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How materials science could revolutionise technology — with Jess Wade

Jess Wade explains the concept of chirality, and how it might revolutionise technological innovation.

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This lecture was recorded at the Ri on 14 June 2025.

Imagine if we could keep our mobile phones on full brightness all day, without worrying about draining our battery? Or if we could create a fuel cell that used sunlight to convert water into hydrogen and oxygen? Or if we could build a low-power sensor that could map out brain function?

Whether it’s optoelectronics, spintronics or quantum, the technologies of tomorrow are underpinned by advances in materials science and engineering. For example, chirality, a symmetry property of mirror-image systems that cannot be superimposed, can be used to control the spin of electrons and photons. Join functional materials scientist Jess Wade as she explores how advances in chemistry, physics and materials offer new opportunities in technological innovation.

Scientists use quantum machine learning to create semiconductors for the first time — and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing.

Study uncovers technologically appealing trick used by microalgae to manipulate light

Skoltech researchers and their colleagues have uncovered an intricate light manipulation mechanism likely used by microscopic algae to boost photosynthesis.

By studying the interaction of light with the elaborately patterned silicon dioxide shells enclosing the , the team hopes to reveal principles that could eventually be leveraged in light detectors, bio-and chemical sensors, protective coatings against ultraviolet rays, , and other nature-inspired technology, right up to artificial photosynthesis systems using CO2 and water to make fuel.

The study was published in the journal Optica.

AI designed peptide-MHC binders expressed in T cells kill cancer cells

Normally, T cells naturally identify cancer cells by recognizing specific protein fragments, known as peptides, presented on the cell surface by molecules called pMHCs. It is a slow and challenging process to utilize this knowledge for therapy, often because the variation in the body’s own T-cell receptors makes it challenging to create a personalized treatment.

In the study, the researchers tested the strength of the AI platform on a well-known cancer target, NY-ESO-1, which is found in a wide range of cancers. The team succeeded in designing a minibinder that bound tightly to the NY-ESO-1 pMHC molecules. When the designed protein was inserted into T cells, it created a unique new cell product named ‘IMPAC-T’ cells by the researchers, which effectively guided the T cells to kill cancer cells in laboratory experiments.

“It was incredibly exciting to take these minibinders, which were created entirely on a computer, and see them work so effectively in the laboratory,” says a co-author of the study.

The researchers also applied the pipeline to design binders for a cancer target identified in a metastatic melanoma patient, successfully generating binders for this target as well. This documented that the method also can be used for tailored immunotherapy against novel cancer targets.

A crucial step in the researchers’ innovation was the development of a ‘virtual safety check’. The team used AI to screen their designed minibinders and assess them in relation to pMHC molecules found on healthy cells. This method enabled them to filter out minibinders that could cause dangerous side effects before any experiments were carried out.


Precision cancer treatment on a larger scale is moving closer after researchers have developed an AI platform that can tailor protein components and arm the patient’s immune cells to fight cancer. The new method, published in the scientific journal Science, demonstrates for the first time, that it is possible to design proteins in the computer for redirecting immune cells to target cancer cells through pMHC molecules.

Progressing future osteoarthritis treatment toward precision medicine: integrating regenerative medicine, gene therapy and circadian biology

Osteoarthritis (OA) is a common joint disease that causes pain and stiffness, especially in older adults. Researchers are exploring new therapies to address this issue, here focusing on regenerative medicine, which uses stem cells to repair damaged cartilage. This involves injecting stem cells into joints to promote healing. However, challenges such as cell survival and long-term effectiveness remain. This study also examines gene therapy, which targets specific genes to reduce inflammation and cartilage breakdown. Biomaterials such as hydrogels and nanoparticles are used to deliver these therapies directly to the joint, improving treatment precision. In addition, this research highlights the role of circadian rhythms in OA, suggesting that timing treatments could enhance their effectiveness. These advancements aim to provide more personalized and effective OA treatments. Future research will focus on refining these approaches for better patient outcomes.

This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

How the brain stores ‘unattended’ information: Neuronal firing disproves activity-silent hypothesis

Understanding how the human brain stores information and later uses it to complete various tasks has been a long-standing goal of neuroscience and psychology research. Past studies have identified different types of memory processes that have distinct roles and characteristics.

One of these, known as working memory, entails the storage and manipulation of important information for short periods of time, particularly information that is helpful for completing reasoning tasks or to make decisions in the short-term. Findings suggest that this temporary storage of information is associated with the continued and persistent firing of specific neurons in the brain.

Most past studies focusing on working relied on experimental tasks that require participants to prioritize and memorize all items they are presented with.

AI-designed T cell receptor substitutes can accelerate precision cancer immunotherapy

New designer proteins created using an AI tool can selectively target peptide segments that bind to markers on diseased cancer cells, acting like molecular flags that signal immune cells to attack and destroy the threats.

In a recent breakthrough, a team of researchers from the U.S. presented protein binders that specifically recognized the peptide portion of 11 diverse pMHCI complexes—amino-acid fragments found on the surface of almost all cells in the body that play a central role in the immune system’s ability to recognize and respond to abnormal or diseased cells, such as cancer cells.

These proteins, designed with the aid of AI, help human immune cells identify the correct targets and function more effectively, according to findings published in Science.

A new approach to combating asthma-induced bronchial remodeling

Patients with bronchial asthma suffer from attacks of shortness of breath caused by constricted airways. “Anti-inflammatory medications are usually given to treat this, although it isn’t quite clear how inflammation and constriction correlate,” says Professor Daniela Wenzel, head of the Department of Systems Physiology in the Faculty of Medicine at Ruhr University Bochum.

“These medications often stop working at a certain point.” Furthermore, often experience a thickening of the bronchial tissue due to the accumulation of collagen. Goblet cells also form in increasing numbers, producing mucus and making breathing even more difficult. Currently, there is no medication to counteract these changes.