Cambridge launches major strategic partnership with IonQ to ‘supercharge’ quantum research in the UK
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Updates every hour. Last Updated: 10-Jun-2026 07:16 ET (10-Jun-2026 11:16 GMT/UTC)
The UK’s most powerful quantum computer, which will accelerate research and discovery in quantum science, engineering, and a range of other applications, will be based at the University of Cambridge as part of a new partnership with the quantum technology company IonQ. The collaboration is the University’s largest-ever corporate research partnership.
In a paper published today in Nature Synthesis, a team from the lab of University of Chicago Pritzker School of Molecular Engineering (UChicago PME) and Chemistry Department Prof. Paul Alivisatos explores the role of cation exchange in one of chemistry and material science’s central challenges: How covalent materials undergo structural change at the nanoscale. This greater understanding of how materials transform could have applications for designing and building semiconductors, unraveling complex chemical processes or creating previously unimagined material architectures, for example, in this work, nanocubes of indium arsenide (InAs) and gallium arsenide (GaAs). The team applied a cellular automaton computational model to explore the science, building a clear, simple model for future researchers to envision these minute changes. They believe this is the first time a cellular automaton model has been applied to the cation exchange reactions of nanocrystals.
A research team from the University of Tokyo and Tokyo University of Agriculture and Technology uncovered a new mechanism of Yaku’amide B, a deep-sea sponge-derived natural product. Using photoaffinity labeling, they found that yaku’amide B transiently binds CD9, inducing its degradation, in addition to inhibiting ATP synthase. This dual action suppresses cancer cell proliferation and migration, opening new avenues for anticancer drug development and protein degradation strategies.
A compact fiber-based system has been developed to compress mid-infrared laser pulses to 187 femtoseconds using low input power. By integrating a holmium-doped ZBLAN photonic crystal fiber within a nonlinear optical loop mirror, the approach achieves high compression efficiency with minimal pedestal energy, offering a simplified route to ultrafast mid-IR sources for spectroscopy and biomedical imaging.
Light speckle fluctuations, a noninvasive proxy for cerebral blood flow index (CBFi), are quantified by diffuse correlation spectroscopy. However, this conventional technique provides marginal brain sensitivity for CBFi in adult humans. To improve the brain sensitivity, researchers have now optimized interferometric diffusing wave spectroscopy—a novel approach to quantify the fluctuations. They demonstrated pulsatile CBFi monitoring at 4–4.5 cm source-collector separation in adults with moderate pigmentation.
Drug-drug interactions (DDI) can cause adverse drug reactions during the co-administration of multiple drugs, necessitating accurate and scalable prediction tools. While deep learning models have shown promise recently, most models show poor performance against drugs not encountered during training. Now, researchers have developed a lightweight and scalable model, called DDINet, designed specifically to predict unseen drug interactions. This innovative model achieves superior accuracy in predicting interactions for unseen drugs, with potential for practical deployment.
At the 2026 MDA Conference in Orlando, Genethon unveiled new two‑year efficacy data for its gene therapy candidate GNT0004, a key milestone for Duchenne muscular dystrophy research.
In new results from a clinical trial, researchers show that electrical stimulation of the spinal cord can restore the muscle control and sensory feedback required for coordinated walking movements.