The world’s climate is on the brink of disaster, with brutal droughts, melting glaciers, and devastating natural disasters ravaging our planet every year. A significant contributor to this crisis is the constant emission of carbon dioxide into the atmosphere, primarily through concrete production. However, a team of researchers at the USC Viterbi School of Engineering has made a groundbreaking discovery that could change everything.

Led by Professors Aiichiro Nakano and Ken-Ichi Nomura, the team developed an artificial intelligence-driven simulation model called Allegro-FM. This revolutionary AI model can simulate the behavior of billions of atoms simultaneously, opening new possibilities for materials design and discovery at unprecedented scales.

The breakthrough lies in the model’s scalability, which is roughly 1,000 times larger than conventional approaches. Allegro-FM demonstrated 97.5% efficiency when simulating over four billion atoms on the Aurora supercomputer at Argonne National Laboratory. This represents computational capabilities that can accurately predict molecular behavior for applications ranging from cement chemistry to carbon storage.

The implications are staggering. Concrete is a fire-resistant material, making it an ideal building choice in areas prone to wildfires. However, concrete production is also a significant emitter of carbon dioxide, a particularly concerning environmental problem in cities like Los Angeles. Allegro-FM has been shown to be carbon neutral, making it a better choice than other concrete.

Moreover, this breakthrough doesn’t only solve one problem. Ancient Roman concrete has lasted for over 2,000 years, whereas modern concrete typically lasts about 100 years on average. The recapture of CO2 can help extend the lifespan of concrete structures, making them more robust and durable.

The professors leading this research have an appreciation for how AI has been an accelerator of their complex work. Normally, to simulate the behavior of atoms, they would need a precise series of mathematical formulas. However, the last two years have changed the way they approach this challenge.

“Now, because of this machine-learning AI breakthrough, instead of deriving all these quantum mechanics from scratch, researchers are taking [the] approach of generating a training set and then letting the machine learning model run,” Nomura said.

This makes their process much faster and more efficient in its technology use. Allegro-FM can accurately predict “interaction functions” between atoms, which would require lots of individual simulations normally.

The traditional approach is to simulate a certain set of materials. However, this new system is also a lot more efficient on the technology side, with AI models making lots of precise calculations that used to be done by a large supercomputer, simplifying tasks and freeing up that supercomputer’s resources for more advanced research.

“[The AI can] achieve quantum mechanical accuracy with much, much smaller computing resources,” Nakano said.

Nomura and Nakano say their work is far from over. They will certainly continue this concrete study research, making more complex geometries and surfaces. This research was published recently in The Journal of Physical Chemistry Letters and was featured as the journal’s cover image.

The scientists at the University of Stuttgart and the Max Planck Institute for Solid State Research have made a groundbreaking discovery in DNA nanotechnology. They’ve developed an innovative approach to create moiré superlattices, a type of material that has been widely explored at the atomic and photonic scales but remained inaccessible at the intermediate nanometer regime.

By combining two powerful DNA nanotechniques – DNA origami and single-stranded tile assembly – the researchers have successfully constructed micrometer-scale superlattices with unit cell dimensions as small as 2.2 nanometers, featuring tunable twist angles and various lattice symmetries. This breakthrough has unlocked entirely new design possibilities at the nanoscale.

The study introduces a new growth process for moiré superlattices, initiated by spatially defined capture strands on the DNA seed that act as molecular ‘hooks’ to precisely bind single-stranded tiles (SSTs) and direct their interlayer alignment. This enables the controlled formation of twisted bilayers or trilayers with accurately aligned SST sublattices.

The new moiré superlattices have significant potential for diverse applications in research and technology, including:

* Nanoscale components with customized 2D and 3D architectures
* Phononic crystals or mechanical metamaterials with tunable vibrational responses
* Gradient-index photonic devices with controlled light or sound trajectories
* Spin-selective electron transport platforms to explore topological spin transport phenomena

“This is not about mimicking quantum materials,” says Laura Na Liu, director of the 2nd Physics Institute at the University of Stuttgart. “It’s about expanding the design space and making it possible to build new types of structured matter from the bottom up, with geometric control embedded directly into the molecules.”

The study has been published in the journal Nature Nanotechnology and has far-reaching implications across molecular engineering, nanophotonics, spintronics, and materials science.

The study published in Royal Society Open Science presents a groundbreaking approach to understanding the mechanical properties of crystals. Researchers from The University of Osaka have successfully used differential geometry to provide a unified description for the mechanics of crystals and their defects. This breakthrough has significant implications for the development of new materials with enhanced strength and durability.

Crystals, renowned for their beauty and elegance, often appear perfect on the outside. However, upon closer examination, they contain small defects in their structure – missing atoms or extra bonds. These imperfections have important mechanical consequences, as they can serve as starting points for fractures or even be used to strengthen materials. Understanding defects and their phenomena is crucial for researchers.

The study’s lead author, Shunsuke Kobayashi, notes that “defects come in many forms.” For instance, there are dislocations associated with the breaking of translational symmetry and disclinations associated with the breaking of rotational symmetry. Capturing all these types of defects within a single mathematical theory is not straightforward.

Previous models have struggled to reconcile the differences between dislocations and disclinations, indicating that modifications to the theory are needed. The research team found that new mathematical tools using differential geometry proved to be exactly what was required to address these issues.

Differential geometry provides an elegant framework for describing these complex phenomena. Simple mathematical operations can capture these effects, allowing researchers to focus on the similarities between seemingly disparate defects. Using the formalism of Riemann-Cartan manifolds, the team elegantly encapsulated the topological properties of defects and rigorously proved the relationship between dislocations and disclinations.

In addition, they derived analytical expressions for the stress fields caused by these defects. The research team hopes that their geometric approach to describing the mechanics of crystals will eventually inspire scientists and engineers to design materials with specific properties by taking advantage of defects, such as the strengthening of materials seen with disclinations. This breakthrough is yet another example of how beauty in mathematics can help us understand beauty in nature.