Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: chemistry

Carbon nanotubes are closing the gap on copper conductivity

Carbon nanotubes are one technology that many observers believe hasn’t quite lived up to the extreme hype that surrounded them when they first appeared on the scene in the late 1990s. At that time, much was made of their extraordinary electrical, thermal, and mechanical properties, with predictions that they would revolutionize materials science, electronics, and daily life. But could we be closer to realizing some of that promise?

In a paper published in the journal Science, researchers describe a method for adding a chemical to carbon nanotube bundles that brings them closer to copper’s ability to conduct electricity.

Carbon nanotubes are nanoscale hollow cylinders of carbon atoms, a structure that allows electricity to flow through them with very low resistance. However, when you bundle millions of them together, as you would need for practical applications like power lines and electrical wiring, they lose some of their exceptional conductivity. Electrons move easily along individual nanotubes, but transferring charge between neighboring tubes in a bundle is much less efficient.

Natural-language AI helps chemists design molecules step by step

Designing molecules is one of chemistry’s most complex challenges. From life-saving drugs to advanced materials, each compound requires a precise sequence of reactions. Planning these steps demands both technical knowledge and strategic insight, making it a task that often relies on years of experience.

Two problems plague much of modern chemistry. The first is retrosynthesis: Chemists start from a target molecule and work backward to identify simpler building blocks and viable reaction pathways. Retrosynthesis involves countless decisions, from choosing starting materials to determining when to form rings or protect sensitive functional groups. While computers can explore vast “chemical spaces,” they often struggle to capture the strategic reasoning used by human experts.

The second problem is reaction mechanisms. These describe how chemical reactions unfold step by step through the movements of electrons. Mechanistic insight helps scientists predict new reactions, improve efficiency, and reduce costly trial and error. Existing computational methods can generate many possible pathways, but often lack the chemical intuition needed to identify the most plausible ones.

Chromosomes condense in three timed chemical waves during cell division, study shows

DNA does not float freely in the cell. Instead, it is wrapped around histone proteins to form structures called nucleosomes. These histones carry numerous chemical modifications that act as molecular signals, controlling how tightly the DNA is packaged and which genes are active. During cell division, this DNA-histone complex—known as chromatin—must be further condensed into compact, rod-shaped chromosomes. Histone modifications play a key role in this process: They change significantly during condensation and regulate the conversion of chromatin.

For the first time, researchers have precisely tracked how molecular marks on DNA proteins change during cell division—and disproved a long-held assumption in the process.

An international research team led by Professor Axel Imhof at LMU’s Biomedical Center and Professor William Earnshaw (University of Edinburgh) has analyzed these changes during cell division with unprecedented precision. To this end, the researchers developed an innovative method that synchronizes the division of cell populations. They then employed high-resolution mass spectrometry to precisely record the changes in histone modifications during cell division. The findings are published in Molecular Cell.

How electron structure affects light responses in moiré materials

In materials science, if you can understand the “texture” of a material—how its internal patterns form and shift—you can begin to design how it behaves. That’s the focus of the work of Zhenglu Li, assistant professor in the Mork Family Department of Chemical Engineering and Materials Science at USC Viterbi School of Engineering. Li’s recently published paper in PNAS, titled “Moiré excitons in generalized Wigner crystals,” demonstrates that the way electrons organize themselves inside a material determines how that material responds to light—and how this organization can be engineered.

“Moiré” is a word that will be familiar to anyone who follows fashion. In the context of textiles, it refers to a larger-scale interference pattern that appears when two repeating patterns are slightly misaligned. Imagine brushing a swatch of velvet in different directions; the material reveals different properties depending on how it is ruffled.

Likewise, in the context of nanoscale materials science, an independent, shimmering or wavelike pattern is formed when two overlapping atomically thin layers are overlaid at an acute angle. The new pattern, moiré superlattice, changes how electrons move, which can give the material unusual properties.

Boosting good gut bacteria population through targeted interventions may slow cognitive decline

The origin of neurodegenerative diseases like Alzheimer’s or dementia isn’t limited to the brain. The state of your gut can quietly set off a cycle of chronic, system-wide inflammation that nudges the brain toward cognitive decline. But how does the pathogenesis of a disease that seems purely brain-based begin in the gut—an organ that is mostly busy producing chemicals for digesting food?

It turns out these two entities are linked by the gut-brain axis, a two-way communication superhighway that constantly sends signals between the digestive tract and the central nervous system. It runs on chemical messengers like neurotransmitters and fatty acids, sharing information that shapes our memory, mood, and inflammation triggers.

An analysis of 15 studies involving more than 4,200 participants found that the gut-brain highway can be put to work as a drug-free route to support cognitive health. Tuning the gut microbiota through diet, supplements, or medical interventions such as fecal microbiota transplantation (FMT) can help improve memory, executive function, and overall cognitive performance, particularly in early or mild cases of cognitive impairment.

Frontiers: Year 2020 this gene therapy in mice shows promise for als gene therapy in humans

Gene therapy is an emerging and powerful therapeutic tool to deliver functional genetic material to cells in order to correct a defective gene. During the past decades, several studies have demonstrated the potential of AAV-based gene therapies for the treatment of neurodegenerative diseases. While some clinical studies have failed to demonstrate therapeutic efficacy, the use of AAV as a delivery tool has demonstrated to be safe. Here, we discuss the past, current and future perspectives of gene therapies for neurodegenerative diseases. We also discuss the current advances on the newly emerging RNAi-based gene therapies which has been widely studied in preclinical model and recently also made it to the clinic.

