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Category: chemistry – Page 38

Enhancement of Li+ transport through intermediate phase in high-content inorganic composite quasi-solid-state electrolytes

Quasi-solid-state electrolytes promise the safety of ceramics, the flexibility of polymers, and the conductivity of liquids—yet the “how” behind their superior ion transport has remained murky. Now, a joint team from Fudan University and the National Institute for Cryogenic & Isotopic Technologies (Romania), led by Professors Aishui Yu and Tao Huang, delivers a decisive answer in Nano-Micro Letters. Their review, “Enhancement of Li⁺ Transport Through Intermediate Phase in High-Content Inorganic Composite Electrolytes,” decodes the hidden chemistry that lets lithium sprint across solid/liquid boundaries.

The Secret Sauce: Acidic Interfaces

Ultrafast untethered levitation device offers frictionless design for omni-directional transport

Advances in technology have led to the miniaturization of many mechanical, electronic, chemical and biomedical products, and with that, an evolution in the way these tiny components and parts are transported is necessary to follow. Transport systems, such as those based on conveyor belts, suffer from the challenge of friction, which drastically slows the speed and precision of small transport.

Researchers from Yokohama National University addressed this issue by developing an untethered levitation device capable of moving in all directions. The frictionless design allows for ultrafast, agile movement that can prove to be very valuable in machine assembly, biomedical and chemical applications via contactless transport.

The results are published in the journal Advanced Intelligent Systems.

Small But Mighty: How is Nanotechnology Powering AI?

The limitations of conventional semiconductor technology have become increasingly apparent as AI applications require exponentially larger computational resources. Once the engines of rapid technological advances, silicon-based transistors are now encountering fundamental physical constraints at the nanoscale that inhibit further scaling and performance enhancement. Moore’s law, which predicted the doubling of transistors on a chip every two years, is running out of space.

On top of that, the breakdown of Dennard scaling, which once enabled simultaneous improvements in speed, power efficiency, and density, has further intensified the need for alternative materials and device architectures capable of sustaining AI-driven workloads.

This is where nanotechnology comes in. Working on a nanoscale offers a pathway to overcome the constraints of conventional tech, enabling the precise manipulation of materials at the atomic and molecular levels, typically within the one to 100 nanometer range.

At this minute scale, materials exhibit unique physical, chemical, and electrical characteristics. These small-scale properties can enable faster operation, lower energy consumption, and can be used to deliver complex functionalities within a single nanoscale architecture.

Discover how nanotechnology is advancing AI with energy-efficient chips, in-memory computing, neuromorphic hardware, and nanoscale data storage solutions.

Northeastern researchers identify proteins receptive to treating ovarian cancer

Researchers at Northeastern University have identified two proteins abundant on drug-resistant ovarian cancer cells that become receptive to chemotherapy when treated with light.

Published in the journal Photochemistry and Photobiology, the research findings represent promising progress in the treatment of one of the most deadly forms of cancer. By targeting cancer cells with photo-sensitive antibodies and then shining light on them, researchers have made previously untreatable tumors receptive to drugs.

(This may be a repost, but still cool. Reposts are cool because it is a sign of something to pay attention to.)

Researchers have developed a light-based ovarian cancer therapy that makes tumors more receptive to chemotherapy.

Computational framework sheds light on how the brain’s decision-making is impacted in psychiatric disorders

Scientists from the Icahn School of Medicine at Mount Sinai, working in collaboration with a team from the University of Texas at El Paso, have developed a novel computational framework for understanding how a region of the brain known as the striatum is involved in the everyday decisions we make and, importantly, how it might factor into impaired decision-making by individuals with psychiatric disorders like post-traumatic stress disorder and substance use disorder.

In a study published in Nature Communications, the team reported that modulating activity within the striosomal compartment—a neurochemically discrete area of the striatum—might be an important therapeutic strategy for promoting healthier in people with psychiatric disorders.

“Though it has been established that the striatum is clearly important for cost-benefit decision-making, the precise role of the striosomal compartment has remained elusive,” says Ki Goosens, Ph.D., Associate Professor of Pharmacological Sciences and Psychiatry, at the Icahn School of Medicine at Mount Sinai and co-lead author of the study.

AI breakthrough designs peptide drugs to target previously untreatable proteins

A study published in Nature Biotechnology reveals a powerful new use for artificial intelligence: designing small, drug-like molecules that can stick to and break down harmful proteins in the body — even when scientists don’t know what those proteins look like. The breakthrough could lead to new treatments for diseases that have long resisted traditional drug development, including certain cancers, brain disorders, and viral infections.

The study was published on August 13, 2025 by a multi-institutional team of researchers from McMaster University, Duke University, and Cornell University. The AI tool, called PepMLM, is based on an algorithm originally built to understand human language and used in chatbots, but was trained to understand the “language” of proteins.

In 2024, the Nobel Prize in Chemistry was awarded to researchers at Google DeepMind for developing AlphaFold, an AI system that predicts the 3D structure of proteins – a major advance in drug discovery. But many disease-related proteins, including those involved in cancer and neurodegeneration, don’t have stable structures. That’s where PepMLM takes a different approach – instead of relying on structure, the tool uses only the protein’s sequence to design peptide drugs. This makes it possible to target a much broader range of disease proteins, including those that were previously considered “undruggable.”

Cubosome-based method for loading mRNA into exosomes

Exosomes, naturally derived vesicles responsible for intercellular communication, are emerging as next-generation drug delivery systems capable of transporting therapeutics to specific cells. However, their tightly packed, cholesterol-rich membranes make it extremely difficult to encapsulate large molecules such as mRNA or proteins.

Conventional approaches have relied on techniques like electroporation or chemical treatment, which often damage both the drugs and exosomes, reduce delivery efficiency, and require complex purification steps—all of which pose significant barriers to commercialization.

The team utilized a lipid-based nanoparticle known as a “cubosome,” which mimics the fusion structure of cell membranes and naturally fuses with exosomes. By mixing cubosomes carrying mRNA with exosomes at room temperature for just 10 minutes, the researchers achieved efficient fusion and confirmed that the mRNA was successfully loaded into the exosomes. Analysis showed that over 98% of the mRNA was encapsulated, while the structural integrity and biological function of the exosomes were preserved.

Furthermore, the engineered exosomes demonstrated the ability to cross the blood-brain barrier, one of the most difficult hurdles in drug delivery. Notably, the team observed a “homing” effect, where exosomes return to the type of cell they originated from, enabling targeted drug delivery to diseased tissues.

Bioelectrosynthesis platform enables switch-like, precision control of cell signaling

Cells use various signaling molecules to regulate the nervous, immune, and vascular systems. Among these, nitric oxide (NO) and ammonia (NH₃) play important roles, but their chemical instability and gaseous nature make them difficult to generate or control externally.

A KAIST research team has developed a platform that generates specific signaling molecules in situ from a single precursor under an applied electrical signal, enabling switch-like, precise spatiotemporal control of cellular responses. This approach could provide a foundation for future medical technologies such as electroceuticals, electrogenetics, and personalized cell therapies.

The research team led by Professor Jimin Park from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Jihan Kim’s group, has developed a bioelectrosynthesis platform capable of producing either or on demand using only an electrical signal. The platform allows control over the timing, spatial range, and duration of cell responses.

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