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Category: chemistry

IBM has just unveiled its boldest quantum computing roadmap yet: Starling, the first large-scale, fault-tolerant quantum computer—coming in 2029. Capable of running 20,000X more operations than today’s quantum machines, Starling could unlock breakthroughs in chemistry, materials science, and optimization.

According to IBM, this is not just a pie-in-the-sky roadmap: they actually have the ability to make Starling happen.

In this exclusive conversation, I speak with Jerry Chow, IBM Fellow and Director of Quantum Systems, about the engineering breakthroughs that are making this possible… especially a radically more efficient error correction code and new multi-layered qubit architectures.

We cover:
- The shift from millions of physical qubits to manageable logical qubits.
- Why IBM is using quantum low-density parity check (qLDPC) codes.
- How modular quantum systems (like Kookaburra and Cockatoo) will scale the technology.
- Real-world quantum-classical hybrid applications already happening today.
- Why now is the time for developers to start building quantum-native algorithms.

00:00 Introduction to the Future of Computing.
01:04 IBM’s Jerry Chow.
01:49 Quantum Supremacy.
02:47 IBM’s Quantum Roadmap.
04:03 Technological Innovations in Quantum Computing.
05:59 Challenges and Solutions in Quantum Computing.
09:40 Quantum Processor Development.
14:04 Quantum Computing Applications and Future Prospects.
20:41 Personal Journey in Quantum Computing.
24:03 Conclusion and Final Thoughts.

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N6-methyladenosine (m6A) is the most common and abundant endogenous mRNA methylation in eukaryotic cells (Huang et al., 2020; Wang et al., 2014). The regulation of this modification is achieved through the coordinated action of three distinct protein groups. The “writers” (methyltransferase complex), which include METTL3, METTL14, and WTAP, are responsible for adding the m6A modification. In contrast, the “erasers” (demethylases), which consist of FTO and ALKBH5, remove this chemical mark. Lastly, the “readers,” a group of proteins including YTHDF1/2/3 and YTHDC1/2, recognize and bind to m6A-modified RNA, thereby modulating diverse RNA metabolic processes. The m6A reader proteins YTHDFs exhibit distinct canonical functional roles: YTHDF1 primarily boosts the efficiency of mRNA translation, YTHDF2 enhances mRNA degradation, and YTHDF3 exerts dual functions by supporting both translation and degradation of mRNA, with its role varying depending on the specific biological context (Roundtree et al., 2017; Shi et al., 2017; Wang et al., 2014; Wang et al., 2015; Zaccara et al., 2019). Recent studies have revealed that YTHDF proteins can influence the efficacy of RT through mechanisms, such as modulating DNA repair and shaping the tumor immune microenvironment (TIME) (Du et al., 2023; Shao et al., 2023; Shi et al., 2023; Wang et al., 2023a; Wang et al., 2023c; Wen et al., 2024a; Yin et al., 2023). Elucidating the functions and mechanisms of YTHDF proteins within the context of radiation biology holds significant potential for advancing therapeutic strategies in cancer RT.

This review provides an overview of recent progress in elucidating the mechanisms by which YTHDF proteins in tumor and immune cells modulate the therapeutic efficacy of RT. By synthesizing current knowledge on the functions of YTHDF proteins in the context of IR, we emphasize their indispensable role in shaping RT outcomes.

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A team of chemists at the University of Cambridge has developed a powerful new method for adding single carbon atoms to molecules more easily, offering a simple one-step approach that could accelerate drug discovery and the design of complex chemical products.

The research, recently published in the journal Nature under the title “One-carbon homologation of alkenes,” unveils a breakthrough method for extending molecular chains—one carbon atom at a time. This technique targets alkenes, a common class of molecules characterized by a double bond between two carbon atoms. Alkenes are found in a wide range of everyday products, from anti-malarial medicines like quinine to agrochemicals and fragrances.

Led by Dr. Marcus Grocott and Professor Matthew Gaunt from the Yusuf Hamied Department of Chemistry at the University of Cambridge, the work replaces traditional multi-step procedures with a single-pot reaction that is compatible with a wide range of molecules.

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Sarin (isopropyl methyl fluorophosphonate) is an organophosphorus nerve agent regulated by the Convention on the Banning of Chemical Weapons. It can enter the body through the respiratory system, skin, or eyes, paralyzing the central nervous system by inhibiting acetylcholinesterase, which can lead to death. Therefore, rapid and sensitive detection of trace sarin is vital for safety and environmental protection.