Gene therapy is an emerging therapeutic tool used to deliver functional genetic material to cells in order to correct a defective gene. By delivering a copy of a therapeutic gene to affected cells, the product encoded by that gene [i.e., its messenger RNA (mRNA) and/or proteins] will be continuously synthesized within the cell, utilizing the cell’s own transcriptional and translational machinery (Porada et al., 2013). The main advantage of this technology is that it offers a potentially life-long therapeutic effect without the need for repeated administration. Gene therapy can be used to correct defective genes by introducing a functional copy of the gene, by silencing a mutant allele using RNA interference (RNAi), by introducing a disease-modifying gene, or by using gene-editing technology (Grimm and Kay, 2007; Dow et al., 2015; Saraiva et al., 2016).

Gene therapy vectors can be either viral or non-viral. Different physical and chemical systems can be applied to deliver therapeutic genes to cells without the need of a viral vector. Non-viral vectors have no size limitation for the therapeutic gene, generally have a low immunogenicity risk, and can be produced at relatively low costs (Nayerossadat et al., 2012). However, due to the fact that high therapeutic doses are required when using non-viral technologies, and the resulting gene expression is generally transient, most gene therapies now rely on viral vectors. Numerous viral vector types have been tested in clinic, including vaccinia, measles, vesicular stomatitis virus (VSV), polio, reovirus, adenovirus, lentivirus, γ-retrovirus, herpes simplex virus (HSV) and adeno-associated virus (AAV) (Lundstrom, 2018).

Machine learning identifies catalyst ‘sweet spot’ for greener urea from waste gases

Urea is an extremely important chemical, especially for fertilizers. But, making urea is energy intensive and relies heavily on fossil fuels. However, new findings from Griffith University and the Queensland University of Technology have highlighted new ways to produce urea electrochemically, using electricity and waste gases such as carbon monoxide (CO) and nitrogen oxides (NO) instead.

The paper, “Machine Learning-Assisted Design Framework of Carbon Edge-Dominated Dual-Atom Catalysts for Urea Electrosynthesis,” has been published in ASC Nano.

“The challenge is that when CO and NO react on a catalyst, they usually don’t form urea,” said co-lead author Professor Qin Li from Griffith University.

Anaerobic digestion of poultry droppings for biogas production: a pilot study of renewable energy technology in the agricultural sector

Proper management of agricultural waste is challenging due to diverse sources, high production volumes, seasonal fluctuations, limited technical knowledge, and insufficient funding. These challenges often lead to soil degradation, environmental pollution, and adverse effects on ecosystems and human health. This study aims to investigate biogas production from poultry droppings using Continuous Stirred Tank Reactor (CSTR) Anaerobic Digestion (AD) technology to promote green energy use and as a sustainable solution for agricultural waste management.

Dried poultry manure samples were collected from two poultry farms in Lafia city and from their manure disposal sources. The samples were thoroughly stirred to ensure homogeneity and digested at a mesophilic temperature of 28.0 °C. With an initial solid concentration of 20.0%, the manure was diluted with water at 1:2 ratio to produce an input slurry containing 12.0% total volatile solids by weight. The experiment was conducted from July 20 to September 10, 2025. Parameters including pH, alkalinity, temperature, and biogas flow rate were monitored daily. Chemical and physical analyses of total solids, total volatile solids, and chemical oxygen demand were conducted during startup using three biological replicates (n = 3), with results expressed using statistical tool of mean ± standard error. Volatile fatty acids and alkalinity were measured using the distillation method.

Atomic-level snapshots reveal how a key copper enzyme powers nature’s chemistry

Researchers from the University of Liverpool, Japan, and Argentina have captured atomic-resolution images of an important copper-containing enzyme using advanced X-ray Free Electron Laser (XFEL) technology at SACLA in Japan. XFEL technology generates ultra-bright, ultra-short X-ray pulses, enabling atomic-scale imaging and real-time observation of chemical, biological, and physical processes.

The international team—led by Dr. Svetlana Antonyuk and Professor Samar Hasnain at the University of Liverpool, Professor Takehiko Tosha at the University of Hyogo, and Dr. Masaki Yamamoto at RIKEN SPring-8—studied a protein that plays a key role in the global nitrogen cycle. This protein converts nitrite, an essential nitrogen intermediate, into nitric oxide gas.

The new details reveal how an enzyme called copper nitrite reductase (CuNiR) from three different organisms converts nitrite to nitric oxide gas, using an electron and a proton—a vital process for both biology and the environment.

AI accelerators deliver accurate models for challenging quantum chemistry calculations

The most demanding calculations in quantum chemistry can now be solved with graphics processing unit (GPU) supercomputers. A recently published study shows that software adapted to use GPU hardware can provide not just speed, but also the accuracy needed to solve complex chemistry problems. The work solved the two chemical structures often seen as too complex and expensive to tackle. The advance, published in the Journal of Chemical Theory and Computation, could allow researchers to make meaningful progress in designing new catalysts and improve predicted behaviors of magnetic and electronic materials.

Specifically, the research team—led by computational chemists from NVIDIA, Sandbox AQ, the Wigner Research Centre in Hungary, the Institute for Advanced Study of the Technical University of Munich in Germany, and the Department of Energy’s Pacific Northwest National Laboratory—showed that NVIDIA Blackwell architecture effectively tackles complex simulations. Here, the researchers used a mixture of mathematically precise and approximated approaches to accomplish their goal.

“Our study shows that AI-oriented hardware can do more than provide speed—it can also power chemically accurate, strongly correlated quantum chemistry at the frontier of what is computationally feasible,” said Sotiris Xantheas, a computational chemist at PNNL and study author. Xantheas also serves as the principal investigator of Scalable Predictive methods for Excitations and Correlated phenomena (SPEC), a Department of Energy initiative.

/* */