the journal.
Not to be outdone, Brock’s provost also disowned Hudlicky in a press statement, calling his views “utterly at odds with the values” of the university; the school then drew attention to its own efforts to purge unconscious bias from its ranks and to further the goals of “accessibility, reconciliation and decolonization.” (None of which have anything to do with synthetic organic chemistry, by the way.) Brock’s knee-jerk criticism of Hudlicky is now also under review, following a formal complaint by another professor that the provost’s statement violates the school’s commitment to freedom of expression.
Physicists’ latest achievement with neutral atoms paves the way for new quantum computer designs.
In the quest to develop quantum computers, physicists have taken several different paths. For instance, Google recently reported that their prototype quantum computer might have made a specific calculation faster than a classical computer. Those efforts relied on a strategy that involves superconducting materials, which are materials that, when chilled to ultracold temperatures, conduct electricity with zero resistance. Other quantum computing strategies involve arrays of charged or neutral atoms.
Now, a team of quantum physicists at Caltech has made strides in work that uses a more complex class of neutral atoms called the alkaline-earth atoms, which reside in the second column of the periodic table. These atoms, which include magnesium, calcium, and strontium, have two electrons in their outer regions, or shells. Previously, researchers who experimented with neutral atoms had focused on elements located in the first column of the periodic table, which have just one electron in their outer shells.
Recent advancements in quantum computing have driven the scientific community’s quest to solve a certain class of complex problems for which quantum computers would be better suited than traditional supercomputers. To improve the efficiency with which quantum computers can solve these problems, scientists are investigating the use of artificial intelligence approaches.
In a new study, scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory have developed a new algorithm based on reinforcement learning to find the optimal parameters for the Quantum Approximate Optimization Algorithm (QAOA), which allows a quantum computer to solve certain combinatorial problems such as those that arise in materials design, chemistry and wireless communications.
“Combinatorial optimization problems are those for which the solution space gets exponentially larger as you expand the number of decision variables,” said Argonne computer scientist Prasanna Balaprakash. “In one traditional example, you can find the shortest route for a salesman who needs to visit a few cities once by enumerating all possible routes, but given a couple thousand cities, the number of possible routes far exceeds the number of stars in the universe; even the fastest supercomputers cannot find the shortest route in a reasonable time.”
A team of researchers with Google’s AI Quantum team (working with unspecified collaborators) has conducted the largest chemical simulation on a quantum computer to date. In their paper published in the journal Science, the group describes their work and why they believe it was a step forward in quantum computing. Xiao Yuan of Stanford University has written a Perspective piece outlining the potential benefits of quantum computer use to conduct chemical simulations and the work by the team at AI Quantum, published in the same journal issue.
Developing an ability to predict chemical processes by simulating them on computers would be of great benefit to chemists—currently, they do most of it through trial and error. Prediction would open up the door to the development of a wide range of new materials with still unknown properties. Sadly, current computers lack the exponential scaling that would be required for such work. Because of that, chemists have been hoping quantum computers will one day step in to take on the role.
Current quantum computer technology is not yet ready to take on such a challenge, of course, but computer scientists are hoping to get them there sometime in the near future. In the meantime, big companies like Google are investing in research geared toward using quantum computers once they mature. In this new effort, the team at AI Quantum focused their efforts on simulating a simple chemical process—the Hartree-Fock approximation of a real chemical system—in this particular case, a diazene molecule undergoing a reaction with hydrogen atoms, resulting in an altered configuration.
Accurate computational prediction of chemical processes from the quantum mechanical laws that govern them is a tool that can unlock new frontiers in chemistry, improving a wide variety of industries. Unfortunately, the exact solution of quantum chemical equations for all but the smallest systems remains out of reach for modern classical computers, due to the exponential scaling in the number and statistics of quantum variables. However, by using a quantum computer, which by its very nature takes advantage of unique quantum mechanical properties to handle calculations intractable to its classical counterpart, simulations of complex chemical processes can be achieved. While today’s quantum computers are powerful enough for a clear computational advantage at some tasks, it is an open question whether such devices can be used to accelerate our current quantum chemistry simulation techniques.
In “Hartree-Fock on a Superconducting Qubit Quantum Computer”, appearing today in Science, the Google AI Quantum team explores this complex question by performing the largest chemical simulation performed on a quantum computer to date. In our experiment, we used a noise-robust variational quantum eigensolver (VQE) to directly simulate a chemical mechanism via a quantum algorithm. Though the calculation focused on the Hartree-Fock approximation of a real chemical system, it was twice as large as previous chemistry calculations on a quantum computer, and contained ten times as many quantum gate operations. Importantly, we validate that algorithms being developed for currently available quantum computers can achieve the precision required for experimental predictions, revealing pathways towards realistic simulations of quantum chemical systems.
Our kidneys are crucial for keeping us alive and healthy. A sort of chemical computer that keeps our blood chemistry stable—whether we’re eating a sugary birthday cake or a vitamin-filled salad—they prevent waste buildup, stabilize our electrolyte levels, and produce hormones to regulate our blood pressure and make red blood cells.
Kidneys clean our blood using nephrons, which are essentially filters that let fluid and waste products through while blocking blood cells, proteins, and minerals. The latter get reintegrated into the blood, and the former leave the body in urine.
Scientists have struggled to come up with viable treatments for kidney disease and renal failure, and their complexity means kidneys are incredibly hard to synthetically recreate; each kidney contains around one million intricately-structured nephrons.