Due to its high toxicity, sarin’s use is strictly controlled, leading researchers to use diethyl chlorophosphate (DCP) as a safer simulant. The common fluorescence detection method takes advantage of DCP’s strong electrophilicity, using recognition sites like hydroxyl oxime and imine for fluorescence quenching to identify the target.

However, this method is affected by photobleaching, acid, and other environmental factors, limiting its application.

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As artificial intelligence (AI) tools shake up the scientific workflow, Sam Rodriques dreams of a more systemic transformation. His start-up company, FutureHouse in San Francisco, California, aims to build an ‘AI scientist’ that can command the entire research pipeline, from hypothesis generation to paper production.

Today, his team took a step in that direction, releasing what it calls the first true ‘reasoning model’ specifically designed for scientific tasks. The model, called ether0, is a large language model (LLM) that’s purpose-built for chemistry, which it learnt simply by taking a test of around 500,000 questions. Following instructions in plain English, ether0 can spit out formulae for drug-like molecules that satisfy a range of criteria.

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Making a discovery with the potential for innovative applications in pharmaceutical development, a West Virginia University microbiology student has found a long sought-after fungus that produces effects similar to the semisynthetic drug LSD, which is used to treat conditions like depression, post-traumatic stress disorder and addiction.

Corinne Hazel, of Delaware, Ohio, an environmental microbiology major and Goldwater Scholar, discovered the new species of fungus growing in morning glory plants and named it Periglandula clandestina.

Hazel made the discovery while working in the lab with Daniel Panaccione, Davis-Michael Professor of Plant and Soil Sciences at the WVU Davis College of Agriculture and Natural Resources. She was studying how morning glories disperse protective chemicals called “ergot alkaloids” through their roots when she saw evidence of a fungus.

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Everything in nature has a geometric pattern—from the tiger’s stripes and spirals in flowers to the unique fingerprints of each human being. While these patterns are sometimes symmetrical, most of such patterns lack symmetry, which leaves us with one major question: How do such unsymmetrical patterns emerge in nature?

Studies report that drying environments cause water evaporation and can lead to the formation of asymmetric patterns during biological growth through a phenomenon called “ breaking.” Although reported through mathematical studies, these studies lack physical-chemical experiments that replicate this phenomenon.

A recent study at the Japan Advanced Institute of Science and Technology (JAIST), led by Associate Professor Kosuke Okeyoshi and doctoral student Thi Kim Loc Nguyen, uncovers the mechanisms behind symmetry breaking during a process called meniscus splitting in evaporating polymer solutions. The findings of the study were published in Advanced Science on June 3, 2025.

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A team at EPFL and the University of Arizona has discovered that making molecules bigger and more flexible can actually extend the life of quantum charge flow, a finding that could help shape the future of quantum technologies and chemical control. Their study is published in the Proceedings of the National Academy of Sciences.

In the emerging field of attochemistry, scientists use to trigger and steer electron motion inside . This degree of precision could one day let us design chemicals on demand. Attochemistry could also enable real-time control over how break or form, lead to the creation of highly targeted drugs, develop new materials with tailor-made properties, and improve technologies like solar energy harvesting and quantum computing.

But the big roadblock is decoherence: Electrons lose their quantum “sync” within a few femtoseconds (a millionth of a billionth of a second), especially when the molecule is large and floppy. Researchers have tried different methods to sustain coherence—using heavy atoms, freezing temperatures etc. Because quantum coherence vanishes at macroscopic scales, most approaches to sustaining coherence operate on the same assumption: larger and more flexible molecules were assumed to lose coherence more rapidly. What if that assumption is wrong?

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Turning crude oil into everyday fuels like gasoline, diesel, and heating oil demands a huge amount of energy. In fact, this process is responsible for about 6 percent of the world’s carbon dioxide emissions. Most of that energy is spent heating the oil to separate its components based on their boiling points.

Now, in an exciting breakthrough, engineers at MIT have created a new kind of membrane that could change the game. Instead of using heat, this innovative membrane separates crude oil by filtering its components based on their molecular size.

“This is a whole new way of envisioning a separation process. Instead of boiling mixtures to purify them, why not separate components based on shape and size? The key innovation is that the filters we developed can separate very small molecules at an atomistic length scale,” says Zachary P. Smith, an associate professor of chemical engineering at MIT and the senior author of the new study.

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