Lifeboat Foundation

Max Planck scientists explore the possibilities of artificial intelligence in materials science and publish their review in the journal Nature Computational Science.

Advanced materials become increasingly complex due to the high requirements they have to fulfil regarding sustainability and applicability. Dierk Raabe, and colleagues reviewed the use of artificial intelligence in materials science and the untapped spaces it opens if combined with physics-based simulations. Compared to traditional simulation methods, AI has several advantages and will play a crucial role in material sciences in the future.

Advanced materials are urgently needed for everyday life, be it in high technology, mobility, infrastructure, green energy or medicine. However, traditional ways of discovering and exploring new materials encounter limits due to the complexity of chemical compositions, structures and targeted properties. Moreover, new materials should not only enable novel applications, but also include sustainable ways of producing, using and recycling them.

Summary: A newly designed dry sensor that can measure brain activity may someday enable mind control of robotic systems.

Source: American Chemical Society.

It sounds like something from science fiction: Don a specialized, electronic headband and control a robot using your mind. But now, recent research published in ACS Applied Nano Materials has taken a step toward making this a reality.

Advanced materials are urgently needed for everyday life, be it in high technology, mobility, infrastructure, green energy or medicine. However, traditional ways of discovering and exploring new materials encounter limits due to the complexity of chemical compositions, structures and targeted properties. Moreover, new materials should not only enable novel applications, but also include sustainable ways of producing, using and recycling them.

Researchers from the Max-Planck-Institut für Eisenforschung (MPIE) review the status of physics-based modelling and discuss how combining these approaches with artificial intelligence can open so far untapped spaces for the design of complex materials.

They published their perspective in the journal Nature Computational Science (“Accelerating the design of compositionally complex materials via physics-informed artificial intelligence”).

Chemically modifying the ends of the molecules opens the door to glass that could decompose with organic waste.

This year’s NVIDIA GPU Technology Conference (GTC) could not have come at a more auspicious time for the company. The hottest topic in technology today is the Artificial Intelligence (AI) behind ChatGPT, other related Large Language Models (LLMs), and their applications for generative AI applications. Underlying all this new AI technology are NVIDIA GPUs. NVIDIA’s CEO Jensen Huang doubled down on support for LLMs and the future of generative AI based on it. He’s calling it “the iPhone moment for AI.” Using LLMs, AI computers can learn the languages of people, programs, images, or chemistry. Using the large knowledge base and based on a query, they can create new, unique works: this is generative AI.

Jumbo sized LLM’s are taking this capability to new levels, specifically the latest GPT 4.0, which was introduced just prior to GTC. Training these complex models takes thousands of GPUs, and then applying these models to specific problems require more GPUs as well for inference. Nvidia’s latest Hopper GPU, the H100, is known for training, but the GPU can also be divided into multiple instances (up to 7), which Nvidia calls MIG (Multi-Instance GPU), to allow multiple inference models to be run on the GPU. It’s in this inference mode that the GPU transforms queries into new outputs, using trained LLMs.

Nvidia is using its leadership position to build new business opportunities by being a full-stack supplier of AI, including chips, software, accelerator cards, systems, and even services. The company is opening up its services business in areas such as biology, for example. The company’s pricing might be based on use time, or it could be based on the value of the end product built with its services.

Engineers at MIT and the University of Massachusetts Medical School have designed a new type of nanoparticle that can be administered to the lungs, where it can deliver messenger RNA encoding useful proteins.

With further development, these particles could offer an inhalable treatment for cystic fibrosis and other diseases of the lung, the researchers say.

“This is the first demonstration of highly efficient delivery of RNA to the lungs in mice. We are hopeful that it can be used to treat or repair a range of genetic diseases, including cystic fibrosis,” says Daniel Anderson, a professor in MIT’s Department of Chemical Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science (IMES).

Turning genes on and off as easily and predictably as flicking a switch could be a powerful tool in medicine and biotech. A type of technology called a riboswitch might be the key. The Okinawa Institute of Science and Technology (OIST) in Japan, in collaboration with Astellas Pharma Inc., has developed a new toolkit that uses small molecules to control the activity of a piece of synthetic RNA, and ultimately regulate gene expression. The technology, which was described in the Journal of the American Chemical Society, worked in mammalian cell cultures and in mice.

The ability to precisely control whether a gene is turned on or off is expected to lead to more efficient production of compounds that are made using animal cells, and make gene therapy, cell therapy, and regenerative medicine safer.

For genes to be expressed, cells make many RNA copies of a section of DNA. These RNA copies, called transcripts, are then used to make the protein. This can lead to the introduction of additional genes (either as DNA or RNA) into cells, which can then be used to make new proteins for a wide variety of applications.

Nanomedicine uses nanomaterials [e.g., carbon nanotubes (CNTs), nanoparticles, and nanodiscs] or organic nanostructures (e.g., DNA origami and liposomes) for drug delivery (8–10), medical imaging (11–14), and tissue regeneration (15). Nanomaterials offer therapeutic efficacy through their tissue permeation, interaction with an external energy source, and capability to be combined with other therapeutic modalities (16, 17). Because we recently demonstrated that GBM cells are mechanosensitive (18), we set to use nanomaterials to develop a nanoscale mechanical approach to treat GBM. Mechanical perturbation has been investigated as an approach to target cancer cells. For example, magnetic field–actuated nanomaterials compromise the integrity of plasma membrane, leading to the death of in vitro–cultured GBM cells (19) and breast cancer cells (20). GBM cells, which were preincubated with magnetic nanoparticles, were implanted into mice to generate xenograft tumors. A rotating magnetic field, which was then applied to these magnetic particles–harboring tumors, suppressed GBM growth (21). Similarly, magnetic field mobilization of mitochondria-targeting magnetic nanoparticle chains demonstrated efficacy in inhibiting GBM growth in mice (22). While these studies showed that magnetic field–controlled nanomaterials can be used in cancer treatment, the utility of magnetic nanomaterials in treating chemoresistant tumors, the root cause of tumor relapse and patient death, remains unexplored.

GBM displays an extreme level of heterogeneity at genomic, epigenetic, biochemical signaling, and cellular composition levels (23). The heterogeneous nature of GBM confers treatment resilience to tumors and leads to a unifying therapy resistance mechanism; i.e., suppressing selected proteins or biochemical pathways provides a fertile ground for alternative signaling mechanisms, which are not targeted by the given therapy, to fuel GBM growth (24). In other words, the “whack-a-mole” approach failed to benefit patients with GBM for decades. For this reason, we hypothesized that nanomaterial-based mechanical treatment of cancer cells, rather than specific targeting of signaling pathways, can overcome the therapy resistance of this biologically plastic disease. To this end, we engineered a mechanical nanosurgery approach using magnetic CNTs (mCNTs; nanotubes with carbon surface and a cavity filled with iron particles) based on the following reasons.

The first possible scenarios for life’s origin is that life may simply have been a miracle. It may have been a divine act of intervention. If so, then the origin of life is not a scientific question. There is no experiment one can propose or an observation one can make.

Yet, it’s equally possible that the origin of life was an event that’s fully consistent with the known laws of physics and chemistry, but an extremely improbable, perhaps unique event; perhaps an event that only took place on Earth. Once again, it’s really not amenable to scientific study, because we can’t go into the laboratory and study a unique event.

And then there is a third possibility, and that’s that life is an inevitable consequence of chemistry. That, given an appropriate environment—an appropriate planet with water, for example—and sufficient time, that life always arises.