Dimpled surfaces offer a useful and easily implementable way to reduce friction between lubricated surfaces as they slide over each other. Through cutting-edge simulations, Dr. Robert Tomkowski and colleagues at the KTH Royal Institute of Technology in Sweden explore how the microscale structures of surface dimples can be optimized to minimize friction. Their findings could help to reduce wear in mechanical systems, while also making them more energy efficient.

As an inherently brittle material, concrete often needs to be replaced after just a few decades: driving a demand which incurs significant costs for Earth’s climate. Through their research, Professors Suzanne Scarlata and Nima Rahbar at Worcester Polytechnic Institute, Massachusetts, introduce a new mechanism that allows concrete to quickly repair itself, with the help of an enzyme vital to the function of living cells. This approach could help to reduce the world’s insatiable demand for concrete.

In the age of big data, and particularly in specialisations such as artificial intelligence, biology, and medicine, researchers often generate large and complex datasets that are challenging to analyse. This is particularly true for multi-view data, otherwise known as multimodal data, which are data that encompass multiple perspectives concerning a single entity or phenomenon. In the case of single-cell genomics, for instance, researchers can measure a huge range of different characteristics concerning an individual cell, such as RNA expression levels or protein levels. While multi-view datasets provide vast amounts of information, they are difficult to analyse because looking at each type of data within them provides only a small part of the overall picture. A new computational approach called Covering Point Set-merge analysis, or CPS-merge analysis for short, has been developed by Lixiang Zhang of Pennsylvania State University and colleagues, and it aims to assist researchers to merge the different types of data present in multi-view datasets into one coherent and meaningful set of results, without misrepresenting the individual contributions of each type of data.

So far, approaches to mapping the density of cities have often been oversimplified, causing them to overlook many key aspects of everyday urban life. Through his research, Dr Elek Pafka at the University of Melbourne introduces two new metrics for measuring urban density, which better capture its complex, multi-scale variations. His research offers deeper insights into how people experience and interact with cities, and could lead to new strategies to make our cities more productive, sustainable, and better places to live.

In principle, travelling wave reactors offer a safe, highly efficient approach to generating nuclear power. However, development has been held back by a variety of challenges linked to the need for extensively high burn-up in the reactor core, meaning very high rates of generated energy which can damage the reactor. Inspired by the principles of Tai-Chi, a team led by Di Yun from Xi’an Jiaotong University has shown that with the right approach, a high temperature operation, usually deemed as a threat, can be transformed into useful advantages, bringing the practical rollout of travelling wave reactors one step closer to reality.

The full extent of the labour and resources which go into creating a modern house is hidden deeply within the buildings we call home. Professor Mark Jarzombek of MIT and Professor Vikramaditya Prakash of the University of Washington are co-founders of the Office of Uncertainty Research, a research collaboration that is dedicated to rethinking architecture in a modern context. Through their research, Jarzombek and Prakash investigate these hidden stories by exploring the history of a recently built modern house in Seattle. Their findings reveal that the presumed transparency of modern architecture conceals deep ethical and environmental challenges, inspiring a call for a critical reassessment of how our current construction practices should be understood and approached.

Studying single molecules provides researchers with unique insights into biological mechanisms and processes and allows them to visualise microscopic structural and functional differences. However, results can be unpredictable, and investigations are labour-intensive and expensive, often requiring extensive training and highly specialised laboratory equipment. Dr Rishabh Shetty and colleagues at Arizona State University, the California Institute of Technology, and the Massachusetts Institute of Technology, USA, have recently developed a simplified single-molecule assessment technique to overcome these limitations with a view to increasing accessibility and precision in molecular-level research.

Today, the success of businesses and technologies relies on their ability to make quick decisions to address complex problems. To make matters more complex, these problems often involve a vast amount of data. Dr Marius Nagy at Prince Mohammad Bin Fahd University, together with Dr Naya Nagy, Imam Abdulrahman Bin Faisal University, investigate the ability of quantum computers to act as an ‘oracle’, and provide quality decisions even after just one invocation. Dr. Nagy and Nagy showed that quantum oracles give richer decision proposals and outperform classical computing oracle versions.

AI appears all-powerful when playing sophisticated games such as Chess and Go against human opponents. Moreover, recent developments in AI have allowed it to summarize bodies of complex text, generate images and even video. These developments come with warnings that AI could replace many jobs, undermine democratic elections or even pose a threat to the existence of humanity. However, AI is largely based on observing and learning patterns; so, what happens when there are no patterns? Professor Steven Brams of New York University and colleagues have analyzed the potential of beating AI when playing a deceptively simple game called Catch-Up, simply by making random moves.

Artificial intelligence – or AI – is receiving increasing attention for its rapid development and potential to change society. Researchers are working hard to develop its capabilities, while regulators are racing to ensure it is managed and governed properly. But what do we mean by AI, and how can we define such a complex term? In a recent paper, Professor Pei Wang at Temple University argues that the lack of an agreed definition makes it difficult for policymakers to assess what AI will be capable of in the near future, or even which kinds of AI are desirable. To combat this, he discusses what makes a robust definition, and suggests his own.