Perspectives

Wearable sensors can expedite personalized medicine by integrating sensors into our daily lives. This Perspective discusses mechanical and electrochemical sensors, including their operating principles, device synthesis, and examples of their use in monitoring disease, and cardiovascular, nervous and musculoskeletal systems

Naturally occurring organisms continue to provide inspiration for advanced functionality in soft robots. This Perspective discusses how achieving autonomy in robots will require interactions with their environment to be taken into consideration in their design.

A major challenge in materials scale-up is the variation in properties between batches. Here, the difficulties in the pilot-scale production of metal-organic frameworks are discussed and suggestions are provided to help improve large-scale synthesis development.

Personalized medicine requires wearable sensors that can detect biomarkers for a wide range of diseases. Here, wearable sensors for identifying chronic kidney disease are discussed, including promising systems, challenges and opportunities.

Thermomechanical stability is a limiting factor when scaling-up perovskite solar cells. This Perspective discusses several aspects of device design that control thermomechanical degradation, including adhesion of layers and encapsulation, and the importance of accelerated degradation testing.

Biomedicinal applications of metal-organic frameworks have mainly focused on nanoscale drug delivery. This Perspective provides an overview of reproducibility issues faced when applying metal-organic framework in nanomedicine, specifically covering their preparation and in vitro analysis.

Wearable electronics provide opportunities for personalized health monitoring and treatment. This Perspective addresses challenges in the field, including material selection for devices, device integration strategies, and public adoption factors.

The design and manufacture of materials that replicate the form, function, and sustainability of biological solutions remains difficult. Here, key challenges and promising approaches to materials development informed by biology are identified.

High-entropy materials have been realized in a wide number of alloys and ceramics, usually in bulk form. This Perspective discusses the emerging field of two-dimensional high-entropy materials, focusing on their formation, structure and applications.

Lead-based relaxor ferroelectrics are known for their large piezoelectric response, but the relation between the response and the nanoscale structure of these materials is still under debate. In this Perspective, the microscopic implications of the polar nature of disordered relaxor ferroelectrics are critically reviewed.

Electrolytes are a key component of a battery and therefore receive extensive research interest. This Perspective discusses how to ensure that reports of non-aqueous electrolyte solutions for lithium batteries are reliable and can be reproduced by others.

High-entropy materials are defined by the configurational entropy of their bulk phase, yet it is interesting to consider whether grain boundaries can also be “high entropy”. This paper discusses a thermodynamic framework for “high-entropy grain boundaries” and relevant concepts and unique thermodynamic properties.

Coin and pouch cells are typically fabricated to assess the performance of new materials and components for lithium batteries. Here, parameters related to cell fabrication that influence the reliability of these measurements are discussed, including guidelines for reliable cell preparation.

3D perovskites are widely researched for their use in optoelectronic devices, yet suffer from issues with environmental stability. Here, the improved stability of 2D and quasi-2D perovskites under a range of environmental factors, as compared to their 3D counterparts, is discussed.

Electrochemical impedance spectroscopy is a powerful and increasingly accessible approach for studying kinetic processes in batteries. Here, key factors for using impedance to obtain accurate and reproducible data from batteries are discussed, providing guidance for researchers.

Machine learning is an increasingly important tool for materials science. Here, the authors suggest that its contextual use, including careful assessment of resources and bias, judicious model selection, and an understanding of its limitations, will help researchers to expedite scientific discovery.

Battery research is often focused on candidate materials that result in the most promising battery performance numbers, which makes it vital that findings are accurately reported. This paper discusses a number of errors that often occur in the battery literature, which impact reproducibility.

There is growing interest in organic semiconductor devices for light-mediated neuromodulation, such as for retinal stimulation. Here, the key working principles of these devices are discussed, as well as promising applications and outstanding challenges for the field.